↓ Skip to main content

Combining evidence of selection with association analysis increases power to detect regions influencing complex traits in dairy cattle

Overview of attention for article published in BMC Genomics, January 2012
Altmetric Badge

Readers on

mendeley
57 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Combining evidence of selection with association analysis increases power to detect regions influencing complex traits in dairy cattle
Published in
BMC Genomics, January 2012
DOI 10.1186/1471-2164-13-48
Pubmed ID
Authors

Hermann Schwarzenbacher, Marlies Dolezal, Krzysztof Flisikowski, Franz Seefried, Christine Wurmser, Christian Schlötterer, Ruedi Fries

Abstract

Hitchhiking mapping and association studies are two popular approaches to map genotypes to phenotypes. In this study we combine both approaches to complement their specific strengths and weaknesses, resulting in a method with higher statistical power and fewer false positive signals. We applied our approach to dairy cattle as they underwent extremely successful selection for milk production traits and since an excellent phenotypic record is available. We performed whole genome association tests with a new mixed model approach to account for stratification, which we validated via Monte Carlo simulations. Selection signatures were inferred with the integrated haplotype score and a locus specific permutation based integrated haplotype score that works with a folded frequency spectrum and provides a formal test of signifance to identify selection signatures. About 1,600 out of 34,851 SNPs showed signatures of selection and the locus specific permutation based integrated haplotype score showed overall good accordance with the whole genome association study. Each approach provides distinct information about the genomic regions that influence complex traits. Combining whole genome association with hitchhiking mapping yielded two significant loci for the trait protein yield. These regions agree well with previous results from other selection signature scans and whole genome association studies in cattle. We show that the combination of whole genome association and selection signature mapping based on the same SNPs increases the power to detect loci influencing complex traits. The locus specific permutation based integrated haplotype score provides a formal test of significance in selection signature mapping. Importantly it does not rely on knowledge of ancestral and derived allele states.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Switzerland 1 2%
Germany 1 2%
United Kingdom 1 2%
Finland 1 2%
Unknown 51 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 25%
Student > Ph. D. Student 13 23%
Student > Doctoral Student 4 7%
Student > Postgraduate 4 7%
Professor > Associate Professor 4 7%
Other 11 19%
Unknown 7 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 68%
Biochemistry, Genetics and Molecular Biology 6 11%
Veterinary Science and Veterinary Medicine 1 2%
Psychology 1 2%
Physics and Astronomy 1 2%
Other 1 2%
Unknown 8 14%