A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq
Abstract The mouse has been widely used as a model organism for studying human diseases and for evaluating drug safety and efficacy. Many diseases and drug effects exhibit tissue specificity that may be reflected by tissue-specific gene-expression profiles. Here we construct a comprehensive mouse tr...
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Nature Portfolio
2017
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oai:doaj.org-article:c86c0d74c7b24470ac896a14ef43ac922021-12-02T16:06:38ZA Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq10.1038/s41598-017-04520-z2045-2322https://doaj.org/article/c86c0d74c7b24470ac896a14ef43ac922017-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-04520-zhttps://doaj.org/toc/2045-2322Abstract The mouse has been widely used as a model organism for studying human diseases and for evaluating drug safety and efficacy. Many diseases and drug effects exhibit tissue specificity that may be reflected by tissue-specific gene-expression profiles. Here we construct a comprehensive mouse transcriptomic BodyMap across 17 tissues of six-weeks old C57BL/6JJcl mice using RNA-seq. We find different expression patterns between protein-coding and non-coding genes. Liver expressed the least complex transcriptomes, that is, the smallest number of genes detected in liver across all 17 tissues, whereas testis and ovary harbor more complex transcriptomes than other tissues. We report a comprehensive list of tissue-specific genes across 17 tissues, along with a list of 4,781 housekeeping genes in mouse. In addition, we propose a list of 27 consistently and highly expressed genes that can be used as reference controls in expression-profiling analysis. Our study provides a unique resource of mouse gene-expression profiles, which is helpful for further biomedical research.Bin LiTao QingJinhang ZhuZhuo WenYing YuRyutaro FukumuraYuanting ZhengYoichi GondoLeming ShiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-10 (2017) |
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Medicine R Science Q Bin Li Tao Qing Jinhang Zhu Zhuo Wen Ying Yu Ryutaro Fukumura Yuanting Zheng Yoichi Gondo Leming Shi A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq |
description |
Abstract The mouse has been widely used as a model organism for studying human diseases and for evaluating drug safety and efficacy. Many diseases and drug effects exhibit tissue specificity that may be reflected by tissue-specific gene-expression profiles. Here we construct a comprehensive mouse transcriptomic BodyMap across 17 tissues of six-weeks old C57BL/6JJcl mice using RNA-seq. We find different expression patterns between protein-coding and non-coding genes. Liver expressed the least complex transcriptomes, that is, the smallest number of genes detected in liver across all 17 tissues, whereas testis and ovary harbor more complex transcriptomes than other tissues. We report a comprehensive list of tissue-specific genes across 17 tissues, along with a list of 4,781 housekeeping genes in mouse. In addition, we propose a list of 27 consistently and highly expressed genes that can be used as reference controls in expression-profiling analysis. Our study provides a unique resource of mouse gene-expression profiles, which is helpful for further biomedical research. |
format |
article |
author |
Bin Li Tao Qing Jinhang Zhu Zhuo Wen Ying Yu Ryutaro Fukumura Yuanting Zheng Yoichi Gondo Leming Shi |
author_facet |
Bin Li Tao Qing Jinhang Zhu Zhuo Wen Ying Yu Ryutaro Fukumura Yuanting Zheng Yoichi Gondo Leming Shi |
author_sort |
Bin Li |
title |
A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq |
title_short |
A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq |
title_full |
A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq |
title_fullStr |
A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq |
title_full_unstemmed |
A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq |
title_sort |
comprehensive mouse transcriptomic bodymap across 17 tissues by rna-seq |
publisher |
Nature Portfolio |
publishDate |
2017 |
url |
https://doaj.org/article/c86c0d74c7b24470ac896a14ef43ac92 |
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