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).
Analysis of germline-driven ancestry-associated gene expression in cancers / Chambwe, Nyasha; Sayaman, Rosalyn W.; Hu, Donglei; Huntsman, Scott; Kemal, Anab; Caesar-Johnson, Samantha; Zenklusen, Jean C.; Ziv, Elad; Beroukhim, Rameen; Cherniack, Andrew D.; Carrot-Zhang, Jian; Berger, Ashton C.; Han, Seunghun; Meyerson, Matthew; Damrauer, Jeffrey S.; Hoadley, Katherine A.; Felau, Ina; Demchok, John A.; Mensah, Michael K. A.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Knijnenburg, Theo A.; Robertson, A. Gordon; Yau, Christina; Benz, Christopher; Huang, Kuan-lin; Newberg, Justin Y.; Frampton, Garrett M.; Mashl, R. Jay; Ding, Li; Romanel, Alessandro; Demichelis, Francesca; Zhou, Wanding; Laird, Peter W.; Shen, Hui; Wong, Christopher K.; Stuart, Joshua M.; Lazar, Alexander J.; Le, Xiuning; Oak, Ninad. - In: STAR PROTOCOLS. - ISSN 2666-1667. - 3:3(2022), pp. 10158601-10158618. [10.1016/j.xpro.2022.101586]
Analysis of germline-driven ancestry-associated gene expression in cancers
Romanel, Alessandro;Demichelis, Francesca;
2022-01-01
Abstract
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).| File | Dimensione | Formato | |
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