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Open Access Research

Contrasting signals of positive selection in genes involved in human skin-color variation from tests based on SNP scans and resequencing

Johanna Maria de Gruijter12, Oscar Lao1*, Mark Vermeulen1, Yali Xue3, Cara Woodwark3, Christopher J Gillson3, Alison J Coffey3, Qasim Ayub3, S Qasim Mehdi4, Manfred Kayser1 and Chris Tyler-Smith3

Author Affiliations

1 Department of Forensic Molecular Biology, Erasmus MC University Medical Center, PO Box 2040, Rotterdam, 3000 CA, The Netherlands

2 Netherlands Forensic Institute, Postbus 24044, The Hague, 2490 AA, The Netherlands

3 Wellcome Trust Genome Campus, Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK

4 Sindh Institute of Urology and Transplantation (SIUT) Karachi, Civil Hospital Karachi 74200, Pakistan

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Investigative Genetics 2011, 2:24  doi:10.1186/2041-2223-2-24

Published: 1 December 2011

Abstract

Background

Numerous genome-wide scans conducted by genotyping previously ascertained single-nucleotide polymorphisms (SNPs) have provided candidate signatures for positive selection in various regions of the human genome, including in genes involved in pigmentation traits. However, it is unclear how well the signatures discovered by such haplotype-based test statistics can be reproduced in tests based on full resequencing data. Four genes (oculocutaneous albinism II (OCA2), tyrosinase-related protein 1 (TYRP1), dopachrome tautomerase (DCT), and KIT ligand (KITLG)) implicated in human skin-color variation, have shown evidence for positive selection in Europeans and East Asians in previous SNP-scan data. In the current study, we resequenced 4.7 to 6.7 kb of DNA from each of these genes in Africans, Europeans, East Asians, and South Asians.

Results

Applying all commonly used neutrality-test statistics for allele frequency distribution to the newly generated sequence data provided conflicting results regarding evidence for positive selection. Previous haplotype-based findings could not be clearly confirmed. Although some tests were marginally significant for some populations and genes, none of them were significant after multiple-testing correction. Combined P values for each gene-population pair did not improve these results. Application of Approximate Bayesian Computation Markov chain Monte Carlo based to these sequence data using a simple forward simulator revealed broad posterior distributions of the selective parameters for all four genes, providing no support for positive selection. However, when we applied this approach to published sequence data on SLC45A2, another human pigmentation candidate gene, we could readily confirm evidence for positive selection, as previously detected with sequence-based and some haplotype-based tests.

Conclusions

Overall, our data indicate that even genes that are strong biological candidates for positive selection and show reproducible signatures of positive selection in SNP scans do not always show the same replicability of selection signals in other tests, which should be considered in future studies on detecting positive selection in genetic data.