Signatures of long-term balancing selection in human genomes

Abstract

Balancing selection maintains advantageous diversity in populations through various mechanisms. While extensively explored from a theoretical perspective, an empirical understanding of its prevalence and targets lags behind our knowledge of positive selection. Here we describe the Non-Central Deviation (NCD), a simple yet powerful statistic to detect long-term balancing selection (LTBS) that quantifies how close frequencies are to expectations under LTBS, and provides the basis for a neutrality test. NCD can be applied to a single locus or genomic data, and can be implemented considering only polymorphisms (NCD1) or also considering fixed differences with respect to an outgroup (NCD2) species. Incorporating fixed differences improves power, and NCD2 has higher power to detect LTBS in humans under different frequencies of the balanced allele(s) than other available methods. Applied to genome-wide data from African and European human populations, in both cases using chimpanzee as an outgroup, NCD2 shows that, albeit not prevalent, LTBS affects a sizable portion of the genome: about 0.6% of analyzed genomic windows and 0.8% of analyzed positions. Significant windows (p < 0.0001) contain 1.6% of SNPs in the genome, which disproportionally fall within exons and change protein sequence, but are not enriched in putatively regulatory sites. These windows overlap about 8% of the protein-coding genes, and these have larger number of transcripts than expected by chance even after controlling for gene length. Our catalog includes known targets of LTBS but a majority of them (90%) are novel. As expected, immune-related genes are among those with the strongest signatures, although most candidates are involved in other biological functions, suggesting that LTBS potentially influences diverse human phenotypes.

Different mechanisms drive the maintenance of polymorphism at loci subject to strong versus weak fluctuating selection

“…The contribution of balancing selection to standing genetic variation can also be substantial (Bitarello et al 2018;Good et al 2017;Charlesworth 2015). In a particularly striking example, sequencing studies in temperate Drosophila populations have found hundreds of polymorphic loci that undergo seasonal oscillations in allele frequency (Bergland et al 2014;Machado et al 2018).…”

Learning the properties of adaptive regions with functional data analysis

“…Moreover, our SURFDAWave approach is not restricted to application on adaptive introgression and selective sweep scenarios, and can be implemented for probing genomic variation of other evolutionary processes that leave a spatial or temporal signature in genomic data. Such examples include the identification of genomic targets of balancing selection (e.g., DeGiorgio et al, 2014;Siewert and Voight, 2017;Bitarello et al, 2018;Cheng and DeGiorgio, 2018;Siewert and Voight, 2018;, complex forms of adaptation such as staggered selective sweeps (Assaf et al, 2015) that have yet to be interrogated for in genomic data, and non-adaptive processes such as recombination rate estimation (e.g., Chan et al, 2018;Flagel et al, 2019).…”

Estimation of FST and the Impact of de novo Mutation

“…An implication is that estimation of F ST is robust to ascertainment for ancestral polymorphisms based on common ancestors older than the chimpanzee-human common ancestor. Empirical evidence suggests that the number of loci under long-term balancing selection in humans is on the order of tens or hundreds, not tens of thousands [31,32] .…”