The DOI matches its Crossref record; 88 of the 88 references it cites were found in a registry or an index.
RNA 5-Methylcytosine Facilitates the Maternal-to-Zygotic Transition by Preventing Maternal mRNA Decay
Open accessAbstract
The maternal-to-zygotic transition (MZT) is a conserved and fundamental process during which the maternal environment is converted to an environment of embryonic-driven development through dramatic reprogramming. However, how maternally supplied transcripts are dynamically regulated during MZT remains largely unknown. Herein, through genome-wide profiling of RNA 5-methylcytosine (m5C) modification in zebrafish early embryos, we found that m5C-modified maternal mRNAs display higher stability than non-m5C-modified mRNAs during MZT. We discovered that Y-box binding protein 1 (Ybx1) preferentially recognizes m5C-modified mRNAs through π-π interactions with a key residue, Trp45, in Ybx1's cold shock domain (CSD), which plays essential roles in maternal mRNA stability and early embryogenesis of zebrafish. Together with the mRNA stabilizer Pabpc1a, Ybx1 promotes the stability of its target mRNAs in an m5C-dependent manner. Our study demonstrates an unexpected mechanism of RNA m5C-regulated maternal mRNA stabilization during zebrafish MZT, highlighting the critical role of m5C mRNA modification in early development.
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
Trimmomatic: a flexible trimmer for Illumina sequence data
Bolger, A. M., Lohse, M., & Usadel, B. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu170 · Cited by 65,548
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
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
Coot : model-building tools for molecular graphics
Emsley, P., & Cowtan, K. (2004) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444904019158 · Cited by 30,571
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
PHENIX : a comprehensive Python-based system for macromolecular structure solution
Adams, P. D., Afonine, P. V., Bunkóczi, G., Chen, V. B., Davis, I. W., Echols, N., Headd, J. J., Hung, L.-W., Kapral, G. J., Grosse-Kunstleve, R. W., et al. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909052925 · Cited by 23,716
HTSeq—a Python framework to work with high-throughput sequencing data
Anders, S., Pyl, P. T., & Huber, W. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu638 · Cited by 21,464
Phaser crystallographic software
McCoy, A. J., Grosse-Kunstleve, R. W., Adams, P. D., Winn, M. D., Storoni, L. C., & Read, R. J. (2007) · Journal of Applied Crystallography · doi:10.1107/s0021889807021206 · Cited by 20,612
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
Metascape provides a biologist-oriented resource for the analysis of systems-level datasets
Zhou, Y., Zhou, B., Pache, L., Chang, M., Khodabakhshi, A. H., Tanaseichuk, O., Benner, C., & Chanda, S. K. (2019) · Nature Communications · doi:10.1038/s41467-019-09234-6 · Cited by 14,611
Cited by
The epitranscriptome beyond m6A
Wiener, D., & Schwartz, S. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-020-00295-8 · Cited by 709
Mapping the epigenetic modifications of DNA and RNA
Zhao, L.-Y., Song, J., Liu, Y., Song, C.-X., & Yi, C. (2020) · Protein & Cell · doi:10.1007/s13238-020-00733-7 · Cited by 361
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
Self-citationThe proteins of mRNA modification: writers, readers, and erasers
Flamand, M. N., Tegowski, M., & Meyer, K. D. (2023) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-052521-035330 · Cited by 164
TET2-mediated mRNA demethylation regulates leukemia stem cell homing and self-renewal
Li, Y., Xue, M., Deng, X., Dong, L., Nguyen, L. X. T., Ren, L., Han, L., Li, C., Xue, J., Zhao, Z., et al. (2023) · Cell Stem Cell · doi:10.1016/j.stem.2023.07.001 · Cited by 110
Self-citation
Metadata
- Authors
- Yang, Y., Wang, L., Han, X., Yang, W.-L., Zhang, M., Ma, H.-L., Sun, B.-F., Li, A., Xia, J., Chen, J., Heng, J., Wu, B., Chen, Y.-S., Xu, J.-W., Yang, X., Yao, H., Sun, J., Lyu, C., Wang, H.-L., Huang, Y., Sun, Y.-P., Zhao, Y.-L., Meng, A., Ma, J., Liu, F., & Yang, Y.-G.
- Venue
- Molecular Cell
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 75
- Issue
- 6
- Pages
- 1188-1202.e11
- ISSN
- 1097-2765 (ISSN-L)
- OpenAlex
- W2964888213
- Cited by
- 432
- References
- 88
- FWCI
- 13.11
- Type
- journal article
- Language
- en
- Open access
- bronze
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: RNA 5-Methylcytosine Facilitates the Maternal-to-Zygotic Transition by Preventing Maternal mRNA Decay. https://app.cochat.ai/papers/10.1016/j.molcel.2019.06.033
- The paper
- Yang, Y., Wang, L., Han, X., Yang, W.-L., Zhang, M., Ma, H.-L., Sun, B.-F., Li, A., Xia, J., Chen, J., Heng, J., Wu, B., Chen, Y.-S., Xu, J.-W., Yang, X., Yao, H., Sun, J., Lyu, C., Wang, H.-L., . . . Yang, Y.-G. (2019). RNA 5-Methylcytosine Facilitates the Maternal-to-Zygotic Transition by Preventing Maternal mRNA Decay. Molecular Cell. https://doi.org/10.1016/j.molcel.2019.06.033
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.