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Open Access Highly Accessed Database

SNP@Evolution: a hierarchical database of positive selection on the human genome

Feng Cheng12, Wei Chen12, Elliott Richards34, Libin Deng15 and Changqing Zeng15*

Author Affiliations

1 Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, PR China

2 Graduate School of the Chinese Academy of Sciences, Beijing, PR China

3 Department of Biology, College of Life Sciences, Brigham Young University, Provo, UT, USA

4 Current address: Baylor College of Medicine, Houston, TX, USA

5 Current address: Medical College of Nanchang University, Nanchang, Jiangxi, PR China

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BMC Evolutionary Biology 2009, 9:221  doi:10.1186/1471-2148-9-221

Published: 5 September 2009

Abstract

Background

Positive selection is a driving force that has shaped the modern human. Recent developments in high throughput technologies and corresponding statistics tools have made it possible to conduct whole genome surveys at a population scale, and a variety of measurements, such as heterozygosity (HET), FST, and Tajima's D, have been applied to multiple datasets to identify signals of positive selection. However, great effort has been required to combine various types of data from individual sources, and incompatibility among datasets has been a common problem. SNP@Evolution, a new database which integrates multiple datasets, will greatly assist future work in this area.

Description

As part of our research scanning for evolutionary signals in HapMap Phase II and Phase III datasets, we built SNP@Evolution as a multi-aspect database focused on positive selection. Among its many features, SNP@Evolution provides computed FST and HET of all HapMap SNPs, 5+ HapMap SNPs per qualified gene, and all autosome regions detected from whole genome window scanning. In an attempt to capture multiple selection signals across the genome, selection-signal enrichment strength (ES) values of HET, FST, and P-values of iHS of most annotated genes have been calculated and integrated within one frame for users to search for outliers. Genes with significant ES or P-values (with thresholds of 0.95 and 0.05, respectively) have been highlighted in color. Low diversity chromosome regions have been detected by sliding a 100 kb window in a 10 kb step. To allow this information to be easily disseminated, a graphical user interface (GBrowser) was constructed with the Generic Model Organism Database toolkit.

Conclusion

Available at http://bighapmap.big.ac.cn webcite, SNP@Evolution is a hierarchical database focused on positive selection of the human genome. Based on HapMap Phase II and III data, SNP@Evolution includes 3,619,226/1,389,498 SNPs with their computed HET and FST, as well as qualified genes of 21,859/21,099 with ES values of HET and FST. In at least one HapMap population group, window scanning for selection signals has resulted in 1,606/10,138 large low HET regions. Among Phase II and III geographical groups, 660 and 464 regions show strong differentiation.