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

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

doi:10.1186/1471-2164-13-48

Abstract

BackgroundHitchhiking 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.ResultsAbout 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.ConclusionWe 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.

Highlights

Hitchhiking mapping and association studies are two popular approaches to map genotypes to phenotypes
A similar trend can be seen for iHSVoight where standard deviation (SD) in the 0.9 is higher compared to the rest of the derived allele frequency bins
We postulate that this is due to increased rates of false positives, since power simulations by [9] and [45] show that iHSVoight is powerful for loci with intermediate allele frequencies and that the power of the test drops substantially when the selective sweep is close to fixation, in other words for SNPs with low MAF

Summary

Introduction

Hitchhiking mapping and association studies are two popular approaches to map genotypes to phenotypes. Qanbari et al [18] employed an extended haplotype homozygosity test and published a genome wide map of recent selection within the German Holstein dairy cattle population. Gautier et al [19] used this signature of selection within a recently admixed Caribbean cattle breed These authors employed a modified version of Rsb scores proposed by [20] to detect local excess or deficiency from a given ancestry relative to the average genome admixture levels. Qanbari et al [21] recently published a genome scan in several dairy and beef breeds including German Brown Swiss cattle based on integrated haplotype scores and when contrasting breeds employing FST statistics. Disentangling selection from nuisance signals caused by the demographic history of a breed or species based on genome wide polymorphism data remains challenging

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Discussion

Conclusion