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PLoS Genet. 2014 Aug 21;10(8):e1004561. doi: 10.1371/journal.pgen.1004561. eCollection 2014 Aug.

A model-based approach for identifying signatures of ancient balancing selection in genetic data.

Author information

1
Department of Biology, Pennsylvania State University, University Park, Pennsylvania, United States of America.
2
Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, United States of America.
3
Department of Integrative Biology, University of California, Berkeley, Berkeley, California, United States of America; Department of Statistics, University of California, Berkeley, Berkeley, California, United States of America; Department of Biology, University of Copenhagen, Copenhagen, Denmark.

Abstract

While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates.

PMID:
25144706
PMCID:
PMC4140648
DOI:
10.1371/journal.pgen.1004561
[Indexed for MEDLINE]
Free PMC Article
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