Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 260

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

TimeLapse-seq: adding a temporal dimension to RNA sequencing through nucleoside recoding

Open access
Schofield, Jeremy A, Duffy, Erin E, Kiefer, Lea, Sullivan, Meaghan C, Simon, Matthew D·2018·Nature Methods

Abstract

RNA sequencing (RNA-seq) offers a snapshot of cellular RNA populations, but not temporal information about the sequenced RNA. Here we report TimeLapse-seq, which uses oxidative-nucleophilic-aromatic substitution to convert 4-thiouridine into cytidine analogs, yielding apparent U-to-C mutations that mark new transcripts upon sequencing. TimeLapse-seq is a single-molecule approach that is adaptable to many applications and reveals RNA dynamics and induced differential expression concealed in traditional RNA-seq.

Overview

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/nmeth.4582

Cites

9 of 9 references verified0 citation errors · 0 not checkable

Statistics

Verification

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.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 33

  1. Bhatt, D.M. et al. Transcript dynamics of proinflammatory genes revealed by sequence analysis of subcellular RNA fractions. Cell 150, 279–290 (2012). · DOI · Paper page
  2. Menet, J.S., Rodriguez, J., Abruzzi, K.C. & Rosbash, M. Nascent-Seq reveals novel features of mouse circadian transcriptional regulation. eLife 1, e00011 (2012). · DOI · Paper page
  3. Wada, Y. et al. A wave of nascent transcription on activated human genes. Proc. Natl. Acad. Sci. USA 106, 18357–18361 (2009). · DOI
  4. Schwalb, B. et al. TT-seq maps the human transient transcriptome. Science 352, 1225–1228 (2016). · DOI · Paper page
  5. Rabani, M. et al. Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells. Nat. Biotechnol. 29, 436–442 (2011). · DOI · Paper page
  6. Duffy, E.E. et al. Tracking distinct RNA populations using efficient and reversible covalent chemistry. Mol. Cell 59, 858–866 (2015). · DOI · Paper page
  7. Melvin, W.T., Milne, H.B., Slater, A.A., Allen, H.J. & Keir, H.M. Incorporation of 6-thioguanosine and 4-thiouridine into RNA. Application to isolation of newly synthesised RNA by affinity chromatography. Eur. J. Biochem. 92, 373–379 (1978). · DOI
  8. Hafner, M. et al. Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell 141, 129–141 (2010). · DOI · Paper page
  9. Mishima, Y. & Steitz, J.A. Site-specific crosslinking of 4-thiouridine-modified human tRNA(3Lys) to reverse transcriptase from human immunodeficiency virus type I. EMBO J. 14, 2679–2687 (1995). · DOI
  10. Yano, M. & Hayatsu, H. Permanganate oxidation of 4-thiouracil derivatives. Isolation and properties of I-substituted 2-pyrimidone 4-sulfonates. Biochim. Biophys. Acta 199, 303–315 (1970). · doi:10.1016/0005-2787(70)90073-0
  11. Ziff, E.B. & Fresco, J.R. A method for locating 4-thiouridylate in the primary structure of transfer ribonucleic acids. Biochemistry 8, 3242–3248 (1969). · doi:10.1021/bi00836a016
  12. Dai, Q. et al. Nm-seq maps 2′-O-methylation sites in human mRNA with base precision. Nat. Methods 14, 695–698 (2017). · DOI · Paper page
  13. Mukherjee, N. et al. Integrative classification of human coding and noncoding genes through RNA metabolism profiles. Nat. Struct. Mol. Biol. 24, 86–96 (2017). · DOI · Paper page
  14. Trinklein, N.D., Murray, J.I., Hartman, S.J., Botstein, D. & Myers, R.M. The role of heat shock transcription factor 1 in the genome-wide regulation of the mammalian heat shock response. Mol. Biol. Cell 15, 1254–1261 (2004). · DOI · Paper page
  15. Mahat, D.B., Salamanca, H.H., Duarte, F.M., Danko, C.G. & Lis, J.T. Mammalian heat shock response and mechanisms underlying its genome-wide transcriptional regulation. Mol. Cell 62, 63–78 (2016). · DOI · Paper page
  16. Shalgi, R., Hurt, J.A., Lindquist, S. & Burge, C.B. Widespread inhibition of posttranscriptional splicing shapes the cellular transcriptome following heat shock. Cell Rep. 7, 1362–1370 (2014). · DOI · Paper page
  17. Russo, J., Heck, A.M., Wilusz, J. & Wilusz, C.J. Metabolic labeling and recovery of nascent RNA to accurately quantify mRNA stability. Methods 120, 39–48 (2017). · DOI
  18. Friedel, C.C., Dölken, L., Ruzsics, Z., Koszinowski, U.H. & Zimmer, R. Conserved principles of mammalian transcriptional regulation revealed by RNA half-life. Nucleic Acids Res. 37, e115 (2009). · DOI · Paper page
  19. Gelsi-Boyer, V. et al. Mutations of polycomb-associated gene ASXL1 in myelodysplastic syndromes and chronic myelomonocytic leukaemia. Br. J. Haematol. 145, 788–800 (2009). · DOI · Paper page
  20. Scotti, M.M. & Swanson, M.S. RNA mis-splicing in disease. Nat. Rev. Genet. 17, 19–32 (2016). · DOI · Paper page
  21. Herzog, V.A. et al. Thiol-linked alkylation of RNA to assess expression dynamics. Nat. Methods 14, 1198–1204 (2017). · DOI · Paper page
  22. Schofield et al. Protocol in Protocol Exchange DOI https://doi.org/10.1038/protex.2018.004 . · doi:10.1038/protex.2018.004
  23. Langmead, B. & Salzberg, S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012). · DOI · Paper page
  24. Sexton, A.N., Wang, P.Y., Rutenberg-Schoenberg, M. & Simon, M.D. Interpreting reverse transcriptase termination and mutation events for greater insight into the chemical probing of RNA. Biochemistry 56, 4713–4721 (2017). · DOI
  25. Siegfried, N.A., Busan, S., Rice, G.M., Nelson, J.A. & Weeks, K.M. RNA motif discovery by SHAPE and mutational profiling (SHAPE-MaP). Nat. Methods 11, 959–965 (2014). · DOI · Paper page
  26. Xu, H. et al. FastUniq: a fast de novo duplicates removal tool for paired short reads. PLoS One 7, e52249 (2012). · DOI · Paper page
  27. Kim, D., Langmead, B. & Salzberg, S.L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015). · DOI · Paper page
  28. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009). · DOI · Paper page
  29. Love, M.I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014). · DOI · Paper page
  30. Robinson, J.T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011). · DOI · Paper page
  31. Van Herreweghe, E. et al. Dynamic remodelling of human 7SK snRNP controls the nuclear level of active P-TEFb. EMBO J. 26, 3570–3580 (2007). · DOI
  32. Thomas, P.D. et al. PANTHER: a library of protein families and subfamilies indexed by function. Genome Res. 13, 2129–2141 (2003). · DOI · Paper page
  33. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate - a practical and powerful approach to multiple testing. J. R. Stat. Soc. B Stat. Methodol. 57, 289–300 (1995). · DOI · Paper page

Cited by

See all 260

Metadata

Authors
Schofield, J. A., Duffy, E. E., Kiefer, L., Sullivan, M. C., & Simon, M. D.
Venue
Nature Methods
Published
2018-01-22
Volume
15
Issue
3
Pages
221-225
ISSN
  • 1548-7091 (ISSN-L)
  • 1548-7105
OpenAlex
W2784500348
Cited by
260
References
9
FWCI
7.93
Type
journal article
Language
en
Open access
green
Licence
www.springer.com/tdm (tdm)

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

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.