Identification of genomic regions distorting population structure inference in diverse continental groups

Abstract

Background: Inference of population structure is crucial for studies of human evolutionary history and genome-wide association studies. While several genomic regions have been reported to distort population structure analysis of European populations, no systematic analysis has been performed on non-European continental groups and with the latest human genome assembly.

Methods: Using the 1000 Genomes Project high coverage whole-genome sequencing data from four major continental groups (Europe, East Asia, South Asia, and Africa), we developed a statistical framework and systematically detected genomic regions with unusual contributions to the inference of population structure for each of the continental groups.

Results: We identified and characterized 27 unusual genomic regions mapped to GRCh38, including 13 regions around centromeres, 2 with chromosomal inversions, 8 under natural selection, and 4 with unknown causes. Excluding these regions would result in a more interpretable population structure inferred by principal components analysis and ADMIXTURE analysis.

Conclusions: Unusual genomic patterns in certain regions can distort the inference of population structure. Our compiled list of these unusual regions will be useful for many population-genetic studies, including those from non-European populations. Availability: The code to reproduce our results is available at the website of Github (/dwuab/UnRegFinder).

Author summary

We propose a systematical analysis framework based on principal component analysis (PCA) to identify such genomic regions. Based on whole-genome sequencing data from four major continental groups with no recent admixture from the 1000 Genomes Project, we compile a list of 27 unusual genomic regions and demonstrate that excluding these regions can lead to more interpretable population structure results. We recommend removing these regions as a routine in the analysis of population structure to avoid artifact results.

Graphical abstract

Keywords

population genetics / population structure / linkage disequilibrium / principal component analysis / natural selection

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SUPPLEMENTARY MATERIALS

The supplementary materials can be found online with this article at https://doi.org/10.15302/J-QB-022-0303.

ACKNOWLEDGEMENTS

This study was funded by the National Natural Science Foundation of China (No. 81973148).

COMPLIANCE WITH ETHICS GUIDELINES

The authors Qiuxuan Liu, Degang Wu, and Chaolong Wang declare that they have no conflict of interest or financial conflicts to disclose. This article does not contain any studies with human or animal subjects performed by any of the authors.

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