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Comparative genomics approaches accurately predict deleterious variants in plants

View ORCID ProfileThomas J.Y. Kono, Li Lei, Ching-Hua Shih, Paul J. Hoffman, Peter L. Morrell, Justin C. Fay
doi: https://doi.org/10.1101/112318
Thomas J.Y. Kono
1Department of Agronomy & Plant Genetics, University of Minnesota, St. Paul, MN 551085
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  • ORCID record for Thomas J.Y. Kono
Li Lei
1Department of Agronomy & Plant Genetics, University of Minnesota, St. Paul, MN 551085
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Ching-Hua Shih
2Department of Genetics, Washington University, St. Louis, MO 63110
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Paul J. Hoffman
1Department of Agronomy & Plant Genetics, University of Minnesota, St. Paul, MN 551085
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Peter L. Morrell
1Department of Agronomy & Plant Genetics, University of Minnesota, St. Paul, MN 551085
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  • For correspondence: fayjustin@gmail.com pmorrell@umn.edu
Justin C. Fay
2Department of Genetics, Washington University, St. Louis, MO 63110
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  • For correspondence: fayjustin@gmail.com pmorrell@umn.edu
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Abstract

Recent advances in genome resequencing have led to increased interest in prediction of the functional consequences of genetic variants. Variants at phylogenetically conserved sites are of particular interest, because they are more likely than variants at phylogenetically variable sites to have deleterious effects on fitness and contribute to phenotypic variation. Numerous comparative genomic approaches have been developed to predict deleterious variants, but they are nearly always judged based on their ability to identify known disease-causing mutations in humans. Determining the accuracy of deleterious variant predictions in nonhuman species is important to understanding evolution, domestication, and potentially to improving crop quality and yield. To examine our ability to predict deleterious variants in plants we generated a curated database of 2,910 Arabidopsis thaliana mutants with known phenotypes. We evaluated seven approaches and found that while all performed well, the single best-performing approach was a likelihood ratio test applied to homologs identified in 42 plant genomes. Although the approaches did not always agree, we found only slight differences in performance when comparing mutations with gross versus biochemical phenotypes, duplicated versus single copy genes, and when using a single approach versus ensemble predictions. We conclude that deleterious mutations can be reliably predicted in A. thaliana and likely other plant species, but that the relative performance of various approaches can depend on the organism to which they are applied.

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Posted February 27, 2017.
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Comparative genomics approaches accurately predict deleterious variants in plants
Thomas J.Y. Kono, Li Lei, Ching-Hua Shih, Paul J. Hoffman, Peter L. Morrell, Justin C. Fay
bioRxiv 112318; doi: https://doi.org/10.1101/112318
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Comparative genomics approaches accurately predict deleterious variants in plants
Thomas J.Y. Kono, Li Lei, Ching-Hua Shih, Paul J. Hoffman, Peter L. Morrell, Justin C. Fay
bioRxiv 112318; doi: https://doi.org/10.1101/112318

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