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Phylogenomic Distance Method for Analyzing Transcriptome Evolution Based on RNA-seq Data

Thanks to the microarray technology, our understanding of transcriptome evolution at the genome level has been considerably advanced in the past decade. Yet, further investigation was challenged by several technical limitations of this technology. Recent innovation of next-generation sequencing, par...

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Autores principales: Gu, Xun, Zou, Yangyun, Huang, Wei, Shen, Libing, Arendsee, Zebulun, Su, Zhixi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3787673/
https://www.ncbi.nlm.nih.gov/pubmed/23940099
http://dx.doi.org/10.1093/gbe/evt121
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author Gu, Xun
Zou, Yangyun
Huang, Wei
Shen, Libing
Arendsee, Zebulun
Su, Zhixi
author_facet Gu, Xun
Zou, Yangyun
Huang, Wei
Shen, Libing
Arendsee, Zebulun
Su, Zhixi
author_sort Gu, Xun
collection PubMed
description Thanks to the microarray technology, our understanding of transcriptome evolution at the genome level has been considerably advanced in the past decade. Yet, further investigation was challenged by several technical limitations of this technology. Recent innovation of next-generation sequencing, particularly the invention of RNA-seq technology, has shed insightful lights on resolving this problem. Though a number of statistical and computational methods have been developed to analyze RNA-seq data, the analytical framework specifically designed for evolutionary genomics remains an open question. In this article we develop a new method for estimating the genome expression distance from the RNA-seq data, which has explicit interpretations under the model of gene expression evolution. Moreover, this distance measure takes the data overdispersion, gene length variation, and sequencing depth variation into account so that it can be applied to multiple genomes from different species. Using mammalian RNA-seq data as example, we demonstrated that this expression distance is useful in phylogenomic analysis.
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spelling pubmed-37876732013-10-17 Phylogenomic Distance Method for Analyzing Transcriptome Evolution Based on RNA-seq Data Gu, Xun Zou, Yangyun Huang, Wei Shen, Libing Arendsee, Zebulun Su, Zhixi Genome Biol Evol Research Article Thanks to the microarray technology, our understanding of transcriptome evolution at the genome level has been considerably advanced in the past decade. Yet, further investigation was challenged by several technical limitations of this technology. Recent innovation of next-generation sequencing, particularly the invention of RNA-seq technology, has shed insightful lights on resolving this problem. Though a number of statistical and computational methods have been developed to analyze RNA-seq data, the analytical framework specifically designed for evolutionary genomics remains an open question. In this article we develop a new method for estimating the genome expression distance from the RNA-seq data, which has explicit interpretations under the model of gene expression evolution. Moreover, this distance measure takes the data overdispersion, gene length variation, and sequencing depth variation into account so that it can be applied to multiple genomes from different species. Using mammalian RNA-seq data as example, we demonstrated that this expression distance is useful in phylogenomic analysis. Oxford University Press 2013 2013-08-11 /pmc/articles/PMC3787673/ /pubmed/23940099 http://dx.doi.org/10.1093/gbe/evt121 Text en © The Author(s) 2013. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Research Article
Gu, Xun
Zou, Yangyun
Huang, Wei
Shen, Libing
Arendsee, Zebulun
Su, Zhixi
Phylogenomic Distance Method for Analyzing Transcriptome Evolution Based on RNA-seq Data
title Phylogenomic Distance Method for Analyzing Transcriptome Evolution Based on RNA-seq Data
title_full Phylogenomic Distance Method for Analyzing Transcriptome Evolution Based on RNA-seq Data
title_fullStr Phylogenomic Distance Method for Analyzing Transcriptome Evolution Based on RNA-seq Data
title_full_unstemmed Phylogenomic Distance Method for Analyzing Transcriptome Evolution Based on RNA-seq Data
title_short Phylogenomic Distance Method for Analyzing Transcriptome Evolution Based on RNA-seq Data
title_sort phylogenomic distance method for analyzing transcriptome evolution based on rna-seq data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3787673/
https://www.ncbi.nlm.nih.gov/pubmed/23940099
http://dx.doi.org/10.1093/gbe/evt121
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