Published in

BMC, Genome Biology, 6(15), p. R88

DOI: 10.1186/gb-2014-15-6-r88



Export citation

Search in Google Scholar

Human genomic regions with exceptionally high levels of population differentiation identified from 911 whole-genome sequences

Journal article published in 2014 by M. von Grotthuss, W. Zhang, X. Zheng Bradley, J. Yu, F. Zhang, M. Zhang, G. del Angel, Y. Yin, Q. Zhang, J. Zhao, M. Zhao, Y. Zhang, X. Zheng, H. Zhang, Y. Zhou and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO


Abstract Background Population differentiation has proved to be effective for identifying loci under geographically localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes. Results We demonstrate that while sites with low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12 , CALD1 and ZNF804 , which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively. Conclusions We identify known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research.