Cited by 189Gene expression and cancer classificationGenomics and Phylogenetic StudiesSingle-cell and spatial transcriptomics

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A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq

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Li, Bin, Qing, Tao, Zhu, Jinhang, Wen, Zhuo, Yu, Ying, Fukumura, Ryutaro, Zheng, Yuanting, Gondo, Yoichi, Shi, Leming·2017·Scientific Reports

DOI 10.1038/s41598-017-04520-zPMC PMC5482823

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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.

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Figure 1 Landscape of the mouse transcriptome. (a) Percentage of expressed (red, FPKM > = 0.1 in at least one sample) and non-expressed (blue, FPKM < 0.1 across all samples) genes by different gene types. PCGs: protein-coding genes; ncRNA: non-coding RNA genes; Others: other genes except PCGs, ncRNA, and pseudogenes. (b) Number of expressed (FPKM > 0.1) genes by tissues. Numbers were averaged over all biological samples for a given tissue. (c) Hierarchical clustering analysis of gene expression profiles of 68 samples with 31,687 genes. Each column indicated a sample, whereas each row indicated a gene. Each tissue symbol was shown upon the color bar for each cluster. The mouse information where each sample came from was also labeled upon the color bar. Mouse 1 and Mouse 2 were two male mice (in blue text), while Mouse 3 and Mouse 4 were two female mice (in red text) as shown in Table 1.CC BY · PubMed Central

Figure 2 Tissue-dependent differentially expressed genes. (a) Number of differentially expressed genes (FDR < 0.05, fold change >2 or <0.5) for each pairwise organs. For each tissue in each column, the figures indicated the numbers of down-regulated genes comparing this tissue to the other tissues. For each tissue in each row, the figures indicated the numbers of up-regulated genes comparing this tissue to the other tissues. The tissues are in the same order as in Fig. 1c. (b) Expression profiles of 5,035 tissue-specific genes across 68 samples were arranged by tissue types (in decreasing order based on the number of organ-enriched genes). Testis expressed the most tissue-specific genes among all tissues.CC BY · PubMed Central

Figure 3 4,781 genes were identified as mouse candidate housekeeping genes. (a) Chromosome distribution of the 4,781 housekeeping genes. The exact number for each chromosome was highlighted in blue figure. Upper panel: the absolute number of housekeeping genes identified on each chromosome; lower panel: percentage of housekeeping genes on each chromosome (divided by the total number of genes on each chromosome). (b) 2,608 genes were both identified as housekeeping genes in mouse (our study, red circle) and human (Eisenberg’s study, blue circle). (c) Expression profiles of the 4,781 genes by groups. Red: genes also identified as housekeeping genes in human; Green: genes not identified in human. (d) Expression of four well-known housekeeping genes (Gapdh, Actb, Hprt, and B2m). Only Hprt was found in our list of housekeeping genes.CC BY · PubMed Central

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Additional file 9 of Integrated analysis of the ubiquitination mechanism reveals the specific signatures of tissue and cancer
Long, D., Zhang, R., Du, C., Tong, J., Ni, Y., Zhou, Y., Zuo, Y., & Liao, M. (2023) · Figshare · doi:10.6084/m9.figshare.24089174
Additional file 4 of Integrated analysis of the ubiquitination mechanism reveals the specific signatures of tissue and cancer
Long, D., Zhang, R., Du, C., Tong, J., Ni, Y., Zhou, Y., Zuo, Y., & Liao, M. (2023) · Figshare · doi:10.6084/m9.figshare.24089153
Additional file 2 of Integrated analysis of the ubiquitination mechanism reveals the specific signatures of tissue and cancer
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Additional file 10 of Integrated analysis of the ubiquitination mechanism reveals the specific signatures of tissue and cancer
Long, D., Zhang, R., Du, C., Tong, J., Ni, Y., Zhou, Y., Zuo, Y., & Liao, M. (2023) · Figshare · doi:10.6084/m9.figshare.24089177
Additional file 7 of Integrated analysis of the ubiquitination mechanism reveals the specific signatures of tissue and cancer
Long, D., Zhang, R., Du, C., Tong, J., Ni, Y., Zhou, Y., Zuo, Y., & Liao, M. (2023) · Figshare · doi:10.6084/m9.figshare.24089168
Additional file 8 of Integrated analysis of the ubiquitination mechanism reveals the specific signatures of tissue and cancer
Long, D., Zhang, R., Du, C., Tong, J., Ni, Y., Zhou, Y., Zuo, Y., & Liao, M. (2023) · Figshare · doi:10.6084/m9.figshare.24089171
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Additional file 5 of Integrated analysis of the ubiquitination mechanism reveals the specific signatures of tissue and cancer
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Additional file 1 of LABRAT reveals association of alternative polyadenylation with transcript localization, RNA binding protein expression, transcription speed, and cancer survival
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Additional file 3 of LABRAT reveals association of alternative polyadenylation with transcript localization, RNA binding protein expression, transcription speed, and cancer survival
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Additional file 1 of Integrated analysis of the ubiquitination mechanism reveals the specific signatures of tissue and cancer
Long, D., Zhang, R., Du, C., Tong, J., Ni, Y., Zhou, Y., Zuo, Y., & Liao, M. (2023) · Figshare · doi:10.6084/m9.figshare.24089144
Additional file 1 of Investigating transcriptome-wide sex dimorphism by multi-level analysis of single-cell RNA sequencing data in ten mouse cell types
Lu, T., & Mar, J. C. (2020) · Figshare · doi:10.6084/m9.figshare.13199098
Additional file 2 of Promoter evolution of mammalian gene duplicates
Fraimovitch, E., & Hagai, T. (2024) · Figshare · doi:10.6084/m9.figshare.26582084
Additional file 4 of LABRAT reveals association of alternative polyadenylation with transcript localization, RNA binding protein expression, transcription speed, and cancer survival
Goering, R., Engel, K. L., Gillen, A. E., Fong, N., Bentley, D. L., & Taliaferro, J. M. (2021) · Figshare · doi:10.6084/m9.figshare.14853539
Additional file 13 of Integrative analyses of the RNA modification machinery reveal tissue- and cancer-specific signatures
Begik, O., Lucas, M. C., Liu, H., Ramírez, J. M., Mattick, J. S., & Novoa, E. M. (2020) · Figshare · doi:10.6084/m9.figshare.12262577
Additional file 6 of Investigating transcriptome-wide sex dimorphism by multi-level analysis of single-cell RNA sequencing data in ten mouse cell types
Lu, T., & Mar, J. C. (2020) · Figshare · doi:10.6084/m9.figshare.13199113
Additional file 1 of Promoter evolution of mammalian gene duplicates
Fraimovitch, E., & Hagai, T. (2024) · Figshare · doi:10.6084/m9.figshare.26582081
Additional file 13 of Full-length transcriptome sequencing and comparative transcriptomic analysis to uncover genes involved in early gametogenesis in the gonads of Amur sturgeon (Acipenser schrenckii)
Zhang, X., Zhou, J., Li, L., Huang, W., Ahmad, H. I., Li, H., Jiang, H., & Chen, J. (2020) · Figshare · doi:10.6084/m9.figshare.12109719
Additional file 2 of LABRAT reveals association of alternative polyadenylation with transcript localization, RNA binding protein expression, transcription speed, and cancer survival
Goering, R., Engel, K. L., Gillen, A. E., Fong, N., Bentley, D. L., & Taliaferro, J. M. (2021) · Figshare · doi:10.6084/m9.figshare.14853533
Additional file 14 of Integrative analyses of the RNA modification machinery reveal tissue- and cancer-specific signatures
Begik, O., Lucas, M. C., Liu, H., Ramírez, J. M., Mattick, J. S., & Novoa, E. M. (2020) · Figshare · doi:10.6084/m9.figshare.12262589
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Lei, H., Long, Y., Wu, S., Wang, X. E., Peng, Y., Liu, Z., Lu, W., Shu, Y., Zhu, H., Zou, M., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-71703-6
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Surana, P., Dutta, P., Papineni, N., Sathian, R., Zhou, Z., Liu, H., & Davuluri, R. V. (2026) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqag050
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Nakamura, M., Chen, X., Yao, S., Chan, L. X., Hongmei, R., Boulinguiez, A., Lally, N., Wu, H., Kodani, K., Hirose, K., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.23.733628
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Hypothalamic lncRNA Synage prevents age-related sperm quality decline by suppressing A-type potassium currents in GnRH neurons
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Authors: Li, B., Qing, T., Zhu, J., Wen, Z., Yu, Y., Fukumura, R., Zheng, Y., Gondo, Y., & Shi, L.
Affiliations: Fudan University (CN)
Sichuan University (CN)
RIKEN BioResource Research Center (JP)
Corresponding author: Zheng, Yuanting
Gondo, Yoichi
Shi, Leming
ORCID: Li, Bin
Qing, Tao
Wen, Zhuo
Yu, Ying
Zheng, Yuanting
Gondo, Yoichi
Shi, Leming
Venue: Scientific Reports
Publisher: Springer Science and Business Media LLC
Published: 2017-06-23
Volume: 7
Issue: 1
Pages: 4200-4200
ISSN: 2045-2322 (ISSN-L)
DOI: 10.1038/s41598-017-04520-z
PMC: PMC5482823
OpenAlex: W2644618666
Cited by: 184
References: 49
Citations by year: 2026: 13 · 2025: 18 · 2024: 18 · 2023: 25 · 2022: 22 · 2021: 22 · 2020: 37 · 2019: 22 · 2018: 6 · 2017: 1
FWCI: 7.38
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor)
Locations: Scientific Reports (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders: National Natural Science Foundation of China (111 Project, B13016, 31671368, 31471239, 31601085, 31471239, 31671368)
Higher Education Discipline Innovation Project (B13016)
Japan Society for the Promotion of Science (16H06279, 17H00789, 25241016)
National Key Research and Development Program of China (2016YFC0901704)
National Supercomputing Center, Korea Institute of Science and Technology Information
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords: mouse transcriptome, tissue-specific gene expression, C57BL/6J mice, tissue-specific genes, housekeeping genes, non-coding RNA, liver transcriptome, tissue expression profiling
MeSH terms: Animals, Female, Male, Mice, Inbred C57BL, Organ Specificity, Sequence Analysis, RNA, Genes, Essential, Gene Expression Profiling, Transcriptome

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A Comprehensive Mouse Transcriptomic BodyMap across 17 Tissues by RNA-seq

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