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De novo mutational profile in RB1 clarified using a mutation rate modeling algorithm

BACKGROUND: Studies of de novo mutations offer great promise to improve our understanding of human disease. After a causal gene has been identified, it is natural to hypothesize that disease relevant mutations accumulate within a sub-sequence of the gene – for example, an exon, a protein domain, or...

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Autores principales: Aggarwala, Varun, Ganguly, Arupa, Voight, Benjamin F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5307739/
https://www.ncbi.nlm.nih.gov/pubmed/28193182
http://dx.doi.org/10.1186/s12864-017-3522-z
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author Aggarwala, Varun
Ganguly, Arupa
Voight, Benjamin F.
author_facet Aggarwala, Varun
Ganguly, Arupa
Voight, Benjamin F.
author_sort Aggarwala, Varun
collection PubMed
description BACKGROUND: Studies of de novo mutations offer great promise to improve our understanding of human disease. After a causal gene has been identified, it is natural to hypothesize that disease relevant mutations accumulate within a sub-sequence of the gene – for example, an exon, a protein domain, or at CpG sites. These assessments are typically qualitative, because we lack methodology to assess the statistical significance of sub-gene mutational burden ultimately to infer disease-relevant biology. METHODS: To address this issue, we present a generalized algorithm to grade the significance of de novo mutational burden within a gene ascertained from affected probands, based on our model for mutation rate informed by local sequence context. RESULTS: We applied our approach to 268 newly identified de novo germline mutations by re-sequencing the coding exons and flanking intronic regions of RB1 in 642 sporadic, bilateral probands affected with retinoblastoma (RB). We confirm enrichment of loss-of-function mutations, but demonstrate that previously noted ‘hotspots’ of nonsense mutations in RB1 are compatible with the elevated mutation rates expected at CpG sites, refuting a RB specific pathogenic mechanism. Our approach demonstrates an enrichment of splice-site donor mutations of exon 6 and 12 but depletion at exon 5, indicative of previously unappreciated heterogeneity in penetrance within this class of substitution. We demonstrate the enrichment of missense mutations to the pocket domain of RB1, which contains the known Arg661Trp low-penetrance mutation. CONCLUSION: Our approach is generalizable to any phenotype, and affirms the importance of statistical interpretation of de novo mutations found in human genomes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3522-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-53077392017-02-22 De novo mutational profile in RB1 clarified using a mutation rate modeling algorithm Aggarwala, Varun Ganguly, Arupa Voight, Benjamin F. BMC Genomics Research Article BACKGROUND: Studies of de novo mutations offer great promise to improve our understanding of human disease. After a causal gene has been identified, it is natural to hypothesize that disease relevant mutations accumulate within a sub-sequence of the gene – for example, an exon, a protein domain, or at CpG sites. These assessments are typically qualitative, because we lack methodology to assess the statistical significance of sub-gene mutational burden ultimately to infer disease-relevant biology. METHODS: To address this issue, we present a generalized algorithm to grade the significance of de novo mutational burden within a gene ascertained from affected probands, based on our model for mutation rate informed by local sequence context. RESULTS: We applied our approach to 268 newly identified de novo germline mutations by re-sequencing the coding exons and flanking intronic regions of RB1 in 642 sporadic, bilateral probands affected with retinoblastoma (RB). We confirm enrichment of loss-of-function mutations, but demonstrate that previously noted ‘hotspots’ of nonsense mutations in RB1 are compatible with the elevated mutation rates expected at CpG sites, refuting a RB specific pathogenic mechanism. Our approach demonstrates an enrichment of splice-site donor mutations of exon 6 and 12 but depletion at exon 5, indicative of previously unappreciated heterogeneity in penetrance within this class of substitution. We demonstrate the enrichment of missense mutations to the pocket domain of RB1, which contains the known Arg661Trp low-penetrance mutation. CONCLUSION: Our approach is generalizable to any phenotype, and affirms the importance of statistical interpretation of de novo mutations found in human genomes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3522-z) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-14 /pmc/articles/PMC5307739/ /pubmed/28193182 http://dx.doi.org/10.1186/s12864-017-3522-z Text en © The Author(s). 2017 Open AccessThis article is 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 you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Aggarwala, Varun
Ganguly, Arupa
Voight, Benjamin F.
De novo mutational profile in RB1 clarified using a mutation rate modeling algorithm
title De novo mutational profile in RB1 clarified using a mutation rate modeling algorithm
title_full De novo mutational profile in RB1 clarified using a mutation rate modeling algorithm
title_fullStr De novo mutational profile in RB1 clarified using a mutation rate modeling algorithm
title_full_unstemmed De novo mutational profile in RB1 clarified using a mutation rate modeling algorithm
title_short De novo mutational profile in RB1 clarified using a mutation rate modeling algorithm
title_sort de novo mutational profile in rb1 clarified using a mutation rate modeling algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5307739/
https://www.ncbi.nlm.nih.gov/pubmed/28193182
http://dx.doi.org/10.1186/s12864-017-3522-z
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