Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx

• Published in: Genome Biology Vol. 21; no. 1; p. 233
• Main Authors: Gay, Nicole R., Gloudemans, Michael, Antonio, Margaret L., Abell, Nathan S., Balliu, Brunilda, Park, YoSon, Martin, Alicia R., Musharoff, Shaila, Rao, Abhiram S., Aguet, François, Barbeira, Alvaro N., Bonazzola, Rodrigo, Hormozdiari, Farhad, Ardlie, Kristin G., Brown, Christopher D., Im, Hae Kyung, Lappalainen, Tuuli, Wen, Xiaoquan, Montgomery, Stephen B.
• Format: Journal Article
• Language: English
• Published: London BioMed Central 11.09.2020; BMC
• Subjects: Admixture; ancestry; Animal Genetics and Genomics; Bioinformatics; Biomedical and Life Sciences; Colocalization; eQTL; Evolutionary Biology; Gene Expression; Gene mapping; genome; Genome, Human; Genome-Wide Association Study; Genomes; Genotype; Genotype & phenotype; Genotypes; GTEx; Human Genetics; Humans; lead; Life Sciences; Local ancestry; Microbial Genetics and Genomics; Plant Genetics and Genomics; Population; Population structure; Population studies; Quantitative Trait Loci; Racial Groups - genetics; Sample size; Colocalization; GTEx; Admixture; Population structure; eQTL; Local ancestry; Gene expression
• ISSN: 1474-760X; 1474-7596; 1474-760X
• DOI: 10.1186/s13059-020-02113-0

Background Population structure among study subjects may confound genetic association studies, and lack of proper correction can lead to spurious findings. The Genotype-Tissue Expression (GTEx) project largely contains individuals of European ancestry, but the v8 release also includes up to 15% of individuals of non-European ancestry. Assessing ancestry-based adjustments in GTEx improves portability of this research across populations and further characterizes the impact of population structure on GWAS colocalization. Results Here, we identify a subset of 117 individuals in GTEx (v8) with a high degree of population admixture and estimate genome-wide local ancestry. We perform genome-wide cis -eQTL mapping using admixed samples in seven tissues, adjusted by either global or local ancestry. Consistent with previous work, we observe improved power with local ancestry adjustment. At loci where the two adjustments produce different lead variants, we observe 31 loci (0.02%) where a significant colocalization is called only with one eQTL ancestry adjustment method. Notably, both adjustments produce similar numbers of significant colocalizations within each of two different colocalization methods, COLOC and FINEMAP. Finally, we identify a small subset of eQTL-associated variants highly correlated with local ancestry, providing a resource to enhance functional follow-up. Conclusions We provide a local ancestry map for admixed individuals in the GTEx v8 release and describe the impact of ancestry and admixture on gene expression, eQTLs, and GWAS colocalization. While the majority of the results are concordant between local and global ancestry-based adjustments, we identify distinct advantages and disadvantages to each approach.