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Updated: Apr 30, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Applying genome-wide gene-based expression quantitative trait locus mapping to study population ancestry and
Hsin-Chou Yang1, Chien-Wei Lin, Chia-Wei Chen
1Institute of Statistical Science, Academia Sinica, No 128, Academia Road, Section 2, Nankang, Taipei, Taiwan. hsinchou@stat.sinica.edu.tw.
This study introduces a gene-based approach to map expression quantitative trait loci (eQTL), identifying ancestry-informative eQTL linked to drug responses and adverse reactions. These findings offer valuable insights for pharmacogenetics and population genetics.
Area of Science:
- Genomics
- Statistical Genetics
- Pharmacogenetics
Background:
- Gene-based analysis offers advantages over single-locus analysis in genomic research.
- Limited research exists on gene-based expression quantitative trait loci (eQTL) mapping.
- The role of ancestry-informative eQTL in pharmacogenetics, integrating SNP-based (s-eQTL) and gene-based (g-eQTL) approaches, remains underexplored.
Purpose of the Study:
- To develop and apply a gene-based framework for mapping eQTL.
- To identify and characterize ancestry-informative eQTL.
- To investigate the role of eQTL in pharmacogenetics, specifically in relation to drug response and adverse reactions.
Main Methods:
- Utilized a gene-based partial least squares (PLS) method to correlate transcript expression levels with gene SNPs.
- Employed rank-score-based multivariate association tests and Fisher's exact test to identify ancestry-informative transcripts and eQTL.
- Analyzed SNP and gene expression data from 210 individuals of African, Asian, and European descent.
Main Results:
- Identified numerous cis- and trans-acting g-eQTL and s-eQTL across different populations.
- Observed enrichment of ancestry information within eQTL.
- Discovered two ancestry-informative eQTL associated with adverse drug reactions (rs1045642 on MDR1) and drug response (rs20455 in KIF6).
Conclusions:
- Developed a gene-based PLS procedure and SAS macro for g-eQTL and s-eQTL identification.
- Established accessible data archives of eQTL for global populations.
- Highlighted the interrelationship between eQTL, ancestry, and pharmacodynamics, providing resources for future research in population and medical genetics.
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