Email updates

Keep up to date with the latest news and content from BMC Genomics and BioMed Central.

Open Access Research article

Application of site and haplotype-frequency based approaches for detecting selection signatures in cattle

Saber Qanbari1*, Daniel Gianola2, Ben Hayes3, Flavio Schenkel4, Steve Miller4, Stephen Moore5, Georg Thaller6 and Henner Simianer1

Author Affiliations

1 Animal Breeding and Genetics Group, Department of Animal Sciences, Georg-August University, 37075 Göttingen, Germany

2 Department of Animal Sciences and Department of Dairy Science, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA

3 Animal Genetics and Genomics, Primary Industries Research Victoria, 475 Mickleham Rd, Attwood, VIC 3049, Australia

4 Centre for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, Guelph, Ontario, N1G 2W1 Canada

5 Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada

6 Institute of Animal Breeding and Animal Husbandry, Christian-Albrechts-University, 24098 Kiel, Germany

For all author emails, please log on.

BMC Genomics 2011, 12:318  doi:10.1186/1471-2164-12-318

Published: 16 June 2011

Abstract

Background

'Selection signatures' delimit regions of the genome that are, or have been, functionally important and have therefore been under either natural or artificial selection. In this study, two different and complementary methods--integrated Haplotype Homozygosity Score (|iHS|) and population differentiation index (FST)--were applied to identify traces of decades of intensive artificial selection for traits of economic importance in modern cattle.

Results

We scanned the genome of a diverse set of dairy and beef breeds from Germany, Canada and Australia genotyped with a 50 K SNP panel. Across breeds, a total of 109 extreme |iHS| values exceeded the empirical threshold level of 5% with 19, 27, 9, 10 and 17 outliers in Holstein, Brown Swiss, Australian Angus, Hereford and Simmental, respectively. Annotating the regions harboring clustered |iHS| signals revealed a panel of interesting candidate genes like SPATA17, MGAT1, PGRMC2 and ACTC1, COL23A1, MATN2, respectively, in the context of reproduction and muscle formation. In a further step, a new Bayesian FST-based approach was applied with a set of geographically separated populations including Holstein, Brown Swiss, Simmental, North American Angus and Piedmontese for detecting differentiated loci. In total, 127 regions exceeding the 2.5 per cent threshold of the empirical posterior distribution were identified as extremely differentiated. In a substantial number (56 out of 127 cases) the extreme FST values were found to be positioned in poor gene content regions which deviated significantly (p < 0.05) from the expectation assuming a random distribution. However, significant FST values were found in regions of some relevant genes such as SMCP and FGF1.

Conclusions

Overall, 236 regions putatively subject to recent positive selection in the cattle genome were detected. Both |iHS| and FST suggested selection in the vicinity of the Sialic acid binding Ig-like lectin 5 gene on BTA18. This region was recently reported to be a major QTL with strong effects on productive life and fertility traits in Holstein cattle. We conclude that high-resolution genome scans of selection signatures can be used to identify genomic regions contributing to within- and inter-breed phenotypic variation.