Detecting fitness epistasis in recently admixed populations with genome-wide data

Abstract

Background: Fitness epistasis, the interaction effect of genes at different loci on fitness, makes an important contribution to adaptive evolution. Although fitness interaction evidence has been observed in model organisms, it is more difficult to detect and remains poorly understood in human populations as a result of limited statistical power and experimental constraints. Fitness epistasis is inferred from non-independence between unlinked loci. We previously observed ancestral block correlation between chromosomes 4 and 6 in African Americans. The same approach fails when examining ancestral blocks on the same chromosome due to the strong confounding effect observed in a recently admixed population. Results: We developed a novel approach to eliminate the bias caused by admixture linkage disequilibrium when searching for fitness epistasis on the same chromosome. We applied this approach in 16,252 unrelated African Americans and identified significant ancestral correlations in two pairs of genomic regions (P-value< 8.11 × 10 − 7) on chromosomes 1 and 10. The ancestral correlations were not explained by population admixture. Historical African-European crossover events are reduced between pairs of epistatic regions. We observed multiple pairs of coexpressed genes shared by the two regions on each chromosome, including ADAR being co-expressed with IFI44 in almost all tissues and DARC being co-expressed with VCAM1, S1PR1 and ELTD1 in multiple tissues in the Genotype-Tissue Expression (GTEx) data. Moreover, the co-expressed gene pairs are associated with the same diseases/traits in the GWAS Catalog, such as white blood cell count, blood pressure, lung function, inflammatory bowel disease and educational attainment. Conclusions: Our analyses revealed two instances of fitness epistasis on chromosomes 1 and 10, and the findings suggest a potential approach to improving our understanding of adaptive evolution.

Efficient estimation for large-scale linkage disequilibrium patterns of the human genome

“…Furthermore, chromosome 8 in ASW fluctuated upwards most from the linear correlation ( Figure 6 ), and even after various analyses, such as expanding SNP numbers. One possible explanation may lay under the complex demographic history of ASW, which can be investigated and tested in additional African American samples or possible existence for epistatic fitness (Ni et al ., 2020).…”

Human genetic admixture

“…The mosaic ancestry patterns of admixed populations can also be used to elucidate the mechanisms and timescales of evolution in humans more generally. For example, ancestry patterns in admixed populations have been used to infer recombination rates [14][15] and to identify epistatically interacting [16][17] (Top) Large-scale movements of individuals allow haplotypes from previously isolated populations to come together in a combined gene pool. Generations of recombination between these haplotypes lead to an admixed population with genetic ancestry that varies between individuals and along haplotypes.…”

“…The mosaic ancestry patterns of admixed populations can also be used to elucidate the mechanisms and timescales of evolution in humans more generally. For example, ancestry patterns in admixed populations have been used to infer recombination rates [ 14 – 15 ] and to identify epistatically interacting [ 16 – 17 ] or adaptive [ 18 – 26 ] alleles. In this context, we use ancestry to describe “genetic ancestry” — the population origins of material within a genome.…”