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Open Access Highly Accessed Methodology article

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

Hermann Schwarzenbacher13, Marlies Dolezal2*, Krzysztof Flisikowski1, Franz Seefried1, Christine Wurmser1, Christian Schlötterer2 and Ruedi Fries1

Author Affiliations

1 Lehrstuhl für Tierzucht, Technische Universität München, Hochfeldweg 1, 85376 Freising-Weihenstephan, Germany

2 Institut für Populationsgenetik, Veterinärmedizinische Universität Wien, Veterinärplatz 1, 1210 Vienna, Austria

3 ZuchtData EDV Dienstleistungen Ges.m.b.H. Dresdner Sraße 89/19 1200 Vienna, Austria

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BMC Genomics 2012, 13:48  doi:10.1186/1471-2164-13-48

Published: 30 January 2012

Abstract

Background

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.

Results

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.

Conclusion

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.

Keywords:
selection signature; whole genome association; cattle; complex trait