The interaction between genetic drift and selection in shaping genetic diversity is not fully understood. In particular, a population’s propensity to drift is typically summarized by its long-term effective population size (N_e ), but rapidly changing population demographics may complicate this relationship. To better understand how changing demography impacts selection, we investigated linked selection in the genomes of 23 domesticated maize and 13 wild maize (teosinte) individuals. We show that maize went through a domestication bottleneck with a population size of approximately 5% that of teosinte before it experienced rapid expansion post-domestication. We observe that hard sweeps on genic mutations are not the primary force driving maize evolution. As expected, a reduced population size during domestication decreased the efficiency of purifying selection to purge deleterious alleles from maize, but rapid expansion after domestication has since increased the efficiency of purifying selection to levels exceeding those seen in teosinte. This final observation demonstrates that rapid demographic change can have wide-ranging impacts on diversity that conflict with would-be expectations based on long-term N_e.

Motivation: A series of methods in population genetics use multilocus genotype data to assign individuals membership in latent clusters. These methods belong to a broad class of mixed-membership models, such as latent Dirichlet allocation used to analyze text corpora. Inference from mixed-membership models can produce different output matrices when repeatedly applied to the same inputs, and the number of latent clusters is a parameter that is varied in the analysis pipeline. For these reasons, quantifying, visualizing, and annotating the output from mixed-membership models are bottlenecks for investigators. Results: Here, we introduce pong, a network-graphical approach for analyzing and visualizing membership in latent clusters with a D3.js interactive visualization. We apply this new method to 225,705 unlinked genome-wide single-nucleotide variants from 2,426 unrelated individuals in the 1000 Genomes Project, and show that pong outpaces current solutions by more than an order of magnitude in runtime while providing a customizable and interactive visualization of population structure that is more accurate than those produced by current tools. Availability: pong is freely available and can be installed using the Python package management system pip.

Complete gene knockouts are highly informative about gene function. We exome sequenced 3,222 British Pakistani-heritage adults with high parental relatedness, discovering 1,111 rare-variant homozygous likely loss of function (rhLOF) genotypes predicted to disrupt (knockout) 781 genes. Based on depletion of rhLOF genotypes, we estimate that 13.6% of knockouts are incompatible with adult life, finding on average 1.6 heterozygous recessive lethal LOF variants per adult. Linking to lifelong health records, we observed no association of rhLOF genotypes with prescription- or doctor-consultation rate, and no disease-related phenotypes in 33 of 42 individuals with rhLOF genotypes in recessive Mendelian disease genes. Phased genome sequencing of a healthy PRDM9 knockout mother, her child and controls, showed meiotic recombination sites localised away from PRDM9-dependent hotspots, demonstrating PRDM9 redundancy in humans.

In a classic example of the invasion of a species by a selfish genetic element, the P-element was horizontally transferred from a distantly related species into Drosophila melanogaster, where it caused a syndrome of abnormal phenotypes, including sterility, called “hybrid dysgenesis”. The P-element spread globally in the course of a few decades in D. melanogaster, while its sister species, including D. simulans, remained P-element free. Here, we find hybrid dysgenesis also occurs between D. simulans strains collected in different years; a survey of 154 strains shows that over one-third of them induce hybrid dysgenesis. Using genomic and transcriptomic data, we show that this dysgenesis-inducing phenotype is associated with the presence of the P-element, which has recently invaded D. simulans. We survey 573 D. simulans strains collected over the past 30 years for the presence of the P-element, and find that the D. simulans invasion of the P-element occurred rapidly, with infected strains across three continents being rare in 2004 and common by 2014. Importantly, strains collected from the latter phase of this invasion have adapted to ameliorate the effects of the P-element, as evidenced by their resistance to the hybrid dysgenesis phenotype. This work demonstrates that selfish elements can cause rapid global change in the genomes of their host species, even faster than previously thought.

Accurate identification of genotypes is critical in identifying de novo mutations, linking mutations with disease, and determining mutation rates. To call genotypes correctly from short-read data requires modeling read counts for each base. True heterozygotes may be affected by mapping reference bias and library preparation, leading to a distribution of reads that does not fit a 1:1 binomial distribution, and potentially resulting failure to call the alternate allele. Homozygous sites can be affected by the alignment of paralogous genes and sequencing error, which could incorrectly suggest heterozygousity. Previous work has modeled increased variance and skewed allele ratios to some degree. Here, we were able to model reads for all data as a mixture of Dirichlet multinomial distributions. This model has a better fit to the data than previously used models. In most cases we observed two distributions: one corresponds to a large proportion of heterozygous sites with a low reference bias and close-to-binomial distribution, and the other to a small proportion of sites with a high bias and overdispersion. The sites with high reference bias have not been previously identified as SNPs in extensive human genome research; thus, we believe these sites are not heterozygous in our data for the individuals studied here, and are falsely identified as heterozygous sites. We propose that this approach to modeling the distribution of NGS data provides a better fit to the data, which should lead to improved genotyping. Furthermore, the mixture of distributions may be used to suggest true and false positive de novo mutations. This approach provides an expected distribution of reads that can be incorporated into a model to estimate de novo mutations using reads across a pedigree.

Much work has been devoted to understanding the evolutionary processes shaping genetic variation across genomes. Studies have found that neutral polymorphism is reduced close to genes and in regions of low recombination, suggesting the effects of natural selection. However, the effect of selection on neutral sequence divergence between species remains ambiguous. While studies have reported correlations between divergence and recombination, theoretical arguments suggest selection may not affect divergence at linked neutral sites. Here we address these outstanding issues by examining how natural selection has affected divergence between distantly related species. We show that neutral divergence is negatively correlated with functional content and positively correlated with estimates of background selection from primates. These patterns persist even when comparing humans and mice, species that split 75 million years ago. Further, neutral divergence is positively correlated with recombination rate. The correlation increases when focusing on genic regions, and biased gene conversion cannot explain all of this correlation. These signatures suggest that natural selection has affected linked divergence between distantly related species. Coalescent models indicate that background selection can generate these patterns. Even when the contribution of ancestral polymorphism to divergence is small, background selection in the ancestral population can still explain a large proportion of the variance in divergence across the genome. Thus, the view that selection does not affect divergence at linked neutral sites needs to be reconsidered. Our work has important implications for understanding evolution of genomes and interpreting patterns of genetic variation.

Analysis of previously unpublished allele counts obtained from the French-San-Neanderthal-Chimpanzee alignment of the high quality DNA sequence of a Neanderthal from the Altai Mountains raises significant questions about the currently accepted phylogenetic model of the origins of Europeans. Previous estimates of the proportion of Neanderthal ancestry in present-day Europeans ranged between 1.3% and 2.7% supporting a recent Out-of Africa dispersal model followed by a low level of admixture with Neanderthals. However, analysis of the allele counts indicates the existence of an unidentified third archaic ancestor of Europeans, which diverged from its common ancestor with sub-Saharan Africans around 900 thousand years ago. This analysis shows that the relative proportions of derived alleles in the 0.0826% of the European genome that is not shared with the common ancestor of humans and chimpanzee are 13.6% Neanderthal, 32.3% sub-Saharan African and 54.2% third archaic ancestor. This analysis together with anthropological and archaeological evidence suggests a new model of human dispersal based on a Eurasian lineage in the Levant, which admixed with Neanderthals and descendants of African mtDNA haplogroup L3, followed by radiation from a basal admixed population around 55-50 Kya, with no subsequent major contribution to the European genome.

The genetic structure of human populations is often characterized by aggregating measures of ancestry across the autosomal chromosomes. While it may be reasonable to assume that population structure patterns are similar genome-wide in relatively homogeneous populations, this assumption may not be appropriate for admixed populations, such as Hispanics and African Americans, with recent ancestry from two or more continents. Recent studies have suggested that systematic ancestry differences can arise at genomic locations in admixed populations as a result of selection and non-random mating. Here, we propose a method, which we refer to as the chromosomal ancestry differences (CAnD) test, for detecting heterogeneity in population structure across the genome. CAnD uses local ancestry inferred from SNP genotype data to identify chromosomes harboring genomic regions with ancestry contributions that are significantly different than expected. In simulation studies with real genotype data from Phase III of the HapMap Project, we demonstrate the validity and power of CAnD. We apply CAnD to the HapMap Mexican American (MXL) and African American (ASW) population samples; in this analysis the software RFMix is used to infer local ancestry at genomic regions assuming admixing from Europeans, West Africans, and Native Americans. The CAnD test provides strong evidence of heterogeneity in population structure across the genome in the MXL sample ($p=4e-05$), which is largely driven by elevated Native American ancestry and deficit of European ancestry on the X chromosomes. Among the ASW, all chromosomes are largely African derived and no heterogeneity in population structure is detected in this sample.

Blindness has evolved repeatedly in cave-dwelling organisms, and investigating loss of sight presents an opportunity to understand the operation of fundamental evolutionary processes, including drift, selection, mutation, and migration. The observation of blind organisms has prompted many theories for their blindness, including loss-by-disuse and selection against eye development when eyes are not used. Here we have developed a model that shows just how strong selection must be for blind populations of a cave-dwelling species to evolve. We used approximations to determine levels of selection that would result in caves containing only sighted individuals, only blind individuals, or a stable population of both. We then incorporated drift into the model using simulations. Based on our model, strong selection is necessary for the evolution of blindness unless immigration rates are extremely low. Drift decreased the fixation of blindness in populations, although for intermediate levels of migration the level of selection required to fix blindness decreased substantially. We hypothesize that this degree of selection may be due to phototaxis in sighted individuals, who move toward the light leaving only blind individuals in the cave.

In clonally propagated crops, non-additive genetic effects can be effectively exploited by the identification of superior genetic individuals as varieties. Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop that feeds hundreds of millions. We quantified the amount and nature of non-additive genetic variation for key traits in a breeding population of cassava from sub-Saharan Africa using additive and non-additive genome-wide marker-based relationship matrices. We then assessed the accuracy of genomic prediction of additive compared to total (additive plus non-additive) genetic value. We confirmed previous findings based on diallel populations, that non-additive genetic variation is significant, especially for yield traits. Further, we show that we total genetic value correlated more strongly to observed phenotypes than did additive value, although this is constrained by low broad-sense heritability and is not beneficial for traits with already high heritability. We address the implication of these results for cassava breeding and put our work in the context of previous results in cassava, and other plant and animal species.