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, 12 (4), e0175105
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Antagonistic Genetic Correlations for Milking Traits Within the Genome of Dairy Cattle

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Antagonistic Genetic Correlations for Milking Traits Within the Genome of Dairy Cattle

Olivier Gervais et al. PLoS One.

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.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1
LRT and percentages of regional (R) and whole genomic variances (W) in total genomic variances (W+R) for three yield traits: (a) milk (MLK), (b) fat (FAT), and (c) protein yield (PRT). The vertical axis indicates the likelihood ratio test (LRT) and ratio (%), and the horizontal axis shows the window number across the genome. In total, 798 windows, each using 100 SNPs, were examined.
Fig 2
Fig 2. LRT and percentages of regional (R) and whole genomic variances (W) in total genomic variances (W+R) using 20 or 10 SNPs for BTA14.
The vertical axis indicates the likelihood ratio test (LRT) and ratio (%), and the horizontal axis is the window number at the end of BTA14. (a) milk (MLK), (b) fat (FAT), and (c) protein yield (PRT); size 20 and size 10 are window sizes using 20 SNPs and 10 SNPs, respectively.
Fig 3
Fig 3. Correlation between regional genomic effects of three traits (MLK, milk; FAT, fat; PRT, protein yield) from the first window using 20 SNPs on BTA14.
Individuals were categorized into three genotypes with the most significant SNP (ARS-BFGL-NGS-4939) in this region. Genotypes (g-type) MM, mm, and Mm are major and minor homozygotes and heterozygotes, respectively. The vertical axes are the regional genomic effects of (a) fat and (b, c) protein yield, and the horizontal axes are (a, b) milk and (c) fat yield.

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