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

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.

Metadata

Item Type:	Article
Authors/Creators:	Fachrul, M. https://orcid.org/0000-0003-2199-5900 Karkey, A. Shakya, M. Judd, L.M. Harshegyi, T. https://orcid.org/0000-0001-9620-8735 Sim, K.S. Tonks, S. Dongol, S. Shrestha, R. Salim, A. Adhikari, A. Banda, H.C. Blohmke, C. Darton, T.C. https://orcid.org/0000-0003-2209-9956 Farooq, Y. Ghimire, M. Hill, J. Hoang, N.T. Jere, T.M. Kamzati, M. Kao, Y.-H. Masesa, C. Mbewe, M. Msuku, H. Munthali, P. Nga, T.V.T. Nkhata, R. Saad, N.J. Van Tan, T. Thindwa, D. Khanam, F. Meiring, J. https://orcid.org/0000-0001-9183-5174 Clemens, J.D. Dougan, G. Pitzer, V.E. Qadri, F. Heyderman, R.S. Gordon, M.A. Voysey, M. Baker, S. Pollard, A.J. https://orcid.org/0000-0001-7361-719X Khor, C.C. https://orcid.org/0000-0002-1128-4729 Dolecek, C. Basnyat, B. Dunstan, S.J. https://orcid.org/0000-0001-7873-933X Holt, K.E. https://orcid.org/0000-0003-3949-2471 Inouye, M. https://orcid.org/0000-0001-9413-6520
Copyright, Publisher and Additional Information:	© 2023 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords:	Humans; Retrospective Studies; Genetics, Population; Genotype; Base Sequence; Sequence Analysis, RNA
Dates:	Published: 2 August 2023 Published (online): 2 August 2023 Accepted: 24 July 2023
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield)
Depositing User:	Symplectic Sheffield
Date Deposited:	08 Sep 2023 11:22
Last Modified:	08 Sep 2023 11:22
Status:	Published
Publisher:	Springer Science and Business Media LLC
Refereed:	Yes
Identification Number:	10.1038/s42003-023-05171-9
Related URLs:	PubMed URL
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:203036

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

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