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Meta-analysis of RNA-seq expression data across species, tissues and studies

BACKGROUND: Differences in gene expression drive phenotypic differences between species, yet major organs and tissues generally have conserved gene expression programs. Several comparative transcriptomic studies have observed greater similarity in gene expression between homologous tissues from diff...

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Detalles Bibliográficos
Autores principales: Sudmant, Peter H., Alexis, Maria S., Burge, Christopher B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4699362/
https://www.ncbi.nlm.nih.gov/pubmed/26694591
http://dx.doi.org/10.1186/s13059-015-0853-4
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author Sudmant, Peter H.
Alexis, Maria S.
Burge, Christopher B.
author_facet Sudmant, Peter H.
Alexis, Maria S.
Burge, Christopher B.
author_sort Sudmant, Peter H.
collection PubMed
description BACKGROUND: Differences in gene expression drive phenotypic differences between species, yet major organs and tissues generally have conserved gene expression programs. Several comparative transcriptomic studies have observed greater similarity in gene expression between homologous tissues from different vertebrate species than between diverse tissues of the same species. However, a recent study by Lin and colleagues reached the opposite conclusion. These studies differed in the species and tissues analyzed, and in technical details of library preparation, sequencing, read mapping, normalization, gene sets, and clustering methods. RESULTS: To better understand gene expression evolution we reanalyzed data from four studies, including that of Lin, encompassing 6–13 tissues each from 11 vertebrate species using standardized mapping, normalization, and clustering methods. An analysis of independent data showed that the set of tissues chosen by Lin et al. were more similar to each other than those analyzed by previous studies. Comparing expression in five common tissues from the four studies, we observed that samples clustered exclusively by tissue rather than by species or study, supporting conservation of organ physiology in mammals. Furthermore, inter-study distances between homologous tissues were generally less than intra-study distances among different tissues, enabling informative meta-analyses. Notably, when comparing expression divergence of tissues over time to expression variation across 51 human GTEx tissues, we could accurately predict the clustering of expression for arbitrary pairs of tissues and species. CONCLUSIONS: These results provide a framework for the design of future evolutionary studies of gene expression and demonstrate the utility of comparing RNA-seq data across studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-015-0853-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-46993622016-01-05 Meta-analysis of RNA-seq expression data across species, tissues and studies Sudmant, Peter H. Alexis, Maria S. Burge, Christopher B. Genome Biol Research BACKGROUND: Differences in gene expression drive phenotypic differences between species, yet major organs and tissues generally have conserved gene expression programs. Several comparative transcriptomic studies have observed greater similarity in gene expression between homologous tissues from different vertebrate species than between diverse tissues of the same species. However, a recent study by Lin and colleagues reached the opposite conclusion. These studies differed in the species and tissues analyzed, and in technical details of library preparation, sequencing, read mapping, normalization, gene sets, and clustering methods. RESULTS: To better understand gene expression evolution we reanalyzed data from four studies, including that of Lin, encompassing 6–13 tissues each from 11 vertebrate species using standardized mapping, normalization, and clustering methods. An analysis of independent data showed that the set of tissues chosen by Lin et al. were more similar to each other than those analyzed by previous studies. Comparing expression in five common tissues from the four studies, we observed that samples clustered exclusively by tissue rather than by species or study, supporting conservation of organ physiology in mammals. Furthermore, inter-study distances between homologous tissues were generally less than intra-study distances among different tissues, enabling informative meta-analyses. Notably, when comparing expression divergence of tissues over time to expression variation across 51 human GTEx tissues, we could accurately predict the clustering of expression for arbitrary pairs of tissues and species. CONCLUSIONS: These results provide a framework for the design of future evolutionary studies of gene expression and demonstrate the utility of comparing RNA-seq data across studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-015-0853-4) contains supplementary material, which is available to authorized users. BioMed Central 2015-12-22 2015 /pmc/articles/PMC4699362/ /pubmed/26694591 http://dx.doi.org/10.1186/s13059-015-0853-4 Text en © Sudmant et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Sudmant, Peter H.
Alexis, Maria S.
Burge, Christopher B.
Meta-analysis of RNA-seq expression data across species, tissues and studies
title Meta-analysis of RNA-seq expression data across species, tissues and studies
title_full Meta-analysis of RNA-seq expression data across species, tissues and studies
title_fullStr Meta-analysis of RNA-seq expression data across species, tissues and studies
title_full_unstemmed Meta-analysis of RNA-seq expression data across species, tissues and studies
title_short Meta-analysis of RNA-seq expression data across species, tissues and studies
title_sort meta-analysis of rna-seq expression data across species, tissues and studies
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4699362/
https://www.ncbi.nlm.nih.gov/pubmed/26694591
http://dx.doi.org/10.1186/s13059-015-0853-4
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