Genome-wide identification and differential analysis of translational initiation

Peng Zhang; Dandan He; Yi Xu; Jiakai Hou; Bih Fang Pan; Yunfei Wang; Tao Liu; Christel M. Davis; Erik A. Ehli; Lin Tan; Feng Zhou; Jian Hu; Yonghao Yu; Xi Chen; Tuan M. Nguyen; Jeffrey M. Rosen; David H. Hawke; Zhe Ji; Yiwen Chen

doi:10.1038/s41467-017-01981-8

Genome-wide identification and differential analysis of translational initiation

Peng Zhang, Dandan He, Yi Xu, Jiakai Hou, Bih Fang Pan, Yunfei Wang, Tao Liu, Christel M. Davis, Erik A. Ehli, Lin Tan, Feng Zhou, Jian Hu, Yonghao Yu, Xi Chen, Tuan M. Nguyen, Jeffrey M. Rosen, David H. Hawke, Zhe Ji, Yiwen Chen^*

^*Corresponding author for this work

Pharmacology

Research output: Contribution to journal › Article › peer-review

81 Scopus citations

Abstract

Translation is principally regulated at the initiation stage. The development of the translation initiation (TI) sequencing (TI-seq) technique has enabled the global mapping of TIs and revealed unanticipated complex translational landscapes in metazoans. Despite the wide adoption of TI-seq, there is no computational tool currently available for analyzing TI-seq data. To fill this gap, we develop a comprehensive toolkit named Ribo-TISH, which allows for detecting and quantitatively comparing TIs across conditions from TI-seq data. Ribo-TISH can also predict novel open reading frames (ORFs) from regular ribosome profiling (rRibo-seq) data and outperform several established methods in both computational efficiency and prediction accuracy. Applied to published TI-seq/rRibo-seq data sets, Ribo-TISH uncovers a novel signature of elevated mitochondrial translation during amino-acid deprivation and predicts novel ORFs in 5′UTRs, long noncoding RNAs, and introns. These successful applications demonstrate the power of Ribo-TISH in extracting biological insights from TI-seq/rRibo-seq data.

Original language	English (US)
Article number	1749
Journal	Nature communications
Volume	8
Issue number	1
DOIs	https://doi.org/10.1038/s41467-017-01981-8
State	Published - Dec 1 2017

Funding

We thank Dr. Roxana S. Redis and Dr. George A. Calin for sharing the HEK293 cells. This work was partially funded by NIH K99/R00 Pathway to Independence Award (NIH R00 CA172700) and Sidney Kimmel Scholar Award to J.H., NIH K99 CA207865 to Z.J., Cancer Prevention Research Institute of Texas (CPRIT) grant RP130397 and NIH 1S10OD012304-01 to D.H.H., NIH R00CA175290 and CPRIT first-time tenure-track faculty recruitment grant RR140071 to Y.C., CPRIT Training Grant RP160283 to T.M.N., NIH CA16303-41 to J.M.R., and Welch Foundation I-1800 and NIH GM114160 to Y.Y. This work was also supported in part by U.S. National Cancer Institute (NCI; MD Anderson TCGA Genome Data Analysis Center) grant CA143883, CPRIT grant RP130397, the Mary K. Chapman Foundation, the Michael & Susan Dell Foundation (honoring Lorraine Dell), and MD Anderson Cancer Center Support Grant P30 CA016672 (the Bioinformatics Shared Resource).

ASJC Scopus subject areas

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

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Cite this

Zhang, P., He, D., Xu, Y., Hou, J., Pan, B. F., Wang, Y., Liu, T., Davis, C. M., Ehli, E. A., Tan, L., Zhou, F., Hu, J., Yu, Y., Chen, X., Nguyen, T. M., Rosen, J. M., Hawke, D. H., Ji, Z., & Chen, Y. (2017). Genome-wide identification and differential analysis of translational initiation. Nature communications, 8(1), Article 1749. https://doi.org/10.1038/s41467-017-01981-8

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abstract = "Translation is principally regulated at the initiation stage. The development of the translation initiation (TI) sequencing (TI-seq) technique has enabled the global mapping of TIs and revealed unanticipated complex translational landscapes in metazoans. Despite the wide adoption of TI-seq, there is no computational tool currently available for analyzing TI-seq data. To fill this gap, we develop a comprehensive toolkit named Ribo-TISH, which allows for detecting and quantitatively comparing TIs across conditions from TI-seq data. Ribo-TISH can also predict novel open reading frames (ORFs) from regular ribosome profiling (rRibo-seq) data and outperform several established methods in both computational efficiency and prediction accuracy. Applied to published TI-seq/rRibo-seq data sets, Ribo-TISH uncovers a novel signature of elevated mitochondrial translation during amino-acid deprivation and predicts novel ORFs in 5′UTRs, long noncoding RNAs, and introns. These successful applications demonstrate the power of Ribo-TISH in extracting biological insights from TI-seq/rRibo-seq data.",

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Genome-wide identification and differential analysis of translational initiation

Abstract

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