학술논문
Direct inference and control of genetic population structure from RNA sequencing data
Document Type
article
Author
Muhamad Fachrul; Abhilasha Karkey; Mila Shakya; Louise M. Judd; Taylor Harshegyi; Kar Seng Sim; Susan Tonks; Sabina Dongol; Rajendra Shrestha; Agus Salim; STRATAA study group; Stephen Baker; Andrew J. Pollard; Chiea Chuen Khor; Christiane Dolecek; Buddha Basnyat; Sarah J. Dunstan; Kathryn E. Holt; Michael Inouye
Source
Communications Biology, Vol 6, Iss 1, Pp 1-9 (2023)
Subject
Language
English
ISSN
2399-3642
Abstract
Abstract 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.