Direct inference and control of genetic population structure from RNA sequencing data

Fachrul, Muhamad, Karkey, Abhilasha M, Shakya, Mila, Judd, Louise, Harshegyi, Taylor, Sim, Kar Seng, Tonks, Susan, Dongol, Sabina, Shrestha, Rajendra, Salim, Agus
et al (show 38 more authors) (2023) Direct inference and control of genetic population structure from RNA sequencing data. COMMUNICATIONS BIOLOGY, 6 (1). 804-.

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RNAseq data can be used to infer genetic variants, yet its use for estimating genetic population structure remains underexplored. Here, we construct a freely available computational tool (RGStraP) to estimate RNAseq-based genetic principal components (RG-PCs) and assess whether RG-PCs can be used to control for population structure in gene expression analyses. Using whole blood samples from understudied Nepalese populations and the Geuvadis study, we show that RG-PCs had comparable results to paired array-based genotypes, with high genotype concordance and high correlations of genetic principal components, capturing subpopulations within the dataset. In differential gene expression analysis, we found that inclusion of RG-PCs as covariates reduced test statistic inflation. Our paper demonstrates that genetic population structure can be directly inferred and controlled for using RNAseq data, thus facilitating improved retrospective and future analyses of transcriptomic data.

Item Type: Article
Uncontrolled Keywords: STRATAA study group, Humans, Retrospective Studies, Sequence Analysis, RNA, Genetics, Population, Base Sequence, Genotype
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Infection, Veterinary and Ecological Sciences
Depositing User: Symplectic Admin
Date Deposited: 03 Oct 2023 08:42
Last Modified: 03 Oct 2023 08:43
DOI: 10.1038/s42003-023-05171-9
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