Applied Bovine Genomics: Chipping away at the genetics underlying disease traits.

Authors: Sonstegard, Tad; VANRADEN, PAUL - USDA,AIPL; WIGGANS, GEORGE - USDA,AIPL; SCHNABEL, STEVEN - UNIVERSITY OF MISSOURI; Liu, Ge - George; MATUKUMALLI, LAKSHMI - GEORGE MASON UNIVERSITY; MCKAY, STEPHANIE - UNIVERSITY OF MISSOURI; Schroeder, Steven - Steve; Gasbarre, Louis; TAYLOR, JEREMY - UNIVERSITY OF MISSOURI; Van Tassell, Curtis - Curt

Submitted to: International Symposium of Animal Functional Genomics
Publication Type: Abstract Only
Publication Acceptance Date: 3/15/2008
Publication Date: 4/6/2008
Citation: Sonstegard, T.S., Vanraden, P., Wiggans, G., Schnabel, S., Liu, G., Matukumalli, L.K., Silva, M.V., Mckay, S., Schroeder, S.G., Gasbarre, L.C., Taylor, J.F., Van Tassell, C.P. 2008. Applied Bovine Genomics: Chipping away at the genetics underlying disease traits.. International Symposium of Animal Functional Genomics.

Interpretive Summary:

Technical Abstract: The sequencing of the bovine genome has resulted in the development of experimental tools and reagents that will greatly enhance genome biology research in cattle, especially for traits affecting health. Previously, mapping studies to identify quantitative trait loci (QTL) affecting health traits were limited by low density microsatellite marker genotypes and the phenotypes that could be extracted from experimental populations optimized for QTL mapping (i.e. F2 and backcross populations). Results from these studies have not always been readily applicable for enhancing genetic improvement in commercial populations. However, some of these limitations can be overcome with the availability of dense single nucleotide polymorphism (SNP) based genotyping assays and copy number variation (CNV) maps. To initiate these studies, we produced a 50,000 SNP assay with uniform distribution of informative markers across the bovine genome, and a map of CNV common to popular cattle breeds. These mapping tools allow determination of linkage disequilibrium for disease traits across populations, or alternatively, the improvement of multiple traits based on genome composition. We are investigating the feasibility of these approaches by performing a genome-wide association study in both the U.S. commercial dairy population (N=4,000 Holstein sires) across all nationally recorded traits and on an experimental cattle population (N=600 animals) previously found to contain QTL for parasite resistance/susceptibility. The goals of these studies will be to implement genome-wide selection based on haplotype, linkage disequilibrium, and CNV information and develop a subset of markers denoting important haplotypes for disease susceptibility diagnostics. Our preliminary analysis of all production and health traits using subset of genotyped Holstein ancestors combined with the genomic predictions by multiple regression suggested overall predictions were significantly (P < .0001) more accurate than official parent averages for all 26 traits. Across all traits, realized reliabilities for the combined genomic predictions averaged 18% higher than reliabilities of parent average (50% vs. 32%). Gains in information were equivalent to 7 daughters for milk yield or 57 daughters for fertility. This strongly suggests the inexpensive genotyping of dense markers for many animals allows inheritance of minor genes to be traced. Therefore, genomic selection can greatly increase accuracy and decrease generation interval, and ultimately should reduce the cost of progeny testing of dairy sires. Eventually, this methodology should prove useful for improving the allele frequencies of disease resistance haplotypes in high production breeds of cattle allowing intensification of production without adversely affecting the genetic diversity. Moreover, these studies will provide new biological information on fertility, mastitis, and parasite resistance/susceptibility.