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Genetic, environmental, and physiological factors involved in the precocious sexual maturation of chinook… Heath, Daniel D. 1992

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GENETIC, ENVIRONMENTAL, AND PHYSIOLOGICAL FACTORS INVOLVED INTHE PRECOCIOUS SEXUAL MATURATION OF CHINOOK SALMON(Oncorhynchus tshawytscha)byDANIEL DAVIDSON HEATHB.Sc., McGill University, 1981M.Sc., McGill University, 1986A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFDOCTOR OF PHILOSOPHYinTHE FACULTY OF GRADUATE STUDIES(Department of Animal Science)We accept this thesis as conformingto th required standardTHE UNIVERSITY OF BRITISH COLUMBIADecember 1992©Daniel Davidson Heath, 1992In presenting this thesis in partial fulfilment of the requirements for an advanceddegree at the University of British Columbia, I agree that the Library shall make itfreely available for reference and study. I further agree that permission for extensivecopying of this thesis for scholarly purposes may be granted by the head of mydepartment or by his or her representatives. It is understood that copying orpublication of this thesis for financial gain shall not be allowed without my writtenpermission.Department of ^Wok_ 5( The University of British ColumbiaVancouver, CanadaDate DE-6 (2/88)ABSTRACTMale chinook salmon (Oncorhynchus tshawytscha), that mature sexually one yearprior to females and after at least one summer in sea water, are known as jacks. Abreeding experiment to test for genetic and environmental (temperature at early rearing)effects on the incidence of jacking in chinook salmon showed significant sire, dam, andenvironmental effects, as well as genotype-by-environment interactions. Heritabilityestimates for incidence of jacking based on sire-offspring regressions within dams were0.48 (± 0.24) and 0.32 (± 0.14) for the accelerated and non-accelerated groupsrespectively.DNA fingerprinting was used to detect differences in allele distribution betweenprecocious males and randomly selected fish, such differences indicate geneticinvolvement. Two oligonucleotide DNA fingerprinting probes were developed, howeverthe resulting banding patterns were judged unsuitable for this application. A novelextension of Random Amplification of Polymorphic DNA (RAPD) allowed the isolation ofa single-locus DNA probe for chinook salmon. This probe and another developed forAtlantic salmon, were hybridized with DNA from 74 jacks and 94 females from farmedchinook salmon (Robertson Creek stock; RC), and with DNA from 45 precociously matureand 56 non-mature chinook salmon parr from the Nicola River (NR). The alleledistributions of the jack and female RC adults differed significantly, however, there was nodifference between the precocious and non-maturing NR parr due, in part, to the relativelylow genetic variability of that stock.The weight-frequency distributions for three year classes of chinook salmon becamesignificantly bimodal in the May prior to maturation due to faster growth of the jacks,relative to the non-maturing fish, from April to June. Plasma cortisol, T3, and testosteroneconcentrations were measured for one of those year classes during the spring and summer.No significant difference between the jacks and non-maturing fish were found for cortisol;however, T3 levels were higher in the jacks in March, and testosterone levels were higheriiiin the jacks throughout the spring and summer. Only T3 levels were correlated (negatively)with growth in the jacks.A correlation analysis using the full- and half-sib families in the breedingexperiment showed that growth-related variables did not predict jacking rates, althoughresting plasma glucose concentration, dam weight, and weight difference between the jacksand non-mature fish at the final sample were significantly correlated with jacking rate.The implications of these finding are discussed with respect to evolutionary theory,aquaculture, and chinook salmon physiology.ivTABLE OF CONTENTSAbstract^ iiTable of Contents^ ivList of Figures viList of Tables^ ixAcknowledgments xiGENERAL INTRODUCTION^ 1Chapter 1.1MATURATION IN CHINOOK SALMON: EARLY IDENTIFICATION BASED ONTHE DEVELOPMENT OF A BIMODAL WEIGHT-FREQUENCY DISTRIBUTION1.1.1 Introduction^ 71.1.2 Material and Methods^ 81.1.3 Results 111.1.4 Discussion 17Chapter 2.1GENETIC, ENVIRONMENTAL, AND INTERACTION EFFECTS ON THEINCIDENCE OF JACKING IN CHINOOK SALMON.2.1.1 Introduction^ 202.1.2 Materials and Methods^ 212.1.3 Results 272.1.4 Discussion 35Chapter 2.2DNA FINGERPRINTS IN SALMONIDS PRODUCED BY HYBRIDIZATION WITHOLIGONUCLEOTIDES.2.2.1 Introduction^ 412.2.2 Materials and Methods^ 432.2.3 Results and Discussion 47Chapter 2.3A NOVEL APPLICATION OF PCR TO AMPLIFY HYPERVARIABLEMINISATELLITE DNA SINGLE LOCUS PROBES.2.3.1 Introduction^ 542.3.2 Materials and Methods^ 552.3.3 Results and Discussion 58VChapter 2.4APPLICATION OF SINGLE-LOCUS MINISATELLITE DNA PROBES TO IDENTIFYGENETIC COMPONENT IN JACKING AND PRECOCIOUS CHINOOK PARR.2.4.1 Introduction^ 702.4.2 Material and Methods^ 722.4.3 Results 762.4.4 Discussion 85Chapter 3.1HORMONAL AND GROWTH CHANGES ASSOCIATED WITH JACKING INCHINOOK SALMON.3.1.1 Introduction^ 893.1.2 Materials and Methods^ 913.1.3 Results 953.1.4 Discussion 101Chapter 3.2PHYSIOLOGICAL CORRELATES WITH THE INCIDENCE OF JACKING INCHINOOK SALMON.3.1.1 Introduction^ 1073.1.2 Materials and Methods^ 1083.1.3 Results 1143.1.4 Discussion 115GENERAL DISCUSSION^ 122Appendix AGENETIC, ENVIRONMENTAL, AND INTERACTION EFFECTS ON GROWTH ANDSTRESS RESPONSE OF CHINOOK SALMON FRY.128Appendix BREPEAT SEXUAL MATURATION OF PRECOCIOUS MALE CHINOOK SALMON(ONCORHYNCHUS TSHAWYTSCHA) TRANSFERRED TO SEA WATER.148Bibliography^ 149viLIST OF FIGURES1. Figure I.1: Schematic diagram of the factors that arehypothesized within the literature to affect theincidence of precocious sexual maturation in malesalmonids^ 32. Figure 1.1.1: Wet weight frequency distribution inchinook salmon in 1987 (1985 Cohort)^ 133. Figure 1.1.2: Wet weight frequency distribution forchinook salmon in 1988 (1986 cohort) 144. Figure 1.1.3: Average wet weight of chinook salmonversus time for the 1985 and 1986 cohorts^ 165. Figure 2.1.1: a) Mean wet weight of the chinooksalmon family groups used in the analysis of jackingrates plotted against time. b) Absolute growth rateof the chinook salmon family groups plotted againsttime^ 286. Figure 2.1.2: Percent survival (from pre-smolt nose-tagging) for each of the 24 chinook salmon familygroups in the analysis of jacking^ 327. Figure 2.1.3: Specific jacking rates (%) for the 24chinook salmon family groups 338. Figure 2.1.4: Norms of reaction for the observedspecific jacking rates in the 12 full- and half-sibchinook salmon family groups reared under twoenvironments^ 349. Figure 2.2.1: DNA fingerprints of a family of chinooksalmon generated by hybridization with sixoligonucleotides^ 4910. Figure 2.2.2: DNA fingerprints of two presumedunrelated individuals from each of eleven species ofsalmonids generated by hybridization with the YN24oligonucleotide^ 5111. Figure 2.2.3: DNA fingerprints of two presumedunrelated individuals from each of eleven species ofsalmonids generated by hybridization with the M13oligonucleotide^ 5212. Figure 2.3.1: Results of PRC using a singleoligonucleotide (core sequence from known VNTRs) asprimer with chinook salmon, bird and human DNA astemplates^ 60vii13. Figure 2.3.2: A schematic diagram of the hypothesizedinversion event that allows PCR amplification ofmultiple-sized DNA fragments using a single primerwith the core sequence from known VNTRs^ 6114. Figure 2.3.3: Autoradiographs of membranes probedwith potential single-locus minisatellite DNA probeswith quail and human families^ 6215. Figure 2.3.4: Autoradiographs of 17 unrelated chinooksalmon probed with the chinook salmon single-locusminisatellite DNA probe OTSL1^6316. Figure 2.3.5: Autoradiographs of three families ofchinook salmon probed with the chinook salmonsingle-locus minisatellite DNA probe OTSL1^6417. Figure 2.3.6: Autoradiograph of six species ofsalmonids probed with the chinook salmon single-locus minisatellite DNA probe OTSL1 at lowstringencies^ 6718. Figure 2.3.7: Base pair sequence of OTSL1^ 6819. Figure 2.4.1: OTSL1 locus allele frequencies (withinallele bins) plotted against median allele size forthe RC adult chinook salmon^ 7720. Figure 2.4.2: OTSL1 locus allele frequencies (withinallele bins) plotted against median allele size forthe NR chinook salmon parr^ 7821. Figure 2.4.3: Ssal locus allele frequencies (withinallele bins) plotted against median allele size forthe RC adult chinook salmon^ 7922. Figure 2.4.4: Ssal locus allele frequencies (withinallele bins) plotted against median allele size forthe NR chinook salmon parr^ 8023. Figure 2.4.5: Mean cumulative number of novel allelesat the OTSL1 locus plotted against cumulative fishnumbers for precocious mature male and non-maturecontrol NR chinook salmon parr, jack and female(non-mature) adult RC chinook salmon, and full-siband unrelated chinook salmon^ 8324. Figure 2.4.6: Mean cumulative number of novel allelesat the Ssal locus plotted against cumulative fishnumbers for precocious mature male and non-maturecontrol NR chinook salmon parr, and jack and female(non-mature) adult RC chinook salmon^ 84viii25. Figure 3.1.1: Weight-frequency distributions for thecombined male, female and jack chinook salmon heldsalt water for the duration of the hormonal analysisexperiments^ 9626. Figure 3.1.2: Mean wet weight (a) and mean relativegrowth (b) of the female, male and jack chinooksalmon groups in salt water used for the hormonalanalysis^ 9727. Figure 3.1.3: Mean plasma concentrations of; a)cortisol, b) T3, and c) testosterone for the male,female, and jack chinook salmon groups in salt water^ 9928. Figure 3.1.4: Correlations between transformedhormonal values, growth, and GSI for the individualjacking chinook salmon^ 10029. Figure 3.1.5: Transformed December wet weightsplotted against December plasma T3 concentrationsfor 15 male chinook salmon^ 10330. Figure 3.2.1: Results of the correlation analyses forfamily means of physiological variables versusfamily specific jacking rates; difference in weightbetween the jacks and non-mature fish at the finalsample plotted against jacking rate, and weight ofthe dam for each family plotted against jackingrate^ 11631. Figure 3.2.2: Results of the correlation analyses formean family plasma glucose concentrations againstgrowth and jacking rates^ 11732. Figure D.1: Schematic diagram of the factors that arehypothesized to affect precocious sexual maturationin salmonids with the factors investigated in thisthesis identified^12733. Figure A.1: Norms of reaction for eight stress- andgrowth-related traits, measured on eight chinooksalmon families, under two incubation temperatures 140ixLIST OF TABLES1. Table 1.1.1: A summary of the number of the chinooksalmon from two year classes that were sampled forweight-frequency distribution bimodality analysis^ 92. Table 1.1.2: Results of the tests for significancefor bimodal weight-frequency distribution for 1987and 1988 samplings of chinook salmon^ 123. Table 2.2.1: A list sex ratios of the 24 full- andhalf-sib family groups used for the analysis of thegenetic and environmental contributions to theincidence of jacking in chinook salmon^ 304. Table 2.1.2: Heritability estimates for the incidenceof precocious sexual maturation (jacking) in farmedRobertson Creek chinook salmon stock^315. Table 2.1.3: Results of the ANOVA on the incidence ofjacking in the progeny of the 12 accelerated and 12non-accelerated full- and half-sib families^ 316. Table 2.1.4: Estimates of heritability taken fromthe literature for mean age of first maturationin salmonids^ 397. Table 2.2.1: A list of the eleven oligonucleotidesthat were screened as potential DNA fingerprintprobes in chinook salmon^ 448. Table 2.2.2: A list of the eleven salmonid specieshybridized with oligonucleotide YN24, and M13 DNAfingerprint probes^ 459. Table 2.3.1: An analysis of the allele inheritanceand mutation in a chinook salmon family composed of23 progeny at the minisatellite DNA locus OTSL1^6510.Table 2.4.1: The frequency of heterozygote chinooksalmon at the minisatellite DNA loci OTSL1 and Ssalfor two stocks and two phenotypes in each stock^8211.Table 3.1.1: Family composition of the fish used forthe analysis of hormonal and growth differencesbetween jacks and non-maturing chinook salmon^ 9312.Table 3.2.1: A list of the 25 variables in fourcategories that were used in the correlationanalysis, with abbreviations^ 10913. Table 3.2.2a: A list of the family mean values forthe 25 variables used for the correlation analysisfor the accelerated groups only^ 112x14.Table 3.2.2b: A list of the family values for the 25variables used in the correlation analysis for thenon-accelerated groups only^ 11315.Table A.1; Survival data on the full- and half-sibfamilies used for the analysis of stress response inchinook salmon fry, along with the nested matingdesign used^13216.Table A.2: ANOVA table for growth and stress-relatedparameters measured on 8 full-sib families ofchinook salmon fry^ 13817.Table A.3: Back-transformed means and confidenceintervals of the traits measured on chinook salmonfry reared at two incubation temperatures^ 142ACKNOWLEDGMENTSI would like to thank Dr. George Iwama for his support throughout the course ofthis work, as well as Dr. Kim Cheng, Dr. Dave Baillie, Dr. Al Castledine, Mr. BillHarrower, and Dr. Dolf Schluter for their assistance with many of the technical hurdles.Dr. Bob Devlin provided facilities and encouragement during my molecular learning curve.I would also like to thank my brother, Dr. John Heath, and sister-in-law, Dr. Ann Heath,as well as their family for considerable assistance and support. Many of my friends andassociates from my fish farming years provided advice and support for this work, inparticular I would like to thank Dr. Jim Brackett (Syndel Labs), Tim Hobbs (Redden Net),Dave Ewart (Quinsam Hatchery), Neal Johnson (Yellow Island Aquaculture), and BryanEriksson (Beaver Aquatics). A special thanks goes to Nicholas Bernier for his help andencouragement. I would also like to acknowledge my wife, Julie Smit, who not only gavemoral support, but also helped sample a few thousand fish. Finally, I thank my mother,father, and family.Financial support for this work was provided by NSERC operating and strategicgrants to Dr. Iwama, and the Canadian Bacterial Disease Network. Further support wassupplied by the Department of Fisheries and Oceans (Canada) through grants to Dr.Devlin. Field work costs were defrayed by Yellow Island Aquaculture Ltd. Personalfunding was provided through a Science and Technology Award for Returning Students(STARS) from the British Columbia Science Council.xi1GENERAL INTRODUCTIONCoastal chinook salmon (Oncorhynchus tshawytscha) stocks in southern BritishColumbia usually smolt and migrate to sea in the spring of their first year, although insome populations the fry may remain in the river for an additional year (Healey 1991). Theadult salmon return to the spawning grounds after 1-5 years at sea (Healey 1991). The term"jacking" in chinook salmon is used to describe the precocious sexual maturation of thesea-run males after at least one year in sea water, usually one year prior to the firstmaturation of the females (Healey 1991). Male chinook salmon may also sexually maturebefore smolting as "precocious parr" (Taylor 1989, Foote et al. 1991), however thisphenomenon is much more common in Atlantic salmon (Salmo salar). Precocious sexualmaturation of females only rarely occurs; this sexual dimorphism may be due to the lowerenergy allocation necessary for sexual maturation in males compared to female fish (Ware1980, Healey 1991). Jacking has been documented in chinook salmon (Healey 1991,Bocking & Nass 1992), coho salmon, Oncorhynchus kisutch (Bilton 1980, Sandercock1991), and sockeye salmon Oncorhynchus nerka (Burgner 1991), while precocious parrhave been observed in chinook salmon (Taylor 1989, Foote et al. 1991), coho salmon(Silverstein & Hershberger 1992), amago and masu salmon Oncorhynchus rhodurus & O.masou (Kato 1991), and sockeye salmon (Ricker 1972, Burgner 1991). Up to 90% of themales in a given chinook salmon stock may be jacks (Hard et al. 1985), although mostchinook stocks exhibit jacking rates around 5-15% of returning fish (both sexes; Bocking& Nass 1992, Healey 1991, Ricker 1972).Precocious maturation in male salmonids is an example of an alternative malestrategy; the smaller, younger males gain access to females for reproduction by utilizing"sneaking" behavior which capitalizes on their smaller size, while the larger, older malesguard females and fight to defend their territory (Gross 1984,1985, Leonardsson &Lundberg 1986, Bohlin et al. 1990, among others). Jacking in coho salmon andprecocious maturation of Atlantic salmon parr have been successfully modelled using game2theory, as alternate Evolutionary Stable Strategies, or ESS (Gross 1984, 1985,Leonardsson & Lundberg 1986, Bohlin et al. 1986). Over 64 species of fish have beenshown to exhibit alternate reproductive strategies (Chan & Ribbink 1990), and size-dependent alternate mating behavior has been reported for mammals (Leboeuf 1974),reptiles (Divers 1976), amphibians (Arak 1988), and insects (Cade 1981). Precociousmaturation in Pacific salmon is particularly useful for life history analysis, since maturationgenerally occurs only once in their lifespan (but see Bernier et al. 1992, Appendix B) andthus the reproductive strategies are discrete (Gross 1985). A key question in these studiesof ESS theory is the inheritance of precocious maturation. If there is no genetic componentto precocious maturation, then selection cannot lead to ESS, and jacking might best bemodelled based on phenotypic plasticity (Stearns & Koella 1986). However if a geneticcomponent exists, then ESS theory can be applied.There is strong evidence that there are both genetic and environmental componentsto the incidence of precocious sexual maturation of coho and Atlantic salmon parr (Glebe& Saunders 1986, Thorpe et al. 1983, Iwamoto et al. 1984, Silverstein & Hershberger1992, see Chapter 2.1). There is, however, very little published information on precociousmaturation of Pacific salmon after smolting and migration. What is published is based onreturns of released smolts, usually with very low survival rates (Bilton 1984, Hard et al.1985). The genetic basis of jacking in Pacific salmon species has not been studiedextensively, perhaps due to the logistical difficulties of rearing large numbers of fish tosexual maturation in salt water.Figure I.1 shows a schematic representation of the most widely accepted factors thatcontribute to the determination of precocious sexual maturation in salmonids. It isimportant to note that there are also interactions among the three broad categories (i.e.genetic effects, environmental effects and physiological "triggers"). For example, thehormonal processes that trigger maturation are probably under some form of geneticcontrol. Furthermore, the timing of the non-genetic factors may be critical, thus a02re)I GENETIC EFFECTS I•^0§PHYSIOLOGICAL TRIGGERS- BODY SIZE- ENERGY STORES- PHOTOPERIOD- HORMONAL PROCESS3ENVIRONMENTAL EFFECTS- GROWTH- SIZE- STRESS TOLERANCE- DEVELOPMENT RATEFigure I.1: A schematic diagram of factors hypothesized to affect the incidence ofprecocious sexual maturation in male salmonids. The horizontal line represents themale fishes' life cycle, starting with the fertilization of the egg and proceedingthrough the freshwater rearing, smolting, and seawater rearing. The genetic effectsare passed on at fertilization, while the environmental effects act throughout the lifecycle. The physiological "triggers" are generally thought to act during the 6-9months prior to maturation (see text).4minimum level of energy stores could be required for sexual maturation, but only duringthe spring prior to maturation. The purpose of Fig. I.1 is to present the possible areas ofstudy for researchers interested in precocious sexual maturation.This thesis is primarily concerned with the investigation of the genetic andenvironmental contributions to precocious sexual maturation of male chinook salmon. Tothis end, an extensive breeding experiment was designed and executed. Furthermore, anadditional approach, based on the relatively new DNA "fingerprinting" technology, wasalso used. During the course of these experiments, a number of physical and physiologicalcharacteristics of precociously maturing male salmon were also examined in an effort tobetter understand the physiological events that accompany precocious sexual maturation.However, the primary goal of this work remained the analysis of the genetic andenvironmental contributions to an alternate life history strategy in male chinook salmon,that is precocious sexual maturation.This thesis has been organized into three sections that address different factors thatpotentially affect jacking in chinook salmon (as identified in Fig. I.1): The first sectionreports on initial observations (i.e. incidence and growth) on jacking in farmed chinooksalmon. The second section comprises an analysis of the genetic and environmentalcontributions to jacking in chinook salmon based on an extensive breeding program as wellas on allele frequencies at two minisatellite DNA loci. The third section describes selectedphysiological characteristics which accompany jacking in chinook salmon as potentialtriggers.The goal of the work described in the first section was to test the hypothesis thatjacking chinook salmon could be identified based on their size relative to the non-maturingfish as early as the spring prior to maturation. This work also provided some backgrounddata on the incidence of jacking in the Robertson Creek chinook stock reared at YellowIsland Aquaculture Ltd., where the breeding experiment was performed.5The purpose of the work described in the second section was twofold; primarily todetermine if there were genetic and environmental components to jacking in RobertsonCreek chinook stock reared at Yellow Island Aquaculture Ltd., and secondarily, toevaluate the utility of relatedness estimates, based on DNA "fingerprinting" (Burke et al.1991), in identifying family effects for specific phenotypes within a random matingpopulation. In order to test the DNA "fingerprinting" approach it was necessary to developand evaluate minisatellite DNA probes for use in chinook salmon.The goal of the third section was to identify physiological characteristics thatdistinguish jacks from non-jacks (i.e normally maturing fish) within the family groups inthe breeding program. The third section tested some of the published observations andhypotheses on the physiological "causes" of precocious sexual maturation in malesalmonids for jacking in chinook salmon.Although the principal goal of the work described here was to investigate thegenetic and environmental contributions to jacking in chinook salmon, the phenomenon iscomplex and generally poorly understood. I therefore expanded the scope of my work toinclude ancillary projects. I feel that the physiological descriptions gathered in theseancillary projects were valuable for understanding the role of jacking in chinook salmon,not only for aquaculture, but also in evolutionary and ecological contexts.Besides the research detailed in this thesis, two other projects were carried out bythe author in collaboration with Nicholas Bernier. The first was an analysis of the genetic,environmental, and interaction effects on the stress response and growth of chinook salmonfry. This work is in press (Canadian Journal of Fisheries and Aquatic Sciences) and themanuscript is presented in Appendix A. The objective of these experiments was to studythe correlations between the measured physiological parameters and the observed jackingrates. The second project was a study of precocious sexual maturation in the under-yearlingNicola River chinook parr at the Spius Creek hatchery. These fish were sampled for DNAfingerprinting analysis, and the hatchery staff later informed us that some of the6precociously mature parr had survived maturation, and had resumed feeding. Survivingmature parr and non-mature controls were collected and held in fresh and salt water untilthe following breeding season. This work has been completed and is in press (CanadianJournal of Zoology); the abstract is presented in Appendix B.71.1 MATURATION IN CHINOOK SALMON: EARLY IDENTIFICATION BASEDON THE DEVELOPMENT OF A BIMODAL WEIGHT-FREQUENCYDISTRIBUTION1.1.1 INTRODUCTIONAlthough the phenomenon of jacking, or precocious maturation of male Pacificsalmon (Oncorhynchus spp.) is well documented (Ricker 1972, Hagar & Noble 1976, Scott& Crossman 1979, Bilton 1980, Hard et al. 1985), most information on jacking is basedon fish returning to Federal hatcheries, or taken in the sport and commercial fisheries (butsee Iwamoto et al. 1984). Typically, survivals (egg to adult) in these stocks have been fivepercent or less (Bilton 1980, 1984). Since there is little known concerning the sources ofmortality during the seawater phase of the salmon's life, conclusions concerning jackingrequire the assumption of uniform mortality (see Ricker 1972, Bilton 1978,1980). Inaquaculture, jacks are either sorted out and sold at little or no profit, or die in the pens.Sorting or removal of the dead fish is costly, therefore monosex female salmon stocks(Hunter et al. 1983) have been developed to avoid the problems of jacking in chinooksalmon, while diet restriction (and consequent slowed growth) has been effective inreducing the number of precocious parr and grilse in Atlantic salmon, Salmo salar L.,(Rowe & Thorpe 1990b, Thorpe et al. 1990). Since jacks are reported as being the mosthardy (Pers. comm. J. Brackett, Syndel Laboratories Ltd., Nanaimo, B. C.) and rapidlygrowing (Lamont 1990) individuals during the first 18 months of ocean rearing (the fastergrowth may be due to the rise in plasma anabolic androgen levels of maturing male salmon- Dye et al. 1986, Higgs et al. 1982) they represent a potential asset to salmon farmers.A reliable method of identifying jacks before secondary sexual characteristicsexpress themselves would allow them to be harvested while they still have commercialvalue. In this study, growth and the weight-frequency distribution over time was measuredfor two year classes of chinook salmon reared on a commercial salmon farm in British8Columbia (B.C.), Canada. Our hypothesis was that jacks could be identified by their highbody weight relative to the general population, before any secondary sexual characteristicswere expressed.1.1.2 MATERIALS AND METHODSFirst generation domestic chinook salmon stock originally from the RobertsonCreek Salmon Enhancement Facility (Department of Fisheries and Oceans, Canada),Vancouver Island, were reared from eggs at Yellow Island Aquaculture Ltd., a commercialsalmon farm on Quadra Island, B.C. Fish were transferred to progressively larger seawatercages as they grew; the first cages were 4.5m X 9.0m X 9.0m deep, the next were 9.0m X9.0m X 9.0m deep, and the last cages were 19m X 19m X 12m deep grow-out pens. Thewater temperature varied from about 7 °C in the winter to approximately 13 °C in thesummer and salinity varied at 26-29 ppt. The fish were fed a varying ration of acommercial dry pelleted diet based on water temperature and fish weight, following therecommendations of the feed supplier (White Crest Mills, Campbell River, B.C.) at 10 to20 minute intervals during daylight hours using automatic feeders.A series of weight measurements was made on cohorts of chinook salmon spawnedin the fall of both 1985, and 1986. The 1985 cohort was transferred to swim-up tanks onFebruary 22, 1986 (avg. wt. =0.66g) and to seawater on June 14, 1986 (avg. wt. =8.96g).The 1986 cohort was transferred to swim-up tanks on February 21, 1987 (avg. wt. =0.74g)and to sea water on July 11, 1987 (avg. wt. =14.60g). The 1985 cohort was sampled fromFebruary to December, 1987 and the 1986 cohort from March to October, 1988. In bothyears the fish were approximately 16 months old (from fertilization) at the start of thesampling and approximately 25 months old at the final sampling. Survivals from transfer toseawater to age 19 months were; 81% for the 1985 cohort and 85% for the 1986 cohort(Table 1.1.1).9Table 1.1.1: A summary of the numbers of chinook salmon from the two year classes thatwere found to be jacks and silvers (non-jacks). The percentages of the totalpopulation, when the fish were sorted, are given in parentheses.TOTAL HIGHGRADELOWGRADE1987Number of SmoltsNumber of Fish at Sort36 00029 000 3 475 25 525(80.5%) (12.0%) (88.0%)Number of Jacks 4 997 3 317 1 680(17.2%) (11.4%) (5.8%)1988Number of Smolts 13 450Number of Fish at Sort 11 391 1 724 9 667(84.7%) (15.1%) (84.9%)Number of Jacks 2 543 1 685 854(22.3%) (14.8%) (7.5%)10Fish were sampled using a 13.0m X 10.0m deep seine, and from each set a randomsample was removed with dip nets. These fish were anesthetized (0.15 ml•L -1 2-phenoxyethanol), weighed on a double beam balance (OHAUS) to the nearest 10g, andreturned to the pens.In late May of 1987, the 1985 cohort was sorted by size into two separate groupsaccording to size such that the upper 10-15% size class (high-grade) was removed and keptin a separate netcage. In early June 1988, the 1986 cohort was similarly sorted. The sortingwas done by estimating the wet weight of the live fish by comparing them to dead fish ofknown weight. Since every fish was handled and no anaesthetic was used, the fish weretreated, as a prophylactic measure, with oxytetracycline before sorting.All the high-graded fish of both year classes were harvested during the fallfollowing sorting, while the low-graded fish were harvested during the winter. Some ofthe average weights reported between the sorting and the harvesting were estimated fromthe weights of mortalities. Due to logistic constraints some weight measurements were notmade on fish individually, thus no estimate of the variance could be generated for thosedata. At harvest, all fish were determined to be either jacks or silvers (non-jacks). Arecord of mortalities was kept and the number of jacks in the low-graded group recorded.By combining the numbers of jacks in the high- and low-graded group, the total jackingrate for each cohort was determined.Statistical MethodsA test for clusters within frequency distributions was used to test for bimodality(Engelman & Hartigan 1969). The null hypothesis was that the observed weight-frequencydistribution was a random sample from a normally distributed fish population. Thealternate hypothesis was that the observed distribution was a random sample from twonormally distributed populations having equal variances but different means (i.e. bimodal).The test for clusters is based on the calculation of a series of variance (likelihood) ratios ofsub-groupings of the data (for detailed descriptions see Engelman & Hartigan 1969,11McLaughlin 1989). The maximum value obtained is the B/WMAX statistic; the criticalvalues are given in Engelman & Hartigan (1969). This test has two advantages overCassie's (1954) method for the identification of bimodality: 1) the inflection point isdetermined and tested for significance based on a maximum likelihood ratio and 2) the testfor clusters can easily be implemented on a personal computer for large data sets.Differences in the slopes of the weight at age data were tested by analysis ofhomogeneity of slopes within an analysis of covariance on the means (Sokal & Rohlf1981). We used the mean Y values to maintain conservative confidence limits (seePetranka 1984, Heath & Roff 1987 for discussion of the use of means and individualvalues in this analysis).1.1.3 RESULTSWeight-Frequency Distributions1985 Cohort (Table 1.1.2; Fig. 1.1.1). The weight-frequency data from February22 to June 21, 1987 showed the development of a clear bimodal distribution. Thedistribution in February and March was not significantly bimodal, although by March thedistribution was visibly skewed to the right. The isolated group of small fish (averageweight = app. 100g) on the left of the main distribution for the months of February andMarch represented unhealthy fish which eventually died, and thus did not appear in thelater samples. The distribution was statistically bimodal by May. In late May, 12.0% ofthe fish were high-graded as potential jacks (Table 1.1.1). Subsequently, a large sizedifference between the two groups was evident (June sampling).1986 Cohort (Table 1.1.2; Fig. 1.1.2). The weight frequency data from March 10to May 17, 1988 did not as clearly develop a bimodal distribution as did the 1985 cohortdue to the smaller sample size; nevertheless, the frequency distribution in May wassignificantly bimodal. In early June, 15.1% of the fish were high-graded as potential jacks(Table 1.1.1); no individual sampling was done after this.Table 1.1.2: Results of the tests for significance in bimodality for the 1987 and 1988weight samplings in chinook salmon (see Fig. 1.1.1 and 1.1.2 for frequencydistributions).Date SamplesizeSignificancelevellDividingWeight2(g)22 Feb. 1987 129 N.S.26 Mar. 1987 154 N.S.26 May 1987 84 P<.01 65821 June 1987 76 P<.005 71010 Mar 1988 62 N.S.12 Apr 1988 56 N.S.17 May 1988 89 P<.01 6471 Significance level generated from B/Wmax statistic (after Engelman & Hartigan 1969).2Dividing weight is the weight of the individual fish that lies on the dividing point betweenthe two distributions.12N - 129 FEB 87r- 154 MCH 8713.... 85^ MAY 87*353025201510s3025201510151012N — 77 JUNE 879631.-GIGILL II0 • •50^350 650 950 1250 1550WEIGHT (g)Figure 1.1.1. Wet weight frequency distribution in chinook salmon in 1987 (1985Cohort). The shaded bars in the June sampling represent fish that had been high-graded, mostly jacks). * represents statistically significant bimodality (P < 0.01).Sample size is indicated for each distribution.89MAY 884e142016105Cl)^0wCC15105>m0Z 0w20wCC 1510N 62^ MARCH 881•■ 56^ APRIL 8850^300^550^800^1050WEIGHT (g)Figure 1.1.2: Wet weight frequency distribution for chinook salmon in 1988 (1986cohort). * represents statistically significant bimodality (P < 0.01). Sample size isindicated for each distribution.15Jacking Rates1985 Cohort (Table 1.1.1): In total, jacks made up 17.2% of the 1985 cohort;11.4% came from the high-graded group (95.4% jacks) and 5.8% came from the low-graded group. Thus the high-graded group contained 66% of the jacks and only 0.6% ofthe silvers while the low-graded group contained 34% of the jacks and 99.4% of thesilvers.1986 Cohort (Table 1.1.1): Jacks made up 22.3% of the 1986 cohort; 14.8% camefrom the high-graded group (97.5% jacks) and 7.5% came from the low-graded group.Thus the high-graded group contained 64% of the jacks and only 0.5% of the silvers whilethe low-graded group contained 36% of the jacks and 99.5% of the silvers.Growth1985 Cohort: Growth curves of the 1985 cohort high- and low-graded fish show thelarge size gap between the two groups in June (Fig. 1.1.3a). This gap increased through tothe early winter, however in December, 1987 the average wet weight of the low-gradedfish (mostly silvers) was very close to that of the high-graded fish (mostly jacks - Fig.1.1.3a). At this time the jacks were in extremely poor condition, with their visceraseverely shrunken and their belly wall very thin. We therefore excluded the Decemberweight measurement for jacks from the analysis of homogeneity of slopes. The slope of thebest-fit line for growth of jacks was significantly greater than the slope for the low-gradedfish (P= 0.0025).1986 Cohort: The growth curves for the 1986 cohort high- and low-graded fishagain show the increasingly large differential in body weight between the two groupsthrough the summer (Fig. 1.1.3b). The slope of the best-fit line for growth of jacks (high-graded fish) was significantly greater than the slope for the low-graded fish (P= 0.0115).,••••I^•••• ft..a4%.ft.,■ •••• -to,,,,iiI-iWz<w22000 rb I25.0.......•ge,MAR APR MAY JUN JUL AUG SEP OCT NOV DEC161500100050002000150010005000,.Figure 1.1.3: Average wet weight of chinook salmon versus time for the 1985 (a) and1986 (b) cohorts. The solid lines represent the low-graded fish (mostly silvers), andthe dotted line represents the high-graded fish (mostly jacks). Data points enclosedin boxes were taken from mortalities, and tend to be smaller sample sizes.171.1.4 DISCUSSIONIn aquaculture, the impact of jacking on the cohort as a whole is extensive. Sincethe jacks are generally larger than the silvers (Fig. 1.1.3a & b) they contributedisproportionately to the total biomass. Within this study, jacks constituted 17.2% of the1985 cohort and 22.3% of the 1986 cohort numerically, but accounted for approximately24% and 31 % of the biomass in September, respectively. Sixty-six percent of the jacks inthe 1985 cohort and 64% of the jacks in the 1986 cohort were sorted out based solely onthe difference in size. This sorting was done before secondary sexual characteristics wereexpressed, and thus at a time when the fish still retained good market value.A bimodal growth pattern has been observed in Atlantic salmon during both thefreshwater and seawater phases of their life-cycle (Simpson & Thorpe 1976, Thorpe 1977,Bailey et al. 1980, Thorpe et al. 1980, 1982, 1990). A probable mechanism for thefreshwater bimodality is the reduction in the feeding activity of the fish in the lower modegroup during the summer prior to the development of the bimodality due to behavioralinteractions (Higgins 1985, Metcalfe et al. 1986, 1989), coupled with an increase infeeding activity in the higher mode group (Metcalfe et al. 1988). Initially bimodality insize of Atlantic salmon parr was thought to be primarily related to maturation and onlyincidentally to smolting (Thorpe et al. 1982); however, Villarreal & Thorpe (1985) latershowed that sexual maturation was not the primary cause of the bimodality. Thorpe (1989)presented a model that proposed critical time windows for the initiation of maturation andsmolting and described possible interactions between the two processes. The similaritiesbetween the bimodal frequency distributions described for the Atlantic salmon parr andthose described in this chapter are striking; it would be reasonable to propose a criticalwindow model similar to that described by Thorpe (1989) for jacking in chinook salmon.In general for salmonids, the age of first maturity is believed to be stronglydependent on individual size and growth rate (Alm 1959, Gardner 1976, Thorpe 1986,1991, but see Naevdal et al. 1978b, Thorpe 1989, Herbinger & Friars 1992). This is18supported by considerable evidence of a negative correlation between the age of maturationand growth rate in chinook salmon (Bilton 1984), Atlantic salmon (Gardner 1976, Gjedrem1984, Randall et al. 1986, Berglund 1992, Saunders et al. 1982, among others), rainbowtrout, Oncorhynchus mykiss (Gjedrem 1984, Tsumura & Hume 1986, Lamont 1990),brook trout, Salvelinus fontinalis (McCormick & Naiman 1984), and coho salmon (Lamont1990, Hagar & Noble 1976).There is strong evidence that altering food availability at critical time periods canincrease or decrease the incidence of precocious maturation (Rowe & Thorpe 1990b,Thorpe et al. 1990). Rowe & Thorpe (1990b) subjected sibling groups of Atlantic salmonparr to seasonal variations in feeding opportunity and found that reduced feed availabilityin the spring prior to maturation suppressed early maturation whereas increased feedingduring the spring enhanced early maturation, while Thorpe et al. (1990) showed a similareffect for grilsing in Atlantic salmon held in seawater netcages. One potential mechanismproposed for the effect of altered feeding levels on the incidence of sexual maturation is aspring threshold stored energy level necessary for maturation (Herbinger & Newkirk 1990,Simpson 1992, Rowe & Thorpe 1990b), although Herbinger & Friars (1992) reported thatthis threshold level for precocious maturation of Atlantic salmon parr was probably low,and hence not a good predictor of maturation. Rowe et al. (1991) recently published astudy showing that the levels of mesenteric fat in May prior to the precocious maturation ofAtlantic salmon parr are critical to precocious maturation, and proposed a model wherebythe mesenteric fat stores act as sites for aromatizing circulating testosterones into estrogens,and that these estrogens then trigger the maturation process. Thus fish with larger stores ofmesenteric fat would have higher rates of aromatization of testosterone into estrogen, andbe more likely to sexually mature (Rowe et al. 1991).The reported correlations between growth rate and sexual maturation do not implythat precociously maturing fish have an accelerated growth rate during the later stages ofgonadal development. In fact, it is generally accepted that as fish progressively mature they19experience a reduction in growth due to allocation of energy to gonadal development (Ware1980, Roff 1983). There are reports of reduced growth of rainbow trout and Atlanticsalmon during maturation (Thorpe 1975, Moller et al. 1976, Naevdal et al. 1978b). Thedata presented here, however, do not support those observations; jacking males, raised innet cages, showed no decline in growth into their spawning period (i.e. September andOctober - see Fig. 1.1.3a & b). Possible mechanisms for the maintained growth seen injacking chinook salmon may be; increased appetite, aggressiveness, and food conversionefficiency and/or hormonal growth stimulation, all of which may relate to the elevatedandrogen, thyroid, and growth hormone levels associated with sexual maturation of themale (see Chapter 3.1). Although there is little published information available on thetiming and nature of the changes in behaviour, physiology, and blood chemistry associatedwith jacking in chinook salmon, observations suggest an increase in aggressiveness of jacksduring maturation (pers. obs.).The results presented here show that it is possible to identify groups of fish that areup to 97% jacks (up to two-thirds of the total number of jacks) before any secondarysexual characteristics are apparent. Furthermore, a bimodality in the weight-frequencydistribution of chinook salmon develops in the spring prior to jacking in two separate yearclasses, suggesting a possible critical time for the initiation of jacking in chinook salmon.202.1 GENETIC, ENVIRONMENTAL, AND INTERACTION ElitECTS ON THEINCIDENCE OF JACKING IN CHINOOK SALMON2.1.1 INTRODUCTIONJacking occurs in most natural and hatchery stocks of chinook salmon, and sincejacks are generally smaller returning fish, they are considered as undesirable by bothcommercial and sports fishermen. Salmon farmers on the west coast of North Americasuffered large losses to jacking during the first years of culture (Hunter et al. 1983) sincethe maturing fish held little market value. Until recently, jacks were routinely excludedfrom Federal Salmon Enhancement Program (SEP) breeding programs, however theincidence of jacking in hatchery stocks is still higher than in wild stocks, despite theselection against jacks (Bocking & Nass 1992).Although there is little solid evidence of a genetic component to jacking in chinooksalmon, Hard et al. (1985) showed a strain effect in the incidence of jacking intransplanted stocks of chinook salmon in Alaska, and this was interpreted as a geneticeffect. There is strong evidence that genetic factors play a role in determining the timing ofsexual maturation in other species of salmonids (see Gardner 1976, Gjedrem 1984, Gall1983, Naevdal 1983). By far the bulk of the detailed genetic work on sexual maturationhas been with Atlantic salmon parr and grilse (Gjerde 1984, Naevdal 1983, Naevdal et al.1978a, Myers et al. 1986, Glebe & Saunders 1986, Thorpe et al. 1983), although somework has been done on coho salmon (Iwamoto et al. 1984, Silverstein & Hershberger1992), rainbow trout (Gall & Gross 1978b, Gall et al. 1988, Moller et al. 1976), andArctic char, Salvelinus alpinus, (Nilsson 1992). There has been relatively little detailedresearch on the incidence of precocious maturation in salmonids after smolting, perhapsdue to the logistic difficulties of rearing large numbers of adult fish in seawater facilities.There is evidence that environmental effects can be highly significant contributorsto the determination of the age of sexual maturation in salmonids (Alm 1959, Gardner211976, Randall et al. 1986, Thorpe 1991). Generally, environmental effects reported ashaving significant effects on the precocious maturation of salmonids are those that relate togrowth acceleration (Thorpe 1991). Experience in the SEP program has shown that growthacceleration in the hatchery leads to higher jacking rates in returning adult coho andchinook salmon (Bilton 1980, 1984), however these observations were based on relativelymodest returns; and therefore must be interpreted with caution. Although the effect ofaccelerated freshwater growth on the incidence of jacking in chinook salmon is not wellknown, it is likely to increase the jacking rate.This study was designed to test for the effects of three factors on the incidence ofjacking in a captive population of chinook salmon. Those were:1) sire age, i.e. jack vs. non jack male parent;2) dam; and3) temperature of early rearing water.The mating design was unconventional in that sires were nested within dams. Although thisdesign complicates the estimation of additive variance, this study was conceived todetermine whether any significant genetic effect was present, rather than to generateheritability estimates. The use of heated water in the early rearing phase was included totest for the effect of growth acceleration on jacking rates, as has been reported by SEP andcommercial hatcheries.2.1.2 Materials and MethodsMating Design and IncubationThe fish used for this breeding experiment were first generation domestic pureRobertson Creek stock, and originated from 15 females mated one-to-one with anequal number of males, all spawned late in the run. In September 1989, over 100sexually maturing male and female chinook salmon were taken at random from thatstock with multiple seine sets at the saltwater rearing facilities of Yellow IslandAquaculture Ltd. (YIAL, Quadra Island, British Columbia), and transferred tofreshwater facilities (aerated well water). On November 9 1989, six 3-year-oldfemales were spawned, and the eggs from each female were divided into twoapproximately equal groups. In order to increase the potential diversity of the malecontribution to the offspring, half of the eggs from each female were fertilized by 2-year-old males (jacks), while the other half were fertilized by 3-year-old males (non-jacks). Each male was used only once and all fertilizations took place within 2 h ofgamete collection. The resulting 12 families were further divided into two sub-groups(Table 2.1.1). The development of one of these sub-groups was accelerated byincubating the eggs and alevins in heated water (average temperature = 10.2 °C;range = 9.0 - 11.1 °C) while the other sub-group was incubated in unheated water(average temperature = 8.0°C; range = 7.4 - 9.0°C). All family groups wereincubated in vertical stack incubation trays (Heath Technicorp., Seattle, Washington)with flows of 12-16 L•min -1 . The eggs were disinfected 2-3 times per week withmalachite green (50-100 mg•L -1 , for 5-10 min. followed by flushing with freshwater) until the eyes of the developing embryo were clearly visible (eyed stage;approximately 30 days at 10°C). Once eyed, the eggs were shocked and dead eggsremoved. All losses were recorded throughout the incubation period. By January 3,1990 the accelerated (Acc) family groups were hatched, and by February 7, thealevins had reached swim-up stage (yolk-sac fully absorbed). The fish in the non-accelerated (N-Acc) family groups were hatched by January 21, 1990, and thosealevins reached swim-up stage by March 13, 1990.Early rearingAt swim-up, each family (500 to 1000 fry) was randomly assigned to one of24 identical 200L outdoor tanks. All tanks received equal water flows (15 L•min -1 )from a common source (average temperature = 8.8°C; range = 7.8 - 10.0°C). For14 days after swim-up, fry were fed during daylight hours with automatic feeders,22eight times per hour. Subsequently, the fry were fed to satiation by hand four timesper day. The fry were fed Biomoist starter diet (Bioproducts Ltd., Warrenton,Oregon) until they reached 1.2 g when they were switched to a semi-moist diet(Moore Clarke Canada, Vancouver, B.C.). Mortalities were removed and recordeddaily.Nose TaggingOn May 8, 1990, 500 fry (average wt= 2.85 g) from each of the 12 Accfamily groups were anesthetized (0.15 ml•L -1 2-phenoxyethanol) and a coded wirenose tag implanted (Jewell & Hager 1972). On May 23, 1990, 500 fry (averagewt= 2.43 g) from each of the 12 N-Acc family groups were anesthetized and a codedwire nose tag implanted (as above). Twenty-four differently coded nose tags wereused, and fish could be identified as to family of origin as well as to Acc or N-Accgroups. After the tagging, the fry were transferred to four 3000 L indoor tanks, andthe Acc and N-Acc groups were kept separate.RearingOn May 22, 1990, the Acc family groups (average wt= 4.0 g) were dip-vaccinated against vibriosis following the manufacture's instructions (Microtek,Victoria, B.C.), and on June 13, 1990, the N-Acc family groups (average wt= 3.7)were similarly vaccinated. The Acc family groups (average weight = 8.4 g) weretransferred to seawater grow-out facilities on June 30, 1990, after a two weekacclimation period with 25 % pumped sea water, and the N-Acc groups (average wt= 7.3 g) were similarly transferred on July 19, 1990. The Acc and N-Acc familygroups were reared in separate netcages; initially 5mX10mX10m enclosures, andlater 10mX10mX10m enclosures. Throughout the seawater rearing period,mortalities were removed weekly by SCUBA divers, and frozen for later nose tagrecovery and decoding. The fish were fed to satiation one or two times daily using acommercially available diet (White Crest Mills, Campbell River, B.C.). The Acc and23N-Acc fish were sampled approximately monthly for weight. In the late summer /early fall of 1990, the Acc and N-Acc family groups both experienced acute losses,presumably due to vibriosis (from August 19-22 for the Acc fish, and from October7-10 for the N-Acc fish), in each case the fish were treated for eight days withantibiotic (0.167 g•Kg -l •day-1 ; Romet, Syndel Laboratories, Vancouver, B.C.). OnDecember 9 and 10, 1990, 415 Acc fish and 439 N-Acc fish were removed from thenetcages, killed in an overdose of 2-phenoxyethanol (2.5 ml•L -1 ), weighed (+ 0.1g), and their nose tags removed and decoded to identify the fish to family of origin.The fish remaining in the netcages were individually counted to establish aninventory of surviving fish. In March, 1991, a further 425 fish were removed fromthe Acc family groups for the analysis of hormonal and growth changes associatedwith jacking (Chapter 3.2). During March and April, 1991, evidence of river otterpredation in both the Acc and the N-Acc family group netcages prompted theemployment of double predator nets and electrified fencing to control predation, andby May, 1991, there was no further evidence of predation.Final SampleBy September 1991, the sexually mature males (jacks) could be distinguishedby body morphology and skin colour. On September 19 and 20, 1991, all the jacks inboth the Acc and N-Acc family groups were individually sorted, anesthetized in CO2saturated water and killed with a sharp blow to the head. The total wet weight andtestes weight was measured, and the nose tag recovered and decoded for each jack.The remaining nonmature fish were commercially harvested during the fall of 1991;at the time of harvest they were individually weighed and their nose tags recoveredand decoded. The sex ratio for each family was estimated using a Y-chromosomalsex probe for chinook salmon (Devlin et al. 1991) and DNA from blood samples forall family groups taken from randomly selected fish prior to sexual maturation of the24jacks (i.e. December 1990 sample, and March 1991 sample). The sex ratio estimatewas based on 17-75 sexed fish per family (Table 2.1.1).AnalysisJacking rate (JR) was calculated as the total number of jacks in each familydivided by the total number of surviving fish in that family (including the jacks). Themale-specific jacking rate (SJR), or the percent of male fish that jacked, wascalculated as follows;.SJR = JR • SR -1 100%Where SR was the estimated sex ratio (Table 2.1.1).A hierarchical series of log-linear models were used to test for the effect ofrearing environment (i.e. Acc versus N-Acc), male parent (i.e. jack versus 3-year-old), female parent, and interactions on the observed jacking rates. The models werefit iteratively using the maximum likelihood criterion (SYSTAT, Evanston, IL,USA). The statistical significance of the various terms was determined by calculatingthe change in the log-likelihood statistic with the removal of the effect in questionfrom the saturated model (Fienberg 1970).There are five difficulties associated with estimating the heritability of jackingwithin this experiment;1) Jacking is a threshold trait and is therefore scored on a binomial scale (i.e."0" or "1"),2) The mating design (males nested within females) does not allow anunbiased estimate of heritability based on a sib-analysis (Falconer1981),3) The number of surviving fish varied widely across the families,25264) The male parents were not randomly selected, but rather for 50% jacks and50% non-jacks, and5) Due to logistic constraints, only 12 families were used, thus any estimateof heritability would have extremely large uncertainty associated withit.Despite these limitations two approaches were used to estimate the heritabilityof jacking in the population of chinook salmon at Yellow Island Aquaculture Ltd.The first was parent - offspring regressions of the jack (value = 1) and non jack(value = 0) sires nested within a single dam on the incidence of jacking (ratio) in thefull-sib offspring. Six regression coefficients were thus generated for the Acc and N-Acc family groups; these were averaged to yield a mean regression coefficient (andSE). Heritabilities for the Acc and N-Acc groups were calculated by multiplying themean slope by two, as described by Falconer (1981) for nested parent-offspringregressions. The second method used to estimate heritability was based on anANOVA on the incidence of jacking in the Acc and N-Acc groups separately. Themodel used was;Y- 1(^+ Dk + Sjk + eijkWhere Y .. k was the sexual maturation status (i.e. 0-male or 1-jack) of the i thprogeny of the j th sire nested within the k th dam, p. is the population (least square)mean, Dk is the effect of the k th dam, Sjk is the effect ofthe effect of the j th sire nested within the kth dam, andeijk is the random error term. Since the number of surviving progeny varied widelybetween families, the ANOVA would be highly unbalanced, thus an approximatelyequal number of progeny was chosen at random for each family to include in theanalysis. The data in this analysis consisted of zeros and ones, and thus theassumption of normality for ANOVA (Sokal and Rohlf 1981) was violated.However, since the incidence of jacking in most families was high, and ANOVA isrelatively robust to non-normality under these conditions (Sokal and Rohlf 1981), theresults of the ANOVA are probably valid. Iwamoto et al. (1984) described a similarexperimental design created to test for genetic effects in the incidence of coho salmonprecocious parr. Despite low average maturation rates (app. 1 %) Iwamoto et al.(1984) used the binomial ANOVA described above. Heritabilities for both the Accand the N-Acc family groups were estimated using the calculated and expected meansquares (following Falconer 1981).All estimated heritabilities were corrected to the continuous liability scale(Van Vleck 1972, Falconer 1981, Iwamoto et al. 1984) using;h2 = h2b z2 / [p(1-p)]Where h2 is the continuous scale heritability, h2b is the binomial scale heritability(calculated from a threshold phenotype), z is the ordinate of the normal distributionat the threshold point which divides jacks from non jacking males, and p is thefrequency of jacking in the offspring (Iwamoto et al. 1984). It should be noted thatthese heritability estimates should be viewed with caution due to the limitations listedabove.2.1.3 ResultsGrowthThe Acc and N-Acc family groups grew at similar rates throughout the duration ofthe experiment, although the Acc groups generally had slightly higher absolute growthrates than the N-Acc groups (Fig. 2.1.1a & b).272.00.0 Acc28- 0 - N-Acc0 50 100 150 200 250 300TIME (days post smolt)43^85 124 150 220 283TIME (days post smolt)AccN-AccFigure 2.1.1: (a) Mean wet weight (± SE) of the accelerated (Acc) and non-accelerated(N-Acc) chinook salmon family groups used in the analysis of jacking rates plottedagainst time. (b) Absolute growth rate (i.e. linear slope of weight vs. time) of theaccelerated (Acc) and non-accelerated (N-Acc) chinook salmon family groups.29SurvivalThere were large differences in the survival of the various family groups within theAcc and N-Acc environments from the time of marking to December 1990, as well as tothe final sampling in September 1991 (Fig. 2.1.2a & b). The overall survival of the Accand N-Acc groups were similar (17% - Acc; 25% - N-Acc), but significantly different (X 2test; P>0. 05). Generally, families from dam 5 and jack sired families had slightlyhigher survival, while families from dam 3 had lower survival (Fig. 2.1.2a & b).Sex RatiosAlthough most families had roughly equal numbers of males and females, a few hadskewed sex ratios (Table 2.1.1). Overall the sex ratio was not significantly different from50:50 (X2 test; P > 0.10).Jacking RatesOverall jacking rates (% jacks in population) were 19.5% for the Acc group and17.3% for the N-Acc group. The specific jacking rates (SJR) varied between and withinthe Acc and N-Acc groups (Fig. 2.1.3a & b). There was a significant effect ofenvironment (Acc vs. N-Acc) on the observed jacking rates (G=14.85; df=1; P < .001)with the Acc groups having a higher jacking rate. There was a significant dam effect on theobserved frequencies of jacking (G=231; df=5; P < .001), as well as a significant sireeffect (jack vs. non-jack) on the observed frequencies (G=22.2; df=1; P< .001). Theinteraction effect of dam-by-environment was found to be significant (G=22.7; df=5;P < .001), as was the sire-by-environment interaction (G=9.43; df=1; P < .003). Thenorms of reaction for jacking rate across the two environments (Fig. 2.1.4) show that thesignificant genotype-by-environment interactions were mainly due to two families (dam 6by jack sire, and dam 3 by non jack sire). The three-way interaction (sire-by-dam-by-environment) was found to be non-significant.30Table 2.1.1: A list of the 24 full- and half-sib family groups used for the analysis of thegenetic and environmental contributions to the incidence of jacking in chinooksalmon. The family groups arose from six dams, twelve sires (six jacks: J, and sixthird year spawners, i.e. non-jacks: N) nested within dams, and all families werereared under two early rearing regimes (accelerated - Acc, and non-accelerated N-Acc). The estimated sex ratio (% males) for each family group is given with thetotal number of fish used for the estimation. The totals are the overall sex ratio andthe total number of fish sexed.DAM SIRE(N / J)ENVIRONMENT(Acc / N-Acc)SEX RATIO(% males)NUMBERN Acc 54 57J Acc 50 321N N-Acc 48 29J N-Acc 43 30N Acc 53 36J Acc 44 682N N-Acc 37 30J N-Acc 57 30N Acc 40 25J Acc 48 253N N-Acc 35 23J N-Acc 50 20N Acc 54 24J Acc 44 454N N-Acc 47 30J N-Acc 50 30N Acc 49 75J Acc 49 695N N-Acc 69 30J N-Acc 43 23N Acc 36 25J Acc 56 276N N-Acc 65 17J N-Acc 42 24TOTALS 48.5% 82431Table 2.1.2: Calculated heritabilities for precocious sexual maturation (jacking) in farmedRobertson Creek chinook salmon stock. The heritabilities were calculated from sire-male offspring regressions, and sib-analysis (ANOVA) with progeny scored as ones(jacks) and zeros (non-mature males). Separate heritability estimates were made forthe accelerated (Acc) and no4i-accelerated groups (N-Acc), and are presented asbinomial scale estimates (hb`), as well as transformed to continuous scale estimates(h'). Standard errors are given for the heritability estimates based on sire - maleoffspring regressions.ENVIRONMENT^SIRE-OFFSPRING^SIB ANALYSISDAM^SIREAcchb2^0.48 (+ 0.24)^0.33^1.16h2^0.77 (± 0.39)^0.53^1.86hb2^0.32 (+ 0.14)^0.22^0.73h2^0.54 (± 0.23)^0.37^1.22N-AccTable 2.1.3: Results of the ANOVA on the incidence of jacking in the progeny of the 12accelerated (Acc) and 12 non-accelerated (N-Acc) families. The sire effect wasnested within the dam effect, and the Acc and N-Acc ANOVAs were runseparately. Expected mean squares were taken from Falconer (1981), where aw2was the within progeny variance component, as  was the between-sires, withindams variance component, and 0-e was the between dams component.AccSOURCE DF MS EXPECTED MSDAM 5 2.456 aw2 + 21as 2 + 42ad2SIRE 6 1.634 aw2 + 21a s2WITHIN 241 0.152 aw2N-AccSOURCE DF MS EXPECTED MSDAM 5 1.865 aw2 + 29as2 + 54ad2SIRE 6 1.217 aw2 + 29as 2WITHIN 341 0.154 aw232DEC 199011 1r^d fa 11 N-Acc^ I^I AccFINALb[11 N J^N J^N J^N J^N J^N J1 2 3 4 5 610090807060504030201001:141009080706050403020100SIREDAMFAMILY OF ORIGINFigure 2.1.2: Percent survival (from pre-smolt nose-tagging) for each of the 24chinook salmon family groups in the analysis of jacking. a) family survivals forDecember 1990 (13 months post-fertilization), and b) for the final sampling inOctober 1991 (23 months post-fertilization). The December survivals are basedon estimates for each family (see text). The families are the progeny of six dams(1 - 6) each mated to two males; one jack (J) and one 3-year-old, or non-jack,male (N).10090807060504030201001009080706050403020100SIREDAMN-AccI I II t7J N^J N5^6riJ N4J N^J N^J N1^2^333FAMILY OF ORIGINFigure 2.1.3: Specific jacking rates (%) for the 24 chinook salmon family groups; a) 12accelerated fish and b) 12 non-accelerated fish. Specific jacking rate is the ratio ofjacks to the estimated total number of males (see text). The families are the progenyof six dams (1 - 6) each mated to two males; one jack (J) and one 3-year-old, ornon-jack, male (N).NON-JACK SIREa10090807060Zig^5040LLI302CC^01000 1009080LL^7060W 5040302010034N-Acc^AccFigure 2.1.4: Norms of reaction for the observed specific jacking rates in the 12 full-and half-sib chinook salmon family groups reared under two environments,accelerated (Acc) and non-accelerated (N-Acc). The norms of reaction areshown for; a) the jack-sired, and b) the non jack sired families separately. Eachline represents a single family, and the dam of the family is shown on the right.The accepted effect of developmental acceleration is an increased jacking rate(see teaxt). Genotype-by-environment interaction is identified by crossing lines.3 5HeritabilityThe heritability estimates from the Acc and N-Acc groups based on regressions ofsire on male offspring (within dam) are presented in Table 2.1.2, along with standarderrors. The results of the 2-way ANOVA for sire and dam effects on jacking incidence areshown in Table 2.1.3, along with expected mean squares. For the heritability estimatesgenerated by the sib analysis (Table 2.1.2), no estimates of standard errors werecalculated. Continuous liability scale heritability estimates are also shown in Table 2.1.2.Note that the sire component heritability estimates exceed 1.0 when converted to thecontinuous scale, indicating possible non-additive effects.2.1.4 DISCUSSIONA genetic component to precocious sexual maturation has been demonstrated inmany salmonid species. Breeding experiments designed to partition this genetic componentto sexual maturation into maternal and paternal contributions have been reported forAtlantic salmon (Gjerde 1984, Naevdal 1983, Naevdal et al. 1978a, Myers et al. 1986,Glebe & Saunders 1986, Thorpe et al. 1983), rainbow trout (Gall & Gross 1978b, Gall etal. 1988, Moller et al. 1976), Arctic char (Nilsson 1992), and coho salmon (Iwamoto etal. 1984, Silverstein & Hershberger 1992). Many of the genetic analyses of precocioussexual maturation in salmonids have been done on pre-smolt parr and one of the commonproblems faced by these analyses has been non-genetic maternal, or "commonenvironmental", effects (Falconer 1981 - see Iwamoto et al. 1984).Non-genetic maternal effects have been identified as factors in precociousmaturation in a number of salmonid species (Silverstein & Hershberger 1992, Bailey et al.1980, Sutterlin & MacLean 1984, Nilsson 1992). Perhaps the most obvious non-geneticeffect of a dam on her offspring is egg size, and hence early growth. The effect of egg sizehas been shown to influence size at age, however this effect decreases with age (Silverstein& Hershberger 1992, Sutterlin & MacLean 1984, Gall 1974, Withler et al. 1987). A3 6maternal effect on early growth could have a profound impact on estimates of the damcomponent of the observed variance in maturation timing (Bradford & Peterman 1987,Silverstein & Hershberger 1992), however Gall et al. (1988) showed that maternal effectswere very small for age at spawning in rainbow trout. Although it is unlikely that such aneffect would be a major factor in the present study, since jacking occurred 18 months post-hatch, non-genetic maternal effects cannot be ruled out.The effect of sire age (i.e. jack vs. non-jack) in the present study was very clear;the SJR of jack sired fish was 44.8%, while the SJR of non-jack sired fish was 26.9%, andfor all but one dam the jack-sired full-sib families had higher SJR (Fig. 2.1.3).Independent of the partitioning of the genetic variance for jacking into additive and non-additive components within the population of chinook salmon examined, it is clear thatjacking incidence could be profoundly affected by the choice of sires. Similar results havebeen reported for coho and Atlantic salmon precocious parr (Glebe & Saunders 1986,Thorpe et al. 1983, Gjerde 1984, Iwamoto et al. 1984).In salmonids, the age of first maturity is generally believed to be stronglydependent on individual size and growth rate (Alm 1959, Thorpe 1986, Randall et al.1986, see Chapter 1.1). Lamont (1990) showed that for individually tagged rainbow troutand coho salmon, the fastest growing individuals were precociously maturing males. Thereported relationships between growth rate and precocious sexual maturation do not,however, imply causation. Iwamoto et al. (1984) conducted a controlled breedingexperiment where no increase in the incidence of precocious maturation was found in cohosalmon where early growth had been accelerated using heated water. Herbinger & Friars(1992) also found no consistent effect of accelerated (or decelerated) growth on theincidence of early maturation in Atlantic salmon parr. In the present study, a statisticallysignificant increase in jacking rate was found for the accelerated family groups, however,the magnitude of the difference was modest (17.3% vs. 19.5%) despite a fairly largedifference in size throughout the saltwater rearing period (Fig. 2.1.1a, b). Although the3 7duration of the growth or developmental acceleration (i.e. heated water) was limited inboth the present study and that of Iwamoto et al. (1984), the differences in the average sizeof the accelerated and control fish were comparable to that reported in studies that found acorrelation between size or growth rate and the incidence of precocious maturation (seeChapter 1.1). Herbinger & Friars (1992) suggested that the energy reserve threshold forprecocious maturation in Atlantic salmon parr may be relatively low, and hence the effectof accelerated growth may not have a large effect. It appears that artificially acceleratedgrowth early in development may elicit a different response than in the naturally fastgrowing individuals in a population.The presence of significant sire- and dam-by-environment effects indicates thatgrowth acceleration early in life does not simply lower the threshold for jacking within allfamilies alike. The norms of reaction presented in Fig. 2.1.4a & b show that most of thegenotype-by-environment interaction is explained by two full-sib families (dam 3, jack-sired; dam 6, non-jack-sired). Genotype-by-environment interactions have been found fortemperature and growth in a number of salmonids (McKay et al. 1984, Nilsson 1992,Iwamoto et al. 1984, Heath et al. 1992 - Appendix A). Few instances of genotype-by-environment interactions for temperature and precocious maturation have been reported insalmonids (Nilsson 1992). The environmental effect in this study includes not only theearly growth and size at age differences between the Acc and N-Acc family groups, butalso any "netcage effects" due to the two groups being held in separate unreplicatednetcages. It is thus difficult to quantify the environmental effects contributing to theinteractions. However, it is fair to say that the fish in this experiment were held in a muchmore homogeneous environment than most wild or enhanced stocks experience.The estimates of heritability based on intra-dam regressions of male offspring onsire (Table 2.1.2) do not include dominance effects (VD) and are not confounded by non-genetic maternal effects (VCE - Falconer 1981), and thus are probably the best heritabilityestimates possible within this study. The heritability estimates based on the sib analysis3 8have a number of limitations (listed in Materials and Methods), however the results werepresented in order to show the differences between the sire and dam estimates. The dam-component heritability is biased by any non-genetic maternal effects (0.25VA + V&), andthe sire-component heritability include dominance effects (0.25VA + 0.25VD). Since thesire-component of heritability is much larger than the dam-component, it is likely that astrong dominance effect (VD) is present, although some form of sex-linkage is alsopossible. The heritability estimates generated by the sire-male offspring regressions areconsiderably lower than those of the sire-component within the sib analysis (Table 2.1.2).This may be due to a dominance effect, or may possibly be due to a difference in thebreeding values of the parental and progeny generations (i.e. a domestication effect). Table2.1.4 shows some reported heritability estimates for early sexual maturation in salmonids.These estimates vary widely, and there is evidence that precocious maturation in saltwateris genetically controlled separately from freshwater precocious maturation in Atlanticsalmon (Glebe & Saunders 1986, Gjedrem 1984).It should be noted that the heritability estimates presented in this study are based ononly twelve families and are thus should be interpreted with caution. However, since thegenetic contribution to the observed variation in jacking rates was so high, the heritabilityestimates may be meaningful. Given the relatively consistent results of this analysis, amore detailed breeding experiment to determine the nature of the observed dominanceeffect in the sire contribution is warranted.Precocious maturation in some fish may be controlled by simple geneticmechanisms. Glebe & Saunders (1986) noted that in Atlantic salmon, the frequencies ofprecocious male parr could be explained by a single gene model, and sexual maturation insome Xiphophorus spp. is also controlled by a single locus (Kaltman & Bao 1982,Zimmerer et al. 1989). The variation in jacking rates in the present study, indicates thatjacking in chinook salmon may also be determined by a few1 as cited in Gjedrem (1984)s •sire componentd dam componentr* parent-offspring regressionprecocious maturation pre-smoltTable 2.1.4: Estimates of heritability for mean age of first maturation in salmonids takenfrom the literature. Three methods of estimation are reported; sire and damestimates refer to sib analysis, presumably on the binomial scale, and parent-offspring regressions. Standard errors were included when reported.SPECIES h2 REFERENCEChinook salmon 0.30 Ricker (1980) 1Coho salmon * 0.05 s (± 0.05) Silverstein & Hershberger(1992)0.13d (± 0.11)0.17 Iwamoto et al.^(1984)Rainbow trout 0.21s Gjerde & Gjedrem (1984)0.26d0.09 s Moller et al.^(1976)0.01dArctic char 0.45 s (± 0.17) Nilsson (1992)0.12 d (± 0.08)0.19 s (± 0.11) I/0.60d (± 0.24)Atlantic salmon 0.39 s Gjerde & Gjedrem (1984)0.49d0.48r394 0loci, although an analysis of F2 progeny would be necessary to confirm this.There is also evidence that jacking in chinook salmon may be sex linked. Twocohorts of female chinook salmon were hormonally masculinized (Hunter et al. 1983) atYellow Island Aquaculture Ltd. These phenotypically male, genotypically female fish hadvery low jacking rates (1.4% in 1990, n= 2300; 2.7% in 1991, n=1500; unpublisheddata) compared to jacking rates of genotypically male fish from similar stocks (30 - 40%).The incidence of third year maturation in the sex-reversed female stocks at Yellow IslandAquaculture were close to that observed for the regular males.412.2 DNA FINGERPRINTS IN SALMONIDS PRODUCED BY HYBRIDIZATIONWITH OLIGONUCLEOTIDES.2.2.1 INTRODUCTIONThe previous chapter described a breeding experiment designed to identify geneticand environmental contributions to jacking in chinook salmon. The next two chaptersdescribe the development of molecular-genetic tools for use in chinook salmon. Theultimate aim of developing such tools was to use them to estimate the relatedness of jackingand randomly selected chinook salmon from a random-mating population. If jacking has afamily component, the average relatedness of the jacking fish should be greater than that ofthe randomly selected fish. A genetic component to jacking may be thus identified, prior tothe large investment of time and resources necessary for extensive breeding programs.Within fisheries science and aquaculture such molecular-genetic tools are alsoneeded to identify stocks, families, parentage, and individual fish on a genetic basis(Hallerman & Beckmann 1988, Bentzen et al. 1991, Harris et al. 1991). Specifically, thepotential uses include;1) identification of valuable brood lines for commercial purposes,2) identification of stocks of fish for management purposes,3) identification of full-sib families for selection experiments without physical tags, and4) identification of relatedness and inbreeding to determine the impact of managementpractices on the genetic diversity of a population.The methods currently used to measure genetic diversity within stocks or populations offish (such as enzyme polymorphisms, mitochondrial DNA Restriction Fragment LengthPolymorphisms (RFLPs), and genomic RFLPs) are limited by either low levels ofheterozygosity, high technical difficulty, or both (Hill 1987, Wetton et al. 1987,Hallerman & Beckmann 1988, Taggart & Ferguson 1990a, Bentzen et al. 1991, Wirgin etal. 1991).4 2An alternate method, DNA fingerprinting, allows visualization of the geneticvariation present in genomic DNA tandem repeats (minisatellite DNA). DNAfingerprinting has been employed or proposed for use in the identification of populations orstocks (see Hallerman & Beckmann 1988, Gilbert et al. 1990, Rogstad et al. 1991, Wirginet al. 1991), as well for the identification of parentage or individual animals of particularinterest (Jeffreys et al. 1985, Burke & Bruford 1987, Hoelzel & Amos 1988, Harris et al.1991). The identification of full- or half-sibs using DNA fingerprinting is problematic dueto the large number of bands and the relatively large probability of band sharing due tochance alone (Anonymous 1989, Devlin et al. 1990, Taggart & Ferguson 1990b, Lynch1991, Burke et al. 1991). However Rico et al. (1991) reported success in identifyingoffspring from a single parent in threespine sticklebacks, Gasterosteus aculeatus, as well asin birds (Burke & Bruford 1987, Wetton et al. 1987, Jones et al. 1991). Perhaps the mostimportant potential application of DNA fingerprinting lies in the estimation of relatednessor genetic diversity of a population of organisms. This has been reported for example, instriped bass populations, Morone saxatilis, (Wirgin et al. 1991), isolated fox populations(Gilbert et al. 1990), inbred chicken lines (Dunnington et al. 1991), and the clonallyreproducing pawpaw tree, Asimina triloba (Rogstad et al. 1991). Many of the applicationsof DNA fingerprinting would benefit from a wide selection of multi-locus hypervariableminisatellite probes (Harris et al. 1991, Burke et al. 1991).Minisatellite DNA sequences (Jeffreys et al. 1985) have been shown to hybridizewith DNA from a wide variety of organisms (Burke & Bruford 1987, Jeffreys & Morton1987, Georges et al. 1988, Ryskov et al. 1988, Taggart & Ferguson 1990b, Harris et al.1991, Rogstad et al. 1991). However, relatively few of the known minisatellite probeshave been tested on salmonids. DNA fingerprints have been reported for Atlantic salmon,(Fields et al. 1989, Taggart & Ferguson 1990, Bentzen et al. 1991), rainbow trout (Fieldset al. 1989, Lloyd et al. 1989, Taggart & Ferguson 1990b, Bentzen et al. 1991), browntrout, Salmo trutta L. (Taggart & Ferguson 1990b), chum salmon, Oncorhynchus keta and4 3coho salmon, (Fields et al. 1989, Bentzen et al. 1991), and chinook salmon, (Bentzen etal. 1991).The use of chemically synthesized oligonucleotides as DNA fingerprinting probeshas been investigated in humans (Ali et al. 1986, Schafer et al. 1988), as well as indomestic animals (Georges et al. 1988), plants (Nybom et al. 1992, Weising et al. 1992),and insects (Blanchetot 1991, 1992). Epplin et al. (1991) reported on over two hundredspecies ranging from fungi to humans that were successfully probed for DNA fingerprintsusing short repetitive-sequence oligonucleotides. A wide variety of chemically synthesizedDNA fingerprint probes could be easily obtained by most laboratories and are simple andfast to label and use (Epplin et al. 1991). For this study eleven oligonucleotides weresynthesized with minisatellite DNA core sequences as reported in the literature (Table2.2.1). The synthesized oligonucleotides ranged from 11 to 18 bases and include theoligonucleotide corresponding to the core sequence of the M13 fragment, reportedelsewhere as producing DNA fingerprints in salmonids (Fields et al. 1989). Oneoligonucleotide was examined that was very similar to the core sequence for the Jeffreysprobes (1985) that have been shown to hybridize with salmonid DNA (Taggart & Ferguson1990b). The purpose of this work was to identify potentially useful DNA fingerprintingprobes for use with chinook and other species of salmon.2.2.2 MATERIALS AND METHODSDNA ExtractionDNA was extracted from liver or testicular tissue samples from one adult male andone adult female chinook salmon (Robertson Creek stock, Vancouver Island, BritishColumbia), and from three of their offspring. DNA was also extracted from two presumedunrelated individuals from eleven other species of salmonids (Table 2.2.2)bes in chinook salmon. The sequence, reference,temperatures are either the optimised conditionsstringency conditions that were used for initialyielded multiple discreet bands.Table 2.2.1: Eleven oligonucleotides screened as potential DNA fingerprint proand origin of each oligonucleotide is given. The hybridization and washused to produce the autoradiograms shown in Fig. 2.2.1, or are the lowscreening. Only the first six (underlined) of the eleven oligonucleotidesOligo-nucleotide SequenceTemperature ( °C)OriginHyb. WashYN24 GGAGCAGTGGGNNNTACA 1 42 42 HumanM13 GAGGGTGGNGGNTCT 2 41 41 Wild type M13 bacteriophageMY01 GGAGGTGGGCAGGGAG 3 38 36 Human myoglobin geneGLOB GNGGGGNACAG4 30 30 Human alpha-globin geneHBV3 GGTGAAGCANAGGTG3 38 36 Hepatitus B virusPERT GACNGGNACNGG 4 38 36 Mouse (related to DrosophilaPER gene)PER2 TCAGGCTCAGGC4 28 28 1 1INS ACAGGGGTGTGGGG 3 28 28 Human insulin geneYN73 CCCGTGGGGCCGCCG1 28 28 HumanYNZ22 CTCTGGGTGTCGTGC 3 28 28 HumanCAC5 CACCACCACCACCAC5 28 28 Human1 Nakamura et al. (1988); 2 Vassart et al. (1987); 3 Nakamura et al. (1987); 4^5Georges et al. (1988); Schafer et al. (1988)45Table 2.2.2: Salmonid species used for hybridizations with oligonucleotides YN24 andM13 DNA fingerprint probes. Except as noted, the mean number of bands are theaverages of the number of distinct bands above 3 Kb (kilobases) counted on theoriginal autoradiograms for two unrelated individuals of each species (digested withHae III), and are given for both probes (YN24 and M13).Species Common Name Mean Number ofBandsYN24 M13Oncorhynchus kisutch Coho salmon 27 240. masou Masu salmon 33 26O. keta Chum salmon 32 29O. nerka Sockeye salmon 29 37 *O. gorbuscha Pink salmon 31 28O. mykiss Rainbow trout 27 21 *Salmo salar Atlantic salmon 31 26Salvelinus alpinus Arctic char 30 24S. malma Dolly Varden 33 24S. namaycush Lake trout 1 9 * 20Coregonus clupeaformis Lake whitefish 28 24* One indivividual counted since the other is not clear.4 6following the protocol described in Devlin et al. (1991). Approximately 100-200 mg offrozen or 95% ethanol preserved tissue was finely chopped and placed into 5.0 ml ofproteinase K buffer (10 mM tris (pH 8.0); 10 mM ethylenediaminetetraacetic acid(EDTA); 1% sodium dodecylsulphate (SDS)), and 200 Ag•m1- 1 of proteinase K. Thesolution was incubated at 37 °C, with gentle rocking overnight. NaC1 was added to a finalconcentration of 1.5 M, and the resulting solution was mixed by inversion, and thencentrifuged (15 mM @ 3500 rpm). The supernatant fluid was extracted once with phenol:chloroform: isoamyl alcohol (50:50:1) and the DNA was precipitated by the addition of0.6 volumes of isopropyl alcohol. The pellet was washed with 70% ethanol, dried, andredissolved in TE (10mM tris (pH 8.0), and 1mM EDTA).DNA Digestion, Fractionating, and TransferFive microgram aliquots of each DNA sample were digested overnight in 30 Alwith Hae III restriction enzyme (BRL, Life Technologies Inc., Gaithersburg, MD., USA)according to the manufacturer's instructions. The digested DNA was fractionated byelectrophoresis on a 25 cm, 0.5% agarose gel at approximately 1.5 V•cm -1 until thefragments smaller than 1 kilobase (Kb) had run off the gel. DNA was transferred toHybond-N nylon filters (Amersham Corp. Illinois) according to Sambrook et al. (1989).OligonucleotidesThe sequence for eleven oligonucleotides ranging from 11 to 18 bases long werechosen from published reports of variable number tandem repeats (VNTR) and minisatelliteDNA core sequences (Table 2.1.1). The oligonucleotides were synthesized at theUniversity of British Columbia's Oligonucleotide Synthesis Laboratory (Vancouver, B.C.).The oligonucleotides were end-labelled with gamma-[ 3211ATP using T4 kinase(Boehringer-Mannheim) as described by Sambrook et al. (1989).Filters were pre-hybridized for 2 h in a solution comprised of 7% SDS, 1 mMEDTA (pH 8.0), 0.263 M Na2HPO4 and 1% bovine serum albumin (fraction V)(Westneat et al. 1988), at 42°C. End-labelled oligonucleotides were mixed with 10 ml of4 7pre-hybridizing solution, added to the filters, and allowed to hybridize overnight. Theeleven oligonucleotides were initially screened by hybridization with chinook salmonfamily DNA at low temperatures (28 °C). Filters were washed twice in 2 X SSC (0.3 MNaC1, 0.3 M sodium citrate, pH 7.0), and 0.1 % SDS for 25 minutes at room temperature,and once at a higher temperature (28-42 °C; Table 2.2.1). Filters were then wrapped inSaran wrap and exposed to X-ray film without an intensifying screen for two to seven daysat room temperature. Oligonucleotides that yielded a variable banding pattern werehybridized at higher stringency to reduce the non-specific binding (30-42 °C hybridizationand final wash temperature: Table 2.2.1).Other Salmonid SpeciesOligonucleotides YN24 and M13 were also hybridized with DNA from twopresumed unrelated individuals of 11 other species of salmonids (Table 2.2.2) underhybridization conditions determined as optimal for the chinook salmon family filters (Table2.2.1).2.2.3 RESULTS AND DISCUSSIONDue to the lack of clarity of even the best performing probes in this study, it wasfelt that an analysis of the relatedness of jacks versus non-jacks within a single populationwas beyond the sensitivity of the DNA fingerprint probes described here. Nevertheless theYN24 DNA fingerprint probe has been successfully applied to the analysis of gynogenesisin albino chinook salmon (B. Carswell, unpub. data), and has other potential uses infisheries science.Chinook Salmon FamiliesEleven oligonucleotides derived from human and other sources (Table 2.2.1) werescreened against Southern blots of chinook salmon family DNAs, and six yieldedfingerprint-like banding patterns (Table 2.2.1, Fig. 2.2.1). Different hybridization andwash temperatures were required to reduce background noise without removing the signal,4 8and presumably those reflected differences in the binding strength (and hence the signal tonoise ratio) of the oligonucleotides with the target DNAs (Fig. 2.2.1). Of the six successfulprobes, YN24 and M13 produced the strongest signal and clearest bands (Fig. 2.2.1).While probes GLOB and MYO1 also yielded multi-banded DNA fingerprints on thechinook salmon families (Fig. 2.2.1), there was more background signal, and the bandswere fainter than those produced by YN24 and M13. Probes PER1 and HBV3 showmultiple variable bands, however the signal strength was low and the resolution very poor(Fig. 2.2.1), although Castelli et al. (1990) reported clear banding patterns with the PER1probe in the barbel. It is possible that PERT and HBV3 might perform better with otherhybridization and wash protocols. The five oligonucleotides that did not produce anydiscernible bands at even the low stringency hybridization and washing conditions (Table2.2.1) are not likely to be useful DNA fingerprinting probes in salmonids. Rico et al.(1991) also found that probe YNZ22 (see Table 2.2.1) was not able to produce DNAfingerprints in the threespine stickleback.Close examination of the original autoradiographs for all probes showed that mostbands in the three offspring (a, b, and c in Fig. 2.2.1) were also seen in either one or bothparents, with only a very few exceptions (i.e. a single band at approximately 4.5 Kb inoffspring b for the M13 probe - Fig. 2.2.1). Novel bands can arise as a consequence ofgerm-line mutation in one of the parents, however, because only three offspring wereanalyzed, no meaningful estimation of the mutation rate was possible (Jeffreys et al. 1985,Hill 1987, Jeffreys et al. 1988). The limited number of offspring examined did not allowdetermination of the extent of alleleism or linkage for these probes, however minisatelliteloci generally show little linkage (Jeffreys et al. 1985, Burke & Bruford 1987, Gyllenstenet al. 1989, Castelli et al. 1990, Taggart & Ferguson 1990b).The banding patterns produced by the six probes were quite distinct from oneanother (Fig. 2.2.1), this indicates that the oligonucleotides hybridized to differentminisatellite loci. Since the six probes yielded informationPROBE: HBV3^PROBE: YN24 PROBE: M13^PROBE: GLOB PROBE: MY01 PROBE: PERI9 „i_ ,... _^9 „i_ L. ,.^9 re.. 1, ,^2 re., 1, ,^2 (-?'2 1, , h cFigure 2.2.1: DNA fingerprints of a family of chinook salmon generated by hybridization with six oligonucleotides. The family iscomprised of an adult female and male, and three of their offspring (a, b, and c). Molecular size markers are shown inkilobases (Kb) on either side.5 0on distinct loci, the use of more than one of these probes would allow more of the genometo be sampled.Other Salmonid Species Because the oligonucleotides M13 and YN24 produced the clearest banding patterns(Fig. 2.2.1), they were further hybridized with DNA from eleven other species ofsalmonids (Table 2.2.2) to assess their general applicability.Probe YN24 generated highly variable multiple banding patterns in all 11 species ofsalmonids considered here (Fig. 2.2.2). There is considerable variability in the number ofbands observed between the species (Table 2.2.2), as well as in the clarity of those bands:lake trout has very indistinct bands, while Atlantic and sockeye salmon have very clearbands (Fig. 2.2.2). Some species, such as chum and pink salmon, appear to have greaterlevels of non-specific binding than others (Fig. 2.2.2). This was also noted by Burke &Bruford (1987) using Jeffreys (1985) probe 33.15 on different species of birds.We tested probe YN24 on chinook salmon DNA digested with three otherrestriction endonucleases (Pst I, Hind III, and Hinf I), as well as combinations of pairs ofthem. We found that for Pst I and Hind III, and combinations Pst I plus Hind III, or HindIII plus Hinf I, the resulting fingerprint patterns were different, but showed essentially thesame complexity and number of bands as for the Hae III digested DNA. However Hinf I,and combinations Pst I plus Hae III, Pst I plus Hinf I, Hind III plus Hinf I, or Hinf I plusHae III, showed considerably less variation and resolution (data not shown). In general, thechoice of restriction enzyme appears to be important to the performance of YN24 as afingerprinting probe. Although the insertion-free M13 bacteriophage has been used widelyfor DNA fingerprinting (Vassart et al. 1987, Georges et al. 1988, Ryskov et al. 1988,Fields et al. 1989, Castelli et al. 1990, Rogstad et al. 1991, Wirgin et al. 1991), theresults presented here show that the M13 oligonucleotide worked as well as the cloned M13fragment for Atlantic, chum, and coho salmon (Fig. 2.2.3), but not as well as the fragmentfor rainbow trout (see Fields et al. 1989).1 2 K b -9 Kb5 K b -3 K b -2 K b -r.Coho salmon^Masu salmon Chum salmon^Sockeye salmon^Pink salmon(0. kistiteh)^(0. mewl)^(0. kits)^(0. narks)^(0. gorbasch.)Rainbow trout^Atlantic salmon^Arctic char^Dolly varden^Lake trout^Lake whitefish(0. my.thys) (Sa/mo ss/sr1^(Ssivellnus alpinus)^(S. ms/mg/^(S. nentsyems4) (Corsganas agooslorm/s)Figure 2.2.2: DNA fingerprints of two presumed unrelated individuals from each of eleven species of salmonids generated byhybridization with the YN24 oligonucleotide. Note that the individual fish are the same as for the M13 hybridizations (Fig.2.2.3). Molecular size markers are shown in kilobases (Kb) on either side. vt- 5 Kb- 3 Kb- 2 Kbbra12 Kb -9 Kb -5 Kb -3 Kb -2 Kb --12 Kb- 9 KbCoho salmon^Masu salmon^Chum salmon^Sockeye salmon^Pink salmon^Rainbow trout^Atlantic salmon^Arctic char^Dolly varden^Lake trout^Lake whitefish(0. A-/suten)^(0. ~sou)^(0. Avis)^(0. Away)^(0. gorbuse/ts) (0. mykiss) (Sobno solorl^(Sairefinas ./p/nos)^(S. ms/ms)^(S. nlynysycilsAl (Corsponas agoourformillFigure 2.2.3: DNA fingerprints of two presumed unrelated individuals from each of eleven species of salmonids generated byhybridization with the M13 oligonucleotide. Note that the individual fish are the same as for the YN24 hybridizations (Fig.2.2.2). Molecular size markers are shown in kilobases (Kb) on either side.53There was considerable variation in the number of discernible bands between species(Table 2.2.2), as well as in the clarity of the bands. For example, rainbow trout DNAfingerprints were not as distinct as those of the Dolly Varden (Fig. 2.2.3).The YN24 and M13 probes produced quite different results for the same species(Fig. 2.2.2 and 2.2.3). For example, the rainbow trout fingerprint was indistinct for theM13 oligonucleotide probe, while the YN24 probe fingerprint was relatively clear.Furthermore, the number of discernible bands was different for a given species betweenM13 and YN24 (Table 2.2.2). Thus, the availability of a selection of different probeswould allow one to choose those that yield the clearest fingerprints for the species understudy.Because of concerns regarding the negative impact of stock enhancement programson the genetic diversity of wild populations of salmonids, there is currently much interestin estimating genetic diversity using DNA fingerprinting techniques. A number of differentDNA fingerprint probes could be used to provide independent estimates of the geneticdiversity of a population of salmonids, allowing the sampling of a greater proportion of theanimal's genome (see Taggart and Ferguson 1990b). Overall, the use of DNAfingerprinting to asses the diversity of "neutral" (or non-coding) DNA is perhaps themethod of choice for use at the population level (Hill 1987, Wetton et al. 1987, Ryskov etal. 1988, Gilbert et al. 1990, Taggart & Ferguson 1990b, Dunnington et al. 1991, Harriset al. 1991, Rogstad et al. 1991, Wirgin et al. 1991).542.3 A NOVEL APPLICATION OF PCR TO AMPLIFY HYPERVARIABLEMINISATELLITE DNA SINGLE LOCUS PROBES2.3.1 INTRODUCTIONIn the previous chapter the uses of multilocus DNA fingerprinting in fisheriesscience and ecology was discussed. Although DNA fingerprinting has been proposed forthe analysis of relatedness between individuals (Jeffreys et al. 1985, Burke & Bruford1987, Hoelzel & Amos 1988, see Chapter 2.2) there are serious problems with such anapplication (Anonymous 1989, Lynch 1991, see Chapter 2.1). In multilocus DNAfingerprints there is a relatively high probability of band sharing due to chance alone,making the identification of kinship or relatedness difficult (Anonymous 1989, Lynch1991). However most of these limitations can be avoided by using minisatellite DNAsingle locus probes (Bentzen et al. 1991, Burke et al. 1991, Lynch 1991). Althoughminisatellite DNA single-locus probes have been isolated for a number of animals, therehave been few applications of them in ecology and evolutionary biology. Although therehave been some studies using single-locus probes to evaluate kinship and relatedness(Amos et al. 1991, Bruford & Burke 1991), by far the most common applications havebeen in human medicine and forensics (Bar & Hummel 1991, Wolff 1991). The mainlimitation on the use of single-locus probes in ecological and evolutionary studies has beenthe unavailability of suitable probes. Single locus probes have historically been technicallydemanding to generate (Burke et al. 1991) and often are relatively species specific.A new Polymerase Chain Reaction (PCR) based technique, Random Amplificationof Polymorphic DNA (RAPD: Williams et al. 1990, Welsh & McClelland 1990), has beenused for the analysis of parentage and kinship (Arnold et al 1991, Scott et al. 1992, seeHadrys et al. 1992), stock and strain identification (Welsh & McClelland 1990, Hadrys etal. 1992), and species identification (Chapco et al. 1992, Arnold et al. 1991, Hadrys et al.1992) in both wild and experimental populations of plants and animals. Due to the ease of55the technique, as well as the small amount of DNA required (Hadrys et al. 1992), RAPDhas many potential applications in fisheries and ecology. There are, however, twolimitation to RAPD; 1) relatively low levels of variation for some applications (Hadrys etal. 1992), and 2) rare PCR "artifacts", or unexplained bands (Scott et al. 1992). This studydescribes an extension of RAPD that generates minisatellite DNA single locus probes,without the necessity of DNA library screening, cloning or sequencing. This novelapplication of PCR is used to develop a minisatellite DNA single locus probe from chinooksalmon DNA, as well as two other potentially useful probes from human and bird DNA.The purpose of developing chinook salmon single locus probes is to estimate relatedness injack and randomly selected groups of fish from a randomly-mated population.2.3.2 MATERIALS AND METHODSGenomic DNADNA was extracted from liver, testes, and blood samples from three of the chinooksalmon families described in Chapter 2.1 (see Chapter 2.2 for protocol). DNA from two tothree unrelated individual coho salmon, chum salmon, sockeye salmon, pink salmon(Oncorhynchus gorbuscha), rainbow trout, and Atlantic salmon was also examined. Quail(Coturnix japonica) DNA from a family of birds and two unrelated individuals wasextracted from blood samples kindly provided by Dr. K. Cheng (Dept. of Animal Science,UBC). Human DNA from a single family (two progeny) was provided by J. Theilman(University of BC, Vancouver, BC). Genomic DNA from all three species (human, quail,and chinook salmon) was digested with Hae III, fractionated by gel electrophoresis, andtransferred to nylon membranes as described in Chapter 2.2, except that all DNAfragments smaller than 2 kilobases (Kb) in size were run off the gel.Polymerase Chain ReactionApproximately 0.5 pg of genomic DNA from chinook salmon, human, and quailwere used as template for 50 ill polymerase chain reactions (PCR). The synthetic5 6oligonucleotides M13, YN73, PER2, and YNZ22 (see Chapter 2.2) were used as primers.Only one oligonucleotide was used per reaction; 0.5 µg per reaction. Note that smalleramounts of primer yielded unreliable results. The balance of the PCR was CETUS buffer(50 mM KC1, 10 mM Tris (pH=4.0 @ 20 °C), 100 pg•m1-1 gelatin), MgC12 (1.5 mM),dNTPs (2.0 mM), and Tag DNA polymerase (0.05 U•p,1 -1 : GIBCO-BRL, GaithersburgMD, USA) as described in Innis et al. 1990. The reactions were run for 35 cycles with a55°C annealing cycle (1.0 min), 72°C extension cycle (1.5 min), and a 95°C denaturingcycle (1.0 min). The resulting reactions were fractionated on 1.5% low melting point(LMP) agarose gels for 3-4 hr at 70V in a coldroom (app. 8 °C). Under UVtransillumination, clearly distinguishable bands were cut out and stored at -20°C.LabellingThe frozen gel slices were heated to 68 °C for 15-30 min, then 8.0 Al wereimmediately added to a 50 itl random priming reaction (as described in Feinberg &Vogelstein 1984) and labelled with alpha-dATP (Amersham Corp., Arlington Heights, IL,USA). The random priming reactions were incubated at 37 °C to minimize thesolidification of the agarose. The completed reactions were run through G50 spin columnsto remove unincorporated nucleotides (Sambrook et al. 1989).Hybridization Membranes were pre-hybridized as in Chapter 2.2. The radio-labelled probes wereadded to approximately 15 ml of hybridization solution and added to the membranes andallowed to hybridize overnight. Hybridization temperatures were kept low (50°C) forscreening but later raised (68 °C) to reduce background signal with potentially usefulprobes. The membranes were washed as described in Chapter 2.2 for the screeningprocess, however the concentration of SSC was lowered to 0.2 X SSC to reducebackground signal. The high temperature wash was at the same temperature as thehybridization. Membranes were then wrapped in Saran wrap and exposed to X-ray film forone to two days with an intensifying screen at -70°C. Potential probes were evaluated on57the number, clarity, and inheritance pattern of the bands seen on the autoradiograph. Atotal of 26 gel slices (i.e. bands resulting from the PCR) were screened for useful single-(or few-) locus probes, they were comprised of; 12 chinook salmon, 8 human, and 6 quailgel slices.Cloning and SequencingOne chinook salmon DNA fragment (app. 400 base pairs) that appeared to detect ahighly-variable locus was re-amplified using "touchdown" PCR protocol (Don et al. 1991).The touchdown thermal cycles started at an annealing temperature of 65°C and reduced byone degree each subsequent cycle to a minimum of 50°C, followed by an additional 20cycles at 50°C annealing temperature. The PCR product was gel purified following theprotocol of Prep-A-Gene DNA Purification Matrix (BIO-RAD, Life Science Group,Hercules CA, USA). The ends of the PCR-amplified DNA were filled in with T4 DNApolymerase (GIBCO-BRL) as described in Sambrook et al. (1989), and cloned into thepBluescript II SK+ vector (Stratagene Cloning Systems, LaJolla CA, USA). Doublestranded DNA was purified from each of 18 insert-positive colonies (Sambrook et al.1989), digested with Xho 1 and Pst 1 (GIBCO-BRL) to release the inserted DNAfragment, and the digestions were size fractionated by gel electrophoresis with LMPagarose. 13 of the 18 colonies proved to contain inserts, and 6 of these were ofapproximately the correct size (400 bp). These 6 inserts were screened by cutting the bandsout of the gel, labelling them as described above, and hybridizing them with genomic DNAfrom chinook salmon (as above) to identify clones that produced the single locus pattern.Double- and single-stranded DNA was prepared from the positively screened clone(Sambrook et al. 1989). Sequencing was performed in both orientations using a Sequenasekit (United States Biochemical Corp.) and was analyzed with PCGene software(Intelligenetics).58ApplicationsThe cloned chinook salmon probe was labelled and hybridized to three chinooksalmon families; two of the families consisted of two parents and four offspring, while thethird consisted of two parents and 23 offspring. The probe was also hybridized with 17presumed unrelated chinook salmon and two to three presumed unrelated individuals fromeach of 6 species of salmonids (see above). One of the human-derived DNA fragments washybridized with DNA from a human family (parents and two progeny), while one of thequail-derived DNA fragments was hybridized with quail genomic DNA (two parents, fourprogeny, and two unrelated individuals).2.3.3 RESULTS AND DISCUSSIONThe PCR using the single oligonucleotides yielded complex banding patterns with 1to 10 clearly distinguishable bands, depending on the primer and the species (Fig. 2.3.1).These patterns were evident for the chinook salmon, human and quail template reactions,although the number and positions of the bands differed between species (Fig. 2.3.1a). ThePCR amplification of a number of different individual chinook salmon shows that althoughthere is some variation between individuals, most of the bands are not variable (Fig.2.3.1b). One hypothesis that explains these bands is presented in Fig. 2.3.2. It is possiblethat a DNA inversion could transfer non-repetitive DNA into the VNTR region. Thiswould account for the PCR amplification of DNA with only one primer since the invertedrepeats would be in the reverse orientation relative to the undisturbed VNTRs (Fig. 2.3.2).The occurrence of such an inversion would be infrequent, thus accounting for the low levelof variation seen in the banding patterns.The PCR protocol described here is an extension of the RAPD protocol. Theessential difference lies in the use of a single known VNTR core sequence as the primer, asopposed to random primers in RAPD. The VNTR core sequence primer directs theamplification to minisatellite regions, thus the process is a Directed Amplification of59Minisatellite (region) DNA (DAMD). It appears that DAMD yields species-specificbanding patterns (Fig. 2.3. la, b), and may also be useful for stock or populationidentification (this has not been tested - all of the chinook salmon shown in Fig. 2.3.1b arefrom a single stock). A PCR based method of identifying closely related species or stockswould have many applications in stock management (Hadrys et al. 1992).If the hypothesized model shown in Fig. 2.3.2 is correct, then the non-VNTR DNAamplified by DAMD could be specific to a single VNTR locus. When 26 of these putativenear-VNTR DNA fragments from chinook salmon, human, and quail were screened asprobes on Southern blots of genomic DNA, the results were one highly variable singlelocus probe for chinook salmon (OTSL1) amplified with the M13 oligonucleotide, as wellas one human and one quail probe that gave relatively simple banding patterns.The quail probe (amplified with the YNZ22 oligonucleotide) yielded two or threeloci; it is difficult to determine the segregation of the bands in the quail since the familyshowed very little variation (Fig. 2.3.3a), however the two unrelated quail show that thereis variation at these loci.The human probe (amplified with the YN73 oligonucleotide) yielded a highmolecular weight single-locus banding pattern, with a multilocus pattern at lower molecularweights (Fig. 2.3.3b). The segregation of the male parent band at approximately 10 Kbappears to show incomplete inheritance (i.e. no male parent band in offspring "b"),although a second male parent band may exist at a lower molecular weight, and may thusbe obscured by the multi-locus signal, or run off the gel.The chinook salmon probe, OTSL1, clearly hybridized to a single highly variablelocus (Fig. 2.3.4), and appeared to be conservatively inherited (Fig. 2.3.5), except for oneobvious mutation within the progeny of the first of three families shown in Fig. 2.3.5. Toinvestigate the mutation further, 23 offspring from that family were hybridized withOTSL1, and an analysis of the inheritance of the alleles is given in Table 2.3.1. Althoughthe inheritance of the alleles appears to be60a^babcdefgri^12345 67 8 9 ;abedFigure 2.3.1: Results of PRC using a single oligonucleotide as primer; 1 Kb ladder markerlanes are identified on each gel. Gel a: the first lane (lane a) is chinook salmonDNA as template with YN73 oligonucleotide as primer, the next three lanes (lanesb, c, & d) are human DNA as template with YN73, M13, and PERI respectively asprimer, the last three lanes (lanes e, f, & g) are quail DNA as template and INS,YN73, and YNZ22. Gel b: the first nine lanes (lanes 1 - 9) are chinook salmonDNA from nine unrelated individuals as template with M13 oligonucleotide asprimer, after the marker lane the next two lanes (lanes a & b) are Atlantic salmonDNA from two unrelated individuals as template with M13 as primer, the last twolanes (lanes c & d) are rainbow trout DNA from two unrelated individuals astemplate with M13 as primer.61Figure 2.3.2: A schematic diagram of the hypothesized inversion event that allows PCRamplification of multiple-sized DNA fragments (see Fig. 2.3.1) using a singleprimer with the core sequence from known VNTRs. The ancestral organizationshows the edge of a VNTR region with non-repetitive DNA represented by thestraight lines and the tandem repeats represented by the arrows. The diagram showsthe boxed section of DNA inverted in the present day organization. In the presentday organization a PCR with the core sequence of the VNTR as the primer wouldamplify the non-repetitive section of DNA enclosed in the VNTR (indicated by theshaded bar). If this hypothesized inversion event model is correct, then the PCRamplified fragment should; 1) show little variation between individuals since theinversion event would be rare, and 2) be homologous to only the minisatellite DNAlocus where the event took place.62QUAIL^ HUMANFigure 2.3.3: Autoradiographs of membranes probed with radio-labelled potential single-locus minisatellite DNA probes. The quail film ("QUAIL") shows two unrelatedindividuals (lanes 1 & 2), and a family; two parents and four offspring (lanes a, b,c, & d). Note the very low level of variation within the family, compared to thetwo unrelated individuals. The Human film ("HUMAN") shows a family; twoparents and two offspring (lanes a & b). The small number of progeny precludes aninterpretation of the inheritance of the bands, however offspring "a" (female)clearly inherited the paternal band, while offspring "b" (male) did not. The missingallele in offspring "b" may be of low molecular weight and thus obscured by themulti-locus signal.SIP•9Kb-ip7Kb-GIP11P• gigo am amp OMa b c d e f g h i j k 1 m n o p q635Kb- •^•4Kb-3Kb-^• •Figure 2.3.4: Autoradiographs of membranes with 17 unrelated chinook salmon probedwith the chinook salmon single-locus minisatellite DNA probe OTSL1. Lanes a - frepresent adult female salmon, lanes g - 1 represent adult male salmon, and lanes m- q represent sexually precocious male salmon (i.e. jacks)..1.. 11, as up —Ow^ IIIMIP IIIIMP7Kb-^imp IIMM 41IND1111111,641^2^32 cfabcd^TYabcd TYabcd12Kb-...,9Kb-IMO Mow .... MEM,UMMM.^ MIIIMD MOW gimp ■ ••••■•5Kb-1IMP^ell. .....4 Kb.^ wm* is3Kb- Figure 2.3.5: Autoradiographs of membranes with three families of chinook salmon probedwith the chinook salmon single-locus minisatellite DNA probe OTSL1. All alleleswere conservatively inherited except for the paternal allele in offspring "c" infamily 1 (marked by an arrow). This mutation represents an increase in molecularweight of the allele of between 1 and 2 Kb, depending on which paternal allelemutated.Table 2.3.1: An analysis of allele inheritance in a chinook salmon family for theminisatellite DNA locus OTSL1. Twenty-three progeny were scored for allelefrequency; expected frequencies were based on Mendelian inheritance. A total offive alleles were observed, one of which was not observed in either parent. Chi-square analysis showed that the observed frequencies were not significantlydifferent from the expected frequencies (P > 0.10).ALLELE#PARENT FREQUENCYOFFSPRINGIN^EXPECTEDFREQUENCY1 FEMALE 8 (17%) 11.5 (25%)FEMALE 15 (33%) 11.5 (25%)3 MALE 13 (28%) 11.5 (25%)4 MALE 9 (20%) 11.5 (25%)*5 - 1 (^2%) 0 (^0%)* Mutant allele from male parent656 6unequal, the segregation of the alleles was not significantly different from Mendelianinheritance (Table 2.3.1). The relatively high mutation rate seen at the OTSL1 locus (Table2.3.1) is consistent with estimates from other VNTR loci (Jeffreys et al. 1988, Bentzen etal. 1991, see Jeffreys et al. 1991a). OTSL1 was found to hybridize with other species ofsalmonids at low stringencies (Fig. 2.3.6), however the banding pattern does not reflectclear single locus variation.OTSL1 was cloned and sequenced in order to investigate the origin of OTSL1 withrespect to the hypothesized inversion event model (Fig. 2.3.2). The nucleotide sequence ofOTSL1 is 382 bases long and the sequence is shown in Fig. 2.3.7. The M13oligonucleotide is present at either end of the sequence in opposite orientation (Fig. 2.3.7),consistent with the inversion event model. The OTSL1 fragment has a total of four Hae IIIrestriction sites (Fig. 2.3.7). There are two repeated sequences within OTSL1 (Fig. 2.3.7),one of these has a Hae III restriction site and thus it is probably not involved in themultilocus fingerprint-like banding patterns observed in the other salmonid species (Fig.2.3.6) as well as in chinook salmon at low stringencies (data not shown). The secondrepeat may hybridize with the salmonid DNA to give the multi-locus banding pattern.The results of the sequencing do not clearly support the hypothesized inversionevent model (Fig. 2.3.2). The large number of Hae III sites within OTSL1 make itunlikely that the cloned fragment exists as genomic DNA at the OTSL1 locus, although theobserved single-locus banding pattern may be due to hybridization with the sequence from291bp - 382bp. The balance of the sequence could hybridize with the Hae III digestedgenomic DNA, however the bands would be off the gel (i.e. < 2.0 Kb). Independent of theorigin of the OTSL1 cloned fragment, some portion of the sequence does hybridize withsalmonid genomic DNA, in chinook salmon the hybridization occurs at a single locus,furthermore, it is likely that the variation in allele size detected at the OTSL1 locus in670. mykiss S. salar^0. keta 0. kisutch 0. garb. 0. nerkaFigure 2.3.6: Autoradiograph of a membrane with six species of salmonids probed with thechinook salmon single-locus minisatellite DNA probe OTSL1 at low stringencies.The species shown are: rainbow trout (0. mykiss) - 3 lanes; Atlantic salmon (S.salar) - 3 lanes; chum salmon (0. keta) - 3 lanes; coho salmon (0. kisutch) - 3lanes; pink salmon (0. gorb.) - 3 lanes; sockeye salmon (0. nerka) - 2 lanes.M13^> HaeIII^ 50GGGTGGCGGT TCTAGTGGCC GGTGATTGTT ATGCAGGGAA ACTGAAATCTCCCACCGCCA AGATCACCGG CCACTAACAA TACGTCCCTT TGACTTTAGA100GTTTTTACCT CATTTTTACC AGCCTGTCAC CTGTGTGCAA CTAGAAGCAACAAAAATGGA GTAAAAATGG TCGGACAGTG GACACACGTT GATCTTCGTT150CAAAACTCTA GATCACCTTT ACCCCACACA CAGAAACTCA TACAACTCTCGTTTTGAGAT CTAGTGGAAA TGGGGTGTGT GTCTTTGAGT ATGTTGAGAG200TCTCGTTGAG AATGATGATC CATGGCAAGA AGCCTCCAGT GATGATCAGTAGAGCAACTC TTACTACTAG GTACCGTTCT TCGGAGGTCA CTACTAGTCAHaeIII^ 250GGCACGAAGC CTCCAGAGAC GGCCTCCAGT CCGGAGCCTT CAGCGACGGTCCGTGCTTCG GAGGTCTCTG CCGGAGGTCA GGCCTCGGAA GTCGCTGCCAHaeIII^ HaeIII^300CCCCAGTCCG GGGCCCGCAA CAAGGTTCCC CAGTCCGGGG CCCGCAACGAGGGGTCAGGC CCCGGGCGTT GTTCCAAGGG GTCAGGCCCC GGGCGTTGCT350GGGTCCCCGC ATGGAGGCGC CACCAAAGTG GGGTGAGTCA GAGGTGGAGCCCCAGGGGCG TACCTCCGCG GTGGTTTCAC CCCACTCAGT CTCCACCTCG382GGGGTCTACG TCCCGCACCA GAGCCGCCAC CCCCCCAGATGC AGGGCGTGGT CTCGGCGGTG GGM13Figure 2.3.7: The base pair sequence of OTSL1. Arrows identify the M13oligonucleotide (and orientation) PCR primers, HaeIII restriction sites arelabelled, and the single and double underlined sequences are the two repeatedsections.686 9chinook salmon is due to VNTR variation (i.e. OTSL1 hybridizes with a VNTR region).The unrelated individuals used for Fig. 2.3.4 were the parents used for the breedingexperiment in Chapter 2.1. Inspection of the banding patterns revealed that all the possibleprogeny were uniquely identifiable using the probe OTSL1. Consequently the logisticaldifficulties with tagging and/or rearing of large numbers of separate families could begreatly reduced by the use of single locus probes such as OTSL1. Furthermore, the fishwould not have to undergo the stress of tagging and their kinship could be determined froma (less stressful) tissue sample without sacrificing the fish.Although the use of multi-locus DNA fingerprinting probes for the analysis ofrelatedness between individuals is currently being re-examined (see Chapter 2.2), many ofthe objections do not apply to single-locus probes (Lynch 1991, Jeffreys et al. 1991b).Single-locus probes are, however, technically demanding to generate (Burke et al. 1991)and are often relatively species specific. DAMD may provide a quick and simple methodfor the generation of single-locus probes for a species under study. Although in this studythe probe (OTSL1) was cloned and sequenced, this generally would not be necessary toapply DAMD-generated probes to biological or ecological problems.702.4 APPLICATION OF SINGLE-LOCUS MINISATELLITE DNA PROBES TOIDENTIFY GENETIC COMPONENT IN JACKING AND PRECOCIOUSCHINOOK PARR2.4.1 INTRODUCTIONIn Chapter 2.1, a controlled breeding experiment was described that was designedto test for a genetic component to jacking in chinook salmon. Chapters 2.2 and 2.3described two molecular biological techniques that could be used to test for geneticcontribution to the incidence of specific phenotypes within a random mating population. Ifjacking has a genetic basis, then the jack group should be the progeny of a sub-group of thepotential parents, and hence have different allele frequencies than randomly selectedindividuals. Minisatellite DNA probes would allow measurement of the genetic diversity(or "relatedness") of jacking fish and of randomly selected individuals from the samerandom-mated population at non-coding or neutral loci (Castelli & Philippart 1990, seeChapter 2.2).Historically, a number of molecular biological techniques have been used toestimate genetic diversity in animals. Protein electrophoresis has been used to demonstratedifferences in genetic diversity between populations of salmonids (Ryman 1983, Stahl1983; Cross & King 1983; Utter et al. 1989, Vespoor et al. 1991), however the relativelylow levels of variation makes protein electrophoresis unsuitable for stock, or withinpopulation, comparisons of genetic diversity (Hallerman & Beckmann 1988, Davidson etal. 1989, Triggs et al. 1992). Mitochondrial Restriction Fragment Length Polymorphisms(RFLP) have been extensively used to show genetic distance between populations andbetween phenotypes within fish populations (Wilson et al. 1987, Bentzen et al. 1989,Bernatchez & Dodson 1990, Chapman 1990, Birt et al. 1991, Knox & Verspoor 1991,Shields et al. 1992). Although mitochondrial RFLP analysis may allow stock identificationwithin a species, the level of variation is usually insufficient to measure relatedness71between groups, within a population. RAPD has also been shown to distinguishpopulations or closely related species of plants and animals (see Hadrys et al. 1992,Chapter 2.3). The potential applications of RAPD to the measurement of within-populationgenetic diversity has not been extensively examined, however RAPD does have promise(Hadrys et al. 1992). Minisatellite DNA fingerprinting has been used to estimate geneticdiversity in a number of populations of plants and animals (Wirgin et al. 1991; Rogstad1991; Dunnington et al. 1991; Gilbert et al. 1990, Triggs et al. 1992, see Chapter 2.2).Single-locus minisatellite DNA probes have been developed for a number of species(Taggart & Ferguson 1990a, Bentzen et al. 1991, Hanotte et al. 1991, see Burke et al.1991), however very few applications of single-locus probes to animal populations havebeen published.Amos et al. (1991) reported on the use of multi-locus and single-locus probes tomeasure relatedness in pods of pilot whales, and a single-locus probe has been used tocompare the genetic diversity of runs of Atlantic salmon on the east coast of NorthAmerica (P. Bentzen - pers. comm.; Marine Gene Probe Lab, Dalhousie University,Halifax N.S.). There have been extensive applications of single-locus minisatellite DNAprobes in humans for medical and forensic purposes (Jeffreys et al. 1991a, Wolff et al.1991). Although the genetic diversity of distinct populations (or stocks) has been estimatedand compared using a variety of molecular biological techniques, there have been noreports of comparisons of the genetic diversity of phenotypes within a population.This study describes the application of two hypervariable single locus probes(OTSL1 - see Chapter 2.3, and Ssal, Bentzen et al. 1991) to examine the geneticcomponent of jacking in chinook salmon, and of precocious sexual maturation in chinooksalmon under-yearling parr. The jacks were from the same breeding population as theparental fish used in the breeding experiment described in Chapter 2.1, where a substantialgenetic component to jacking was demonstrated (see Chapter 2.1). Therefore, if theanalysis of allele distribution of the jacks and randomly selected individuals shows no7 2differences, then we can conclude that the approach is not sensitive enough for this type ofapplication. The analysis of precocious chinook salmon parr is an example of this approachapplied to an uncontrolled situation.2.4.2 MATERIALS AND METHODSFish Stocks Two groups of fish were used for this experiment; underyearling chinook salmonparr from the Spius Creek Hatchery, Nicola River stock (see Appendix B), and two-year-old chinook salmon (Robertson Creek (RC) stock) from the commercial grow-out site ofYellow Island Aquaculture Ltd (YIAL). The Nicola River (NR) fish were of uncertainparentage, however hatchery personnel estimate that approximately 70 females contributedto the yearclass. The adult RC chinook salmon population was the progeny of one to onefertilization of fifteen females and an equal number of males. The NR parr were incubatedin varying temperature water (1 - 14 °C), while the RC stock was incubated in relativelyconstant temperature water (average T = 8.2 °C). The NR parr were reared (post-hatch) ina concrete raceway. The RC fish were reared in 3000 L rectangular tanks, then transferredto seawater netcages at 5-10 g average weight. The RC stock was reared to sexual maturityunder typical commercial rearing conditions at YIAL (see Chapter 1.1).SamplingNicola River parr: Approximately 50-70 precociously sexually mature male parr wereselected at random from the population (approx. 80,000 individuals) of NR parr held atSpius Creek hatchery in the fall of 1989. The precocious parr were identified as describedin Bernier et al. (1992, see Appendix B). At the same time, an equal number of non-mature parr were also taken at random. The fish were killed by a blow to the head,individually wrapped in plastic, and frozen (-20 °C) until DNA was extracted.Robertson Creek adults: In the fall of 1989 approximately 150 jacks and 200 non-maturefish were taken from a single netcage (approx. 12,000 individuals) at YIAL using a hook7 3and line as well as by recovering recent mortalities and moribund fish by SCUBA diving.All live fish were killed by a blow to the head. Liver or testes tissue samples were takenfrom all fish and were individually bagged and frozen (-20 °C) until DNA was extracted.DNA Extraction and Southern TransferThe whole fish samples from the Nicola River parr were dissected while still frozenand liver tissue was taken for the DNA extraction. The extraction protocol for all sampleswas that described in Chapter 2.2. Sex was determined for all the non-mature fish usingthe Y-chromosomal probe developed by Devlin et al. (1991). Approximately 3µg of DNAfrom 74 jacks, 95 females, and 22 non-mature males from the RC stock, and from 45precociously mature male parr, 29 females, and 22 non-mature males from the NR stockwere digested overnight with Hae III, size fractionated by gel electrophoresis (0.6%agarose), and transferred to nylon membranes (as described in Chapter 2.2). DNA fromone individual was run on all gels to act as a control for the band position determination.Molecular weight standards (1 Kb ladder DNA - Gibco-BRL) were run on both end lanesand in the middle lane of all gels. Polaroid photographs were taken of the UVtransilluminated gels (0.5 µg•m1 -1 ethidium bromide added to the gels) with a rulerincluded for reference to allow band size determination based on the positions of themolecular weight standards.Probes and HybridizationThe filters were hybridized with two probes; OTSL1, the chinook hypervariablesingle locus probe (SLP) described in Chapter 2.3, and Ssal, a highly variable SLPdeveloped for Atlantic salmon (Bentzen et al. 1991). The hybridization protocol used forboth probes is described in Chapter 2.3. Each filter was stripped of probe (followingmanufactures instructions - Amersham Corp. IL, USA) after being hybridized withOTSL1, then re-hybridized with Ssal. The hybridized filters were exposed to X-ray filmwith intensifying screens at -70 °C for one to three days.Allele Scoring7 4To determine the molecular size of each allele, a linear relation was generatedbetween the natural log of the migration distance (with respect to the loading wells) and thenatural log of the size (Kb) of the marker bands for each gel, based on measurements madeon the Polaroid photos. Distance measurements (to the nearest mm) were made from theloading wells to the top (closest to loading wells) of all bands (alleles) for the OTSL1- andSsal-probed autoradiographs. These distance measurements were converted to approximatefragment sizes (in Kb) using the log-log relation described above. The individual that wasrun on all gels was used to confirm the allele size conversion for each gel. All patternswhich consisted of a single band were identified as homozygous for that probe, although,formally, hemizygosity cannot be ruled out. The Ssal probe yielded higher backgroundsignal than OTSL1, however the bands were still distinguishable.Allele BinningOnce all individuals had both OTSL1 and Ssal allele sizes scored, an estimation ofthe error associated with the calculated allele sizes was made. Error in allele size originatesfrom two sources; within gel errors (measurement errors, non-uniform migration speed,etc.), and between gel errors. The repeated individual lane allowed an estimation of therange of between gel error, while the frequently occurring "common alleles" allowed anestimate of the within gel error. Using this information, allele "bins" were definedconsisting of ranges of allele sizes that were slightly larger than the total observed errorrange. Since the error range increased with allele size, the bin width was set using a simplelinear function based on + 2.5% of the median allele size for OTSL1 and + 3.5% of themedian allele size for Ssal. Thus at small allele sizes (i.e. 3.0 Kb) the bin width was small(i.e. 2.93 Kb - 3.07 Kb), while larger allele sizes (i.e. 15 Kb) had correspondingly largerbin widths (i.e. 14.62 Kb - 15.38 Kb). Once a series of bins had been defined that coveredthe range of measured allele sizes (for both probes and stocks) the bins were shifted by 0.1Kb increments until the alleles that were known to be of the same fragment size fell into a75single bin. The range of bin shifts that allowed the known alleles to fall into a single binwas determined and the bin shift was set to the center of this range.Data AnalysisTo test for differences in the distribution of the allele sizes between; 1) the jacksand the non-mature adult chinook salmon, and 2) the precocious parr and the non-maturecontrols, a log-linear model was fitted to the frequency distribution;log Mij = A + Si + Bj ± SBijWhere Mii is the expected number of alleles for the i th sexual maturation category (matureor non-mature), and j th bin number, A is the grand mean of the expected counts, Si is themain effect of the i th sexual maturation category, Iii is the main effect of the j th binnumber, and SBii is the interaction of the ith sexual maturation category and the j th binnumber. This model is saturated and gives expected cell counts equal to the observed cellcounts (SYSTAT, Evanston, IL, USA). To test the interaction between sexual maturationstatus and bin number for significance the above model was modified by dropping theinteraction term, then rerun. If the modified model gives expected counts that aresignificantly different (based on the G statistic described in Sokal & Rohlf 1981) from theobserved then the interaction is significant. A significant interaction indicates the frequencydistribution of the two sexual maturation categories (mature versus non-mature) arestatistically different. Two factors combine to make this analysis highly conservative; 1) asa non-parametric analysis, the log-linear model is inherently conservative (Sokal & Rohlf1981), and 2) the use of wide band widths for the allele binning (see above) probablysuppresses some allelic variation (i.e. true allele differences are binned together). Theoverall effect of this analysis is therefore a higher probability of a Type II error (Sokal &Rohlf 1981), that is, accepting an incorrect null hypothesis.7 6Differences in the frequency of homozygous loci between; 1) jacks and females,and 2) precocious parr and controls, were tested using the 2-way contingency table analysis(Sokal & Rohlf 1981).Mean cumulative frequencies of novel alleles were calculated by counting thenumber of "novel" alleles per fish within a single gel. An allele was defined as novel whenit had not been observed in any of the previously scored fish. Counts were made withingels to allow visual scoring of alleles, rather than the using the conversion and binningroutine described above. Since the sexually mature and non-mature controls from bothstocks occurred on more than one gel, the numbers of novel alleles for each fish wereaveraged to give a mean cumulative frequency distribution. The use of the average reducesthe variation in the first few fish scored (i.e. the impact of a homozygous fish would belessened). The mean cumulative frequency of novel alleles for OTSL1 and Ssal wasplotted against fish number for the mature and non-mature groups from the RC and NRstocks. The cumulative frequency of novel alleles for OTSL1 was also plotted against fishnumber for a full-sib family and for 17 unrelated individuals (these were not repeated thusthe cumulative frequencies could not be averaged). High relative relatedness appears as alower sloped curve on such a plot. The cumulative frequency distributions were tested forsignificant differences using the two-sample Kolmogorov-Smirnov test (Sokal & Rohlf1981).2.4.3 RESULTSOTSL1: Frequency histograms for the range of allele bins generated by OTSL1 areshown in Fig. 2.4.1 for the adult RC fish, and in Fig. 2.4.2 for the NR parr. Few allelesfell on the borders of the allele bins, indicating that the bin positions were probablyadequate. The RC jack and female OTSL1 allele frequency distributions were significantlydifferent (G=57.9, df=9, P< .001), while the NR precocious parr and control parrfrequency distributions were not (G=11.1, df=7, P > .13).2015aO152577a- I^_11111^II_ MIN LI NIL3^3.8^4.8^6.2^7.9^10.^12.MEDIAN ALLELE SIZE (Kb)Figure 2.4.1: OTSL1 locus allele frequencies (within allele bins) plotted against medianallele size for the RC adult chinook salmon; a) adult female salmon (N=95), b)jacking salmon (N=74), and c) the difference of (a) and (b) allele frequencies. Theallele frequency distribution of the jacks is significantly different from that of thefemales.b5040302010O78I. 111 IN 111b50403020100W 30^ C0Z 20LUIX^10u.^ou_ -10CI-203.2^4.1^5.2^6.6^8.5^10.MEDIAN ALLELE SIZE (Kb)Figure 2.4.2: OTSL1 locus allele frequencies (within allele bins) plotted against medianallele size for the NR chinook salmon parr; a) non-mature control parr (N=51), b)precociously mature male parr (N=45), and c) the difference of (a) and (b) allelefrequencies. The allele frequency distributions of the mature parr and the non-mature control fish are not significantly different.40353025201510aO 79abCLi3.3^4.4^5.9^7.9^10.^14.^18.MEDIAN ALLELE SIZE (Kb)Figure 2.4.3: Ssal locus allele frequencies (within allele bins) plotted against median allelesize for the RC adult chinook salmon; a) adult female salmon (N=87), b) jackingsalmon (N=68), and c) the difference of (a) and (b) allele frequencies. The allelefrequency distribution of the jacks is significantly different from the females.403530262015106O151050-a- 10- 15- 20- 25■^-.III Ilmm .1.a-^C J-I Li'U30-^ I^b- ml^Al I= ...I .. I..1 0 -5 -8030252015105O252015015w0 10zw scc^0WLLU.^-gsC) -10-152.0^4.2^8.0^8.7^12.^17.^25.MEDIAN ALLELE SIZE (Kb)Figure 2.4.4: Ssal locus allele frequencies (within allele bins) plotted against median allelesize for the NR chinook salmon parr; a) non-mature control parr (N=47), b)precociously mature male parr (N=41), and c) the difference of (a) and (b) allelefrequencies. The allele frequency distributions of the mature parr and the non-mature control fish are not significantly different.81Ssal: Frequency histograms for the range of allele bins generated by Ssal areshown in Fig.s 2.4.3 & 2.4.4 for the adult RC fish the NR parr, respectively. Few allelesfell on the borders of the allele bins, indicating that the bin positions were probablyadequate. The RC jack and female Ssal allele frequency distributions were significantlydifferent (G=45.1, df=12, P < .001), while the NR precocious parr and control parrfrequency distributions were not (G=15.2, df=9, P> .08).The observed frequencies of heterozygotes are given in Table 2.4.1 for both lociand both stocks. There were no significant differences in heterozygosity found betweensexually mature and non-mature fish at either locus, or within either stock (Table 2.4.1).However the RC stock (females) had a significantly higher frequency of heterozygotes thanthe NR stock (controls) at the OTSL1 locus (P < 0.05). The overall heterozygosity for theOTSL1 locus in the RC and NR stocks combined was 82%. The heterozygosity for theSsal locus in the RC and NR stocks combined was 91 %.The mean cumulative frequency of novel OTSL1 alleles for the RC stock (jacks vs.females), the NR stock (precocious parr vs control parr), and 17 unrelated and 17 full sibindividuals are shown in Fig. 2.4.5. There were no significant differences between themean cumulative frequencies of the sexually mature and non-mature fish for either the RCor NR stocks. The mean cumulative frequency of novel Ssal alleles for the RC stock (jacksvs. females), and the NR stock (precocious parr vs control parr) are shown in Fig. 2.4.6.There were no significant differences between the mean cumulative frequencies of thesexually mature and non-mature fish for either the RC or NR stocks.82Table 2.4.1: The frequency of heterozygote chinook salmon at the minisatellite DNA lociOTSL1 and Ssal. Two stocks and two phenotypes in each stock of chinook salmonare presented; jacks and females from a population of Robertson Creek (RC) adults,and sexually precocious male parr and non-mature controls from a population ofNicola River (NR) parr. There were no significant differences between thephenotypes for frequency of heterozygotes at either locus (G test, P > 0.05).LOCUS STOCK PHENOTYPE HETEROZYGOSITY SAMPLE(%) NUMBEROTSL1 RC JACK 85.1 74FEMALES 87.2 94NR MATURE MALE 57.6 45CONTROLS 73.2 56SSA1 RC JACK 79.1 67FEMALES 90.3 72NR PRECOCIOUS PARR 93.1 43CONTROLS 92.9 56- b201812a400 FEMALES0 JACKS• CONTROLS0 PRECOCIOUS201012a400 12• 153 ^II1883O^3^•^a^12^15^180^a^•^a^12^15^18CUMULATIVE FISH NUMBERSFigure 2.4.5: Mean cumulative number of novel alleles at the OTSL1 locus plotted againstcumulative fish numbers for: a) precocious mature male and non-mature control NRchinook salmon parr, b) jack and female (non-mature) adult RC chinook salmon,and c) a full-sib chinook salmon family and 17 unrelated chinook salmon.Differences in allele diversity are identified by differences in the elevation of theplots. There were no significant differences between the mean cumulative novelallele frequencies for the mature and non-mature fish, however the RC adult stockdid have a significantly higher allele diversity than the NR parr stock.201012a40• FULL-SIBS0 UNRELATED84201512ao CONTROLSa• PRECOCIOUS4 3 • • 12 16^1a20 bis12 ,- O FEMALES• JACKSa43 a • 12 1a^18CUMULATIVE FISH NUMBERSFigure 2.4.6: Mean cumulative number of novel alleles at the Ssal locus plotted againstcumulative fish numbers for: a) precocious mature male and non-mature control NRchinook salmon parr, and b) jack and female (non-mature) adult RC chinooksalmon. Differences in allele diversity are identified by differences in the elevationof the plots. There were no significant differences between the mean cumulativenovel allele frequencies for the mature and non-mature fish.8 52.4.4 DISCUSSIONBefore the results of the allele frequency analysis can be discussed in detail, it isimportant to make two points:1) Our analysis is based on only two loci, and thus "relatedness" and diversity based onthese two loci do not necessarily reflect the whole genome; and2) The two loci examined in this analysis have not been mapped, or extensively checkedfor linkage with phenotypes, thus it is possible that one or both loci may be undersome form of selection pressure.Nevertheless, since both OTSL1 and Ssal are minisatellite DNA-associated probes, theyprobably behave similarly to Variable Number Tandem Repeat (VNTR) loci in humans inthat they hybridize with non-coding or "neutral" areas of the genome (Castelli & Philippart1990), and can be used as unbiased measures of kinship or relatedness.The analysis of the allele frequency distributions for the OTSL1 and Ssal locishowed that jacks represented a genetic subset of the RC population, i.e. there weresignificant differences in the allele frequency distributions at both loci; some alleles wereover-represented in the jacks, while others were under-represented (Fig. 2.4.1 & 2.4.3).Thus the jacks did not represent a random sample from the population, assuming therandomly selected females adequately represented the population (this assumption would beviolated if the populations had experienced significant sex-specific selection or mortality).The differences in the allele frequency distributions may have been due to either; 1)genetic effects (i.e. certain families being predisposed to jacking), or 2) non-geneticmaternal and "tank" effects leading to non-uniform mortality (selection): our approachcannot distinguish between these possibilities. However, since the fish were held in acommon environment from hatch, and non-genetic maternal effects are generally notsignificant for fish at these ages (see Chapter 2.1), it is likely that the differences in allelefrequencies reflects genetic contributions to the incidence of jacking. The analysisdescribed here also shows that single-locus minisatellite DNA probes are sensitive enough8 6to identify differences between phenotypes in random-mated populations. In the case ofchinook salmon jacks, it is not surprising that the mature males formed a (genetic) subsetof the population, since the breeding experiment (based on the same population of fish)showed strong family effects for jacking (see Chapter 2.1).There was no difference between the precocious and non-mature control NR parr inallele frequencies for the OTSL1 and Ssal loci, however, one of the limitations of ouranalysis is that non-significant results are ambiguous. There are three possible explanationsfor the lack of differences:1) there was no family component to precocious maturation;2) there was too little allelic variation in the parental generation; and3) the sample size was not large enough, given the conservative nature of theanalysis.Although it is possible that there was no family component to the incidence of precociousparr in the NR stock, it is unlikely since there is evidence for family or stock effects inother chinook populations (Chapter 1.1). If the parental generation had low levels ofvariation at the OTSL1 and Ssal loci, then the resolving power of our analysis would begreatly reduced. For example, consider the extreme case where all parents have the samealleles at both loci; in such a case, no differences would be detectable between the allelefrequency distributions of any sub-groups of the progeny. There is evidence that theparents of the sampled NR parr were, in fact, fairly related. Inspection of the allelefrequency histograms of their progeny (Fig. 2.4.2 & 2.4.4) shows that the NR parr hadconsiderably fewer alleles than the RC adult chinook salmon, and furthermore, the NR parrhad one or two extremely common alleles at both the OTSL1 and Ssal loci (Figs 2.4.2 &2.4.4). In general, the NR parr appear to be inbred, relative to the RC adults. It is difficultto determine how much of an increased sample size would be necessary to yield significantresults, or even if any sample size would be large enough, given the probable limited allelediversity in the parental generation. The results do indicate, however, that the NR chinook8 7salmon population at the Spius Creek hatchery is probably not a good candidate for anextensive breeding experiment.Although the mean heterozygosity at the OTSL1 and Ssal loci were comparable toother single-locus minisatellite DNA probes (Henke et al. 1991, Jeffreys et al. 1991a),there were no differences between the maturing and non-maturing groups in either stock.This reflects the difference between relatedness and inbreeding; it is possible for a group offish to be related, but not be inbred. Thus, although the jacks were found to be a geneticsubset of the adult chinook salmon population, they did not have a lower level ofheterozygosity. It is obvious that a comparison of heterozygosity levels cannot generally beused to infer genetic differences between phenotypes in random mating populations. It isinteresting to note that the heterozygosity of the adult female RC chinook was significantlyhigher than the control NR chinook parr. This suggests that the NR stock has lower geneticdiversity than the RC stock.The mean cumulative novel allele frequencies for both loci showed no differencesbetween the maturing and randomly selected fish (Figs. 2.4.5 & 2.4.6). This type ofpresentation is designed to reflect differences in allele diversity, not allele distribution.Since the analysis of the allele frequency distribution showed a difference between thejacks and the females, and the mean cumulative novel allele plots showed no difference,the genetic differences detected between jacks and females were due to differences in alleledistribution, not allele diversity. The mean cumulative allele plots also show that, ingeneral, the NR parr were less genetically diverse at the OTSL1 and Ssal loci than the RCadults, at least within the hatchery-reared population. That is, the curves for the NR parrare generally lower than the RC adults (Figs. 2.4.5 & 2.4.6). The extreme examples ofunrelated individuals and a full-sib family (Fig. 2.4.5) show the potential range of themean cumulative allele frequencies for the OTSL1 locus; the NR parr and the RC adultsare both of intermediate allele diversity, between unrelated and full-sib individuals.88The analysis of the allele distribution frequencies for phenotypes of interest (lifehistory strategies) in random mating populations has two important potential applications.One of these is screening wild populations for family effects in traits of interest. In theory,any measurable phenotypic trait could be used, however quantitative traits would have tobe arbitrarily divided into two or more groups (such as "large" and "small" for size at agedifferences). This study describes the first attempt to determine family effects in a specifictrait within a random mating population, using DNA-based technology. Although the useof single-locus minisatellite DNA probes simplifies the analysis, multi-locus fingerprintingprobes could also be used, provided the signals were clear. The use of minisatellite DNAvariation to estimate relatedness in groups of animals should prove to be a valuable tool forstudying natural populations, especially those that cannot be sampled or selectively bred.The second potential application is the comparison of genetic diversity betweenpopulations. Although the absolute magnitude of the allele diversity would have littlepractical value (it would depend on the specific loci sampled), a comparison of diversitieswould be useful to determine the effects of various management practices on the geneticdiversity of threatened populations.8 93.1 HORMONAL AND GROWTH CHANGES ASSOCIATED WITH JACKING INCHINOOK SALMON3.1.1 INTRODUCTIONFive months prior to maturation, cultured chinook salmon develop a bimodalweight frequency distribution (Chapter 1.1). The upper mode, or the largest fish, wereshown to consist almost exclusively of jacks, while the lower mode was mostly composedof non-jacks, or silvers (Chapter 1.1). Although the work described in Chapter 1.1 impliedthat jacking chinook salmon experienced an elevated growth rate during the late springprior to maturation, it did not identify individual growth curves until June, nor could therelative position of the jacks within the normally distributed weight frequency distributionprior to the bimodality be determined.A growth pattern similar to that described in Chapter 1.1 for chinook salmon jackshas been observed in a number of salmonid species (see Chapter 1.1), the bulk of the workhaving been done on precocious male Atlantic salmon parr (Chapter 1.1). One difference,however, between maturing parr and the results of Chapter 1.1 is that precocious parrexperience a growth reduction during the summer prior to maturation (Leyzerovich 1973,Rowe & Thorpe 1990a, Foote et al. 1991, Randall et al. 1986, see Chapter 1.1). Berglundet al. (1992) showed that testosterone implants in non-mature Atlantic parr produced apattern of growth very similar to that of the precocious maturing parr, as well as increasedincidence of sexual maturation. Hunt et al. (1982) measured growth, 11-oxotestosterone,and testosterone in a group of adult male Atlantic salmon over the course of their sexualmaturation, and showed that growth increased in the spring prior to maturation (correlatedwith serum testosterone concentration), then decreased through the summer. A number ofexperiments have shown that testosterone enhances growth in salmonids, often with anaccompanying increased rate of sexual maturation (Higgs et al. 1982, Schreck & Fowler1982, Borghetti et al. 1989).9 0Thyroid hormones, triiodo-L-thyronine (T3) and thyroxine (T4), are involved in themediation of growth and metabolism in fish (Higgs et al. 1982). There has also beenextensive work showing maturation-related changes in circulating thyroid hormoneconcentrations in salmonids; Atlantic salmon (Dickhoff et al. 1989, Mayer et al. 1990a,b,Rydevik et al. 1989), sockeye salmon (Biddiscombe & Idler 1983), rainbow trout (Pavlidiset al. 1991), amago salmon (Nagahama et al. 1982), coho salmon (Leatherland &Sonstegard 1981a,b, Sower & Schreck 1982); brook trout (Audet & Claireaux 1992); andpink salmon (Leatherland et al. 1989).Elevated circulating levels of cortisol have been shown to be associated with finalmaturation in salmonids (Morrison et al. 1985, Audet & Claireaux 1992, see Barton &Iwama 1991). High levels of cortisol, often associated with stress, have also been shown todown-regulate testosterone in maturing salmonids (Pickering et al. 1987, Pickering et al.1991, Donaldson 1990, Barton & Iwama 1991). Finally, in coho salmon, injected orimplanted cortisol resulted in reduced plasma T3, but not T4, concentrations (Redding etal. 1984, Vijayan & Leatherland 1989), although there are reports of inconsistent responseof T3 to cortisol during smoltification (Redding et al. 1991). It is likely that circulatingtestosterone, thyroid hormone, and cortisol concentrations may be involved, additively orsynergistically, to influence the growth pattern characteristic of jacking chinook salmon.The study described here was designed to test three main hypotheses:1)jacking chinook salmon experience elevated growth in the spring prior to maturation,relative to the non-mature fish;2) jacking chinook salmon have different circulating T3, testosterone, and cortisolconcentration profiles during the seven months prior to sexual maturation; and3) the circulating hormonal concentrations of jacking chinook salmon correlate with their(elevated) growth rate.91This study described the growth and changes in circulating levels of cortisol, total T3thyroid hormone, and total testosterone of individually tagged non-mature males, females,and jacking chinook salmon from identical familial backgrounds.3.1.2 MATERIALS AND METHODSSampled FishOn December 9 & 10, 1990 and March 17 & 18, 1991, 415 and 425 fish,respectively, were randomly selected from multiple seine sets made in the 10mX10mX10mnetcage at Yellow Island Aquaculture Ltd. (YIAL - Quadra Island, B.C.) that contained theaccelerated family groups described in Chapter 2.1. The sample population consisted of 12full- and half-sib chinook salmon families, all identified by coded wire nose tag implants totheir family of origin (see Chapter 2.1).December Sample: The selected fish were exposed to a lethal dose of 2-phenoxyethanol (2.5 ml•L -1 ) immediately after capture. The fish were weighed (± 0.1 g)and blood was collected in heparinized syringes from the caudal vessel. The blood sampleswere centrifuged and the plasma and packed cells were separated and frozen at -20 °C forapproximately seven days until transferred to a -70 °C freezer where they were held untilanalysis.March Sample: The selected fish were anesthetized with 2-phenoxyethanol (0.15ml•L-1 ) immediately after capture, weighed (± 0.1 g), and blood was collected inheparinized syringes from the caudal vessel. Each fish was also injected intraperitoneallywith a Passive Integrated Transponder (PIT) tag (Canadian Biosonics Ltd., Vancouver,B.C. - see Moore 1992). The PIT tag was read at the time of injection and the 10 digitalpha-numeric code recorded, this allowed the identification of individual fish through-outthe experiment. The blood samples were centrifuged and the plasma and packed cells were9 2separated and frozen at -20 °C for approximately three days until transferred to a -70°Cfreezer where they were held until analysis.The PIT tagged fish were held for the duration of the experiment in a 4mX4mX4mnetcage at YIAL; the characteristics of the grow-out site are described in Chapter 1.1. Thefish were fed to satiation one or two times daily with a commercially available feed (WhiteCrest Mills, Campbell River, B.C.). The fish were orally treated with oxytetracycline, as aprophylactic measure, for approximately 10 days following handling. Mortalities wererecovered on a weekly basis and frozen pending PIT and nose tag recovery.Further SamplingOn April 25, May 26, and June 15, 1991, all surviving PIT tagged fish wereanesthetized, weighed, and blood samples taken (for plasma extraction) following theprotocol of the first sampling. On August 13, 1991, the PIT tagged fish were killed,weighed, their PIT tag read and recorded, and blood samples taken (for plasma extraction -as above). The fish were then dissected to recover nose tags for later decoding. Jacks wereclearly identifiable by their developed testes. Testes were removed and weighed (± 0.1 g)for all jacking fish.All fish were sexed using DNA from the packed blood cells taken during thesampling in December and March with the Y-chromosomal DNA probe for chinooksalmon developed by Devlin et al. (1991). Fish were selected for analysis from the totalsample size based on their sex (male - female), maturation state (jack - non-jack), andfamilial background (family of origin - determined by nose tag recovery). To reduce thepossibility of family effects on the measured parameters, the jack, male (non-mature), andfemale groups of chinook salmon were selected to have identical familial representation(Table 3.1.1). Ideally, a single full-sib family would have been used for the analysis,however families with large numbers of jacks tended to have few non-mature males, andvice-versa, thus no single family had sufficient numbers of jacks and non-mature males.Table 3.1.1: Family composition of the fish used for the analysis of hormonal andgrowth differences between jacks and non-maturing chinook salmon.FEMALE^MALE^JACKS^FEMALES^MALES(J / N) (#'s) (#'s) (#'s)93A total of 20 jacks, 20 non-mature males, and 20 females were selected for theexperimental period, and 16 males and 16 females were chosen at random from theDecember sampling for growth and hormonal analysis.AssaysPlasma concentrations of cortisol, total testosterone, and total T3 were determinedby 1251 radioimmunoassay clinical kits (COAT-A-COUNT, Diagnostic Products Corp.Los Angeles, CA, USA: cat. #s; TKC01, TKTT1, and TKT31). Cross reactivity wasreported low for all of the kits. The clinical assay kits were validated for use with chinooksalmon by evaluation of serially diluted chinook salmon plasma (using zero standard), aswell as chinook salmon plasma serially spiked with known concentrations of the purehormone. The measured values were in close agreement with the known concentrations,with the exception of very high values of cortisol ([cortisol] > 300 ng•m1 -1 ), where themeasured values were approximately 10-15% lower than the known concentrations,probably due to saturation effects. The samples with measured values of plasma cortisolgreater than 300 ng•m1 -1 were corrected for this effect.Statistical AnalysisGonadosomatic index (GSI) was calculated by;GSI -1= Wttestes • (Wttotal) • 100%Where Wttestes was the weight of the testes and Wttotai was the weight of the whole fish(including the testes).Relative growth rate (RGR) was calculated for the time periods between samplingdates for each individual fish;94RGR = (Wtfinal - Wtin itiai) • (Wtinitiai • Days) -1 • 100%9 5Where Wtinitial was the weight of an individual fish at one sampling date, Wtfi nai was theweight of the same fish one sampling date later, and Days was the number of days betweenthe two consecutive sampling dates.Weight-frequency distributions were generated for the sampled fish (jacks, non-mature males, and females combined) for the five sampling dates and tested for bimodalityusing the test for clusters described in Chapter 1.1. A one way ANOVA was used to testfor differences in plasma cortisol, T3, and testosterone concentrations between jacks, non-mature males, and females within sampling dates (hormone concentrations were naturallogarithm transformed). One way ANOVA was also used to test for differences in RGRbetween jacks, non-mature males, and females within sampling dates (RGR was ARCSINV- transformed - Sokal & Rohlf 1981). Correlations between RGR, wet weight, plasmahormone concentrations, and GSI were tested using regression analysis on the transformeddata. All data is presented before transformation.3.1.3 RESULTSThe weight-frequency distribution for the jacks, males and females combined isshown in Fig. 3.1.1. The frequency distribution became significantly bimodal in May, andthe spread increased through the summer (Fig. 3.1.1). Mean wet weights for the non-mature male, female, and jack groups are plotted against time, and mean relative growthrates (RGR) are shown for the three intervals between the weight samples in Figure 3.1.2aand b. The jacks had a significantly higher wet weight from March to August, however thejacks had higher mean RGR during the April - May and the May - June time periods only(Fig. 3.1.2a & b). Generally, RGR decreased into June, then increased through summer.The significantly higher RGR of the jack group is due mostly to a reduction in growth ofthe non-mature fish, rather than an increased jack growth rate,it114.41 /4Pt. 1 00114.1210a0.420 r MAPR. 1 00114121000.4.aO9614121 0a0.4a0141210a0.42OMAY 1 001JUNE 1001AIJOI. 1 001141210100 200 300 400 000 000WEIGHT (g)Figure 3.1.1: Weight-frequency distributions for the combined male, female and jackchinook salmon in salt water used for the hormonal analyses. The total number offish at all sampling periods was 60. The shaded bars represents fish that eventuallyjacked. The distribution became significantly bimodal in May: * = P < 0.05; **=P < 0.01; *** = P < 0.001.a0.42O97- 0 - FEMALES - 0 - MALES^- • - JACKSa500 -400300^-_ -200 ■••AN,or.1000 ^DEC MAR APR MAY JUNE^AUGFEMALES MALES JACKS0.800.700.600.500.400.300.200.10MAR-APR APR-MAY MAY-JUNE^JUNE-AUGFigure 3.1.2: a) Mean wet weight (± SE) of the female, male and jack chinook salmongroups in salt water used for the hormonal analysis (N=20). The jack group wassignificantly heavier from March to August. b) Mean relative growth (± SE) of thethree groups of fish used for the hormonal analyses (N=20). *** = P < 0.001.9 8nevertheless the development of the bimodal distribution in May - June is explained by thegrowth differences.Cortisol: Mean plasma cortisol concentration is presented for the male, female, andjack groups in Fig. 3.1.3a. Although there was a general rise in the mean valuesthroughout the sample period, no differences were found between the three groups withinsampling dates. The mean plasma cortisol concentrations for all groups were extremelyhigh, ranging from approximately 85 to 220 ng . m1-1 .Testosterone: Mean plasma testosterone is presented for the male, female and jackgroups in Fig. 3.1.3b. The non-mature male and female groups mean values were notsignificantly different from zero, however the jack group mean values were significantlygreater than either of the non-mature group means throughout the duration of theexperiment (Fig. 3.1.3b). The jack group mean plasma testosterone concentration remainedrelatively low from March to May, then increased dramatically in June and August (Fig.3. 1 . 3b) .T3: Mean plasma T3 concentration is presented for the male, female, and jackgroups in Fig. 3.1.3c. The male and female group mean values were not significantlydifferent from each other throughout the sampling experiment, however jack group meanwas significantly higher than the non-mature group means in March only (Fig. 3.1.3c).The jack group mean plasma T3 was not different from the non-mature groups means fromApril to the end of the experiment (Fig. 3.1.3c).Individual plasma cortisol and testosterone concentrations were not correlated withrelative growth rates within the jack group at any time during the experiment. Thesignificant correlation of jack plasma T3 concentration in March with the May-Junerelative growth rates is shown in Fig. 3.1.4a. No other combination of jack hormoneconcentration and relative growth yielded a significant correlation. The August plasmatestosterone concentrations were found to be highly correlated with the GSI of the jacks(Fig. 3.1.4b), however,250200150100500IN.99a- o.0..^MALESO FEMALES■0.—^JACKSDEC^MAR APR MAY JUNE^AUG b ••403020100Tie•• i11-------- :op^0, t  8 ^ S- •DEC^MAR APR MAY JUNE^AUG•12 - C1086420DEC^MAR APR MAY JUNE^AUGFigure 3.1.3: Mean plasma concentrations (± SE) of; a) cortisol, b) T3, and c)testosterone for the male, female, and jack chinook salmon groups in salt water.The December data are from 16 randomly selected fish, while the other data arefrom 20 fish sampled over the whole period. ** = P < 0.01; *** = P < 0.001.•y■0.097 - 0.013x r - 0.54^n- 20•• •• •••0.15• •b0.300.25C/3CD0.20CD0100y - 0.11 +0.0.88x r - 0.86^n - 20• •• •• ••0.10•••a0.85 - •>-cc0.75Cr •0.65ci20.55CC0.451.00^1.50^2.00^2.50^3.00^0.00^0.50^1.00^1.50^2.00^2.50LOG (pi) MOH LOG ([TEST]) AUGd6.00y - 5.35 - 0.85x r - 0.44 n - 208.00 - y 5.73 - 0.24x r - 0.40 n - 18•• • •LU 5.50 • • • • • •• •• •EC 5.50 •cc5.00 • • •0c-) 4.50 • •C.,5.00•-J 4.00 • •3.50 4.500.00^0.20^0.40^0.60^0.80^1.00^1.20^0.00^0.50^1.00^1.50^2.00^2.50LOG (REST]) JUNE LOG (REST]) AUGFigure 3.1.4: Correlations between transformed hormonal values, growth, and GSI for theindividual jacking chinook salmon: a) correlation between the March plasma T3concentrations for individual jack chinook salmon in salt water and relative growth(RGR); b) correlation between the August plasma testosterone concentrations forindividual jack chinook salmon and gonadosomatic index (GSI); c) correlationbetween the June plasma testosterone (TEST) and cortisol (CORT) concentrations inthe jacks; d) correlation between the August plasma testosterone concentrations inthe jacks and the cortisol. All regression equations are given, and all slopes weresignificantly different from zero.101no correlation was found between jack plasma testosterone concentration and GSI for anyother sample date. A significant negative correlation between jack plasma cortisol andtestosterone concentrations was found for June and August sampling dates (Fig. 3.1.4c,d).All of the hormonal observations presented here are single data points within adynamic system. Seasonal and diel fluctuations for all three hormones have beendocumented (Barton & Iwama 1991, Audet & Claireaux 1992, Baynes & Scott 1985).Furthermore, plasma concentrations do not reflect differences in clearance rates orproduction levels, and may thus be misleading.3.1.4 DISCUSSIONThe PIT tagged fish in this experiment generated a bimodal weight-frequencydistribution very similar to those reported in Chapter 1.1. However, since the fish wereindividually identified (PIT tags), the jacks, males (non-maturing) and females wereindividually identifiable from March through August. As is the case for precociouslymaturing male fish from other species of salmonids (Randall et al. 1986, Foote et al. 1991,see Chapter 1.1), the jacks were the largest fish before any bimodality could be identified(Fig. 3.1.2a). Although the growth of the jacks was higher than either the males or femalesfrom March to June, this was not due to an increase in the growth of the jacks, but rather adecrease in growth of the non-mature fish (Fig. 3.1.2a,b). Unlike the growth described forprecociously maturing parr, the growth of the jacks did not decrease during the summer,although the growth of the non-mature fish increased dramatically. The results of this worksupport the findings described in Chapter 1.1; the general pattern of the growth of chinookjacks during the nine months prior to sexual maturation is similar to that reported for otherprecociously maturing salmonids except for the maintained fast growth through the summer(see Chapter 1.1).The rapid increase in circulating testosterone observed in the jacks during thesummer months prior to maturation (Fig. 3.1.3b) is also typical of maturing salmonids102(Hunt et al. 1982, Baynes & Scott 1985, Scott & Sumpter 1989, Mayer et al. 1990b,Mayer et al. 1992). The slightly elevated levels of testosterone in the jacks from March toMay, forming a small peak, is similar to those reported by Hunt et al. (1982), Schultz(1984), and Mayer et al. (1990b) in maturing male salmonids, and has been tentativelyidentified as a possible trigger for the initiation of testicular development (Hunt et al.1982). Although the testosterone levels of the jacks were already elevated relative to thenon-mature fish in March, there was no evidence of higher testosterone levels in any of themale fish assayed in December. Based on the known jacking rate (Chapter 1.1), six orseven of the male fish sampled in December would have been expected to be jacks, yetthere was no dichotomy of testosterone levels in the male fish (most were below the levelof detection). Thus the circulating levels of testosterone in the jacks probably began toincrease between December and March.The drop in jack circulating T3 level in April (Fig. 3.1.3c) coincided with thedevelopment of the bimodality in the weight-frequency distribution. T3 has been shown tostimulate growth when fed to salmonids (see Higgs et al. 1982). It is thus surprising thatcirculating T3 levels dropped in the jacking fish just prior to the development of thebimodality. A considerable body of work has shown that T3 drops during final maturation,however the drop is usually closely associated with spawning (Biddiscombe & Idler 1983;Pavlidis et al. 1991; Audet & Claireaux 1992; Leatherland et al. 1989), although Rydeviket al. (1989) reported elevated circulating T3 levels through the breeding season inprecocious male Atlantic salmon parr. Audet & Claireaux (1992) found a T3 peak in thespring prior to the maturation of brook trout, and Dickhoff et al. (1989) also reported a T3peak in the spring prior to maturation in adult Atlantic salmon. The elevated T3 levels inthe jacks in March could be interpreted as a peak if the T3 of the jacks in December waslow relative to the March value. Although it is not possible to positively identify thepotential jacking fish in the December sample, Figure 3.1.5 shows log (weight) plottedagainst log (T3) for the 16 male fish measured in December. Approximately 6 - 8 of2.502.00POTENTIAL"NON-JACKS"1.50 •1.00••••POTENTIAL"JACKS"• ••1034.10^4.30^4.50^4.70^4.90^5.10LOG (WEIGHT) DECFigure 3.1.5: Transformed December wet weight plotted against December plasma T3concentrations for 15 male chinook salmon. The points within the circle may bemale fish that eventually become jacks, while the points outside the circle may benon-maturing males (see text). The purpose of this figure is to identify any possibledifference in T3 levels between the jacks and non-mature males in December.104these 16 randomly selected fish are expected to be jacks based on observed jacking rates(app. 40%; see Chapter 2.1). Two groups of fish can be identified in Fig. 3.1.5; high T3 -high weight, and low T3 - low weight, these two groups fit the expected numbers of fish inthe jack and non-jack categories. It is possible that the high T3 - high weight group may bejacks, if this were the case these "jacks" would have a mean T3 value in December of 9.0ng•m1-1 . Thus the March circulating T3 levels in the jacks represent a peak, independent ofwhether the two groups seen in Fig. 3.1.5 correspond to jacking and non-maturing fish.Although the elevated T3 levels of the maturing males in March may constitute the spring"peak" reported elsewhere, the subsequent drop in circulating T3 has not, to ourknowledge, been reported elsewhere for maturing male salmonids.There was no difference between the jack and non-maturing fish circulating levelsof cortisol throughout the course of the experiment. Although a rise in cortisol has beenreported in maturing salmonids (Morrison et al. 1985, Audet & Claireaux 1992, see Barton& Iwama 1991), circulating cortisol increased in all fish in this study. It is thus unlikelythat the rise in cortisol through the spring and summer is related to sexual maturation. Theactual plasma cortisol concentrations reported here are extremely high (10-20 X reportedresting values) compared to published values for salmonids (see Barton & Iwama 1991);however, most of the reported cortisol concentrations are from juvenile freshwater fish,and may not be comparable to the values reported here. Morrison et al. (1985) measuredcirculating cortisol levels in sexually mature adult coho salmon and reported valuescomparable to those presented here. It is unlikely that the circulating cortisol levels in ourstudy represent a stress response, since the values were so high as to normally represent asevere acute stress response, at least in rainbow trout and juvenile salmon (Barton &Iwama 1991). It is unlikely that such a stress response could be maintained for eightmonths. It is unclear what the function is of these high levels of circulating cortisol,although it may be that resting values are naturally high in adult Pacific salmon.105Although a number of the characteristics of the hormone profiles shown in Fig.3.1.3 coincide with the development of the bimodal weight-frequency distribution, thecritical test was to correlate individual hormonal measurements with growth rates withinthe jacking group, as well as within the data set as a whole. The only variable thatcorrelated with growth was T3 concentration in the jacks in March, showing a negativerelationship with growth (Fig. 3.1.4a), that is, the jacks with the highest T3 concentrationin March were generally the slowest growing from May to June. This agrees with theobservation that circulating T3 levels in jacks decreased during the development of thebimodal weight-frequency distribution. It would seem that, in this experiment, elevatedcirculating T3 concentrations did not stimulate somatic growth in a dose dependent fashion,as has been reported elsewhere for juvenile fish (see Higgs et al. 1982). The significantnegative correlations between circulating levels of cortisol and testosterone in June andAugust, agrees with other work in non-mature salmonids (Pickering et al. 1987, see Barton& Iwama 1991). Cortisol has also been shown to reduce levels of circulating T3 inimmature and smolting salmonids (Redding et al. 1984; Vijayan & Leatherland 1989),possibly through a reduction of the T4 - T3 conversion or an increase in T3 clearance rates(Redding et al. 1984). In our study there was no correlation between measured levels ofcortisol and T3 within the jack group, or within the data set as a whole. Finally thesignificant correlation between the circulating levels of testosterone and GSI seen in Augustindicates that; 1) the rate of gonad development was dependent on the level of testosterone,or 2) the rate of testosterone production was dependent on the size of the gonad. In eithercase, since the jacks were not expressing milt at the time of the August sample, their testeswere not fully developed.Three hypotheses were tested in this study; 1) jacking chinook salmon experienceelevated growth, relative to the non-maturing fish, during the spring prior to maturationand this leads to the observed bimodality in the weight-frequency distribution, 2) jackingchinook salmon have characteristic circulating levels of T3, testosterone, and cortisol106during the 7 months prior to maturation, and 3) the circulating T3, testosterone, and/orcortisol levels correlate with the (elevated) growth of the jacks. The first two hypotheseswere consistent with the data (although there was no difference in the cortisol levelsbetween the jacks and non-jacks); however, no clear correlate with the elevated growth ofthe jacks was identified. The observed differences in circulating T3 is probably notstimulating the growth of the jacks, since it decreased during the period of elevatedgrowth, and was found to be negatively correlated with individual growth rates. Althoughcirculating testosterone was slightly elevated at the time of divergent growth, and indeedthis spring "peak" has been proposed as a potential factor in the growth of precociousAtlantic salmon parr (Hunt et al. 1982, Schultz 1984, Mayer et al. 1990b), testosteronedid not correlate with individual growth rates within the jacking group or the whole dataset. It is possible, but unlikely, that the elevated testosterone levels in the jacks wasstimulating growth but was not acting in a dose dependent manner (see Higgs et al. 1982).It is also possible that another circulating hormone may be more directly stimulating thegrowth of the jacks, relative to the non-maturing fish, and one potential candidate issomatotropin. Somatotropin has been shown to be positively correlated with cortisol(Pickering et al. 1991), thus the increased levels of circulating cortisol in the fish throughthe spring and summer would not be unexpected. Somatotropin has been shown tostimulate the release of testosterone (see Planas et al. 1992), and may also explain theslightly elevated circulating testosterone levels in the spring observed in this study andothers. Somatotropin can increase circulating levels of T3 and T4 (see Leatherland &Farbridge 1992), thus we would expect circulating T3 levels to increase with growth,however this was not the case. Most of the work that has been done with somatotropin insalmonids has been done on immature juvenile salmonids, and hence our discussion of itspossible role in the precocious maturation of adult chinook salmon is highly speculative,and represents only one possibility.1073.2 PHYSIOLOGICAL CORRELATES WITH THE INCIDENCE OF JACKING INCHINOOK SALMON3.2.1 INTRODUCTIONThere are a variety of physiological variables that have been shown to correlatewith age of maturity in salmonids. Although there has been some work published onphysiological correlates with precocious sexual maturation in Pacific salmon, Atlanticsalmon parr have been particularly well studied. This may be due to the relative ease ofrearing these fish to maturity (less than 2 years in freshwater). Precocious sexually maturemale rainbow trout, coho, Atlantic, and chinook salmon parr and Atlantic salmon grilsehave been shown to be the largest and/or fastest growing individuals in the population(Foote et al. 1991, Lamont 1990, Hagar & Noble 1976, Saunders et al. 1982, Berglund1992, Randall et al. 1986, Thorpe et al. 1990, Herbinger & Newkirk 1990, Thorpe 1991,see Appendix B). Although Bilton's (1980, 1984) work with coho and chinook salmonindicated that pre-smolt growth (or size at age) correlated with jacking rates, much of thework on Atlantic salmon indicates that the critical time period for growth and/or size, isduring the winter or spring preceding maturation (see Thorpe 1991).Recently there has been work published indicating that fat stores may be morecritical to sexual maturation of Atlantic salmon parr than is total weight or growth duringthe spring prior to maturation (Herbinger & Friars 1992, Rowe et al. 1991, Simpson1992). A correlation between condition factor and incidence of precocious maturation inchinook and Atlantic salmon parr has been interpreted as potentially a minimum energy"threshold" necessary for maturation (Rowe & Thorpe 1990a, Leyzerovich 1973, Dailey etal. 1983, Herbinger & Newkirk 1990, Foote et al. 1991). A correlation between fat storesand condition factor for individual Atlantic salmon parr has been demonstrated, explaininga possible mechanism for the correlation between condition factor and sexual maturation(Herbinger & Friars 1992, Simpson 1992).108There has been work done that showed that non-genetic maternal effects could havean effect on the incidence of precocious maturation salmon parr (Silverstein & Hershberger1992, see Chapter 2.1). Bradford & Peterman (1987) pointed out that reported correlationsbetween age of maturation in dam and offspring could be due to non-genetic maternaleffects, specifically differences in early growth due to egg size.The environmental stress response in salmonids has been shown to interfere withsexual maturation and reproduction (Donaldson 1990; Pickering 1989; Wedemeyer et al.1984).The analyses described here was designed to test some of the hypothesizedcorrelates with precocious sexual maturation in chinook salmon using the 24 chinooksalmon family groups in the breeding experiment described in Chapter 2.1. A total of 25variables were measured for the 24 family groups (accelerated and non-accelerated - seeChapter 2.1). The variables included measurements of parental characteristics as well asmeasurements of physiological parameters of the family groups themselves from the frystage to sexually mature adults (two years post fertilization). The variables were classifiedas;1) parental characteristics (4 variables),2) growth and size at age parameters (10 variables),3) stress response (7 variables), and4) survival/mortality (4 variables).Table 3.2.1 gives a list of the specific variables measured in each category.3.2.2 MATERIALS AND METHODSThe parental characteristics were measured at spawning and included; total weights(± 10 g), individual egg weights (average of 100 eggs), and total egg weights (from whichfemale GSI was calculated as described in Chapter 3.1).VARIABLEDESCRIPTION^(ABRV.)DAM WEIGHT (DAMWT)SIRE WEIGHT^(SIRWT)GONADOSOMATICINDEX (GSI)EGG WEIGHT^(EGGWT)UNITSgggVARIABLECATEGORYPARENTALCHARACTERISTCSGROWTH & SIZE^INITIAL ALEVINAT AGE^ WEIGHTFINAL ALEVIN WTALEVIN GROWTHFRY WTFRY GROWTHFRY CONDITIONFACTORDECEMBER WTJACK FINAL WTNON-JACK FINAL WTJACK/NON-JACKDIFFERENTIAL WT(ALVWT1)(ALVWT2)(ALVGRO)(FRYWT2)(FRYGRO)(FRYCF)(DECWT)(JKWT)(NJKWT)(DIFF)gg%'day- 'g%'day-'g'cm-3ggggTable 3.2.1: A list of the 25 variables within the four categories that were used in thecorrelation analysis. Each of the variables are means or ratios (percent) for the24 full- and half-sib families used for the analysis of the genetic component tojacking.STRESSRESPONSECONTROL HEMATOCRITSTRESSED HEMATOCRITCONTROL CORTISOLCONCENTRATIONSTRESSED CORTISOLCONC.CONTROL GLUCOSECONC.STRESSED GLUCOSECONC.DECEMBER CONTROLCORTISOL CONC.(HEMCON)(HEMSTR)(CORTCON)^ng'm1-1(CORTSTR)^ng'm1-1(GLUCON)^mg'd1-1(GLUSTR)^mg'd1-1(DECCORT)^ng'm1-1SURVIVAL/^EYED EGG SURVIVAL (EGGSURV)MORTALITY DECEMBER SURVIVAL (DECSURV)FINAL SURVIVAL^(FINSURV)VIBRIO MORTALITY^(VIBMORT)109110The fry and alevin growth and wet weight measurements were made before thefamily groups were pooled in May 1990, and included the measurements made during thestress response experiments (see Appendix A). The fry condition factor was based onmeasurements of weight and length taken during the freshwater growth period (Heath et al.1992 - Appendix A), and was calculated as the wet weight divided by the total lengthcubed (X 100%). Since the identification of family of origin required the recovery anddecoding of nose tags after the family groups had been pooled, the December, 1990 andfinal sample (September, 1991) jack and non-jack mean family weights were made on fishthat had been killed (see Chapter 2.1). The mean weight estimates of the jacks and non-jacks at the final sample was based on a random sample of the non-jacks, and all of therecovered jacks. All relative growth rates (RGR) were calculated as described in Chapter3.1.The data on the stress response of the fry family groups were taken from the stressresponse study (Heath et al. 1992 - see Appendix A), while the December plasma cortisolconcentrations were determined from the plasma samples taken during the Decembersampling (see Chapter 2.1). The stress related parameters were taken following standardpractices for the measurement of hematocrit and plasma concentrations of glucose andcortisol (Heath et al. 1992 - Appendix A).The eyed egg to hatch survivals were based on twice-weekly dead egg removal andcounting (see Chapter 2.1). The vibrio mortality (vibriosis was identified as the pathogenbased on gross clinical signs) estimates were based on the numbers of mortalities recoveredby SCUBA diving during the August, 1990, vibrio outbreak (accelerated) and the October,1990, vibrio outbreak (non-accelerated) as described in Chapter 2.1. The inventory ofsurviving fish in each family group for December, 1990, was calculated by multiplying theproportion of each family group taken in a random sample (app. 420 fish from theaccelerated and non-accelerated groups - see Chapter 2.1) by the total number of fish in thenetcages. The estimate of fish alive in December was divided by the original number of111fish tagged in each family (500 fish) to give percent survival. The final survival rate wascalculated as above except that the number of surviving fish in each family group wascounted, rather than calculated.Tables 3.2.2a & b give the mean values for all variables as well as jacking rate (i.e.specific jacking rate (SJR) as defined in Chapter 2.1) for all families, the abbreviations areas defined in Table 3.2.1.AnalysisThe analysis was designed to test the 25 variables for correlation with the observedjacking rates for the 24 family groups reared in the breeding experiment. All variablesexpressed as percents were ARCSIN -V - transformed, while all other variables were naturallogarithm transformed for analysis.The four categories of variables were initially screened for correlation with SJR rateusing a stepwise multiple regression routine (SYSTAT, Evanston, IL, USA). The generalform of the model was;SJR = {CONSTANT + D + S + E} + VAR1 + VAR2 + ... + VAR nWhere SJR was the (transformed) specific jacking rate for each family; D, S, and E werecategorical (non-transformed) variables for dam, sire (jack or non-jack) and environment(accelerated or non-accelerated) respectively, and VAR1 to VARn were the (transformed)variables in the category being examined. The categorical variables (D, S, & E) wereincluded to account for genetic and environmental differences between the family groups.The stepwise multiple regression routine tested the inclusion of each variable for asignificant increase in the explained variance (over that explained by the sire, dam andenvironment variables); only variables that contributed significantly to the final model wereretained. It is important to note that the stepwise multiple regressionTable 3.2.2a: A list of the family values for the 25 variables used for the correlation analysis. Data shown are for the acceleratedgroups only. See Table 3.2.1 for meaning of abbreviations.VARIABLE FAMILY13 1N 2J 2N 3J 3N 4J 4N 5J^5N 6J 6NSJR 23.6 6.1 35.7 24.3 52.1 50 10.7 7 80.6^54.9 98.8 15.3FRYCF 1.125 1.16 1.122 1.16 - 1.056 1.082 1.067 1.091 1.102 1.102 1.097EGGSURV 16 4.1 9.1 6.4 41.4 18.2 1.1 1.1 0.8^4.9 1.9 1.9FINSURV 14.4 12 20 20 8 5 25.6 10.6 40^29 9.4 14.6DECSURV 99 57 93 81 73 75 61 49 36^63 47 45VIBMORT 7.5 10.2 4.9 9.8 7.2 9.6 5.1 12.6 5.6^7.6 8.3 11.3DECWT 120.4 106 116.7 114.2 120.4 137.2 117 115 138.8 147.1 114.3 127.1NJKWT 879 711 834 959 787 1023 1033 831 1026^1143 815 973JKWT 1251 1250 1254 1379 1512 1677 1469 1605 1621^1919 1328 1498DIFF 372 539 420 420 725 654 436 774 595^776 513 525DAMWT 4.7 4.7 5.2 5.2 4.1 4.1 5.2 5.2 4.2^4.2 4.6 4.6SIRWT 1.0 4.65 1.42 7.22 1.5 6.7 1.5 5.95 1.6^7.2 1.8 5.8EGGWT 0.234 0.234 0.225 0.227 0.159 0.162 0.207 0.208 0.236 0.237 0.203 0.208GSI 26 26 33 33 24 24 31 31 26^26 30 30FRYWT2 7.6 7.1 6.4 7.5 - 8.1 8.4 7.1 7.5^9 6.2 6.4FRYGRO 3.4 3.2 2.6 3.1 - 3.7 2.9 3.2 2.6^2.9 3.1 2.8HEMCON 44.8 51.3 49.8 52.8 - 48.1 45.2 45.6 42.4^43.1 44.3 46.4HEMSTR 50.2 52.2 49.2 50.2 - 48.8 45.3 45.3 46.1^47.8 49.1 53.8CORTCON 31.2 67.6 89.8 53.3 - 24.0 77.0 87.0 61.0^59.0 74.0 29.0CORTSTR 174 150 240 146 - 161 150 215 168^124 156 202GLUCON 85.7 80 84.2 96.8 - 77.1 85.2 89.1 73.3^72.6 63.6 86.6GLUSTR 104.3 91.8 106.2 97 - 104.3 102.9 99 65.6^78.5 95.4 108.8DECCORT 59.2 85.2 204 126 103 152 138 59 164^116 127 196ALVWT1 0.73 0.81 0.67 0.65 0.56 0.47 0.74 0.72 0.77^0.9 0.65 0.65ALVWT2 2.66 2.52 2.43 2.83 2.7 2.42 3.86 2.72 3.5^3.69 2.39 2.69ALVGRO 1.649 1.542 1.641 1.752 1.801 1.831 1.837 1.671 1.772^1.718 1.654 1.723Table 3.2.2b: A list of the family values for the 25 variables used in the correlation analysis. Data shown are for non-acceleratedgroups only. See Table 3.2.1 for the meaning of the abbreviations.VARIABLES FAMILY1J 1N 2J 2N 3J 3N 4J 4N 5J 5N 6J 6NSJR 21.4 10.8 31.4 28.6 43.2 11.4 3 9.6 74.9 47.8 39.8 9.5FRYCF 1.15 1.17 - 1.15 1.10 1.06 1.13 1.09 1.10 1.13 1.11 1.08EGGSURV 1.8 7.4 10.7 4.3 33.3 23.5 2.9 4.9 1.2 1.7 3.5 0.7FINSURV 33 15.4 29 19 19 10 26 18 58 29 11 29DECSURV 80 72 64 87 39 45 91 72 85 45 47 33VIBMORT 7.1 14.4 6.2 7.6 7.9 8.2 4.4 16.2 2.9 5.9 11.8 7.4DECWT 91.3 83.8 106.1 98.3 101.9 111.3 95.4 94.5 94.4 114.2 89.4 102.8NJKWT 650 615 696 594 732 763 750 725 947 764 673 758JKWT 1061 991 1117 1333 1263 1150 1093 1160 1474 1349 1095 1113DIFF 411 376 421 739 531 387 343 435 527 585 422 355DAMWT 4.7 4.7 5.2 5.2 4.1 4.1 5.2 5.2 4.2 4.2 4.6 4.6SIRWT 1.0 4.65 1.42 7.22 1.5 6.7 1.5 5.95 1.6 7.2 1.8 5.8EGGWT 0.223 0.263 0.235 0.224 0.162 0.161 0.213 0.208 0.205 0.21 0.238 0.236GSI 26 26 33 33 24 24 31 31 26 26 30 30FRYWT2 5.2 5.3 - 5.3 5.8 5.6 5.3 5.3 5.7 6 4.2 4.4FRYGRO 3.6 3.8 - 4 3.5 4.4 3.1 3.7 2.6 3.5 3.4 3.8HEMCON 47.1 45.7 - 47 41.9 50.1 42.5 42.8 42.8 44.2 47.3 50.2HEMSTR 52.8 44.3 - 44.1 43.1 50.2 37 39.7 45.3 42.2 48.1 44.5CORTCON 21 67 - 87 21 73 0.2 42 37 21 110 100CORTSTR 117 168 - 148 130 114 144 211 178 101 151 172GLUCON 86.7 84.4 - 95.5 85.3 104.4 71.5 97.9 74.9 76.2 72.3 95.1GLUSTR 141.9 120.1 - 112.8 102.2 143.2 65.7 112.1 86.2 109.8 88.1 105.1DECCORT 33 17.6 46 29.4 140 60.9 32.4 44.2 28.8 61.9 58.7 116ALVWT1 0.35 0.36 0.35 0.35 0.26 0.25 0.3 0.32 0.38 0.39 0.31 0.3ALVWT2 1.51 1.36 1.66 1.37 1.33 1.28 1.52 1.55 1.63 1.76 1.31 1.29ALVGRO 1.74 1.67 1.79 1.69 1.82 1.82 1.82 1.80 1.74 1.77 1.73 1.74routine is extremely prone to Type I errors (rejecting a true null hypothesis), especiallywith a large set of independent variables, and thus the routine is useful only to identifypotential correlates, not as a method of generating predictive relations.Linear regression analysis (SYSTAT Evanston, IL, USA) was performed on thevariables identified by the stepwise multiple regression analysis as significant, to test forindividual correlations with SJR.3.2.3 RESULTSStepwise analysisParental characteristics: The final multivariate linear model for the parentalcharacteristic category was;SJR = {CONSTANT + (S) + (E)} - 4.28(DAMWT) + 7.82(GSI)Thus variables that were retained in the model by the stepwise routine were dam weightand dam GSI. Note that the CONSTANT, S, AND E terms are as described above.Growth and size at age parameters: The final model found for the growth andweight variables was;SJR = {CONSTANT + (S) + (D)} + 0.467(DIFF)The only variable retained in the stepwise routine was the differential jack-nonjack finalweight. No significant model resulted from only growth rate variables included in themodel.Stress response parameters: The final model found for the stress related variables114was;115SJR = {CONSTANT + (D)} + 0.087(CORTCON) - 1.55(GLUCON) - 3.99(HEMCON)Three variables were retained by the stepwise routine; control fry cortisol concentration,control fry glucose concentration, and fry control hematocrit. None of the post-stressresponse variables were retained in the model.Survival/mortality parameters: The final model found using the survival/mortalityvariables was;SJR = {CONSTANT + (D) + (S)} -1.07(FINSURV)The only variable retained by the stepwise routine was final survival.Linear regression Linear regressions were performed on all the variables identified as potentialpredictors in the stepwise routine; only DIFF, dam weight, and control fry glucoseconcentration were found to be significantly correlated with SJR. These regressions areshown in Fig. 3.2.1a & b, and Fig. 3.2.2a. Figure 3.2.2b shows the significant linearregression between control fry glucose concentration and fry relative growth (FRYGRO).3.2.4 DISCUSSIONNon-genetic maternal effects on growth and size at age have been reported inchinook salmon up to the smolt stage (Withler et al. 1987). Silverstein & Hershberger(1992) showed that wet weight at three (but not five) months post-hatch in coho salmon frywas correlated with egg size, and they also found a significant, but weak, correlationbetween egg size and incidence of precocious maturation in parr. Similarly, Bradford &Peterman (1987) hypothesized that the observed correlation between age of maturation offemale parents and offspring in Pacific salmon may be due to non-genetic maternal effects(egg size differences). However, no significant116y - -2.38 + 0.48xr = 0.39••••••1.80 a1.501.200.900.60 • i0.30 • •• ••0.00• •••5.70 5.95^6.20 6.45^6.700.00 ^1.40LOG (DIFF)y = 3.13 - 1.65xr = 0.50••$•• ••1.50^1.60^1.70 1.801.501.200.900.600.30b_ •I•LOG (DAMWT)Figure 3.2.1: Results of the correlation analyses for family means of physiologicalvariables versus family specific jacking rates (SJR): a) transformed difference inwet weight between the jacks and non-mature fish at the final sample (DIFF)plotted against the transformed family jacking rates (SJR); and b) transformed wetweight of the dam for each family (DAMWT) plotted against transformed familyjacking rates (SJR). Regression equations are given for both relations, all slopeswere significantly different from zero.1.200.900.600.300.004.00••5.004.504.25 4.75117^1.80^ y - 8.37 - 1.76xa r = 0.67^1.50^•LOG (GLUCON)0.22 b^y - -0.069 + 0.057xr - 0.53^ •0.210.20• ••0.19^ •^o.•0.18 •• •^ •0.17^ • • •0.16• •^•0.154.10^4.20^4.30^4.40^4.50^4.60^4.70LOG (GLUCON)Figure 3.2.2: Results of the correlation analyses for mean family plasma glucoseconcentrations against growth and jacking rates: a) transformed control (non-stressed) plasma glucose concentration in chinook salmon fry (GLUCON) plottedagainst transformed family jacking rates (SJR); and b) transformed control (non-stressed) plasma glucose concentration (GLUCON) plotted against transformedrelative growth (FRYGRO) for chinook salmon fry. Regression equations are givenfor both relations, all slopes were significantly different from zero.•118correlation between egg size and jacking rates was found in this study, although asignificant negative correlation between dam wet weight and jacking rates was observed(thus the larger females produced, on the average, fewer jacks). Since there was nocorrelation between egg size and jacking rates, it is not clear how dam wet weight couldaffect the incidence of jacking. One possibility is that the size of the 3-year-old femaleparents was negatively correlated with the presence of "jacking genes". That is, the smallerfemales have genetic jacking tendencies that could not be expressed phenotypically sinceonly males jack (see Chapter 1.1). Alternately, since the full-sib families used for thisanalysis were the progeny of only six females, the sample size of the regression analysismay be inflated and thus the significance of the regression is potentially suspect. However,the four full-sib families from each dam had different sires and different environmentalconditions thus they are, at worst, pseudo-replicates.It is widely believed that freshwater growth rate and/or size at release has aprofound effect on jacking rate, and this is supported by evidence that shows that the returnrate of jacks increases with growth acceleration in coho and chinook salmon (Bilton 1980,1984). Recently published escapement statistics for the Stamp River system (RobertsonCreek Hatchery, Vancouver Island, British Columbia) show that the incidence of 2-year-old returning male chinook salmon (jacks) in the hatchery-reared (i.e. accelerated growth)fish was more than twice that of the river-reared fish (9.1% vs. 3.4% - Bocking & Nass1992). Lamont (1990) also showed that size at age was critical in determining sexualmaturation in male rainbow trout and coho salmon parr. There is extensive evidence thatgrowth rate or size at age plays an important role in the precocious sexual maturation ofAtlantic salmon parr (see Chapter 1.1, & 2.1). Thorpe (1986) described a growth ratethreshold model and hypothesized that early sexual maturation was determined, in part, byenergy reserves during a critical time "window". Support for such a model came fromwork that showed ration limitation during the spring prior to maturation could significantlyreduce the incidence of precocious parr and grilsing in Atlantic salmon (Rowe & Thorpe1191990b; Thorpe et al. 1990). Some correlation of fry growth and/or size at age with jackingrates was expected, however, none of the freshwater growth or size at age variables weresignificantly correlated with jacking rate, despite a large range in observed jacking ratesand the growth/size related variables (see Table 3.2.2a & b). This does not agree withresults published by Bilton (1980, 1984), or with conventional belief within the SEP andcommercial hatcheries in British Columbia. There was also no correlation between jackingrates and fry condition factor, however it is not surprising that condition factor would notbe correlated with jacking 15 months before maturation (Berglund 1992). The work thathas associated condition factor with sexual maturation has been almost exclusively withAtlantic salmon precocious parr (Simpson 1992, Herbinger & Newkirk 1990, Dailey et al.1983, Leyzerovich 1973, Rowe & Thorpe 1990a). Unfortunately, length measurementswere not taken during the December or final sampling, thus condition factor differencescloser to maturation could not be tested for correlation with jacking in this experiment.The single size-related variable that did correlate significantly with jacking rateswas the difference in mean weights between the jacks and non-jacks at the final sampling(DIFF). That is, the families that had the greatest separation in weight between jacks andthe non-maturing fish also had the highest jacking rates. This correlation may have little todo with the energy reserve thresholds discussed above, since final jack weight or final non-jack weight should have reflected such an effect better. It is possible that families withhigher jacking rates have, in general, higher androgen levels in the maturing fish, andhence, enhanced jack growth rates prior to maturation (see Chapter 3.1). Further work isnecessary to investigate this correlation.Since freshwater size at age or growth rate is often reported as being involved inprecocious maturation in salmonids (see above), it was theorized that the stress response infry may also be involved, since changes in growth is a tertiary stress response (Heath et al.1992 - see Appendix A). The December plasma cortisol concentrations were included inthe analysis because elevated plasma cortisol may have negative effects on reproductive120processes (Donaldson 1990, Barton & Iwama 1991, see Chapter 3.1). The only stress-related factor that was significantly correlated with jacking rates was control fry glucoseconcentration (GLUCON). Our results indicate that families with low GLUCON tended tohave high jacking rates. Since we know that metabolic rate, growth and circulating glucoselevels are inter-related (Higgs et al. 1992, Umminger 1977, Jobling 1983, Barton 1988),we tested freshwater growth variables for correlation with glucose levels and found asignificant positive correlation of fry relative growth rate with GLUCON. Although thepositive correlation of GLUCON with growth is expected (Heath et al. 1992 - AppendixA), these results imply that full-sib families with high GLUCON have high growth, butalso low jacking rates, in contradiction of previous work and accepted beliefs. Theanomalous correlation of GLUCON with jacking rate represents the only freshwatercorrelate with jacking rate found in this study and since there is clearly some freshwatereffect on jacking rates in Pacific salmon (Bilton 1980, 1984, Bocking & Nass 1992), thecorrelation of GLUCON with jacking rate should be investigated more thoroughly.The results of the correlation analysis presented here should be interpreted withcaution. It should be noted that the correlations described in this report are mostly based onfamily means, and are thus somewhat insensitive to effects on the individual level. Forexample, although our results showed that families with higher freshwater growth or largersize at age do not have a higher incidence of jacking, the individual fast growing or largerfish within the families may indeed have had a higher probability of jacking. The latterhypothesis cannot be tested using our approach (but see Chapter 3.1).Although the relations presented here are statistically significant, even allowing forthe relatively large number of correlations tested (Bonferroni-adjusted probabilities -SYSTAT Evanston, IL, USA), they are correlations only and cannot be interpreted asimplying causation. The results of a correlational analysis such as this has two mainpurposes; 1) to generate predictive models, and 2) to identify potentially productive areasof research. Since the relations presented here are probably not quantitatively applicable to121other stocks under other rearing conditions, they are not useful predictors of jacking ratesin general. On the other hand, our results have identified three previously unreportedcorrelates with jacking, indicating areas of potentially useful future research.122GENERAL DISCUSSIONThe results of the breeding experiment showed that jacking in chinook salmon iscontrolled, to a great extent, by maternal and paternal genetic effects. Although thepossibility of non-genetic maternal or early-rearing tank effects cannot be formallyexcluded, their contributions are probably small (see Chapter 2.1). The magnitude of thegenetic component found for jacking in chinook salmon is greater than most other estimatesfor precocious maturation in salmonids (see Chapter 2.1). Glebe & Saunders (1986)speculated that a simple (single locus) genetic model might explain their observedmaturation rates in an Atlantic salmon breeding program. It is possible that a simplegenetic model might also apply to jacking in chinook salmon. The existence of a stronggenetic effect in jacking supports previous work showing that jacking in Pacific salmonmay be an evolutionary stable state (Gross 1984, 1985). Independent of the theoreticalimplications of a major genetic contribution to jacking, it also indicates that jacking ratesshould respond to selection. Although the use of mono-sex (all female) stocks of chinooksalmon has eliminated the economic impact of jacking in the culture of that species (Hunteret al. 1983), genetically high- and low jacking chinook strains could still be useful inbreeding programs.The analysis of allele frequencies at two minisatellite DNA loci (OTSL1 and Ssal)agreed with the results of the breeding program; the incidence of jacking was found to befamily dependent. Allele frequency analysis does not allow partitioning of the observedfamily (genetic) variation into maternal and paternal effects. Therefore, minisatellite alleleanalysis cannot replace breeding experiments for quantitative traits, but rather may serve asa method to determine whether an extensive breeding program is worthwhile.The manipulation of water temperature to control early development was limited induration, yet had a significant effect on jacking rates in the chinook salmon family groups.It is likely that the much greater difference in early rearing environments experienced bywild versus hatchery-reared salmonids would have a correspondingly larger effect on123jacking rates. Indeed it is possible that the genetic effects could be masked byenvironmental effects at very low rates of development in the early life stages (i.e. coldwater and limited food). One most unexpected result of the correlational analysis was theabsence of significant growth- and size-related correlations with jacking rates. Althoughthere was considerable variation in jacking rates, growth, and size at age among the full-sibfamilies, the fast-growing, (or high mean weight) families experienced no higher jackingrates than the slow-growing (or low mean weight) families. This is at odds with much ofthe published information for other salmonids (see Chapters 1.1, 2.1, 3.2), as well as withthe results of the breeding experiment described here. At least two possible explanationspresent themselves; 1) the between-family growth variation was too small to significantlyaffect jacking rates, and/or 2) the artificially accelerated development was fundamentallydifferent from naturally occurring fast-growth families. Further experiments to test thesetwo possibilities would be conceptually simple, however the resources required to rearlarge numbers of salmon to sexual maturation in sea water are daunting.The presence of a significant genotype-by-environment interaction effect on theincidence of jacking indicates that the accelerated early development did not affect allfamilies in the same manner. The significant interaction was mainly due to two familiesthat responded to the acceleration treatment with a drastic increase in jacking rate (Fig.2.1.6). Inspection of the reaction norms presented in Fig. 2.1.6 indicates that jacking ratesin chinook salmon are clearly not a linear function of early developmental rates.The results of the weight-frequency distribution analyses indicated that chinooksalmon exhibit an unusual growth pattern during the spring and summer prior to sexualmaturation. The jacks experienced high growth relative to the non-maturing fish in Apriland May, with little or no reduction in growth during gonadal development through thesummer (see Chapters 1.1 and 3.1). There is no obvious explanation for this result as itcontradicts published reports on the growth of precociously maturing chinook, coho, andAtlantic salmon parr reared in captivity (see Chapters 1.1 and 3.1). One possible124explanation may be behavioral differences between jacking chinook salmon andprecociously maturing parr. Observations of marked increases in aggressiveness in jackingchinook salmon during gonadal development have been noted (pers. obs.). Metcalfe et al.(1986, 1988, 1989) showed that the development of a bimodal size distribution in smoltingand non-smolting Atlantic salmon parr could be explained by differences in feedingbehavior; similar experiments with chinook salmon jacks might prove valuable.The analysis of hormonal changes associated with the elevated growth of jacksrelative to non-maturing fish showed a number of clear differences that coincided with thedevelopment of a bimodal weight-frequency distribution. However, the more directanalysis of hormonal correlates with growth and size at age on an individual fish basisfailed to identify any potential causative relations. Thus, some other unidentified hormone,or combinations of hormones acting synergistically, stimulated the growth of the jackingfish 5-6 months prior to final maturation. One potential candidate identified for such agrowth stimulation was somatotropin, or growth hormone. The somatotropin hypothesiswould account for some of the changes in hormonal profiles described in Chapter 3.1.Unfortunately the reliable measurement of salmon growth hormone is still possible in onlya few laboratories, and since the assay is in high demand, the measurement of growthhormone was not feasible within this thesis.The minisatellite DNA probes developed for use in salmonids (Chapters 2.2 & 2.3)are potentially important tools for the study of individual, groups, and populations ofsalmon. Although the DNA fingerprint probes could not be used effectively for theestimating relatedness in the analysis of the genetic component of jacking (Chapter 2.2),they are effective in identifying parentage and individual fish. The chinook salmon single-locus minisatellite DNA probe (OTSL1) represents a valuable tool for the study of chinooksalmon at the individual or population level (Burke et al. 1991). However, the methodused to isolate OTSL1 (i.e. "DAMD") is perhaps more significant, since it means that125other probes, specific to a species of interest, can be developed with relatively lowinvestment in time and equipment.The application of OTSL1 and Ssal to the question of genetic involvement injacking of chinook salmon, described in this thesis, is one of very few such studies inanimal populations (Chapter 2.3), although extensive applications of single-locus probeshave been documented in human medicine and forensic science. The comparison ofrelatedness estimates generated by single-locus probes for specific phenotypes within arandom-mated population (Chapter 2.4) is a novel use of DNA fingerprinting technology.The success of this technique in identifying allele distribution differences between jacksand females indicates that it is sensitive enough to be a potentially valuable approach,especially for wild populations where breeding experiments are not feasible. Anotherpossible application of relatedness estimation using single-locus probes is the measurementof inbreeding or genetic diversity. The Nicola River chinook salmon parr were notpreviously suspected of having low genetic diversity, however the analysis in Chapter 2.4shows that this population exhibits low variability at the OTSL1 locus, relative to anotherchinook population. An extensive survey of chinook salmon stocks using single-locusminisatellite DNA probes to estimate relatedness could provide valuable information on thelevel of genetic diversity in chinook salmon stocks. Such information would be of greatbenefit to stock enhancement and preservation efforts.CONCLUSIONSThe key findings of this research on the incidence of jacking in chinook salmonwere;Primary Findings1) There is a strong genetic contribution to jacking.2) The genetic contribution has both sire and dam components.3) There is a positive effect of increased early-rearing development rate on jacking rates.4) There are genotype-by-environment interactions for the incidence of jacking.126Secondary Findings5) Mean family growth and/or size at age do not predict jacking rate.6) Jacking chinook salmon experience an elevated growth rate relative to non-maturing fishin the spring prior to maturation.7) Jacks do not experience reduced growth during gonadal development under cultureconditions.8) Plasma concentrations of testosterone and T3 are elevated in jacks up to eight monthsprior to final maturation.9) Neither testosterone, T3, nor cortisol is positively correlated with the elevated growth ofjacks in the spring.Figure D.1 shows the diagram presented in the General Introduction, with the areasthat have been addressed in this research marked. The physiological triggers of jacking inchinook salmon have received the least attention in this thesis; however, these triggers havebeen extensively investigated, particularly in the Atlantic salmon parr (see Chapters 1.1,3.1, 3.2).Although questions have been addressed and answered by the research constitutingthis thesis, an even greater number of additional questions have been suggested by theresults of this research. A number of possible avenues of research have been proposedthrough-out the text, and other approaches will occur to researchers interested in thephenomenon of jacking in Pacific salmon. Research into the phenomenon of jacking inPacific salmon is valuable, not only for the physiological aspects of precocious maturation,but also as a relatively straightforward example of an alternate male life history strategy inthose species.**GENETIC EFFECTS I PHYSIOLOGICAL TRIGGERS**BODY SIZE- ENERGY STORES- PHOTOPERIODa+ HORMONAL PROCESSI •ENVIRONMENTAL EFFECTSII; GROWTHSIZE** STRESSSS TOLERANCE**DEVELOPMENT RATE127E-1•-102CI)Figure D.1: A schematic diagram of the reported factors hypothesized to affect theincidence of precocious sexual maturation in male salmonids, as described in theGeneral Introduction. The factors investigated in this thesis are identified witharrows. The two factors not dealt with were; energy (or fat) stores 6-9 months priorto maturation, and the effect of photoperiod.Appendix AHeath, D.D., N.J. Bernier, J.W. Heath, and G.K. Iwama. IN PRESS. Genetic,environmental, and interaction effects on growth and stress response of chinooksalmon fry. Can. J. Fish. Aquat. Sci. 00: 000-000.AbstractEight full- and half-sib families of chinook salmon were held during eggdevelopment at two temperatures (8.0 °C and 10.2°C). As fry, these families weremeasured for: relative growth rate, initial and final wet weight, hematocrit values beforeand 2 h after a 30 s handling stress, and plasma cortisol and glucose concentrations beforeand after stress. Significant sire effects were found for all measured traits, and significantdam effects were found for all traits except for the post-stress increases in cortisolconcentrations. There were significant genotype-by-environment interactions for all traitsexcept unstressed (control) plasma glucose concentrations. Incubation temperature had asignificant effect on relative growth rate and final wet weight only. We found a significantcorrelation between post-stress plasma glucose concentration and relative growth rate forall fish, independent of family; while resting plasma cortisol concentration and post-stresshematocrit correlated with wet weight only when analyzed within the eight individualfamilies. Genetic contributions to stress-related parameters and genotype-by-environmentinteractions should be considered as a factor in stress-related research with fish.IntroductionChinook salmon are reared extensively in government hatcheries on the west coastof North America as part of stock enhancement programs. In the last decade, chinooksalmon have also been reared as food fish by private hatcheries and salmon farms. Manyculture techniques result in stress to the fish (Floc et al. 1988, Barton & Iwama 1991). The128129effects of chronic and acute stressors on these artificially reared fish have been shown toimpact their performance and survival (see Wedemeyer et al. 1984, Maule et al. 1989,Pickering 1989, Barton & Iwama 1991).A genetic component to stress response has been proposed for salmonids (Schreck1981, Barton 1988, Wedemeyer et al. 1990, Barton and Iwama 1991); however, there arefew experimental data to support this hypothesis. Differences in the endocrine stressresponse between species of fish have been shown (Davis & Parker 1983, 1986, Sumpteret al. 1986, Fevolden et al. 1991), as well as differences between stocks within a species(coho salmon, McGeer et al. 1991; wild and hatchery-reared rainbow trout, Woodward &Strange 1987). Fall and spring emigrating stocks of chinook salmon fry in the ColumbiaRiver system have different sensitivities to handling and transportation stress as measuredby plasma cortisol concentration, [cortisol]pi, and plasma glucose concentration,[glucose]pi, (Maule et al. 1988). These differences were attributed, in part, to geneticeffects. Refstie's (1982, 1986) work on the genetic contribution to stress response withinand between species using controlled breeding experiments for rainbow trout and Atlanticsalmon indicated a heritable component to both [glucose] pi and [cortisol]pl responses.Fevolden et al. (1991) also found a heritable stress response in rainbow trout and Atlanticsalmon in a selection experiment for high and low [cortisol]pi response to stress. It ispossible that physiological responses such as the primary and secondary stress responses(see Wedemeyer et al. 1990, Barton & Iwama 1991) may be under relatively simplegenetic control.Genotype-by-environment interactions within stress responses have not beeninvestigated in fish. If these interactions exist, such phenotypic plasticity of the endocrinestress response would indicate that a fish's response to stress would, at least in part, dependon its environment and thus the environmental history of the study fish would be importantto the interpretation of investigations into the genetic basis of the stress response.130Although the genetic component of the stress responses of salmonids is not wellunderstood, the genetics of growth and size at age has been examined extensively(Reisenbichler & McIntyre 1977, Gall & Gross 1978a,b, Thorpe & Morgan 1978, Ayles &Baker 1983, Bailey & Saunders 1984, Gjerde & Gjedrem 1984, Robison & Luempert1984, deMarch 1991). Such investigations with chinook salmon fry have shown thatgrowth and growth-related characteristics generally have significant genetic components(Cheng et al. 1987, Withler et al. 1987). The effect of rearing temperature on growth andsize at age of salmonid fry has been extensively described (Clarke et al. 1981, Iwama &Tautz 1981, Baker 1983, Clarke & Shelbourn 1985, Pereira & Adelman 1985), andgenotype-by-environment interactions involving growth rate and rearing temperature havebeen reported for rainbow trout (McKay et al. 1984).The main purpose of this study was to investigate the effects of genetic andenvironmental (incubation temperature) factors, as well as the genotype-by-environment interaction, on growth-related and stress-related traits. Specifically, thispaper reports experiments using a nested mating design with two incubationtemperatures to test for sire, dam, environmental and interaction contributions to:freshwater growth, wet weight at eight months of age, stress responses, as measuredby hematocrit (Hct), [cortisol] pi and [glucose]pi. We also investigated correlationsbetween the growth and stress related variables within the full-sib families as well asacross all families.Materials and MethodsMating Design and Incubation In September, 1989, over 100 sexually maturing male and female chinooksalmon (first generation domestic Robertson Creek stock) were taken at random frommultiple seine sets at the saltwater rearing facilities of Yellow Island AquacultureLtd. (YIAL, Quadra Island, British Columbia), and transferred to freshwaterfacilities (aerated well water). On November 9, 1989, four 3-year-old females werespawned, and the eggs from each female were divided into two approximately equalgroups. In order to increase the potential diversity of the male contribution to theoffspring, half of the eggs from each female were fertilized by 2-year-old males,while the other half were fertilized by 3-year-old males. Each male was used onlyonce and all fertilizations took place within 2 h of gamete collection. The resultingeight families were further divided into two sub-groups (Table A.1). Thedevelopment of one of these sub-groups was accelerated by incubating the eggs andalevins in heated water (average temperature = 10.2 °C; range = 9.0 - 11.1 °C)while the other sub-group was incubated in unheated water (average temperature =8.0°C; range = 7.4 - 9.0°C). All family groups were incubated in vertical stackincubation trays (Heath Technicorp., Seattle, Washington) with flows of 12-16L•min -1 . The eggs were disinfected 2 -3 times per week with malachite green (50-100mg•L-1 flush treatment) until the eyes of the developing embryo were clearly visible(eyed stage; approximately 30 days at 10 °C). Once eyed, the eggs were shocked anddead eggs removed. All losses were recorded throughout the incubation period. ByJanuary 3, 1990 all the accelerated family groups were hatched and the alevins hadreached swim-up stage (yolk sac fully absorbed) by February 7, 1990. All of the fishin the non-accelerated family groups were hatched by January 21, 1990, and thosealevins reached swim-up stage by March 13, 1990.Family GroupsAt swim-up, each family (500 to 1000 fry) was randomly assigned to one of16 identical 200L outdoor tanks. All tanks received equal water flows (15 L• min -1 )from a common source (average temperature = 8.8°C; range = 7.8 - 10.0°C). For14 days after swim-up, fry were fed during daylight hours with automatic feeders,eight times per hour. Subsequently, the fry were fed to satiation by hand four timesper day. The fry were fed Biomoist starter131Table A.1; Schematic diagram of the nested mating design used, across two incubation temperatures. The dams were all 3-year-oldchinook salmon and the sires were aged as noted, family numbers are those referenced in Fig. A.1. The survival data over thefirst two periods are based on 520-977 fish. The survival data given for the trial period are presented as percent values, withinitial number in parentheses.Dam Sire FamilyNumberIncubationStrategySurvival (%)FertilizationTo Swim-up iSwim-upTo Trial 2TrialPeriod3Male 1 1 Accel. 82.0 97.6 100^(42) d(2-yr-old) Non-accel. 92.5 95.6 91.5^(42)Female 1Male 2 2 Accel. 94.4 97.9 88.0^(42)(3-yr-old) Non-accel. 89.6 96.7 76.0^(42)Male 3 3 Accel. 97.1 97.4 97.6^(42)(2-yr-old) Non-accel. 94.4 97.9 91.7^(12)Female 2Male 4 4 Accel. 98.5 98.3 97.6^(41)(3-yr-old) Non-accel. 93.5 99.0 95.2^(42)Male 5 5 Accel. 97.2 99.1 97.6^(42)(2-yr-old) Non-accel. 97.6 99.2 94.8^(19)Female 3Male 6 6 Accel. 93.3 98.7 95.2^(42)(3-yr-old) Non-accel. 97.9 98.4 88.1^(42)Male 7 7 Accel. 96.4 98.0 74.0^(42)(2-yr-old) Non-accel. 91.9 98.3 90.5^(42)Female 4Male 8 8 Accel. 96.2 98.3 87.5^(40)(3-yr-old) Non-accel. 94.1 97.3 95.2^(42)1^ •No significant differences (chi square=21.2; df=15); 2 No significant differences (chi square=0.99; df=15); 3 No significantdifferences (chi square=3.83; df=15)diet (Bioproducts Ltd., Warrenton, Oregon) until they reached 1.2 g when they wereswitched to a semi-moist diet (Moore Clarke Canada, Vancouver, B.C.). Mortalitieswere removed and recorded daily.On May 24, 1990, about 40 fish from each of the 16 family groups wereanaesthetized in 20 mg•L-1 MS-222 (Syndel Laboratories, Vancouver, B.C.), andeach was injected intraperitoneally with a passive integrated transponder (PIT) tag.The PIT tag allowed the identification of each individual fish throughout the durationof the experiment. At the same time wet weight (±0.1 g) was measured; this was theinitial weight measurement for subsequent growth calculations. Tagged fish weretransferred into a single 3 000 L indoor tank receiving a flow of 40 L . min-1 undersimulated natural photoperiod and fed with automatic feeders every 5 min duringdaylight hours. To minimize the possibility of tank effects during the experiment, thefish were held in this common environment from May 25 to July 01, 1990, (37days). All mortalities were removed and frozen for later identification. The fry werestarved from June 29 to July 1, at which time the pooled fish were anaesthetized(0.12 mg•L-1 2-phenoxyethenol), weighed (± 0.1 g), and identified by their PITtag. This weight was the final weight that was used in the growth calculations. Thefish were then returned to their 16 original family tanks and left undisturbed forapproximately three days (until July 3-4).To investigate the role of genetics in the stress response, six to 16 fish fromeach of the 16 family groups were subjected to an acute handling stress by placingthem on a flat screen suspended in the air for 30 s, and then returning them to aholding tank for recovery. At the same time, a similar number of fish from the samefamily groups were immediately transferred to a lethal dose of 2-phenoxyethanol (5ml•L-1 ); they lost equilibrium and were dead within 20 s. These fish were the non-stressed controls, while the stressed fish were sampled 2 h after the handling stress(see Barton & Iwama 1991). At the time of sampling, all fish were identified by133their PIT tag code and, within 15 min of capture, bled from the caudal vasculatureinto an ammonium-heparinized capillary tube after the caudal peduncle was severed.The capillary tubes were centrifuged, Hct measured (as percent packed cell volume),and the plasma was frozen (-20°C) and stored for later cortisol and glucose analyses.All sampling was carried out between 9:00 and 17:00 to reduce the possibility ofdiurnal effects (Thorpe et al. 1987).Plasma cortisol concentration was determined by 125I cortisolradioimmunoassay (Clinical Assay No. 529; Baxter Healthcare Corp., Cambridge,Mass.). This procedure is based on the competitive binding principles ofradioimmunoassay as described by Sumpter & Donaldson (1986) and has been usedto measure [cortisol] p1 in salmonids (Wedemeyer & Yasutake 1977, Iwama et al.1989, Wedemeyer et al. 1990). Plasma glucose concentration was measured using amodification of Trinder's (1969) colorimetric procedure with premixed 4-aminoantipyrine (Glucose [TRINDER] procedure No. 315; Sigma ChemicalCompany, St.Louis, Missouri).Statistical AnalysisSurvival of the 16 family groups during three rearing periods: (1) incubation(fertilization to swim-up), (2) rearing from swim-up to the beginning of theexperiment, and (3) the experimental period was compared using the chi-squaregoodness of fit procedure (Zar 1974). Survival was not significantly different amongthe 16 family groups for any of the time periods analyzed (Table A.1).Since the growth of the fish during the experiment was approximately linear,we used relative growth rate (RG) in our analyses. Because the PIT tags allowed usto identify individual fish we calculated RG for each fish using:RG = (Wtfinal - Wti n itiai) X 100%(Wtinitial X Time)134Where Wtinitiai, and Wtfino, are the individual weights measured at the time oftagging, and the final sampling, respectively, and Time is the number of daysbetween the initial and final weight measurements.The changes in [glucose]pi and [cortisol]pi in response to the handling stresswere standardized by subtracting the family mean value for the control fish from theindividual post-stress measurements (referred to as o[glucose]pi , and O [cortisol]pi).The use of n[glucose]pi , and O [cortisol]pi allowed the analysis of the change in[glucose]pi and [cortisol] pi due to the stressor, without the confounding unstressedcomponent.Since RG was a percentage value, it was transformed using the arcsine squareroot transformation, however the Hct measurements were within the 30-70% range,thus the arcsine square root transformation was not used (Sokal & Rohlf 1981). Allvariables (except RG) were found to be heteroscedastic and were thereforetransformed using the natural logarithm (Sokal & Rohlf 1981). Analyses wereperformed on the transformed data and reported means and 95 % confidence limitsare back-transformed values (Sokal & Rohlf 1981).To test for sire, dam, and environmental (incubation temperature) effects, aswell as incubation temperature-by-sire and -by-dam interactions (genotype-by-environment interactions) a three-way nested ANOVA (males nested within females)was used. The model was:Ypmno= A + E0 + Dn + S mn + EDon + ESomn + emnop^(Model A)Where Ypmno is the observation on the pth progeny of the mth sire nested within thenth dam, within the oth incubation strategy; and p. is the population (least square)mean. E0 is the fixed effect of the oth incubation strategy (accelerated or non-135accelerated); Dn is the random effect of the nth dam; S mn is the random effect of themth sire nested within the nth dam; EDon is the interaction of the oth incubationstrategy and the nth dam (genotype by environment interaction); ES omn is theinteraction of the oth incubation strategy and the mth sire nested within the nth dam(genotype by environment interaction); and emnop is the random error term.Since the sire component estimated in Model A would also include any sireage effects (i.e. differences between the progeny of the 2- and 3-year-old sires), wetested for the effect of sire age using a saturated four-way ANOVA. The main effectswithin the model were; incubation strategy (fixed effect), treatment (fixed effect),dam (random effect), and sire age (two and three years of age - fixed effect), and allinteraction terms were also included. The purpose of this analysis was to test forstrong sire age effects which, if present, would contribute to the random sire effectdescribed in Model A.A two-way ANOVA was used to test for family by incubation temperatureinteractions (genotype by environment interactions). The model used was:Yijk= A + q ± Ei + CE1.0 + eijk^(Model B)Where Yijk is the observation of the kth progeny of the jth cross from the ithincubation strategy, it is the population (least square) mean, q is random effect ofthe jth full-sib family, Ei is the fixed effect of the ith incubation strategy, CEij is theinteraction between the jth cross and the ith incubation strategy (the genotype-by-environment interaction), and eijk is the random error term. It should be noted thatModel B does not include the half-sib relationships of some of the families makingthe analysis conservatively suboptimal. Model B is thus prone to Type II errors(Sokal & Rohlf 1981), and any nonsignificant results within Model B must be viewedwith caution.136A four-way nested ANOVA (males nested within females) was used to test forthe effect of the applied stress (treatment). The model was:Yqpmno= A + Tp + E0 + Dn + Snm + TDpn + TSpmn + emnopq (Model C)Where Yomno is the observation on the qth progeny of the mth sire nested withinthe nth dam, within the oth incubation strategy, within the pth treatment; and A is thepopulation (least square) mean. Tp is the fixed effect of the pth treatment (stressed ornon-stressed); E0 , Dn , and S mn are as in Model A; TDpn is the interaction of thepth treatment and the nth dam; TS pmn is the interaction of the pth treatment and themth sire nested within the nth dam; and e mnopq is the random error term.Since all of the ANOVA models described above are mixed models, the errorterms and degrees of freedom used for the tests of significance of the interactionterms, as well as the main effects, were estimated as described in Zar (1974).Regression analysis was used to test for correlations between final weight andcontrol and post-stress: (1) [glucose] pi; (2) [cortisol]pi; and (3) Hct. Regressionanalysis was also used to test for correlations between RG and control and post-stress: (1) [glucose]pi; (2) [cortisol]pi; and (3) Hct. The regression analysis was donewithin each family separately, as well as across all families. To test for the possibleeffect of the incubation temperature a dummy variable coding for accelerated versusnon-accelerated groups was included in a multiple regression analysis.ResultsSire and Dam EffectsThe nested ANOVA (Model A) allowed the estimation of the sire and damcomponents of the observed variance. Sire effects were significant for all traits measured(Table A.2), while the dam effect was significant for all traits except for137Table A.2: ANOVA table (model A; see text) for growth and stress-related parameters measured on 8 full-sib families of chinooksalmon fry. Mean squares (MS) are given for sire (S), dam (D), incubation temperature (IT), and interaction effects. Sireswere nested within dams and both are random effects, while IT was a fixed effect.Source ->^Dam^Sire^Incubation^D X IT^S X IT^MS(D) (S) Temperature (IT)^Interaction^Interaction^ErrorTrait^(df=3)^(df=4)^(df=1) (df=3)^(df=4)^(df)Wet weight^1.3 *** 0.12 ** 11.3 *** 0.022NS 0.069 * 0.025(g)^ (354)RG 0.004 *** 0.002 *** 0.013 ** 0.001NS^ 0.001 ** 0.0002(%'day-1 )^ (354)[Cortis91],31^3.0** 4.5***^7.5NS 8.6*** 1.7 *** 0.24(Agd1 ±) (177)[Glucos] p i^0.21 *** 0.26 *** 0.068NS^0.043NS^0.048NS^ 0.032(mg'd1-± ) (166)Control Hct^0.098 *** 0.028 ** 0.002NS^ 0.026 *^0.025 * 0.008(%)^ (177)n[Cortiqol] pi 0.20NS^0.54 *** 0.017NS^0.96 *** 0.092NS^ 0.10(pg'd1 --")^ (168)n[Glucoqe]pi^0.91 **^0.43 *^0.74NS 1.18 ***^0.18NS 0.042(mg'dl-i ) (167)Post-stress^0.27 *** 0.049 ***^0.24NS 0.053 ** 0.066 *** 0.01Hct (%) (168)NS^• •^* . .^** . .^*** .Not significant at P < 0.05; Significant at P <0.05;^Significant at P <0.01;^Significant at P <0.001.139O [cortisollo (Table A.2). The effect of sire age (2-year-old versus 3-year-old sires) wasfound to be not significant (P> 0.05) for all of the traits measured when analyzed with thefour-way saturated ANOVA. The effect of sire age was therefore not a major contributorto the observed individual sire effects described above.Genotype-by-Environment InteractionsThe family-by-incubation temperature interaction was found to be significant for alltraits measured except for final wet weight and [glucosej pl (Fig. A.1). The norms ofreaction (Fig. A.1) indicated possible incubation temperature interactions with the sire anddam effects. The nested ANOVA (Model A) allowed analysis of the sire-by- and dam-by-incubation temperature interactions separately. The dam-by-incubation interaction wassignificant for all traits except for final wet weight, RG, and [glucose] pj (Table A.2),while the sire-by-incubation temperature interaction was significant for all traits except for[glucose]pi, O [glucose]pj, and O [cortisolipj (Table A.2).Treatment ResponsesThe nested ANOVA (Model C) showed that the effect of the applied stress wassignificant for [cortisol] pi (P < 0.005) and [glucose] pj (P < .01), however there was nosignificant treatment (stress) effect for the Hct values (P> .05). The [cortisol] pj and[glucose]pi mean values were higher 2 h post-stress than the control values (i.e.O[cortisolipj and 0 [glucose]pi are not negative in Table A.3)Incubation Temperature EffectsWithin the nested ANOVA (Model A), there was a significant incubationtemperature effect for both final wet weight, and RG over the duration of the experiment(Table A.2). Mean wet weight of the fish in the accelerated groups was greater than that ofthe fish in the non-accelerated groups (Table A.3), and RG was higher in the fish in thenon-accelerated groups than in the accelerated groups (Table A.3). None of the stressrelated traits showed significant incubation temperature effects (Table A.2), and the mean140Figure A.1: Back-transformed means for the measured traits for the eight chinook salmonfamilies (numbered as in Table A.1). Means are given for the two incubationtemperatures (accelerated and non-accelerated), and the lines joining the full-sibgroup means are norms of reaction. Genotype-by-incubation temperatureinteractions are identified by crossing of these lines. RG is relative growth, Hct ishematocrit, [cortisol]pil and [glucose]pi are the plasma concentrations of cortisol andglucose respectively, O[cortisol]pi and n[glucose]pi are the changes in plasmaconcentrations of cortisol and glucose 2 h post stress. P is the statistical significanceof the full-sib family-by-incubation temperature interaction from the Model BANOVA (see text).50oooo  85271716GLIE'5616• 480IX 48z0C..) 44442141528635P<.0015510090807060P=.3366573P<.001126318• 15co• 12—11O 9ce)I-:04 603ACCELERATED^NON•ACCELERATED^ACCELERATED ^NON-A CCELERATED4.00Ss• 3.503.002.50ACCELERATED^NON-ACCELERATEDACCELERATED^NON-ACCELERATED142Table A.3: Back-transformed means and confidence intervals of the traits measured onchinook salmon fry reared at two incubation temperatures (accelerated and non-accelerated). RG is relative growth rate, [cortisol] Di and [glucose] Di are the plasmaconcentrations of the control fish, and O[cortisol]im and n[gluco§e]pi are thechanges in plasma concentration due to handling stress.Parameter Accelerated(Heated Water)Group MeanNon-Accelerated(Un-heated Water)Group MeanWet weight(g)7.27 (7.06-7.49) 1 5.06 (4.92-5.21) 1RG(Vday-1 )3.00 (2.92-3.06) 3.49 (3.42-3.57)[Cortis9l]pi(gg'd1 -1 )5.42 (4.80-6.11) 3.57 (2.82-4.41)[Glucose]pl(mg'd1-1 )77.5 (74.4-80.6) 83.1 (79.8-86.5)Control Hct(%)45.2 (44.3-46.1) 45.2 (44.3-46.1)in[Cortis91]pi 9.26 (7.81-10.8) 9.14 (7.85-10.5)n[Glucoe] pi(mg'd110.5 (5.32-15.9) 20.9 (15.2-26.8)Post-stressHct^(%)47.7 (46.5-48.6) 45.6 (43.6-46.8)1 95% confidence interval.143values were not very different between the treatments (Table A.3).Growth Rate and Body Size EffectsTo test for the overall effect of final weight and growth during the study period onthe stress related traits, regression analysis was performed on the data across all familygroups. Few of the stress-related parameters were correlated with either RG or finalweight. However, in [glucose]pi was positively correlated with RG (slope = 6.69;P <0.01; r2 =0.18; n=180). To test for family-specific relationships between final weightor RG and the stress related parameters, regression analysis was performed separately onthe data from each full-sib family. Significant relationships between [cortisol] pi and finalweight were found in six of the eight families (P <0.05). Five of the eight families hadsignificant relationships between the Hct and wet weight values in the post-stress fish(P <0.01). Multiple regression analysis showed that the incubation temperature effect wasnot significant (P >0.05) within the regressions.DiscussionGenetic Effects We found significant dam and sire effects for most of the traits that we measured.Previous researchers have shown that wet weight and growth are heritable in chinooksalmon fry (Cheng et al. 1987, Withler et al. 1987), and our results for the RobertsonCreek stock are consistent with this work. A genetic component to stress-related traits inchinook salmon has not been previously reported, although significant sire and dam effectsfor [glucose]pi and [cortisol]pi have been found for rainbow trout and Atlantic salmon(Refstie 1982, 1986, Fevolden et al. 1991). Furthermore, stock and strain differences in[cortisol]o, [glucose] pi and Hct, have been reported for chinook salmon (Barton et al.1986, Maule et al. 1988), coho salmon (McGeer et al. 1991), rainbow trout (Casillas &Smith 1977, Refstie 1982, Woodward & Strange 1987), and largemouth bass, Micropterussalmoides, (Williamson & Carmichael 1986); these differences have been interpreted as144evidence for a genetic component to these parameters. Our results support thoseinterpretations.Our results indicate that the pedigree of the fish may have a major impact on thestress-response of salmonids, and thus some knowledge of the genetic history of the fish isnecessary for meaningful comparisons between groups of control and challenged fish.Furthermore, the variability among family members was considerably less than that usuallyreported for randomly chosen groups of individuals (Barton & Schreck 1988, Maule et al.1989), thus full-sib or, ideally, clonal fish should be used when high sensitivity is desiredfor stress response experiments. The genetic effects observed in this study for [cortisol] piand [glucose] pi may have been due to genetic differences in endocrine system responsetime, peak plasma hormone concentration, clearance rate, or any combination thereof. Wewere not able to determine which mechanism(s) led to the observed differences from thisstudy.Our mating design allowed the partitioning of the observed variation in themeasured traits into sire and dam components but since the sires were nested within thedams, and only four females were used there was little power to resolve dam effects.Furthermore, the dam effects included "maternal" or "common environmental" effects (i.e.crD2 = 0.25V A + VCE, where VCE is the maternal common environment effect -Falconer 1981). Maternal common environment effects are non-genetic influences, such asegg size, egg quality, etc., of the dam on her offspring. These effects have been shown tobe relatively small for growth and size related measurements in salmonids of the size ofthose in this study (Iwamoto et al. 1984, Withler et al. 1987). However, no studies havereported the magnitude of maternal effects for stress response traits. Furthermore, since thesire component of the observed variance (i.e. as2 = 0.25VA + 0.25VD - Falconer 1981)includes dominance effects (VD), no unbiased estimate of VA is possible. No estimate ofheritability (h 2) was attempted due to the uncertainty of the magnitude of the contributionof the non-additive effects (i.e. VCE and VD). Furthermore, even if the non-additive145effects were assumed to be negligible, the standard error of heritability estimates based ononly 8 families would be unacceptably large.Genotype-by-Environment InteractionsThe family by environment interactions found for RG, [cortisol] pl, to [cortisollo ,O [glucose]o, and Hct of control and post-stress fish indicate that the relative ranking ofthe eight families is different between the two incubation temperature regimes (Fig. A.1),and thus the genetic component of the stress responses of fish varies widely depending ontheir environmental history. The genotype by environment interaction is even more evidentwhen the full-sib families are broken down into sire and dam components (Table A.2).Social interactions can affect chronic stress responses (Schreck 1981, Schreck 1990), andsince the fish in this study were held in a single tank for the duration of the trial, complexbehavioral interactions may have contributed to the observed genotype-by-environmentinteraction terms. Since the family groups were held in separate tanks prior to the trialperiod, tank effects would also contribute to the incubation temperature-by-genotypeinteraction, thus the environmental effects are not just due to incubation temperaturedifferences but represent a combination of environmental effects. The genotype-by-environment interaction is quite apparent upon inspection of the norms of reactionpresented in Fig. A.1.Independent of the source of the interaction, our results indicate that environmentalhistory and developmental stage of the fish is critical to the comparison and interpretationof most of the stress-related traits examined in this study. Furthermore, these resultsindicate that selection on these traits would be most effective on family groups withidentical rearing histories. Gains realized by this selection could be lost by changes inrearing practices in subsequent generations.Environmental EffectsOne of the most obvious differences between the fish from the two incubationtemperatures was size (Table A.3). Since smolting in chinook salmon is strongly dependent146on fish size (Clarke 1982, Clarke & Shelbourn 1985), it is possible that the accelerated andnon-accelerated family groups were at different physiological stages within the smoltingprocess. Although there was no significant differences between the accelerated and non-accelerated fish for the stress-related traits (Table A.2), it is possible that the differences inthe final weight or RG of the two groups may have indirectly influenced the stress relatedtraits. If this were the case, we would expect to find correlations between weight or RG,and the stress-related traits. It has been previously shown that resting [cortisol]o is notcorrelated with body size in salmonids (Mazur 1991, Fevolden et al. 1991), and our resultssupport this conclusion based on the analysis across all families. We found, however,significant correlations between wet weight and [cortisol] pi within six of the eight full-sibfamilies. Correlations between [cortisol]p1 and weight have probably not been previouslyobserved because of the family dependent nature of the relationship (i.e. the slope of theregression varies between families). The positive correlation between post-stress[glucose]pi and RG probably reflects the fact that both are positively related to metabolicrate (Umminger 1977, Jobling 1983, Barton 1988).The control values of [cortisol]pi were relatively high (Table A.3) compared tothose reported elsewhere for chinook salmon (see Barton & Iwama 1991), and may beassociated with smoltification in these fish, similar to that which occurs in coho salmon(Barton et al. 1985; Young et al. 1989). Despite the high resting values, mean [cortisol] piincreased almost three-fold two hours after the handling stress (Table A.3), indicating thatthe interrenal tissue was still capable of releasing cortisol in response to acute stress.However, the family groups with the highest average resting [cortisol] p1 tended to be thegroups with the lowest mean [cortisol]o increase due to stress (r2 =0.29; P <0.05;slope=-0.30; N=16). This supports the hypothesis of a negative feedback mechanism thatlimits the release of cortisol when the existing plasma concentrations are already elevated(Fryer & Peter 1977).147The response of fish to chronic and acute stress is very important to fish husbandry,and these results indicate that selection for tolerance to stress is probably possible.However, until the nature of the genotype-by-environmental interaction is betterunderstood, the implementation of an effective selection program would be problematic.The genetic contribution to the variance observed in the growth-related and the stress-related traits considered in our study is very important to research which involves makingcomparisons between groups of fish. Precise comparisons would only be valid if the fishwere of similar genetic background, or from a randomized genetic mixture. Geneticallyrandomized groups of fish are logistically difficult to obtain, and would greatly increasewithin-group variance, thus reducing the precision of the experiment. Due to thelimitations of our mating design no unbiased estimate of the additive genetic variance forthe traits studied was possible. Our results do indicate, however that further research usinga more appropriate mating design (i.e. dams nested within sires and more families) iswarranted.Appendix BBernier, N.J., D.D. Heath, D.J. Randall, and G.K. Iwama. IN PRESS. Repeat sexualmaturation of precocious male chinook salmon (Oncorhynchus tshawytscha)transferred to sea water. Can. J. Zool. 00: 0000-0000.AbstractPrecocious sexual maturation in salmonid parr occurs under wild and cultureconditions. We investigated the possibility of repeat maturation in chinook salmonprecocious parr from the Nicola River, British Columbia. Precocious and immature(control) yearling parr were reared in fresh water from March, 1990 to mid-June, and thentransferred to salt water (29-30 ppt) until September, 1990. The precocious parr weresignificantly larger than the control from March to July and there were no differences inrelative growth rate between the groups throughout the study. Total mortalities were45.7% and 5.9% for precocious and control fish, respectively. All the precocious, butnone of the control fish expressed milt in March in fresh water. None of the fish expressedmilt soon after the transfer to salt water in June, but all precocious fish and 18.8% of thecontrol expressed milt in September. There were no significant differences in the averageplasma concentrations of Na + , Cl- , and cortisol between groups in September, suggestingthat both precocious parr and control groups were saltwater competent. 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