title: Antagonistic genetic correlations for milking traits within the genome of dairy cattle.
abstract: Genome-wide association studies can be applied to identify useful SNPs associated with complex traits. Furthermore, regional genomic mapping can be used to estimate regional variance and clarify the genomic relationships within and outside regions but has not previously been applied to milk traits in cattle. We applied both single SNP analysis and regional genomic mapping to investigate SNPs or regions associated with milk yield traits in dairy cattle. The de-regressed breeding values of three traits, total yield (kg) of milk (MLK), fat (FAT), and protein (PRT) in 305 days, from 2,590 Holstein sires in Japan were analyzed. All sires were genotyped with 40,646 single-nucleotide polymorphism (SNP) markers. A genome-wide significant region (P < 0.01) common to all three traits was identified by regional genomic mapping on chromosome (BTA) 14. In contrast, single SNP analysis identified significant SNPs only for MLK and FAT (P < 0.01), but not PRT in the same region. Regional genomic mapping revealed an additional significant region (P < 0.01) for FAT on BTA5 that was not identified by single SNP analysis. The additive whole-genomic effects estimated in the regional genomic mapping analysis for the three traits were positively correlated with one another (0.830-0.924). However, the regional genomic effects obtained by using a window size of 20 SNPs for FAT on BTA14 were negatively correlated (P < 0.01) with the regional genomic effect for MLK (-0.940) and PRT (-0.878). The BTA14 regional effect for FAT also showed significant negative correlations (P < 0.01) with the whole genomic effects for MLK (-0.153), FAT (-0.172), and PRT (-0.181). These negative genomic correlations between loci are consistent with the negative linkage disequilibrium expected for traits under directional selection. Such antagonistic correlations may hamper the fixation of the FAT increasing alleles on BTA14. In summary, regional genomic mapping found more regions associated with milk production traits than did single SNP analysis. In addition, the existence of non-zero covariances between regional and whole genomic effects may influence the detection of regional effects, and antagonistic correlations could hamper the fixation of major genes under intensive selection.
authors.affiliation: Kyoto University, Graduate School of Informatics, Kyoto Japan.
authors.forename: Olivier
authors.initials: O
authors.lastname: Gervais
authors.affiliation: The Roslin Institute and R(D)SVS, University of Edinburgh, Midlothian, United Kingdom.
authors.forename: Ricardo
authors.initials: R
authors.lastname: Pong-Wong
authors.affiliation: MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom.
authors.forename: Pau
authors.initials: P
authors.lastname: Navarro
authors.affiliation: The Roslin Institute and R(D)SVS, University of Edinburgh, Midlothian, United Kingdom.|MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom.
authors.forename: Chris S
authors.initials: CS
authors.lastname: Haley
authors.affiliation: Nihon University, Bio-resource Science, Fujisawa, Japan.
authors.forename: Yoshitaka
authors.initials: Y
authors.lastname: Nagamine
mesh_terms: D000818:Animals; D002417:Cattle / Q000235:genetics*; D002874:Chromosome Mapping; D005260:Female; D016678:Genome / Q000235:genetics*; D055106:Genome-Wide Association Study / Q000662:veterinary; D007774:Lactation / Q000235:genetics*; D008892:Milk / Q000378:metabolism; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D019655:Quantitative Trait, Heritable