ArticleNucleic acids research2012
Computational inference of mRNA stability from histone modification and transcriptome profiles.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Differential contribution to gene expression prediction of histone modifications at enhancers or promoters.PLoS computational biology · 2021Article
- Dynamics of transcriptional and post-transcriptional regulation.Briefings in bioinformatics · 2021Review
- Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters.Epigenetics & chromatin · 2018Article
- The integrated landscape of causal genes and pathways in schizophrenia.Translational psychiatry · 2018Article
- Global intron retention mediated gene regulation during CD4+ T cell activation.Nucleic acids research · 2016Article
- Analysis of RNA decay factor mediated RNA stability contributions on RNA abundance.BMC genomics · 2015Article
- Predicting expression: the complementary power of histone modification and transcription factor binding data.Epigenetics & chromatin · 2014Article
- Inferring chromatin-bound protein complexes from genome-wide binding assays.Genome research · 2013Article
- Uniform, optimal signal processing of mapped deep-sequencing data.Nature biotechnology · 2013Article
- Influence of untranslated regions on retroviral mRNA transfer and expression.BMC biotechnology · 2013Article
- Coordinated Regulation of PPARγ Expression and Activity through Control of Chromatin Structure in Adipogenesis and Obesity.PPAR research · 2012Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Histone modifications play important roles in regulating eukaryotic gene expression and have been used to model expression levels. Here, we present a regression model to systematically infer mRNA stability by comparing transcriptome profiles with ChIP-seq of H3K4me3, H3K27me3 and H3K36me3. The results from multiple human and mouse cell lines show that the inferred unstable mRNAs have significantly longer 3'Untranslated Regions (UTRs) and more microRNA binding sites within 3'UTR than the inferred stable mRNAs. Regression residuals derived from RNA-seq, but not from GRO-seq, are highly correlated with the half-lives measured by pulse-labeling experiments, supporting the rationale of our inference. Whereas, the functions enriched in the inferred stable and unstable mRNAs are consistent with those from pulse-labeling experiments, we found the unstable mRNAs have higher cell-type specificity under functional constraint. We conclude that the systematical use of histone modifications can differentiate non-expressed mRNAs from unstable mRNAs, and distinguish stable mRNAs from highly expressed ones. In summary, we represent the first computational model of mRNA stability inference that compares transcriptome and epigenome profiles, and provides an alternative strategy for directing experimental measurements.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.