Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/51489
Title: Detecting Genotype-Population Interaction Effects by Ancestry Principal Components
Contributor(s): Yu, Chenglong (author); Ni, Guiyan  (author); Van Der Werf, Julius  (author)orcid ; Lee, S Hong  (author)
Publication Date: 2020-04-21
Open Access: Yes
DOI: 10.3389/fgene.2020.00379
Handle Link: https://hdl.handle.net/1959.11/51489
Abstract: 

Heterogeneity in the phenotypic mean and variance across populations is often observed for complex traits. One way to understand heterogeneous phenotypes lies in uncovering heterogeneity in genetic effects. Previous studies on genetic heterogeneity across populations were typically based on discrete groups in populations stratified by different countries or cohorts, which ignored the difference of population characteristics for the individuals within each group and resulted in loss of information. Here, we introduce a novel concept of genotype-by-population (G × P) interaction where population is defined by the first and second ancestry principal components (PCs), which are less likely to be confounded with country/cohort-specific factors. We applied a reaction norm model fitting each of 70 complex traits with significant SNP-heritability and the PCs as covariates to examine G × P interactions across diverse populations including white British and other white Europeans from the UK Biobank (N = 22,229). Our results demonstrated a significant population genetic heterogeneity for behavioral traits such as age at first sexual intercourse and academic qualification. Our approach may shed light on the latent genetic architecture of complex traits that underlies the modulation of genetic effects across different populations.

Publication Type: Journal Article
Grant Details: NHMRC/1087889
ARC/DP190100766
ARC/FT160100229
Source of Publication: Frontiers in Genetics, v.11, p. 1-12
Publisher: Frontiers Research Foundation
Place of Publication: Switzerland
ISSN: 1664-8021
Fields of Research (FoR) 2020: 310207 Statistical and quantitative genetics
Socio-Economic Objective (SEO) 2020: 200104 Prevention of human diseases and conditions
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

Files in This Item:
2 files
File Description SizeFormat 
openpublished/DetectingNiVanDerWerfLee2020JournalArticle.pdfPublished version1.94 MBAdobe PDF
Download Adobe
View/Open
Show full item record

SCOPUSTM   
Citations

2
checked on Mar 16, 2024

Page view(s)

1,246
checked on Mar 24, 2024

Download(s)

30
checked on Mar 24, 2024
Google Media

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons