4.5 Article

Exploration of relationships between production and fertility traits in dairy cattle via association studies of SNPs within candidate genes derived by expression profiling

期刊

ANIMAL GENETICS
卷 42, 期 3, 页码 251-262

出版社

WILEY
DOI: 10.1111/j.1365-2052.2010.02148.x

关键词

association analysis; genetic marker; reproduction

资金

  1. German Ministry of Education and Research, BMBF
  2. Forderverein Biotechnologieforschung e.V. (FBF), Bonn
  3. Lohmann Tierzucht GmbH, Cuxhaven
  4. Deutsche Forschungsgemeinschaft (Research Unit 'Mechanisms of embryo-maternal communication')
  5. BMBF (FUGATO Fertilink)

向作者/读者索取更多资源

The objective of this work was to integrate findings from functional genomics studies with genome-wide association studies for fertility and production traits in dairy cattle. Association analyses of production and fertility traits with SNPs located within or close to 170 candidate genes derived from two gene expression studies and from the literature were performed. Data from 2294 Holstein bulls genotyped for 39557 SNPs were used. A total of 111 SNPs were located on chromosomal segments covered by a candidate gene. Allele substitution effects for each SNP were estimated using a mixed model with a fixed effect of marker and a random polygenic effect. Assumed covariance was derived either from marker or from pedigree information. Results from the analysis with the kinship matrix built from marker genotypes were more conservative than from the analysis with the pedigree-derived relationship matrix. From sixteen SNPs with significant effects on both classes of traits, ten provided evidence of an antagonistic relationship between productivity and fertility. However, we found four SNPs with favourable effects on fertility and on yield traits, one SNP with favourable effects on fertility and percentage traits, and one SNP with antagonistic effects on two fertility traits. While most quantitative genetic studies have proven genetic antagonisms between yield and functional traits, improvements in both production and functionality may be possible when focusing on a few relevant SNPs. Investigations combining input from quantitative genetics and functional genomics with association analysis may be applied for the identification of such SNPs.

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