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Alu Exonization Events Reveal Features Required for Precise Recognition of Exons by the Splicing Machinery

Despite decades of research, the question of how the mRNA splicing machinery precisely identifies short exonic islands within the vast intronic oceans remains to a large extent obscure. In this study, we analyzed Alu exonization events, aiming to understand the requirements for correct selection of...

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Detalles Bibliográficos
Autores principales: Schwartz, Schraga, Gal-Mark, Nurit, Kfir, Nir, Oren, Ram, Kim, Eddo, Ast, Gil
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2639721/
https://www.ncbi.nlm.nih.gov/pubmed/19266014
http://dx.doi.org/10.1371/journal.pcbi.1000300
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author Schwartz, Schraga
Gal-Mark, Nurit
Kfir, Nir
Oren, Ram
Kim, Eddo
Ast, Gil
author_facet Schwartz, Schraga
Gal-Mark, Nurit
Kfir, Nir
Oren, Ram
Kim, Eddo
Ast, Gil
author_sort Schwartz, Schraga
collection PubMed
description Despite decades of research, the question of how the mRNA splicing machinery precisely identifies short exonic islands within the vast intronic oceans remains to a large extent obscure. In this study, we analyzed Alu exonization events, aiming to understand the requirements for correct selection of exons. Comparison of exonizing Alus to their non-exonizing counterparts is informative because Alus in these two groups have retained high sequence similarity but are perceived differently by the splicing machinery. We identified and characterized numerous features used by the splicing machinery to discriminate between Alu exons and their non-exonizing counterparts. Of these, the most novel is secondary structure: Alu exons in general and their 5′ splice sites (5′ss) in particular are characterized by decreased stability of local secondary structures with respect to their non-exonizing counterparts. We detected numerous further differences between Alu exons and their non-exonizing counterparts, among others in terms of exon–intron architecture and strength of splicing signals, enhancers, and silencers. Support vector machine analysis revealed that these features allow a high level of discrimination (AUC = 0.91) between exonizing and non-exonizing Alus. Moreover, the computationally derived probabilities of exonization significantly correlated with the biological inclusion level of the Alu exons, and the model could also be extended to general datasets of constitutive and alternative exons. This indicates that the features detected and explored in this study provide the basis not only for precise exon selection but also for the fine-tuned regulation thereof, manifested in cases of alternative splicing.
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spelling pubmed-26397212009-03-06 Alu Exonization Events Reveal Features Required for Precise Recognition of Exons by the Splicing Machinery Schwartz, Schraga Gal-Mark, Nurit Kfir, Nir Oren, Ram Kim, Eddo Ast, Gil PLoS Comput Biol Research Article Despite decades of research, the question of how the mRNA splicing machinery precisely identifies short exonic islands within the vast intronic oceans remains to a large extent obscure. In this study, we analyzed Alu exonization events, aiming to understand the requirements for correct selection of exons. Comparison of exonizing Alus to their non-exonizing counterparts is informative because Alus in these two groups have retained high sequence similarity but are perceived differently by the splicing machinery. We identified and characterized numerous features used by the splicing machinery to discriminate between Alu exons and their non-exonizing counterparts. Of these, the most novel is secondary structure: Alu exons in general and their 5′ splice sites (5′ss) in particular are characterized by decreased stability of local secondary structures with respect to their non-exonizing counterparts. We detected numerous further differences between Alu exons and their non-exonizing counterparts, among others in terms of exon–intron architecture and strength of splicing signals, enhancers, and silencers. Support vector machine analysis revealed that these features allow a high level of discrimination (AUC = 0.91) between exonizing and non-exonizing Alus. Moreover, the computationally derived probabilities of exonization significantly correlated with the biological inclusion level of the Alu exons, and the model could also be extended to general datasets of constitutive and alternative exons. This indicates that the features detected and explored in this study provide the basis not only for precise exon selection but also for the fine-tuned regulation thereof, manifested in cases of alternative splicing. Public Library of Science 2009-03-06 /pmc/articles/PMC2639721/ /pubmed/19266014 http://dx.doi.org/10.1371/journal.pcbi.1000300 Text en Schwartz et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Schwartz, Schraga
Gal-Mark, Nurit
Kfir, Nir
Oren, Ram
Kim, Eddo
Ast, Gil
Alu Exonization Events Reveal Features Required for Precise Recognition of Exons by the Splicing Machinery
title Alu Exonization Events Reveal Features Required for Precise Recognition of Exons by the Splicing Machinery
title_full Alu Exonization Events Reveal Features Required for Precise Recognition of Exons by the Splicing Machinery
title_fullStr Alu Exonization Events Reveal Features Required for Precise Recognition of Exons by the Splicing Machinery
title_full_unstemmed Alu Exonization Events Reveal Features Required for Precise Recognition of Exons by the Splicing Machinery
title_short Alu Exonization Events Reveal Features Required for Precise Recognition of Exons by the Splicing Machinery
title_sort alu exonization events reveal features required for precise recognition of exons by the splicing machinery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2639721/
https://www.ncbi.nlm.nih.gov/pubmed/19266014
http://dx.doi.org/10.1371/journal.pcbi.1000300
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