You are here

  • Home
  • Archive
  • Volume 67, Issue 3
  • Characterising cis-regulatory variation in the transcriptome of histologically normal and tumour-derived pancreatic tissues

Article Text

Article menu
Download PDFPDF
Pancreas
Original article
Characterising cis-regulatory variation in the transcriptome of histologically normal and tumour-derived pancreatic tissues
  1. Mingfeng Zhang1,
  2. Soren Lykke-Andersen2,
  3. Bin Zhu3,4,
  4. Wenming Xiao5,
  5. Jason W Hoskins1,
  6. Xijun Zhang3,6,
  7. Lauren M Rost1,
  8. Irene Collins1,
  9. Martijn van de Bunt7,8,
  10. Jinping Jia1,
  11. Hemang Parikh1,9,
  12. Tongwu Zhang1,
  13. Lei Song4,
  14. Ashley Jermusyk1,
  15. Charles C Chung3,6,
  16. Bin Zhu3,6,
  17. Weiyin Zhou3,6,
  18. Gail L Matters10,
  19. Robert C Kurtz11,
  20. Meredith Yeager3,6,
  21. Torben Heick Jensen2,
  22. Kevin M Brown1,
  23. Halit Ongen12,
  24. William R Bamlet13,
  25. Bradley A Murray14,
  26. Mark I McCarthy7,8,15,
  27. Stephen J Chanock3,
  28. Nilanjan Chatterjee4,16,
  29. Brian M Wolpin17,
  30. Jill P Smith18,
  31. Sara H Olson19,
  32. Gloria M Petersen13,
  33. Jianxin Shi4,
  34. Laufey Amundadottir1
  1. 1 Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, Maryland, USA
  2. 2 Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
  3. 3 Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, Maryland, USA
  4. 4 Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, Maryland, USA
  5. 5 Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, FDA, Jefferson, Missouri, USA
  6. 6 Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc, Frederick, Maryland, USA
  7. 7 Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
  8. 8 Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, UK
  9. 9 Health Informatics Institute, Morsani College of Medicine, University of South Florida, Tampa, Florida, USA
  10. 10 Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania, USA
  11. 11 Department of Medicine, Memorial Sloan Kettering Cancer Center, New York City, New York, USA
  12. 12 Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
  13. 13 Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota, USA
  14. 14 The Eli and Edythe L Broad Institute of Massachusetts Institute of Technology and Harvard University Cambridge, Cambridge, Massachusetts, USA
  15. 15 Oxford NIHR Biomedical Research Centre, Churchill Hospital, Headington, Oxford, UK
  16. 16 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
  17. 17 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
  18. 18 Division of Gastroenterology and Hepatology, Georgetown University Hospital, Washington, D.C., USA
  19. 19 Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, New York, USA
  1. Correspondence to Professor Laufey Amundadottir, Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Advanced Technology Center, 8717 Grovemont Circle, Bethesda, MD 208924605, USA; amundadottirl{at}mail.nih.gov

Abstract

Objective To elucidate the genetic architecture of gene expression in pancreatic tissues.

Design We performed expression quantitative trait locus (eQTL) analysis in histologically normal pancreatic tissue samples (n=95) using RNA sequencing and the corresponding 1000 genomes imputed germline genotypes. Data from pancreatic tumour-derived tissue samples (n=115) from The Cancer Genome Atlas were included for comparison.

Results We identified 38 615 cis-eQTLs (in 484 genes) in histologically normal tissues and 39 713 cis-eQTL (in 237 genes) in tumour-derived tissues (false discovery rate <0.1), with the strongest effects seen near transcriptional start sites. Approximately 23% and 42% of genes with significant cis-eQTLs appeared to be specific for tumour-derived and normal-derived tissues, respectively. Significant enrichment of cis-eQTL variants was noted in non-coding regulatory regions, in particular for pancreatic tissues (1.53-fold to 3.12-fold, p≤0.0001), indicating tissue-specific functional relevance. A common pancreatic cancer risk locus on 9q34.2 (rs687289) was associated with ABO expression in histologically normal (p=5.8×10−8) and tumour-derived (p=8.3×10−5) tissues. The high linkage disequilibrium between this variant and the O blood group generating deletion variant in ABO (exon 6) suggested that nonsense-mediated decay (NMD) of the ‘O’ mRNA might explain this finding. However, knockdown of crucial NMD regulators did not influence decay of the ABO ‘O’ mRNA, indicating that a gene regulatory element influenced by pancreatic cancer risk alleles may underlie the eQTL.

Conclusions We have identified cis-eQTLs representing potential functional regulatory variants in the pancreas and generated a rich data set for further studies on gene expression and its regulation in pancreatic tissues.

  • gene expression
  • eQTL
  • pancreas
  • RNA-seq
  • allele specific expression.

https://doi.org/10.1136/gutjnl-2016-313146

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    View Full Text

    Footnotes

    • Contributors LA and MZ had full access to all data in the study and take responsibility for the integrity of the data and the accuracy of data analysis. LA: study concept and design. MZ, BZ, WX, JWH, MvdB, HP, MIM, SJC, NC, JPS, SHO, GMP and JS: contribution to study design. MZ, BZ, WX, IC, JS and LA: acquisition of data. MZ, SLA, BZ, WX, JWH, XZ, LMR, MvdB, JJ, HP, TZ, LS, AJ, CCC, BZ, WZ, THJ, MIM, NC, BMW, JPS, SHO, GMP, JS and LA: analysis and interpretation of data. MZ and LA: drafting the manuscript. SJC and KMB: critical review of the manuscript. MZ, BZ, JS and LA: statistical analysis. BAM, WRB, HO, MY, RCK, GLM, IC and LA: administrative, technical or material support. LA: funding and study supervision.

    • Funding This study was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health. MvdB is supported by a Novo Nordisk postdoctoral fellowship run in partnership with the University of Oxford. MIM is a Wellcome Trust Senior Investigator and is supported by Wellcome Trust awards (#098381, 090532) and NIH grants (U01DK105535). SO at MSKCC is also supported by P30CA008748, C.Thompson, PI.

    • Competing interests None declared.

    • Patient consent Consents were signed at each institution that participated in the research (Mayo Clinic and Memorial Sloan Kettering Cancer Center).

    • Ethics approval National Cancer Institute/NIH, Mayo Clinic, Memorial Sloan Kettering Cancer Center, Penn State University.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement Data from RNA sequencing and GWAS genotyping will be deposited in dbGAP and are available from the authors upon reasonable request.

    Linked Articles