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Genome-wide inference of natural selection on human transcription factor binding sites

Nature Genetics volume 45, pages 723–729 (2013)Cite this article

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Abstract

For decades, it has been hypothesized that gene regulation has had a central role in human evolution, yet much remains unknown about the genome-wide impact of regulatory mutations. Here we use whole-genome sequences and genome-wide chromatin immunoprecipitation and sequencing data to demonstrate that natural selection has profoundly influenced human transcription factor binding sites since the divergence of humans from chimpanzees 4–6 million years ago. Our analysis uses a new probabilistic method, called INSIGHT, for measuring the influence of selection on collections of short, interspersed noncoding elements. We find that, on average, transcription factor binding sites have experienced somewhat weaker selection than protein-coding genes. However, the binding sites of several transcription factors show clear evidence of adaptation. Several measures of selection are strongly correlated with predicted binding affinity. Overall, regulatory elements seem to contribute substantially to both adaptive substitutions and deleterious polymorphisms with key implications for human evolution and disease.

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Figure 1: Results for data sets simulated under three different mixtures of selective modes.
Figure 2: Estimates of key parameters for the binding sites of each transcription factor in our study.
Figure 3: Information content, binding affinity and selection.
Figure 4: Genome-wide analyses of adaptive and deleterious mutations in protein-coding sequences and transcription factor binding sites.

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Acknowledgements

We thank R. Blekhman, C. Danko, A. Boyko, K. Pollard, N. Goldman and A. Clark for comments on the manuscript. This research was supported by a Packard Fellowship, a Sloan Research Fellowship, US National Science Foundation grant DBI-0644111 and US National Institutes of Health (National Institute of General Medical Sciences, NIGMS) grant GM102192 (to A.S.). In addition, L.A. was supported in part by a postdoctoral fellowship award from the Cornell Center for Vertebrate Genomics, and B.A.A. was supported by US National Institutes of Health training grant T32-GM083937.

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Authors and Affiliations

  1. Department of Biological Statistics & Computational Biology, Cornell University, Ithaca, New York, USA

    Leonardo Arbiza, Ilan Gronau, Melissa J Hubisz, Alon Keinan & Adam Siepel

  2. Tri-Institutional Training Program in Computational Biology & Medicine, New York, New York, USA

    Bulent A Aksoy, Alon Keinan & Adam Siepel

  3. Graduate Field of Computer Science, Cornell University, Ithaca, New York, USA

    Brad Gulko, Alon Keinan & Adam Siepel

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  1. Leonardo Arbiza
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Contributions

L.A., I.G. and A.S. conceived and designed the study. L.A., I.G., B.A.A., M.J.H., B.G. and A.S. analyzed the data. L.A., I.G., B.A.A. and M.J.H. contributed materials and analysis tools. A.S. and A.K. supervised the research. L.A., I.G. and A.S. wrote the manuscript with review and contributions from all authors.

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Correspondence to Adam Siepel.

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Arbiza, L., Gronau, I., Aksoy, B. et al. Genome-wide inference of natural selection on human transcription factor binding sites. Nat Genet 45, 723–729 (2013). https://doi.org/10.1038/ng.2658

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