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Genome-wide determination of RNA stability reveals hundreds of short-lived noncoding transcripts in mammals
Open accessAbstract
Mammalian genomes produce huge numbers of noncoding RNAs (ncRNAs). However, the functions of most ncRNAs are unclear, and novel techniques that can distinguish functional ncRNAs are needed. Studies of mRNAs have revealed that the half-life of each mRNA is closely related to its physiological function, raising the possibility that the RNA stability of an ncRNA reflects its function. In this study, we first determined the half-lives of 11,052 mRNAs and 1418 ncRNAs in HeLa Tet-off (TO) cells by developing a novel genome-wide method, which we named 5′-br omo-uridine i mmunoprecipitation c hase–deep sequencing analysis (BRIC-seq). This method involved pulse-labeling endogenous RNAs with 5′-bromo-uridine and measuring the ongoing decrease in RNA levels over time using multifaceted deep sequencing. By analyzing the relationship between RNA half-lives and functional categories, we found that RNAs with a long half-life (t1/2 ≥ 4 h) contained a significant proportion of ncRNAs, as well as mRNAs involved in housekeeping functions, whereas RNAs with a short half-life (t1/2 < 4 h) included known regulatory ncRNAs and regulatory mRNAs. The stabilities of a significant set of short-lived ncRNAs are regulated by external stimuli, such as retinoic acid treatment. In particular, we identified and characterized several novel long ncRNAs involved in cell proliferation from the group of short-lived ncRNAs. We designated this novel class of ncRNAs with a short half-life as S hort-Li ved noncoding T ranscripts (SLiTs). We propose that the strategy of monitoring RNA half-life will provide a powerful tool for investigating hitherto functionally uncharacterized regulatory RNAs.
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Cites
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
Global quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566 · cited 6×
“It has been proposed that the specific half-life of each mRNA is closely related to its physiological function (Lam et al. 2001; Yang et al. 2003; Raghavan and Bohjanen 2004; Sharova et al. 2009; Rabani et al. 2011; Schwanhäusser et al. 2011).”
BackgroundMethodResultInfluentialChromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals
Guttman, M., Amit, I., Garber, M., French, C., Lin, M. F., Feldser, D., Huarte, M., Zuk, O., Carey, B. W., Cassady, J. P., et al. (2009) · Nature · doi:10.1038/nature07672 · Cited by 4,098
Khalil, A. M., Guttman, M., Huarte, M., Garber, M., Raj, A., Rivea Morales, D., Thomas, K., Presser, A., Bernstein, B. E., van Oudenaarden, A., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0904715106 · Cited by 2,872
Clemson, C. M., Hutchinson, J. N., Sara, S. A., Ensminger, A. W., Fox, A. H., Chess, A., & Lawrence, J. B. (2009) · Molecular Cell · doi:10.1016/j.molcel.2009.01.026 · Cited by 1,445
Yap, K. L., Li, S., Muñoz-Cabello, A. M., Raguz, S., Zeng, L., Mujtaba, S., Gil, J., Walsh, M. J., & Zhou, M.-M. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.03.021 · Cited by 1,391
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
Self-citationSharova, L. V., Sharov, A. A., Nedorezov, T., Piao, Y., Shaik, N., & Ko, M. S. H. (2009) · DNA Research · doi:10.1093/dnares/dsn030 · Cited by 591 · cited 4×
“These results indicate that mRNA half-lives are correlated with the functions of genes, consistent with previous reports (Lam et al. 2001; Yang et al. 2003; Raghavan and Bohjanen 2004; Sharova et al. 2009; Rabani et al. 2011; Schwanhäusser et al. 2011).”
BackgroundResultInfluential
Research works printed but not linked: 46
- 10.1038/nature07759 · DOI · Paper page
- 10.1016/j.ceb.2004.03.003 · DOI · Paper page
- 10.1073/pnas.0600148103 · DOI
- 10.1126/science.1103388 · DOI · Paper page
- 10.1128/MCB.20.10.3616-3625.2000 · DOI
- 10.1002/jnr.21473 · DOI
- 10.1016/0003-2697(87)90021-2 · DOI · Paper page
- 10.1126/science.1162228 · DOI · Paper page
- 10.1016/0012-1606(84)90162-3 · DOI · Paper page
- 10.1093/nar/gkp542 · DOI · Paper page
- 10.1038/nature08975 · DOI
- 10.1016/S1097-2765(03)00446-5 · DOI · Paper page
- 10.1186/1471-2164-8-39 · DOI · Paper page
- 10.1261/rna.1657609 · DOI
- 10.1093/emboj/20.3.541 · DOI
- 10.1073/pnas.0808480105 · DOI · Paper page
- 1994, Elongation factor-1 α mRNA is selectively translated following mitogenic stimulation, J Biol Chem, 269, 4367, 10.1016/S0021-9258(17)41789-3 · DOI
- 10.1261/rna.1951310 · DOI · Paper page
- 10.1210/en.2009-1250 · DOI
- 10.1126/scisignal.2000568 · DOI · Paper page
- 10.1038/onc.2010.568 · DOI · Paper page
- 2001, Genomic-scale measurement of mRNA turnover and the mechanisms of action of the anti-cancer drug flavopiridol, Genome Biol, 2, research0041
- 10.1038/nrg1321 · DOI · Paper page
- 10.1038/ng1429 · DOI · Paper page
- 10.1101/gr.095976.109 · DOI
- Miyagawa R , Tano K , Mizuno R , Nakamura Y , Ijiri K , Rakwal R , Shibato J , Masuo Y , Mayeda A , Hirose T , . 2012. Identification of cis- and trans-acting factors involved in the localization of MALAT-1 noncoding RNA to nuclear speckles. RNA doi: 10.1261/rna.028639.111. · DOI
- 10.1126/science.1158441 · DOI · Paper page
- 10.1101/gad.1484207 · DOI · Paper page
- 10.1126/science.1164096 · DOI · Paper page
- 10.1038/nbt.1861 · DOI · Paper page
- 10.1093/bfgp/3.2.112 · DOI
- 10.1038/nsmb886 · DOI · Paper page
- 2000, Retinoids in embryonal development, Physiol Rev, 80, 1021, 10.1152/physrev.2000.80.3.1021 · DOI · Paper page
- 10.1073/pnas.0807899106 · DOI · Paper page
- 10.1093/nar/gkp967 · DOI · Paper page
- 10.1126/science.1162253 · DOI · Paper page
- 1998, Classification of gas5 as a multi-small-nucleolar-RNA (snoRNA) host gene and a member of the 5′-terminal oligopyrimidine gene family reveals common features of snoRNA host genes, Mol Cell Biol, 18, 6897, 10.1128/MCB.18.12.6897 · DOI · Paper page
- 10.1242/jcs.009357 · DOI · Paper page
- 10.1101/gr.087775.108 · DOI · Paper page
- 10.1016/j.febslet.2010.10.008 · DOI · Paper page
- 10.1093/dnares/dsp022 · DOI
- 10.1016/j.cell.2005.04.030 · DOI · Paper page
- 10.1093/nar/gkp1017 · DOI
- 10.1101/gr.110254.110 · DOI
- 10.1101/gr.1272403 · DOI · Paper page
- 10.1016/j.cell.2011.08.054 · DOI · Paper page
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Arango, D., Sturgill, D., Alhusaini, N., Dillman, A. A., Sweet, T. J., Hanson, G., Hosogane, M., Sinclair, W. R., Nanan, K. K., Mandler, M. D., et al. (2018) · Cell · doi:10.1016/j.cell.2018.10.030 · Cited by 862
TAIL-seq: Genome-wide Determination of Poly(A) Tail Length and 3′ End Modifications
Chang, H., Lim, J., Ha, M., & Kim, V. N. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.02.007 · Cited by 454
Cells exhibiting strong p16 INK4a promoter activation in vivo display features of senescence
Liu, J.-Y., Souroullas, G. P., Diekman, B. O., Krishnamurthy, J., Hall, B. M., Sorrentino, J. A., Parker, J. S., Sessions, G. A., Gudkov, A. V., & Sharpless, N. E. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1818313116 · Cited by 306
Gaidatzis, D., Burger, L., Florescu, M., & Stadler, M. B. (2015) · Nature Biotechnology · doi:10.1038/nbt.3269 · Cited by 313
Large-scale investigation of the reasons why potentially important genes are ignored
Stoeger, T., Gerlach, M., Morimoto, R. I., & Nunes Amaral, L. A. (2018) · PLOS Biology · doi:10.1371/journal.pbio.2006643 · Cited by 261
Tunable protein synthesis by transcript isoforms in human cells
Floor, S. N., & Doudna, J. A. (2016) · eLife · doi:10.7554/elife.10921 · Cited by 265
Regulation of long non-coding RNAs and genome dynamics by the RNA surveillance machinery
Nair, L., Chung, H., & Basu, U. (2020) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0209-0 · Cited by 203
Single-cell sequencing to multi-omics: technologies and applications
Wu, X., Yang, X., Dai, Y., Zhao, Z., Zhu, J., Guo, H., & Yang, R. (2024) · Biomarker Research · doi:10.1186/s40364-024-00643-4 · Cited by 222
“The technology was initially applied at the bulk RNA level [30].”
MethodThe genetic and biochemical determinants of mRNA degradation rates in mammals
Agarwal, V., & Kelley, D. R. (2022) · Genome Biology · doi:10.1186/s13059-022-02811-x · Cited by 155
Biased Allelic Expression in Human Primary Fibroblast Single Cells
Borel, C., Ferreira, P. G., Santoni, F., Delaneau, O., Fort, A., Popadin, K. Y., Garieri, M., Falconnet, E., Ribaux, P., Guipponi, M., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.12.001 · Cited by 120
Time-resolved single-cell RNA-seq using metabolic RNA labelling
Erhard, F., Saliba, A.-E., Lusser, A., Toussaint, C., Hennig, T., Prusty, B. K., Kirschenbaum, D., Abadie, K., Miska, E. A., Friedel, C. C., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00157-z · Cited by 73
Impact of Methods on the Measurement of mRNA Turnover
Wada, T., & Becskei, A. (2017) · International Journal of Molecular Sciences · doi:10.3390/ijms18122723 · Cited by 66
Bouhaddou, M., Barrette, A. M., Stern, A. D., Koch, R. J., DiStefano, M. S., Riesel, E. A., Santos, L. C., Tan, A. L., Mertz, A. E., & Birtwistle, M. R. (2018) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005985 · Cited by 58
Transimulation - Protein Biosynthesis Web Service
Siwiak, M., & Zielenkiewicz, P. (2013) · PLoS ONE · doi:10.1371/journal.pone.0073943 · Cited by 50
Krenning, L., Sonneveld, S., & Tanenbaum, M. E. (2022) · eLife · doi:10.7554/elife.71356 · Cited by 41
Single-cell proteomic landscape of the developing human brain
Wu, T., Jiang, L., Mukhtar, T., Wang, L., Jian, R., Wang, C., Trinh, T., Kriegstein, A. R., Snyder, M., & Li, J. (2026) · Nature Biotechnology · doi:10.1038/s41587-025-02980-7 · Cited by 23
Wolfe, M. B., Schagat, T. L., Paulsen, M. T., Magnuson, B., Ljungman, M., Park, D., Zhang, C., Campbell, Z. T., Goldstrohm, A. C., & Freddolino, P. L. (2020) · RNA · doi:10.1261/rna.077362.120 · Cited by 22
Comprehensive analysis of the circadian nuclear and cytoplasmic transcriptome in mouse liver
Hurni, C., Weger, B. D., Gobet, C., & Naef, F. (2022) · PLOS Genetics · doi:10.1371/journal.pgen.1009903 · Cited by 14
Murphy, A. E., Askarova, A., Lenhard, B., Skene, N. G., & Marzi, S. J. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkae1212 · Cited by 10
Besic, V., Habibolahi, F., Noël, B., Rupp, S., Genovesio, A., & Lebreton, A. (2020) · RNA Biology · doi:10.1080/15476286.2020.1777380 · Cited by 10
Metabolic turnover and dynamics of modified ribonucleosides by 13C labeling
Gameiro, P. A., Encheva, V., Dos Santos, M. S., MacRae, J. I., & Ule, J. (2021) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2021.101294 · Cited by 10
Imai, H., Utsumi, D., Torihara, H., Takahashi, K., Kuroyanagi, H., & Yamashita, A. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad545 · Cited by 9
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Xu, Z., & Asakawa, S. (2021) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1009188 · Cited by 9
Forés-Martos, J., Forte, A., García-Martínez, J., & Pérez-Ortín, J. E. (2021) · Cells · doi:10.3390/cells10020334 · Cited by 8
Metadata
- Authors
- Tani, H., Mizutani, R., Salam, K. A., Tano, K., Ijiri, K., Wakamatsu, A., Isogai, T., Suzuki, Y., & Akimitsu, N.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2012-02-27
- Volume
- 22
- Issue
- 5
- Pages
- 947-956
- ISSN
- 1088-9051 (ISSN-L)
- OpenAlex
- W2136086657
- Cited by
- 464
- References
- 8
- Type
- posted content
- Language
- en
- Open access
- bronze
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