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Stochastic noise in splicing machinery

The number of known alternative human isoforms has been increasing steadily with the amount of available transcription data. To date, over 100 000 isoforms have been detected in EST libraries, and at least 75% of human genes have at least one alternative isoform. In this paper, we propose that most...

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Detalles Bibliográficos
Autores principales: Melamud, Eugene, Moult, John
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2724286/
https://www.ncbi.nlm.nih.gov/pubmed/19546110
http://dx.doi.org/10.1093/nar/gkp471
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author Melamud, Eugene
Moult, John
author_facet Melamud, Eugene
Moult, John
author_sort Melamud, Eugene
collection PubMed
description The number of known alternative human isoforms has been increasing steadily with the amount of available transcription data. To date, over 100 000 isoforms have been detected in EST libraries, and at least 75% of human genes have at least one alternative isoform. In this paper, we propose that most alternative splicing events are the result of noise in the splicing process. We show that the number of isoforms and their abundance can be predicted by a simple stochastic noise model that takes into account two factors: the number of introns in a gene and the expression level of a gene. The results strongly support the hypothesis that most alternative splicing is a consequence of stochastic noise in the splicing machinery, and has no functional significance. The results are also consistent with error rates tuned to ensure that an adequate level of functional product is produced and to reduce the toxic effect of accumulation of misfolding proteins. Based on simulation of sampling of virtual cDNA libraries, we estimate that error rates range from 1 to 10% depending on the number of introns and the expression level of a gene.
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spelling pubmed-27242862009-08-18 Stochastic noise in splicing machinery Melamud, Eugene Moult, John Nucleic Acids Res Computational Biology The number of known alternative human isoforms has been increasing steadily with the amount of available transcription data. To date, over 100 000 isoforms have been detected in EST libraries, and at least 75% of human genes have at least one alternative isoform. In this paper, we propose that most alternative splicing events are the result of noise in the splicing process. We show that the number of isoforms and their abundance can be predicted by a simple stochastic noise model that takes into account two factors: the number of introns in a gene and the expression level of a gene. The results strongly support the hypothesis that most alternative splicing is a consequence of stochastic noise in the splicing machinery, and has no functional significance. The results are also consistent with error rates tuned to ensure that an adequate level of functional product is produced and to reduce the toxic effect of accumulation of misfolding proteins. Based on simulation of sampling of virtual cDNA libraries, we estimate that error rates range from 1 to 10% depending on the number of introns and the expression level of a gene. Oxford University Press 2009-08 2009-06-22 /pmc/articles/PMC2724286/ /pubmed/19546110 http://dx.doi.org/10.1093/nar/gkp471 Text en © 2009 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Melamud, Eugene
Moult, John
Stochastic noise in splicing machinery
title Stochastic noise in splicing machinery
title_full Stochastic noise in splicing machinery
title_fullStr Stochastic noise in splicing machinery
title_full_unstemmed Stochastic noise in splicing machinery
title_short Stochastic noise in splicing machinery
title_sort stochastic noise in splicing machinery
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2724286/
https://www.ncbi.nlm.nih.gov/pubmed/19546110
http://dx.doi.org/10.1093/nar/gkp471
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