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Microsatellite DNA variation in domestic ratite populations Benun, Assaf 1999

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MICROSATELLITE DNA VARIATION IN DOMESTIC RATITE POPULATIONS by ASSAF BENUN B.Sc. (Hons) Agr. , The Hebrew University of Jerusalem, 1998 A T H E S I S S U B M I T E D I N P A R T I A L F U L F I L L M E N T O F T H E R E Q U I R E M E N T S O F T H E D E G R E E O F M A S T E R O F S C I E N C E in T H E F A C U L T Y O F G R A D U A T E S T U D I E S (The Genetics Graduate Program) We accept this thesis confirming to the required standard T H E U N I V E R S I T Y O F B R I T I S H C O L U M B I A July, 1999 © Assaf Benun, 1999 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of G~€^&1 :cS (yYaJjyb-S ^o>j Vex IM^ The University of British Columbia Vancouver, Canada D a t e j ^ W V flfl DE-6 (2/88) A B S T R A C T Ostrich {Struthio camelus) farming in North America is a growing industry that recently started moving from the breeder market to the slaughter market. The domesticated ostriches, the Black {Struthio camelus var domesticus) and the Blue (S. c. australis). have been bred in South Afr ica and farmed in the past 150 years. More recently, another subspecies, the Red {S. c. massaicus) has been added to the farm population. The commercial importation to North America has only begun in the mid 1980s. Unlike other poultry, ostriches have a relatively long generation time, require more rearing space, and have a high per unit dollar value. Because their pedigrees have not been wel l kept, the genetic variation of North American ostriches is not known. Fears of inbreeding and limited heterozygosity arose from limited knowledge of the breeders background and may affect the type of genetic manipulation that w i l l be necessary for improving production, i.e., selection, cross-breeding and inbreeding. I used 8 recently developed microsatellite markers to measure the genetic variability in breeding flocks (66 birds) from 3 farms in British Columbia. Significant allelic frequency differences were found between breeding flocks as wel l as between different ostrich subspecies. The Blue seems to be genetically closer to the Black than the Red. Heterozygosity was found to be comparable to that reported in other ostrich populations. Positive correlation (r = 0.28) was found between heterozygosity and body weight, however, there were no obvious signs of inbreeding depression. The results suggest breeding stocks o f the three farms came from diverse sources. Calculated genetic distances confirmed the genetic relationship between the different subspecies. Among other paleognathous birds farmed today, emu (Dromaius novaehollandiae) farming is a growing industry in North America and the tinamou (Nothroprocta perdicaria sanbonii) is a newly farmed bird in British Columbia. The development o f microsatellite markers for these two species w i l l be useful for genomic studies. The cross-species amplification o f microsatellites in these two species with the application of ten ostrich primer sets was examined. Five primer sets amplified emu D N A and four sets amplified tinamou D N A . Microsatellite marker LIST002 was found to be 68% conserved between the emu and the ostrich. For marker O S M 4 ostrich sequence was found to be conserved in both the tinamou and emu (68% and 79% respectively) in the stretch prior to the repeats region. O S M 1 was 50% conserved among the tinamou and the emu. One locus (LIST002) showed polymorphism in the tinamou. However, it is not known whether it contains a microsatellite. The results indicated that cross-species amplification o f D N A using ostrich primers in the emu and tinamou can be obtained quite efficiently. However, obtaining microsatellites using cross species amplification is inferior to a species specific library. Albeit , microsatellite repeat were found and should be considered for use in future research. T A B L E O F C O N T E N T S A B S T R A C T 11 T A B L E O F C O N T E N T S I V T A B L E O F T A B L E S V I T A B L E O F F I G U R E S vfii A C K N O W L E D G M E N T S X D E D I C A T I O N XI I 1 G E N E R A L I N T R O D U C T I O N 1 1.1.1 Paleognathous Birds and Ratitae Phylogeny 1 1.1.2 Phylogeography of The Ostrich 4 2 G E N E T I C V A R I A T I O N I N D O M E S T I C O S T R I C H B R E E D I N G S T O C K I N B R I T I S H C O L U M B I A A S S E S S E D W I T H M I C R O S A T E L L I T E M A R K E R S 8 2.1 I N T R O D U C T I O N 8 2.1.1 Ostrich Farming: History 8 2.1.2 Ostrich Breeding in British Columbia 12 2.1.3 Genetic Variation in Populations 14 2.1.4 Genome Organization and Microsatellite D N A 19 2.2 O B J E C T I V E S O F T H E S T U D Y 29 2.3 E X P E R I M E N T A L M E T H O D S 30 2.3.1 Source of Birds 30 2.3.2 Collection o f Blood Samples 31 2.3.3 D N A Extraction and Purification 31 2.3.4 Source of Primers 32 2.3.5 P C R Amplification 32 2.3.6 Analysis of P C R Products 37 2.3.7 Data Analysis 37 2.4 R E S U L T S '. 41 2.4.1 Genetic Variations in Ostrich Breeder Flocks 42 2.4.2 Genetic Relationship of the Subspecies 51 2.4.3 Body Size and Body Weight Measurements 59 2.5 D I S C U S S I O N 64 2.5.1 Genetic Variation Within and Among Different Breeder Flocks 65 2.5.2 Genetic Variation in The Subspecies 68 2.5.3 Correlation Between Heterozygosity and Body Weight 69 V 2.6 C O N C L U S I O N S 70 3 E M U A N D T I N A M O U M I C R O S A T E L L I T E L O C I A M P L I F I E D B Y O S T R I C H P R I M E R S 72 3.1 I N T R O D U C T I O N 72 3.1.1 Cross-Species Amplification Using Ostrich Microsatellite markers 72 3.1.2 Emu Farming 76 3.1.3 Partridge Tinamou: a Newly Developed Farm B i r d 78 3.2 O B J E C T I V E S O F T H E S T U D Y 79 3.3 E X P E R I M E N T A L M E T H O D S 80 3.3.1 Experimental Birds and D N A Samples 80 3.3.2 P C R Cross-Species Amplification 80 3.4 R E S U L T S 84 3.5 D I S C U S S I O N 91 4 G E N E R A L D I S C U S S I O N 94 R E F E R E N C E S C I T E D 97 A P P E N D I X A : K i w i Microsatellite L o c i Amplified by Ostrich Primers 110 LIST O F T A B L E S Table 1.1 Mitochondrial D N A sequence divergence among the four l iving subspecies o f ostrich (Freitag and Robinson, 1993) 8 Table 2.1 Sample size o f the subspecies in the different farms 34 Table 2.2 The primer sequences used in this study 35 Table 2.3 P C R amplification optimization: Results of cross-species amplification at the various annealing temperatures tested 36 Table 2.4 The expected and observed annealing temperature and allele number in the eight loci that were successfully amplified 44 Table 2.5 Summary o f heterozygosity o f an individual in the subpopulation (farm) (H0), expected heterozygosity for an individual in a subpopulation (Hs), and expect heterozygosity in the total population (H,) 49 Table 2.6 F Statistics o f genetic differentiation o f ostriches among farms 50 Table 2.7 The genetic distance between the breeder flocks in the different farms according to Nei ' s measurement 51 Table 2.8 Summary o f H 0 , H s , H t for three different subspecies and two crosses 56 Table 2.9 F statistics for genetic differentiation among subspecies 57 Table 2.10 The genetic identity of the subspecies and crosses according to Nei ' s measurement '. 58 Table 2.11 Body weights o f the different subspecies and their crosses 61 Table 3.1 The results of cross amplification of 8 ostrich specific microsatellite primers in other ratite birds 75 Table 3.2 P C R amplification optimization in cross-species amplification using ostrich primers on tinamou D N A 82 Table 3.3 P C R amplification optimization in cross-species amplification using ostrich primers on emu D N A 83 Table 3.4 Amplification results in the emu and tinamou using ostrich specific microsatellite markers 87 Table A . l P C R amplification optimization in cross-species amplification using ostrich primers on k i w i D N A I l l Table A . 2 P C R results in the k iwi using ostrich specific microsatellite markers 112 VIII LIST O F FIGURES Figure 1.1 The distribution of ostrich subspecies and the Little Karoo region o f South Africa (modified from Freitag and Robinson, 1993) 7 Figure 2.1 Al le le frequency histograms for six ostrich microsatellite D N A loci in Australian and Kenyan populations (Ward et ah, 1994; Ward et al, 1998) 28 Figure 2.2 Body measurements taken from the ostriches 33 Figure 2.3 Photograph o f ethidium bromide stained nondenaturing polyacrylamide gel with ostrich microsatellite alleles o f locus O S M 4 34 Figure 2.4 Al le l i c frequency in the seven polymorphic microsatellite loci o f ostriches pooled over all three breeder flocks 45 Figure 2.5 Al l e l i c frequency in the three different farms (A, B and C) at the seven polymorphic loci 47 Figure 2.6 Al l e l i c frequency in the three different subspecies and crosses at the seven polymorphic loci 53 Figure 2.7 U P G M A phenogram based on Nei ' s genetic distances in eight loci among subspecies of domesticated ostriches and their crosses 58 Figure 2.8 Calculated body weight in the different subspecies and crosses 60 Figure 2.9 Correlation between back height and body weight 62 Figure 2.10 Correlation between heart girth and body weight 62 Figure 2.11 Correlation between Heterozygosity of birds and body weight 64 Figure 3.1 Photograph o f ethidium bromide stained nondenaturing polyacrylamide gel with emu (left) and k i w i (right) cross amplification products at locus O S M 4 and 1 M b p D N A marker in the flanking lanes 88 Figure 3.2 Photograph of ethidium bromide stained nondenaturing polyacrylamide gel with tinamou cross amplification products at locus LIST002 and 100 bp D N A marker in the first left lane 88 Figure 3.3 Sequence of the cross amplification products in the emu and tinamou. Underlined nucleotides represent part of the forward primer and the areas of repeats sequence. Markers are aligned for the emu and the ostrich where alignment was possible 89 Figure A . l Sequence o f the cross amplification products in the k iw i . Underlined nucleotides represent part of the forward primer and the area o f repeats sequence 113 X A C K N O W L E D G M E N T S In my thesis study, numerous people assisted me on the way, from obtaining samples through laboratory work to results analysis. I wish to express my gratitude for all these people, from supervisors, laboratory colleagues, researchers in the academy and farmers from the ostrich industry in British Columbia. I wish to thank Dr. Carol Ritland for introducing me into the laboratory and instructing me in the operation, procedures, and regulations of the laboratory environment. With patience and dedication Dr . Ritland taught me the skills I needed in order to study in details my samples. I also want to thank my supervisor Dr . Kimberly M . Cheng. Dr. Cheng help (from the first contact we made while on different continents all the way to the last day) is immeasurable. Dr. Cheng is a dedicated instructor with an "open-door" policy and always there to lend an ear in any professional but most importantly in every personal burden as well as Joyful days. N o superlative could describe my appreciation to Dr. Cheng my supervisor and most importantly a friend. Special thanks are for Dr. Dawn Marshall o f the Genetic Data Centre, University o f Brit ish Columbia for sequencing samples with great competence and proficiency. Dr . Marshall help is extremely appreciated and stands-out to be with extreme importance. I wish to thank M s . Shirley Pang for her help in the laboratory, D r Kermit Ritland for help in the statistical analysis o f the results and for providing important insights for the examination o f the results. I also wish to thank M r . Oliver Haddrath from the Centre for Biodiversity and Conservation Biology of the Royal Ontario Museum for providing k i w i and emu samples. I was supported by a University of British Columbia Graduate Fellowship, a C W Roberts Memorial Scholarship, and The Pacific Egg and Poultry Association Scholarship. M y research project was supported by a grant from the B C Ministry o f Agriculture and Food (Partners in Progress Program) and a grant from the Tinamou International Inc. DEDICATION To my beloved father Johnathan Benun 1935 -1999 So powerful, in years of strength and also in days of weakness 1 1 G E N E R A L INTRODUCTION 1.1.1 Paleognathous Birds and Ratitae Phytogeny The division Neornithes includes all l iving birds and is divided into two subdivisions, the paleognathous and the neognathous. The paleognathous group includes the Tinamidae and Ratitae. The living ratitae include the ostrich {Struthio camelus), emu {Dromaius novaehollandiae), rhea {Rhea dimericana), k iw i {Apteryx australis), as well as cassowaries (Casuarius). The Tinamidae includes 47 species of Tinamous (Sibley and Ahlquist, 1990). These two subdivisions were classified into a separate subgroup on the basis o f their distinctive palate morphology. The Ratitae have no keel on the sternum (flat sterna), reduced wings and are flightless (Houde, 1988J. The Tinamidae have a keeled sternum, reduced wings and have limited flying capability. Distinct behavioral characteristics shared by paleognathous (Meise, 1963) and osteological details (Cracraft, 1974) further validated the anatomical data to establish a common progenitor. Sibley and Ahlquist (1990) conducted D N A hybridization tests to compare D N A - D N A hybrids among the ratites and tinamou. The D N A - D N A hybridization technique is based on different melting curves that depict the relationship between D N A - D N A heteroduplexes and homoduplexes. Hence, the denaturing temperature (T m ) reflects the extent of divergence between the species and could be adjusted to a time frame given a point in time. Based on these tests the paleognathous group was found to be monophyletic. 2 Although neognathous and paleognathous are both members o f the division Neornithes the time of divergence between the two subgroups is still a matter o f controversy. Furthermore, the phylogenetic relationship within the paleognathous is inconclusive. Hence, with no rooted phylogenetic trees the interpretation o f exact time frame is unsettled. Based upon morphological data Cracraft (1974) found the Apteryx to be basal to other ratites phylogenetically. Conversely, molecular data suggests Casuarius and Dromorius to be the predecessors. Furthermore, paleontological confirmation o f data sets is ambiguous due to the scarcity of fossil records. The light-boned constitution o f birds repudiates the embedding of sediment and fossilization (Harlid et al., 1997). Sibley and Afilquist (1990) also suggested that the earliest divergence in the ratites were between the ostrich-rhea group and the cassowary-emu-kiwi group at 80-81 M Y A (million years ago). However, this was not consistent with the timing o f the breakup o f the South America-Antarctica-Australia landmass, which was around 90 M Y A . It was estimated that the k i w i was separated from the cassowary-emu branch around 40-45 M Y A . The dichotomy between the rhea and the ostrich was scaled for 80 M Y A based on the separation o f Africa from South America (However, it seems that this separation occurred 1 0 0 M Y A ; Smith et al, 1994). In the most recent attempt to resolve the question of the phylogeny, van Tuinen et al. (1998) used the complete mitochondrial ribosomal genes (2.8 kb) from representative o f the Ratitae. Although the genomic interval is smaller than a similar research performed 3 by Harl id et al. (1997) the results were similar they added the factor o f plate tectonics and biogeography o f the Ratitae progenitors. A t the time in question (about 90 M Y A ) major tectonic movements occurred that could aid in narrowing possible solutions. South America and Afr ica separated approximately 100 M Y A and recent suggestion propose that South America remained in contact with Australia via Antarctica (Smith et al, 1994) for additional 30-40 mil l ion years, van Tuinen et al. (1998) proposed two alternatives for the dispersal of Ratitae. The first suggests an African origin hypothesis. Ratitae existed in the African and South American continents and by the separation o f the continents the Tinamidae lineage was established in South America. In the next 30 mil l ion years, the ratites moved to Laurasia and leaving in Africa the Struthio lineages. The Rhea lineage was probably established after the migration from As ia through North America to South America. The Australian lineage would be the product of the Rhea migration through the land bridge o f Antarctica. The second explanation suggests a South American origin after the separation from Africa, leaving behind the Tinamidae lineage, the Struthio lineages could move to As i a through North America. Finally, the Struthio lineages reached Afr ica from Asia . A second wave of migration from the Americas would establish the Australian lineage. These two explanations are relying on dispersal by land bridges and lack of flying ability. Other explanations are possible but these two models fit the molecular data in regards to ratite problematic phylogeny. Thus far, the dating of the divergence between the neognathous and paleognathous is still a matter o f ambiguity and further examination is required. In the future, additional 4 nuclear genes would be needed in order to resolve the discussion (van Tuinen et al, 1988). In order to resolve phylogenetic question through the nuclear genome large number o f neutral genes must be identified in order to reduce perplexity caused by recombination events that occur in the nuclear genes. Interestingly, the karyotypes of the ratites (ostrich, emu and rhea) are remarkably similar. Ostrich has 2N=80, emu 2N=80, rhea 2N=82. Furthermore, significant similarities in relative lengths at each o f the chromosomes were found throughout all these species in the corresponding chromosomes (Takagi et al., 1972). 1.1.2 Phylogeography of The Ostrich The ostrich (Struthio camelus, Linnaeus, 1758), is now endemic only to Afr ica but had had a range extended to Arabia and Central As ia (Jennings, 1986). Currently, ostriches are found from south of the Sahara to the Cape Provinces. Extensions of the population reach Northern Africa through the Sahara. The range is broken in Central Africa by a woodland belt (Hamilton, 1982). Currently the species includes four subspecies as follows (Figure 1.1): S. c. camelus: Formerly found throughout North Africa, this subspecies is now only found in a band from Mauritania to Ethiopia. The male has collar o f white feathers between the upper and lower neck, black body and white wings and tail. The female has dark brown body with paler edges and paler tail and wing feathers. Male and female weights are 100-130 kg and 90-110 kg respectively (Hamilton, 1982). 5 S. c. massaicus: This subspecies is also called the Red, and is found in Tanzania and Kenya. This is the only subspecies that is almost completely feathered. The male's neck is bright red in the breeding season, thus the name. S. c. molybdophanes: The tallest of the ostriches is found in Somalia, Ethiopia and Kenya (The Horn o f Africa). The males' plumage is black and white and the females are gray. S. c. australis: This subspecies is commonly known as Blue. Originally endemic to South Africa, this subspecies is currently also found in Namibia, Botswana and Zimbabwe. The neck of the male is blue-gray during non-breeding season and red during breeding season. The tail plumage is dull to bright brown and the rest of the plumage is similar to S. c. molybdophanes. Male body weight reaches up to 157 kg (Maclean, 1993). Formerly, the ostrich included an extinct subspecies, S. c. syriacus, in Arabia and Palestine (Freitag and Robinson, 1993). The limited records about S. c. syriacus described it as smaller than other ostriches and having red coloring of the neck (Seddon and Soore, 1998). The S. c. syriacus is thought to be extinct in the early 1930's, although a report o f a dead ostrich swept in floods in Jordan in the 1960s has been recorded (Jennings, 1986). Freitag and Robinson (1993) assayed restriction-site differences in m t D N A within and among populations o f the ostrich throughout its African distribution to test for geographic structuring in m t D N A haplotypes among the ostrich subspecies. Their results showed low levels of m t D N A diversity, both in term of the number of haplotypes present and the close relationship among them (Table 1.1). They suggested that historical 6 interconnections and the lack o f real barriers to movement across Africa account for the limited m t D N A diversity. It seems that the species had high levels of gene flow through hybridization. Furthermore, the South African ostrich farming industry bred the S. c. australis with "Barbary birds" (S. c. camelus) and the extinct S. c. syriacus (see Section 2.1.1). This crossbreeding might have caused contamination o f the endemic South African population. The S. c. australis and the S. c. massaicus also showed low levels o f diversity between them. This low level of diversity is indicating that the Central African woodland belt was not effective in isolating the two subspecies. It seems that in times o f a receding Central African woodland high levels of gene flows had occurred. Nevertheless, clear divergence was identified between the S. c. camelus and the S. c. molybdophanes. It seems that the S. c. molybdophanes has diverged from a common ancestor o f the other three subspecies approximately 3.6 to 4.1 mil l ion years ago (Freitag and Robinson, 1993). The geographical separation is accounted by the Ethiopian system of the Great-Rift Valley, which might have served as a major geographical barrier disrupting gene flow (Freitag and Robinson, 1993). Figure 1.1 The distribution of ostrich subspecies and the Little Karoo region of South Africa (modified from Freitag and Robinson, 1993). 8 Table 1.1 Mitochondrial DNA sequence divergence (percent of nucleotide substitutions per site) among the four living subspecies of ostrich (Freitag and Robinson, 1993) Subspecies S. c. australis S. c. massaicus S. c. camelus S. c. molybdophanes S. c. australis1 0.15 0.06 1.21 7.16 S. c. massaicus1 0.05 1.27 7.25 S. c. camelus1 - 8.23 S. c. molybdophanes2 0.04 Based on 15 restriction enzymes. Based on 14 restriction enzymes. 2 G E N E T I C V A R I A T I O N IN D O M E S T I C O S T R I C H B R E E D I N G S T O C K IN BRITISH C O L U M B I A ASSESSED W I T H M I C R O S A T E L L I T E M A R K E R S 2.1 I N T R O D U C T I O N 2.1.1 Ostrich Farming: History The first ostrich farm was established in South Africa in 1838 to provide feathers (Grizmek, 1995). However, commercial ostrich breeding was only initiated in the 1880s (Deeming and Angel , 1996). Feather was the main product until World War I and 9 commercial ostrich farming was prosperous in the Little Karoo region (Figure 1.1) of South Africa. Between 1857 and 1864 commercial ostrich farming was recognized as a new branch o f the agricultural industry in South Africa (Smit, 1963). Since 1850, South African farmers developed the domesticated ostrich (S. c. var. domesticus). Three expeditions, in 1886, 1888, and 1903 (Drenowatz et al, 1995; Maclean, 1993) brought 2 subspecies o f ostriches, the North African S. c. camelus and the S. c. syriacus from the Arabian desert and Palestine. Together with the South African S. c. australis and through selective breeding, cross breeding and culling the domesticated ostrich, more commonly known as the Black, was developed. The Black is smaller than the wi ld subspecies, with shorter legs and necks and the female has more white plumes (Dernowatz et al., 1995). Mean body weight o f 116kg for males (with a range of 84-159) and 107kg (range 72-142) was recorded in ostrich breeding pairs at the K l e i n Karoo Agricultural Development Center (van Schalkwyk et al., 1996). In 1913 ostrich feathers were the forth largest export product of South Africa (Smit, 1963). Wi th the outbreak o f the First World War and the 1914 world depression the industry collapsed. Ostrich farmers slaughtered or sold most of their ostriches and ostrich number shrunk from 775,313 in 1913 to 32,500 in 1930 (Smit, 1963). However, Karoo farmers kept the highest quality ostriches with the hope that the industry would recover (Smith et al., 1995). In 1925, a cooperative association, the South African Ostrich Farmers Cooperative Ltd. , was established in order to fix prices, regulate the market and promote the industry. This was 11 years after the collapse of the feather market and unfortunately 10 this undertaking was a failure almost from the start. It was not until 1946 that a renewed interest in the ostrich (still mainly in the feathers) revived the industry. In the 1960's, ostriches were still farmed mainly in the Little Karoo area. In 1965 the K l e i n Karoo Co-op was formed and had control of 95% of the world's ostrich market. Even though the Black population had a dramatic decline (with only 4% of the 1913 effective population size to survive), it is today the highest quality commercial ostrich. The domestic Ostrich is producing 10 times more eggs per year than the wi ld ostriches. In 1983 the domesticated population reached 200,000 ostriches in South Africa (Smith et al., 1995). However, since the industry evolved to the production of ostrich meat and leather the small size o f the Black is becoming less desirable (Bilinsky, per. com.). In the 1920's a number of farmers began considering making biltong (dried meat strips) from ostrich meat. The demand for biltong grew rapidly and abattoir was built by the K l e i n Karoo Agricultural Cooperative. This facility was expended and modernized in 1980/81 for the processing o f ostrich meat for the export market. Ostrich skins were initially tanned overseas, but in 1970 the K l e i n Karoo Agricultural Cooperative built a tannery and from August that year all the skins were tanned and colored for local and foreign markets. Today approximately 85% of all skins are exported. In the late 1970's and early 1980's the ostrich industry mainly operated in the Little Karoo, with Oudtshoorn as the center. In accordance with legislation the Kle in Karoo, Agricultural Cooperative continued to control the industry within a single-channel marketing system and in the 11 1980's the industry suddenly started to expand rapidly (Marrette, 1996 South Afr ica Stud Book and Livestock Improvement Association In the 1970's, Blacks were exported to Israel to create an industry that today holds the second largest per capita ostrich population after South Africa. In the mid 1980's the U S A began an importation program directly from South Africa and also from Israel. In M a y 1988 the South African government passed a law banning exportation o f ostriches in order to maintain monopoly on the industry. Furthermore, Heartwater fever disease, was introduced to the U . S . with the ostriches, and resulted in a 1989 importation restrictions by the U . S . government (Trade and Environment Database 1996 Ostrich farming Case 289, In the early 1990's most o f the ostriches imported to the U S were the product o f illegal smuggling. The locations from which the smuggling was operated were the semi-independent South African province o f Bophuthatswana (reabsorbed into South Afr ica in 1994) and the South African disputed territory o f Namibia (independent since 1990) (Ostrichesonline Inc., 1999, http://www.ostrichesonline.corn/library/briemistory.html). From these territories many S. c. australis (Blue) birds were brought. S. c. massaicus (Red) was heavily imported to the U . S . during the late 1980s and early 1990s (American Ostrich Association Brochure 1998). The illegal importation to North America caused much damage to the U S industry since wi ld ostriches eggs were sold as domesticated Black ostriches. 12 Today the ostrich industry is approaching 2 mil l ion birds with farming in over 50 countries worldwide. The breeder industry in the U S A is at present paying excellent prices for breeding material. Today, an ostrich egg sells for about C$35, a day old chick C$125 and an adult breeding pair can cost C$1,000 to C$5,000 (Province o f British Columbia Ministry of Agriculture and Food, 1999). This creates a market for eggs and breeding birds where prices can be obtained which are considerably higher than in South Africa. Greater emphasis is currently put on the health aspect o f ostrich meat. The ostrich industry therefore moved away from a regulated, local industry in the Karoo region to a growing international industry. Approximately 160,000 ostriches are slaughtered in South Afr ica annually, but because o f strong competition, it is difficult to know to what extent the industry w i l l grow before it stabilizes again (Marrette, 1996). Other countries with major farming operations are Israel (estimated with 15,000 birds in 1980) and Australia (36,000 birds). In Europe the number stands on less than 10,000 birds. In North America, the number o f birds is estimated over 500,000 birds (Deeming and Angel , 1996). 2.1.2 Ostrich Breeding in British Columbia In Brit ish Columbia (BC) the ostrich production for breeding purposes initiated in the late 1980's via the importation of live birds. Initially the main sources for ostrich importation to B C were Alberta, Saskatchewan, Washington State, Oregon, Holland and Africa. (Kermode, 1993). A n ostrich industry survey completed in 1992 found twenty five ostrich producers in B C that held 244 ostriches with an approximate value of $2 mil l ion. Ostrich farms in B C are active in the Okanagan Valley, the Lower Mainland and on 13 Vancouver Island. The B C Ostrich Association (B .C .O .A) was formed in 1992 and comprised o f 37 members. It grew to 250 active members in 1995. However, it was dissolved in 1997 due to lack of involvement, interest and also because some farmers left the business. Today, the B C O A is operating as a skeleton body with no activities. Recently, the markets became more mature and prices are more stable (Cox, per. com.). The number o f ostrich producers in B C , today, is estimated at 100 with flocks totaling 3,000 ostriches. In Canada the total number o f ostriches is estimated at 27,900 with the main farming operations in Alberta (350 producers with 10,300 ostriches), Ontario (60 producers with 5000 ostriches) and Quebec (100 producers and 3,500 ostriches) (Elison, per. com.). The main concerns of the B C ostrich industry are husbandry, nutrition, breeding and reproduction. Since until now bookkeeping in the ostrich industry was poor, bird identification and registry is also o f great importance. A s a consequence, the risk o f inbreeding as a factor affecting production is posing a challenge. Hand-in-hand with the fear o f inbreeding is the fear of loss o f genetic variation. Currently, two thirds of the bylaws of animal registry with conjunction of Agriculture Canada have been compiled. Genetic identification is one of the factors already agreed upon to be implemented in the future (Ellison, per. com.). 14 2.1.3 Genetic Variation in Populations Genetic variation is the quantity and distance by which genes differ from organism to organism within the same gene pool. The genetic variance of a species contains the diversity within populations and among populations (Meffe and Carroll, 1997). Genetic variation arises due to mutations in the genome. In addition, recombination and independent assortment during the formation of the gametes produce an infinite variety o f combinations from the parental genome (Shorrocks, 1984). Reduction in genetic variation results from genetic drift, genetic bottleneck and inbreeding which, in turn, are affected by the effective population size. Genetic Drift Genetic drift is the random change in gene frequency caused by sampling errors in small populations (Hartl and Clark, 1998). It occurs whenever the population is not infinite in size and seen most radically in very small populations. A "small population" is a population in which, being a small sample of the total population, alleles might drift in frequency to a different value or disappear altogether. In a large enough sample that is being separated from the total population, genetic drift probably would not occur and can be ignored (Hartl and Clark, 1989). Hence, allele frequency is dependent upon the size o f the population and the number of generations since separation. Numerically, a population with the effective population size range of 10-100 is referred as small whereas 1000 is considered large (Hi l l , 1986). Likewise, in domesticated populations, genetic drift results in reduction of the proportion of polymorphism by elevating the chance of fixation o f an 15 allele at a locus. This results in reduction o f genetic variation unless it would be reintroduced through mutation or immigration. The interaction o f genetic drift, selection in a random environment (forces which reduce genetic variation) and mutation (a force which increase genetic variation) was investigated by Gillespie (1985). Based on assumptions o f weak mutation and strong selection forces he showed that genetic drift can be a potent force for removing variation from the population. Ne i (1988) argues that although cases of frequency dependent selection exist, this form of selection is apparently unimportant for the maintenance o f genetic variability except in some special cases. Since selection and mutation work on a longer time scale, in recently diverging populations genetic drift would be the strongest force determining the genetic variation and would be with great importance for small populations. Genetic Bottleneck A genetic bottleneck is the result of a severe and temporary reduction in the population size (Hartl and Clark, 1997). The change in the genetic variation in this case depends upon the initial allelic variation and frequencies in the original population. Furthermore, it also depends upon the duration o f the bottleneck and the degree in which the surviving alleles are randomized from the total frequency (Frankel and Soule, 1981). I f genetic variation exists in the original population, a bottleneck would reduce the genetic variability in the population. For example, Leberg (1992) reported significant differences in allele frequencies at three o f the seven loci examined between bottlenecked and founder populations o f mosquitofish (Gambusia holbrooki). The differences were attributed to loss 16 of rare alleles during the bottleneck. Houlden et al. (1996) found a reduction in genetic variability of the Koala (Phascolarctos cinereus) in South Eastern Australia following a severe population bottleneck. Based on microsatellite loci allelic diversity values were reduced from 8.0 to 1.7. After the occurrence of a population bottleneck when the population would rebound to its original size, the variability is still low until new mutation would create new polymorphism or until genetic variability would arrive from another population. Inbreeding Inbreeding is defined as mating between relatives (Hartl, 1980). Inbreeding increases the population's homozygosity through the whole genome. The effect o f inbreeding is usually measured through the inbreeding coefficient (F). The inbreeding coefficient is the probability that two alleles at a locus in an individual are identical by descent. One detrimental effect of inbreeding is inbreeding depression. Inbreeding depression is caused by the accumulation of harmful recessive alleles. Inbreeding and its effect inbreeding depression can arise in the cases of catastrophic decline in number (genetic bottleneck) and genetic drift in small population when new colonies are founded by small number o f individuals (Greenwood, 1987). It has long been known that the effects on birds are pronounced in reproductive traits (Abplanalp 1974; B l o w and Glazner, 1953; Shoffner, 1948). Sittmann et al. (1966) studied inbreeding effects in the Japanese Quail and found that at F = 0.25 under full-sib mating, there was a decline in viability to 81.5% compared to a non inbred population. Fertility declined to 79.2%, hatchability o f inbred 17 embryo to 72.6%, egg production to 88.9% and body-weight to 96.4%. In inbred leghorn chicken (F = 0.25, under full-sib and half-sib mating), Flock et al. (1991) found only a small decrease in viability to 99.1%, egg production to 96.7% and body weight to 98.1%. It seems that leghorn chickens suffered less inbreeding depression at the same level o f inbreeding. In leghorns chickens, perhaps due to the fact that they had undergone more intensive selection than the Japanese quail deleterious genes with large effects have been reduced (Abplanalp, 1990). To further highlight these point, in turkeys, inbreeding effects at F= 0.25 also included loss of 5.25% hatchability due to mother's inbreeding, 5.66% due to embryo inbreeding and 1.4% increased mortality (Cahaner et al., 1980). However male lines suffered greater inbreeding than female lines in all traits except egg weight. The lower inbreeding effects o f female lines suggests that selection for higher production, better reproduction and viability eliminated deleterious genes from these populations. Body weight measurements in broiler chickens at F = 0.25 under full-sib mating was 92.4% of the non-inbred broilers and viability was 95.2%. When the inbreeding coefficient equaled 0.5 the decline in body weight was to 77.3% and viability to 84.7%. Other birds at F - 0.25 also showed decline in body-weight: White leghorn chickens at 95%, Japanese Quail 96.4, and broad breasted turkeys to 89.9% of the normal body weight. (Cahaner et al, 1980; Abplanalp, 1974; Abplanalp and Woodard, 1967; Sittmann et al, 1966; Woodard et al, 1982). 18 Molecular Determination of Variation Several methods are applicable to measure genetic variation within or between populations. Quantitative genetics has often been used to evaluate economically important traits. While Mendelian genetics is measuring the frequency of the phenotypes, quantitative genetics relies heavily on the mean, the variation, and covariation o f the phenotypes. The use o f these parameters is to estimate regression, correlation coefficients, and the relationship o f these statistics to heritability and repeatability (van Vleck 1987). While the quantitative genetic approach is in the level of the whole animal and thus requires more measurements and the power of statistics, molecular methods have been developed to examine genetic variations at the D N A level and thus are deemed more accurate and require less number of generations. Several molecular methods are appropriate to measure variation within a population. These methods rely on D N A polymorphism and thus can give accurate predications about the future generation. The molecular methods considered for this study were restriction fragment length polymorphism (RFLPs) , random amplified polymorphic D N A ( R A P D ) and microsatellite D N A polymorphism. The R F L P technique involves cleavage o f the D N A at specific sites with restriction endonucleases. Each enzyme has a target sequence o f D N A , which it recognizes and cuts. Depending on the number o f sites in the genome, fragments of various lengths are generated. The fragments are run on a gel to give a distinctive pattern for each individual. The advantage o f R F L P s is their codominant nature in which the heterozygote is 19 recognizable. Their main disadvantage is their relatively low polymorphism (Narayanan, 1991; Gillet, 1991). The R A P D method create genomic fingerprints from species o f which little is known about the target sequence to be amplified. Strain-specific arrays o f D N A fragments (fingerprints) are generated by use o f polymerase chain reaction (PCR) amplification using arbitrary oligonucleotides to prime D N A synthesis from genomic sites which they fortuitously match or almost match. R A P D s exhibit polymorphism and thus can be used as genetic markers. R A P D s are dominant and the presence of a R A P D band does not allow distinction between heterozygous and homozygous states. (Welsh et al, 1990, Wil l iams et al, 1990) 2.1.4 Genome Organization and Microsatellite DNA The eukaryotic genome is customarily distinguished using three D N A categories based on concentration and temperature (Cot plots) D N A annealing curves (Thompson and Murray, 1981). L o w frequency or single copy D N A has relatively slow reassocation time and mostly constitutes the coding genes o f the genome. Moderate frequency D N A with faster reassociation time makes up mostly functional R N A products such as ribosomal R N A , transfer R N A and small nuclear R N A s . High frequency D N A with short reassociation time constitutes repetitive sequences. These repetitive sequences in the genome can be classified as follows: 20 Satellite D N A with repeat size of 5 to 100 bp, usually in clusters o f up to 100 Kbp . Characteristically, satellite D N A is located in the heterochromatin near the centromere (Tyler ef al, 1993). Minisatellite D N A consists arrays with repeats o f 15-70 bp that range in size from 0. 5 to 30 Kbp . Generally they are located in euchromatic regions o f the chromosome (Koreth et al, 1996). Microsatellite D N A consists arrays (often less than 0.1 Kbp) o f tandem repeats o f a very simple sequence, between 1 and 6 bp. Microsatellite are found in the euchromatin regions and their repeat size is highly variable within populations (Koreth et al, 1996). Microsatellites are usually less than 50 repeats in length (Garza, Slatkind and Fremier, 1995) and have a high degree of polymorphism. Polymorphism is primarily due to variation in the number o f repeat units (Bruford and Wayne, 1993). Certain repeats, such as ( C A ) n , occur more often than others in birds. However, repeat type and frequency varies across taxa (Tautz and Schlotterer, 1994; Primmer et al, 1997). Two types of mechanisms theoretically explain the difference in allele sizes and variation (McMurray 1995). The first is unequal crossing over in a recombination event, 1. e. simple repeats located on different D N A molecules pair in a misaligned configuration when a crossing over occurs. This events results in arrays with reciprocal additions and deletions. The second mechanism is D N A polymerase slippage, i.e. during D N A 21 replication, there is a transient dissociation of the template and the forming strands followed by their reanealing in a configuration in which one or more o f the repeats is unpaired. This w i l l lead to either gain or loss of one or more repeats units. Unt i l now microsatellites showed no clear function and further studies are required to clarify their involvement in gene regulation (Lubjuhn et al, 1994; Fitch et al., 1990). However microsatellites have been shown in the past to bind specific nuclear proteins and were thought to play a part in chromatin folding, gene regulation, telomere formation and as a hot-spot for recombination (Tautz and Renz, 1984, Mauler et al., 1992). Furthermore, analysis o f human microsatellites reveals association between certain types of repeats to genomic retrotransposons. For example, poly A tract next to 3' end o f A l u sequences in humans, C A retrotransposons were associated with ( C A ) n in bovine genome (Kavkinen and Varivo 1992). This association is suggesting a common evolutionary process for these repeats with retrotransposons (Nadir et ah, 1996). However, it does not explain association in other types of repeats such as those found in disease associated regions as in fragile-X syndrome, Huntington disease and Myotonic dystrophy. (Nadir et ah, 1996). Microsatellite DNA Applications The use o f polymorphism in genomic sites (loci) of a population can evaluate the genetic variation within the population. The advantages of microsatellite D N A markers -high heterozygosity, ubiquity through the genome (especially adjacent to coding euchromatin regions), and P C R applicability combined with multiplexing- enables their 22 utilization as excellent markers in genome analysis. The applications o f microsatellite markers range from positional gene cloning, quantitative trait loci (QTL) analysis, to populations studies (McDonald et al, 1997). Although a certain class o f microsatellites is usually distributed throughout the genome, each area o f repeats is flanked by unique D N A sequence stretches (Lehmann et al, 1996). These sequence stretches are appropriate for development of P C R priming sites. This facilitates the identification of differences in the number of motif repetitions, among individuals, at a specific genomic site (locus). Soon after they were discovered, it was noted that the length o f the repeat was highly variable. This proved significant for detecting differences in a population and between individuals. The high degree o f polymorphism may yield the most informative data (Ashley et al, 1994, Koreth et al, 1996). Microsatellite markers have been used as a robust tool to determine population variation and structure (Small et al, 1998). Furthermore, The molecular analysis o f economical Q T L is dependent upon the initial characterization o f the variation within the population and the number of available markers. Assessing Genetic Variation Using Microsatellite DNA Microsatellite D N A alleles correspond to Hardy-Weinberg principles and segregate in a Mendelian fashion. Furthermore, since they are codominant and thought to be neutral and they are found in non-coding regions, they have the potential to address an array o f population genetics questions (FitzSimmons, 1995). They can be used to estimate effective 23 populations sizes, assess levels o f gene flow locally or across geographic barriers and hybrid zones, and determine deviation from Hardy-Weinberg (Ashley and Dow, 1994). For example, Abernethy (1994) used microsatellites markers to detect an hybridization zone between the Japanese sika deer (Cervus nippon nippon), which was introduced to Scotland 80 years ago, and the native red deer (Cervus elaphus). The hybridization zone was also found to be at strong linkage disequilibrium. Conversely, areas far from the hybridization zones were at linkage equilibrium. Microsatellites can also be used to detect genetic variation in species that show little allozyme polymorphism (Hughes and Queller, 1993). For example, Blanco et al. (1996) found that heterozygosity in Atlantic salmon (Salmo salar), using allozymes, that polymorphism level was 0.21 ± 0.03 whereas according to the more polymorphic microsatellites it was 0.46 ± 0.04. In a more extreme case, in the social wasp {Polistes annularis), when 33 allozymes loci showed 0.035 heterozygosity, 6 microsatellite loci had heterozygosity of 0.62 (Hughes and Queller, 1993). The difference in polymorphism and heterozygosity is explained by the higher mutation rate at a microsatellite locus, which ranges from 10"3 to 5 x 10"6 per locus per gamete, (Edwards et al, 1992; Bowcock et al, 1994; Forbes et al, 1995; Queller et al, 1993; Jin et al, 1996) whereas an allozyme locus have a lower mutation rate that stands at 10"6 -10"9 (Ayala, 1976). Analysis o f microsatellite allele frequencies in populations has been used to determine 'genetic distance' between populations under the assumption that genetic distance increases linearly with time in isolated populations when the population sizes are 24 constant. I f the population sizes are not constant the rates o f distance w i l l vary. Several studies have used microsatellite D N A to assess aspects of gene flows between populations, population structure in affiliation with migration patterns and relatedness identification (Westneat and Webster 1994). Three models commonly explain microsatellite allele distribution: The estimation o f variation in populations using microsatellite can be resolved through measuring the allele frequencies. In addition to the allele frequency also allele size can be incorporated into the calculations (Freimer and Slatkin, 1996). The use o f allele frequencies in calculation o f variation is done similarly to allozyme and R F L P s using the deviations from Hardy-Weinberg expectations measured as the heterozygote deficiency (F). The incorporation o f allele size into the calculation, is based on the stepwise mutation model ( S M M ) (Ohta and Kimura, 1973) and its derivative the two phase model (TPM) . Another model is the infinite allele model ( IAM) . A l l these models rely on variation in allele sizes. However, according to the stepwise mutation model (Valdes, et al, 1993; Charlesworth, et al., 1994), repeat number increases or decreases by one repeat and there is an equal probability for the occurrence o f either event. A n expansion of this model (TPM) assumes that occasionally mutations increase in more than steps o f one (Freimer and Slatkin, 1996). The I A M model assumes that there are no constraints on allele size. Freimer and Slatkin (1996), suggested that upper and lower limits do exist. Goldstein and Pollock (1996) suggested that the lack o f very large alleles is an evidence for an upper constraint. Garza, et al., (1995) suggested that selection on the loci , gene conversions and biased mutation at 25 a loci might be mechanisms that regulate the repeats number. Angers and Bernatchez (1997) indicated that awareness of the mechanisms of the repeat number variability are important before making assumptions based on variation in allele size. However, the variation in allele size is problematic since the expected frequencies of the sizes are sometimes not visible (null alleles) and also because microsatellite are subject to homoplasmy (Garza and Freimer, 1996). Homoplasmy is the convergence of alleles in different populations or individuals to the same size. Hence, alleles that are identical in state are sometimes not identical by descent. Orti et al. (1997) detected only a weak correlation between the variation of allele size and genealogical relationships. Primmer and Ellegren (1998) in their study of patterns of avian microsatellite evolution found that in some cases instability in allele sizes disclosed unlimited possibilities for homoplasmy. In addition, the spread o f new mutations at microsatellite loci among populations might be faster i f there is gene flow between demes. In this case the deme where the mutation arose might be indistinguishable from the other demes because the mutation would spread due to the gene flow (Streiff et al, 1998). Furthermore, Primmer and Ellegren (1998), also found that the evolution of microsatellites between loci might differ considerably. They found some alleles to remain stable over more than 60 mil l ion years (Myr), and some to be very unstable. Lastly, the avian genome is considerably smaller than the mammalian genome (Hughes and Hughes, 1995). Tiersch and Wetchel (1991) found the D N A content in 165 avian species to 2.83±0.3 pg per cell whereas mammals were found to have about 8 pg per 26 cell (Bachman, 1972; Olmo et a l , 1989). Hughes and Hughes (1995) suggested that since deletions in large introns occurred independently, the reduction o f avian genome was a gradual process prolonging over a long period. Primmer et al. (1997) found that microsatellites occur with low frequency in the avian genome. Evidently, in the avian genome there are additional constraints that affect its size and the frequency of its microsatellites. Thus, the constraints on the frequency of microsatellite might have an influence on microsatellite allele variation. Genetic Variation in Ostriches When discussing the genetic variation of domesticated ostriches it is imperative to understand historic information as wel l as the actual genetic makeup of the farm populations. Wi th regards to the S. c. domesticus, the collapse o f the ostrich industry in South Afr ica between 1913 and 1930 reduced the population from 775,313 to 32,500 (Smit, 1963) which is 4 % of the original population. Whether this "bottleneck" reduced the genetic variation in the Blacks is uncertain. Furthermore, introduction o f w i ld birds into the current farming operation would maintain or increase genetic variation. Pettite et al. (1996) studied genetic diversity in commercial ostrich stocks in the U . S . using multilocus D N A fingerprinting with the M13 minisatellite probe (Ryskov et al, 1988). In the analysis of just 10 birds, 36 bands were scored. Each bird had an average of 9.5 ± 0.3 bands. Band sharing was 0.36 + 0.06 and average band frequency was 0.26 ± 0.8. The studied birds were obtained from known sources and assumed to have inbreeding coefficient of 0. Estimated variability was calculated using pair-wise band sharing. Unrelated individuals 27 were estimated for their variability and band sharing and band frequency was relatively low relatively to commercial poultry stocks. However, compared with w i ld populations of other bird species, the band sharing was higher. For example, in populations of European bee eaters (Merpus apiaster) bands scored per birds were 18.9 with mean allele frequency o f 0.088 and band sharing of 0.169 (Jones et al, 1991). In four Brazilian Macaws species bands scored per bird ranged between 21 to 28 and band sharing ranged between 0.16 and 0.21 (Miyak i et al, 1993). Ma' the ' et al. (1993) examined D N A fingerprints in 23 endangered species of birds o f prey and parrots and found band sharing to be between 0.1 and 0.25. Ward et al. (1998) isolated 5 microsatellite loci from unrelated Australian domesticated ostrich blood samples. The analysis of these loci revealed high degree o f polymorphism. The average degree o f heterozygosity was Ho = 0.80. A previous study by Ward et al. (1994), on a different microsatellite locus, showed Ho = 0.34 in 73 unrelated domesticated ostriches (65 Australian and 8 Kenyan). The distribution of the allele frequency in both studies is given in Figure 2.1. Kimwale et al. (1998) reported Ho = 0.58 in seven microsatellite loci taken from S. c. massaicus, with mean allele number o f 6. Kumari and Kemp (1998) developed primers for 14 microsatellite loci in two ostrich subspecies, S. c. massaicus (n = 6) and S. c. molybdophanes (n = 12). The two subspecies showed significant differences in the distribution of alleles and some alleles were subspecies-specific. Furthermore, in two loci no common alleles were shared. This 28 research is supporting Freitag and Robinson, (1993) observation that S. c. molybdophanes may be very different from the other three subspecies (Kumari and Kemp, 1998). Figure 2.1 Allele frequency histograms for six ostrich microsatellite DNA loci in Australian and Kenyan populations (Ward et al, 1994; Ward et ah, 1998). VIAS-OS4 VIAS-OS8 VIAS-OS14 0.35 0.25 0.15 0.05 < O >^  o a U to O 00 CM i - CD CM CM CM CM VIAS-OS22 VIAS-OS29 0.3 T 0.25 0.15 0.18 0.16 0.14 0.12 0.08 0.06 0.04 0.02 O) IO y N . 10 O) O i - CM CM CO CO CM CM CM CM CM CM VIAS-OS2 0.05 O l ^ c i i - . c o t - . c o h - i ^ . C M C M P J C O t t m i O C O J l 29 2.2 O B J E C T I V E S O F T H E STUDY N o extensive study has been performed to evaluate genetic variability in ostrich breeding stocks in Canada. The objective of the study was to evaluate the genetic variability o f ostrich breeders in British Columbia farms. The evaluation o f genetic diversity is o f profound importance to create a planned breeding program. The evaluation o f genetic diversity was pursued through molecular analysis o f microsatellite markers. The characterization o f these markers in domestic ostrich stock is also an important first step for future attempt to map Q T L in domestic ostriches using microsatellite markers. Further, a related objective o f this study is to examine the inbreeding coefficient and to examine i f there is any correlation of heterozygosity in an individual to body weight. Furthermore, no information is available regarding the North American domestic ostrich microsatellite variability. Hence, it could initiate further studies into the question o f genetic variability and the level of inbreeding ( i f any) in domesticated ostrich breeders. Evaluating the genetic variability is important for maintaining genetic diversity and securing genetic stock since genetic variants could contribute additional diversity to domestic breeds for the food and agriculture in the future (Scherf, 1995). Lastly, acquiring a microsatellite profile for ostriches in the farms can help in identification and placing an individual to its population and thus can help in maintaining better bookkeeping methods. Besides, obtaining a microsatellite profile can aid in 30 determination o f stolen breeding stock (Beamonte et al, 1995) and thus can prevent illegal appropriation o f birds. 2.3 E X P E R I M E N T A L M E T H O D S 2.3.1 Source of Birds Blood samples from ostriches were obtained from three commercial farms in British Columbia. Hereinafter, these 3 farms are denoted as A , B and C . Heart girth (measured as the circumference from the top of the bird's back to underneath the bird's trunk anteriorly to the bird's thighs) and back height (Measured from the top o f the back to the bottom o f the foot with the bird standing) (Figure 2.2) o f most birds were measured ( N = 39 and 54, respectively). In farm A , where a scale was available, body weights were also taken (N= 22). Referring to domesticated ostrich populations, the genetic relationship between the Blue (S. c. australis), Red (S. c. massaycus), and Black (S. c. var domesticus) a. cross product o f several subspecies (S. c. camelus, S. c. syriacus, S. c. australis) is not clear (Pettite et al, 1996) because of pedigree errors and possible contamination. In the literature they have been referred to variably as breeds, varieties, lines or subspecies (Pettite et al, 1996). In this thesis I w i l l use the term subspecies as used by Deeming (1996), Drenowatz et al. (1995) and Seddon et al. (1998). 31 The breeding stocks commonly found in British Columbia farms comprise o f the three major subspecies (Reds, Blues, and Blacks) and their crosses (BluexRed, BluexBlack and RedxBlack). A l l the birds sampled were adult breeders. Fifty-three birds were classified into subspecies or crosses according to their phenotypic characteristics and from information provided by the farmers. The remaining fourteen birds were not clearly classifiable (see Table 2.1). 2.3.2 Collection of Blood Samples One m l o f blood was obtained from each bird. Birds were restrained by two assistants while I drew the blood via venepuncture of the wing vein with a one m l tuberculin syringe. The blood sample was immediately transferred into a 1.5 m l cryovial and placed in liquid nitrogen for transportation back to the laboratory. The blood samples were stored in - 7 0 ° C until extraction. 2.3.3 DNA Extraction and Purification D N A extraction and purification followed the Proteinase K method for general digestion o f protein in biological samples (Sambrook et al., 1988). Fifteen u l o f blood were added to 360 ul S T E buffer, 40 ul 10% SDS, 4 ul proteinase K solution (20 mg/ml) and mixed vigorously. Samples were incubated overnight (at least 12 hours) at 55°C. Extraction was conducted using standard protocol described in Sambrook et al. (1988). D N A was extracted with equal volume of phenol-chloroform-isoamyl alcohol (v/v, 24:1) twice, then with equal volume of chloroform-isoamyl alcohol (v/v, 24:1) once. Crude D N A 32 was washed and precipitated first with two volumes of -20°C 100% ethanol and then with one volume o f -20°C 70% ethanol, air-dried, and resuspended in 200 u l water. The yields of D N A were calculated from the absorbency at 260 nm using a spectrophotometer and by comparison with a 1 Kbp molecular weight D N A standard on a 2% agarose gel stained with ethidium bromide. 2.3.4 Source of Primers Twenty-two primer sequences for ostrich specific microsatellite markers have been published (Ward et al, 1994; Kimwele et al., 1998; Kumari and Kemp, 1988). For use in my experiment, 10 primer pairs (Table 2.2) were synthesized ( G I B C O / B R L Custom primers). These primer sets were chosen by their product size to include both short (100 bp) and long (200 bp) amplification products, simple and compound repeats microsatellites, and different types o f repeats ((CA) n , (TG)„, (TA) n ) . The primer sequences, their reported optimal annealing temperature and the size o f the product are listed in Table 2.2. 2.3.5 P C R Amplification The reaction condition for the markers after optimization are described in Table 2.3 together with the expected condition (Ward et al., 1994; Kimwele et al., 1998; Kumari and Kemp, 1988). Optimization was achieved through trials of varying annealing temperatures; first at the expected (published) annealing temperature and than when an amplification product was visible temperatures were increased (or decreased by 1-4°C) 33 until a clear specific band was attained. Reaction volumes of 30 ul contained 2.0-3.0 m M M g C l 2 ; 10 m M d N T P mix ( G I B C O B R L ) , lOng genomic D N A , 10 pmol o f forward and reverse primers, 2.5 U Taq D N A Polymerase ( G I B C O B R L ) in 200 m M T r i s - H C l (pH 8.4) and 500 m M K C 1 . The reactions were layered with mineral o i l before the placement in a Perkin Elmer D N A Thermal Cycler 480PCR. Amplification program was as follows: denature cycle at 94°C (6 minutes), then 35 cycles o f the following: 94°C (45 sec); optimized annealing temperature (as per marker) for 1 min.; 72°C (45 seconds); final extension at 72°C (6 minutes). The amplification of the 10 markers was tested on 2% agaroze gel with D N A extracted from ostrich muscle tissue. The products o f the amplification were visualized for determination of allele variability through separation on gel electrophoresis on 7% polyaclylamide gel and presented as a photo-image using ultraviolet viewing (Figure 2.3). Figure 2.2 Body measurements taken from the ostriches Back height 34 Table 2.1 Sample size of the subspecies in the different farms. Farm A Farm B Farm C Blue 4 7 8 Red I 3 0 Black 5 1 2 BluexRed 4 2 3 BluexBlack 6 3 3 RedxBlack 0 1 0 Undetermined 11 2 1 Total 31 19 17 Figure 2.3 Photograph of ethidium bromide stained nondenaturing polyacrylamide gel with ostrich microsatellite alleles of locus O S M 4. 200 bp D N A " > marker 100 bp D N A - > marker 00 H o < oo O oo to r r r1 I—I I—I H H 00 00 00 H- H H ~ o ~ o O 00 o o M ^ *o K) C\ o 00 GO 0 0 O ^ ® 5" B" g 5- p.' 3 a* a" 13 » » sr. B D HJ ©• P-5 "» «> S" D o "I B O B n n s 8» a o B 3 » as + + I I I + • • + + -I- + CD 9£ 37 2.3.6 Analysis of P C R Products P C R products (12uf aliquots) were analyzed by polycryamide (7%) gel electrophoresis in 1 X T B E buffer, at 43W for 15 hours. 100 bp D N A ladder ( G I B C O B R L ) was also run in flanking and center lanes for aiding size determination o f alleles. A positive control o f ostrich D N A , as wel l as a negative control of P C R master mix without template D N A (blank P C R control) were also included to detect any handling errors and contamination. Gels were stained with 0.3-0.4 \ig/ml o f ethidium bromide (14 min), de-stained with distilled water (30 min). I examined the distribution of allele size differences by lining together side-by side the samples with the same allele pattern (haplotype) to determine the allele size with reference to a known standard (Weir 1990; Neilan et al, 1994). This analysis provided a convenient summary of the allele sizes and reduced error since all alleles in a locus were scored across the samples horizontally (across haplotypes). 2.3.7 Data Analysis The distribution of genetic diversity within and among breeder flocks and subspecies was calculated through Wright's F statistics: FiS FST and FIT (Wright 1951; also see below) with the aid o f the population genetics programs GENES IN POPULATION 2.0 (May et al., 1995) and Phylip 3.5 (Felsenstein and the University of Washington 1986-1993). Likelihood-ratio test of significance (G statistics; Sokal and Rohl f 1981) of the genetic differentiation o f breeder flock and subspecies was conducted based on allele frequencies calculated. For each 38 population heterozygosity measures were calculated in the forms of Hi. Hs, Hj for each loci and averaged across loci . The subdivision o f populations evokes inbreeding like effect: Since the total population is composed o f several sub-populations, each sub-population may carry only part o f the genetic variation and/or different allele frequencies distribution from the total population. Heterozygosity (H), or the proportion of the genome that is heterozygote can be structured to the different levels of the population. Hi is the observed heterozygosity of an individual in a subpopulation, Hs is the expected heterozygosity of the individual when subpopulations are pooled under random mating (Hardy-Weinberg). HT is the expected heterozygosity o f the individual under Hardy-Weinberg population using the same allele frequency in the total population. The change in the variation in the subpopulation due the inbreeding like effect was measured through Wright's (1951) F statistics. The inbreeding coefficient o f an individual (F) in a subpopulation can also be termed FIS . It measures the reduction in heterozygosity o f an individual in a sub population due to a genetic drift i.e. H — H FJS = —- . The FJS value can be smaller than "0" in a case that the heterozygotes Hs proportion is greater than expected. This situation may arise when there is outcrossing between subpopulations. FST or also the fixation index is a measure for the subpopulation and it reflects its subdivision. The reduction o f heterozygosity in the subpopulation due to Hj — Hs genetic drift is hence FST = . Another measure for the individual is the reduction of Hj H — H heterozygosity relative to the total population. Hence Fn = — . Fn takes into account H -p 39 the effect of subpopulation's nonrandom mating and the effect of the population's genetic differentiation. Measures o f genetic identity and distance were calculated using Nei ' s (Nei, 1976) Genetic distance with the aid of Phylip 3.5 (Felsenstein and the University of Washington 1986-1993). Genetic distance is the genetic difference between populations derived from the gene and allele differences. When two populations are isolated from each other through geographic or other reproductive barriers, the populations would accumulate different genes. The differences can occur from genetic drift and on a longer time-scale from selection and mutations. A convenient and practical measure o f genetic distance is based on the proportion of shared alleles (Chakraborty and Jin, 1993). This distance is useful when measuring distance between populations as well as individuals. This distance measure was found successful when estimating distances between populations as wel l as when placing an unknown individual back to its original population (Estoup et al, 1995). The estimation o f YuS shared alleles dictates the identity by PSAj = ==^—. Where S is the number of shared alleles summed over u loci . The distance between individuals is estimated by DSA/ = \-PSAj • Ne i ' s (1975) measure of genetic distance is one o f the most widely used measures o f genetic distance (Hartl & Clark, 1989). The idea behind the method is expressing the probability that two alleles in a locus would be identical. Chosen from the two populations the distance is measures versus two alleles in the same locus in one of the populations. Thus, in two populations, denoted X and Y, Jxx is the probability that two alleles chosen at random from 40 population X are identical (homozygous). Jyy is the probability that two alleles from population Y are identical and Jxy is the probability that two alleles, one chosen from population X and one from Y would be identical. The normalized identity (i) developed by J Nei is defined as / = . . The summation over alleles would be / = . . PXXJYY VSa-'E^-2 The standard genetic distance, D , would be D = -Ln(I). The averaging over many loci naturally gives a much more reliable measure (Nei, 1976). Empirically, Ruzzante (1998) found F$T to be a most reliable (unbiased) measure in estimating genetic distance in sample sizes larger than N=50 to N=100 for two microsatellite loci . The reliability o f the FST measure was found to be dependent both on number of loci , allele per locus and the range of alleles. Sample sizes larger than 100 were found not to decrease the confidence intervals in the estimation o f the genetic distance. Slatkin (1995), measured the FST performance and found it to be reliable when time since divergence is relatively short. FST does not consider the stepwise mutation model and consequently does not take into consideration the distance between alleles only i f the are different. Hence the FST would be reliable when the main difference between population is genetic drift. Phenograms were obtained through Phylip 3.5 as well , using U P G M A methods of phylogenetic tree reconstruction (Sokal and Michner, 1958). The U P G M A was originally developed for the construction of phylogenetic trees based upon phenotypic similarities between operational taxonomic units (OTU). Nevertheless, U P G M A can also be applied for the construction of dendograms using distances acquired from molecular data. However, in 41 this case, the assumption that the rates of evolution amongst the different lineages are constant must hold. Thus, U P G M A is using a linear relation between evolutionary distance and divergence time (Nei 1975). Nei ' s genetic distance is assuming constant rates of evolution among the different lineages. Hence, the employment o f these distances into the U P G M A clustering is appropriate. The U P G M A method is using a sequential clustering algorithm: the lineages with the closest distance are first clustered together and afterwards the next closest is clustered with relationship to the first two, using them as an independent topological unit ( L i , 1997). Hence, relationships between two composite O T U are built on the basis o f increasing distance. The distance between a still unclustered O T U and the new O T U , which is composed o f two OTUs , is computed as follows: using the arithmetic mean of the pairwise distances between the constituent OTUs of the two composite O T U s and the new O T U . Correlation of body measurement parameters, heterozygosity and analysis o f variance were conducted using JMP 3.2 (SAS institute 1989-1997). 2.4 R E S U L T S O f the 10 ostrich specific microsatellite markers, LIST011 generated amplification products but was not possible to score since it showed two bands across all samples, and V I A S - O S 2 did not generate any P C R product after repeated trials. The remaining eight have been amplified successfully and were compared with the original publication on the basis of 42 their expected (published) and observed (optimized) annealing temperatures and size for confirmation o f their identity (Table 2.4). Seven o f the eight loci were polymorphic in the total population (Figure 2.4) and in each farm (Figure 2.5). However, the number o f alleles observed was lower than that reported (Kimwele et al, 1998; Kumari and Kemp 1988; Ward et al, 1994). LIST009 was monomorphic. The number of alleles at the eight loci ranged between 1 and 5 (mean = 4). Population specific alleles were found in loci OSM11 (allele 120 was found only in farm B) and O S M 5 (allele 183 was found only in farm A ) . 2.4.1 Genetic Variations in Ostrich Breeder Flocks Heterozygosity values ranged between 0.488 (Farm C) and 0.553 (Farm A ) (Table 2.5). Within population standard error (S.E.) was similar in all 3 farms ranging from 0.104 in farm A to 0.12 in farm C. Although only 4 loci indicated significant genetic differentiation between the breeder flocks, overall, differentiation based on microsatellite loci was significant between the breeder flocks over the eight loci . The G value of 100 (df = 52) summed across all loci was significant at the a = 0.001 level and the FST value was 0.031 with the low S.E. of 0.000 (Table 2.6). The inbreeding coefficient Fis value (which measures the decrease in heterozygosity due only to inbreeding within subdivisions) was 0.045 with S.E. o f 0.042. The low inbreeding coefficient indicates that inbreeding is not observed across the farms based on the correlation allele frequency in the population relative to alleles drawn at random from within a subpopulation. Some Fis Values were negative indicating an excess o f heterozygotes over what is expected of a Hardy-Weinberg population. 43 Genetic identity, the level in which two populations are indistinguishable (Hartl and Clark, 1997) based on their microsatellite allele frequency, was found to be higher between farms A and B (0.0386) than between A and C (0.0538) or B and C (0.0730) according to Nei ' s identity (Table 2.7). r r i—i i—i oo oo oo H H H o o © o o o to ON oo Ul 00 H o o Ul O 00 4^  00 H o o Ul Ul Ul Ul Ul 0 0 Ul Ul Ul Ul ON Ul Ul Ul Ul ON Ul Ul ON ON Ul to p—> (O i— » OJ H - to M0 oo Ul Ul o 4^  o 0 0 o to to o 0 0 o to to o ON ON Ul o 00 Ul Ul to o Ul o Ul IB i j O fjq ^ £ °> W p , CO i f 6 ' CD o CM O P » n O S 2 Q • • o 8 Q 3 a,, 45 Figure 2.4 Allelic frequency in the seven polymorphic microsatellite loci of ostriches pooled over all three breeder flocks. OSM 11 LIST001 0.523 0 s o o o o in o o O CM CM CO CM CM CM CM CM OSM 4 0.413 160 178 180 190 Allele Length (bp) Figure 2.4 continued next page 46 Figure 2.4 Allelic frequency in the seven polymorphic microsatellite loci of ostriches pooled over all three breeder flocks (cont). LIST002 OSM 5 0.652 13 o o 142 150 158 166 0.7 T 0.6 -0.5 0.4 0.3 0.2 0.1 0.62 0.11 0.16 • 0.09 m co o N . oo o T- T " CN LIST006 0.3 -r 0.25 0.15 0.277 0.05 co oo Allele Length (hp^ 47 Figure 2.5 Allelic frequency in the three different farms (A, B and C) at the seven polymorphic loci. LIST001 0.5 T 160 178 180 190 LIST005 Allele Length (bp^ Figure 2.5 continued next page 48 Figure 2.5 Allelic frequency in the three different farms (A, B and C) at the seven polymorphic loci (cont.). 0.8 0.6 0.4 0.2 0 0 s -13 <4H o >^  3 0.4 0.3 0.2 0.1 0 175 140 143 OSM 5 • A • B • C 183 LIST006 190 200 _ j fcJ. id, h , fe • c 145 150 153 148 LIST002 0.8 0.6 0.4 0.2 0 142 • A • B • C 150 158 166 Allele Length (bp^ 49 Table 2.5 Summary of heterozygosity of an individual in the subpopulation (farm) (H0), expected heterozygosity for an individual in a subpopulation (Hs), and expect heterozygosity in the total population (Ht). Locus Ht Hs Ho O S M 1 0.629 0.607 0.387 LIST001 0.778 0.755 0.879 O S M 4 0.732 0.702 0.49 A B C LIST005 0.335 0.322 0.402 Average Hs 0.553 0.548 0.488 O S M 5 0.556 0.542 0.356 S.E. 0.091 0.102 0.091 LIST006 0.805 0.785 0.844 Average H0 0.513 0.482 0.522 LIST002 0.54 0.525 0.688 S.E. 0.104 0.106 0.12 LIST009 0 0 0 H, H H0 Average 0.547 0.53 0.506 Variance 0.009 0.008 0.011 S.E. 0.095 0.092 0.103 50 Table 2.6 F Statistics of genetic differentiation of ostriches among farms. For the average F statistics S.E. values are given in brackets. Locus FJS FIT FST G D f O S M 1 0.362 0.385 0.036** 16.084 8 LIST001 -0.165 -0.13 0.03* 13.487 8 O S M 4 0.303 0.331 0.04** 24.517 8 LIST005 -0.248 -0.199 0.039 6.936 4 O S M 5 0.344 0.361 0.026** 18.794 8 LIST006 -0.075 -0.048 0.025 10.28 10 LIST002 -0.312 -0.275 0.028 9.904 6 LIST009 - - - - -Average Fis FIT FST 0.045 (0.042) 0.075 (0.041) 0.031 (0.000) Total G D f (FST significant at a = 0.001) 100.002 52 * Significant at a=0.05 ** Significant at ct=0.001 51 Table 2.7 The genetic distance between the breeder flocks in the different farms according to Nei's measurement. Nei 's Distance Farm A B A B 0.0386 C 0.0538 0.0730 2.4.2 Genetic Relationship of the Subspecies Al le l i c distributions in the subspecies are given in Figure 2.6. Since the Black, a synthetic subspecies, has a polyphyletic origin consisting mainly of the Blue, it is expected to share a large number o f alleles with the Blue. In locus O S M 11, the Blue and Black have common alleles 120, 130 and 140 but the same alleles were not found in pure Red. In locus LIST001, alleles 200, 230, and 240 were not found in the Black were also not found in the Red. Other alleles shared by the Black and Blue but not found in the Red are: locus LIST005, allele 225; locus O S M 5, alleles 175 and 200; locus LIST006, alleles 140,143,145, and 150; locus LIST002 alleles 142 and 158. In locus O S M 4, the Blue and the Black shared an allele not found in the Red (190). However the Red and the Blue shared an allele (160) not found in the Black. 52 Heterozygosity values ranged between 0.439 (Blue x Red) and 0.536 (Black). However, the S.E's. were large (ranged between 0.064 (Red) and 0.101 (Blue); Table 2.8). Although individually only one locus showed significant genetic differentiation among subspecies, overall, it was found significant when all eight loci were considered together (Table 2.8). The G value of 73.007 (df = 52) summed across all loci was significant at the a = 0.05 level o f critical value (Table 2.9). Examination of allelic and genotipic frequencies revealed that these populations were not in Hardy-Weinberg equilibrium. Some FJS values were negative indicating an excess of heterozygotes over what is expected o f Hardy-Weinberg populations. The over-all FST value of 0.114 with S.E. of 0.009 indicates that moderate differentiation exists in the subspecies and it is significant (FST values o f 0.05 to 0.15, 0.15 to 0.25, and above 0.25 are considered moderate, great and very great differentiation respectively) (Hartl, 1980). However, extreme caution should be taken with these results due to the small sample size Figure 2.7 shows the U P G M A phenogram based on genetic distances among the subspecies and crosses. The distances were calculated both according to Nei ' s genetic distance (Table 2.10). The Blue, BluexBlack cross, and BluexRed cross formed a very close cluster with the Black slightly more distant and the Red a long distance away. This phenogram was the expected under the assumption that the Blue was the base population for the creation o f the Black. Thus the Blue, Black and their crosses should be more similar genetically than either one of them and the Red. 53 Figure 2.6 Allelic frequency in the three different subspecies and crosses at the seven polymorphic loci. OSM 11 0.8 0.6 0.4 0.2 + 0 • 120 0130 • 140 1150 • 155 B L A C K B L U E / B L A C K B L U E B L U E / R E D R E D Figure 2.6 continued next page 54 Figure 2.6 Allelic frequency in the three different subspecies and crosses at the seven polymorphic loci (cont.). LIST005 0 s -u "33 O 2 0.8 0.6 0.4 0.2 J J J J I B L A C K B L U E / B L A C K B L U E B L U E / R E D R E D OSM 5 • 225 • 40 • 247 • 175 S3180 • 183 • 190 • 200 B L A C K B L U E / B L A C K B L U E B L U E / R E D R E D LIST006 B L A C K B L U E / B L A C K B L U E B L U E / R E D R E D Figure 2.6 continued next page 55 Figure 2.6 Allele frequency in the three different subspecies and crosses at the seven polymorphic loci (cont.). LIST002 B L A C K B L U E / B L A C K B L U E B L U E / R E D R E D Table 2.8 Summary of H„, H s , H t for three different subspecies and two crosses Locus Ht Hs H0 O S M 1 0.548 0.471 0.247 LIST001 0.716 0.588 0.74 O S M 4 0.715 0.576 0.539 LIST005 0.312 0.287 0.365 O S M 5 0492 0.435 0.273 LIST006 0.56 0.586 0.747 LIST002 0.561 0.492 0.755 LIST009 0 0 0 H Hs Ho Average 0.488 0.429 0.458 Variance 0.007 0.005 0.01 Total 0.083 0.071 0.1 Black Black x Blue Blue Blue x Red Red Average Hs 0.527 0.519 0.546 0.483 0.375 S.E. 0.086 0.084 0.101 0.09 0.064 Average H0 0.536 0.506 0.518 0.439 0.5 S.E. 0.106 0.096 0.11 0.12 0.154 57 Table 2.9 F statistics for genetic differentiation among subspecies For the average F statistics S.E. values are given in brackets. Locus Fis FIT O S M 1 04(39 0479" LIST001 -0.274 -0.145 O S M 4 0.138 0.354 LIST005 -0.252 -0.181 O S M 5 0.381 0.427 LIST006 -0.34 -0.227 LIST002 -0.538 -0.438 LIST009 FST G D f _ _ _ _____ 0.101 7.955 8 0.25* 23.303 8 0.057 4.982 4 0.074 7.514 8 0.084 9.396 10 0.065 6.665 6 Average Fis FIT -0.073 (0.053) 0.049 (0.052) Total G df 73.007 52 FST 0.114(0.009) (FST Significant at a = 0.05 level) * Significant at a=0.05 58 Table 2.10 The genetic identity of the subspecies and crosses according to Nei's measurement. Nei 's Distance Black B l u e x B l a c k Blue BluexRed Black BluexBlack 0.1061 Blue 0.0533 0.0466 BluexRed 0.0944 0.0441 0.0486 Red 0.2939 0.1628 0.2163 0.2019 Figure 2.7 U P G M A phenogram based on Nei's genetic distances in eight loci among subspecies of domesticated ostriches and their crosses. 59 2.4.3 Body Size and Body Weight Measurements Body weight differences among subspecies The mean body weight of the different subspecies and crosses is shown in Figure 2.8. The Black had the lowest mean body weight (113 kg) with the lightest bird at 98 kg and the heaviest at 154 kg. . It should be noted, however, that all the Blacks sampled were females, van Schalkwyk et al. (1996) found the mean weight of Blacks to be 120 kg Red had the highest mean (146) with the lightest bird at 130 kg and the heaviest bird at 160 kg. The Blue had mean weight of 135 kg with the lightest bird at 114kg and the heaviest bird at 155 kg. (Table 2.11). The crosses between subspecies (the crosses) had the respective intermediate values. Sex differences in body weight among subspecies Male and female body weight are given in Table 2.11. In all cases the males were heavier than the females (PO.0059). Red had the highest mean both for females and males (141 and 159 kg, respectively) in the pure subspecies. The Blue females had mean weight of 132 kg and Blue males weighed 141 kg (Maclean (1993) reported that Blue males may reach 157 kg. Figure 2.8CaIculated body weight in the different subspecies and crosses. The line across diamonds reflects group means. Diamond height represents 95% confidence interval and diamond width represents the group sample size. 61 Table 2.11 Body weights of the different subspecies and their crosses Subspecies Male body weight Female body weight N k g ± S E N k g ± S E Black 8 113.1 ± 3 . 4 3 BluexBlack 3 135.9-5 .60 7 114.6 ± 3 . 6 7 Blue 8 141.4 ±3.43 11 132.0 ± 3 . 0 7 BluexRed 3 146.4 ± 6 . 8 7 6 143.4 ± 3 . 6 7 Red 1 159.6 ± 9 . 7 1 3 141.8 ± 5 . 6 0 Correlation of body measurement parameters The following section describes correlation o f body weight measurements that were calculated in order to find whether the degree of heterozygosity in an ostrich affects its body weight. Body weight measurements were only taken from a limited number of ostriches (N=22). However the birds with available weight belonged to several subspecies and crosses in both sexes and the samples were also not balanced. Since heart girth and back measurements were highly correlated with body weight (see below), additional 26 samples were obtained by converting body size measurements to body weight. The following section describes the correlations o f body weight measurement that were studied to perform the conversion. Correlation between back height and body weight 62 The mean body weight was 131.28 kg and mean back height was 1.38 m. The correlation between the back height and body weight (r = 0.64) (Figure 2.9) was highly significantly (P< 0.0013). The number of birds sampled was 21. Correlation between heart girth and body weight The mean heart girth was 1.89 m. The correlation between the bird's heart girth and body weight (r = 0.84) (Figure 2.10) was highly significant (P < 0.001). The number o f birds sampled was 22. Figure 2.9 Correlation between back height and body weight r = 0.64 Weight = -103.34 + 172.513xBack height 1.15 1.20 1.25 1.30 1.35 1.40 1.45 1.50 1.55 Back height (m) Figure 2.10 Correlation between heart girth and body weight. 63 r - 0 . 8 4 Weight = -134.15 + 168.818xHeart girth 1.40 1.45 1.50 1.55 1.60 1.65 1.70 1.75 1.80 Heart girth Conversion of body size measurements to body weight Both back height and heart girth are significantly correlated with body weight (See previous section). Since back height was measured in a larger number o f individuals than heart girth, it was used to estimate body weight of additional 30 birds using the following equation: Weight = -103.34 + 172.513 Back height. In order to measure the correlation between body weight and heterozygosity effects across treatments had to be removed. The treatments that were taken into consideration were the farm, sex and subspecies effects. Accordingly, the following formula, which is based on decomposition of the means, was used. It should be noted that the data set is not balanced in all farm, subspecies and sexes. Body Weight = \iBWMrd-\iBWsubspecier\iBWgender\i£Wfarm+\\3BW Correlation between heterozygosity and body weight 64 The correlation between the bird's heterozygosity values and adjusted body weight (Figure 2.11) (r = 0.28) was low but significant (P < 0.05). The number o f birds used in the analysis was 48 (4 birds were excluded from the analysis since they were not classified to one o f the subspecies or crosses). For individual locus, there was no difference in body weight between homozygotes and heterozygotes for all loci examined. There was also no association of any particular genotype or allele with body weight. Figure 2.11 Correlation between Heterozygosity of birds and body weight r - 0 . 2 8 3 Weight = 124.057 + 18.4823xHeterozygosity Heterozygosity 2.5 DISCUSSION The objectives of this study were to examine the genetic variation within and among ostrich breeder flocks in B C as well as estimating the level o f inbreeding. A further aim was to acquire genetic data that could help ostrich breeders with a breeding plan. The study o f genetic variation in domesticated ostrich breeding stock is posing an interesting challenge due to the 65 complexity o f the ostrich breeding operation. The ostrich breeding stock has gone through genetic drifts in the creation of the base population, cross breeding for the creation of the Black as wel l as bottlenecks as previously described (Section 2.1.1) . The farm operations today are usually small relatively to other poultry species. Furthermore, the breeding scheme of ostriches does not allow the breeding of one male with more than two or three females. A l l these constraints combined may have an effect on the genetic variation. 2.5.1 Genetic Variation Within and Among Different Breeder Flocks Genetic variation in the breeding stock of British Columbia based on the population o f the three farms examined is lower than that reported for Australian ostrich farm operations (Ward et al., 1998). Ward et al. (1998) isolated 5 microsatellite loci from unrelated Australian domesticated ostriches and found high degree of polymorphism (Ho = 0.80). It should be noted, however, that he selected unrelated animals in his study that may result in the high Ho- A previous study by Ward et al: (1994), based on one microsatellite locus, showed Ho = 0.34 in 73 unrelated domesticated ostriches. Kimwale et al. (1998) reported Ho = 0.58 in seven microsatellite loci taken from S. c. massaicus, with mean allele number of 6. Even though I used different loci the Ho value I found in my populations was therefore within the range of Ho values for ostrich populations reported in the literature. In wi ld bird species, Ho values ranges between 0.65 and 0.8 (Piertney and Dallas 1997; Piertney et al, 1998; Petern et al, 1988; McRae et al, 1999; Sachs et al, 1999; Primmer et al, 1995; Neuman and Wetton 1996). The heterozygosity found in the ostriches is similar to that found in some broiler chicken lines (Ho = 0.53) (Crooijmans et al, 1996). 66 The analysis in this study was conducted solely through microsatellite D N A variation. Microsatellite markers have been used to determine variability in avian populations previously and were useful for the detection of genetic variation and regional differentiation (Piertney et al, 1998). Nevertheless, other methods are applicable to measure genetic variation. Petitte et al. (1996) used multilocus D N A fingerprinting and similarly found substantial variation in domesticated American ostriches. Even though no allozymes variation data is available for ostriches, allozymes studies in birds indicated that they possess levels of variation at these genes comparable to other vertebrate classes. Eighty-five bird species were found to have He= 0.063 per individual per locus and mean percent of polymorphism of 29% in 109 bird species (Evans, 1987). Since there is no information regarding ostrich allozymes variability, I assume it to be in the general range of other vertebrates. Given that the ostrich genetic variation as revealed from genomic polymorphism (both D N A fingerprinting and microsatellite D N A variation) is suggesting substantial variation at a comparable level of other domesticated and natural populations. Hence, it is -safe to assume that their genomic (multilocus fingerprints and microsatellite D N A ) heterozygosity is at the acceptable merits of their representation of total genomic variation. Even though some layer chicken lines have heterozygosity o f Ho = 0.27. Variability of eight chicken lines using microsatellite markers reveals heterozygosity levels o f 0.293 to 0.67 with most lines at 0.4. This heterozygosity is lower than that found in the ostrich studies including this research. Furthermore, FST values for chickens range between 0.204 to 0.602, 67 suggesting high degree of differentiation (Vanhala, 1998). This large differentiation is probably because the chicken has been domesticated for thousands of years and in the last century has been subjected to extensive selection with the creation of specialized breeds and lines. The ostrich, however, has not gone through the same process of intense selective breeding. Even at the same time frame, ostriches w i l l evolve slower than chickens due to a longer generation interval. The comparability of the genomic variation as found previously and in this study of ostriches recently taken from the wi ld , further validates this point; Hence it is safe to assume, both on the account of D N A fingerprinting (Petitte et al, 1996) and the comparability to other ostrich variation studies that the results represent actual differentiation. In contrast to wi ld animals, the appearance o f domestic animals is very diverse, especially with the respect to the color and type of coat, the body size and shape. The diversity is based on the reduction in natural selection on the one hand and artificial selection in the course of breeding on the other. This provides the foundation for the numerous breeds (Hemmer, 1990). The ostrich is a fairly recent domesticate compared to most domesticated animals and is polyphyletic. Hence, it should still carry large amount of diversity accumulated in the wi ld . From the FST values and the identity between the breeder flocks in the 3 farms it seems that the farms hold genetically differentiated breeders stocks. The low FJS value o f 0.015 indicates that inbreeding was not found throughout the farms. Some FJS values were even negative because of excess in heterozygotes over the expected frequency. The negative FJS value 68 might be explained by the prudence that farmers might be implementing when setting up mating pairs to be from different sources in order to avoid inbreeding. Based on my findings, there does not seem to be a serious problem o f inbreeding among the breeder stocks in B . C . ostrich farms. 2.5.2 Genetic Variation in The Subspecies Genetic variation between subspecies was found to be agreeable with the history and evolution of ostriches and the farming operations in the ostrich. Since the Blue (S. c. australis) was the base population in the creation o f the Black, the two should be genetically closer than the Red. The other subspecies that were introduced for the creation in the Black, i.e. S. c. syriacus and S. c. camelus were not available for examination. The S. c. syriacus is now extinct and the S. c. camelus o f the sub-Saharan regions is not found in major farming operations. I therefore was not able to examine their relatedness with the other subspecies. The Red that originated mainly from Kenya was found to be different from the Blue, Black and their crosses. The U P G M A phenogram shows that the Red is the most distant from the rest of the ostrich clad and the rest have relatively short branches. Furthermore, in locus O S M 5, there were alleles that were present in the Blacks and Blues that were absent in the BluexRed cross and the Red. This provided additional support that the Red was genetically more distant than the Blue and the Black. In my study, I detected some subspecies-specific alleles. The number of birds tested in each subspecies was small and these alleles may not be truly subspecies-specific when a larger number of birds are examined. The fact that these alleles were only present in a subspecies and 69 their crosses, and not found in unrelated crosses seemed to provide support that alleles not found in certain subspecies may indeed be absent or in extremely low frequency. 2.5.3 Correlation Between Heterozygosity and Body Weight There was a low but significant correlation (r = 0.28) between heterozygosity and body weight. Since there seems to be little inbreeding among the breeder flocks in the farms, this correlation may not indicate any inbreeding depression. While I have standardized the body weights by subspecies, farms, and sexes, the formula may not be totally effective in eliminating these biases. On the other hand, this correlation may indicate heterosis in body weight traits. Recently, microsatellites, that are often assumed to be neutral, have been reported to co-segregate with fitness-associated genes and their analysis revealed heterosis (Biern et al, 1988; Coulson et al, 1988). Populations of red deer have been reported to show in areas of mixed populations, higher heterozygosity and also heterosis in body weight. Similarly, the ostrich breeding stocks are o f varying genetic backgrounds (Black, Blue and Red). There was also recent inclusions of w i ld ostriches in the farm populations which could create this heterosis. Microsatellites have been a useful tool measuring outbreeding and inbreeding in populations (Coulson et al, 1988). Even though the exact reason for positive correlation between heterozygosity and body weight is not known, recommendations to the ostrich breeders could still be brought about. In any event, farmers should cross birds that are the least genetically related based on microsatellite D N A markers. This would not only prevent inbreeding depression but also make 70 use o f heterosis to breed a heavier bird for the market. I have calculated genetic relatedness of individual birds within each breeder flock and recommendations can be made to the farmers for such a breeding scheme. Furthermore, since the different domestic subspecies cross-breed successfully, outbreeding depression associated with genetic incompatibility through mating an individual of different genotype (Greenwood, 1987) does not seem to be a problem in the ostriches, at least as indicated by body weight. Since the breeding flocks are usually small and farmers do not exchange breeding bird often, it w i l l be important for farmers to avoid inbreeding under these constraints. The ameliorated captive environment provided protection from many natural elements to the birds, and is fairly stable over time. In many cases, inbreeding can develop without inbreeding depression being detected (Lacy et al. 1993) until there is a change in the environment. Hence, the effects o f inbreeding depression are more serious i f they are inclined to be unseen temporarily under an hospitable environment. 2.6 CONCLUSIONS The distinct genetic profile o f each farm maintained can allow farmers to have a better book keeping method. The estimation and quantification of allelic frequencies within and between farms and subspecies allows examining population structure and confirming the identity o f individuals (Estoup et al., 1995) using the genetic distance based on the proportion o f shared alleles. (Bowcock et al., 1994). Even though farm specific alleles were found, their frequencies are very low and thus introgerssion of a marker into the whole population in the farm is not feasible under the current methods and the long generation time in ostriches (2-3 71 years). Furthermore, future importation o f breeders stock could distort this distinctiveness o f a certain farm. The results are suggesting that genetic variation of ostrich breeding flocks in B C is comparable with other ostrich farming operations. The correlation between heterozygosity and body weight found is suggesting o f increment in body weight with higher levels of heterozygosity in the farms examined. However, since many conversions have been performed in standardizing the body weight, this correlation remains inconclusive and should be further studied. The results are also suggesting that the different subspecies are distinctively different in their genetic pools. This is suggesting that they represent genetically distinct lines. Hence, the appropriation o f a higher genetic variation in the breeding stock could be achieved by mixing as much as variants of subspecies as possible to increase the genetic stock. A s a consequence of this study a genetic profile of ostrich breeders in three different farms based on microsatellite markers was obtained. The farmers can now obtain a knowledge o f the genetic relatedness o f their breeders. Mating breeders with a dissimilar microsatellite profile can now aid the breeders in the avoidance of inbreeding without relying on the often erroneous pedigree records. 72 3 E M U AND T I N A M O U M I C R O S A T E L L I T E L O C I A M P L I F I E D B Y OSTRICH PRIMERS 3.1 INTRODUCTION 3.1.1 Cross-Species Amplification Using Ostrich Microsatellite markers Microsatellite as D N A markers for genomic or population studies have the advantage of having high heterozygosity, ubiquity through the genome, and their flanking regions are appropriate for utilizing the P C R amplification procedure (McDonald et al, 1997). However, the main disadvantage o f using microsatellite D N A is its nature o f being genome specific (Queller et al., 1993). The isolation o f primers for a genus specific microsatellites requires construction of a genomic library, sequencing of numerous clones and designing appropriate primers (Rassmann et al., 1991, Ashley and Dow, 1994). Formally, the lack o f primers that amplify species specific loci was limiting microsatellite usage (Schlotterer and Pemberton, 1994). A convenient way to get around this problem to a certain degree is to attain markers through cross-species amplification. In cross-species amplification o f microsatellites, D N A primers designed in one species amplify specific microsatellite regions in closely related species (Brudford and Wayne, 1993; Hughes and Queller, 1993; Tautz and Schlotterer, 1994; Schlotterer and Pemberton, 1994). For example, human primers work in rhesus macaques (Macaca mulatto) (Kayser et al., 1996), chimpanzees (Pan troglodytes) (Deka et al., 1994), baboons (Papio hamadryas) and other primates (Coote and Brudford, 1996). Canine primers 73 cross amplify loci within the fox family (Vulpus velox), coyote (Canis lanrans), and grey wolves (Canis lupus) (Roy et al, 1994). Primers designed for the domestic cat (Felis catus) can cross amplify puma (Puma concolor), l ion (Panthera leo), and cheeta (Acinonyx jubatus) (Menotti-Raymond and O'Brien, 1995) D N A . Bovine primers show cross amplification in goats (Pepin et al, 1995) and also in sheep (Moore et al, 1991). In the division Neornithes, microsatellites among various waterfowl species appear to be conserved (Fields and Scribner, 1997). Primers developed in swallow and pied flycatcher also amplify microsatellites in a wide range of birds (Primmer, Mol ler and Ellegran, 1996). Primer and Ellegren (1998) analyzed the cross amplification o f three microsatellite loci (one was cloned in pied flycatcher and the other two in barn swallow), in birds spanning all avian phylogeny including the ostrich. They found that detectable patterns o f microsatellite evolution probably differ markedly between loci . One primer set successfully cross-amplified microsatellites in 58 out of 58 birds species tested including representatives of all major bird lineages. This locus was also found in the most distant ostriches. The other two primer sets cross-amplified only partly across lineages. Their study also supported the notion that homoplasmy occurs in these loci through forward and backward mutations. The success of heterologous primers depends upon the conservation of primer sequences and the stability of microsatellite repeats over time (Tautz and Schlotterer, 1994; Ashley and Dow, 1994; Menotti-Raymond and O'brien, 1995). On the other hand, since microsatellites are mostly located in non-coding regions, they are subjected to high mutation rates. 74 Accumulation o f mutations that can inhibit amplification in one species with primers developed in a distantly related species (Primmer, et al, 1996). Primer et al. (1996) found that the proportion o f microsatellites that amplified various avian species decreased with increased genetic distance. Studies of cross-species amplification have also shown that smaller alleles, less heterozygosity and less genetic variation can be expected in non-source species (Forbes et al, 1995; Ellegran et al, 1997). Mutation rates and dynamics at homologous loci may also differ within a taxa (Forbes et al, 1995; Garza, et al, 1995). However, Angers and Bernatchez (1997) found that homologous sections of a microsatellite locus were exposed to the same mutational event across salmonid species. Petren (1997) suggests that i f possible, cross-species amplification should be performed with primers designed in closely related species to yield the best results. In addition, even after amplification a degree of caution should be taken in the interpretation of the results. The paleognathous subdivision o f the l iving birds also shows cross-species amplification. Kimwele et al. (1998) developed seven primers for ostrich microsatellites and tested the cross amplification with three other ratites. Amplification varied between the species, however the amplification was generally successful (Table 3.1). Ward et al. (1994) examined cross-species amplification of emu (Dromaius novaehollandiae) genomic D N A with primers for one ostrich microsatellite marker, however no amplification product was visible (Table 3.1). 75 Table 3.1 The results of cross amplification of 8 ostrich specific microsatellite primers in other ratite birds. Locus* Cassowary TV = 6 Rhea TV =6 Emu TV= 6 O S M 1 + (2) + (4) + (4) O S M 2 + (2) + (4) + (4) O S M 3 + (3) + (3) -O S M 4 + (2) - + (4) O S M 5 - - + (2) O S M 6 - - + (4) O S M 7 + (1) + (2) + (4) V I A S - O S TV is the number of individuals tested. + represents positive amplification (In bracts the number of samples amplified) - represents negative amplification * O S M 1 to 7 were tested by Kimwele et al. (1998) and VIAS-OS2 was tested by Ward et al (1994) 76 Even though the extent o f polymorphism in the cross-amplified loci was not known for the emu before, the application o f such markers in the paleognathous subdivision could contribute to farming operations by assessing the genetic makeup o f an individual or population, for identification purposes, introgression programs and predicting heterosis (Hi l le l et al, 1992). It is also o f interest to acquire more knowledge, particularly for other paleognathous farm birds such as the partridge tinamou (Nothroprocta perdicaria sanbonii). Paleognathous bird farming operations are juvenile industry and there is only limited information regarding their genome compared to traditional poultry operations. In previous attempts, five out o f seven ostrich specific primers amplified D N A sequences in the emu (Kimwele et al, 1998) and further examination o f other primer sets could contribute the attainment of more markers. The benefits could be the acquirement of markers for positional gene cloning, Q T L analysis, population studies and marker assisted selection. 3.1.2 Emu Farming In Australia the first emu farming operation commenced in Queensland late in 1976 when the Department of Environment and Heritage allowed the Cherbourg Aboriginal Community at Murgon to take emus from the wi ld under Section 25 o f the Fauna Conservation Act . However, the wider commercial industry started in 1987 in that state. Emus are ki l led when they are between 1 and 2 years old. Their main products are o i l for cosmetics and rubbing ointments; leather and meat (Pope S. 1998 Animal Liberation S A , E m u farming 77 The source o f farm emus in North America is zoo stock, mainly from a 1901 shipment directly from Australia (Sager, per. com.) since when the emu became Australia's national bird in 1950, the government banned its export. The American Emu Association ( A E A ) has 1,700-member o f breeders, producers and marketers o f emu meat and oi l . Founded in 1989 by producers desiring national representation for this new industry, A E A ' s mission is to establish value of emu products through research, market development, and industry positioning in the emu industry which are currently raised in at least 43 states in the U . S . (American Emu Association 1999, Wi th state and federal inspection now in force, plus interstate and international shipping, and with 40 USDA-approved plants around the country processing the meat, the U S emus farmed are estimated at 1.5 mil l ion birds (Weeks, Emu farming. Sandlapper. 1988). Today, the emu industry is represented in Korea, Vietnam, China, New Zealand, France and Canada. In Canada, the Canadian Emu Association ( C E A ) was established in 1993 and included 40 Members with 400 birds. In 1995, 800 birds were farmed across Canada. In British Columbia the start of farming operations was in 1991 and in 1992 there were 36 birds farmed across B C (with 28 in the same farm) when the price for a bird was $500. In 1995, prices surged to $20,000 per mature bird but soon after, due to marketing problems and a non-realistic return prospects, many farmers left the industry. Currently the emu population farmed in Canada is estimated at about 5000 birds (500 in B C in 30 farms), (Billesberger, 78 pers. Comm.). Today, A pair o f 6-month-olds may cost $400-600, 1-year-olds $1,000-2,000, and older pairs with records may cost several thousand dollars. 3.1.3 Partridge Tinamou: a Newly Developed Farm Bird The tinamou is a newly developed farm birds and in North America the only population outside zoos is located in the University of British Columbia San Rafael Research Aviary. The partridge tinamou feathers are gray, brown or cinnamon and their plumage has soft bars and spots. Male and female tinamous are similar in coloring and external shape, however the males are slightly heavier. In captivity, the bird reaches maturity in 16 weeks and a hen may lay two eggs a week from A p r i l to September. With a population of 2000 birds, research has been conducted on captive rearing, breeding and feeding (Kermode 1997). The British Columbia tinamou flock was established in 1989 with a flock o f 30 partridge tinamou, however, today's population originated from only 10 males and 6 females in 1992. The partridge tinamou is currently not available for commercial consumption. However, Tinamou International Investments Inc., a company dedicated for the commercial production of tinamous, has signed a joint venture agreement with U B C to further develop the birds for commercial production (Cheng, per. com.). Together with contributions from Demonstration o f Agricultural Technology and Economics Projects (D.A.T.E. ) funding from the Ministry o f Agriculture, Fisheries and Food, support from the San Rafael Foundation, 79 and recent Industrial Research Assistance Program (I.R.A.P.) the U B C flock is maintained for research as a newly farmed bird. 3.2 O B J E C T I V E S O F T H E STUDY In this study microsatellite primers designed for the ostrich were.used to amplify emu and tinamou D N A through P C R . The intention was to ascertain whether these specific microsatellite regions can be used across species o f paleognathous farm birds. A n y markers obtained through cross amplification can be used for assessing the genetic makeup o f an individual or population in these farmed species, and for identification purposes, introgression programs and predicting heterosis as mentioned previously. Further, microsatellites are lower in frequency in avian genome; approximately one microsatellite every 16-20 kb compared with one every 6 kb in human (Primmer et al, 1997). Hence, this deficiency can pose an obstacle for genetic mapping in birds (Primmer et al., 1997). For this reason, the appropriation of many microsatellites (in addition to other markers) in avian species is of great importance. Concurrently, cross amplification of k i w i (Apteryx australis) (not a farmed species) D N A using ostrich microsatellite primers was examined and the results reported in Appendix A . 80 3.3 E X P E R I M E N T A L M E T H O D S 3.3.1 Experimental Birds and DNA Samples Blood samples from 20 partridge tinamous (Nothroprocta perdicaria sanbonii) were obtained from the University o f British Columbia San Rafael Research Aviary. The U B C tinamou flock was established in 1989 consisting of 30 birds four or five generations removed from the wi ld . However from this base population only 6 females and 10 males were used for the current 2000 birds population. One m l of blood was obtained via venepuncture of the wing vein from each o f twenty partridge tinamous. Handling of the blood samples and D N A extraction protocol was similar to that previously described for the ostrich samples. D N A samples of emu (N=3) were obtained from The Centre for Biodiversity and Conservation Biology at the Royal Ontario Museum. O f the three emu samples one was obtained from a bird from Western Australia, one was from a bird in the Toronto Metro Zoo and one from a farm near Guelph (Haddrath, per. com.). 3.3.2 P C R Cross Species Amplification P C R was used to amplify emu and tinamou genomic D N A . The same 10 ostrich specific microsatellite primer sets (see section 2.3.4) were tested at a variety o f annealing 81 temperatures to examine i f the appropriate microsatellite sequences and their unique flanking sequences are conserved across these three species. Initially, a low annealing temperature o f 48°C was chosen and i f a putative microsatellite product was visible temperatures were increased (or decreased) until a clear specific band was attained. When no product was seen after amplification at various temperatures the primers were assumed to have no specific binding site. The primer sequences, their optimal annealing temperature and the size o f the product are listed in Table 3.2 for the tinamou and Table 3.3 for the emu. The reagents in the reaction were as described in Experimental Methods o f chapter 1. P C R products were visualized on 1-2% agarose gels with ethidium bromide. I f a positive product was found the sample was run on 7% non-denaturing polyacrylamide gels at 43 volts for 15 hours in order to determine whether they are putative microsatellite markers. Polycryamide gels were stained with ethidium bromide. Cross amplification products were sent for sequencing o f the putative microsatellite at the Genetic Data Centre, Faculty of Forestry, University of British Columbia in order to confirm the existence of an homologous microsatellite region in the other species. I f a band was visible near the predicted microsatellite size range (-100-300 bp) the band was isolated from the gel and purified directly from the reaction tube using Wizard ® P C R preps D N A Purification System (Promega). Sequencing was performed through tailed primer dideoxy termination on a Licor (modification Marshall and Ritland C . per. com.) automatic sequencer. 82 i n < o o S a a o s m O DC a s a #o M u a « C« '3 CD • Cfl O _ a a .a e a o a • o + C3 V s H Rt u s S C3 U s "3 OJ o. a o O a 03 «!§ 2 g « © "J* 5 oo fa Z u S n, B u PM CS — ! 3 H '•8 O o o H O O O H 00 N O C N o o H  H O N O O H 00 O 00 00 oo I—I t — ( >—i h J h J h - l C N O £ + * 83 Table 3.3 P C R amplification optimization in cross-species amplification using ostrich primers on emu DNA. Marker Results of P C R D N A amplification in various temperatures (C°) annealing name 48 examined 53 58 O S M 1 * + LIST001 -O S M 4 * + LIST005 - - + O S M 5 + LIST006 -LIST002 + LIST009 -V I A S - O S 2 * * -LIST011 -+ Solid bands * Faint bands No amplification or non specific amplification (smear) 84 3.4 R E S U L T S Out o f ten markers examined 6 amplified D N A stretches in the emu and 4 in the tinamou. (Table 3.4). Locus O S M 1 was originally identified to contain a simple ( C A ) n repeat in the ostrich. This locus was identified both in the tinamou and emu in the same size range of the original microsatellite (120 bp in the tinamou and emu and HObp in the ostrich). However in the emu and tinamou, although dinucleotide repeats were found they were not ( C A ) n . In the emu a compound microsatellite was found with mostly (TG) n repeats with varying repeat number (between 2 and 5). Towards the 3' end also small ( G A ) n (n = 2) sequence was found but also interrupted (Figure 2.3). In the tinamou a very close similarity to the emu was also found with allele at the same size and also (TG) n (n = 3) and ( G A ) n (n = 5) repeats towards the 3' end. Alignment of the emu and tinamou sequences shows that 50% o f the emu sequence is conserved in the tinamou but is not seen in the ostrich. In the ostrich, locus O S M 4 was characterized as containing simple (TA)i6 repeat with mean allele size o f 134 bp. However in the emu there seems to be no conservancy of this dinuleotide repeat. The product size in the Emu is 154 bp (see Figure 2.1) and shows long mono- repeats of T(20), A(17),T(12) and C(12). In the Tinamou two putative bands were found with corresponding sizes of 144 pb and 200 bp. Only the 144 bp size amplification product was sequenced and no microsatellite was found, even though a large 85 segments of sequencing was not successful the bases sequence o f the area before the ostrich's microsatellite repeats shows conservation in both the emu (79% of the ostrich sequence preserved) and the tinamou (74% preserved). Ostrich locus LIST005 was identified to contain a compound microsatellite dinucleotide T G repeats with mean allele size o f 197 bp. LIST005 primers cross amplified emu D N A to give a 205 bp size product. However, no microsatellite repeats region was found after sequencing the product. Locus LIST002 in the ostrich was characterized as containing compound ( A C ) n repeats with mean allele size o f 123 bp. LIST002 cross amplified with emu D N A to give an amplification product of product size of 134 bp. The sequencing of the amplification product shows two ( C A ) n repeats regions of n = 3 and n = 5 respectively in close proximity to one another. This locus showed high conservancy between the ostrich and the emu (see Figure 2.3) with 68% conservation of the ostrich sequence in the emu. Cross amplification with Tinamou D N A gave a 150 bp mean size product. Among the cross amplification reactions, this is the only locus to show polymorphism (Figure 2.2). However, since sequencing o f this amplification product was not successful, there is no verification for the existence o f a microsatellite in this locus in the tinamou. In the ostrich, LIST011 was characterized as a simple (GT)24 microsatellite repeat with mean allele size o f 135 bp. N o successful cross amplification was obtained with the 86 emu samples. With the tinamou samples a successful amplification was obtained with product size o f 160 bp. Sequencing of the cross amplification product revealed repetitive G T repeats through a large segment o f the D N A sequenced, however it was interrupted repeatedly. In the ostrich, O S M 5 was characterized as a simple (CA)2o microsatellite repeat with mean allele size o f 232 bp. Cross amplification product was found in the emu with the size of 140 bp. However, no base sequence is available. In the tinamou a product was not found. For loci V I A S - O S 2 , LIST006 compound, LIST009 and LIST001 no cross amplification was found in either emu or tinamou samples across all the temperatures tested. 87 Table 3.4 Amplification results in the emu and tinamou using ostrich specific microsatellite markers. "+" Symbolizes amplification and "-" no amplification Emu Tinamou O S M 1 + + LIST001 - -O S M 4 + + LIST005 + -O S M 5 + -LIST006 - -LIST002 + + LIST009 - -V I A S - O S 2 - -LIST011 - + 88 Figure 3.1 Photograph of ethidium bromide stained nondenaturing polyacrylamide gel with emu (left) and kiwi (right) cross amplification products at locus O S M 4 and 1 Mbp DNA marker in the flanking lanes. 201 bp D N A marker 134 bp D N A marker Figure 3.2 Photograph of ethidium bromide stained nondenaturing polyacrylamide gel with tinamou cross amplification products at locus LIST002 and 100 bp DNA marker in the first left lane. 200 bp D N A marker 100 bp D N A marker >-a a <u VI <u u a <u u v> 0) 03 • a 9 a .2° 1 - 1 o u S en •a ° .9 TJ "S S3 "2 3 5 1 = 3 « O * C * * a >-a *~ •a a a ox 1 - 1 a >» — « u ^ B aj o a a. s 9 w VI « "B u w jS ft OH | _ I o v « 2 © a « * a 9 OO c5 <u u S OX) V £ 5 •a u S V) o u o o H 00 3 O w o a • o H 3 2 u 9 u •< u o S3 a 3 u u u O O H H 3 3 o 3 3 3 n H n fl .a f .a .a H O H H o o •a o o m o u <u 3 3 T 3 T 3 OX) « a. «u a •a V =3 #g a o tj rn s OX) u g o o 0 0 <v H U H _3 + J O T3 <; z a U 0 « O H nrii TGG CA v TGG O <u u _3 H a O _ u H . O u O •a 0 H < O a alig TG GT alig 0 H cu 0 <: S3 H H CA U 0 rke O h 0 0 H H H O ce. b H ce. 0 O quen <: O quen H a quen 0 0 <: u < < u < u o H o u u u u u <c o u < 5 _J ^ rt _ Z •< Q U H H U H n O o O h , H <; t_i •5 u P < H b 9 _ H < h <c U t - 1 H O U H < o z oH 2 < < o u H <; <; u H u <C < _ 2 U H H ^ ^ » \ « / c|S 3 2 5 <; H . u o a < b o o a b "1 Ifl V I 3 • M H O 91 3.5 DISCUSSION This study aimed to investigate the existence of orthologous microsatellite markers in the emu and tinamou using ostrich specific microsatellites primers. The reason was to inspect the possibility of using these markers for future research without the need of developing species specific markers through more expensive methods. Since cross amplification is more likely to occur in closely related species, two other paleognathous farm birds were chosen, i.e., the emu and the tinamou. Analysis o f mutations in microsatellite evolution by sequencing between species can reveal how repeat structure evolved over long time scale. Most often allele length changes are due to size alterations in the repeat region (Estoup et al. 1995; Garza and Freimer 1996; Angers and Bernatchez 1997). Since the repeat sequence is the most affected region it can lead to interruptions and alterations in the repeats motif which usually leads to reduced polymorphism (Primmer and Ellegren, 1998). Hence, the application of cross-species amplification o f microsatellite D N A in order to acquire markers in a species is potentially inferior to developing species specific markers. Furthermore, mutations are also frequently found in the primers sequences flanking microsatellites which consequently leads to difficulties in optimization of P C R amplification and the creation of null alleles (FitzSimmons et al., 1995, Angers and Bernatchez, 1997). 92 However, since patterns of microsatellite evolution may differ substantially between loci and some markers are remarkably stable (Primmer and Ellegren, 1998), the utilization of cross-species amplification o f microsatellite can aid in obtaining new markers for a species especially in a monophyletic group. Out of ten markers examined 6 amplified D N A stretches in the emu and 4 in the tinamou. In each species 3 successful sequencing reactions revealed the conservancy o f only one microsatellite, locus LIST002 in the emu. Even though, base sequence is not available for the tinamou in this locus, it showed polymorphism in this species. This is the only locus to show polymorphism in all the sequences obtained. The time of separation between the Tinamidae and the Ratitae phylogenies is estimated at 9 0 M Y A (however with large confidence intervals ranging tens of millions of years). In addition to the long time frame, the time of separation within the ratites followed rapidly after and a star phylogeny was formed (Lee at al., 1997) Interestingly, the genome o f the ratites seems to be very conserved within the group (de Boer, 1980). It is most probable that homologues sequences have been altered between those two groups. Even within the Ratitae the time o f separation between the ostrich and the emu is estimated around 70 M Y A . Hence, it leaves room for additional mutational events that would change sequences in uncoding D N A 93 Due to the long time since divergence, it should be taken into consideration that loci found in this research might not be the homologue sequences even though they might be similar. However, since the high degree o f conservation, it seems unlikely. It is also possible that null alleles of homologue sequences could not been amplified and thus although other microsatellites sequences exist their primers binding sites changed. Nevertheless, some microsatellite can be conserved over the period of divergence o f paleognathous and neognathous (Primmer and Ellegren, 1998), hence, it is anticipated to find conservancy within the paleognathous and ratite phylogeny. Among the aims o f this research was to find whether these cross species markers would be appropriate for further use as microsatellite markers. Even though cross amplification occurred in five and four times out o f 10 markers tersted in the emu and tinamou respectively, it is not known whether these markers are polymorphic (except LIST002). There were only three emu D N A samples and the U B C tinamou population has gone through a genetic bottleneck that probably reduced its genetic variability. Only one marker, LIST002, showed polymorphism in the tinamou and it seems to be favorable for future research Furthermore, the high conservancy of this locus between the ostrich and emu is suggesting that it may wel l indeed be a microsatellite. Nevertheless, the rate o f success of the cross-species amplification was high and in several cases repeat sequences were found ( O S M 1 with (TG) n repeats in the emu and tinamou, LIST002 with ( C A ) n in the emu, LIST001 with (GT) n repeats in the tinamou). These markers should be considered favorably for utilization as microsatellite markers i f they are found polymorphic. However, creation of 94 a species-specific library could be more effective for having a higher number o f microsatellite markers and since they would be species specific they would contain higher polymorphism. 4 G E N E R A L DISCUSSION The increasing commercial interest in domesticated paleognathous birds and especially in the ostrich is demanding a unique standpoint as to the means of genetic manipulation and improvement that should take place (Gavora, 1994). Microsatellites have been the markers of choice in chickens as tools for genetic mapping (Cheng and Crittenden, 1994; Cheng et al, 1995) and also for determination o f genetic variation within and between chicken lines (Crooijmans et al, 1996; Vanhala et al, 1998). The result o f this thesis research, which was aimed to investigate how genetically diverse the B C ' s ostrich breeding flocks are with the use o f D N A microsatellite markers, suggests that considerable genetic variation is present and inbreeding is not prevalent in the breeding flocks. However, one o f the basic needs in a breeding program is a system to keep accurate records o f relationships and pedigrees (Gavora, 1994). Records o f performance and reliable identification are now universally accepted as a necessary foundation for a progress in genetic manipulation. The ostrich industry bookkeeping has been suffering from erroneous records that hinder the implementation o f adequate breeding programs. Microsatellite markers as a single locus fingerprinting method provided in this study an identification label that farmers can now use in the creation of a 95 herd book, that even though open, (i.e. geneological relationships of birds in the records is not known), can still aid in the planing o f which birds to use for mating since genetic relationships are given. The farmers can now access the records o f this study in order to know the relationships of all prospective pairs. M y recommendation to farmers is to have in the record for each bird these relationships. Furthermore, since the pedigree and relationship information without performance records is essentially useless (van Vleck, 1987), farmers should also measure production traits in their birds (such as body weight, longevity, fertility, etc.). This study demonstrated how body weight can be correlated with heterozygosity. In the future, better records o f the birds together with their genetic profiles can further pursue this initiative in order to genetically correlate and improve economically important traits. The ostrich products are leather, meat, eggs, o i l and feathers. Hence, measuring these production traits simultaneously and repeatedly is favorable so selection for overall economic value would be possible. Microsatellite markers associated with overall economic value could be used, than, in markers assisted selection. The generation interval of ostriches is about two to three years. A n ostrich is reaching its market value at the ages of 10 months to one year old. Hence, it would take three to four years to evaluate the performance o f a breeding bird. Correlation o f a microsatellite profile with performance can shorten the time o f evaluation and increase 96 the rate that selection can be performed since bird's future performance could be predicted already from juvenile parameters. Early evaluation o f breeding birds could also eliminate the need for maintaining a large number of birds for evaluation. Lastly, the commercial initiatives now taken in other paleognathous poultry, the tinamou and more importantly the emu deem it essential to apply knowledge from the ostrich studies (including genetic principals and tools such as microsatellite D N A data). The world-wide chicken breeders industry is controlled by about a dozen large companies (Gavora, 1994) whereas the ratite breeding industry is spread over many small-scale operators. In my view, the creation o f active regional associations is the key for scientific progress in this industry. Together those small scale producers would be able to support academic and scientific research for the benefit o f the whole industry. Hand-in-hand, this fledgling industry by learning from paleognathous specific research should eventually lead itself to survival and success. 97 R E F E R E N C E S CITED Abernethy K (1994). The establishment o f a hybrid zone between red and sika deer (Genus Cervus). M o l . Ecol . 3: 551-62. Abplanalp H . (1990) Inbreeding. In: R . D . Crawford. Poultry Breeding and Genetics. Elsvier Amsterdam-Oxford-New York-Tokyo.Pg. 966. Abplanalp, H . (1974). Inbreeding as a tool for poultry improvement. Proc. 3 r d Wor ld Cong. Genet. A p p l . Livestock Prod. (Lincoln) 10:257-272. Abplanalp H . and Woodard A . E . (1967). Inbreeding effects under continued sib-mating in turkeys. Poult. Sci . 46: 1225-1226. Al la rd M W , Ellsworth D . L . and Honeycutt R . L . (1991). The production o f single-stranded D N A suitable for sequencing using the polymerase chain reaction. Biotechniques 10:24-26. American Ostrich Association (1998). Ostrich Primer brochure. Angers B . and Bernatchez L . (1997). Complex evolution o f a salmonid microsatellite locus and its consequences in inferring allelic divergence from size information. M o l . B i o l . Evo l . 14: 230-8. Ashley M . V . and D o w BD.(1994). The use of microsatellite analysis in population biology, background, methods and potential applications In: B . Schierwater, B . Streit, G.P. Wagner and DeSalle R. Molecular Ecology and Evolution: Approaches and Applications. Birhauser Verlag, Basel, Switzerland. Pg. 185-201. Bachman K . (1972). Genome size in mammals. Chromosoma 37: 85-93. Beamonte D . , Guerra A . , Ruiz B . and Alemany J. (1995). Microsatellite D N A polymorphism in analysis in a case of an illegal cattle purchase. J Forensic Sc. 40: 692-4. Bierne N . , Launcy S., Naciri-Graven Y . and Bonhomme F. (1998). Early effect of inbreeding as revealed by microsatellite analyses on Ostrea edulis larvae. Genetics 148: 1893-1906. Bowcock A . M . , Ruiz-Linares A . , Tomfohrde J., M i n c h E . , K i d d J.R., and Cavalli-Sforza L . L . (1994). High resolution of human evolution with polymorphic microsatellites. Nature 368: 455-457. 98 Brown L . H . , Urban E . K . and Newman K . (1982). The Birds of Africa. V o l . 1 . Academic Press, London. Pg.1-2. Bradford M . W and Wayne R . K . (1993) Microsatellite and their application to population genetics studies. Curr. Opin.Genet. Dev. 3: 939-943. Cahaner A . , Ablanalp H . and Shultz F.T. (1980). Effects of inbreeding on production traits in turkeys. Poult. Sci . 59:1353-1362. Chakaborty R and Jin L . (1993). Detection of nonrandom association of alleles from the distribution o f the number of heterozygous loci in a sample. Genetics 108:719-731. Charlsworth B . , Sniegowski P. and Stephan W . (1994). The evolutionary dynamics o f repetitive D N A in eukaryotes, Nature 37:215-220. Cheng H . H . and Crittenden L . B . (1994). Microsatellite markers for genetic mapping in the chicken. Poult. Sci . 73:539-546. Cheng H . H . , Lev in I., Vallejo R . L . , Khatib H . , Dodgson J.B. , Crittenden L . B . , H i l l e l J. (1995). Development o f a genetic map with markers o f high utility. Poult. Sci . 74:1855-1874. Coote T., and Bradford M . W . (1996). Human microsatellites applicable for analysis o f genetic variation in apes and Old World monkeys. J Hered 87:406-410. Coulson T . N . , Pemberton J . M . , A lbon S.D., Beaumont, Marshall T C , Slate J, Guiness F E , and Clutton-Brock T . H . (1988). Microsatellites reveal heterosis in red deer. Proc R Soc Lond B B i o l Sci 265: 489-495. Cracraft J. (1974). Phylogeny and evolution o f the ratite birds. Ibis 116:494-521. Crooijmans R.P. , Goren A . F . , V a n Kampen A . J . , V a n der Beek S., V a n der Poel J.J. and Groenen M . A . (1996). Microsatellite polymorphism in commercial broiler and layer lines estimated using pooled blood samples. Poult. Sci . 75:904-9. de Boer L . E . M . (1980). Do the chromosomes of the k i w i provide evidence for a monophyletic origin of the ratites? Nature 287:84-85. Deeming D . C . and Angel C .R. (1996) Introduction to the ratites and farming operations around the world. A n international conference held at Dalton- El l i s Ha l l , University of Manchester, England 27 t h -29 t h March 1996 . 99 Deka R., DeCroo S., Jin L , McGarvey S.T., Rothhammer F., Ferrel R . E . and Chakraborty R. (1994). Population genetic characteristics of The D1S80 Locus in seven human populations. Hum. Genet. 94:252-258. Drenowatz C. , Sales J.D., Sarasqueta D . V . , and Weilbrenner A . (1995). History and geography, the ratite encyclopedia. Ratite Records, San Antonio, Texas. Pg. 3-29. Edwards A . , Hammond H . A . , Jin L . , Caskey C.T. and Chakraborty R. (1992). Genetic variation at five trimeric and tetrameric tandem repeat loci in four human population groups. Genomics 12:241-253. Estoup A . , Garnery L . , Solignac M . , and Cornuet J . M . (1995). Microsatellite variation in honeybee populations: hierachical genetic structure and test of I A M and S M M . Genetics 140:679-695. Evans P . G . H . (1987). Electrophoretic variability of gene products. In: Cooke F and Buckley P A . A v i a n Genetics. Academic Press Inc. (London). Pg. 105-163. Felsenstein J. (1981). Evolutionary trees From D N A Sequences: a maximum likelihood approach. J. M o l . Evo l . 17:368-376. Fields R . L . and Scribner K . T . (1997). Isolation and characterization o f novel waterfowl microsatellite loci: cross-species comparisons and research applications. M o l . Ecol . 6:199-202. Fitch W . M . (1971). Toward defining the course of evolution, minimum change from a specific tree topology. Syst. Zool . 20:406-415. Fitch D . H . A , Mainone C , Goddman M . and Slighton J .L. (1990). Molecular history of gene conservation in the primate fetal g-Golbin genes. J. B i o l . Chem. 265:781-793. FitzSimmons N . N . , Mori tz C . and Moree S.S. (1995). Conservation and dynamics o f microsatellite loci over 300 millions years of marine turtle evolution. M o l . B o l . Evo l . 12:432-440. Flock D . K . , A m e l i H . and Glodek P. (1991). Inbreeding and heterosis effects on quantitative traits in a White leghorn population under long-term reciprocal recurrent selection. Br . Poult. Sci . 32:451-62. Forbes S.H. , Hogg J.T., Buchanan F . C . Crawford A . M . and Allendorf F . W . (1995). Microsatellite evolution in congeneric mammals: domestic and bighorn sheep. M o l . B i o l . Evo l . 12:1106-1113. Frankel O . H . and Soule M . E . (1981). Conservation and Evolution. Cambridge University Press, N Y . Pg. 87-90. 100 Freimer N . B . and Slatkin M . (1996). Microsatellite evolution and mutational processes. Ciba Foundation Symposium. 197:51-67. Freitag S. and Robinson T.J.. (1993). Phylogeographic patterns in mitochondrial D N A of the ostrich {Struthio camelus) The A u k 110:614-622. Garza J.C., Slatkin M . and Freimer N . B . (1995) Microsatellite allele frequencies in human and chimpanzees with implications for constraints on allele size. M o l . B i o l . Evo l . 12:594-603. Garza J.C. and Freimer N . . B . (1996). Homoplasy for size at microsatellite loci in humans and chimpanzees. Genome Res. 6:211-217. Gavora J.S. (1994). Learning from poultry. Basic principles o f genetic improvement o f poultry as it may apply to ostrich breeding. Canadian Ostrich Apr /May 1994 52-55. Gillet E . M . (1991). Genetic analysis o f nuclear D N A restriction fragments patterns. Genome 34:693-703. Gillespie J .H . (1985). The interaction of genetic drift and mutation with selection in a fluctuating environment. Theor. Popul. B i o l . 27:222-237. Glazner E . W . , B l o w W . L . , Bostian C . H . , and Dearstyne R.S . (1951). Effects o f inbreeding on broiler weight and feathering in fowl. Poult. Sci . 30:108-112. Goldstein D . B . and Pollock D . D . (1997) A review o f mutation processes and methods of phylogenetic inference. J. Hered. 5:335-342. Goodnight, C.J . (1995). Epistasis and the increase in additive genetic variance: implications for phase 1 o f wright's shifting balance process. Evo l . 49:502-511. Greenwood P.J. (1987). Inbreeding, philopatry and optimal outbreeding in birds. In avian Genetics. Ed . by F A Cooke and P A Buckley. Academic Press Inc.(London).Pg.207-222. Grizmek B . (1995). The Economic uses o f ostrich feathers. In: Animal life encyclopedia, B . Grizmeck. V a n Nostrad R. Company. New York, Cincenati, Toronto London, Melbourne Pg. 96-100. Hamilton A . C . (1982). Environmental history of East Africa: a study of the quaternary. Academic Press, London. Pg. 19, 36. 101 Harlid A . , Janke A . and Arnason U . (1997). The m t D N A sequence o f The ostrich and the divergence between paleognathous and neognathous birds. M o l . B i o l . Evo l . 14:754-761. Hartl D . L . (1980) Principles of Population Genetics, Second Edition. Sinauer Associates, Inc. Publishers. Sunderland, Massachusetts Pg. 117-168. Hartl D . L . and Clark A G . (1989). Principles of Population Genetics, Second Edition. Sinauer Associates, Inc. Publishers. Sunderland, Massachusetts Pg. 301-305. Hartl D . L . and Clark A G . (1997). Principles of Population genetics, Third Edition. Sinauer Associates, Inc. Publishers. Sunderland, Massachusetts Pg. 83-85. Hemmer H . (1990). Domestication, The Decline O F Environmental Appreciation. Cambridge University Press. Pg. 187-191. H i l l W . G . , (1986). Population size and design o f breeding programmes, In: Proc. 3 r d Wor ld Congrr. Genet. A p l l . Livest. Prod. Univ . of Nebraska, Lincoln, Nebraska X I L 2 4 5 -256. H i l l W . G . and Robertson A . (1968). The effects of inbreeding at loci with heterozygote advantage. Genetics 60:615-628. H i l l e l J., Dunnington E A . and Siegel P .B . (1992). D N A markers in poultry and genetic analyses. Poult. Sci . 4:169-186. Horn G.T. , Richards B . and Klinger K . W . (1989). Amplification of a highly polymorphic V N T R segment by the polymerase chain reaction. Nuc l . Acids Res 11 17:52140. Houde P .W. (1988). Paleognathous birds from the early tertiary o f the Northern Hemisphere. Cambridge, Mass. : Nuttall Ornithological Club. Pg.1-3. Houlden B . A . , England P.R., Taylor A . C . , Greville W . D . and Sherwin W . B . (1996). L o w genetic variability of the koala (Phascolarctos cinereus) in South Eastern Australia following a severe population bottleneck. M o l . Ecol . 5:269-81. Hughes C.R. and Queller D . C . (1993). Detection o f highly polymorphic microsatellite loci in a species with little allozyme polymorphism. M o l . Eco l . 2:131-137. Hughes A . L . and Hughes M . K . (1995). Small genomes for better flyers. Nature 377:391. Ibe S.N. , Rutledge J.J. and McGibbon W . H . (1983). Inbreeding effects on fertility and hatchability associated with the formation of sublines. Poult Sci 62:1543-1547. 102 Jackson H.J . (1938). The Birds of Kenya Colony and Uganda Protectorate, V o l . I, Gurney and Jackson, London. Jennings M . C . (1986). The distribution o f the extinct Arabian Ostrich Struthio camelus syriacus Rotcschild, 1919. Fauna of Saudi Arabia Vol .8 1986. Kingdom o f Saudi Arabia Meteorology and Environmental Protection Administration. Pg.447-461. Jin L . , Macaubas C , Hallmayer J., Kimura A . and Mignot E . (1996). Mutation rate varies among alleles at a microsatellite locus: phylogenetic evidence. Proc. Natl . Acad. U S A 93:15285-15288. Jones C.S . Lessells C M . and Kerbs J.R. (1991). Helpers-at-the-nest in European bee-eaters (Merops apiaster): a genetic analysis In D N A Fingerprinting: Approaches and Applications. Ed . by Burke T, D o l f G , Jeffreys A J and Wol f f R. Birkhauser Verlag Basel Switzerland. Pg. 169-192. Kavkinen J. and Varvio S. (1992). Artiodactyl retroposons: Association with microsatellites and use in SiNEmorph detection by P C R . Nuc l . Acids Res. 20:2955-2958. Kayser M . , Ritter H . , Bercovitch F., Mrug M . , Roewer L . and Nurnberg P.(1996).Identification of highly polymorphic microsatellites in the rhesus Macaque Macaca mulatto by cross-species amplification. M o l . Ecol . 5:157-9. Kermode D . (1993). Investment analysis model, ostrich production. Bachelor of Science thesis, Agricultural Economics, University of British Columbia. Pg. 1-2.. Kermode D . (1997). The production o f non-traditional poultry in Brit ish Columbia and the introduction o f a new poultry species: partridge tinamou. Master o f Science thesis, University of British Columbia. Pg. 39-41. Kimwele C . N . , Graves J .A. , Burke T., and Hanotte O. (1998). Development o f microsatellite markers for parentage typing of chicks in the ostrich Struthio camelus. M o l . Ecol . 7:249-251. Koreth J., O'leary J.J. and Mcgee J.O. (1996). Microsatellites and P C R genomic analysis. J. Pathol. 178:239 -248. Kumari P. and Kemp S.J. (1998). Polymorphic microsatellite markers in the ostrich. M o l . Ecol . 7:133-140. Lacy R . C . , Petric A . and Warneke M . (1993). Inbreeding and outbreeding in captive populations of wi ld animal species. In Thornhill N . W . ed. The Natural Fistory of Inbreeding and Outbreeding. Theoretical and Empirical Perspectives. Chicago: University o f Chicago Press. Pg.352-373. 103 Leberg P . L . (1992). Effects o f population bottlenecks on genetic diversity as measured by allozyme electrophoresis. Evolution 46:477-494. Lee K . , Feinstein J. and Cracraft J. (1997). The phylogeny of ratite birds: resolving conflicts between molecular and morphological data sets. In: D .P . Minde l l , ed. Av ian Molecular Evolution and Systematics. Academic Press, San Diego. Pg. 173-208. Lehmann T., Hawley W . A . and Collins F . H . (1996). A n evaluation o f evolutionary constraints on microsatellite loci using null alleles. Genetics 144:1155-63. L i W . H . (1997) Molecular Evolution. Sinauer Associates, Inc. Publishers. Sunderland, Massachusetts. 105-106. Linnaeus C. (1758). Systema Naturae per Regna Tria Naturae, Secundum Classes, Ordines, Genera, Species, Cum Characteribus, Differentiis, Synonymis, Locis. Holmiae (Stockhlom) Impensis Direct Laurentii Salvii V o l : 1155. Lubjuhn T., Schwaiger F . W . and Epplen J.T. (1994) The analysis of simple repeat loci as applied in evolutionary and behavioral science. In molecular ecology and evolution: approaches and applications ed. by B . Schierwater, B . Streit, G.P. Wagner & R. DeSalle. Birkhauser Verlag Basel/ Switzerland. Pg. 33-34. Maclean G . L . (1993). Robert's birds o f Southern Africa, John Voelcker B i r d Book Fund, Cape Town. Pg. 1-3. Maeda Y . and Hashiguchi T. (1981). Trends in heterozygosity in the process o f producing inbred strains of Japanese quail. A n i m Blood Groups. Biochem Genetics 12:277-85. Ma' the ' J., Eisenmann C. and Seitz A . (1993). Paternity testing o f endangered species of birds by D N A fingerprinting with non-radioactive Labelled oligonucleotide probes. In: D N A Fingerprinting: State of The Science. Pena SDJ , Chakarborty R , Epplen JT and Jeffreys A J . Birkhauser Verlag Basel Switzerland. Pg. 387-393. Maueler W. , Frank G . , Siedlaczck I., Epplen J.T. and Melmer G . (1992). P C R amplification products are o f limited use for the study of DNA/protein interaction. Electrophoresis 13:641-643. McDonald D . B . and Potts W . K . (1997). D N A microsatellites as genetic markers at several scales. In: Minde l l D P . In: Avian Molecular Evolution and Systematics. San Diego: Academic Press. Pg. 30-32. McMurray C.T. (1995). Mechanisms of D N A Expansion. Chromosoma (Berl). 104:2-13. 104 McRae S.B and Amos W . (1999). Characterization o f hypervariable microsatellites in cooperatively breeding white-browed sparrow weaver Plocepasser mahali. M o l . Ecol . 8:903-905. Meffe G . K . and Carroll R. (1997). Principles o f Conservation Biology. 2nd edition. Sinauer Associates, I N C . Sunderland, Massachusetts. Menotti-Raymond M . A . and Obrien S.J. (1995). Evolutionary conservation o f ten microsatellite loci in four species of Felidae. J. Hered. 86:319-22. M i n a N . S . , Sheldon B . L . , Y o o B . H . and Frankham R. (1991). Heterozygosity at protein loci in inbred and outbred lines of chickens. Poult Sci 70:1864-72. M i y a k i C . Y . , Hanotte O., Wajntal A . and Burke T. (1993). Characterization and application o f multilocus D N A fingerprints in Brazilian endangered macaws. In: D N A Fingerprinting: State of The Science. Pena SDJ , Chakarborty R, Epplen JT and Jeffreys A J . Birkhauser Verlag Basel Switzerland. Pg. 395-401. Moore S.S., Sargeant L . L . , K i n g T.J., Mattick J.S., Georges M . and Hetzel D J . (1991). The conservation of dinucleotide microsatellites among mammalian genomes allows the use o f heterologous P C R primer pairs in closely related species. Genomics 10:654-60. Nadir E . , Margalit H . , Gal l i ly T. and Ben-Sasson S.A. (1996). Microsatellite spreading in human genome: evolutionary mechanisms and structural implications. Proc. Natl . Acad. Sci . U S A 93:6476-6475. Narayanan S. (1991). Applications of restriction fragment length polymorphism. A n n C l i n Lab Sci 1991 21:291-296. N e i M . (1975). Molecular population genetics and evolution. North-Holland, Amsterdam. Pg. 197-202. N e i M . (1976). Mathematical models of speciation and genetic distance. In Kar l in S and Nevo. Population Genetics and Ecology. Academic Press, New-York . Pg. 723-766. N e i M . (1988). Relative roles o f mutation and selection in the maintenance o f genetic variability. Philos Trans R Soc Lond B B i o l Sci 319:615-629. Neilan B . A . , Leigh D . A . , Rapley E . and McDonald B . L . (1994). Microsatellite genome screening: rapid non-denaturing, non-isotopic dinucleotide repeat analysis. Biotechniques 17:708, 710, 712. 105 Nordskog A . W . and Cheng S. (1988). Inbreeding effects on fertility and hatchability associated with the formation o f sublines. Poult. Sci . 67:859-64. Neumann K . and Wetton J .H. (1996) Highly polymorphic microsatellites in the house sparrow Passer domesticus. M o l . Ecol . 5:307-309. Ohta T. and Kimura K . (1973). The model of mutation appropriate to estimate the number of electrophoretically detectable alleles in a genetic population. Genet. Res. 22:201-204. Olmo E . , Capriglione T. and Odiema G . (1989). Genome size evolution in vertebrates: trends.and constraints. Comp. Biochem Physiol. 92:447-453. Orgel L . E . and Crick F.H.C.(1980). Selfish D N A : The ultimate parasite. Nature 284:604-607. Orti G . , Pearse D . E . and Avise A . C . (1997). Phylogenetic assessment of length variation at a microsatellite locus. Proc Natl Acad Sci U S A 94:20 10745-10749. Petitte J .N. , Petitte J . M . and Scheideler S.E. (1996) Determination o f genetic diversity in commercial ratite stocks using multilocus D N A fingerprinting. A n international conference held at Dalton- El l i s Ha l l , University of Manchester, England 27 t h -29 t h March 1996. Pg. 69-77. Pepin L . , Amigues Y . , Lepingle A . , Berthier J .L. , Bensaid A . and Vaiman D . (1995). Sequence conservation of microsatellites between Bos taurus (cattle), Capra hircus (goat) and related species. Examples of Use in Parentage Testing and Phylogeny Analysis. Heredity 1:53-6. Petern K . (1998). Microsatellite primers from Geospiza fortis and cross-species amplification in Darwin's finches. M o l . Ecol . 7:1782-1784. Piertney S.B. and Dallas J.F. (1997) Isolation and characterization of hypervariable microsatellites in the red grous Lagopus lagopus scoticus. M o l . Ecol . 6:93-95. Piertney S.B., Gosstkey A . , Dallas J.F. and Carss D . N . (1998). Highly polymorphic microsatellite markers in the greta cormorant {Phalacrocorx carbo). M o l . Ecol . 7:138-140. Primmer C.R. , Mol le r A . P . and Ellegren H . (1997) A wide-range survey o f cross-species microsatellite amplification in birds. M o l . Ecol . 6:101. Primmer C.R. , Raudsepp T., Chowdhary B .P . , Mol ler A . P . and Ellegren H . (1997). L o w frequency o f microsatellites in the avian genome. Genome Res. 471-481. 106 Primmer C .R . and Ellegren H . (1998). Patterns o f molecular evolution in avian microsatellite. M o l . B i o l . Evo l . 15:997-1008. Province o f Brit ish Columbia, Ministry o f Agriculture and Food. (1999). B C farm products ostrich and emu. Queller D . C . , Strassmann J.E. and Hughes C.R. (1993). Microsatellites and kinship. Trends Ecol . Evo l . 8:285-288. Reynolds J., Weir B .S . and Cockerham C . C . (1983). Estimation of the coancestry coefficient: basis for a short-term genetic distance. Genetics 105:767-779. Roy M . S . , Geffen E . , Smith D . , Ostrander E . A . and Wayne R . K . (1994). Patterns o f differentiation and hybridization in North American wolflike canids, revealed by analysis o f microsatellite Loc i . M o l . B i o l . Evo l . 11:553-570. Rumball W. , Franklin I.R., Frankham R. and Sheldon B . L . (1994). Decline in heterozygosity under full-sib and double first-cousin inbreeding in Drosophila melanogaster. Genetics 136:1039-1049. Ruzzante D . E . (1998). A comparison of several measures o f genetic distance and population structure with microsatellite data: bias and sampling variance. Can. J. Fish. Aqua. Sci . 55:1-14. Ryskov A . P . , Jincharadze A . G . , Prosnyak M. I . , Ivanov P . L . and Limborska S.A. (1988). M l 3 Phage D N A as a universal marker for D N A fingerprinting o f animals plants and microorganisms. F E B S Letters 233:388-392. Sachs J .L. and Hughes C.R. (1999). Characterization of microsatellite loci for red-necked grebes Podiceps grisegena. M o l . Ecol . 8:687-68h8. Saiki R. (1990). Amplification of genomic D N A . In: Innis M A , Gefland D H , Sninsky JJ, White TJ , eds. P C R Protocols: A guide to methods and applications. San Diego: Academic Press. Pg. 13-20. Sambrook J., Fritsch E .F . and Maniatis T.(1988). Proteinase K extraction. In: Molecular Cloning, A Laboratory Manual. Co ld Spring Harbor Laboratory Press. Sec. 3.16. Sanchez J .A. , Clabby C , Ramos D . , Blanco G. , Flavin F. , Vazquez E . and Powell R. (1996). Protein and microsatellite single locus variability in Salmo salar L (Atlantic Salmon). Hered. 77:423-432. 107 Satiou N . and N e i M . (1987). The neighbor-joining method, a new method for reconstructing phylogenetic Trees. M o l . B i o l . Evo. 4:406-425. Schlotterer C . and Pemberton J. (1994). The use o f microsatellites for genetic analysis of natural populations. E X S 69:203-214. Schwaiger F .W. , Weyerrs E . , Epplen C , Bran J., Ruff G . , Crawford A . and Epplen J.T. (1993). The paradox o f M H C - D R B Exon/Intron evolution: a-Helix and b-Sheet encoding regions diverge while hepervaiable intronic simple repeats co-evolve with b-sheet codons. J. M o l . Evo l . 37:260-272. Seddon P.J. and Soore P.S. (1998). Guidlines for substitutions in wildlife restoration projects. Conservation Biology 13:177-184. Scherf B . D . (1995). World watch list for domestic animal diversity. Food and Agriculture Organization o f the United Nations, Rome. Pg. 18-20. Shorrocks B . (1984). The genesis o f diversity. Hodder A n d Stoughton, London Sydney Auckland Toronto. Pg. 15-26. Sibley C . G . and Ahlquist J.E. (1990). Phylogeny and classification o f birds. Yale University Press, New Haven & London. Pg. 272-288. Selander R . K . (1976). Genetic variation in natural populations. In Aya la FJ . Molecular Evolution. Sinauer Associates, Sunderland. M A . Pg. 21-34. Shofmer R . N . (1948). The variation within and inbred line of s . c. w. leghorns. Poult. Sci . 27:235-236. Sittmann K . , Abplanalp H . and Fraser R . A . (1966). Inbreeding depression in Japanese quail. Genetics. 54:371-379 Slatkin M . (1995). A measure o f population subdivision based on microsatellite allele frequencies. Genetics 139: 457 -462. Smit, D.J .v .Z. (1963). Ostrich farming in the Little Karoo. Republic o f South Afr ica Department o f Agriculture Technical Services, Bulletin 358. Smith A . G . , Smith D . G . , and Funnell B . M . (1994). Atlas o f Mesozoic and Cenozoic Coastlines. Cambridge University Press, Cambridge, England. Pg. 38. Smith W . A . , Cillers S.C., Mellett F . D . and van Schalkwyk S.J. (1995). Ostrich production- a South African perspective. Canadian Ostrich October 1995 18-20. 108 Sokal R .R . and Michler C D . (1958) A Statistical method for evaluating systematic relationships. University of Kansas Sci . B u l l . 28: 1409-1438. Sokal, R .R . and Roh l f F.J . (1981). Biometry. W H Freeman and Company. New-York Pg. 309-312. Stevens L . (1991). Genetics and Evolution of The Domestic Fowl . Cambridge University Press. Pg. 8-13. Stewart J.S. (1992) Descriptors: dromaius novaehollandiae; Struthio camelus; animals-and-man; commercial farming, overview. Proceedings Annual Conference Association of A v i a n Veterinarians September 1-5,. Lake Worth, F L : The Association. Pg. 304-306. Streiff R. , Labbe T., Bacil ieri R., Steinkellner H . , Glossl J. and Kremer A . (1998) Within-population structure in Quercus robur L . and Quercus petraea (Matt.) L ieb l . assessed with isozymes and microsatellites M o l . Ecol . 7:317-328. Takagi N , Ttoh M and Sasaki M . (1972). Chromosome studies in four species of ratitae (Aves). Chromosoma (Berl.) 36:281-291. Tautz D . and Renz M.(1984). Simple sequences are ubiquitous repetitive components of eukaryotic genomes. Nuc l . Acids Res. 12:4127-4138. Tautz D . and Schlotterer C. (1994) Simple sequences. Curr Opin Genet Dev 4:832-837. Tiersch T.R. and Wetchel S.S. (1991). On the evolution o f genome size o f birds. J Hered. 82:363-368. Thompson W . F . and Murray M . G . (1981). The nuclear genome: structure and function, in Biochemistry of Plants. V o l . 6, Proteins and Nucleic Acids. A . Marcus, ed. Academic Press, New York. . Pg 1-81. Tyler S.C. and Wil lard H .F . (1993). Mammalian chromosome structure. Curr. Opin. Genet. Dev. 3: 390-397. Valdes A . M . , Slatkin M . and Freimer N . B . (1993). Al le le frequencies at microsatellite loci: the stepwise mutation model revisited. Genetics 133:737-749. Vanhala T., Tuikula-Haavisto M . , Elo K . , V i l k k i J. and Makai-Tanila A . (1998). Evaluation of genetic variability and genetic distances between eight chicken lines using microsatellite markers. Poult. Sci . 77:783-790. van Vleck L . D . , Pollak E.J . and Branford 0.1987). Genetics for the animal sciences. W . H . Freeman and Company, New York Pg. 232-242. 109 van Schalkwyk S.J., Cloete S.W.P. and de Kock J .A. (1996). Repeatability and phenotypic correlations for body weight and reproduction in commercial ostrich breeding pairs. British Poult. Sci . 37:953-962. van Tuinen M . , Sibley C . G . and Hedges S.B. (1998). Phylogeny and biogeography o f ratite birds inferred from D N A sequences o f the mitochondrial ribosomal genes. M o l . B i o l . E v o l . 15:370-376. Ward W . K . , Matthews M . E . , Murray N . D . and Robinson N . A . (1994). A n ostrich dinucleotide repeat at the V I A S - O S 2 locus. An im. Genet. 25:291. Ward W . K . , McPartlan H . C . , Matthews M . E . and Robinson N . A . (1998). Ostrich microsatellite at the V I A S - O S 4 , V I A S - O S 8 , VIAS-OS14 , V I A S - O S 4 , V I A S - O S 2 2 , and V I A S - O S 2 9 loci . A n i m . Genet. 29:331. Weir B . S . (1990). Genetic data analysis. Sinauer Associates, Sunderland. Pg. 222-224. Welsh J and McCle l land M . (1990). Fingerprinting genomes using P C R with arbitrary primers. Nuc l . Acids Res. 19:303-306. Westneat D.F . , and Webster M . S . (1994). Molecular analysis of kinship in birds: interesting questions and useful techniques. In: Molecular Ecology and Evolution: Approaches and applications (Schierwater B , Streit B , Wanger G P , DeSalle R.) . Birkhauser Verlag, Basel, Switzerland.. Pg. 91-126. Wil l iams J .G. , Kubelik A . R . , Livak K . J . , Rafalski J .A. and Tingey S V . (1990). D N A Polymorphisms amplified by arbitrary primers are useful as genetic markers. Nuc l . Acids Res. 18:6531-6535. Woodard A . E . , Abplanalp H . , and Snyder L . (1982). Inbreeding depression in The Red-Legged Partridge. Poult. Sci . 62:1579-1584. Wright S. (1951). The genetical structure of populations. Ann . Eugenics, 15:323-354. 110 Appendix A Kiwi Microsatellite Loci Amplified by Ostrich Primers The cross-species amplification of ten available ostrich microsatellite markers was examined in five k i w i (Apteryx australis) DNA samples from the Royal Ontario Museum. The five samples were from a single population. The cross amplification and sequencing protocol was as described in Chapter 2. Amplification conditions are given in Table A . l Three markers out of ten cross-amplified (Table A.2) . Purified DNA was sequenced (Figure A . l ) to verify the existence of an homologous microsatellite in the k iw i . The three loci that amplified successfully were O S M 1, O S M 4 and O S M 5 (Figure A.2) with 120bp, 135bp and 180bp amplification products respectively. O S M 1 and O S M 4 base sequence is given in Figure A . l . The ostrich O S M 4 base sequence was 60% conserved in the pre-repeats stretch. However no C A repeats were found as in the ostrich, but many interspersed G T repeats as in the emu and tinamou in this locus. O S M 1 did not show homology to the ostrich sequence however it was found highly conserved among the emu and tinamou (80% and 47% of the k i w i sequence was found in the emu and tinamou respectively) Il l Table A.1 P C R amplification optimization in cross-species amplification using ostrich primers on kiwi DNA. Marker Results of P C R D N A amplification in various temperatures (C°) annealing name 48 examined 53 58 O S M 1 * + LIST001 -O S M 4 * + LIST005 - - -O S M 5 - + LIST006 -LIST002 - -LIST009 - -V I A S - O S 2 * * -LIST011 -+ Solid bands * Faint bands No amplification or non specific amplification (smear) Table A.2 P C R results in the kiwi using ostrich specific microsatellite markers. k i w i O S M 1 + LIST001 -O S M 4 + LIST005 -O S M 5 + LIST006 -LIST002 -LIST009 -V I A S - O S 2 -LIST011 -+ Symbolizes amplification - Symbolizes no amplification >/•) >ri i n J 3 t_1 W 3 111 i JS 4 3 4 3 43 <J u u o 1 "B B B B | B H O O O O O O n « v i i n 3 o s .a 3 til 2 w P 6 3 w 3 H O 


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