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Systematic evaluation of the effects of genetic variants on PIWI-interacting RNA expression across 33 cancer types.

Authors
  • Xin, Junyi1, 2
  • Du, Mulong3
  • Jiang, Xia4
  • Wu, Yanling1, 2
  • Ben, Shuai1, 2
  • Zheng, Rui1, 2
  • Chu, Haiyan1, 2
  • Li, Shuwei1, 2
  • Zhang, Zhengdong1, 2
  • Wang, Meilin1, 2, 5
  • 1 Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China. , (China)
  • 2 Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China. , (China)
  • 3 Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China. , (China)
  • 4 Department of Clinical Neuroscience, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden. , (Sweden)
  • 5 Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China. , (China)
Type
Published Article
Journal
Nucleic Acids Research
Publisher
Oxford University Press
Publication Date
Jan 11, 2021
Volume
49
Issue
1
Pages
90–97
Identifiers
DOI: 10.1093/nar/gkaa1190
PMID: 33330918
Source
Medline
Language
English
License
Unknown

Abstract

PIWI-interacting RNAs (piRNAs) are an emerging class of non-coding RNAs involved in tumorigenesis. Expression quantitative trait locus (eQTL) analysis has been demonstrated to help reveal the genetic mechanism of single nucleotide polymorphisms (SNPs) in cancer etiology. However, there are no databases that have been constructed to provide an eQTL analysis between SNPs and piRNA expression. In this study, we collected genotyping and piRNA expression data for 10 997 samples across 33 cancer types from The Cancer Genome Atlas (TCGA). Using linear regression cis-eQTL analysis with adjustment of appropriate covariates, we identified millions of SNP-piRNA pairs in tumor (76 924 831) and normal (24 431 061) tissues. Further, we performed differential expression and survival analyses, and linked the eQTLs to genome-wide association study (GWAS) data to comprehensively decipher the functional roles of identified cis-piRNA eQTLs. Finally, we developed a user-friendly database, piRNA-eQTL (http://njmu-edu.cn:3838/piRNA-eQTL/), to help users query, browse and download corresponding eQTL results. In summary, piRNA-eQTL could serve as an important resource to assist the research community in understanding the roles of genetic variants and piRNAs in the development of cancers. © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

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