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BMC Genet. 2016 Mar 22;17:55. doi: 10.1186/s12863-016-0363-8.

Genome-wide association analysis of milk yield traits in Nordic Red Cattle using imputed whole genome sequence variants.

Author information

1
Animal Genomics, Green Technology, Natural Resources Institute Finland (Luke), Jokioinen, Finland. terhi.iso-touru@luke.fi.
2
Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark.
3
Animal Genomics, Green Technology, Natural Resources Institute Finland (Luke), Jokioinen, Finland.

Abstract

BACKGROUND:

The Nordic Red Cattle consisting of three different populations from Finland, Sweden and Denmark are under a joint breeding value estimation system. The long history of recording of production and health traits offers a great opportunity to study production traits and identify causal variants behind them. In this study, we used whole genome sequence level data from 4280 progeny tested Nordic Red Cattle bulls to scan the genome for loci affecting milk, fat and protein yields.

RESULTS:

Using a genome-wise significance threshold, regions on Bos taurus chromosomes 5, 14, 23, 25 and 26 were associated with fat yield. Regions on chromosomes 5, 14, 16, 19, 20 and 25 were associated with milk yield and chromosomes 5, 14 and 25 had regions associated with protein yield. Significantly associated variations were found in 227 genes for fat yield, 72 genes for milk yield and 30 genes for protein yield. Ingenuity Pathway Analysis was used to identify networks connecting these genes displaying significant hits. When compared to previously mapped genomic regions associated with fertility, significantly associated variations were found in 5 genes common for fat yield and fertility, thus linking these two traits via biological networks.

CONCLUSION:

This is the first time when whole genome sequence data is utilized to study genomic regions affecting milk production in the Nordic Red Cattle population. Sequence level data offers the possibility to study quantitative traits in detail but still cannot unambiguously reveal which of the associated variations is causative. Linkage disequilibrium creates difficulties to pinpoint the causative genes and variations. One solution to overcome these difficulties is the identification of the functional gene networks and pathways to reveal important interacting genes as candidates for the observed effects. This information on target genomic regions may be exploited to improve genomic prediction.

KEYWORDS:

Association study; Milk traits; Nordic Red Cattle; Whole genome sequence

PMID:
27006194
PMCID:
PMC4804490
DOI:
10.1186/s12863-016-0363-8
[Indexed for MEDLINE]
Free PMC Article

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