Integrative Analysis of Somatic Mutations in Non-coding Regions Altering RNA Secondary Structures in Cancer Genomes

被引:0
作者
Funan He
Ran Wei
Zhan Zhou
Leihuan Huang
Yinan Wang
Jie Tang
Yangyun Zou
Leming Shi
Xun Gu
Melissa J. Davis
Zhixi Su
机构
[1] Fudan University,Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences
[2] Zhejiang University,Institute of Drug Metabolism and Pharmaceutical Analysis and Zhejiang Provincial Key Laboratory of Anti
[3] Fudan University,Cancer Drug Research, College of Pharmaceutical Sciences
[4] Iowa State University,Shanghai Cancer Center and Cancer Institute
[5] Walter and Eliza Hall Institute of Medical Research,Department of Genetics, Development and Cell Biology
[6] 1G Royal Parade,Bioinformatics Division
[7] Singlera Genomics Inc,undefined
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Scientific Reports | / 9卷
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摘要
RNA secondary structure may influence many cellular processes, including RNA processing, stability, localization, and translation. Single-nucleotide variations (SNVs) that alter RNA secondary structure, referred to as riboSNitches, are potentially causative of human diseases, especially in untranslated regions (UTRs) and noncoding RNAs (ncRNAs). The functions of somatic mutations that act as riboSNitches in cancer development remain poorly understood. In this study, we developed a computational pipeline called SNIPER (riboSNitch-enriched or depleted elements in cancer genomes), which employs MeanDiff and EucDiff to detect riboSNitches and then identifies riboSNitch-enriched or riboSNitch-depleted non-coding elements across tumors. SNIPER is available at github: https://github.com/suzhixi/SNIPER/. We found that riboSNitches were more likely to be pathogenic. Moreover, we predicted several UTRs and lncRNAs (long non-coding RNA) that significantly enriched or depleted riboSNitches in cancer genomes, indicative of potential cancer driver or essential noncoding elements. Our study highlights the possibly neglected importance of RNA secondary structure in cancer genomes and provides a new strategy to identify new cancer-associated genes.
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