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Expression divergence measured by transcriptome sequencing of four yeast species
BACKGROUND: The evolution of gene expression is a challenging problem in evolutionary biology, for which accurate, well-calibrated measurements and methods are crucial. RESULTS: We quantified gene expression with whole-transcriptome sequencing in four diploid, prototrophic strains of Saccharomyces s...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3296765/ https://www.ncbi.nlm.nih.gov/pubmed/22206443 http://dx.doi.org/10.1186/1471-2164-12-635 |
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author | Busby, Michele A Gray, Jesse M Costa, Allen M Stewart, Chip Stromberg, Michael P Barnett, Derek Chuang, Jeffrey H Springer, Michael Marth, Gabor T |
author_facet | Busby, Michele A Gray, Jesse M Costa, Allen M Stewart, Chip Stromberg, Michael P Barnett, Derek Chuang, Jeffrey H Springer, Michael Marth, Gabor T |
author_sort | Busby, Michele A |
collection | PubMed |
description | BACKGROUND: The evolution of gene expression is a challenging problem in evolutionary biology, for which accurate, well-calibrated measurements and methods are crucial. RESULTS: We quantified gene expression with whole-transcriptome sequencing in four diploid, prototrophic strains of Saccharomyces species grown under the same condition to investigate the evolution of gene expression. We found that variation in expression is gene-dependent with large variations in each gene's expression between replicates of the same species. This confounds the identification of genes differentially expressed across species. To address this, we developed a statistical approach to establish significance bounds for inter-species differential expression in RNA-Seq data based on the variance measured across biological replicates. This metric estimates the combined effects of technical and environmental variance, as well as Poisson sampling noise by isolating each component. Despite a paucity of large expression changes, we found a strong correlation between the variance of gene expression change and species divergence (R(2 )= 0.90). CONCLUSION: We provide an improved methodology for measuring gene expression changes in evolutionary diverged species using RNA Seq, where experimental artifacts can mimic evolutionary effects. GEO Accession Number: GSE32679 |
format | Online Article Text |
id | pubmed-3296765 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32967652012-03-09 Expression divergence measured by transcriptome sequencing of four yeast species Busby, Michele A Gray, Jesse M Costa, Allen M Stewart, Chip Stromberg, Michael P Barnett, Derek Chuang, Jeffrey H Springer, Michael Marth, Gabor T BMC Genomics Research Article BACKGROUND: The evolution of gene expression is a challenging problem in evolutionary biology, for which accurate, well-calibrated measurements and methods are crucial. RESULTS: We quantified gene expression with whole-transcriptome sequencing in four diploid, prototrophic strains of Saccharomyces species grown under the same condition to investigate the evolution of gene expression. We found that variation in expression is gene-dependent with large variations in each gene's expression between replicates of the same species. This confounds the identification of genes differentially expressed across species. To address this, we developed a statistical approach to establish significance bounds for inter-species differential expression in RNA-Seq data based on the variance measured across biological replicates. This metric estimates the combined effects of technical and environmental variance, as well as Poisson sampling noise by isolating each component. Despite a paucity of large expression changes, we found a strong correlation between the variance of gene expression change and species divergence (R(2 )= 0.90). CONCLUSION: We provide an improved methodology for measuring gene expression changes in evolutionary diverged species using RNA Seq, where experimental artifacts can mimic evolutionary effects. GEO Accession Number: GSE32679 BioMed Central 2011-12-29 /pmc/articles/PMC3296765/ /pubmed/22206443 http://dx.doi.org/10.1186/1471-2164-12-635 Text en Copyright ©2011 Busby et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Busby, Michele A Gray, Jesse M Costa, Allen M Stewart, Chip Stromberg, Michael P Barnett, Derek Chuang, Jeffrey H Springer, Michael Marth, Gabor T Expression divergence measured by transcriptome sequencing of four yeast species |
title | Expression divergence measured by transcriptome sequencing of four yeast species |
title_full | Expression divergence measured by transcriptome sequencing of four yeast species |
title_fullStr | Expression divergence measured by transcriptome sequencing of four yeast species |
title_full_unstemmed | Expression divergence measured by transcriptome sequencing of four yeast species |
title_short | Expression divergence measured by transcriptome sequencing of four yeast species |
title_sort | expression divergence measured by transcriptome sequencing of four yeast species |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3296765/ https://www.ncbi.nlm.nih.gov/pubmed/22206443 http://dx.doi.org/10.1186/1471-2164-12-635 |
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