Large-scale analysis of the human and mouse transcriptomes
Open accessAbstract
High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we have generated and analyzed gene expression from a set of samples spanning a broad range of biological conditions. Specifically, we profiled gene expression from 91 human and mouse samples across a diverse array of tissues, organs, and cell lines. Because these samples predominantly come from the normal physiological state in the human and mouse, this dataset represents a preliminary, but substantial, description of the normal mammalian transcriptome. We have used this dataset to illustrate methods of mining these data, and to reveal insights into molecular and physiological gene function, mechanisms of transcriptional regulation, disease etiology, and comparative genomics. Finally, to allow the scientific community to use this resource, we have built a free and publicly accessible website ( http://expression.gnf.org ) that integrates data visualization and curation of current gene annotations.
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BIN1 transcript levels are higher in human white matter than gray matter according to independent microarray analyses.
“This finding is in agreement with the comparison of BIN1 transcript levels between the human white matter and the gray matter reported from independent microarray analyses [50, 52, 53].”
From Predominant expression of Alzheimer’s disease-associated BIN1 in mature oligodendrocytes and localization to white matter tracts (2016) · cites this paper as [52]
The Materials and Methods and Results and Discussion describe microarray profiling across human tissues, but the passages in our copy do not report a BIN1 comparison between human white and gray matter. Searches for BIN1, white matter, and gray matter found no passage establishing the claimed difference; page numbers were not supplied. (LLM, conf=0.73)
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- Authors
- Su, A. I., Cooke, M. P., Ching, K. A., Hakak, Y., Walker, J. R., Wiltshire, T., Orth, A. P., Vega, R. G., Sapinoso, L. M., Moqrich, A., Patapoutian, A., Hampton, G. M., Schultz, P. G., & Hogenesch, J. B.
- Affiliations
- Scripps Research Institute (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2002-03-19
- Volume
- 99
- Issue
- 7
- Pages
- 4465-4470
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC123671
- OpenAlex
- W2022756254
- Cited by
- 1,466
- References
- 1
- Citations by year
- 2026: 5 · 2025: 12 · 2024: 14 · 2023: 23 · 2022: 18 · 2021: 20 · 2020: 27 · 2019: 31 · 2018: 25 · 2017: 25 · 2016: 37 · 2015: 41 · 2014: 61 · 2013: 57 · 2012: 82
- FWCI
- 34.74
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HAL AMU (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- 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
- Keywords
- human transcriptome, mouse transcriptome, tissue-specific gene expression, transcriptional regulation, comparative genomics, gene function, etiology, genome annotation
- MeSH terms
- Animals, Collagen, Female, Humans, Male, Organ Specificity, Receptors, Cell Surface, Transcription, Genetic, Polymerase Chain Reaction, Gene Expression Profiling, Mice
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