Variants at IRX4 as prostate cancer expression quantitative trait loci

被引:0
|
作者
Xing Xu
Wasay M Hussain
Joseph Vijai
Kenneth Offit
Mark A Rubin
Francesca Demichelis
Robert J Klein
机构
[1] Clinical Genetics Service,Department of Medicine
[2] Memorial Sloan-Kettering Cancer Center,Department of Pathology and Laboratory Medicine
[3] Program in Cancer Biology and Genetics,undefined
[4] Memorial Sloan-Kettering Cancer Center,undefined
[5] Weill Cornell Medical College,undefined
[6] Institute for Computational Biomedicine,undefined
[7] Weill Cornell Medical College,undefined
[8] Centre for Integrative Biology,undefined
[9] CIBIO,undefined
[10] University of Trento,undefined
来源
European Journal of Human Genetics | 2014年 / 22卷
关键词
expression quantitative trait loci; eQTL; prostate cancer; GWAS; risk SNPs;
D O I
暂无
中图分类号
学科分类号
摘要
Genome-wide association studies (GWAS) have identified numerous prostate cancer-associated risk loci. Some variants at these loci may be regulatory and influence expression of nearby genes. Such loci are known as cis-expression quantitative trait loci (cis-eQTL). As cis-eQTLs are highly tissue-specific, we asked if GWAS-identified prostate cancer risk loci are cis-eQTLs in human prostate tumor tissues. We investigated 50 prostate cancer samples for their genotype at 59 prostate cancer risk-associated single-nucleotide polymorphisms (SNPs) and performed cis-eQTL analysis of transcripts from paired primary tumors within two megabase windows. We tested 586 transcript–genotype associations, of which 27 were significant (false discovery rate ≤10%). An equivalent eQTL analysis of the same prostate cancer risk loci in lymphoblastoid cell lines did not result in any significant associations. The top-ranked cis-eQTL involved the IRX4 (Iroquois homeobox protein 4) transcript and rs12653946, tagged by rs10866528 in our study (P=4.91 × 10−5). Replication studies, linkage disequilibrium, and imputation analyses highlight population specificity at this locus. We independently validated IRX4 as a potential prostate cancer risk gene through cis-eQTL analysis of prostate cancer risk variants. Cis-eQTL analysis in relevant tissues, even with a small sample size, can be a powerful method to expedite functional follow-up of GWAS.
引用
收藏
页码:558 / 563
页数:5
相关论文
共 50 条
  • [21] Loci nominally associated with autism from genome-wide analysis show enrichment of brain expression quantitative trait loci but not lymphoblastoid cell line expression quantitative trait loci
    Lea K Davis
    Eric R Gamazon
    Emily Kistner-Griffin
    Judith A Badner
    Chunyu Liu
    Edwin H Cook
    James S Sutcliffe
    Nancy J Cox
    Molecular Autism, 3
  • [22] Learning classifiers from discretized expression quantitative trait loci
    Masegosa, Andres
    Abad-Grau, Maria M.
    Moral, Serafin
    Matesanz, Fuencisla
    PROCEEDINGS IWBBIO 2013: INTERNATIONAL WORK-CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING, 2013, : 427 - +
  • [23] Association of expression quantitative trait loci for long noncoding RNAs with lung cancer risk in Asians
    Sun, Qi
    Wang, Yuzhuo
    Fan, Jingyi
    Li, Zhihua
    Zhang, Jiahui
    Wang, Lijuan
    Fan, Xikang
    Ji, Mengmeng
    Zhu, Meng
    Dai, Juncheng
    Ma, Hongxia
    Jin, Guangfu
    Hu, Zhibin
    Shen, Hongbing
    MOLECULAR CARCINOGENESIS, 2019, 58 (07) : 1303 - 1313
  • [24] Genome-wide expression quantitative trait loci analysis in asthma
    Bosse, Yohan
    CURRENT OPINION IN ALLERGY AND CLINICAL IMMUNOLOGY, 2013, 13 (05) : 487 - 494
  • [25] IsomiR-eQTL: A Cancer-Specific Expression Quantitative Trait Loci Database of miRNAs and Their Isoforms
    Moradi, Afshin
    Whatmore, Paul
    Farashi, Samaneh
    Barrero, Roberto A.
    Batra, Jyotsna
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2022, 23 (20)
  • [26] Meta-Analyses of Splicing and Expression Quantitative Trait Loci Identified Susceptibility Genes of Glioma
    Patro, C. Pawan K.
    Nousome, Darryl
    Lai, Rose K.
    FRONTIERS IN GENETICS, 2021, 12
  • [27] Discretization of Expression Quantitative Trait Loci in Association Analysis Between Genotypes and Expression Data
    Masegosa, Andres R.
    Armananzas, Ruben
    Abad-Grau, Maira M.
    Potenciano, Victor
    Moral, Serafin
    Larranaga, Pedro
    Bielza, Concha
    Matesanz, Fuencisla
    CURRENT BIOINFORMATICS, 2015, 10 (02) : 144 - 164
  • [28] Using expression quantitative trait loci data and graph-embedded neural networks to uncover genotype-phenotype interactions
    Guo, Xinpeng
    Han, Jinyu
    Song, Yafei
    Yin, Zhilei
    Liu, Shuaichen
    Shang, Xuequn
    FRONTIERS IN GENETICS, 2022, 13
  • [29] Development of a tissue augmented Bayesian model for expression quantitative trait loci analysis
    Zhuang, Yonghua
    Wade, Kristen
    Saba, Laura M.
    Kechris, Katerina
    MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2020, 17 (01) : 122 - 143
  • [30] Methods and Insights from Single-Cell Expression Quantitative Trait Loci
    Kang, Joyce B.
    Raveane, Alessandro
    Nathan, Aparna
    Soranzo, Nicole
    Raychaudhuri, Soumya
    ANNUAL REVIEW OF GENOMICS AND HUMAN GENETICS, 2023, 24 : 277 - 303