STAR Protocols (Sep 2022)

Analysis of germline-driven ancestry-associated gene expression in cancers

  • Nyasha Chambwe,
  • Rosalyn W. Sayaman,
  • Donglei Hu,
  • Scott Huntsman,
  • Anab Kemal,
  • Samantha Caesar-Johnson,
  • Jean C. Zenklusen,
  • Elad Ziv,
  • Rameen Beroukhim,
  • Andrew D. Cherniack,
  • Jian Carrot-Zhang,
  • Ashton C. Berger,
  • Seunghun Han,
  • Matthew Meyerson,
  • Jeffrey S. Damrauer,
  • Katherine A. Hoadley,
  • Ina Felau,
  • John A. Demchok,
  • Michael K.A. Mensah,
  • Roy Tarnuzzer,
  • Zhining Wang,
  • Liming Yang,
  • Theo A. Knijnenburg,
  • A. Gordon Robertson,
  • Christina Yau,
  • Christopher Benz,
  • Kuan-lin Huang,
  • Justin Y. Newberg,
  • Garrett M. Frampton,
  • R. Jay Mashl,
  • Li Ding,
  • Alessandro Romanel,
  • Francesca Demichelis,
  • Wanding Zhou,
  • Peter W. Laird,
  • Hui Shen,
  • Christopher K. Wong,
  • Joshua M. Stuart,
  • Alexander J. Lazar,
  • Xiuning Le,
  • Ninad Oak

Journal volume & issue
Vol. 3, no. 3
p. 101586

Abstract

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Summary: Differential mRNA expression between ancestry groups can be explained by both genetic and environmental factors. We outline a computational workflow to determine the extent to which germline genetic variation explains cancer-specific molecular differences across ancestry groups. Using multi-omics datasets from The Cancer Genome Atlas (TCGA), we enumerate ancestry-informative markers colocalized with cancer-type-specific expression quantitative trait loci (e-QTLs) at ancestry-associated genes. This approach is generalizable to other settings with paired germline genotyping and mRNA expression data for a multi-ethnic cohort.For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020), Robertson et al. (2021), and Sayaman et al. (2021). : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

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