Thiol-linked alkylation for the metabolic sequencing of RNA
Open accessPreprint — published as 10.1038/nmeth.4435 · Paper page
Abstract
Gene expression profiling by high-throughput sequencing reveals qualitative and quantitative changes in RNA species at steady-state but obscures the intracellular dynamics of RNA transcription, processing and decay. We developed thiol(SH)-linked alkylation for the metabolic sequencing of RNA (SLAM-seq), an orthogonal chemistry-based epitranscriptomics-sequencing technology that uncovers 4-thiouridine (s 4 U)-incorporation in RNA species at single-nucleotide resolution. In combination with well-established metabolic RNA labeling protocols and coupled to standard, low-input, high-throughput RNA sequencing methods, SLAM-seq enables rapid access to RNA polymerase II-dependent gene expression dynamics in the context of total RNA. When applied to mouse embryonic stem cells, SLAM-seq provides global and transcript-specific insights into pluripotency-associated gene expression. We validated the method by showing that the RNA-polymerase II-dependent transcriptional output scales with Oct4/Sox2/Nanog-defined enhancer activity; and we provide quantitative and mechanistic evidence for transcript-specific RNA turnover mediated by post-transcriptional gene regulatory pathways initiated by microRNAs and N 6 -methyladenosine. SLAM-seq facilitates the dissection of fundamental mechanisms that control gene expression in an accessible, cost-effective, and scalable manner. One Sentence Summary: Chemical nucleotide-analog derivatization provides global insights into transcriptional and post-transcriptional gene regulation
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607 · see citing works
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709 · see citing works
featureCounts: an efficient general purpose program for assigning sequence reads to genomic features
Liao, Y., Smyth, G. K., & Shi, W. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt656 · Cited by 27,219 · see citing works
MicroRNAs: Target Recognition and Regulatory Functions
Bartel, D. P. (2009) · Cell · doi:10.1016/j.cell.2009.01.002 · Cited by 20,068 · see citing works
TopHat: discovering splice junctions with RNA-Seq
Trapnell, C., Pachter, L. S., & Salzberg, S. L. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp120 · Cited by 11,477 · see citing works
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197 · see citing works
Most mammalian mRNAs are conserved targets of microRNAs
Friedman, R. C., Farh, K. K.-H., Burge, C. B., & Bartel, D. P. (2009) · Genome Research · doi:10.1101/gr.082701.108 · Cited by 8,462 · see citing works
deepTools2: a next generation web server for deep-sequencing data analysis
Ramírez, F., Ryan, D. P., Grüning, B., Bhardwaj, V., Kilpert, F., Richter, A. S., Heyne, S., Dündar, F., & Manke, T. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw257 · Cited by 8,096 · see citing works
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 3× · see citing works
“Note, that the ability to determine de novo synthesized transcripts will depend on (1) the s(4)U uptake kinetics of the chosen cellular system, (2) the overall transcriptional activity of the cell type and (3) the library sequencing depth.”
BackgroundImproved vectors and genome-wide libraries for CRISPR screening
Sanjana, N. E., Shalem, O., & Zhang, F. (2014) · Nature Methods · doi:10.1038/nmeth.3047 · Cited by 5,239 · see citing works
VarScan 2: Somatic mutation and copy number alteration discovery in cancer by exome sequencingPreprint
Koboldt, D. C., Zhang, Q., Larson, D. E., Shen, D., McLellan, M. D., Lin, L., Miller, C. A., Mardis, E. R., Ding, L., & Wilson, R. K. (2012) · Genome Research · doi:10.1101/gr.129684.111 · Cited by 4,822 · see citing works
Master Transcription Factors and Mediator Establish Super-Enhancers at Key Cell Identity Genes
Whyte, W. A., Orlando, D. A., Hnisz, D., Abraham, B. J., Lin, C. Y., Kagey, M. H., Rahl, P. B., Lee, T. I., & Young, R. A. (2013) · Cell · doi:10.1016/j.cell.2013.03.035 · Cited by 4,143 · see citing works
PANTHER: A Library of Protein Families and Subfamilies Indexed by FunctionPreprint
Thomas, P. D., Campbell, M. J., Kejariwal, A., Mi, H., Karlak, B., Daverman, R., Diemer, K., Muruganujan, A., & Narechania, A. (2003) · Genome Research · doi:10.1101/gr.772403 · Cited by 2,912 · see citing works
Transcriptome-wide Identification of RNA-Binding Protein and MicroRNA Target Sites by PAR-CLIP
Hafner, M., Landthaler, M., Burger, L., Khorshid, M., Hausser, J., Berninger, P., Rothballer, A., Ascano, M., Jungkamp, A.-C., Munschauer, M., et al. (2010) · Cell · doi:10.1016/j.cell.2010.03.009 · Cited by 2,873 · see citing works
MicroRNA maturation: stepwise processing and subcellular localization
Lee, Y., Jeon, K., Lee, J., Kim, S., & Kim, V. N. (2002) · The EMBO Journal · doi:10.1093/emboj/cdf476 · Cited by 2,468 · see citing works
Gene silencing by microRNAs: contributions of translational repression and mRNA decay
Huntzinger, E., & Izaurralde, E. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2936 · Cited by 2,339 · see citing works
BEDTools: The Swiss‐Army Tool for Genome Feature Analysis
Quinlan, A. R. (2014) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1112s47 · Cited by 2,286 · see citing works
Nascent RNA Sequencing Reveals Widespread Pausing and Divergent Initiation at Human Promoters
Core, L. J., Waterfall, J. J., & Lis, J. T. (2008) · Science · doi:10.1126/science.1162228 · Cited by 1,986 · see citing works
Gene expression regulation mediated through reversible m6A RNA methylation
Fu, Y., Dominissini, D., Rechavi, G., & He, C. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3724 · Cited by 1,926 · see citing works
AmiGO: online access to ontology and annotation data
Carbon, S., Ireland, A., Mungall, C., Shu, S., Marshall, B., Lewis, S., Hub, T. A., & the Web Presence Working Group (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn615 · Cited by 1,918 · see citing works
m 6 A mRNA methylation facilitates resolution of naïve pluripotency toward differentiation
Geula, S., Moshitch-Moshkovitz, S., Dominissini, D., Mansour, A. A., Kol, N., Salmon‐Divon, M., Hershkovitz, V., Peer, E., Mor, N., Manor, Y. S., et al. (2015) · Science · doi:10.1126/science.1261417 · Cited by 1,560 · see citing works
Relief of microRNA-Mediated Translational Repression in Human Cells Subjected to Stress
Bhattacharyya, S. N., Habermacher, R., Martiné, U., Closs, E. I., & Filipowicz, W. (2006) · Cell · doi:10.1016/j.cell.2006.04.031 · Cited by 1,332 · see citing works
m6A RNA Modification Controls Cell Fate Transition in Mammalian Embryonic Stem Cells
Batista, P. J., Molinié, B., Wang, J., Qu, K., Zhang, J., Li, L., Bouley, D. M., Lujan, E., Haddad, B., Daneshvar, K., et al. (2014) · Cell stem cell · doi:10.1016/j.stem.2014.09.019 · Cited by 1,276 · see citing works
Structural basis of N6-adenosine methylation by the METTL3–METTL14 complex
Wang, X., Feng, J. Q., Xue, Y. C., Guan, Z., Zhang, D., Liu, Z., Gong, Z., Wang, Q., Huang, J. B., Tang, C., et al. (2016) · Nature · doi:10.1038/nature18298 · Cited by 1,218 · see citing works
Control of the Embryonic Stem Cell State
Young, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.01.032 · Cited by 1,189 · see citing works
Diversifying microRNA sequence and function
Ameres, S. L., & Zamore, P. D. (2013) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3611 · Cited by 1,175 · see citing works
Self-citationBrennan, C. M., & Steitz*, J. A. (2001) · Cellular and Molecular Life Sciences · doi:10.1007/pl00000854 · Cited by 1,095 · see citing works
The dynamic epitranscriptome: N6-methyladenosine and gene expression control
Meyer, K. D., & Jaffrey, S. R. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3785 · Cited by 1,056 · see citing works
Enhancer function: new insights into the regulation of tissue-specific gene expression
Ong, C.-T., & Corces, V. G. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2957 · Cited by 929 · see citing works
RNA N 6 -methyladenosine methylation in post-transcriptional gene expression regulationPreprint
Yue, Y., Liu, J., & He, C. (2015) · Genes & Development · doi:10.1101/gad.262766.115 · Cited by 918 · see citing works
Precise Maps of RNA Polymerase Reveal How Promoters Direct Initiation and Pausing
Kwak, H., Fuda, N. J., Core, L. J., & Lis, J. T. (2013) · Science · doi:10.1126/science.1229386 · Cited by 849 · see citing works
Nascent transcript sequencing visualizes transcription at nucleotide resolution
Churchman, L. S., & Weissman, J. S. (2011) · Nature · doi:10.1038/nature09652 · Cited by 823 · see citing works
Pott, S., & Lieb, J. D. (2014) · Nature Genetics · doi:10.1038/ng.3167 · Cited by 745 · see citing works
Rabani, M., Levin, J. Z., Fan, L., Adiconis, X., Raychowdhury, R., Garber, M., Gnirke, A., Nusbaum, C., Hacohen, N., Friedman, N., et al. (2011) · Nature Biotechnology · doi:10.1038/nbt.1861 · Cited by 583 · see citing works
TT-seq maps the human transient transcriptome
Schwalb, B., Michel, M., Zacher, B., Frühauf, K., Demel, C., Tresch, A., Gagneur, J., & Cramer, P. (2016) · Science · doi:10.1126/science.aad9841 · Cited by 548 · see citing works
Ke, S., Pandya‐Jones, A., Saito, Y., Fak, J. J., Vågbø, C. B., Geula, S., Hanna, J. H., Black, D. L., Darnell, J. E., Jr., & Darnell, R. B. (2017) · Genes & Development · doi:10.1101/gad.301036.117 · Cited by 537 · see citing works
Summary: the modified nucleosides of RNA
Limbach, P. A., Crain, P. F., & McCloskey, J. A. (1994) · Nucleic Acids Research · doi:10.1093/nar/22.12.2183 · Cited by 523 · see citing works
Epitranscriptome sequencing technologies: decoding RNA modifications
Li, X., Xiong, X., & Yi, C. (2017) · Nature Methods · doi:10.1038/nmeth.4110 · Cited by 447 · see citing works
NextGenMap: fast and accurate read mapping in highly polymorphic genomes
Sedlazeck, F. J., Rescheneder, P., & von Haeseler, A. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt468 · Cited by 429 · see citing works
Self-citationMohn, F., Sienski, G., Handler, D., & Brennecke, J. (2014) · Cell · doi:10.1016/j.cell.2014.04.031 · Cited by 415 · see citing works
Dölken, L., Ruzsics, Z., Rädle, B., Friedel, C. C., Zimmer, R., Mages, J., Hoffmann, R. F. G., Dickinson, P., Forster, T., Ghazal, P., et al. (2008) · RNA · doi:10.1261/rna.1136108 · Cited by 407 · see citing works
Mullokandov, G., Baccarini, A., Ruzo, A., Jayaprakash, A. D., Tung, N., Israelow, B., Evans, M. J., Sachidanandam, R., & Brown, B. D. (2012) · Nature Methods · doi:10.1038/nmeth.2078 · Cited by 394 · see citing works
Dynamic transcriptome analysis measures rates of mRNA synthesis and decay in yeast
Miller, C., Schwalb, B., Maier, K. C., Schulz, D., Dümcke, S., Zacher, B., Mayer, A., Sydow, J. F., Marcinowski, L., Dölken, L., et al. (2011) · Molecular Systems Biology · doi:10.1038/msb.2010.112 · Cited by 393 · see citing works
Regulating RNA polymerase pausing and transcription elongation in embryonic stem cellsPreprint
Min, I. M., Waterfall, J. J., Core, L. J., Munroe, R. J., Schimenti, J. C., & Lis, J. T. (2011) · Genes & Development · doi:10.1101/gad.2005511 · Cited by 297 · see citing works
QuantSeq 3′ mRNA sequencing for RNA quantification
Moll, P. R., Ante, M., Seitz, A., & Reda, T. (2014) · Nature Methods · doi:10.1038/nmeth.f.376 · Cited by 296 · see citing works
Sun, M., Schwalb, B., Schulz, D., Pirkl, N., Etzold, S., Larivière, L., Maier, K. C., Seizl, M., Tresch, A., & Cramer, P. (2012) · Genome Research · doi:10.1101/gr.130161.111 · Cited by 289 · see citing works
Forward and Reverse Genetics through Derivation of Haploid Mouse Embryonic Stem Cells
Elling, U., Taubenschmid, J., Wirnsberger, G., O’Malley, R. C., Demers, S.-P., Vanhaelen, Q., Иванович, Ш. А., Schmauss, G., Schramek, D., Schnütgen, F., et al. (2011) · Cell stem cell · doi:10.1016/j.stem.2011.10.012 · Cited by 232 · see citing works
Self-citationHigh-Resolution Sequencing and Modeling Identifies Distinct Dynamic RNA Regulatory Strategies
Rabani, M., Raychowdhury, R., Jovanovic, M., Rooney, M., Stumpo, D. J., Pauli, A., Hacohen, N., Schier, A. F., Blackshear, P. J., Friedman, N., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.015 · Cited by 226 · see citing works
WGE: a CRISPR database for genome engineering
Hodgkins, A., Farne, A., Perera, S., Grego, T., Parry-Smith, D., Skarnes, W., & Iyer, V. (2015) · Bioinform. · doi:10.1093/bioinformatics/btv308 · Cited by 202 · see citing works
Cleary, M. D., Meiering, C. D., Jan, E., Guymon, R., & Boothroyd, J. C. (2005) · Nature Biotechnology · doi:10.1038/nbt1061 · Cited by 198 · see citing works
Tracking Distinct RNA Populations Using Efficient and Reversible Covalent Chemistry
Duffy, E. E., Rutenberg-Schoenberg, M., Stark, C., Kitchen, R. R., Gerstein, M., & Simon, M. D. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.07.023 · Cited by 193 · see citing works
TU-tagging: cell type–specific RNA isolation from intact complex tissues
Miller, M. R., Robinson, K. J., Cleary, M. D., & Doe, C. Q. (2009) · Nature Methods · doi:10.1038/nmeth.1329 · Cited by 176 · see citing works
The 3′-to-5′ Exoribonuclease Nibbler Shapes the 3′ Ends of MicroRNAs Bound to Drosophila Argonaute1
Han, B., Hung, J., Weng, Z., Zamore, P. D., & Ameres, S. L. (2011) · Current Biology · doi:10.1016/j.cub.2011.09.034 · Cited by 164 · see citing works
Self-citation4-thiouridine inhibits rRNA synthesis and causes a nucleolar stress response
Burger, K., Mühl, B., Kellner, M., Michaela, R., Anita, G.-E., Windhager, L., Friedel, C. C., Dölken, L., & Eick, D. (2013) · RNA Biology · doi:10.4161/rna.26214 · Cited by 131 · see citing works
Nucleobase Transport by Human Equilibrative Nucleoside Transporter 1 (hENT1)
Yao, S. Y. M., Ng, A. M. L., Cass, C. E., Baldwin, S. A., & Young, J. D. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.236117 · Cited by 128 · see citing works
Genome-wide technology for determining RNA stability in mammalian cells
Tani, H., & Akimitsu, N. (2012) · RNA Biology · doi:10.4161/rna.22036 · Cited by 120 · see citing works
Gay, L. S., Miller, M. R., Ventura, P. B., Devasthali, V., Vue, Z., Thompson, H. L., Temple, S., Zong, H., Cleary, M. D., Stankunas, K., et al. (2013) · Genes & Development · doi:10.1101/gad.205278.112 · Cited by 114 · see citing works
UV-Induced Stabilization of c-fos and Other Short-Lived mRNAs
Blattner, C., Kannouche, P. L., Litfin, M., Bender, K., Rahmsdorf, H. J., Angulo, J. F., & Herrlich, P. A. (2000) · Molecular and Cellular Biology · doi:10.1128/mcb.20.10.3616-3625.2000 · Cited by 109 · see citing works
PAR-CLIP (Photoactivatable Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation)
Spitzer, J., Hafner, M., Landthaler, M., Ascano, M., Farazi, T. A., Wardle, G. S., Nusbaum, J. D., Khorshid, M., Burger, L., Zavolan, M., et al. (2014) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/b978-0-12-420120-0.00008-6 · Cited by 107 · see citing works
Gorospe, M., Wang, X., & Holbrook, N. J. (1998) · Molecular and Cellular Biology · doi:10.1128/mcb.18.3.1400 · Cited by 104 · see citing works
Uridylation of RNA Hairpins by Tailor Confines the Emergence of MicroRNAs in Drosophila
Reimão-Pinto, M. M., Ignatova, V. V., Burkard, T. R., Hung, J., Manzenreither, R. A., Sowemimo, I., Herzog, V. A., Reichholf, B., Fariña-Lopez, S., & Ameres, S. L. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.05.033 · Cited by 78 · see citing works
Self-citationDetection of nucleic acid modifications by chemical reagents
Heiß, M., & Kellner, S. M. (2016) · RNA Biology · doi:10.1080/15476286.2016.1261788 · Cited by 26 · see citing works
Shugart, L. R. (1972) · Archives of Biochemistry and Biophysics · doi:10.1016/0003-9861(72)90167-1 · Cited by 14 · see citing works
Thiol-linked alkylation for the metabolic sequencing of RNA (SLAMseq)
Ameres, S. L., Herzog, V. A., Reichholf, B., & Ameres, S. L. (2017) · Protocol Exchange · doi:10.1038/protex.2017.105 · Cited by 9 · see citing works
Self-citationRNA Sequencing by Primer ExtensionPreprint
Nilsen, T. W. (2013) · Cold Spring Harbor Protocols · doi:10.1101/pdb.prot079400 · Cited by 3 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
RNA sequencing: the teenage years
Stark, R., Grzelak, M., & Hadfield, J. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0150-2 · Cited by 1,906 · see citing works
mRNAs, proteins and the emerging principles of gene expression control
Buccitelli, C., & Selbach, M. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0258-4 · Cited by 1,243 · see citing works
Paris, J., Morgan, M., Campos, J., Spencer, G. J., Shmakova, A., Ivanova, I., Mapperley, C., Lawson, H., Wotherspoon, D., Sepúlveda, C., et al. (2019) · Cell stem cell · doi:10.1016/j.stem.2019.03.021 · Cited by 502 · see citing works
Deciphering the “m6A Code” via Antibody-Independent Quantitative Profiling
García-Campos, M. A., Edelheit, S., Toth, U., Safra, M., Shachar, R., Viukov, S. V., Winkler, R., Nir, R., Lasman, L., Brandis, A. S., et al. (2019) · Cell · doi:10.1016/j.cell.2019.06.013 · Cited by 479 · see citing works
Small RNAs Are Trafficked from the Epididymis to Developing Mammalian Sperm
Sharma, U., Sun, F., Conine, C. C., Reichholf, B., Kukreja, S., Herzog, V. A., Ameres, S. L., & Rando, O. J. (2018) · Developmental Cell · doi:10.1016/j.devcel.2018.06.023 · Cited by 429 · see citing works
Self-citationH3K4me3 regulates RNA polymerase II promoter-proximal pause-release
Wang, H., Fan, Z., Shliaha, P. V., Miele, M., Hendrickson, R. C., Jiang, X., & Helin, K. (2023) · Nature · doi:10.1038/s41586-023-05780-8 · Cited by 422 · see citing works
Mechanisms of lncRNA biogenesis as revealed by nascent transcriptomics
Nojima, T., & Proudfoot, N. J. (2022) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-021-00447-6 · Cited by 424 · see citing works
SLAM-seq defines direct gene-regulatory functions of the BRD4-MYC axis
Muhar, M., Ebert, A., Neumann, T., Umkehrer, C., Jude, J., Wieshofer, C., Rescheneder, P., Lipp, J., Herzog, V. A., Reichholf, B., et al. (2018) · Science · doi:10.1126/science.aao2793 · Cited by 364 · see citing works
Self-citationRapid and accurate alignment of nucleotide conversion sequencing reads with HISAT-3NPreprint
Zhang, Y., Park, C., Bennett, C. G., Thornton, M. A., & Kim, D. (2021) · Genome Research · doi:10.1101/gr.275193.120 · Cited by 344 · see citing works
Translation affects mRNA stability in a codon-dependent manner in human cells
Wu, Q., Medina, S. G., Kushawah, G., DeVore, M. L., Castellano, L. A., Hand, J. M., Wright, M., & Bazzini, A. A. (2019) · eLife · doi:10.7554/elife.45396 · Cited by 283 · see citing works
Boulias, K., Toczydłowska-Socha, D., Hawley, B. R., Liberman, N., Takashima, K., Zaccara, S., Guez, T., Vasseur, J., Debart, F., Aravind, L., et al. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.06.006 · Cited by 273 · see citing works
TimeLapse-seq: adding a temporal dimension to RNA sequencing through nucleoside recoding
Schofield, J. A., Duffy, E. E., Kiefer, L. A., Sullivan, M., & Simon, M. D. (2018) · Nature Methods · doi:10.1038/nmeth.4582 · Cited by 261 · see citing works
SARS-CoV-2 uses a multipronged strategy to impede host protein synthesis
Finkel, Y., Gluck, A., Nachshon, A., Winkler, R., Fisher, T., Rozman, B., Mizrahi, O., Lubelsky, Y., Zuckerman, B., Slobodin, B., et al. (2021) · Nature · doi:10.1038/s41586-021-03610-3 · Cited by 260 · see citing works
Nascent RNA analyses: tracking transcription and its regulation
Wissink, E. M., Vihervaara, A., Tippens, N. D., & Lis, J. T. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0159-6 · Cited by 247 · see citing works
Wang, J.-Z., Li, Y.-C., Wang, P., Han, G.-X., Zhang, T.-T., Chang, J., Yin, R., Yi, S., Wen, J., Xie, X., et al. (2020) · Cell Stem Cell · doi:10.1016/j.stem.2020.04.001 · Cited by 220 · see citing works
Predicting mRNA Abundance Directly from Genomic Sequence Using Deep Convolutional Neural Networks
Agarwal, V., & Shendure, J. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107663 · Cited by 243 · see citing works
TDP-43 condensation properties specify its RNA-binding and regulatory repertoire
Hallegger, M., Chakrabarti, A. M., Lee, F. C. Y., Lee, B. L., Amalietti, A. G., Odeh, H. M., Copley, K. E., Rubien, J. D., Portz, B., Kuret, K., et al. (2021) · Cell · doi:10.1016/j.cell.2021.07.018 · Cited by 240 · see citing works
U1 snRNP regulates chromatin retention of noncoding RNAs
Yin, Y., Lu, J., Zhang, X., Shao, W., Xu, Y., Li, P., Hong, Y., Cui, L., Shan, G., Tian, B., et al. (2020) · Nature · doi:10.1038/s41586-020-2105-3 · Cited by 224 · see citing works
scSLAM-seq reveals core features of transcription dynamics in single cells
Erhard, F., Baptista, M. A. P., Krammer, T., Hennig, T., Lange, M., Arampatzi, P., Jürges, C. S., Theis, F. J., Saliba, A.-E., & Dölken, L. (2019) · Nature · doi:10.1038/s41586-019-1369-y · Cited by 233 · see citing works
Feng, M., Xie, X., Han, G., Zhang, T., Li, Y., Li, Y., Yin, R., Wang, Q., Zhang, T., Wang, P., et al. (2021) · Blood · doi:10.1182/blood.2020009676 · Cited by 213 · see citing works
Haas, L., Elewaut, A., Gerard, C. L., Umkehrer, C., Leiendecker, L., Pedersen, M., Kręcioch, I., Hoffmann, D., Novatchkova, M., Kuttke, M., et al. (2021) · Nature Cancer · doi:10.1038/s43018-021-00221-9 · Cited by 196 · see citing works
Self-citationMitogen‐activated protein kinase activity drives cell trajectories in colorectal cancer
Uhlitz, F., Bischoff, P., Peidli, S., Sieber, A., Obermayer, B., Blanc, E., Trinks, A., Lüthen, M., Ruchiy, Y., Sell, T., et al. (2021) · EMBO Molecular Medicine · doi:10.15252/emmm.202114123 · Cited by 193 · see citing works
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 195 · see citing works
Temporal modelling using single-cell transcriptomics
Ding, J., Sharon, N., & Bar-Joseph, Z. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-021-00444-7 · Cited by 195 · see citing works
Loganathan, T., & Doss, C. G. P. (2023) · Functional & Integrative Genomics · doi:10.1007/s10142-022-00947-4 · Cited by 190 · see citing works
Inferring Causal Gene Regulatory Networks from Coupled Single-Cell Expression Dynamics Using Scribe
Qiu, X., Rahimzamani, A., Wang, L., Ren, B., Mao, Q., Durham, T., McFaline-Figueroa, J. L., Saunders, L., Trapnell, C., & Kannan, S. (2020) · Cell Systems · doi:10.1016/j.cels.2020.02.003 · Cited by 185 · see citing works
Massively parallel and time-resolved RNA sequencing in single cells with scNT-seq
Qiu, Q., Hu, P., Qiu, X., Govek, K. W., Cámara, P. G., & Wu, H. (2020) · Nature Methods · doi:10.1038/s41592-020-0935-4 · Cited by 172 · see citing works
Thiecke, M. J., Wutz, G., Muhar, M., Tang, W., Bevan, S., Malysheva, V., Stocsits, R., Neumann, T., Zuber, J., Fraser, P., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107929 · Cited by 177 · see citing works
Self-citationSci-fate characterizes the dynamics of gene expression in single cells
Cao, J., Zhou, W. Y., Steemers, F. J., Trapnell, C., & Shendure, J. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0480-9 · Cited by 162 · see citing works
CDK13 cooperates with CDK12 to control global RNA polymerase II processivity
Fan, Z., Devlin, J. R., Hogg, S. J., Doyle, M. A., Harrison, P. F., Todorovski, I., Cluse, L. A., Knight, D. A., Sandow, J. J., Gregory, G., et al. (2020) · Science Advances · doi:10.1126/sciadv.aaz5041 · Cited by 164 · see citing works
Time-Resolved Small RNA Sequencing Unravels the Molecular Principles of MicroRNA Homeostasis
Reichholf, B., Herzog, V. A., Fasching, N., Manzenreither, R. A., Sowemimo, I., & Ameres, S. L. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.06.018 · Cited by 157 · see citing works
Self-citationDirect detection of RNA modifications and structure using single-molecule nanopore sequencing
Stephenson, W., Razaghi, R., Busan, S., Weeks, K. M., Timp, W., & Smibert, P. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100097 · Cited by 155 · see citing works
Neumann, T., Herzog, V. A., Muhar, M., von Haeseler, A., Zuber, J. A., Ameres, S. L., & Rescheneder, P. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-2849-7 · Cited by 157 · see citing works
Self-citationThe 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 · see citing works
Zuckerman, B. M., Ron, M., Mikl, M., Segal, E., & Ulitsky, I. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.05.013 · Cited by 154 · see citing works
Recent advances in the detection of base modifications using the Nanopore sequencer
Xu, L., & Seki, M. (2019) · Journal of Human Genetics · doi:10.1038/s10038-019-0679-0 · Cited by 147 · see citing works
Qu, Y., Wang, Z., Shen, Y., Lan, Y., Zhong, X., Luo, X., Yang, T., Zhang, M., Zuo, B., Zeng, T., et al. (2024) · Advanced Science · doi:10.1002/advs.202309290 · Cited by 144 · see citing works
Mapperley, C., van de Lagemaat, L. N., Lawson, H., Tavosanis, A., Paris, J., Campos, J., Wotherspoon, D., Durko, J., Sarapuu, A., Choe, J., et al. (2020) · The Journal of Experimental Medicine · doi:10.1084/jem.20200829 · Cited by 138 · see citing works
Dissecting newly transcribed and old RNA using GRAND-SLAM
Jürges, C., Dölken, L., & Erhard, F. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty256 · Cited by 137 · see citing works
Stress-induced nuclear condensation of NELF drives transcriptional downregulation
Rawat, P., Boehning, M., Hummel, B., Aprile-Garcia, F., Pandit, A. S., Eisenhardt, N., Khavaran, A., Niskanen, E. A., Vos, S. M., Palvimo, J. J., et al. (2021) · Molecular Cell · doi:10.1016/j.molcel.2021.01.016 · Cited by 137 · see citing works
Occurrence and Functions of m 6 A and Other Covalent Modifications in Plant mRNA
Arribas‐Hernández, L., & Brodersen, P. (2019) · PLANT PHYSIOLOGY · doi:10.1104/pp.19.01156 · Cited by 135 · see citing works
Guirguis, A. A., Ofir-Rosenfeld, Y., Knezevic, K., Blackaby, W., HARDICK, D. J., Chan, Y.-C., Motazedian, A., Gillespie, A., Vassiliadis, D., Lam, E. Y. N., et al. (2023) · Cancer Discovery · doi:10.1158/2159-8290.cd-23-0007 · Cited by 137 · see citing works
Global analyses of the dynamics of mammalian microRNA metabolism
Kingston, E. R., & Bartel, D. P. (2019) · Genome Research · doi:10.1101/gr.251421.119 · Cited by 133 · see citing works
Motorin, Y., & Helm, M. (2019) · Genes · doi:10.3390/genes10010035 · Cited by 126 · see citing works
NASC-seq monitors RNA synthesis in single cells
Hendriks, G., Jung, L. A., Larsson, A. J. M., Lidschreiber, M., Forsman, O. A., Lidschreiber, K., Cramer, P., & Sandberg, R. (2019) · Nature Communications · doi:10.1038/s41467-019-11028-9 · Cited by 117 · see citing works
Using TTchem-seq for profiling nascent transcription and measuring transcript elongation
Gregersen, L. H., Mitter, R., & Svejstrup, J. Q. (2020) · Nature Protocols · doi:10.1038/s41596-019-0262-3 · Cited by 117 · see citing works
Conformation of sister chromatids in the replicated human genome
Mitter, M., Gasser, C., Takács, Z., Langer, C. C. H., Tang, W., Jessberger, G., Beales, C. T., Neuner, E., Ameres, S. L., Peters, J., et al. (2020) · Nature · doi:10.1038/s41586-020-2744-4 · Cited by 107 · see citing works
Self-citationPredictive models of subcellular localization of long RNAs
Zuckerman, B. M., & Ulitsky, I. (2019) · RNA · doi:10.1261/rna.068288.118 · Cited by 115 · see citing works
Translation and mRNA Stability Control
Wu, Q., & Bazzini, A. (2023) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-052621-091808 · Cited by 117 · see citing works
Structural basis for piRNA targeting
Anzelon, T. A., Chowdhury, S., Hughes, S. M., Xiao, Y., Lander, G. C., & MacRae, I. J. (2021) · Nature · doi:10.1038/s41586-021-03856-x · Cited by 113 · see citing works
Sun, Y., & Chen, Y.-Q. (2020) · Journal of Hematology & Oncology · doi:10.1186/s13045-020-00945-8 · Cited by 108 · see citing works
ELAVL1 Primarily Couples mRNA Stability with the 3’UTRs of Interferon Stimulated Genes
Rothamel, K. L., Arcos, S., Kim, B., Reasoner, C., Lisy, S. M., Mukherjee, N., & Ascano, M. (2020) · Cell Reports · doi:10.1016/j.celrep.2021.109178 · Cited by 89 · see citing works
Translation‐coupled mRNA quality control mechanisms
Monaghan, L., Longman, D., & Cáceres, J. F. (2023) · The EMBO Journal · doi:10.15252/embj.2023114378 · Cited by 98 · see citing works
mRNA stability and m6A are major determinants of subcellular mRNA localization in neurons
Loedige, I., Baranovskii, A., Mendonsa, S., Dantsuji, S., Popitsch, N. P., Breimann, L., Zerna, N., Cherepanov, V., Milek, M., Ameres, S. L., et al. (2023) · Molecular Cell · doi:10.1016/j.molcel.2023.06.021 · Cited by 96 · see citing works
Self-citationm6A sites in the coding region trigger translation-dependent mRNA decay
Zhou, Y., Ćorović, M., Hoch-Kraft, P., Meiser, N., Mesitov, M. V., Körtel, N., Back, H., Vries, I. S. N., Katti, K., Obrdlík, A., et al. (2024) · Molecular Cell · doi:10.1016/j.molcel.2024.10.033 · Cited by 97 · see citing works
BRD4 orchestrates genome folding to promote neural crest differentiation
Linares-Saldana, R., Kim, W., Bolar, N. A., Zhang, H., Koch-Bojalad, B. A., Yoon, S., Shah, P. P., Karnay, A. M., Park, D. S., Luppino, J. M., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00934-8 · Cited by 87 · see citing works
NAT10 Is Involved in Cardiac Remodeling Through ac4C-Mediated Transcriptomic Regulation
Shi, J., Yang, C., Zhang, J., Zhao, K., Li, P., Kong, C., Wu, X., Sun, H., Zheng, R., Sun, W. Y., et al. (2023) · Circulation Research · doi:10.1161/circresaha.122.322244 · Cited by 93 · see citing works
DNA-guided transcription factor cooperativity shapes face and limb mesenchyme
Kim, S., Morgunova, E. Y., Naqvi, S., Goovaerts, S., Bader, M., Koska, M., Popov, A. N., Luong, C., Pogson, A. N., Swigut, T., et al. (2024) · Cell · doi:10.1016/j.cell.2023.12.032 · Cited by 81 · see citing works
Time-resolved structured illumination microscopy reveals key principles of Xist RNA spreading
Rodermund, L., Coker, H. A., Oldenkamp, R., Wei, G., Bowness, J. S., Rajkumar, B., Nesterova, T. B., Pinto, D. M. S., Schermelleh, L., & Brockdorff, N. (2021) · Science · doi:10.1126/science.abe7500 · Cited by 89 · see citing works
Klein-Brill, A., Joseph-Strauss, D., Chappleboim, A., & Friedman, N. (2019) · Cell Reports · doi:10.1016/j.celrep.2018.12.020 · Cited by 88 · see citing works
Targeted protein degradation reveals a direct role of SPT6 in RNAPII elongation and termination
Narain, A., Bhandare, P., Adhikari, B., Backes, S., Eilers, M., Dölken, L., Schlösser, A., Erhard, F., Baluapuri, A., & Wolf, E. (2021) · Molecular Cell · doi:10.1016/j.molcel.2021.06.016 · Cited by 80 · see citing works
A neural m6A/Ythdf pathway is required for learning and memory in Drosophila
Kan, L., Ott, S., Joseph, B. J., Park, E. S., Dai, W. H., Kleiner, R. E., Claridge‐Chang, A., & Lai, E. C. (2021) · Nature Communications · doi:10.1038/s41467-021-21537-1 · Cited by 87 · see citing works
MYC amplifies gene expression through global changes in transcription factor dynamics
Patange, S., Ball, D. A., Wan, Y., Karpova, T., Girvan, M., Levens, D., & Larson, D. R. (2022) · Cell Reports · doi:10.1016/j.celrep.2021.110292 · Cited by 86 · see citing works
mRNA ageing shapes the Cap2 methylome in mammalian mRNA
Despic, V., & Jaffrey, S. R. (2023) · Nature · doi:10.1038/s41586-022-05668-z · Cited by 85 · see citing works
Modulating Androgen Receptor-Driven Transcription in Prostate Cancer with Selective CDK9 Inhibitors
Richters, A., Doyle, S. K., Freeman, D. B., Lee, C., Leifer, B. S., Jagannathan, S., Kabinger, F., Koren, J. V., Struntz, N. B., Urgiles, J., et al. (2021) · Cell Chemical Biology · doi:10.1016/j.chembiol.2020.10.001 · Cited by 86 · see citing works
Multi-Omics Approaches in Immunological Research
Chu, X., Zhang, B., Koeken, V. A. C. M., Gupta, M. K., & Li, Y. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.668045 · Cited by 86 · see citing works
Parsing the role of NSP1 in SARS-CoV-2 infection
Fisher, T., Gluck, A., Narayanan, K., Kuroda, M., Nachshon, A., Hsu, J. C., Halfmann, P., Yahalom-Ronen, Y., Tamir, H., Finkel, Y., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110954 · Cited by 84 · see citing works
Ietswaart, R., Smalec, B. M., Xu, A., Choquet, K., McShane, E., Jowhar, Z. M., Guegler, C. K., Baxter-Koenigs, A. R., West, E. R., Fu, B. X. H., et al. (2024) · Molecular Cell · doi:10.1016/j.molcel.2024.06.008 · Cited by 83 · see citing works
RNA damage compartmentalization by DHX9 stress granules
Zhou, Y., Panhale, A., Shvedunova, M., Balan, M., Gomez-Auli, A., Holz, H., Seyfferth, J., Helmstädter, M., Kayser, S., Zhao, Y., et al. (2024) · Cell · doi:10.1016/j.cell.2024.02.028 · Cited by 83 · see citing works
Determining mRNA half-lives on a transcriptome-wide scale
Lugowski, A., Nicholson, B. L., & Rissland, O. S. (2017) · Methods · doi:10.1016/j.ymeth.2017.12.006 · Cited by 77 · see citing works
Single-molecule imaging reveals translation-dependent destabilization of mRNAs
Dave, P., Roth, G., Griesbach, E., Matějů, D., Hochstoeger, T., & Chao, J. (2023) · Molecules and Cells · doi:10.1016/j.molcel.2023.01.013 · Cited by 66 · see citing works
Analytical Methods for Deciphering RNA Modifications
Chen, B., Yuan, B., & Feng, Y. (2018) · Analytical Chemistry · doi:10.1021/acs.analchem.8b04078 · Cited by 74 · see citing works
iCodon customizes gene expression based on the codon composition
Diez, M., Medina-Muñoz, S. G., Castellano, L. A., Pescador, G. D. S., Wu, Q., & Bazzini, A. (2022) · Scientific Reports · doi:10.1038/s41598-022-15526-7 · Cited by 74 · see citing works
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 · see citing works
Crosstalk between codon optimality and cis-regulatory elements dictates mRNA stability
Medina-Muñoz, S. G., Kushawah, G., Castellano, L. A., Diez, M., DeVore, M. L., Salazar, M. J. B., & Bazzini, A. (2021) · Genome biology · doi:10.1186/s13059-020-02251-5 · Cited by 69 · see citing works
Margvelani, G., Maquera, K. A. A., Welden, J. R., Rodgers, D. W., & Stamm, S. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1167 · Cited by 77 · see citing works
Ushering in a new era of single-cell transcriptomics in bacteria
Homberger, C., Barquist, L., & Vogel, J. (2022) · microLife · doi:10.1093/femsml/uqac020 · Cited by 65 · see citing works
Müller, M. B. D., Kasturi, P., Jayaraj, G. G., & Hartl, F. U. (2023) · Cell · doi:10.1016/j.cell.2023.05.035 · Cited by 78 · see citing works
A kinetic dichotomy between mitochondrial and nuclear gene expression processes
McShane, E., Couvillion, M., Ietswaart, R., Prakash, G., Smalec, B. M., Soto, I. C., Baxter‐Koenigs, A. R., Choquet, K., & Churchman, L. S. (2024) · Molecular Cell · doi:10.1016/j.molcel.2024.02.028 · Cited by 67 · see citing works
Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data
Blumberg, A., Zhao, Y., Huang, Y.-F., Dukler, N., Rice, E. J., Chivu, A. G., Krumholz, K., Danko, C. G., & Siepel, A. C. (2021) · BMC Biology · doi:10.1186/s12915-021-00949-x · Cited by 66 · see citing works
Marinov, G. K., Trevino, A. E., Xiang, T., Kundaje, A. B., Grossman, A. R., & Greenleaf, W. J. (2021) · Nature Genetics · doi:10.1038/s41588-021-00848-5 · Cited by 65 · see citing works
Trisomy of a Down Syndrome Critical Region Globally Amplifies Transcription via HMGN1 Overexpression
Mowery, C. T., Reyes, J. M., Cabal‐Hierro, L., Higby, K. J., Karlin, K. L., Wang, J. H., Kimmerling, R. J., Cejas, P., Lim, K., Li, H., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.10.061 · Cited by 64 · see citing works
Native molecule sequencing by nano-ID reveals synthesis and stability of RNA isoformsPreprint
Maier, K. C., Gressel, S., Cramer, P., & Schwalb, B. (2020) · Genome Research · doi:10.1101/gr.257857.119 · Cited by 64 · see citing works
Analysis of RNA Modifications by Second- and Third-Generation Deep Sequencing: 2020 Update
Motorin, Y., & Marchand, V. (2021) · Genes · doi:10.3390/genes12020278 · Cited by 63 · see citing works
Alternative polyadenylation by sequential activation of distal and proximal PolyA sites
Tang, P., Yang, Y., Li, G., Huang, L., Wen, M., Ruan, W., Guo, X., Zhang, C., Zuo, X., Luo, D., et al. (2022) · Nature Structural & Molecular Biology · doi:10.1038/s41594-021-00709-z · Cited by 63 · see citing works
LSD1 inhibition induces differentiation and cell death in Merkel cell carcinoma
Leiendecker, L., Jung, P. S., Kręcioch, I., Neumann, T., Schleiffer, A., Mechtler, K., Wiesner, T., & Obenauf, A. C. (2020) · EMBO Molecular Medicine · doi:10.15252/emmm.202012525 · Cited by 62 · see citing works
Self-citationZepeda-Martínez, J. A., Pribitzer, C., Wang, J., Bsteh, D., Golumbeanu, S., Zhao, Q., Burkard, T. R., Reichholf, B., Rhie, S. K., Jude, J., et al. (2020) · Science Advances · doi:10.1126/sciadv.aax5692 · Cited by 62 · see citing works
Self-citationSingle‐Cell Sequencing Methodologies: From Transcriptome to Multi‐Dimensional Measurement
Chen, Y., Song, J. T., Ruan, Q., Zeng, X., Wu, L., Cai, L., Wang, X., & Yang, C. J. (2021) · Small Methods · doi:10.1002/smtd.202100111 · Cited by 59 · see citing works
Transcriptional kinetics and molecular functions of long noncoding RNAs
Johnsson, P., Ziegenhain, C., Hartmanis, L., Hendriks, G., Hagemann-Jensen, M., Reinius, B., & Sandberg, R. (2022) · Nature Genetics · doi:10.1038/s41588-022-01014-1 · Cited by 61 · see citing works
Genetic circuit characterization by inferring RNA polymerase movement and ribosome usage
Borujeni, A. E., Zhang, J., Doosthosseini, H., Nielsen, A. A. K., & Voigt, C. A. (2020) · Nature Communications · doi:10.1038/s41467-020-18630-2 · Cited by 61 · see citing works
Circular RNAs: The Brain Transcriptome Comes Full Circle
Gokoolparsadh, A., Loy, C. T., Halliday, G. M., & Voineagu, I. (2020) · Trends in Neurosciences · doi:10.1016/j.tins.2020.07.007 · Cited by 60 · see citing works
Spatio-temporal mRNA tracking in the early zebrafish embryo
Holler, K., Neuschulz, A., Drewe-Boß, P., Mintcheva, J., Spanjaard, B., Arsiè, R., Ohler, U., Landthaler, M., & Junker, J. P. (2021) · Nature Communications · doi:10.1038/s41467-021-23834-1 · Cited by 55 · see citing works
Specific tRNAs promote mRNA decay by recruiting the CCR4-NOT complex to translating ribosomes
Zhu, X., Cruz, V. E., Zhang, H., Erzberger, J. P., & Mendell, J. T. (2024) · Science · doi:10.1126/science.adq8587 · Cited by 60 · see citing works
Berry, S. M., Müller, M., Rai, A., & Pelkmans, L. (2022) · Cell Systems · doi:10.1016/j.cels.2022.04.005 · Cited by 53 · see citing works
Bhat, P., Cabrera-Quio, L. E., Herzog, V. A., Fasching, N., Pauli, A., & Ameres, S. L. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112070 · Cited by 57 · see citing works
Self-citationX-chromosome upregulation is driven by increased burst frequency
Larsson, A. J. M., Coucoravas, C., Sandberg, R., & Reinius, B. (2019) · Nature Structural & Molecular Biology · doi:10.1038/s41594-019-0306-y · Cited by 50 · see citing works
RAD51 protects human cells from transcription-replication conflicts
Bhowmick, R., Lerdrup, M., Gadi, S. A., Rossetti, G. G., Singh, M. I., Liu, Y., Halazonetis, T. D., & Hickson, I. D. (2022) · Molecular Cell · doi:10.1016/j.molcel.2022.07.010 · Cited by 54 · see citing works
The ADAR1 editome reveals drivers of editing-specificity for ADAR1-isoforms
Kleinová, R., Rajendra, V., Leuchtenberger, A. F., Giudice, C. L., Vesely, C., Kapoor, U., Andrea Tanzer, A., Derdak, S. V., Picardi, E., & Jantsch, M. F. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad265 · Cited by 55 · see citing works
Time-resolved profiling of RNA binding proteins throughout the mRNA life cycle
Choi, Y., Um, B., Na, Y., Kim, J., Kim, V. N., & Kim, V. N. (2024) · Molecular Cell · doi:10.1016/j.molcel.2024.03.012 · Cited by 55 · see citing works
Duffy, E. E., Schofield, J. A., & Simon, M. D. (2018) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1513 · Cited by 51 · see citing works
- Authors
- Herzog, V. A., Reichholf, B., Neumann, T., Rescheneder, P., Bhat, P., Burkard, T. R., Wlotzka, W., von Haeseler, A., Zuber, J., & Ameres, S. L.
- Affiliations
- Institute of Molecular Biotechnology (AT)
- Research Institute of Molecular Pathology (AT)
- Max Perutz Labs (AT)
- Corresponding author
- Ameres, Stefan L.
- Venue
- Nature Methods
- Publisher
- openRxiv
- Published
- 2017-08-17
- Volume
- 14
- Issue
- 12
- Pages
- 1198-1204
- ISSN
- 1548-7091 (ISSN-L)
- PMC
- PMC5712218
- OpenAlex
- W2759506905
- Cited by
- 622
- References
- 66
- Citations by year
- 2026: 80 · 2025: 79 · 2024: 117 · 2023: 84 · 2022: 71 · 2021: 73 · 2020: 52 · 2019: 44 · 2018: 21 · 2017: 1
- FWCI
- 13.19
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Nature Methods (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Österreichischen Akademie der Wissenschaften
- Austrian Science Fund (W12-7-B09, Y-733-B22 START, F4322)
- Wirtschaftsagentur Wien
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Keywords
- SLAM-seq, RNA turnover, RNA metabolism, RNA polymerase II transcription, gene expression dynamics, microRNA, N6-methyladenosine, post-transcriptional regulation, mouse embryonic stem cells, enhancer activity
- MeSH terms
- Alkylation, RNA, RNA Polymerase II, RNA Processing, Post-Transcriptional, Sulfhydryl Compounds, Thiouridine, Gene Expression Profiling, Gene Regulatory Networks, Embryonic Stem Cells, High-Throughput Screening Assays, High-Throughput Nucleotide Sequencing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review