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Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing
Splicing is highly regulated and is modulated by numerous factors. Quantitative predictions for how a mutation will affect precursor mRNA (pre-mRNA) structure and downstream function are particularly challenging. Here, we use a novel chemical probing strategy to visualize endogenous precursor and ma...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9236610/ https://www.ncbi.nlm.nih.gov/pubmed/35695373 http://dx.doi.org/10.7554/eLife.73888 |
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author | Kumar, Jayashree Lackey, Lela Waldern, Justin M Dey, Abhishek Mustoe, Anthony M Weeks, Kevin M Mathews, David H Laederach, Alain |
author_facet | Kumar, Jayashree Lackey, Lela Waldern, Justin M Dey, Abhishek Mustoe, Anthony M Weeks, Kevin M Mathews, David H Laederach, Alain |
author_sort | Kumar, Jayashree |
collection | PubMed |
description | Splicing is highly regulated and is modulated by numerous factors. Quantitative predictions for how a mutation will affect precursor mRNA (pre-mRNA) structure and downstream function are particularly challenging. Here, we use a novel chemical probing strategy to visualize endogenous precursor and mature MAPT mRNA structures in cells. We used these data to estimate Boltzmann suboptimal structural ensembles, which were then analyzed to predict consequences of mutations on pre-mRNA structure. Further analysis of recent cryo-EM structures of the spliceosome at different stages of the splicing cycle revealed that the footprint of the B(act) complex with pre-mRNA best predicted alternative splicing outcomes for exon 10 inclusion of the alternatively spliced MAPT gene, achieving 74% accuracy. We further developed a β-regression weighting framework that incorporates splice site strength, RNA structure, and exonic/intronic splicing regulatory elements capable of predicting, with 90% accuracy, the effects of 47 known and 6 newly discovered mutations on inclusion of exon 10 of MAPT. This combined experimental and computational framework represents a path forward for accurate prediction of splicing-related disease-causing variants. |
format | Online Article Text |
id | pubmed-9236610 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-92366102022-06-28 Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing Kumar, Jayashree Lackey, Lela Waldern, Justin M Dey, Abhishek Mustoe, Anthony M Weeks, Kevin M Mathews, David H Laederach, Alain eLife Computational and Systems Biology Splicing is highly regulated and is modulated by numerous factors. Quantitative predictions for how a mutation will affect precursor mRNA (pre-mRNA) structure and downstream function are particularly challenging. Here, we use a novel chemical probing strategy to visualize endogenous precursor and mature MAPT mRNA structures in cells. We used these data to estimate Boltzmann suboptimal structural ensembles, which were then analyzed to predict consequences of mutations on pre-mRNA structure. Further analysis of recent cryo-EM structures of the spliceosome at different stages of the splicing cycle revealed that the footprint of the B(act) complex with pre-mRNA best predicted alternative splicing outcomes for exon 10 inclusion of the alternatively spliced MAPT gene, achieving 74% accuracy. We further developed a β-regression weighting framework that incorporates splice site strength, RNA structure, and exonic/intronic splicing regulatory elements capable of predicting, with 90% accuracy, the effects of 47 known and 6 newly discovered mutations on inclusion of exon 10 of MAPT. This combined experimental and computational framework represents a path forward for accurate prediction of splicing-related disease-causing variants. eLife Sciences Publications, Ltd 2022-06-13 /pmc/articles/PMC9236610/ /pubmed/35695373 http://dx.doi.org/10.7554/eLife.73888 Text en © 2022, Kumar et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Computational and Systems Biology Kumar, Jayashree Lackey, Lela Waldern, Justin M Dey, Abhishek Mustoe, Anthony M Weeks, Kevin M Mathews, David H Laederach, Alain Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing |
title | Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing |
title_full | Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing |
title_fullStr | Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing |
title_full_unstemmed | Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing |
title_short | Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing |
title_sort | quantitative prediction of variant effects on alternative splicing in mapt using endogenous pre-messenger rna structure probing |
topic | Computational and Systems Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9236610/ https://www.ncbi.nlm.nih.gov/pubmed/35695373 http://dx.doi.org/10.7554/eLife.73888 |
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