Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 210

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Translating mRNAs strongly correlate to proteins in a multivariate manner and their translation ratios are phenotype specific

Open access
Wang, Tong, Cui, Yizhi, Jin, Jingjie, Guo, Jiahui, Wang, Guibin, Yin, Xingfeng, He, Qing-Yu, Zhang, Gong·2013·Nucleic Acids Research

Abstract

As a well-known phenomenon, total mRNAs poorly correlate to proteins in their abundances as reported. Recent findings calculated with bivariate models suggested even poorer such correlation, whereas focusing on the translating mRNAs (ribosome nascent-chain complex-bound mRNAs, RNC-mRNAs) subset. In this study, we analysed the relative abundances of mRNAs, RNC-mRNAs and proteins on genome-wide scale, comparing human lung cancer A549 and H1299 cells with normal human bronchial epithelial (HBE) cells, respectively. As discovered, a strong correlation between RNC-mRNAs and proteins in their relative abundances could be established through a multivariate linear model by integrating the mRNA length as a key factor. The R(2) reached 0.94 and 0.97 in A549 versus HBE and H1299 versus HBE comparisons, respectively. This correlation highlighted that the mRNA length significantly contributes to the translational modulation, especially to the translational initiation, favoured by its correlation with the mRNA translation ratio (TR) as observed. We found TR is highly phenotype specific, which was substantiated by both pathway analysis and biased TRs of the splice variants of BDP1 gene, which is a key transcription factor of transfer RNAs. These findings revealed, for the first time, the intrinsic and genome-wide translation modulations at translatomic level in human cells at steady-state, which are tightly correlated to the protein abundance and functionally relevant to cellular phenotypes.

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 · 10.1093/nar/gkt178

Cites

12 of 12 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

Show all 12 references

Cited by

See all 210

Metadata

Authors
Wang, T., Cui, Y., Jin, J., Guo, J., Wang, G., Yin, X., He, Q.-Y., & Zhang, G.
Venue
Nucleic Acids Research
Published
2013-03-20
Volume
41
Issue
9
Pages
4743-4754
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W1980599684
Cited by
210
References
12
FWCI
4.30
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: Translating mRNAs strongly correlate to proteins in a multivariate manner and their translation ratios are phenotype specific. https://app.cochat.ai/papers/10.1093/nar/gkt178
The paper
Wang, T., Cui, Y., Jin, J., Guo, J., Wang, G., Yin, X., He, Q.-Y., & Zhang, G. (2013). Translating mRNAs strongly correlate to proteins in a multivariate manner and their translation ratios are phenotype specific. Nucleic Acids Research. https://doi.org/10.1093/nar/gkt178

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.