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Computational inference of mRNA stability from histone modification and transcriptome profiles.

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.

SUBMITTER: Wang C

PROVIDER: S-EPMC3413115 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Computational inference of mRNA stability from histone modification and transcriptome profiles.

Wang Chengyang C Tian Rui R Zhao Qian Q Xu Han H Meyer Clifford A CA Li Cheng C Zhang Yong Y Liu X Shirley XS

Nucleic acids research 20120410 14

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 ...[more]

PMID: 22495509

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Project description:In vitro maturation (IVM) refers to the process of developing immature oocytes into the mature in vitro under the microenvironment analogous to follicle fluid. It is an important technique for patients with polycystic ovary syndrome and, especially, those young patients with the need of fertility preservation. However, as the mechanisms of oocyte maturation have not been fully understood yet, the cultivation efficiency of IVM is not satisfactory. It was confirmed in our previous study that oocyte maturation was impaired after N-acetyltransferase 10 (NAT10) knockdown (KD). In the present study, we further explored the transcriptome alteration of NAT10-depleted oocytes and found that O-GlcNAcase(OGA) was an important target gene for NAT10-mediated ac4C modification in oocyte maturation. NAT10 might regulate OGA stability and expression by suppressing its degradation. To find out whether the influence of NAT10-mediated ac4C on oocyte maturation was mediated by OGA, we further explored the role of OGA in IVM. After knocking down OGA of oocytes, oocyte maturation was inhibited. In addition, as oocytes matured, OGA expression increased and, conversely, O-linked N-acetylglucosamine (O-GlcNAc) level decreased. On the basis of NAT10 KD transcriptome and OGA KD transcriptome data, NAT10-mediated ac4C modification of OGA might play a role through G protein–coupled receptors, molecular transduction, nucleosome DNA binding, and other mechanisms in oocyte maturation. Rsph6a, Gm7788, Gm41780, Trpc7, Gm29036, and Gm47144 were potential downstream genes. In conclusion, NAT10 maintained the stability of OGA transcript by ac4C modification on it, thus positively regulating IVM. Moreover, our study revealed the regulation mechanisms of oocytes maturation and provided reference for improving IVM outcomes. At the same time, the interaction between mRNA ac4C modification and protein O-GlcNAc modification was found for the first time, which enriched the regulation network of oocyte maturation.

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Computational inference of mRNA stability from histone modification and transcriptome profiles.

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Computational inference of mRNA stability from histone modification and transcriptome profiles.

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