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Evolutionary diagnosis method for variants in personal exomes

Nature Methods volume 9, pages 855–856 (2012)Cite this article

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Each human exome contains thousands of nonsynonymous single-nucleotide variants (nSNVs) that have unknown biological effects. The potential impact of nSNVs on biological function is now routinely assessed using computational methods for application in biomedical research and clinical genome profiling reports. Of the variants receiving a non-neutral (function-damaging) prediction, those at evolutionarily conserved sites are frequently of heightened interest for scientists and clinicians because such sites are among the most critical for proper protein function. Indeed, a majority of amino acid mutations that have been investigated experimentally are located at ultraconserved sites1, which show no amino acid residue difference among diverse species spanning over 500 million years of evolution (Supplementary Fig. 1). Functionally damaging mutants at these sites are likely to have significant consequences for health and disease.

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Figure 1: Performance and application of the EvoD method.

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Acknowledgements

We thank N. Gerek, C. Hepp and M. Champion for insightful comments and J. Akey for providing the 5,400 exomes data. C. Williams provided editorial support. This research was supported by a research grant from the National Library of Medicine (R01 LM010834) and a Postbaccalaureate Research Education Program grant (R25 GM071798) from the US National Institutes of Health.

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Authors and Affiliations

  1. Center for Evolutionary Medicine and Informatics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA

    Sudhir Kumar, Maxwell Sanderford, Vanessa E Gray, Jieping Ye & Li Liu

  2. School of Life Sciences, Arizona State University, Tempe, Arizona, USA

    Sudhir Kumar

  3. School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, Arizona, USA

    Jieping Ye

Authors
  1. Sudhir Kumar
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  2. Maxwell Sanderford
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  3. Vanessa E Gray
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  4. Jieping Ye
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  5. Li Liu
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Corresponding author

Correspondence to Sudhir Kumar.

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The authors declare no competing financial interests.

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Supplementary Text and Figures

Supplementary Figures 1–5, Supplementary Table 1 and Supplementary Methods (PDF 672 kb)

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Kumar, S., Sanderford, M., Gray, V. et al. Evolutionary diagnosis method for variants in personal exomes. Nat Methods 9, 855–856 (2012). https://doi.org/10.1038/nmeth.2147

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