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The little greenbul, a common rainforest passerine from sub-Saharan Africa, has been the subject of long-term evolutionary studies to understand the mechanisms leading to rainforest speciation. Previous research found morphological and behavioural divergence across rainforest-savannah transition zones (ecotones), and a pattern of divergence with gene flow suggesting divergent natural selection has contributed to adaptive divergence and ecotones could be important areas for rainforests speciation. Recent advances in genomics and environmental modelling make it possible to examine patterns of genetic divergence in a more comprehensive fashion. To assess the extent to which natural selection may drive patterns of differentiation, here we investigate patterns of genomic differentiation among populations across environmental gradients and regions. We find compelling evidence that individuals form discrete genetic clusters corresponding to distinctive environmental characteristics and habitat types. Pairwise FST between populations in different habitats is significantly higher than within habitats, and this differentiation is greater than what is expected from geographic distance alone. Moreover, we identified 140 SNPs that showed extreme differentiation among populations through a genomewide selection scan. These outliers were significantly enriched in exonic and coding regions, suggesting their functional importance. Environmental association analysis of SNP variation indicates that several environmental variables, including temperature and elevation, play important roles in driving the pattern of genomic diversification. Results lend important new genomic evidence for environmental gradients being important in population differentiation. [ABSTRACT FROM AUTHOR]

Quantifying the number of deleterious mutations per diploid human genome is of crucial concern to both evolutionary and medical geneticists. Here we combine genome-wide polymorphism data from PCR-based exon resequencing, comparative genomic data across mammalian species, and protein structure predictions to estimate the number of functionally consequential single-nucleotide polymorphisms (SNPs) carried by each of 15 African American (AA) and 20 European American (EA) individuals. We find that AAs show significantly higher levels of nucleotide heterozygosity than do EAs for all categories of functional SNPs considered, including synonymous, non-synonymous, predicted ‘benign’, predicted ‘possibly damaging’ and predicted ‘probably damaging’ SNPs. This result is wholly consistent with previous work showing higher overall levels of nucleotide variation in African populations than in Europeans. EA individuals, in contrast, have significantly more genotypes homozygous for the derived allele at synonymous and non-synonymous SNPs and for the damaging allele at ‘probably damaging’ SNPs than AAs do. For SNPs segregating only in one population or the other, the proportion of non-synonymous SNPs is significantly higher in the EA sample (55.4%) than in the AA sample (47.0%; P < 2.3 × 10-37). We observe a similar proportional excess of SNPs that are inferred to be ‘probably damaging’ (15.9% in EA; 12.1% in AA; P < 3.3 × 10-11). Using extensive simulations, we show that this excess proportion of segregating damaging alleles in Europeans is probably a consequence of a bottleneck that Europeans experienced at about the time of the migration out of Africa. [ABSTRACT FROM AUTHOR]

Phenotype prediction is a key goal for medical genetics. Unfortunately, most genome-wide association studies are done in European populations, which reduces the accuracy of predictions via polygenic scores in non-European populations. Here, we use population genetic models to show that human demographic history and negative selection on complex traits can result in population-specific genetic architectures. For traits where alleles with the largest effect on the trait are under the strongest negative selection, approximately half of the heritability can be accounted for by variants in Europe that are absent from Africa, leading to poor performance in phenotype prediction across these populations. Further, under such a model, individuals in the tails of the genetic risk distribution may not be identified via polygenic scores generated in another population. We empirically test these predictions by building a model to stratify heritability between European-specific and shared variants and applied it to 37 traits and diseases in the UK Biobank. Across these phenotypes, ∼30% of the heritability comes from European-specific variants. We conclude that genetic association studies need to include more diverse populations to enable the utility of phenotype prediction in all populations., (Copyright © 2021 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Despite the widespread study of genetic variation in admixed human populations, such as African-Americans, there has not been an evaluation of the effects of recent admixture on patterns of polymorphism or inferences about population demography. These issues are particularly relevant because estimates of the timing and magnitude of population growth in Africa have differed among previous studies, some of which examined African-American individuals. Here we use simulations and single-nucleotide polymorphism (SNP) data collected through direct resequencing and genotyping to investigate these issues. We find that when estimating the current population size and magnitude of recent growth in an ancestral population using the site frequency spectrum (SFS), it is possible to obtain reasonably accurate estimates of the parameters when using samples drawn from the admixed population under certain conditions. We also show that methods for demographic inference that use haplotype patterns are more sensitive to recent admixture than are methods based on the SFS. The analysis of human genetic variation data from the Yoruba people of Ibadan, Nigeria and African-Americans supports the predictions from the simulations. Our results have important implications for the evaluation of previous population genetic studies that have considered African-American individuals as a proxy for individuals from West Africa as well as for future population genetic studies of additional admixed populations.