Diversification of transcriptional modulation: Large-scale identification and characterization of putative alternative promoters of human genes
Open accessAbstract
By analyzing 1,780,295 5′-end sequences of human full-length cDNAs derived from 164 kinds of oligo-cap cDNA libraries, we identified 269,774 independent positions of transcriptional start sites (TSSs) for 14,628 human RefSeq genes. These TSSs were clustered into 30,964 clusters that were separated from each other by more than 500 bp and thus are very likely to constitute mutually distinct alternative promoters. To our surprise, at least 7674 (52%) human RefSeq genes were subject to regulation by putative alternative promoters (PAPs). On average, there were 3.1 PAPs per gene, with the composition of one CpG-island-containing promoter per 2.6 CpG-less promoters. In 17% of the PAP-containing loci, tissue-specific use of the PAPs was observed. The richest tissue sources of the tissue-specific PAPs were testis and brain. It was also intriguing that the PAP-containing promoters were enriched in the genes encoding signal transduction-related proteins and were rarer in the genes encoding extracellular proteins, possibly reflecting the varied functional requirement for and the restricted expression of those categories of genes, respectively. The patterns of the first exons were highly diverse as well. On average, there were 7.7 different splicing types of first exons per locus partly produced by the PAPs, suggesting that a wide variety of transcripts can be achieved by this mechanism. Our findings suggest that use of alternate promoters and consequent alternative use of first exons should play a pivotal role in generating the complexity required for the highly elaborated molecular systems in humans.
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Genes often have alternative TSSs, which are differentially used across tissues.
“Genes often have alternative TSSs, which are differentially used across tissues36–38.”
From Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation (2025) · cites this paper as [36]
Cites
Fredriksson, R., Lagerström, M. C., Lundin, L.-G., & Schiöth, H. B. (2003) · Molecular Pharmacology · doi:10.1124/mol.63.6.1256 · Cited by 2,941 · see citing works
Xie, X., Lu, J., Kulbokas, E. J., Golub, T. R., Mootha, V., Lindblad-Toh, K., Lander, E. S., & Kellis, M. (2005) · Nature · doi:10.1038/nature03441 · Cited by 1,872 · see citing works
Complete sequencing and characterization of 21,243 full-length human cDNAs
Ota, T., Suzuki, Y., Nishikawa, T., Otsuki, T., Sugiyama, T., Irie, R., Wakamatsu, A., Hayashi, K., Sato, H., Nagai, K., et al. (2004) · Nature Genetics · doi:10.1038/ng1285 · Cited by 925 · see citing works
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Conserved role of intragenic DNA methylation in regulating alternative promoters
Maunakea, A. K., Nagarajan, R. P., Bilenky, M., Ballinger, T. J., D’Souza, C., Fouse, S. D., Johnson, B. E., Hong, C., Nielsen, C., Zhao, Y., et al. (2010) · Nature · doi:10.1038/nature09165 · Cited by 1,743 · see citing works
AceView: a comprehensive cDNA-supported gene and transcripts annotation
Thierry-Mieg, D., & Thierry-Mieg, J. (2006) · Genome Biology · doi:10.1186/gb-2006-7-s1-s12 · Cited by 629 · see citing works
Insights from genomic profiling of transcription factors
Farnham, P. J. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2636 · Cited by 519 · see citing works
The functional consequences of alternative promoter use in mammalian genomes
Davuluri, R. V., Suzuki, Y., Sugano, S., Plass, C., & Huang, T. H.-M. (2008) · Trends in Genetics · doi:10.1016/j.tig.2008.01.008 · Cited by 408 · see citing works
Self-citationEndogenous retroviral LTRs as promoters for human genes: A critical assessment
Cohen, C. J., Lock, W. M., & Mager, D. L. (2009) · Gene · doi:10.1016/j.gene.2009.06.020 · Cited by 314 · see citing works
Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation
Linder, J., Srivastava, D., Yuan, H., Agarwal, V., & Kelley, D. R. (2025) · Nature Genetics · doi:10.1038/s41588-024-02053-6 · Cited by 265 · see citing works
Amaral, P. P., Neyt, C., Wilkins, S. J., Askarian-Amiri, M. E., Sunkin, S. M., Perkins, A. C., & Mattick, J. S. (2009) · RNA · doi:10.1261/rna.1705309 · Cited by 209 · see citing works
Herová, M., Schmid, M., Gemperle, C., & Hersberger, M. (2015) · The Journal of Immunology · doi:10.4049/jimmunol.1402166 · Cited by 157 · see citing works
Stein, J. L., Hua, X., Morra, J. H., Lee, S., Hibar, D. P., Ho, A. J., Leow, A. D., Toga, A. W., Sul, J. H., Kang, H. M., et al. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.02.068 · Cited by 145 · see citing works
Turner, J. D., Pelascini, L. P. L., Macedo, J. A., & Muller, C. P. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn897 · Cited by 104 · see citing works
Genetic Markers of Comorbid Depression and Alcoholism in Women
Procopio, D. O., Saba, L. M., Walter, H., Lesch, O., Skala, K., Schlaff, G., Vanderlinden, L., Clapp, P., Hoffman, P. L., & Tabakoff, B. (2013) · Alcoholism: Clinical and Experimental Research · doi:10.1111/acer.12060 · Cited by 52 · see citing works
Induction of a Unique Isoform of the <i>NCOA7</i> Oxidation Resistance Gene by Interferon β-1b
Yu, L., Croze, E., Yamaguchi, K. D., Tran, T., Reder, A. T., Litvak, V., & Volkert, M. R. (2015) · Journal of Interferon & Cytokine Research · doi:10.1089/jir.2014.0115 · Cited by 41 · see citing works
- Authors
- Kimura, K., Wakamatsu, A., Suzuki, Y., Ota, T., Nishikawa, T., Yamashita, R., Yamamoto, J.-I., Sekine, M., Tsuritani, K., Wakaguri, H., Ishii, S., Sugiyama, T., Saito, K., Isono, Y., Irie, R., Kushida, N., Yoneyama, T., Otsuka, R., Kanda, K., Yokoi, T., Kondo, H., Wagatsuma, M., Murakawa, K., Ishida, S., Ishibashi, T., Takahashi-Fujii, A., Tanase, T., Nagai, K., Kikuchi, H., Nakai, K., Isogai, T., & Sugano, S.
- Affiliations
- Hitachi (Japan) (JP)
- The University of Tokyo (JP)
- Institute of Medical Science, The University of Tokyo (JP)
- National Institute of Technology and Evaluation (JP)
- Tokyo University of Technology (JP)
- Takara Shuzo Co., Ltd. (Japan) (JP)
- ORCID
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2005-12-12
- Volume
- 16
- Issue
- 1
- Pages
- 55-65
- ISSN
- 1088-9051 (ISSN-L)
- PMC
- PMC1356129
- OpenAlex
- W2138197117
- Cited by
- 506
- References
- 3
- Citations by year
- 2026: 5 · 2025: 18 · 2024: 14 · 2023: 11 · 2022: 32 · 2021: 29 · 2020: 28 · 2019: 15 · 2018: 15 · 2017: 19 · 2016: 21 · 2015: 23 · 2014: 14 · 2013: 24 · 2012: 28
- Type
- posted content
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Genome Research (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministry of Economy, Trade and Industry
- National Institutes of Health (Z99 DA999999)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- alternative promoters, transcription start sites, human genes, full-length cDNA, CpG islands, tissue-specific promoters, alternative splicing, signal transduction genes, extracellular proteins, transcriptome complexity
- MeSH terms
- Base Sequence, Exons, Multigene Family, Humans, Molecular Sequence Data, Organ Specificity, Promoter Regions, Genetic, Transcription, Genetic, Signal Transduction, Gene Library, CpG Islands, Quantitative Trait Loci
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