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In silico estimation of translation efficiency in human cell lines: potential evidence for widespread translational control.

ABSTRACT: Recently large scale transcriptome and proteome datasets for human cells have become available. A striking finding from these studies is that the level of an mRNA typically predicts no more than 40% of the abundance of protein. This correlation represents the overall figure for all genes. We present here a bioinformatic analysis of translation efficiency - the rate at which mRNA is translated into protein. We have analysed those human datasets that include genome wide mRNA and protein levels determined in the same study. The analysis comprises five distinct human cell lines that together provide comparable data for 8,170 genes. For each gene we have used levels of mRNA and protein combined with protein stability data from the HeLa cell line to estimate translation efficiency. This was possible for 3,990 genes in one or more cell lines and 1,807 genes in all five cell lines. Interestingly, our analysis and modelling shows that for many genes this estimated translation efficiency has considerable consistency between cell lines. Some deviations from this consistency likely result from the regulation of protein degradation. Others are likely due to known translational control mechanisms. These findings suggest it will be possible to build improved models for the interpretation of mRNA expression data. The results we present here provide a view of translation efficiency for many genes. We provide an online resource allowing the exploration of translation efficiency in genes of interest within different cell lines (http://bioanalysis.otago.ac.nz/TranslationEfficiency).

SUBMITTER: Stevens SG

PROVIDER: S-EPMC3584024 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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In silico estimation of translation efficiency in human cell lines: potential evidence for widespread translational control.

Stevens Stewart G SG Brown Chris M CM

PloS one 20130227 2

Recently large scale transcriptome and proteome datasets for human cells have become available. A striking finding from these studies is that the level of an mRNA typically predicts no more than 40% of the abundance of protein. This correlation represents the overall figure for all genes. We present here a bioinformatic analysis of translation efficiency - the rate at which mRNA is translated into protein. We have analysed those human datasets that include genome wide mRNA and protein levels det ...[more]

PMID: 23460887

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Project description:BackgroundFibrosis is a common pathology in many cardiac disorders and is driven by the activation of resident fibroblasts. The global posttranscriptional mechanisms underlying fibroblast-to-myofibroblast conversion in the heart have not been explored.MethodsGenome-wide changes of RNA transcription and translation during human cardiac fibroblast activation were monitored with RNA sequencing and ribosome profiling. We then used RNA-binding protein-based analyses to identify translational regulators of fibrogenic genes. The integration with cardiac ribosome occupancy levels of 30 dilated cardiomyopathy patients demonstrates that these posttranscriptional mechanisms are also active in the diseased fibrotic human heart.ResultsWe generated nucleotide-resolution translatome data during the transforming growth factor β1-driven cellular transition of human cardiac fibroblasts to myofibroblasts. This identified dynamic changes of RNA transcription and translation at several time points during the fibrotic response, revealing transient and early-responder genes. Remarkably, about one-third of all changes in gene expression in activated fibroblasts are subject to translational regulation, and dynamic variation in ribosome occupancy affects protein abundance independent of RNA levels. Targets of RNA-binding proteins were strongly enriched in posttranscriptionally regulated genes, suggesting genes such as MBNL2 can act as translational activators or repressors. Ribosome occupancy in the hearts of patients with dilated cardiomyopathy suggested the same posttranscriptional regulatory network was underlying cardiac fibrosis. Key network hubs include RNA-binding proteins such as Pumilio RNA binding family member 2 (PUM2) and Quaking (QKI) that work in concert to regulate the translation of target transcripts in human diseased hearts. Furthermore, silencing of both PUM2 and QKI inhibits the transition of fibroblasts toward profibrotic myofibroblasts in response to transforming growth factor β1.ConclusionsWe reveal widespread translational effects of transforming growth factor β1 and define novel posttranscriptional regulatory networks that control the fibroblast-to-myofibroblast transition. These networks are active in human heart disease, and silencing of hub genes limits fibroblast activation. Our findings show the central importance of translational control in fibrosis and highlight novel pathogenic mechanisms in heart failure.

Dataset Information

In silico estimation of translation efficiency in human cell lines: potential evidence for widespread translational control.

Publications

In silico estimation of translation efficiency in human cell lines: potential evidence for widespread translational control.

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