1. ¹Leverhulme Centre for Human Evolutionary Studies, University of Cambridge, Cambridge, UK
2. ²Department of Zoology, University of Cambridge, Cambridge, UK
3. ³Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
4. ⁴Department of Biological Sciences, The University of Hull, Hull, UK
5. ⁵Department of Infectious Disease Epidemiology, MRC Centre for Outbreak Analysis and Modelling, Imperial College Faculty of Medicine, London, UK

Correspondence: Dr F Balloux, Department of Infectious Disease Epidemiology, MRC Centre for Outbreak Analysis and Modelling, Imperial College Faculty of Medicine, St Mary's Campus, Norfolk Place, London W2 1PG, UK. E-mail: fballoux@imperial.ac.uk; Dr A Manica, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK. E-mail: am315@cam.ac.uk

Received 7 April 2008; Revised 24 June 2008; Accepted 11 July 2008; Published online 3 September 2008.

Abstract

Our understanding of the distribution of worldwide human genomic diversity has greatly increased over recent years thanks to the availability of large data sets derived from short tandem repeats (STRs), insertion deletion polymorphisms (indels) and single nucleotide polymorphisms (SNPs). A concern, however, is that the current picture of worldwide human genomic diversity may be inaccurate because of biases in the selection process of genetic markers (so-called 'ascertainment bias'). To evaluate this problem, we first compared the distribution of genomic diversity between these three types of genetic markers in the populations from the HGDP-CEPH panel for evidence of bias or incongruities. In a second step, using a very relaxed set of criteria to prevent the intrusion of bias, we developed a new set of unbiased STR markers and compared the results against those from available panels. Contrarily to recent claims, our results show that the STR markers suffer from no discernible bias, and can thus be used as a baseline reference for human genetic diversity and population differentiation. The bias on SNPs is moderate compared to that on the set of indels analysed, which we recommend should be avoided for work describing the distribution of human genetic diversity or making inference on human settlement history.