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Correcting for Differential Transcript Coverage Reveals a Strong Relationship between Alternative Splicing and Organism Complexity

What at the genomic level underlies organism complexity? Although several genomic features have been associated with organism complexity, in the case of alternative splicing, which has long been proposed to explain the variation in complexity, no such link has been established. Here, we analyzed ove...

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Autores principales: Chen, Lu, Bush, Stephen J., Tovar-Corona, Jaime M., Castillo-Morales, Atahualpa, Urrutia, Araxi O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4032128/
https://www.ncbi.nlm.nih.gov/pubmed/24682283
http://dx.doi.org/10.1093/molbev/msu083
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author Chen, Lu
Bush, Stephen J.
Tovar-Corona, Jaime M.
Castillo-Morales, Atahualpa
Urrutia, Araxi O.
author_facet Chen, Lu
Bush, Stephen J.
Tovar-Corona, Jaime M.
Castillo-Morales, Atahualpa
Urrutia, Araxi O.
author_sort Chen, Lu
collection PubMed
description What at the genomic level underlies organism complexity? Although several genomic features have been associated with organism complexity, in the case of alternative splicing, which has long been proposed to explain the variation in complexity, no such link has been established. Here, we analyzed over 39 million expressed sequence tags available for 47 eukaryotic species with fully sequenced genomes to obtain a comparable index of alternative splicing estimates, which corrects for the distorting effect of a variable number of transcripts per species—an important obstacle for comparative studies of alternative splicing. We find that alternative splicing has steadily increased over the last 1,400 My of eukaryotic evolution and is strongly associated with organism complexity, assayed as the number of cell types. Importantly, this association is not explained as a by-product of covariance between alternative splicing with other variables previously linked to complexity including gene content, protein length, proteome disorder, and protein interactivity. In addition, we found no evidence to suggest that the relationship of alternative splicing to cell type number is explained by drift due to reduced N(e) in more complex species. Taken together, our results firmly establish alternative splicing as a significant predictor of organism complexity and are, in principle, consistent with an important role of transcript diversification through alternative splicing as a means of determining a genome’s functional information capacity.
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spelling pubmed-40321282014-06-18 Correcting for Differential Transcript Coverage Reveals a Strong Relationship between Alternative Splicing and Organism Complexity Chen, Lu Bush, Stephen J. Tovar-Corona, Jaime M. Castillo-Morales, Atahualpa Urrutia, Araxi O. Mol Biol Evol Discoveries What at the genomic level underlies organism complexity? Although several genomic features have been associated with organism complexity, in the case of alternative splicing, which has long been proposed to explain the variation in complexity, no such link has been established. Here, we analyzed over 39 million expressed sequence tags available for 47 eukaryotic species with fully sequenced genomes to obtain a comparable index of alternative splicing estimates, which corrects for the distorting effect of a variable number of transcripts per species—an important obstacle for comparative studies of alternative splicing. We find that alternative splicing has steadily increased over the last 1,400 My of eukaryotic evolution and is strongly associated with organism complexity, assayed as the number of cell types. Importantly, this association is not explained as a by-product of covariance between alternative splicing with other variables previously linked to complexity including gene content, protein length, proteome disorder, and protein interactivity. In addition, we found no evidence to suggest that the relationship of alternative splicing to cell type number is explained by drift due to reduced N(e) in more complex species. Taken together, our results firmly establish alternative splicing as a significant predictor of organism complexity and are, in principle, consistent with an important role of transcript diversification through alternative splicing as a means of determining a genome’s functional information capacity. Oxford University Press 2014-06 2014-03-27 /pmc/articles/PMC4032128/ /pubmed/24682283 http://dx.doi.org/10.1093/molbev/msu083 Text en © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Discoveries
Chen, Lu
Bush, Stephen J.
Tovar-Corona, Jaime M.
Castillo-Morales, Atahualpa
Urrutia, Araxi O.
Correcting for Differential Transcript Coverage Reveals a Strong Relationship between Alternative Splicing and Organism Complexity
title Correcting for Differential Transcript Coverage Reveals a Strong Relationship between Alternative Splicing and Organism Complexity
title_full Correcting for Differential Transcript Coverage Reveals a Strong Relationship between Alternative Splicing and Organism Complexity
title_fullStr Correcting for Differential Transcript Coverage Reveals a Strong Relationship between Alternative Splicing and Organism Complexity
title_full_unstemmed Correcting for Differential Transcript Coverage Reveals a Strong Relationship between Alternative Splicing and Organism Complexity
title_short Correcting for Differential Transcript Coverage Reveals a Strong Relationship between Alternative Splicing and Organism Complexity
title_sort correcting for differential transcript coverage reveals a strong relationship between alternative splicing and organism complexity
topic Discoveries
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4032128/
https://www.ncbi.nlm.nih.gov/pubmed/24682283
http://dx.doi.org/10.1093/molbev/msu083
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