September 27-September 29, 2013 Boston, MA Thank you to our generous sponsors Perpetual public-accessible conference proceedings website: www.vin.com/tufts/2013 2 6th Tufts’ Canine and Feline Breeding and Genetics Conference Scientific Program Saturday, September 28 Lecture Time: Title of Lecture: Speaker: 8:30-9:10 Unraveling the Sources of Genetic Structure Within Breeds Dr. Pam Wiener 9:10-9:50 Taking Advantage of Dog Breed Structure to Understand Dr. Elaine Ostrander Health 10:10-10:30 Genetics of Cat Populations and Breeds: Implications for Dr. Leslie Lyons Breed Management for Health! 10:30-11:10 Breeding Practices According to Breeds; Time, Place, and Dr. Grégoire Leroy Consequences 11:10-11:30 Inbreeding, Outbreeding, and Breed Evolution Dr. Jerold Bell 1:15-1:55 Unraveling the Phenotypic and Genetic Complexity of Dr. Paula Henthorn Canine Cystinuria 1:55-2:35 How to Use and Interpret Genetic Tests for Heart Disease Dr. Kathryn Meurs in Cats and Dogs 2:55-3:35 Update on Genetic Tests for Diseases and Traits in Cats: Dr. Leslie Lyons Implications for Cat Health, Breed Management and Human Health 3:35-4:15 Hereditary Gastric Cancer in Dogs Dr. Elizabeth McNiel 3 The sources of genetic structure within breeds and its implications Pam Wiener, Ph.D. The Roslin Institute, R(D)SVS, University of Edinburgh, Division of Genetics and Genomics [email protected] Genetic analyses of domesticated animal species have proved very useful for determining relationships between breeds (Wiener et al., 2004), for illuminating the processes underlying the domestication process (Wiener & Wilkinson, 2011), and for identifying genes associated with specific traits (Georges, 2007). An important tool is the use of clustering-based population genetic methods, in which populations are determined based on the genetic make- up of individuals, without prior population labelling. These techniques have been applied to domesticated animal species in a number of studies and in most cases, have demonstrated good correspondence between breeds and genetically-defined populations. Use of this approach has proven to be particularly useful for identifying animals that do not fit the general genetic profile of a given breed, for example, cross-bred or mis-classified individuals. Within-breed genetic differentiation In some cases, however, clustering techniques have revealed population structure below the breed level, such that separate groupings are identified within breeds. This was demonstrated in an analysis of British pig breeds, in which the British Saddleback breed showed internal genetic structure (Wilkinson et al., 2008). There appeared to be greater differentiation between the two British Saddleback clusters than between some breed pairs (Figure 1). A similar finding was found for several British chicken breeds (Wilkinson et al., 2011), in which within-breed differentiation was associated with different morphological types for some breeds and with different flocks in others (Figure 2). The latter pattern indicates restricted gene flow between breeders, which can lead to high rates of inbreeding. Figure 2. Individual assignment based on clustering analysis at K=35. Histograms demonstrate the proportion of each individual’s genome that originated from each of 24 populations. Each individual is represented by a vertical line corresponding to its membership coefficient (q). Genetic structure is seen within breeds such as Araucana, Leghorn , eMaran, Silki and Sussex. Figure 1. A neighbour‐joining tree of British pigs constructed Reproduced from Wilkinson et al. (2011). from allele‐sharing distances among all individuals. Bootstrap values greater than 500 are shown (out of 1000). British Saddleback individuals are found in two separate clusters. Reproduced from Wilkinson et al. (2008). 4 Several recent studies in dogs have also identified within-breed differentiation, which derives from several sources. Quignon et al. (2007) analysed American and European samples from four breeds and demonstrated a clear genetic separation of US and EU Golden retrievers. They also identified genetic differentiation within Bernese mountain dogs, but it was not clearly associated with geographical origin. Two other breeds in that study (Flat coated retrievers and Rottweilers) did not show evidence of genetic structure. In other cases, genetic differentiation is associated with phenotypic traits. Bjornfeldt et al. (2008) identified strong genetic differentiation in poodles due to size and coat colour. Standard poodles were clearly genetically distinct from all other poodles, while the smaller poodles were differentiated from each other based on a combination of size and coat colour. A study on Schnauzer breeds revealed a similar pattern of differentiation (Streitberger et al. 2011); the authors found that Giant Schnauzers were strongly differentiated from the other Schnauzer breeds, while the smaller Schnauzers clustered based on both coat colour and size. Mellanby et al. (2013) also demonstrated genetic structure within UK Cavalier King Charles spaniels, although the source of the differentiation was not clear. Preliminary analysis of UK Labrador retrievers indicates within-breed genetic differentiation related to the role of dogs (i.e. working gun dogs versus pets) as well as phenotypic characteristics (unpublished results). Implications for managing recessive diseases: Strong population structure may lead to high levels of inbreeding by creating partially independent sub-populations with relatively small effective population sizes, increasing the role of genetic drift. This can thereby increase the overall levels of homozygosity and thus, may also increase the numbers of individuals homozygous for recessive disease alleles. Management practices that increase mixing within the breed will reduce overall levels of inbreeding and therefore, may help reduce the levels of such diseases. Somewhat ironically, in rare breeds, management strategies that involve reduced breeding from a segment of the breed that carries known disease-associated variants may exacerbate the problem at other loci by reducing the effective population size (Collins et al., 2011) and thus these strategies must be designed with care and forethought. Implications for genetic association studies and genetic evaluation: It is well established that the existence of genetic structure can lead to spurious associations in genome-wide association studies if the trait of interest is not evenly distributed with respect to genetic sub- groups (Lander & Schork, 1994; Price et al., 2006). Therefore, it is recommended that in such cases, stratification should be accounted for (Price et al., 2010). Population structure may also influence the implementation of genomic evaluation schemes, in which breeding decisions are based on genomic marker information; however, the implications of such structure are less clear in this case. For example, Daetwyler et al. (2012) conclude that the accuracy of prediction may be reduced by accounting for population stratification in some situations (e.g. low or medium density markers). Further study is required on this issue. References Björnfeldt, S., F. Hailer, M. Nord & C. Vilà. (2008). Assortative mating and fragmentation within dog breeds. BMC Evolutionary Biology 8:28. Collins, L.M., L. Asher, J. Summers & P. McGreevy. (20110). Getting priorities straight: Risk assessment and decision-making in the improvement of inherited disorders in pedigree dogs. The Veterinary Journal 189: 147–154. Daetwyler, H.D., K.E. Kemper, J.J.J. van der Werf & B.J. Hayes. (2012). Components of the accuracy of genomic prediction in a multi-breed sheep population. Journal of Animal Science 90: 3375- 3384. Georges, M. (2007). Mapping, fine mapping, and molecular dissection of quantitative trait loci in domestic animals. Annual Review of Genomics and Human Genetics 8: 131-162. 5 Lander, E.S. & N.J. Schork. (1994). Genetic dissection of complex traits. Science 265: 2037-2048. Mellanby, R.J., R. Ogden, D.N. Clements, A.T. French, A.G. Gow, et al. (2013). Population structure and genetic heterogeneity in popular dog breeds in the UK. The Veterinary Journal 196: 92-97. Quignon, P., L. 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