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New Maximum Likelihood Estimators for Eukaryotic Intron Evolution

The evolution of spliceosomal introns remains poorly understood. Although many approaches have been used to infer intron evolution from the patterns of intron position conservation, the results to date have been contradictory. In this paper, we address the problem using a novel maximum likelihood me...

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Detalles Bibliográficos
Autores principales: Nguyen, Hung D, Yoshihama, Maki, Kenmochi, Naoya
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1323467/
https://www.ncbi.nlm.nih.gov/pubmed/16389300
http://dx.doi.org/10.1371/journal.pcbi.0010079
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author Nguyen, Hung D
Yoshihama, Maki
Kenmochi, Naoya
author_facet Nguyen, Hung D
Yoshihama, Maki
Kenmochi, Naoya
author_sort Nguyen, Hung D
collection PubMed
description The evolution of spliceosomal introns remains poorly understood. Although many approaches have been used to infer intron evolution from the patterns of intron position conservation, the results to date have been contradictory. In this paper, we address the problem using a novel maximum likelihood method, which allows estimation of the frequency of intron insertion target sites, together with the rates of intron gain and loss. We analyzed the pattern of 10,044 introns (7,221 intron positions) in the conserved regions of 684 sets of orthologs from seven eukaryotes. We determined that there is an average of one target site per 11.86 base pairs (bp) (95% confidence interval, 9.27 to 14.39 bp). In addition, our results showed that: (i) overall intron gains are ~25% greater than intron losses, although specific patterns vary with time and lineage; (ii) parallel gains account for ~18.5% of shared intron positions; and (iii) reacquisition following loss accounts for ~0.5% of all intron positions. Our results should assist in resolving the long-standing problem of inferring the evolution of spliceosomal introns.
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spelling pubmed-13234672005-12-30 New Maximum Likelihood Estimators for Eukaryotic Intron Evolution Nguyen, Hung D Yoshihama, Maki Kenmochi, Naoya PLoS Comput Biol Research Article The evolution of spliceosomal introns remains poorly understood. Although many approaches have been used to infer intron evolution from the patterns of intron position conservation, the results to date have been contradictory. In this paper, we address the problem using a novel maximum likelihood method, which allows estimation of the frequency of intron insertion target sites, together with the rates of intron gain and loss. We analyzed the pattern of 10,044 introns (7,221 intron positions) in the conserved regions of 684 sets of orthologs from seven eukaryotes. We determined that there is an average of one target site per 11.86 base pairs (bp) (95% confidence interval, 9.27 to 14.39 bp). In addition, our results showed that: (i) overall intron gains are ~25% greater than intron losses, although specific patterns vary with time and lineage; (ii) parallel gains account for ~18.5% of shared intron positions; and (iii) reacquisition following loss accounts for ~0.5% of all intron positions. Our results should assist in resolving the long-standing problem of inferring the evolution of spliceosomal introns. Public Library of Science 2005-12 2005-12-30 /pmc/articles/PMC1323467/ /pubmed/16389300 http://dx.doi.org/10.1371/journal.pcbi.0010079 Text en Copyright: © 2005 Nguyen 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
Nguyen, Hung D
Yoshihama, Maki
Kenmochi, Naoya
New Maximum Likelihood Estimators for Eukaryotic Intron Evolution
title New Maximum Likelihood Estimators for Eukaryotic Intron Evolution
title_full New Maximum Likelihood Estimators for Eukaryotic Intron Evolution
title_fullStr New Maximum Likelihood Estimators for Eukaryotic Intron Evolution
title_full_unstemmed New Maximum Likelihood Estimators for Eukaryotic Intron Evolution
title_short New Maximum Likelihood Estimators for Eukaryotic Intron Evolution
title_sort new maximum likelihood estimators for eukaryotic intron evolution
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1323467/
https://www.ncbi.nlm.nih.gov/pubmed/16389300
http://dx.doi.org/10.1371/journal.pcbi.0010079
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