The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Measuring Absolute RNA Copy Numbers at High Temporal Resolution Reveals Transcriptome Kinetics in Development
Open accessAbstract
Transcript regulation is essential for cell function, and misregulation can lead to disease. Despite technologies to survey the transcriptome, we lack a comprehensive understanding of transcript kinetics, which limits quantitative biology. This is an acute challenge in embryonic development, where rapid changes in gene expression dictate cell fate decisions. By ultra-high-frequency sampling of Xenopus embryos and absolute normalization of sequence reads, we present smooth gene expression trajectories in absolute transcript numbers. During a developmental period approximating the first 8 weeks of human gestation, transcript kinetics vary by eight orders of magnitude. Ordering genes by expression dynamics, we find that "temporal synexpression" predicts common gene function. Remarkably, a single parameter, the characteristic timescale, can classify transcript kinetics globally and distinguish genes regulating development from those involved in cellular metabolism. Overall, our analysis provides unprecedented insight into the reorganization of maternal and embryonic transcripts and redefines our ability to perform quantitative biology.
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.
Integrity signals
Registry
Cites
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.
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
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
Trapnell, C., Williams, B. A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M. J., Salzberg, S. L., Wold, B. J., & Pachter, L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1621 · Cited by 15,556
Gaussian Processes for Machine Learning
Rasmussen, C. E., & Williams, C. K. I. (2005) · doi:10.7551/mitpress/3206.001.0001 · Cited by 11,705
Spatial reconstruction of single-cell gene expression data
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055
Zebrafish MiR-430 Promotes Deadenylation and Clearance of Maternal mRNAs
Giraldez, A. J., Mishima, Y., Rihel, J., Grocock, R. J., Van Dongen, S., Inoue, K., Enright, A. J., & Schier, A. F. (2006) · Science · doi:10.1126/science.1122689 · Cited by 1,647
MicroRNAs Regulate Brain Morphogenesis in Zebrafish
Giraldez, A. J., Cinalli, R. M., Glasner, M. E., Enright, A. J., Thomson, J. M., Baskerville, S., Hammond, S. M., Bartel, D. P., & Schier, A. F. (2005) · Science · doi:10.1126/science.1109020 · Cited by 1,315
Modelling and analysis of gene regulatory networks
Karlebach, G., & Shamir, R. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2503 · Cited by 1,296
Quantitative single-cell RNA-seq with unique molecular identifiers
Islam, S., Zeisel, A., Joost, S., La Manno, G., Zajac, P., Kasper, M., Lönnerberg, P., & Linnarsson, S. (2014) · Nature Methods · doi:10.1038/nmeth.2772 · Cited by 1,183 · cited 1×
“Previous reports have used spike-ins to normalize for sequencing depth, to control for technical variability, and to calculate estimates of absolute transcript numbers (Brennecke et al., 2013; Islam et al., 2014; Junker et al., 2014; Risso et al., 2014).”
BackgroundComputational and analytical challenges in single-cell transcriptomics
Stegle, O., Teichmann, S. A., & Marioni, J. C. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3833 · Cited by 1,170
A major developmental transition in early xenopus embryos: II. control of the onset of transcription
Newport, J., & Kirschner, M. (1982) · Cell · doi:10.1016/0092-8674(82)90273-2 · Cited by 1,055
Cited by
SpatialDE: identification of spatially variable genes
Svensson, V., Teichmann, S. A., & Stegle, O. (2018) · Nature Methods · doi:10.1038/nmeth.4636 · Cited by 695
Power analysis of single-cell RNA-sequencing experiments
Svensson, V., Natarajan, K. N., Ly, L.-H., Miragaia, R. J., Labalette, C., Macaulay, I. C., Cvejic, A., & Teichmann, S. A. (2017) · Nature Methods · doi:10.1038/nmeth.4220 · Cited by 568
The maternal-to-zygotic transition revisited
Vastenhouw, N. L., Cao, W. X., & Lipshitz, H. D. (2019) · Development · doi:10.1242/dev.161471 · Cited by 445
A high-resolution mRNA expression time course of embryonic development in zebrafish
White, R. J., Collins, J. E., Sealy, I. M., Wali, N., Dooley, C. M., Digby, Z., Stemple, D. L., Murphy, D. N., Billis, K., Hourlier, T., et al. (2017) · eLife · doi:10.7554/elife.30860 · Cited by 361
Matsunami, M., Suzuki, M., Haramoto, Y., Fukui, A., Inoue, T., Yamaguchi, K., Uchiyama, I., Mori, K., Tashiro, K., Ito, Y., et al. (2019) · DNA Research · doi:10.1093/dnares/dsz003 · Cited by 51
Metadata
- Authors
- Owens, N. D. L., Blitz, I. L., Lane, M. A., Patrushev, I., Overton, J. D., Gilchrist, M. J., Cho, K. W. Y., & Khokha, M. K.
- Venue
- Cell Reports
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 14
- Issue
- 3
- Pages
- 632-647
- ISSN
- 2211-1247 (ISSN-L)
- OpenAlex
- W2230625883
- Cited by
- 191
- References
- 14
- FWCI
- 11.44
- Type
- journal article
- Language
- en
- Open access
- gold
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Measuring Absolute RNA Copy Numbers at High Temporal Resolution Reveals Transcriptome Kinetics in Development. https://app.cochat.ai/papers/10.1016/j.celrep.2015.12.050
- The paper
- Owens, N. D. L., Blitz, I. L., Lane, M. A., Patrushev, I., Overton, J. D., Gilchrist, M. J., Cho, K. W. Y., & Khokha, M. K. (2016). Measuring Absolute RNA Copy Numbers at High Temporal Resolution Reveals Transcriptome Kinetics in Development. Cell Reports. https://doi.org/10.1016/j.celrep.2015.12.050
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.
