Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 9/8/2009
Publication Date: 8/1/2010
Publication URL: http://handle.nal.usda.gov/10113/47634
Citation: Vallet, J.L., Nonneman, D.J., Kuehn, L.A. 2010. Quantitative genomics of female reproduction. In: Jiang, Z., Ott, T.L., editors. Reproductive Genomics in Domestic Animals. Ames, IA: Wiley-Blackwell Publishing. p. 23-51. Interpretive Summary:
Technical Abstract: Numerous quantitative trait loci (QTL) for reproductive traits in domestic livestock have been described in the literature. In this chapter, the components needed for detection of reproductive trait QTL are described, including collection of phenotypes, genotypes, and the appropriate statistical analysis to either demonstrate significant associations between chromosomal regions and reproductive traits or predict breeding values for reproductive traits given sufficiently dense genome-wide genotyping. The sometimes complex genetic architecture of some female reproductive traits (e.g., both sire, dam, and fetal genotypes play a role in success of a trait like pregnancy) add complexity to female reproduction QTL, however, most published QTL for reproductive traits focus on only the genotype of the dam. Like other traits, the genes responsible for reproductive QTL may influence other traits (resulting in correlated responses) so care should be exercised when using QTL for selection because unwanted correlated changes in other traits may occur. Most genome scans for reproductive traits in livestock have been performed using linkage analysis, which is then followed up by dense genotyping within the QTL region and linkage disequilibrium analysis to narrow the region to a handful of possible candidate genes. It has been possible to determine the gene(s) and the polymorphism(s) responsible for differences in a few reproductive traits, however, this doesn't always lead to a complete understanding of the physiological mechanism involved. Recent developments in genotyping in livestock will allow dense genome-wide linkage disequilibrium analysis, which if appropriately analyzed will improve genetic selection for low heritability traits like reproduction. This may also provide the ability to assess how different regions of the genome interact (epistasis) to affect traits. The advent of genome-wide dense genotyping will result in the identification of specific markers that may be manipulated to alter a trait in a variety of populations, but it is more likely that instead it will be used to predict the effect of the whole genome simultaneously. Because of this, it is unlikely to be necessary to identify the gene or the physiological mechanism in order for this technology to be useful. On the other hand, even though identification of the genes and polymorphisms responsible for differences in traits don't always result in a full understanding of the underlying physiological mechanisms involved, they will provide important and novel clues to these physiological mechanisms and enhance our understanding of reproductive biology in livestock.