Mapping Genes for Complex Traits in Domestic Animals and Their Use in Breeding Programmes

REVIEWS Mapping genes for complex traits in domestic animals and their use in breeding programmes Michael E. Goddard*‡ and Ben J. Hayes‡ Abstract | Genome-wide panels of SNPs have recently been used in domestic animal species to map and identify genes for many traits and to select genetically desirable livestock. This has led to the discovery of the causal genes and mutations for several single-gene traits but not for complex traits. However, the genetic merit of animals can still be estimated by genomic selection, which uses genome-wide SNP panels as markers and statistical methods that capture the effects of large numbers of SNPs simultaneously. This approach is expected to double the rate of genetic improvement per year in many livestock systems. Quantitative trait Traits that are controlled by a single gene, such as flower Over the past 20 years, two approaches have been A measurable trait that colour in pea plants, have been important in elucidat- used to discover the genes and polymorphisms contrib- depends on the cumulative ing the mechanisms of heredity, yet most traits that are uting to variation in complex traits. In one approach action of many genes and the important in agriculture, medicine and evolution candidate genes have been targeted based on their role environment, and that can vary quantitative traits among individuals over a given are complex or . These traits include: in the physiology of the trait (for example, the expres- range to produce a continuous susceptibility to many diseases, such as diabetes in sion level of milk proteins), and in the other approach distribution of phenotypes. humans; agriculturally important traits, such as the milk the genes that affect a trait of interest have been mapped yield of dairy cows; and traits that affect fitness in the to a chromosomal location using genetic markers2–4. Estimated breeding value wild, such as the clutch size of birds. However, progress in identifying the causal genes for An estimate of the additive genetic merit for a particular Identifying genes for complex traits would greatly complex traits has been slow as linkage mapping results trait that an individual will pass enhance our understanding of these traits, but in domes- in large confidence intervals. on to its descendents. tic animals there would also be a practical benefit to agri- The recent availability of large panels of SNPs in culture. Traditionally, the genetics of complex traits in domestic species has given new momentum to the Heritability The proportion of phenotypic these species has been studied without identifying the search for the mutations underlying variation in com- variance caused by additive genes involved. Selection has been based on estimated plex traits through the use of genome-wide association genetic variation. breeding values calculated from phenotypic records and (GWA) studies. This Review concentrates on domesti- pedigrees, and on knowledge of the heritability of each cated species, especially those for which the possibility trait. This has been successful, but the process is slow if of dissecting the architecture of important quantitative the trait can only be measured in one sex (for example, traits is enhanced by the availability of genome-wide milk yield), after death (for example, meat quality) or SNP panels — these species include cattle, dogs and *Department of Agriculture late in life (for example, longevity), or if measuring the chickens. Genome-wide SNP panels for sheep, pigs and Food Systems, University trait is expensive (for example, methane production, and horses have also recently become available. of Melbourne, Royal Parade, feed requirement or disease resistance). Therefore, to We first discuss the experimental designs, statistical Parkville 3010, Australia. ‡Biosciences Research improve on these traits, it would be advantageous analyses and results of this research. GWA studies have Division, Department of to identify genes for them and select animals carrying successfully identified genes causing simple Mendelian Primary Industries, Victoria, the desirable alleles1. Thus, compared with research on traits, but these studies have not yet identified genes for 1 Park Drive, Bundoora complex traits in humans, there is greater emphasis in complex traits. Animal breeders can nevertheless use 3083, Australia. domesticated animals on predicting genetic merit and the results of GWA studies for genetic improvement of Correspondence to M.E.G. genomic e-mail: phenotype and less emphasis on discovering genes domestic animals by using a technique called [email protected] and pathways. However, both aims are important and are selection, which potentially leads to large increases in doi:10.1038/nrg2575 covered in this Review. the rate of genetic improvement5. Genomic selection is NATURE REVIEWS | GENETICS VOLUME 10 | JUNE 2009 | 381 © 2009 Macmillan Publishers Limited. All rights reserved REVIEWS already being used successfully to select dairy cattle car- long-range LD does not apply across breeds because rying desirable alleles for milk yield and other traits, and animals from different breeds do not share a recent is likely to be applied to all livestock in the near future common ancestor. This Ne history is similar to that as well as to crops and aquaculture. We describe the experienced by dogs, which show a similar pattern of science behind this revolution and, finally, we discuss LD to cattle15, but is the opposite of that experienced by the directions for future research into complex traits in humans. The European human Ne was only ~3,000 but domesticated animals. then increased enormously in the last 10,000 years12 (FIG. 1). Consequently, humans have similar LD to cattle The history of QTL mapping at short distances but almost no LD at long distances In the decades before the advent of GWA studies, genes (FIG. 2a). Genetic improvement affecting production and fitness traits in domestic ani- This pattern of LD in domestic animals means that Deliberate genetic change in a mals were mapped to chromosomal regions using link- a marker may be in LD with a QTL some distance away population of domestic animals linkage disequilibrium or plants brought about by age analysis and (LD) between and hence show an association with the trait affected human control of their selection markers and QTLs. As we explain below, differences by the QTL. Consequently, one does not need as dense and breeding that makes them between animals and humans in family structure and a panel of SNPs for a GWA study in many domestic more suitable for the purpose in the extent of LD affected the power and precision of animal species as in humans. Conversely, markers that for which they are kept. mapping in animal studies compared with observations are located several centimorgans from the QTL can Genomic selection in human studies. show an association to the trait, making precise map- Selection of animals for ping more difficult. This problem can be overcome by breeding based on Linkage analysis. Early attempts to map QTLs used using multiple breeds: markers that show a consistent estimated breeding values blood groups as genetic markers6–8. However, the power pattern of LD with a QTL across breeds must be close calculated from the joint (FIG. 2b) effects of genetic markers of this approach was markedly enhanced by the identifi- to that QTL . covering the whole genome. cation of numerous highly variable microsatellite mark- The traditional mapping strategy was to use linkage ers. Typically, a linkage analysis was performed using to map a QTL to a large region and then use LD to map Linkage disequilibrium microsatellite markers, often with large half-sibling it more precisely. However, discovering and typing a The absence of linkage 9 equilibrium so that the allele at families . The ability to generate hundreds of offspring panel of dense markers across the confidence interval of one locus is correlated with the per sire made this approach more powerful in livestock a single QTL was a major undertaking until the arrival allele at another locus. than in humans. However, linkage analysis usually of genome-wide panels of SNPs. mapped the QTLs to a large interval of 20 centimorgans Effective population size (cM) or more4,9, which made it difficult to identify the GWA studies The number of individuals in underlying mutation and to use the marker information Principles and tools. The basic design of a GWA study is an idealized population with random mating and no in animal breeding programmes. that a sample of animals are recorded for a trait of inter- selection that would lead to the est and assayed for a genome-wide panel of markers to same rate of inbreeding as LD and the effect of effective population size. More detect statistical associations between the trait and any observed in the real population. precise mapping is possible using LD between markers of the markers. Design parameters include the choice The effective population size can be much less than the and QTLs because LD decays quickly as the distance and number of animals and markers. Most commonly, actual population size owing between marker and QTL increases. A linkage analy- the data from a GWA study are analysed one SNP at a to the unequal genetic sis uses recombination events in the recorded pedigree time using a simple linear model that includes: the effect contribution of individuals to and traces chromosome segments to a common ances- of a SNP; fixed effects, such as the cohort or group to the next generation. tor in the pedigree. By contrast, LD mapping relies on which the animal belongs; and the polygenic breeding value Linear model chromosome segments inherited from a common ances- of each animal, which is due to all other genes A statistical model that tor before the recorded pedigree — this is because it is affecting the trait. assumes that the observed the inheritance of identical chromosome segments by The genomic sequence is available for several phenotypic value can be multiple descendents from a common ancestor that domestic species, including cattle, horses, chickens and explained by the sum of the effects of independent causes LD.

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