Science, Faculty of
Zoology, Department of
DSpace
UBCV
McMaster, Aidan Clark
Master of Science - MSc
University of British Columbia
Understanding how morphology is shaped by captive breeding and rearing of fish is becoming increasing important for policy-making surrounding the conservation of aquatic species, as hatchery supplementation becomes more and more commonplace and the potential for impacts on wild populations grows. Therefore, the objective of this thesis was to explore how genetics and environment shape the morphological phenotypes of domestic-wild hybrid salmonids. First, I used photos of F2 hybrid rainbow trout parr after a single growing season in a semi-natural environment to determine whether “domestic” or “wild” phenotypes predominate under these conditions. I found differences in overall body shape, particularly in the head and deepness of the body between the domestic and wild fish. Some phenotypes in the F2s were more similar to those of one or the other of the grandparents reared in hatchery conditions, and others were entirely different, likely due to the differences in food availability, presence of predation, water velocity, etc. in the semi-wild environment compared to a hatchery environment. Next, I used photos of F2 offspring of domestic and wild strains of coho salmon to do a similar analysis, which revealed an extremely fast-growing group of juveniles. I then used next-generation genomic sequencing (PoolSeq) to attempt to find SNPs correlated with this fast growth trait. I found three large regions of differentiation between the fast growing and slow growing F2 fish, with enrichment for processes such as musculoskeletal development, omega peptidase activity, and folate transmembrane transport. The results of my first chapter indicate that the environment has extremely large impacts on morphological phenotypes; however, as shown by my second chapter, genotype can create drastic differences in morphology when rearing conditions are identical. The results of this thesis illustrate the interacting effects of genetics and environment on morphological phenotypes in salmonids.
GENETIC AND ENVIRONMENTAL INFLUENCES ON MORPHOLOGICAL TRAITS IN SALMONIDS by Aidan Clark McMaster BSc Hons, University of Regina, 2020 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in The Faculty of Graduate and Postdoctoral Studies (Zoology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) August 2023 ©Aidan Clark McMaster, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: GENETIC AND ENVIRONMENTAL INFLUENCES ON MORPHOLOGICAL TRAITS IN SALMONIDS submitted by Aidan Clark McMaster in partial fulfilment of the requirements for the degree of Master of Science in Zoology Examining Committee: Patricia Schulte, Professor, Zoology, UBC Supervisor Katie Marshall, Professor, Zoology, UBC Supervisory Committee Member Judith Mank, Professor, Zoology, UBC Additional Examiner Additional Supervisory Committee Members Dolph Schluter, Professor, Zoology, UBC Supervisory Committee Member iii Abstract Understanding how morphology is shaped by captive breeding and rearing of fish is becoming increasing important for policy-making surrounding the conservation of aquatic species, as hatchery supplementation becomes more and more commonplace and the potential for impacts on wild populations grows. Therefore, the objective of this thesis was to explore how genetics and environment shape the morphological phenotypes of domestic-wild hybrid salmonids. First, I used photos of F2 hybrid rainbow trout parr after a single growing season in a semi-natural environment to determine whether “domestic” or “wild” phenotypes predominate under these conditions. I found differences in overall body shape, particularly in the head and deepness of the body between the domestic and wild fish. Some phenotypes in the F2s were more similar to those of one or the other of the grandparents reared in hatchery conditions, and others were entirely different, likely due to the differences in food availability, presence of predation, water velocity, etc. in the semi-wild environment compared to a hatchery environment. Next, I used photos of F2 offspring of domestic and wild strains of coho salmon to do a similar analysis, which revealed an extremely fast-growing group of juveniles. I then used next-generation genomic sequencing (PoolSeq) to attempt to find SNPs correlated with this fast growth trait. I found three large regions of differentiation between the fast growing and slow growing F2 fish, with enrichment for processes such as musculoskeletal development, omega peptidase activity, and folate transmembrane transport. The results of my first chapter indicate that the environment has extremely large impacts on morphological phenotypes; however, as shown by my second chapter, genotype can create drastic differences in morphology when rearing conditions are identical. The results of this thesis illustrate the interacting effects of genetics and environment on morphological phenotypes in salmonids. iv Lay summary The body shape of fish is very important because it can influence the ability of a fish to escape predators and capture prey. The goal of my thesis was to explore genetic and environmental influences on the body shape of salmonid fishes, using crosses between domesticated and wild strains of rainbow trout and coho salmon that are known to differ in body size and shape. The results on rainbow trout presented in Chapter 2 indicate that early rearing environment has large impacts on body size and shape, but as shown in Chapter 3 from work on coho salmon, genetic effects can also result in drastic differences in morphology even when rearing conditions are identical. v Preface This thesis is original, unpublished, independent work by the author, Clark McMaster. The F2 crosses used in Chapters 2 and 3 were generated by Robert Devlin at the Department of Fisheries and Oceans. Pond stocking and sampling of rainbow trout presented in Chapter 2 was led by Madison Earhart. All experiments were performed under UBC Animal Care and Use Protocol number A16-0329. vi Table of Contents Abstract ................................................................................................................................ iii Lay summary ........................................................................................................................ iv Preface .................................................................................................................................. v Table of Contents .................................................................................................................. vi List of Figures........................................................................................................................ ix Acknowledgements.............................................................................................................. xii Chapter 1: Introduction .......................................................................................................... 1 1.1 Introduction ............................................................................................................................ 1 1.2 Domestication in fishes ............................................................................................................ 1 1.3 Phenotypes of cultured salmonids ........................................................................................... 2 1.4 Ecological impacts of cultured salmonids .................................................................................. 3 1.5 Thesis Objectives ..................................................................................................................... 4 1.5.1 Chapter 2: Characterization of juvenile morphology of a wild and domestic strain of rainbow trout (Oncorhynchus kisutch)......................................................................................................................................... 5 1.5.2 Chapter 3: Initial characterization of the genetics of variation in growth rate in coho salmon (Oncorhynchus kisutch)......................................................................................................................................... 5 1.6 Potential implications .............................................................................................................. 5 Chapter 2: Characterization of juvenile morphology of a wild and domestic strain of rainbow trout (Oncorhyncus mykiss) .................................................................................................... 6 vii 2.1 Introduction ............................................................................................................................ 6 2.2 Materials and Methods ...........................................................................................................11 2.2.1 Experimental animals ................................................................................................................................ 11 2.2.4 Photo analysis ............................................................................................................................................ 12 2.2.3 Morphometry and parr mark analysis ....................................................................................................... 13 2.2.4 Statistical Analysis ...................................................................................................................................... 15 2.3 Results ...................................................................................................................................16 2.3.1 Differences in morphology between wild and domestic strains of Rainbow trout ................................... 16 2.3.2 Principal component analysis of variation in morphology and markings between wild and domestic strains of Rainbow trout ..................................................................................................................................... 17 2.3.3 Variation in morphology and markings between F2 crosses and grandparental strains .......................... 19 2.3.4 Traits that distinguish F2 pond fish from the grandparental hatchery strains .......................................... 20 2.3.5 Traits that exhibited altered variation in F2 pond fish ............................................................................... 29 2.3.6 Effects of body length on trait values ........................................................................................................ 30 2.4 Discussion ..............................................................................................................................33 Chapter 3: Initial characterization of the genetics of variation in growth rate in coho salmon (Oncorhynchus kisutch) ........................................................................................................ 41 3.1 Introduction ...........................................................................................................................41 3.2 Materials and Methods ...........................................................................................................43 3.2.1 Animals ...................................................................................................................................................... 43 3.2.2 Geometric morphometrics ........................................................................................................................ 43 3.2.3 DNA isolation and sequencing ................................................................................................................... 44 3.2.4 Bioinformatics ............................................................................................................................................ 44 3.3 Results ...................................................................................................................................45 viii 3.3.1 Morphometrics .......................................................................................................................................... 45 3.3.2 Poolseq....................................................................................................................................................... 49 3.3.3 Functional Enrichment ............................................................................................................................... 51 3.4 Discussion ..............................................................................................................................55 3.4.1 Chromosome regions associated with increased growth.......................................................................... 55 3.4.2 Implications for aquaculture and hatchery management ......................................................................... 58 3.4.3 Limitations and future directions .............................................................................................................. 59 Chapter 4: General Discussion and Conclusion ...................................................................... 60 4.1 Thesis Summary .....................................................................................................................60 4.2 Limitations and Future Directions ............................................................................................62 4.2.1 Chapter 2 ................................................................................................................................................... 62 4.2.2 Chapter 3 ................................................................................................................................................... 63 Bibliography ........................................................................................................................ 64 Appendix: Supplementary Figures ........................................................................................ 80 ix List of Figures Figure 2.1. Comparison of original photo (left) with the processed photo corrected for white balance and colour......................................................................................................................... 13 Figure 2.2. Positions of landmarks used for geometric morphometrics in rainbow trout. Red dots indicate the position of landmarks placed on the body. ................................................................ 14 Figure 2.3. Wireframe comparison of average shape of Fraser Valley (top) and Pennask (bottom) strains of rainbow trout. Arrow A emphasizes the difference in distance from the lateral line of the fish to the bottom of the stomach. Arrow B emphasizes the difference in distance from the bottom edge of the eye to the bottom of the head. ........................................................................ 16 Figure 2.4. PCA comparing both parr mark measurements and body dimension data from grandparental strains Pennask (pn) and Fraser Valley (fv). .......................................................... 19 Figure 2.5. Directional loadings of principle components for PCA in Figure 2.4. Positively correlated with PC1 are body width, caudal width, and body length. Negatively correlated with PC1 is head angle. Positively correlated with PC2 is normalized parr mark area, and negatively correlated is parr mark lightness. .................................................................................................. 19 Figure 2.6. PCA of grandparental strains (fv and pn) with length and parr mark data from F2s projected into the transformed space. ........................................................................................... 20 Figure 2.7. Distribution of body dimensions for Fraser Valley (fv), Pennask (pn), and pond 11 and 12 (p11, p12) individuals. A: body length for B: body depth. C: Body ratio (body depth relative to body length). ................................................................................................................ 24 Figure 2.8. Distribution of caudal ratios (caudal width/ body length) for Fraser Valley individuals (fv), Pennask individuals (pn), and pond 11 and 12 individuals (p11, p12). ................................ 25 x Figure 2.9. Distribution of head angles for Fraser Valley individuals (fv), Pennask individuals (pn), and pond 11 and 12 individuals (p11, p12). ......................................................................... 26 Figure 2.10. Histograms comparing relative parr mark size (parr mark size normalized to body length) of the four groups. Fv: Fraser Valley, pn: Pennask, p11: pond 11, p12: pond 12. ............ 28 Figure 2.11. Distribution of normalized eye size for Fraser Valley (fv), Pennask (pn), and pond 11 and 12 (p11, p12) individuals. .................................................................................................. 30 Figure 2.12. Regression of caudal width against body length. ..................................................... 31 Figure 2.13. Regression of body width against body length. ........................................................ 31 Figure 2.14. Regression of eye height against body length. ......................................................... 32 Figure 2.15. Regression of head height against body length. ....................................................... 32 Figure 2.16. Regression of head angle against body length. ......................................................... 33 Figure 3.1. A. Individuals belonging to the smaller sized distribution. B. Individuals belonging to the larger sized distribution. C. Histograms comparing counts of individuals against weight (g) and length (cm). ............................................................................................................................ 46 Figure 3.2. PCA plot of individuals using weight (g) and length (cm) as variables. Numbers represent sample number............................................................................................................... 47 Figure 3.3. A. Plot of TPS warps relative to the consensus (plot centre). Red dots indicate fast growing individuals. B. Consensus warp of slow-growing individuals. Front of fish is on the left, each dot represents a landmark. C. Consensus warp of fast-growing individuals. Front of fish is on the left, each dot represents a landmark. .................................................................................. 48 Figure 3.4. Manhattan plot of all linkage groups sequenced. Arrows highlight highly differential regions on LG18, LG19, and LG24. ............................................................................................. 49 Figure 3.5. Manhattan plots of single linkage groups 18, 19, and 24. .......................................... 50 xi Figure 3.6. Enriched processes in the differentiated region on LG18 (highlighted boxes are processes that are significant at P<10-3). ...................................................................................... 52 Figure 3.7. Enriched processes in the differentiated region on LG19 (highlighted boxes are processes that are significant at P<10-3). ...................................................................................... 53 Figure 3.8. Enriched processes in the differentiated region on LG24 (highlighted boxes are processes that are significant at P<10-3). ...................................................................................... 54 Supplementary Figure 1. Number of marks on individuals of each strain. ................................. 80 Supplementary Figure 2. Histograms comparing greyscale values for parr marks (parr mark lightness). Higher values on the x-axis correspond to lighter parr marks. Fv: Fraser Valley, pn: Pennask, p11: pond 11, p12: pond 12. .......................................................................................... 81 xii Acknowledgements Words cannot explain how grateful I am to Patricia Schulte, my supervisor and committee chair, for her outstanding patience and guidance. I certainly could not have gone on this journey without the help of my defense committee, who kindly shared their knowledge and expertise. Furthermore, without Alisha Goodbla and Madison Earhart from our lab, Bob Devlin and the DFO, as well as the BC Freshwater Fisheries Society, this initiative would not have been possible. I am also grateful to my classmates and cohort members, particularly my labmates Madison Earhart and Tessa Blanchard, for their editing assistance, late-night feedback sessions, and moral support. Finally, I would be remiss if I did not acknowledge my family, particularly my wife Blake, my parents and step-parents, and my siblings. Their confidence in me has kept my spirits and motivation strong throughout the process. I'd also like to thank my cat for providing both entertainment and emotional support. 1 Chapter 1: Introduction 1.1 Introduction Domestication in animals has been a process intertwined with human history since the dawn of agriculture. Human societies rearing crops and animals in controlled conditions have been shaping species morphology since the Neolithic era, beginning with crops such as lentils being purposefully cultivated, and quickly expanding to complex systems of artificial selection in large bovine animals (Diamond 2002; Sonnante et al. 2009). Humans first began domesticating animals when, at the end of the Pleistocene era, food supply was unpredictable and the first choices of big game for hunter-gatherers were in a decline (Binford 1968; Flannery 1969; Diamond 2002). Eventually, the lifestyle of food production began to outcompete hunter gathering, and modern agriculture as we know it today began to develop (Diamond 2002). Today, modern breeding practices involve the selection of plants or animals with traits deemed desirable. For example, maize has been selectively bred for many generations resulting in higher yield crops, larger harvestable fruit, and more uniformity (Duvick 2005). The process of selective breeding in animals is similar, and also involves the selection of desirable traits such as resistance to disease or adaptation to a specific environment (Gjedrem et al. 2012). 1.2 Domestication in fishes Aquaculture originated with ancient civilizations, where aquatic species were confined and raised in pens or trapped behind impermeable structures (Fitzpatrick 2020). For example, the Romans acquired and domesticated common carp (Cyprinus carpio) approximately 2000 years ago, and this species had been being bred successfully in China for over 2000 years (Balon 2004). These practices continued, and today modern hatcheries still use captive and selective breeding in multiple species of fish to produce desirable traits or to supplement wild populations. 2 In species of fish that were once plentiful, we have begun to observe steep declines in population numbers due to overharvesting, climate change, and habitat destruction through projects such as damming (Beamish et al. 2010; Bradford and Irvine 2011). As a result, commercial aquaculture, and supplementation of wild stocks with hatchery reared fish have become increasingly commonplace. 1.3 Phenotypes of cultured salmonids Cultured fish tend to display a series of traits that can be considered a “domestication syndrome”, which often involves fast growth and changes in the stress response (Milla et al. 2021). However, because of the great diversity of fish species and types of culture conditions, as well as the relatively recency of domestication in many fish species, it is less clear whether there is a universal domestication syndrome in fish. Domesticated salmonids have been reported to have faster growth rates than wild fish; however, this is strongly influenced by environmental factors such as temperature and food availability (Lucas et al. 2004; Tymchuk et al. 2006b,a; Martens et al. 2014), as well as differences in behavior. For example, some domesticated fish were observed to grow faster, but they were also more aggressive, ingesting more food over time (Tymchuk et al. 2006a). Additionally, the magnitude to which this difference extends is dependent on the purpose that the domestic strain was bred for (Tymchuk et al. 2006a). Morphological differences have also been observed between wild and domestic strains of salmonid species. For example, domestic individuals are typically much deeper through the body than wild individuals, with sharp distinctions in fin and caudal peduncle size (Pulcini et al. 2013). Specifically, the caudal peduncle is deeper in domestic salmonids than in wild ones, in both parr and adults, as is trunk depth (Pulcini et al. 2013). Domestic salmonids were also observed to have larger, blunter heads than wild salmonids (Pulcini et al. 2013). As is the case with growth rates, these morphological differences may be attributed to phenotypic plasticity in 3 response to the environment in some cases. For example, Atlantic salmon were observed to develop a body deeper through the middle when in the presence of competitors (Smith et al. 2017). Interestingly, the extent and direction of this phenotypic plasticity differs across species. For example, brown trout in fast flow develop streamlined bodies, while salmon in fast flow became thicker (Pakkasmaa and Piironen 2001). This highlights the earlier point that the effect the environment has on morphology depends on both the natural history of the species or strain and its domestication history. 1.4 Ecological impacts of cultured salmonids Cultured salmonids have the potential for causing ecological impacts, either through releases of hatchery fish with the goal of sustaining natural populations, or through escapes of aquacultured fish. For example, 80% of juvenile coho salmon sampled in coastal British Columbia were identified as hatchery fish released for the purposes of supplementing existing populations (Beamish et al. 2010). This can have important consequences, as it has been shown that even a single generation of captive rearing is enough to quantitatively change the phenotype and negatively affect the fitness of a wild strain of Atlantic salmon (Milot et al. 2013). Understanding the mechanisms of how the phenotypes of captive-reared and wild strains are shaped is important to ensure that any crossing between introduced and wild fish does not decrease the fitness of the existing wild population as a whole. Negative effects of escaped, non-native salmon from commercial aquaculture have also been documented (Fleming et al. 2000; Volpe et al. 2001; Volpe 2007). These studies were conducted using a non-native (domesticated) strain of Atlantic salmon invading a wild population; although the fish are the same species, the domestic strains often differ in both phenotype and behaviour, and likely possess hatchery selected alleles that may confer negative fitness when introduced into the wild. In order to properly inform commercial aquaculture policy 4 and conservation efforts, working to understand the evolutionary impact of aquaculture escapees on increasingly threatened wild stocks is of paramount importance. 1.5 Thesis Objectives The objective of my thesis work was to examine variation in growth and morphology among domesticated and wild salmonids. To achieve this objective, I have chosen two different species of salmonids: Rainbow trout (Chapter 2) and Coho salmon (Chapter 3). These two species are native to waters along the western coast of North America, with a range extending from Mexico to Alaska. Rainbow trout specifically have been stocked all over the world, and is species this widely considered to be one of the most popular sport fishes. Both of these species are stream spawning, and coho specifically have seen a massive decline in population numbers since the mid-1900s due to overfishing, habitat loss, and climate change (Brown et al. 1994). Rainbow trout, residing mainly in lakes, have been widely stocked across Canada, and less than 10% of wild trout populations assessed have been predicted to be vulnerable to overfishing (Webb 2006); however, it is important to bear in mind that while abundant, this species is not immune to habitat perturbations. In both chapters I take advantage of F2 crosses between a domesticated and a wild strain to examine morphological variation among these offspring and assess the genetic and environmental factors that may be shaping the phenotypes of these species. While descriptive in nature, my findings will generally inform to what extent a hatchery-wild hybrid may be phenotypically shaped by either its immediate environment, or by its underlying genetics. This research will hopefully contribute to the understanding of domestication and phenotypic plasticity in salmonids, as well as convey meaningful insights for conservation and management of fish populations. 5 1.5.1 Chapter 2: Characterization of juvenile morphology of a wild and domestic strain of rainbow trout (Oncorhynchus kisutch) In this chapter, my objective was to assess the importance of variation in body morphology and colouration for performance in a semi-natural environment, using F2 individuals from a wild-domestic cross of rainbow trout. Ecologically relevant traits such as body size, body shape (shown to affect swim performance), juvenile markings (shown to affect susceptibility to predation), and eye size (relevant to feeding ability in various water conditions) were examined. 1.5.2 Chapter 3: Initial characterization of the genetics of variation in growth rate in coho salmon (Oncorhynchus kisutch) In this chapter, my objective was to assess the genetic basis of variation in growth rate between domesticated and wild coho salmon. As in the rainbow trout experiment, I used an F2 crossing design and examined ecologically relevant traits such as body size and body shape, and I utilized wholegenome pool-seq as a first step towards identifying regions of the genome that may be involved in determining body size around the time of smolting. 1.6 Potential implications Because of the rapidly changing habitat and conservation status of salmonids, it is important to develop an understanding of how, and to what extent, the environment they are in will shape their phenotypes, and the role of underlying genetic factors. This will provide insight into how these species may respond to rapidly shifting environmental conditions. This also has important implications for conservation efforts. Knowledge of how a species responds to different habitat conditions and the phenotypes of domestic-wild hybrids can help inform policy and guide management decisions aimed at preserving biodiversity. 6 Chapter 2: Characterization of juvenile morphology of a wild and domestic strain of rainbow trout (Oncorhyncus mykiss) 2.1 Introduction There is substantial variation in body morphology and colour patterns within and among populations of salmonids that is thought to have important effects on performance and fitness (Garcia De Leaniz et al. 2007). Morphological traits that exhibit intraspecific variation include pectoral fin and eye size, head length, and overall body shape (Pakkasmaa and Piironen 2001; Solem and Berg 2011; Drinan et al. 2012; Liasko et al. 2012; Pulcini et al. 2013). There are also numerous studies reporting variation in juvenile colouration such as parr marks and spots (Aparicio et al. 2005; Arostegui and Quinn 2019; Lorenzoni et al. 2019). Variation in morphology and colour is often associated with habitat and this phenotype-environment covariation is thought to be the result of a combination of both local adaptation and phenotypic plasticity (Pakkasmaa and Piironen 2000; Robinson and Parsons 2002; Garcia De Leaniz et al. 2007; Fraser et al. 2011). The physical attributes that define fish shape and size are well known to influence various aspects of performance. In particular, overall fish shape (robustness/slenderness) is important for swimming performance, a trait that can have substantial impacts on fitness (Webb 1984). For example, in juvenile brown trout, size and body morphology had a measurable effect on swim performance, notably impacting endurance in fast moving water (Ojanguren and Brana 2003). These elements of body shape can be strongly influenced by phenotypic plasticity. In Atlantic salmon (Salmo salar), fish developed a deeper body in the presence of competitors, whereas in the absence of competitors they developed more fusiform body shapes (Smith et al. 2017). Additionally, the fusiform body shape was correlated with increases in swim performance, compared to the fish in the presence of competitors, which were negatively 7 affected (Smith et al. 2017). Other environmental variables such as temperature and hydraulic flow rate have also been shown to have a strong effect on body and fin size, as well as body shape (Sfakianakis et al. 2011; Greenberg et al. 2021). For example, Atlantic salmon in fast flow became more robust, while brown trout in fast flow developed more fusiform, streamlined bodies (Pakkasmaa and Piironen 2000). These data highlight the plasticity of body shape in salmonids and the likely importance of this plasticity in body shape for fitness. Further, variation in body morphology likely has a genetic component (Riddell and Leggett 2011; Reis Neto et al. 2019; Nazari and Paknejad 2020). Hatchery brook trout (Salvelinus fontinalis) demonstrate significant additive genetic variation for both morphology and size, suggesting not only heritability, but more importantly that these traits are susceptible to artificial and natural selection (Varian and Nichols 2010). Similarly, significant single nucleotide polymorphisms (SNPs) associated with body shape and fin position have been identified in Atlantic salmon, Salmo salar (Boulding et al. 2008). Colouration is also thought to have important consequences for fitness in salmonids. In juvenile salmonids, parr marks and body colouration have been suggested to play a role in crypsis, providing camouflage that may be important to help avoid predation (Donnelly and Dill 1984; Donnelly and Whoriskey 1993). As with morphological traits, body colour and markings are also influenced by both genetics and phenotypic plasticity. Coho salmon acclimated to tanks of different colour results in colour matching towards the tank background (Donnelly and Whoriskey 1991). When predation risk was tested in an arena matching the background colour of the acclimation tank, acclimated fish made up only 37% of the predation, whereas fish that were not colour matched accounted for 63% of the predation (Donnelly and Whoriskey 1991). This ability to adopt cryptic colouration has been demonstrated in multiple studies, showing that skin and fin colouration in salmonids is highly plastic in response to substrate colour and other 8 visibility-related attributes of the rearing environment such as brightness (Westley et al. 2013; Kasagi et al. 2020). On the other hand, there is also evidence of a genetic basis of variation in colour and body markings in salmon. For example moderately high heritability of skin colour and spottiness have been detected in rainbow trout (Oncorhynchus mykiss), which led the authors to conclude that these traits can be manipulated through selective breeding for aquaculture purposes (Kause et al. 2002). In addition, SNPs associated with both parr mark number and parr mark contrast have been identified in Atlantic salmon (Boulding et al. 2008). Hence, the ability of fish to exhibit variability in color may contribute to their survival in natural habitats by reducing predation, making it a trait that can be genetically selected for and aiding their adaptation to new environments through plasticity. Colouration and body morphology have been shown to covary in salmonids. For example, rainbow trout with more black spots were more dominant and more efficient feeders, resulting in larger body size (Rodríguez et al. 2019). In the same study, these differences in spotting and body weight were shown to have a positive genetic relationship (Rodríguez et al. 2019). Particularly clear examples of morphological and colour variation come from studies comparing domesticated and wild strains of salmonids (Solem et al. 2006; Pulcini et al. 2013). In general, domestication in salmonids tends to result in faster growing individuals with a characteristic body morphology including a deeper body, blunter head, and smaller eyes (Fleming and Einum 1997; Pulcini et al. 2013; Perry et al. 2021). These differences are so distinct that researchers have been able to use them to accurately classify domestic and wild Chinook salmon based on these characteristics (Wessel et al. 2011). Second generation hybrids were classified in the same study and were found to be morphologically intermediate between the domestic and wild strain, although they were more similar to the wild phenotype (Wessel et 9 al. 2011). Hatchery and domesticated fish have been subject to strong selection in an environment with minimal predation and a surplus of resources in which rapid growth and high aggression is favoured (Gjedrem 2000), and where selection is relaxed on other aspects of performance such as predator evasion and swimming ability (Fleming et al. 2000). Thus, when in an environment with both predation and intra- and interspecific competition, domesticated fish may not be able to compete effectively, despite often having growth advantages as juveniles. For example, one study examining overwintering of domestic-wild hybrids found that domestic and hybrid individuals performed so poorly that the study could not continue through a second winter (Mason et al. 1967). In general, hatchery and domestic fish likely are such poor performers due to being phenotypically mismatched to the natural environment (Skaala et al. 2012; Stringwell et al. 2014). To further examine the significance of variation in morphology and colour in salmonids, we took advantage of known phenotypic variation between a wild (Pennask) and domesticated (Fraser Valley) strain of rainbow trout to assess their performance in a semi-natural environment. The domesticated strain is particularly known for its aggressive behaviour, large girth, and fast rates of growth (FFSBC 2004; Gale 2019). The wild strain differs in these aspects, being typically much smaller at maturity, with a slow growth rate unless in a productive monoculture environment, and a more slender body shape (FFSBC 2004; Tymchuk and Devlin 2005). These differences have important ecological implications, especially in natural or semi-natural conditions with strong resource competition. Domestic trout with fast growth rates and aggressive behaviour, such as the Fraser Valley strain used in this study, tend to have higher rates of growth and survival, as they are better equipped to utilize limited food resources, and potentially act as predators towards slower growing individuals, such as the wild strain we used. However, faster growing individuals tend to be more susceptible to predation, and therefore 10 exhibit poorer growth and survival in habitats with high predation, which suggests a behaviorally mediated trade-off between rapid growth and predator avoidance (Biro et al. 2004, 2006; Tymchuk et al. 2007). We used a genetic approach to assess the importance of variation in body morphology and colouration in natural environments by generating four F2 families from crosses between the Fraser Valley Domestic and Pennask trout strains and rearing them from the alevin stage in a semi-natural ponds with competition and predation. We then assessed the morphological and colour phenotypes of the surviving individuals after 6 months under these conditions. In hatchery environments, F2 offspring of these strains have been shown to have phenotypically intermediate for growth relative to the two grandparental strains (Tymchuk and Devlin 2005), which has been suggested to be the result of additive genetic variation under the control of multiple genes. However, little is known about other morphological phenotypes of such crosses or the phenotypes of these fish when reared in natural environments. The phenotypic distributions in an F2 cross between divergent lines have the potential to provide information about the underlying genetic basis of the phenotype. When two divergent strains are crossed, we do not expect to see an increase in the phenotypic variance in the F1 generation because all of the F1 offspring should be heterozygous at loci that are differentiated in the parental strains, as they will carry one allele from each divergent parent. However, different patterns can be observed in the F2 generation as a result of combination (Wright 1968; Lande 1981).For polygenic traits controlled by multiple loci, the F2 generation would be expected to show the same variation as the grandparental strains and the F1s, but if the trait is controlled by a small number of genes, the F2s would exhibit the full spectrum of phenotypes between the two grandparental strains, with an approximately normal distribution, resulting in a greater degree of 11 phenotypic variation. However, this pattern is only expected if the genetic effects are largely additive and there is limited phenotypic plasticity or environmental selection. However, strong selection in a natural environment might be expected to result in an F2 population with a much narrower range of phenotypes than is observed in the parental populations, and thus reduced phenotypic variation. Alternatively, hybrids can display a phenomenon known as transgressive segregation in which phenotypes more extreme than those of the parental lines are observed (Rieseberg et al. 1999). In addition, natural and hatchery environments differ in many respects, and phenotypic plasticity could give rise to phenotypes in F2s reared in natural environments that differ from those of grandparental lines reared in a hatchery. Thus, phenotypic mean and variance in F2s reared in natural environments can provide clues as to the roles of phenotypic plasticity, selection, and genetics in determining body shape and colouration. 2.2 Materials and Methods 2.2.1 Experimental animals Four families of F2 wild/domestic hybrids were created as a cross from grandparental strains Pennask rainbow trout and Fraser Valley domestic rainbow trout (Oncorhynchus mykiss). The F2 hybrids were ponded as alevin in April 2020 in the UBC experimental ponds. These ponds act as semi-natural, unmanipulated systems that simulate a normal wild ecosystem that these fish would inhabit including natural food and the presence of avian and invertebrate predators, although no other fish are present in these ponds. They are 25 m x 15 m, with a linear depth gradient descending to 6 m. Individuals were introduced to two ponds, 5000 into pond 11 and 5000 into pond 12, with representatives of each family in each pond which allows the ponds to be treated as replicates. Fish remained in the experimental ponds for six months until September 2020 when they were recaptured by minnow traps and fyke nets. 133 fish were recaptured from pond 11 and 169 fish were recaptured from pond 12. Following hypoxia trials 12 (which were performed in the context of a different study), all fish were euthanized by lethal anesthesia with MS-222 (0.5g.ml-1 buffered with equal parts sodium bicarbonate), weighed, measured and photographed. All experiments were performed under UBC Animal Care and Use Protocol number A16-0329. 2.2.4 Photo analysis Photos of grandparental strain individuals (described above) from the hatchery were taken in January 2021 and photos of juvenile F2 offspring from the ponds were captured in September 2020 on an iPhone 12 Mini, alongside an Xrite Colorchecker Classic. Although the data for grandparental and F2 individuals were taken in different years and at different times of the year, the grandparentals were approximately the same age at the time of sampling as the F2s were that were sampled earlier. Photos were taken using a tripod located directly above samples at a distance of 24 inches. All photos were taken within 2 min of anesthesia. The photos were then imported into DaVinci Resolve 16 media software using the following settings: 3840 x 2160 Ultra HD timeline resolution, UHD 2160p 60 video format. Photos of the F2 individuals were taken under a blue awning, resulting in a non-natural colour and white balance (Figure 2.1). Thus, correction was needed to ensure accurate colour measurements were being taken. Global white balance correction and colour normalization were then performed using the integrated colour match function under the following settings: Rec.709 source gamma, Rec.709 target gamma, Rec.709 colour space, 6500K white balance, 0.9 white level. The same corrections were performed on photos of the grandparental strains to ensure homogeneity in treatment. The adjusted files were then moved to ImageJ for analysis. 13 Figure 2.1. Comparison of original photo (left) with the processed photo corrected for white balance and colour. 2.2.3 Morphometry and parr mark analysis Morphometric analysis (Anumudu 2015; Savriama 2018) was performed on photos of the two grandparental groups (Fraser Valley domestic and Pennask wild) as well as the F2 offspring using a modified method based on Fenkes et al (Fenkes et al. 2018) and thin plate spline (TPS) programs (tpsDig, tpsRelw) (Park et al. 2013) to identify any traits that may be morphologically divergent between the two strains. Landmarks (x/y coordinates) were placed digitally over photos of the fish, and linear measurements were taken between them. Landmarks were chosen based on Fenkes et al. (Fenkes et al. 2018) and Anumudu et al. (Anumudu 2015) with four landmarks added on the high and low edges of the eye, and the top and bottom of the head directly adjacent (Figure 2.2). Measurements between landmarks were performed in R using the geomorph package (Baken et al. 2021; Adams et al. 2022). All linear measurements were normalized to 14 body size so they could be compared. Because fish were not the same size, I wanted a ratio that could be directly compared between individuals regardless of size. Ratios calculated were (1) normalized eye size (eye height relative to head height), (2) body ratio (body depth relative to body length), (3) caudal ratio (caudal peduncle depth relative to body length), and (4) head angle (angle between bottom of jaw and top of snout). The landmarks were then used to generate a consensus shape for each group (wild grandparental, domestic grandparental, Pond 11 F2s, Pond 12 F2s) which the geometry of each individual was compared against. A consensus wireframe is generated as the average shape of the rotated and size scaled coordinates of the individuals; in other words, it is the average shape of the population. The same image analysis was then performed using the same landmarks on the two populations of F2 offspring (Pond 11 and Pond 12). By comparing the fish body shape of the F2 individuals to that of the grandparental group, we may be able to classify F2 individuals as resembling the morphology of one of the two grandparental strains. Figure 2.2. Positions of landmarks used for geometric morphometrics in rainbow trout. Red dots indicate the position of landmarks placed on the body. An analysis of the parr marks was also performed using the colour corrected photos. After correction in DaVinci Resolve, photos were moved to FIJI (ImageJ) which was used to measure 15 parr mark size, number and colour. Parr marks were selected manually on each fish using an ellipse tool, and selections were added to the region of interest (ROI) manager for analysis. Ellipses were placed using the top, bottom, and sides of each mark as borders. Scale was set on each image individually using the rule on the Colorchecker. A measurement macro within FIJI was then used to measure the median, minimum, maximum, and standard deviation of the pixel values within each ROI for each RGB channel. I also measured the parr mark area in mm2 using across all ROI. Results were exported to a .csv file which was then cleaned and visualized in Python. 2.2.4 Statistical Analysis A principal component analysis (PCA) was performed on the linear measurements of body shape and parr mark data of the grandparental-strain individuals using custom scripts in Python; this was to determine if there was any differentiation between the grandparental strains, before adding the data of the F2s which was expected to be intermediate in most cases. An analysis of body shape and parr mark data was then performed using PCA. This PCA was fitted (trained) using the grandparental data, after which the data from the F2s were projected into the transformed space, in order to compare the distribution of F2 data to the distribution of the grandparental data. There were multiple families within the dataset and family identity is unknown, which leads to potential issues of pseudoreplication artificially inflating statistical power and p-values. Therefore further statistical analyses were not performed and groups are compared qualitatively. 16 2.3 Results 2.3.1 Differences in morphology between wild and domestic strains of Rainbow trout Consensus shapes for the grandparental strains differed substantially in terms of body depth (girth) and head shape (Figure 2.3). The Pennask wild strain was much more streamlined or dart shaped, whereas the Fraser Valley domestic strain was much blunter and fatter across the middle. Additionally, in the Pennask wild strain the eye was much lower on the head compared to the Fraser Valley strain (Figure 2.3). Figure 2.3. Wireframe comparison of average shape of Fraser Valley (top) and Pennask (bottom) strains of rainbow trout. Arrow A emphasizes the difference in distance from the lateral line of the fish to the bottom of the stomach. Arrow B emphasizes the difference in distance from the bottom edge of the eye to the bottom of the head. 17 2.3.2 Principal component analysis of variation in morphology and markings between wild and domestic strains of Rainbow trout Examining grandparental body shape and parr mark data together using PCA (Figures 2.4, 2.5), highlighted that the differences in morphology largely account for the separation between the two grandparental strains. PC1, which is the main component that separates the two strains and accounts for 59% of the variation in the dataset, primarily consists of body shape (normalized for body size). Individuals lower on PC1 are more square (i.e. deeper in body and shorter in length), while having blunter heads. Mean greyscale, normalized parr mark size, and eye size made up PC2, which accounts for 14% if the variation, did not appear to separate the groups. 18 Figure 2.4. Directional loadings of principle components for PCA in Figure 2.4. Positively correlated with PC1 are body width, caudal width, and body length. Negatively correlated with PC1 is head angle. Positively correlated with PC2 is normalized parr mark area, and negatively correlated is parr mark lightness. bodyW caudalW bodyL Head angle Eye height Parr mark area Parr mark lightness 19 Figure 2.5. PCA comparing both parr mark measurements and body dimension data from grandparental strains Pennask (pn) and Fraser Valley (fv). 2.3.3 Variation in morphology and markings between F2 crosses and grandparental strains Adding the data collected for body shape and parr mark lightness from the F2s to the grandparental PCA, there is a clear separation between the grandparental strains and the F2s. This separation is primarily on PC1 which consists of the body shape attributes head angle (bluntness) increasing as PC1 decreases, while head ratio (eye size relative to head size) caudal ratio (caudal depth relative to body length), body ratio (body depth relative to body length), and parr mark area normalized to body length increase as PC1 increases. Parr mark size increases with PC2, while parr mark lightness is negatively correlated with PC2. 20 Figure 2.6. PCA of grandparental strains (fv and pn) with length and parr mark data from F2s projected into the transformed space. 2.3.4 Traits that distinguish F2 pond fish from the grandparental hatchery strains As outlined above, several traits were drivers of separation between F2 pond fish and hatchery fish from the grandparental strains in the PCA. The grandparental PN individuals tended to be longer than the FV, although the FV were deeper through the body based on the visualized data (Figures 2.7A, B). F2s from pond 11 and pond 12 had similar distributions of body length to the grandparental FV individuals (Figure 2.7A). Fish from ponds 11 and 12 were similar, having means of 4.27 0.73 cm, and 4.44  0.56 cm respectively. The PN group had a mean of 6.2  1.1 cm, and the FV had a mean of 4.0  0.5 cm, placing the F2s between the two grandparental distributions. 21 The distributions of body depth were also different between the four groups, with the F2 groups having a similar, low body depth. FV fish were slightly thicker, with PN fish being the deepest, but also the longest (Figure 2.7B). Fish from ponds 11 and 12 had similar means, with pond 11 having a mean of 0.88  0.1 cm, and pond 12 having a mean of 0.95  0.14 cm. This contrasts with both grandparental groups, with the PN having a mean of 2.55  0.48 cm, and the FV having a mean of 1.72  0.2 cm. The PN and FV had minimum body depth measurements of 1.39 and 1.48 cm respectively, placing the tail of their distributions 3 standard deviations away from the mean of either of the F2 groups. The body ratios of both grandparental groups compared to the F2s were larger, indicating fatter fish (deeper bodies versus their length) (Figure 2.7C). Pond 11 and pond 12 again were very similar, with mean ratios of 0.20  0.01, and 0.21  0.01 respectively. The grandparental groups were also very similar, with the FV having a mean ratio 0.43  0.02 and a minimum of 0.36, and the PN having a mean ratio of 0.41  0.02 and a minimum of 0.33. This places the body ratios of the grandparentals well outside 3 standard deviations from the means of the F2s. Similar results were observed in the caudal ratio measurements. Caudal ratios appeared similar between P11 and P12 groups, but very different from those of the FV and PN groups (Figure 2.8). Pond 11 and pond 12 both had mean ratios of 0.11  0.01, while the FV and PN groups had mean ratios of 0.60  0.02 and 0.59  0.02 respectively. This again indicates the grandparentals were much fatter than the F2s, in a similar trend to that of the body ratios. Head angles were larger in the pond raised groups, with FV and PN being slightly lower than P11 and P12 (Figure 2.9). P11 and P12 had mean head angles of 80.3  6.8, and 81.9  4.5 respectively. FV and PN had mean head angles of 63.6  6.0 and 60.2  4.9. While having 22 slightly overlapping distributions, the means of the grandparentals are 2 standard deviations lower than the means of the F2s. A. 23 B. 24 Figure 2.7. Distribution of body dimensions for Fraser Valley (fv), Pennask (pn), and pond 11 and 12 (p11, p12) individuals. A: body length for B: body depth. C: Body ratio (body depth relative to body length). C. 25 Figure 2.8. Distribution of caudal ratios (caudal width/ body length) for Fraser Valley individuals (fv), Pennask individuals (pn), and pond 11 and 12 individuals (p11, p12). 26 Figure 2.9. Distribution of head angles for Fraser Valley individuals (fv), Pennask individuals (pn), and pond 11 and 12 individuals (p11, p12). Relative parr mark size is a comparison of parr mark size to body length of the individual; in other words, it describes the proportional coverage of the body of each parr mark. Interestingly, the grandparentals had much larger parr marks than the F2s in both pond replicates. The Pennask individuals had the largest parr marks, although they were still quite similar to those 27 of the Fraser Valley individuals (Figure 2.10). The P11s and P12s had similar means of 0.015  0.01 and 0.015  0.008. The FVs had a mean of 0.097  0.04, and the PNs had a mean of 0.12  0.06. The means of the pond fish were roughly two standard deviations away from the means of the grandparentals, however the minimum parr mark sizes of the grandparentals were similar to those of the F2s. 28 Figure 2.10. Histograms comparing relative parr mark size (parr mark size normalized to body length) of the four groups. Fv: Fraser Valley, pn: Pennask, p11: pond 11, p12: pond 12. The remaining traits did not clearly distinguish F2 pond fish from the hatchery reared grandparental strains. See supplemental material. 29 2.3.5 Traits that exhibited altered variation in F2 pond fish Relative parr mark size (Figure 2.11) exhibited markedly reduced variation in the F2 pond raised fish compared to fish from the grandparental strains reared under hatchery conditions. The variance of both the pond groups (P11 and P12) were both less than 0.0001, although the PN and FV groups were markedly higher with variances of 0.004 and 0.002 respectively. The remaining traits did not exhibit any signs of significantly reduced variation in F2s compared to grandparentals. Most traits exhibited similar levels of variation in the F2s compared to the grandparentals, although eye size relative to head size exhibited higher variance in the F2s (Figure 2.11) In addition, head angle (bluntness) had somewhat higher variance in pond 11 than in pond 12, although neither had substantially higher variance than did the grandparental strains (Figure 2.9). 30 Figure 2.11. Distribution of normalized eye size for Fraser Valley (fv), Pennask (pn), and pond 11 and 12 (p11, p12) individuals. 2.3.6 Effects of body length on trait values A series of linear regressions of the different features against body length confirmed that body width and caudal width are likely the main phenotypes separating the pond fish from the grandparentals. Although the lengths of the pond fish were similar to the smaller grandparentals, 31 the corresponding widths were much smaller (Figures 2.11, 2.12). Additionally, the slopes of the grandparental regression appeared visually steeper, indicating that in the grandparentals, body and caudal widths scaled differently than in the pond fish. Figure 2.12. Regression of caudal width against body length. Figure 2.13. Regression of body width against body length. 32 Eye height and head height also appeared to be positively correlated with body length (Figures 2.13, 2.14), although these traits did not appear to strongly separate the groups. Figure 2.14. Regression of eye height against body length. Figure 2.15. Regression of head height against body length. 33 Finally, head angle was not influenced by body length within a group, although the pond fish were clearly separated from the grandparents (Figure 2.15). However, there was a significant regression when all strains were analyzed together. Given that Pennask fish were generally longer and had smaller head anglesthis effect of body size on head angle is likely a result of differences between the strains rather than an effect of body size per se. Figure 2.16. Regression of head angle against body length. 2.4 Discussion In this chapter I show that the grandparental Fraser Valley and Pennask strains differ in body shape and, to a lesser extent, in body markings when reared under common hatchery conditions, which suggests that variation in these traits has a genetic component. More strikingly, my data highlight the large differences in body morphology and markings between these captive-reared individuals and F2 crosses between these strains reared in a semi-natural environment, which could be due to either genetic effects or phenotypic plasticity. These data highlight the complex interplay between genetic factors and environment in shaping body morphology and markings in rainbow trout. 34 Principle component analysis of the data we collected revealed Fraser Valley and Pennask strains to be grouping somewhat discretely, being separated by primarily traits associated with body shape (body length, caudal depth, body depth). When the pond fish data was projected into the PC space, they grouped most closely to the Fraser Valley fish, but were still clearly a separate group. The two ponds grouped nearly identically, suggesting that any environmental differences between the two ponds had limited effects on the observed phenotypes. The Fraser Valley and Pennask rainbow trout strains differed in body shape, with the Fraser Valley individuals being slightly deeper through the midsection compared to their length, with a shorter, blunter head, whereas the Pennask individuals were more streamlined and narrower. The slopes of the regressions of body depth traits against body length were visually quite similar between the two strains, indicating that while their body shapes are subtly different, body length has a similar effect on body depth for both these strains. The Fraser Valley and Pennask strains have very different life histories and histories of selection. Fraser Valley is a domestic strain, raised for the purposes of aquaculture and hatchery supplementation, and which is thought to originate primarily from a California strain of rainbow trout. In contrast, while Pennask trout have also been stocked, they are a true wild strain from Pennask Lake in British Columbia, which is a region that has never been stocked, and thus there is thought to be no introduction of domesticated genetic material into this strain, which maintains its wild characteristics. The differences in body shape that I observed are consistent with comparisons between wild and domesticated salmonids more generally, as they show that domesticated fish generally have higher condition factor (fatter, less streamlined bodies) than do wild fish when reared under common hatchery conditions (Glover et al. 2009; Pulcini et al. 2013; Perry et al. 2021). The fact that these differences persist in a common environment across multiple generations strongly suggests that they are genetically based. Interestingly, growth hormone 35 transgenesis also increases body depth in salmonids (Devlin et al. 2001), although the effects are not as marked when the transgene is introduced into a wild strain versus a domesticated strain (Devlin et al. 2001). These differences in body morphology and streamlining may be important for individual level swim performance. For example, a recent review of 204 studies testing 34 species of fish found off the Iberian Peninsula concluded that while body length was the most important predictor of sustained aerobic swimming performance (Ucrit), body shape was also important (Cano-Barbacil et al. 2020). Body shape is highly variable across species and habitats, and is highly relevant to individual habitat choice, and aspects of survival such as feeding, predation, and spawning because of the fluid-body interactions that the individual animal will experience (Bensing et al. 2022). There were subtle differences parr mark size between the Fraser Valley and Pennask strains, although there were no differences in parr mark number. Because they were reared in the same environment (tanks), if parr mark attributes were entirely environmentally determined, we would expect the distributions to be the same across the two groups. The fact that they differ suggests a genetic effect that differs between the two strains. The ecological and evolutionary significance of these differences in unknown but could result in differences in crypsis between the two strains. In this experiment, the F2 pond replicate populations represent an environmental test of the success of crosses between the parental populations, which would be expected to result in a range of intermediary phenotypes. However, in the ponds, the fish were exposed to strong selection, as 5,000 alevin were released into each pond, and only 302 individuals were recaptured across both ponds (133 from pond 11 and 169 from pond 12), despite depletion netting. 36 Subsequent removal of all remaining fish (9 from pond 11 and 21 from pond 12) from the pond by introduction of rotenone confirmed that the depletion netting captured almost all of the surviving fish. In addition, the environment in the ponds differs substantially from that in a hatchery or laboratory setting in terms of food availability, intensity of competition, presence of predators, and differences in water flow and turbidity, which could result in changes in morphology due to phenotypic plasticity. Given the relatively low food availability in the ponds compared to ad libitem feeding in the hatchery, it is not surprising that the pond fish were much thinner for their body length than were their hatchery reared grandparents (Fig. 5C). Condition factor (a metric of “fatness” in fish) is well known to be influenced by feeding (Elvingson and Johansson 1993), and thus this morphological difference is likely the result of this phenotypic plasticity. On the other hand, variation in body morphology has been shown to have a genetic component in salmonids. For example, crosses between domesticated and wild strains of coho salmon produce F2s with intermediate mass and length, consistent with a strong additive genetic basis of these traits (Tymchuk et al. 2009). However, the data presented here are not consistent with an additive genetic basis, as the F2 generation expresses body shape traits that are well outside the range of phenotypes in the grandparental generation. This could potentially be due to a phenomenon termed “transgressive segregation”. Transgressive segregation is a phenomenon that is often observed in hybrids that can be caused by a variety of genetic factors (Rieseberg et al. 1999) - most commonly thought of as a result of the interaction of complementary genes fixed for alleles with opposite effects in the grandparental populations. However, given the extreme phenotypic plasticity known for condition factor in fish, the narrower body shape of the pond fish is much more likely to have been caused by differences in food availability between the ponds and the hatchery. 37 The pond fish also differed from their hatchery-reared grandparents in caudal ratio, being much narrower relative to their body length near the tail. Similar differences in caudal peduncle depth have been observed in wild versus captively reared coho salmon (Hard et al. 2000) suggesting (as was the case for body ratio) that this difference may be the result of phenotypic plasticity. In general, salmonids that live in habitats with higher water velocities tend to have deeper caudal peduncles than populations found in slower- or standing-water habitats (Pakkasmaa and Piironen 2000). For example, Drinan et al. performed a similar morphometric assessment of body shape in brown trout and Atlantic salmon, and found that changes in body length and depth correlated with different catchments with contrasting hydraulic environments (Drinan et al. 2012). In our experiment, the pond habitat is characterized by relatively still standing water, whereas hatchery tanks are maintained with substantial flow, so the morphological differences detected here are consistent with these observations. The pond fish also had a larger head angle (blunter head) than did their hatchery grandparents, although in this case there was some overlap in the phenotypic distribution between the grandparents and the F2 offspring. Head shape has been shown to be affected by hatchery rearing in coho salmon (Hard et al. 2000) and between both brown trout and Atlantic salmon in drainages with different flow characteristics (Drinan et al. 2012). Higher flow habitats were associated with a more streamlined head, which is consistent with the observation of blunter heads in the F2 trout reared in the static pond environment. Greater streamlining of both the body and head is thought to contribute to increased swimming performance in flow. Pond fish also had substantially larger eyes relative to their body size compared to the hatchery-reared grandparents. Variation in this trait may have a genetic component as domesticated Atlantic salmon have previously been shown to have a smaller eye size than wild 38 fish when reared under identical conditions, although when the parr were introduced to a natural environment, these differences were reduced (Perry et al. 2021), suggesting a gene by environment interaction. Indeed, other studies have emphasized the importance of phenotypic plasticity in this trait. For example, Drinan et al. suggested that larger eye size in parr is developed in response to turbid, low visibility environments or as a result of low nutrient availability (Drinan et al. 2012). This is consistent with the larger eye size observed in the F2 population in my experiment compared to the tank reared parental fish; which could be due to the decreased visibility in the experimental ponds versus the lab tanks. Eye size is a trait that has been shown to be important for fitness and overall success due to increased visual acuity and light sensitivity with larger eyes (Caves et al. 2017; Perry et al. 2021). One of the most apparent differences between the F2 and parental generations was the relative size of the parr marks. On the F2 individuals, the mean parr mark size relative to body length was 0.0145  0.0003 (pond 11) and 0.0157  0.0004 (pond 12), whereas for the parentals it was 0.097  0.002 for the Fraser Valley strain and 0.124  0.002 for the Pennask strain. This indicates that in the semi-natural pond environment, individuals making it through the summer growing season to the sampling period had very small parr marks relative to their body size, compared to the parental individuals that were sampled at the same lifestage. It is unclear whether this difference in parr mark size could be due to early developmental plasticity or environmental selection, but there is only limited evidence of a genetic basis of variation in this trait. For example, in Atlantic salmon variation in the most significantly associated quantitative trait loci could explain only than 10% of the variance of this phenotype (Pedersen et al. 2018). Parr mark size and number are thought to be important for crypsis and have been shown to correlate with the gravel “background” in streams in coho salmon (Donnelly 1985). 39 In addition to these differences in trait values between the pond-raised F2s and the hatchery-reared grandparent strains there were also differences in the shape of the phenotypic distributions for various traits. Some traits exhibited high variance in the F2s compared to the variance in the parentals. This was most significant in normalized eye size (eye size relative to head size); however, head angle (bluntness) also had a much higher variance in one of the ponds than the other groups, which were all fairly similar in variance, making this trait harder to interpret. In general, F2 hybrids are expected to display a broad phenotypic distribution for traits that are influenced by additive genetic variation. In addition, segregation of alternative alleles can cause an increase in variance if the studied trait is controlled by a small number of genes, and the F2s are a result of divergent parental lines (Lande 1981; Benowicz et al. 2020). However, neither of these explanations is likely account for the broader distribution of eye size in the F2 hybrids, because the two grandparental strains reared in the hatchery did not differ in eye size. It is possible that phenotypic plasticity in response to high turbidity, discussed above, may have resulted in more variable phenotypes in the pond fish. Other traits, especially those concerning overall body shape, had low variance in the F2s compared to the parentals. This is suggestive of either strong environmental selection or developmental plasticity resulting in a canalization of the phenotype. As mentioned above, differences in body shape are unlikely to be genetic in nature (save bluntness of the head), and are more likely determined by environmental factors such as nutrient availability and hydraulic forces. A particularly striking example of this phenomenon can be seen for parr mark size (Figure 2.10) in which the phenotypic distribution of parr mark sizes is extremely constrained and very similar between the two pond replicates, compared to the hatchery reared grandparental fish. As discussed above, parr mark size may be important for crypsis, which could indicate strong natural selection on this trait. Conversely, head bluntness was shown not to scale with body 40 length while clearly separating the four groups. This, taken with the other evidence suggest that head bluntness is genetically controlled without a significant environmental effect, and differs between strains. Overall, the data in this chapter are suggestive of strong environmental effects on morphological and patterning traits in rainbow trout that are consistent with some combination of natural selection and phenotypic plasticity. The observed differences in body morphology and markings between the Fraser Valley and Pennask strains, as well as the F2 crosses, could have ecological implications in their respective natural environments. For example, differences in body shape and streamlining could impact swimming performance and behaviour, potentially affecting feeding efficiency, predator avoidance, and spawning success. Differences in parr mark lightness and size could also impact crypsis and camouflage effectiveness, affecting the ability of individuals to avoid predators and ambush prey. In addition, the differences observed between captive and semi-natural environments raise questions about the potential impacts of hatchery-raised fish on wild populations. Domestication selection and phenotypic plasticity can lead to differences in morphology and behavior that may affect the fitness and success of hatchery-raised fish when they are released into the wild. This is particularly relevant for conservation efforts that rely on hatchery supplementation to enhance wild populations. Overall, understanding the genetic and environmental factors that shape morphology and behaviour in rainbow trout is important for managing and conserving this valuable species. Further research is needed to investigate the ecological implications of the observed differences and to assess the potential impacts of hatchery-raised fish on wild populations. 41 Chapter 3: Initial characterization of the genetics of variation in growth rate in coho salmon (Oncorhynchus kisutch) 3.1 Introduction Humans have been domesticating animals for millennia (Diamond 2002), and even the domestication of fishes has been ongoing for almost 10,000 years (Teletchea 2021). During domestication, the phenotype of the organism is typically altered over many generations as a result of natural or artificial selection (Devlin et al. 1999; Jhingan et al. 2003; Leggatt et al. 2016). The goal of domesticating captive fish is to modify selected traits over many generations to produce more adapted and productive individuals for commercial use. However, the use of domesticated fish can be extremely problematic in other contexts. For example, in conservation hatcheries, where domesticated broodstock (spawning adults) can be used to create offspring that are stocked into wild environments to supplement wild populations. These domesticated offspring are often phenotypically and genetically mis-matched with the wild environments they are introduced to and their mating with native fish has been shown to lower reproductive fitness in wild populations (Araki et al. 2007). Thus, understanding how domesticated organisms have been transformed from their wild progenitors can help us identify the genetic basis of important traits, to provide insight into evolutionary processes, and to yield practical information for future enhancement of agricultural strains and hatchery stocking. Aquaculture fish breeding programs have historically focused on improving growth through selection (Ali et al. 2020; Teletchea 2021), and growth rate has been demonstrated to rapidly change over generations. Thus, domesticated fish provide a useful model system in which to investigate the genetic basis of variation in growth rate. Indeed, this question has been intensively investigated in several species of salmonids, with the majority of studies conducted in 42 Atlantic salmon and rainbow trout. Multiple genome wide association studies have identified single nucleotide polymorphisms (SNPs) that are significantly associated with growth (Gutierrez et al. 2015; Tsai et al. 2015b,a; Yoshida et al. 2017; Reis Neto et al. 2019); however most SNPs indicate that growth related traits are intensely polygenic with the loci of greatest impact explaining around 3% of genetic variance (Tsai et al. 2015a; Yoshida et al. 2017; Reis Neto et al. 2019). There are eight species of domesticated salmonids used in aquaculture (Teletchea 2021), including coho salmon, which have also been selectively bred for aquaculture and hatchery purposes, although this domestication is relatively recent. Coho salmon were first introduced to aquaculture in the 1980s, and thus current strains have been in production for approximately 15 generations (Tymchuk et al. 2009). Fish culturists generally choose the largest and fastest growing individuals to produce future generations (Tave 1989), which results in strong selection for rapid growth. Thus, domestic coho are typically faster growing than their wild progenitors (Solberg et al. 2013). Fast-growing domestic families have also been shown to have a reduced antipredator response, compared to wild fish (Tymchuk et al. 2006a). Additionally, domestic coho have been shown to ingest more food when fed to satiation, and are more efficient at utilizing those extra resources relative to wild lines (Neely et al. 2008). Prior studies have detected a significant genotype effect (using familial data) on both length and mass (Tymchuk et al. 2006a; Neely et al. 2008). However, the underlying genetic basis of these differences in growth and behavior remains unknown. In this study we took advantage of the known differences in growth rate between wild and domesticated coho salmon to begin to explore the genetic basis of variation in growth rate in this species by using F2 offspring of a cross between a wild and domesticated strain of coho salmon. 43 In this chapter my objective was to assess the genetic basis of variation in growth rate between domesticated and wild coho salmon. 3.2 Materials and Methods 3.2.1 Animals Two crosses were made between grandparental strains Kitimat wild and Target domestic coho. Target was chosen as the domestic strain as it is derived from Kitimat and Kitimat only, whereas other domestic strains are thought to contain genetic contributions from an unknown number of wild or domestic strains. Two F2 families were then generated from these F1s. Of the two crosses, only one was chosen for genomic analysis, due to very few individuals remaining in the other. The families were reared separately in 4000L tanks in 10°C well water. The fish were fed with life stage appropriate commercial salmon feed and single tanks per family were used to avoid tank effects within a family. Rearing was conducted in accordance with Canadian Council on Animal Care guidelines under Fisheries and Oceans Canada Animal Use Protocol Ex. 7.1. 3.2.2 Geometric morphometrics Photos were taken of every F2 individual at time of sampling, when they were approximately one year old, which is the typical time of smoltification in this species. A DSLR was positioned on a tripod 24 inches above each sample, with a standard ruler next to the sample for scaling. Geometric morphometrics were performed using the photos of the F2 individuals in order to quantify phenotypes to try and define subgroups within the general population. Landmarks were placed according to a previous study on brown trout body geometry (Fenkes et al. 2018), and thin plate spline (TPS) programs (Park et al. 2013) were used to place landmarks and take geometric measurements that were used previously. These landmarks were used to find a consensus (average) shape which was visualized using warp plots (Figures 3.3B,C), which then 44 all the individuals were plotted against. The geometric measurement data were then further visualized using histogram and principal component analysis (PCA) plots. 3.2.3 DNA isolation and sequencing Two groups of individuals were defined using the results derived from the geometric morphometric data (see results). Therefore, we elected to use a Poolseq approach to identify genomic regions associated with these morphological differences which is a cost-effective method for sequencing of pooled DNA samples (Schlötterer et al. 2014). Genomic DNA was isolated from 30 of the fast-growing individuals and 40 of the slower growing individuals using a Qiagen DNeasy Blood and Tissue kit, and standardized to a concentration of 5 ng/ul (±20%) using Qubit fluorometric quantification to ensure equal genomic representation in the pool from each individual. The DNA was then pooled with a target of 25 ng of genomic DNA contributed to the pool from each sample, resulting in a DNA pool from the fast-growing group, and a second pool from the “typical” group. NEB Ultra II shotgun libraries were then constructed and sequenced by Genome Quebec on the NovaSeq 6000 platform, resulting in 500-800 million paired end reads per pool. 3.2.4 Bioinformatics The raw paired-end reads produced for the two pools were primarily aligned and analyzed using the PoolParty bash and R pipeline (Micheletti and Narum 2018). For the trimming and alignment step, the PPalign bash script was used using the following parameters: BQUAL: 20, MAPQ: 20, SNPQ: 20, MINLEN: 25, INWIN: 15, MAF: 0.05, MINDP: 20. Fst was then calculated using a non-overlapping sliding window (size 10,000bp with a step size of 10,000bp). Finally, regions that were highly differentiated compared to the rest of the genome 45 were used as the target of a gene ontology enrichment analysis using the GOrilla analysis tool (Eden et al. 2007, 2009). 3.3 Results 3.3.1 Morphometrics Body length and depth were first visualized using simple histogram plots at which point two distinct groups of individuals became apparent (Figure 3.1). These data were then visualized using singular value decomposition PCA (Figure 3.2) using length, width, and weight as variables. Both length and width appeared to contribute to the separation between these two groups equally, indicating that rather than body shape determining the groups, overall size is what was important. However, a consensus plot revealed a slight segregation of the fast-growing population compared to the slow growing population, indicating that a signal related to overall body dimension may also be present (Figure 3.3). Fast-growing individuals appeared to be deeper across their bodies relative to their length, with larger, rounded stomachs, relative to slower-growing individuals that were somewhat more streamlined in comparison. A. 46 Figure 3.1. A. Individuals belonging to the smaller sized distribution. B. Individuals belonging to the larger sized distribution. C. Histograms comparing counts of individuals against weight (g) and length (cm). B. C. 47 Figure 3.2. PCA plot of individuals using weight (g) and length (cm) as variables. Numbers represent sample number. 48 Figure 3.3. A. Plot of TPS warps relative to the consensus (plot centre). Red dots indicate fast growing individuals. B. Consensus warp of slow-growing individuals. Front of fish is on the left, A. B. C. 49 each dot represents a landmark. C. Consensus warp of fast-growing individuals. Front of fish is on the left, each dot represents a landmark. 3.3.2 Poolseq Three chromosomal regions of interest were identified due to their high Fst compared to the surrounding background Fst in the rest of the genome. These regions were in linkage groups 18, 19, and 24 (Figure 3.4). The three Fst peaks were quite wide and likely represent entire chromosome arms (Figure 3.5). Linkage groups 18 and 19 are both metacentric, while linkage group 24 is acrocentric with the centromere occupying approximately the first half of the chromosome (Kodama et al. 2014). Based on the position of the proposed centromeres (Kodama et al. 2014), the differentiated region of LG18 is likely the lower arm and part of the centromere. The differentiated region of LG19 is likely the p-arm of the chromosome, as well as the entire centromere and a small section of the q-arm. The differentiated region of LG24 is likely the entire arm as well as a large portion of the centromere. Figure 3.4. Manhattan plot of all linkage groups sequenced. Arrows highlight highly differential regions on LG18, LG19, and LG24. 50 Figure 3.5. Manhattan plots of single linkage groups 18, 19, and 24. LG18 LG19 LG24 51 3.3.3 Functional Enrichment A gene ontology enrichment analysis targeting the differentiated areas of linkage groups 18, 19, and 24 found significant enrichment for a number of pathways (P-value < 10-3). Genes in the differentiated region of linkage group 18 were enriched for folic acid-containing compound metabolic process, folic acid transport, folate transmembrane transport, and folate import across plasma membranes. The GO analysis specifically identified two genes in this region: folate receptor 2 (folr2) and a folate carrier (slc46ai) (Figure 3.6). The high Fst region of linkage group 19 was enriched for muscle cell fate commitment, positive regulation of myoblast differentiation, positive regulation of myotube differentiation, and positive regulation of skeletal muscle tissue and fiber development (Figure 3.7). Two genes were identified by the analysis within this region: myogenic factors 5 and 6 (myf5, myf6). The differentiated region of linkage group 24 was enriched for omega peptidase activity (Figure 3.8), and two more genes were identified: acylaminoacyl-peptide hydrolase (apeh) and gamma-glutamyltransferase 7 (ggt7). 52 Figure 3.6. Enriched processes in the differentiated region on LG18 (highlighted boxes are processes that are significant at P<10-3). 53 Figure 3.7. Enriched processes in the differentiated region on LG19 (highlighted boxes are processes that are significant at P<10-3). 54 Figure 3.8. Enriched processes in the differentiated region on LG24 (highlighted boxes are processes that are significant at P<10-3). 55 3.4 Discussion 3.4.1 Chromosome regions associated with increased growth One of the two F2 crosses between a wild and domestic strain of coho salmon resulted in a highly bimodal phenotypic distribution, with a subset of individuals attaining much larger size as juveniles (Figures 3.1 and 3.2). These fast-growing fish were similar in terms of body shape to the slower growing fish, although TPS analysis revealed a slight difference between the body shapes of the two groups, with the larger group also being somewhat fatter (Figure 3.3A). However, the difference in body shape was small, and the PCA suggests that body size is still the main factor driving the separation (Figure 3.2). Pooled whole-genome sequencing revealed that three chromosome regions were highly differentiated between the two groups: linkage groups 18, 19, and 24 (Figures 3.4 and 3.5). A gene ontology analysis elucidated that these regions all play roles in cellular development and multiplication. Taken together these data confirm the highly polygenic nature of growth traits in salmonids. A recent study in farmed coho salmon utilized a high density SNP chip to identify signatures of domestication selection (López et al. 2021). They identified significant SNPs on 10 linkage groups: 5, 6, 14, 15, 17, 18, 22, 26, 28, and 29. Only LG18 overlaps with my analysis, however interestingly, LG18 was one of the most significant signals in their study. Together with the evidence presented here, may indicate that genes on LG18 are a strong driver of growth in coho. The populations of study animals used in this prior study (López et al. 2021) were two domestic populations of coho salmon that had been cultured in Chile, and that had been subjected to eight generations of artificial selection for growth rate (López et al. 2021). These two populations are thought to be derived principally from two original broodstocks, one from the Kitimat river, BC and one from Oregon. Thus, they share some ancestry with the stocks used 56 here, which are wild Kitimat fish and a domesticated strain derived solely from the Kitimat wild stock. We detected functional enrichment for processes related to folate acid transport and metabolic process on linkage group 18. Because fish cannot produce folic acid themselves, they rely entirely on dietary folic acid, which is absorbed in the upper part of the small intestine (Jamalzad Falah et al. 2020). Thus, this pathway is especially relevant to growth performance (Ramamoorthy and Verma 2008). For example, supplementation with folic acid has been shown to improve growth performance in fingerling Siberian sturgeon (Acipenser baerii) and freshwater prawn (Macrobrachium rosenbergii) (Asaikkutti et al. 2016; Jamalzad Falah et al. 2020). In Atlantic salmon, key genes belonging to the folate cycle (shmt2, mthfd1l, mthfd2-like, and mtdclike), similar to folr2, were shown to be downregulated in fish fed a surplus of methionine, folic acid, and vitamins B6 and B12. The authors suggest that because methionine is key for protein synthesis, fish not fed a surplus must compensate via upregulation to meet the demand for growth (Adam et al. 2022). Furthermore, mthfd1l is present in the differentiated region of LG18. Taken together, this evidence suggests that folate receptor genes could be involved in variation in growth rate in coho salmon. However, these genes were not detected in the prior study of signatures of selection in coho salmon (López et al. 2021), and thus other genes on this chromosome arm could be important. The differentiated region of linkage group 19 that we identified was enriched for processes associated with cellular development, namely muscle and myotube generation. These processes likely encompass genes similar to known growth factor-producing genes such as insulin-like growth factor 1 (igf1) and 2 (igf2), growth hormone receptor (ghr), and thyroid hormone receptor (thr). Of these genes, a BLAST indicates that igf1 is present in the 57 differentiated region of LG19, while also annotated on LG9, but the other genes are elsewhere in the genome. This suite of genes has control over when precursor muscle cells proliferate or differentiate into myotubes. The myogenic factors (myf5/6) identified on linkage group 19 have also been annotated in humans (Cupelli et al. 1996; Roy et al. 2002), and have also been mapped across multiple Salmoninae genera (Moghadam et al. 2007). Myf5 is critical for muscle development, and when silenced, completely disrupts muscle formation, whereas myf6 is a downstream regulator determining terminal differentiation (Sun et al. 2015). A study in Korean cattle identified a SNP genotype in myf5 that was found to have a significant effect on both weight after 12 months and rate of weight gain, with some animals being heavier and gaining weight faster than others (Chung and Kim 2005); a result not dissimilar to the difference in growth in the population used in this experiment. A similar association was found in chickens (Yin et al. 2011), as well as a myriad of other studies in cattle and pigs that also found increases in body size, weight, and muscle quality (Te Pas et al. 2000; Zhang et al. 2007; Zhao et al. 2020). Myf5 was also shown to be upregulated in fast-growing domestic and full-fed transgenic coho salmon, with a significant difference compared to wildtype and ration-restricted transgenic coho salmon (Overturf et al. 2010). A second study in Atlantic salmon fingerlings showed that increased photoperiod in a hatchery setting correlated with faster growth, with a sharp increase in myf5 expression after three months of continuous light (Churova et al. 2020). In the future, more specific experiments should be done to investigate myf5 expression specifically in salmon at different stages of growth and development. Additionally, an assay could be completed to determine which myf5 allele is present in the fast-growing group in this study, compared to the slow-growing group. The specific genes identified in the GO analysis on LG24 have been shown to be related to response to oxidative stress (ggt7) and immune function (apeh) in humans. That being said, 58 omega peptidase activity was the only process identified as significantly enriched on LG24. Peptidases can play a key role in protein turnover, and thus their function is plausibly related to growth rate. Indeed, a recent genome-wide associated study (GWAS) in rainbow trout identified several peptidases as candidate genes associated with growth (Ali et al. 2020). One similar peptidase to the ones identified by Ali et al. was found in the peak of LG24 (slc35a2), which when mutated in humans, can cause failure to grow or gain weight (Ali et al. 2020). Additionally, although it was not specifically identified by the GO analysis, the peak on LG24 also contains bgn, a biglycan coding gene related to bone growth, muscle development/regeneration, and collagen fibril assembly in muscle tissues (NM_001711.6), further indicating that this region may be associated with increased rates of growth. This might indicate that there are further, more important loci in this region that will become clear as analyses and annotation of gene function progress. 3.4.2 Implications for aquaculture and hatchery management My results confirm the polygenic genetic architecture of variation in growth rate, as there is not a single clear locus associated with the dramatic variation in growth phenotype that I observed. That being said, multiple genes identified as potential candidates in this study have been previously associated with increased growth and muscle quality in fish, as well as in other terrestrial, agricultural species. Most interestingly, the genes identified on LG19 were previously shown to be extremely significant determinants of growth rate, as well as muscle quality in multiple different genera. While they have not been studied in aquatic species, based on this data I demonstrate that there function likely carries over, and justifies a study comparing gene expression and growth across populations with differential SNPs. In addition, the differentiated region I identified on LG18 is likely to encompass several genes in addition to the ones identified in this study affecting the growth phenotype. 59 As a result of the highly complex and polygenic nature of growth as an overall phenotype being selected for, aquaculture and hatchery managers should be aware of how difficult it may be to specifically select for a highly polygenic trait such as growth, without affecting other processes. Additionally, it will prove difficult to identify which alleles are desirable, as many genes are responsible for producing this trait. Attempting to isolate and select for increased growth may result in decreased genetic diversity, and thereby increased susceptibility to disease or change in environmental factors. Therefore, it is important that managers work to maintain genetic diversity in order to keep their populations healthy and resilient. 3.4.3 Limitations and future directions In the future, a comparative GWAS between populations of fast growers and typical growers focusing on these regions with individual level resolution may prove beneficial. A major drawback of my approach is the inability to tease apart the subtle, more nuanced phenotypes genetically. Although my study groups differed significantly, there are sure to be subtler phenotypic differences among and between them. Additionally, a transcriptomic approach may be useful focusing specifically on the genes identified in this study, surveyed at different stages of development, and under different conditions of growth (e.g., feeding level, light exposure, etc.). 60 Chapter 4: General Discussion and Conclusion 4.1 Thesis Summary Salmonids are a commonly utilized resource for commercial aquaculture as well as use in stocking for conservation and recreation. Due to factors such as historic overharvesting, habitat change or loss, and climate change, the future of our wild populations of salmonids is threatened. Because of this, supplementation of wild populations has become commonplace in most regional conservation programs. However, as research shows that even a single generation of hatchery rearing actively changes the phenotype of these fish, it is of paramount importance that we understand the implications of releasing phenotypically different fish into a wild population. For example, questions have been raised such as how the competitive interaction between hatchery and wild fish will change the wild phenotype, and even more importantly, whether introgression of domestic alleles to a wild population could have a downstream impact on the fitness of the population overall. In my first chapter I investigated the body shape and parr mark patterns of F2 hybrids produced between a domestic and wild strain of rainbow trout, and then compared it to the same measurements taken from the parental strains. This represented a natural environmental test of potential domestic-wild hybrid phenotypes outside of a hatchery or lab environment. One of the most striking observations from this chapter was that, parr mark size in the pond-raised F2 fish did not follow the same distribution of variance as the tank-raised parental generation, and the means of the F2 pond fish differed greatly. This indicates that parr mark size is not influenced by a small number of genes and is instead more likely controlled by early developmental plasticity and environmental factors such as nutrient availability and predation. Next, I found eye size and head bluntness to have significantly higher variance in the F2s compared to the parentals. I inferred from this result that they are more likely to be genetically influenced than environmentally influenced. This contradicts Bernard Perry et al. (Perry et al. 2021) who argued 61 that eye size is more likely to be environmentally controlled. However, due to a difference in rearing and sampling conditions of the F2s, I believe that eye size is genetically controlled, but the rearing environment (i.e., differing hydraulic factors) may influence the extent to which the phenotype is controlled. In other words, I hypothesize that in standing water eye size is primarily determined genetically, whereas in moving or turbid water, the trait is strongly influenced by the environment. I also observed substantial differences in body shape between the parental strains and F2s, but I suggest that this observation is likely that the result of environmental factors such as nutrient availability and hydraulic forces were more important in shaping these traits. That being said, it is possible that genetic differences in behaviour between domestic and wild strains that have been previously described account for the differences in body shape and size I described between the wild and domestic parents. However, these differences were not apparent in the F2s, with a small amount of variance in the pond fish as compared to the parents. Parr mark colour saturation/lightness was also compared between the F2s and the parentals. The means of both pond replicates differed significantly from both parental strains, although less so compared to the Pennask wild strain. I inferred from this that the F2s, while still an intermediate phenotype, were converging on a phenotype more similar to that of the wilds when introduced to a natural environment, which could either indicate a semi-dominant genetic contribution from the Pennask strain, or some form of environmental selection. In my second chapter I investigated variation in size within a family of F2 domestic-wild hybrid coho salmon. Within this family of F2 hybrids, there was a distinct differential growth phenotype, where a small number of salmon had grown extremely quickly compared to the overall population. Using PoolSeq, I found three regions of the genome in the F2s that had high Fst between fast and slow growing fish, indicating an allelic difference in these areas. A gene ontology enrichment analysis uncovered enrichment for pathways including positive regulation 62 of skeletal muscle tissue development, transmembrane folate transport, and omega peptidase activity. Looking closer at the genes in these regions, two main genes of interest were found: MYF5 and MYF6. Although not described in fish, in other agricultural animals such as cows, pigs, and chickens, an allelic variant is described that induces increased rates of weight gain, body size, and muscle quality. This genotype, if present in these coho, may explain why they had such an increased rate of growth compared to the typical salmon. This would hold relevance to both commercial aquacultures, as well as conservation. Understanding the genetic architecture influencing growth obviously holds relevance to hatchery breeding programs, as when rearing fish for the purposes of supplementation of wild stock, to maintain as close to a wild phenotype (and genotype) as possible. That being said, the results of my first chapter indicate that at least in the short term, the rearing environment plays a much greater role in shaping the phenotype than does the genotype. In other words, although these fish may be able to grow faster, in the absence of proper nutrient supply, they may still develop normally, or may even be disadvantaged if these genotypes are costly in another way. 4.2 Limitations and Future Directions 4.2.1 Chapter 2 Due to the lack of genotyping in this chapter, a genome wide association study should be performed to investigate any correlations between specific SNP loci and the traits identified to be likely genetically influenced. Additionally, it would be interesting to raise F2 domestic-wild hybrids in lab conditions, to see what extent the variance of the phenotypes change, compared to the natural conditions. In the same way, raising the parental strains in natural conditions and quantifying these traits when environmental selection is present compared to when they are in 63 tanks may also elucidate to what extent the pond environment is driving phenotypic development. Finally, since based on these results rearing environment is likely the main driver of these phenotypes, rearing juveniles in different hydraulic flow rates and turbidity, then quantifying morphology in a similar way may be interesting. 4.2.2 Chapter 3 The main limitation of any PoolSeq analysis is the lack of resolution at an individual level. This means that it is harder to discern a genotype corresponding to any subtle or individual level phenotype. However, as I was focusing on a very distinct phenotype, this is not necessarily a disadvantage for my analysis. This analysis was performed on samples taken in 2019, and unfortunately, I did not have tissue samples from the original parentals. Because of that, genotypes for the parental strains were unavailable. In the future, SNP genotyping should be performed on members of the parental strains to determine if the genotype that the fast-growing group possesses is unique to one of these two strains. 64 Bibliography Adam, A. C., T. Saito, M. Espe, J. M. D. O. Fernandes, V. Vikeså, and K. H. Skjærven. 2022. Metabolic and molecular signatures of improved growth in Atlantic salmon (Salmo salar) fed surplus levels of methionine, folic acid, vitamin B6 and B12 throughout smoltification. Br. J. Nutr. 127:1289–1302. Cambridge University Press. Adams, D. C., M. L. Collyer, A. Kaliontzopoulou, and E. K. Baken. 2022. Geomorph: Software for geometric morphometric analyses. R package version 4.0.4. Ali, A., R. Al-Tobasei, D. Lourenco, T. Leeds, B. Kenney, and M. Salem. 2020. Genome-wide identification of loci associated with growth in rainbow trout. BMC Genomics 2020 211 21:1–16. BioMed Central. Anumudu, C. 2015. Advanced Techniques for Morphometric Analysis in Fish. J. Aquac. Res. Dev. 06:6–11. Aparicio, E., E. García-Berthou, R. M. Araguas, P. Martínez, and J. L. García-Marín. 2005. Body pigmentation pattern to assess introgression by hatchery stocks in native Salmo trutta from Mediterranean streams. J. Fish Biol. 67:931–949. John Wiley & Sons, Ltd. Araki, H., B. Cooper, and M. S. Blouin. 2007. Genetic effects of captive breeding cause a rapid, cumulative fitness decline in the wild. Science 318:100–103. Science. Arostegui, M. C., and T. P. Quinn. 2019. Ontogenetic and ecotypic variation in the coloration and morphology of rainbow trout (Oncorhynchus mykiss) in a stream–lake system. Biol. J. Linn. Soc. 128:681–699. Oxford Academic. Asaikkutti, A., P. S. Bhavan, and K. Vimala. 2016. Effects of different levels of dietary folic acid 65 on the growth performance, muscle composition, immune response and antioxidant capacity of freshwater prawn, Macrobrachium rosenbergii. Aquaculture 464:136–144. Elsevier. Baken, E. K., M. L. Collyer, A. Kaliontzopoulou, and D. C. Adams. 2021. geomorph v4.0 and gmShiny: enhanced analytics and a new graphical interface for a comprehensive morphometric experience. Balon, E. K. 2004. About the oldest domesticates among fishes. J. Fish Biol. 65:1–27. John Wiley & Sons, Ltd. Beamish, R. J., R. M. Sweeting, K. L. Lange, D. J. Noakes, D. Preikshot, and C. M. Neville. 2010. Early Marine Survival of Coho Salmon in the Strait of Georgia Declines to Very Low Levels. Mar. Coast. Fish. 2:424–439. Benowicz, A., M. Stoehr, A. Hamann, and A. D. Yanchuk. 2020. Estimation of the F2 generation segregation variance and relationships among growth, frost damage, and bud break in coastal Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) wide-crosses. Ann. For. Sci. 77:28. Bensing, K., J. A. Tuhtan, G. Toming, · Ali, H. Khan, and B. Lehmann. 2022. Fish body geometry reduces the upstream velocity profile in subcritical flowing waters. 84:32. Binford, L. 1968. New Perspectives in Archaeology. Biro, P. A., M. V. Abrahams, J. R. Post, and E. A. Parkinson. 2006. Behavioural trade-offs between growth and mortality explain evolution of submaximal growth rates. J. Anim. Ecol. 75:1165–1171. John Wiley & Sons, Ltd. Biro, P. A., M. V. Abrahams, J. R. Post, and E. A. Parkinson. 2004. Predators select against high growth rates and risk-taking behaviour in domestic trout populations. Proceedings. Biol. Sci. 66 271:2233–2237. Proc Biol Sci. Boulding, E. G., M. Culling, B. Glebe, P. R. Berg, S. Lien, and T. Moen. 2008. Conservation genomics of Atlantic salmon: SNPs associated with QTLs for adaptive traits in parr from four trans-Atlantic backcrosses. Heredity (Edinb). 101:381–391. Bradford, M. J., and J. R. Irvine. 2011. Land use, fishing, climate change, and the decline of Thompson River, British Columbia, coho salmon. https://doi.org/10.1139/f99-283 57:13–16. NRC Research Press Ottawa, Canada . Brown, L. R., P. B. Moyle, and R. M. Yoshiyama. 1994. Historical Decline and Current Status of Coho Salmon in California. North Am. J. ofFisheries Manag. 14:237–261. Cano-Barbacil, C., J. Radinger, M. Argudo, F. Rubio-Gracia, A. Vila-Gispert, and E. García-Berthou. 2020. Key factors explaining critical swimming speed in freshwater fish: a review and statistical analysis for Iberian species. Sci. Rep. 10. Nature Publishing Group. Caves, E. M., T. T. Sutton, and S. Johnsen. 2017. Visual acuity in ray-finned fishes correlates with eye size and habitat. J. Exp. Biol. 220:1586–1596. Company of Biologists Ltd. Chung, E. R., and W. T. Kim. 2005. Association of SNP Marker in IGF-I and MYF5 Candidate Genes with Growth Traits in Korean Cattle. Asian-Australasian J. Anim. Sci. 18:1061–1065. Asian-Australasian Association of Animal Production Societies. Churova, M. V., N. Shulgina, A. Kuritsyn, M. Y. Krupnova, and N. N. Nemova. 2020. Muscle-specific gene expression and metabolic enzyme activities in Atlantic salmon Salmo salar L. fry reared under different photoperiod regimes. Comp. Biochem. Physiol. Part B Biochem. Mol. Biol. 239:110330. Pergamon. 67 Cupelli, L., B. Renault, J. Leblanc-Straceski, A. Banks, D. Ward, R. S. Kucherlapati, and K. Krauter. 1996. Assignment of the human myogenic factors 5 and 6 (MYF5, MYF6) gene cluster to 12q21 by in situ hybridization and physical mapping of the locus between D12S350 and D12S106. Cytogenet. Cell Genet. 72:250–251. Cytogenet Cell Genet. Devlin, R. H., C. A. Biagi, T. Y. Yesaki, D. E. Smailus, and J. C. Byatt. 2001. Growth of domesticated transgenic fish. Nat. 2001 4096822 409:781–782. Nature Publishing Group. Devlin, R. H., J. I. Johnsson, D. E. Smailus, C. A. Biagi, E. Jönsson, and B. T. Björnsson. 1999. Increased ability to compete for food by growth hormone-transgenic coho salmon Oncorhynchus kisutch (Walbaum). Aquac. Res. 30:479–482. John Wiley & Sons, Ltd. Diamond, J. 2002. Evolution, consequences and future of plant and animal domestication. Nat. 2002 4186898 418:700–707. Nature Publishing Group. Donnelly, W. A. 1985. THE ADAPTIVE SIGNIFICANCE OF STREAM COLOURATION: PARR MARK PATTERNS AND CRYPSIS IN COHO SALMON (ONCORHYNCHUS KISUTCH). Donnelly, W. A., and L. M. Dill. 1984. Evidence for crypsis in coho salmon, Oncorhynchus kisutch (Walbaum), parr: substrate colour preference and achromatic reflectance. J. Fish Biol. 25:183–195. Donnelly, W. A., and F. G. Whoriskey. 1991. Background-Color Acclimation of Brook Trout for Crypsis Reduces Risk of Predation by Hooded Mergansers Lophodytes cucullatus. North Am. J. Fish. Manag. 11:206–211. Donnelly, W. A., and F. G. Whoriskey. 1993. Transplantation of Atlantic salmon (Salmo salar) and crypsis breakdown. Can. Spec. Publ. Fish. Aquat. Sci. 25–34. BOOKS EXPRESS. 68 Drinan, T. J., P. McGinnity, J. P. Coughlan, T. F. Cross, and S. S. C. Harrison. 2012. Morphological variability of Atlantic salmon Salmo salar and brown trout Salmo trutta in different river environments. Ecol. Freshw. Fish 21:420–432. John Wiley & Sons, Ltd. Duvick, D. N. 2005. The Contribution of Breeding to Yield Advances in maize (Zea mays L.). Adv. Agron. 86:83–145. Academic Press. Eden, E., D. Lipson, S. Yogev, and Z. Yakhini. 2007. Discovering Motifs in Ranked Lists of DNA Sequences. PLOS Comput. Biol. 3:e39. Public Library of Science. Eden, E., R. Navon, I. Steinfeld, D. Lipson, and Z. Yakhini. 2009. GOrilla: A tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics 10:1–7. BioMed Central. Elvingson, P., and K. Johansson. 1993. Genetic and environmental components of variation in body traits of rainbow trout (Oncorhynchus mykiss) in relation to age. Aquaculture 118:191–204. Elsevier. Fenkes, M., H. A. Shiels, and R. L. Nudds. 2018. Body shape and robustness response to water flow during development of brown trout Salmo trutta parr. J. Fish Biol. 93:360–369. FFSBC. 2004. Rainbow Trout Strains Currently Stocked in BC Waters. Fitzpatrick, S. M. 2020. Ancient aquaculture and the rise of social complexity. Proc. Natl. Acad. Sci. U. S. A. 117:9151–9153. National Academy of Sciences. Flannery, K. 1969. The Domestication of Plants and Animals. Fleming, I. A., and S. Einum. 1997. Experimental tests of genetic divergence of farmed from wild Atlantic salmon due to domestication. ICES J. Mar. Sci. 54:1051–1063. 69 Fleming, I. A., K. Hindar, I. B. Mjolnerod, B. Jonsson, T. Balstad, and A. Lamberg. 2000. Lifetime success and interactions of farm salmon invading a native population. Proc. R. Soc. London. Ser. B Biol. Sci. 267:1517–1523. The Royal Society . Fraser, D. J., L. K. Weir, L. Bernatchez, M. M. Hansen, and E. B. Taylor. 2011. Extent and scale of local adaptation in salmonid fishes: review and meta-analysis. Hered. 2011 1063 106:404–420. Nature Publishing Group. Gale, K. 2019. Freshwater Fisheries Society of BC - Origins of the Fraser Valley Rainbow Trout Strain. Garcia De Leaniz, C., I. A. Fleming, S. Einum, E. Verspoor, W. C. Jordan, S. Consuegra, N. Aubin-Horth, D. Lajus, B. H. Letcher, A. F. Youngson, J. H. Webb, L. A. Vøllestad, B. Villanueva, A. Ferguson, and T. P. Quinn. 2007. A critical review of adaptive genetic variation in Atlantic salmon: implications for conservation. Biol. Rev. 82:173–211. John Wiley & Sons, Ltd. Gjedrem, T. 2000. Genetic improvement of cold-water fish species. Aquac. Res. 31:25–33. John Wiley & Sons, Ltd. Gjedrem, T., N. Robinson, and M. Rye. 2012. The importance of selective breeding in aquaculture to meet future demands for animal protein: A review. Aquaculture 350–353:117–129. Elsevier. Glover, K. A., H. Otterå, R. E. Olsen, E. Slinde, G. L. Taranger, and Ø. Skaala. 2009. A comparison of farmed, wild and hybrid Atlantic salmon (Salmo salar L.) reared under farming conditions. Aquaculture 286:203–210. Elsevier. 70 Greenberg, L., B. Jonsson, J. R. Norrgård, A. Erlandsson, and E. Bergman. 2021. Body shape and fin size in juvenile Atlantic salmon (Salmo salar): effects of temperature during embryogenesis. https://doi.org/10.1139/cjz-2020-0101 99:381–389. NRC Research Press 1840 Woodward Drive, Suite 1, Ottawa, ON K2C 0P7 . Gutierrez, A. P., J. M. Yáñ Ez, S. Fukui, B. Swift, and W. S. Davidson. 2015. Genome-Wide Association Study (GWAS) for Growth Rate and Age at Sexual Maturation in Atlantic Salmon (Salmo salar). PLoS One 10:e0119730. Public Library of Science. Hard, J. J., B. A. Berejikian, E. P. Tezak, S. L. Schroder, C. M. Knudsen, and L. T. Parker. 2000. Evidence for morphometric differentiation of wild and captively reared adult coho salmon: A geometric analysis. Environ. Biol. Fishes 58:61–73. Jamalzad Falah, F., H. Rajabi Islami, and M. Shamsaie Mehrgan. 2020. Dietary folic acid improved growth performance, immuno-physiological response and antioxidant status of fingerling Siberian sturgeon, Acipenser baerii (Brandt 1896). Aquac. Reports 17:100391. Elsevier. Jhingan, E., R. H. Devlin, and G. K. Iwama. 2003. Disease resistance, stress response and effects of triploidy in growth hormone transgenic coho salmon. J. Fish Biol. 63:806–823. John Wiley & Sons, Ltd. Kasagi, S., M. Miura, T. Okazaki, K. Mizusawa, and A. Takahashi. 2020. Effects of tank color brightness on the body color, somatic growth, and endocrine systems of rainbow trout Oncorhynchus mykiss. Gen. Comp. Endocrinol. 298. Gen Comp Endocrinol. Kause, A., O. Ritola, T. Paananen, U. Eskelinen, and E. A. Mäntysaari. 2002. QUANTITATIVE GENETIC PARAMETERS FOR APPEARANCE OF RAINBOW TROUT. Proc. 7th World 71 Congr. Genet. Appl. to Livest. Prod. 6. Lande, R. 1981. THE MINIMUM NUMBER OF GENES CONTRIBUTING TO QUANTITATIVE VARIATION BETWEEN AND WITHIN POPULATIONS. Genetics 99:541–553. Leggatt, R. A., L. Fredrik Sundström, W. E. Vandersteen, and R. H. Devlin. 2016. Alternate directed anthropogenic shifts in genotype result in different ecological outcomes in coho salmon oncorhynchus kisutch fry. PLoS One 11:1–15. Liasko, R., C. Anastasiadou, A. Ntakis, C. Gkenas, and I. D. Leonardos. 2012. Morphological differentiation among native trout populations in North-Western Greece. J. Biol. Res. 17:33–43. López, M. E., M. I. Cádiz, E. B. Rondeau, B. F. Koop, and J. M. Yáñez. 2021. Detection of selection signatures in farmed coho salmon (Oncorhynchus kisutch) using dense genome-wide information. Sci. Reports 2021 111 11:1–13. Nature Publishing Group. Lorenzoni, M., A. Carosi, M. Giovannotti, G. La Porta, A. Splendiani, and V. C. Barucchi. 2019. Morphological survey as powerful detection tool of pure and local phenotypes in Salmo trutta complex. Knowl. Manag. Aquat. Ecosyst. 2019:48. EDP Sciences. Lucas, M. D., R. E. Drew, P. A. Wheeler, P. A. Verrell, and G. H. Thorgaard. 2004. Behavioral differences among rainbow trout clonal lines. Behav. Genet. 34:355–365. Behav Genet. Martens, M. T., A. J. Wall, G. G. Pyle, B. A. Wasylenko, W. A. Dew, R. H. Devlin, and P. J. Blanchfield. 2014. Growth and feeding efficiency of wild and aquaculture genotypes of rainbow trout (Oncorhynchus mykiss) common to Lake Huron, Canada. J. Great Lakes Res. 40:377–384. Elsevier. 72 Mason, J., O. Brynildson, and P. Degurse. 1967. Comparative Survival of Wild and Domestic Strains of Brook Trout in Streams: Transactions of the American Fisheries Society: Vol 96, No 3. Micheletti, S. J., and S. R. Narum. 2018. Utility of pooled sequencing for association mapping in nonmodel organisms. Mol. Ecol. Resour. 18:825–837. John Wiley & Sons, Ltd. Milla, S., A. Pasquet, L. El Mohajer, and P. Fontaine. 2021. How domestication alters fish phenotypes. Rev. Aquac. 13:388–405. John Wiley & Sons, Ltd. Milot, E., C. Perrier, L. Papillon, J. J. Dodson, and L. Bernatchez. 2013. Reduced fitness of Atlantic salmon released in the wild after one generation of captive breeding. Evol. Appl. 6:472–485. John Wiley & Sons, Ltd. Moghadam, H. K., M. M. Ferguson, C. E. Rexroad, I. Coulibaly, and R. G. Danzmann. 2007. Genomic organization of the IGF1, IGF2, MYF5, MYF6 and GRF/PACAP genes across Salmoninae genera. Anim. Genet. 38:527–532. John Wiley & Sons, Ltd. Nazari, S., and H. Paknejad. 2020. Investigation of quantitative trait loci (QTL) variations for growth-related traits in farmed rainbow trout (Oncorhynchus mykiss). Util. Cultiv. Aquat. 9:95–104. Gorgan University of Agricultural Sciences and Natural Resources. Neely, K. G., J. M. Myers, J. J. Hard, and K. D. Shearer. 2008. Comparison of growth, feed intake, and nutrient efficiency in a selected strain of coho salmon (Oncorhynchus kisutch) and its source stock. Aquaculture 283:134–140. Elsevier. Ojanguren, A. F., and F. Brana. 2003. Effects of size and morphology on swimming performance in juvenile brown trout (Salmo trutta L.). Ecol. Freshw. Fish 12:241–246. 73 Overturf, K., D. Sakhrani, and R. H. Devlin. 2010. Expression profile for metabolic and growth-related genes in domesticated and transgenic coho salmon (Oncorhynchus kisutch) modified for increased growth hormone production. Aquaculture 307:111–122. Pakkasmaa, S., and J. Piironen. 2001. Morphological differentiation among local trout (Salmo trutta) populations. Biol. J. Linn. Soc. 72:231–239. Oxford Academic. Pakkasmaa, S., and J. Piironen. 2000. Water velocity shapes juvenile salmonids. Evol. Ecol. 2000 148 14:721–730. Springer. Park, P. J., W. E. Aguirre, D. A. Spikes, and J. M. Miyazaki. 2013. Landmark-Based Geometric Morphometrics: What Fish Shapes Can Tell Us about Fish Evolution. Test. Stud. Lab. Teach. Proc. Assoc. Biol. Lab. Educ. 34:361–371. Pedersen, S., L. Liu, B. Glebe, S. Leadbeater, S. Lien, and E. G. Boulding. 2018. Mapping of quantitative trait loci associated with size, shape, and parr mark traits using first-and second-generation backcrosses between European and North American Atlantic salmon (Salmo salar). Genome 61:33–42. Canadian Science Publishing. Perry, W. B., J. Kaufmann, M. F. Solberg, C. Brodie, A. M. Coral Medina, K. Pillay, A. Egerton, A. Harvey, K. P. Phillips, J. Coughlan, F. Egan, R. Grealis, S. Hutton, F. Leseur, S. Ryan, R. Poole, G. Rogan, E. Ryder, P. Schaal, C. Waters, R. Wynne, M. Taylor, P. Prodöhl, S. Creer, M. Llewellyn, P. McGinnity, G. Carvalho, and K. A. Glover. 2021. Domestication-induced reduction in eye size revealed in multiple common garden experiments: The case of Atlantic salmon (Salmo salar L.). Evol. Appl. 14:2319–2332. John Wiley & Sons, Ltd. Pulcini, D., P. A. Wheeler, S. Cataudella, T. Russo, and G. H. Thorgaard. 2013. Domestication shapes morphology in rainbow trout Oncorhynchus mykiss. J. Fish Biol. 82:390–407. 74 Ramamoorthy, K., and R. S. Verma. 2008. Convergence pattern studies of folate receptor. Bioinformation 3:168. Biomedical Informatics Publishing Group. Reis Neto, R. V., G. M. Yoshida, J. P. Lhorente, and J. M. Yáñez. 2019. Genome-wide association analysis for body weight identifies candidate genes related to development and metabolism in rainbow trout (Oncorhynchus mykiss). Mol. Genet. Genomics 2019 2943 294:563–571. Springer. Riddell, B. E., and W. C. Leggett. 2011. Evidence of an Adaptive Basis for Geographic Variation in Body Morphology and Time of Downstream Migration of Juvenile Atlantic Salmon (Salmo salar). https://doi.org/10.1139/f81-042 38:308–320. NRC Research Press Ottawa, Canada . Rieseberg, L. H., M. A. Archer, and R. K. Wayne. 1999. Transgressive segregation, adaptation and speciation. Hered. 1999 834 83:363–372. Nature Publishing Group. Robinson, B. W., and K. J. Parsons. 2002. Changing times, spaces, and faces: tests and implications of adaptive morphological plasticity in the fishes of northern postglacial lakes. https://doi.org/10.1139/f02-144 59:1819–1833. NRC Research Press Ottawa, Canada. Rodríguez, F. H., G. Cáceres, J. P. Lhorente, S. Newman, R. Bangera, T. Tadich, R. Neira, and J. M. Yáñez. 2019. Genetic (co)variation in skin pigmentation patterns and growth in rainbow trout. Animal 13:675–682. Elsevier. Roy, K., I. L. De La Serna, and A. N. Imbalzano. 2002. The myogenic basic helix-loop-helix family of transcription factors shows similar requirements for SWI/SNF chromatin remodeling enzymes during muscle differentiation in culture. J. Biol. Chem. 277:33818–33824. J Biol Chem. 75 Savriama, Y. 2018. A Step-by-step guide for geometric morphometrics of floral symmetry. Front. Plant Sci. 9:1–23. Schlötterer, C., R. Tobler, R. Kofler, and V. Nolte. 2014. Sequencing pools of individuals — mining genome-wide polymorphism data without big funding. Nat. Rev. Genet. 2014 1511 15:749–763. Nature Publishing Group. Sfakianakis, D. G., I. Leris, A. Laggis, and M. Kentouri. 2011. The effect of rearing temperature on body shape and meristic characters in zebrafish (Danio rerio) juveniles. Environ. Biol. Fishes 2011 922 92:197–205. Springer. Skaala, Ø., K. A. Glover, B. T. Barlaup, T. Svåsand, F. Besnier, M. M. Hansen, and R. Borgstrøm. 2012. Performance of farmed, hybrid, and wild atlantic salmon (Salmo salar) families in a natural river environment. Can. J. Fish. Aquat. Sci. 69:1994–2006. Smith, A. D., A. L. S. Houde, B. Neff, and P. R. Peres-Neto. 2017. Effects of competition on fitness-related traits. Oecologia 2017 1833 183:701–713. Springer. Solberg, M. F., Ø. Skaala, F. Nilsen, and K. A. Glover. 2013. Does Domestication Cause Changes in Growth Reaction Norms? A Study of Farmed, Wild and Hybrid Atlantic Salmon Families Exposed to Environmental Stress. PLoS One 8:e54469. Public Library of Science. Solem, O. K. Berg, and A. J. Kjøsnes. 2006. Inter- and intra-population morphological differences between wild and farmed Atlantic salmon juveniles. J. Fish Biol. 69:1466–1481. John Wiley & Sons, Ltd. Solem, O., and O. K. Berg. 2011. Morphological differences in parr of Atlantic salmon Salmo salar from three regions in Norway. J. Fish Biol. 78:1451–1469. John Wiley & Sons, Ltd. 76 Sonnante, G., K. Hammer, and D. Pignone. 2009. From the cradle of agriculture a handful of lentils: History of domestication. Rend. LINCEI 2009 201 20:21–37. Springer. Stringwell, R., A. Lock, C. J. Stutchbury, E. Baggett, J. Taylor, P. J. Gough, and C. Garcia de Leaniz. 2014. Maladaptation and phenotypic mismatch in hatchery-reared Atlantic salmon Salmo salar released in the wild. J. Fish Biol. 85:1927–1945. J Fish Biol. Sun, H., Y. Cao, Y. Zhao, L. Lu, L. Zhou, L. Wang, X. Chen, and H. Wang. 2015. MicroRNAs in Skeletal Muscle Differentiation. MicroRNA Regen. Med. 419–446. Elsevier Inc. Tave, D. 1989. The Domsea selective breeding program with coho salmon. Aquac. Mag. 15:63-67; Te Pas, M. F. W., F. J. Verburg, C. L. M. Gerritsen, and K. H. De Greef. 2000. Messenger ribonucleic acid expression of the MyoD gene family in muscle tissue at slaughter in relation to selection for porcine growth rate. J. Anim. Sci. 78:69–77. Oxford Academic. Teletchea, F. 2021. Fish domestication in aquaculture: 10 unanswered questions. Anim. Front. 11:87–91. Oxford Academic. Tsai, H. Y., A. Hamilton, D. R. Guy, A. E. Tinch, S. C. Bishop, and R. D. Houston. 2015a. Verification of SNPs Associated with Growth Traits in Two Populations of Farmed Atlantic Salmon. Int. J. Mol. Sci. 17. Int J Mol Sci. Tsai, H. Y., A. Hamilton, A. E. Tinch, D. R. Guy, K. Gharbi, M. J. Stear, O. Matika, S. C. Bishop, and R. D. Houston. 2015b. Genome wide association and genomic prediction for growth traits in juvenile farmed Atlantic salmon using a high density SNP array. BMC Genomics 16:1–9. BioMed Central Ltd. 77 Tymchuk, W., R. Devlin, and R. Withler. 2006a. The Role of Genotype and Environment in Phenotypic Differentiation among Wild and Cultured Salmonids. Tymchuk, W. E., C. Biagi, R. Withler, and R. H. Devlin. 2006b. Growth and Behavioral Consequences of Introgression of a Domesticated Aquaculture Genotype into a Native Strain of Coho Salmon. Trans. Am. Fish. Soc. 135:442–455. Tymchuk, W. E., and R. H. Devlin. 2005. Growth differences among first and second generation hybrids of domesticated and wild rainbow trout (Oncorhynchus mykiss). Aquaculture 245:295–300. Tymchuk, W. E., L. F. Sundström, and R. H. Devlin. 2007. Growth and survival trade-offs and outbreeding depression in rainbow trout (Oncorhynchus mykiss). Evolution (N. Y). 61:1225–1237. Tymchuk, W., D. Sakhrani, and R. Devlin. 2009. Domestication causes large-scale effects on gene expression in rainbow trout: Analysis of muscle, liver and brain transcriptomes. Gen. Comp. Endocrinol. 164:175–183. Varian, A., and K. M. Nichols. 2010. Heritability of Morphology in Brook Trout with Variable Life Histories. PLoS One 5:e12950. Public Library of Science. Volpe, J. P. 2007. “Salmon sovereignty” and the dilemma of intensive Atlantic salmon aquaculture development in British Columbia Some of the authors of this publication are also working on these related projects: Global Aquaculture Performance Index View project Boreal white-tailed deer project View project. Volpe, J. P., B. R. Anholt, and B. W. Glickman. 2001. Competition among juvenile Atlantic salmon ( Salmo salar ) and steelhead ( Oncorhynchus mykiss ): relevance to invasion 78 potential in British Columbia. Can. J. Fish. Aquat. Sci. 58:197–207. NRC Research Press Ottawa, Canada. Webb, P. W. 1984. Body Form, Locomotion and Foraging in Aquatic Vertebrates. Integr. Comp. Biol. 24:107–120. Oxford Academic. Webb, S. L. 2006. Assessing the vulnerability of wild rainbow trout (Oncorhynchus mykiss) stocks to overfishing in the Thompson Nicola Region of British Columbia. Thompson Rivers University. Wessel, M. L., W. W. Smoker, and J. E. Joyce. 2011. Variation of Morphology among Juvenile Chinook Salmon of Hatchery, Hybrid, and Wild Origin. Chang. Publ. Wiley 135:333–340. Taylor & Francis Group . Westley, P. A. H., R. Stanley, and I. A. Fleming. 2013. Experimental Tests for Heritable Morphological Color Plasticity in Non-Native Brown Trout (Salmo trutta) Populations. PLoS One 8:e80401. Public Library of Science. Yin, H., X. Zhao, and Y. Wang. 2011. Association of MyF5, MyF6 and MyOG Gene Polymorphisms with Carcass Traits in Chinese Meat Type Quality Chicken Populations. Artic. J. Anim. Vet. Adv., doi: 10.3923/javaa.2011.704.708. Yoshida, G. M., J. P. Lhorente, R. Carvalheiro, and J. M. Yáñez. 2017. Bayesian genome-wide association analysis for body weight in farmed Atlantic salmon (Salmo salar L.). Anim. Genet. 48:698–703. Anim Genet. Zhang, R. F., H. Chen, C. Z. Lei, C. L. Zhang, X. Y. Lan, Y. D. Zhang, H. J. Zhang, B. Bao, H. Niu, and X. Z. Wang. 2007. Association between Polymorphisms of MSTN and MYF5 Genes and Growth Traits in Three Chinese Cattle Breeds. Asian-Australasian J. Anim. Sci. 79 20:1798–1804. Asian-Australasian Association of Animal Production Societies. Zhao, C., S. H. A. Raza, R. Khan, A. Sabek, S. Khan, I. Ullah, S. Memon, A. H. A. El-Aziz, M. A. Shah, L. Shijun, L. Wang, X. Liu, Y. Zhang, L. Gui, and L. Zan. 2020. Genetic variants in MYF5 affected growth traits and beef quality traits in Chinese Qinchuan cattle. Genomics 112:2804–2812. Academic Press. 80 Appendix: Supplementary Figures Supplementary Figure 1. Number of marks on individuals of each strain. 81 Supplementary Figure 2. Histograms comparing greyscale values for parr marks (parr mark lightness). Higher values on the x-axis correspond to lighter parr marks. Fv: Fraser Valley, pn: Pennask, p11: pond 11, p12: pond 12.
Thesis/Dissertation
eng
Zoology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Schulte, Patricia M.
Genetic and environmental influences on morphological traits in salmonids
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