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Xuerui YangĄ¯s group developed a new data-mining method for dissection of the landscapes of RNA translation

Recently emerging evidence has revealed active translations of many previously annotated non-coding RNA species and regions, such as long non-coding RNAs and 5’ or 3’ untranslated regions (UTRs). The canonical definitions of coding vs. non-coding RNA species are being challenged, and therefore, comprehensive de novo annotations of the context-dependent translatomes are urgently needed for dissection of gene translation. A team led by Dr. Xuerui Yang in the School of Life Sciences at Tsinghua has developed a new method, RiboCode, for assessment of RNA translation and de novo annotation of the translatomes with ribosome profiling (Ribo-seq) data. Their paper introducing the method, “De novo annotation and characterization of the translatome with ribosome profiling data”(link), was published online in Nucleic Acids Research on March 10th, 2018.

By capturing and sequencing the RNA fragments protected by translating ribosomes, ribosome profiling provides snapshots of translation at subcodon resolution. The growing needs for comprehensive annotation and characterization of the context-dependent translatomes call for an efficient and unbiased method to accurately recover the signal of active translation from the ribosome profiling data. However, the ribosome occupancy itself, as indicated by the ribosome protected fragment (RPF) reads mapped on the transcriptome, is not sufficient for calling of active translation, given the possible noise from the data processing and experimental procedures, regulatory RNAs that bind ribosomes, and ribosome engagement without translation. This therefore necessitates a specially designed method to recover the active translation events from the usually distorted and ambiguous signals in the ribosome profiling data.

Xuerui Yang’s group developed a new statistically vigorous method, RiboCode, for comprehensive de novo annotation of the translatome with ribosome profiling data. Tested with both simulated and real data, and further benchmarked with cell-type specific QTI-seq and mass spectrometry data, RiboCode exhibited superior efficiency, sensitivity, and accuracy to the existing methods. In the paper, the authors showed the application of RiboCode for assembly of the condition-specific translatomes of human cell lines, mouse cells, zebrafish, and yeast, which led to insightful observations about stress-induced upstream and downstream ORFs.

The RiboCode program, which was released 3 months ago, has already received much attention of the community, with more than 550 downloads worldwide before the paper was published.

One of the major efforts in Xuerui Yang’s lab has been dedicated to developing efficient data-mining methods and analysis pipelines for dissection of gene translation with different types of data. Previously, they have published another method paper in Nature Communications (link), introducing a different data-mining method, Xtail, for quantitative evaluations of differential translation rates between different experimental or physiological conditions. The two methods, Xtail and RiboCode, now have covered the two major applications of ribosome profiling. Being well-equipped with the experimental and bioinformatics toolsets, Xuerui Yang’s group is actively pursuing more thorough and comprehensive understandings about translation in complex biological processes such as cancer and cell development.

Zhengtao Xiao, who has recently finished his PhD program in Xuerui Yang’s lab, is the first author of the paper. Dr. Haiteng Deng’s group provided the MS data and helped for data processing. The study was supported by the national key research and development program, Precision Medicine Project, the National Natural Science Foundation of China, the Tsinghua University Initiative Scientific Research Program, the Tsinghua–Peking Joint Center for Life Sciences, and the 1000 talent program (Youth Category). The study also received supports from the Protein Chemistry and Computing core facilities at the National Protein Science Facility (Beijing) and the Center for Biomedical Analysis of Tsinghua University.



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