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Comparative Genomics Approaches Accurately Predict Deleterious Variants in Plants
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 delet...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Genetics Society of America
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6169392/ https://www.ncbi.nlm.nih.gov/pubmed/30139765 http://dx.doi.org/10.1534/g3.118.200563 |
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author | Kono, Thomas J.Y. Lei, Li Shih, Ching-Hua Hoffman, Paul J. Morrell, Peter L. Fay, Justin C. |
author_facet | Kono, Thomas J.Y. Lei, Li Shih, Ching-Hua Hoffman, Paul J. Morrell, Peter L. Fay, Justin C. |
author_sort | Kono, Thomas J.Y. |
collection | PubMed |
description | 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 the approaches are nearly always assessed 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, their relative ranking differed from prior benchmarks in humans. 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 does not necessarily translate from one species to another. |
format | Online Article Text |
id | pubmed-6169392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Genetics Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-61693922018-10-04 Comparative Genomics Approaches Accurately Predict Deleterious Variants in Plants Kono, Thomas J.Y. Lei, Li Shih, Ching-Hua Hoffman, Paul J. Morrell, Peter L. Fay, Justin C. G3 (Bethesda) Investigations 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 the approaches are nearly always assessed 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, their relative ranking differed from prior benchmarks in humans. 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 does not necessarily translate from one species to another. Genetics Society of America 2018-08-29 /pmc/articles/PMC6169392/ /pubmed/30139765 http://dx.doi.org/10.1534/g3.118.200563 Text en Copyright © 2018 Kono et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Investigations Kono, Thomas J.Y. Lei, Li Shih, Ching-Hua Hoffman, Paul J. Morrell, Peter L. Fay, Justin C. Comparative Genomics Approaches Accurately Predict Deleterious Variants in Plants |
title | Comparative Genomics Approaches Accurately Predict Deleterious Variants in Plants |
title_full | Comparative Genomics Approaches Accurately Predict Deleterious Variants in Plants |
title_fullStr | Comparative Genomics Approaches Accurately Predict Deleterious Variants in Plants |
title_full_unstemmed | Comparative Genomics Approaches Accurately Predict Deleterious Variants in Plants |
title_short | Comparative Genomics Approaches Accurately Predict Deleterious Variants in Plants |
title_sort | comparative genomics approaches accurately predict deleterious variants in plants |
topic | Investigations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6169392/ https://www.ncbi.nlm.nih.gov/pubmed/30139765 http://dx.doi.org/10.1534/g3.118.200563 |
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