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Generation and network analysis of an RNA-seq transcriptional atlas for the rat
The laboratory rat is an important model for biomedical research. To generate a comprehensive rat transcriptomic atlas, we curated and downloaded 7700 rat RNA-seq datasets from public repositories, downsampled them to a common depth and quantified expression. Data from 585 rat tissues and cells, ave...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8900154/ https://www.ncbi.nlm.nih.gov/pubmed/35265836 http://dx.doi.org/10.1093/nargab/lqac017 |
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author | Summers, Kim M Bush, Stephen J Wu, Chunlei Hume, David A |
author_facet | Summers, Kim M Bush, Stephen J Wu, Chunlei Hume, David A |
author_sort | Summers, Kim M |
collection | PubMed |
description | The laboratory rat is an important model for biomedical research. To generate a comprehensive rat transcriptomic atlas, we curated and downloaded 7700 rat RNA-seq datasets from public repositories, downsampled them to a common depth and quantified expression. Data from 585 rat tissues and cells, averaged from each BioProject, can be visualized and queried at http://biogps.org/ratatlas. Gene co-expression network (GCN) analysis revealed clusters of transcripts that were tissue or cell type restricted and contained transcription factors implicated in lineage determination. Other clusters were enriched for transcripts associated with biological processes. Many of these clusters overlap with previous data from analysis of other species, while some (e.g. expressed specifically in immune cells, retina/pineal gland, pituitary and germ cells) are unique to these data. GCN analysis on large subsets of the data related specifically to liver, nervous system, kidney, musculoskeletal system and cardiovascular system enabled deconvolution of cell type-specific signatures. The approach is extensible and the dataset can be used as a point of reference from which to analyse the transcriptomes of cell types and tissues that have not yet been sampled. Sets of strictly co-expressed transcripts provide a resource for critical interpretation of single-cell RNA-seq data. |
format | Online Article Text |
id | pubmed-8900154 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-89001542022-03-08 Generation and network analysis of an RNA-seq transcriptional atlas for the rat Summers, Kim M Bush, Stephen J Wu, Chunlei Hume, David A NAR Genom Bioinform Standard Article The laboratory rat is an important model for biomedical research. To generate a comprehensive rat transcriptomic atlas, we curated and downloaded 7700 rat RNA-seq datasets from public repositories, downsampled them to a common depth and quantified expression. Data from 585 rat tissues and cells, averaged from each BioProject, can be visualized and queried at http://biogps.org/ratatlas. Gene co-expression network (GCN) analysis revealed clusters of transcripts that were tissue or cell type restricted and contained transcription factors implicated in lineage determination. Other clusters were enriched for transcripts associated with biological processes. Many of these clusters overlap with previous data from analysis of other species, while some (e.g. expressed specifically in immune cells, retina/pineal gland, pituitary and germ cells) are unique to these data. GCN analysis on large subsets of the data related specifically to liver, nervous system, kidney, musculoskeletal system and cardiovascular system enabled deconvolution of cell type-specific signatures. The approach is extensible and the dataset can be used as a point of reference from which to analyse the transcriptomes of cell types and tissues that have not yet been sampled. Sets of strictly co-expressed transcripts provide a resource for critical interpretation of single-cell RNA-seq data. Oxford University Press 2022-03-07 /pmc/articles/PMC8900154/ /pubmed/35265836 http://dx.doi.org/10.1093/nargab/lqac017 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), 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 | Standard Article Summers, Kim M Bush, Stephen J Wu, Chunlei Hume, David A Generation and network analysis of an RNA-seq transcriptional atlas for the rat |
title | Generation and network analysis of an RNA-seq transcriptional atlas for the rat |
title_full | Generation and network analysis of an RNA-seq transcriptional atlas for the rat |
title_fullStr | Generation and network analysis of an RNA-seq transcriptional atlas for the rat |
title_full_unstemmed | Generation and network analysis of an RNA-seq transcriptional atlas for the rat |
title_short | Generation and network analysis of an RNA-seq transcriptional atlas for the rat |
title_sort | generation and network analysis of an rna-seq transcriptional atlas for the rat |
topic | Standard Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8900154/ https://www.ncbi.nlm.nih.gov/pubmed/35265836 http://dx.doi.org/10.1093/nargab/lqac017 |
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