Emergence and Spread of Basal Lineages of Yersinia pestis during the Neolithic Decline.

Between 5,000 and 6,000 years ago, many Neolithic societies declined throughout western Eurasia due to a combination of factors that are still largely debated. Here, we report the discovery and genome reconstruction of Yersinia pestis, the etiological agent of plague, in Neolithic farmers in Sweden, pre-dating and basal to all modern and ancient known strains of this pathogen. We investigated the history of this strain by combining phylogenetic and molecular clock analyses of the bacterial genome, detailed archaeological information, and genomic analyses from infected individuals and hundreds of ancient human samples across Eurasia. These analyses revealed that multiple and independent lineages of Y. pestis branched and expanded across Eurasia during the Neolithic decline, spreading most likely through early trade networks rather than massive human migrations. Our results are consistent with the existence of a prehistoric plague pandemic that likely contributed to the decay of Neolithic populations in Europe.

Human Disease Variation in the Light of Population Genomics.

Identifying the causes of similarities and differences in genetic disease prevalence among humans is central to understanding disease etiology. While present-day humans are not strongly differentiated, vast amounts of genomic data now make it possible to study subtle patterns of genetic variation. This allows us to trace our genomic history thousands of years into the past and its implications for the distribution of disease-associated variants today. Genomic analyses have shown that demographic processes shaped the distribution and frequency of disease-associated variants over time. Furthermore, local adaptation to new environmental conditions-including pathogens-has generated strong patterns of differentiation at particular loci. Researchers are also beginning to uncover the genetic architecture of complex diseases, affected by many variants of small effect. The field of population genomics thus holds great potential for providing further insights into the evolution of human disease.

Physiological and Genetic Adaptations to Diving in Sea Nomads.

Understanding the physiology and genetics of human hypoxia tolerance has important medical implications, but this phenomenon has thus far only been investigated in high-altitude human populations. Another system, yet to be explored, is humans who engage in breath-hold diving. The indigenous Bajau people ("Sea Nomads") of Southeast Asia live a subsistence lifestyle based on breath-hold diving and are renowned for their extraordinary breath-holding abilities. However, it is unknown whether this has a genetic basis. Using a comparative genomic study, we show that natural selection on genetic variants in the PDE10A gene have increased spleen size in the Bajau, providing them with a larger reservoir of oxygenated red blood cells. We also find evidence of strong selection specific to the Bajau on BDKRB2, a gene affecting the human diving reflex. Thus, the Bajau, and possibly other diving populations, provide a new opportunity to study human adaptation to hypoxia tolerance. VIDEO ABSTRACT.

Genomic Analyses from Non-invasive Prenatal Testing Reveal Genetic Associations, Patterns of Viral Infections, and Chinese Population History.

We analyze whole-genome sequencing data from 141,431 Chinese women generated for non-invasive prenatal testing (NIPT). We use these data to characterize the population genetic structure and to investigate genetic associations with maternal and infectious traits. We show that the present day distribution of alleles is a function of both ancient migration and very recent population movements. We reveal novel phenotype-genotype associations, including several replicated associations with height and BMI, an association between maternal age and EMB, and between twin pregnancy and NRG1. Finally, we identify a unique pattern of circulating viral DNA in plasma with high prevalence of hepatitis B and other clinically relevant maternal infections. A GWAS for viral infections identifies an exceptionally strong association between integrated herpesvirus 6 and MOV10L1, which affects piwi-interacting RNA (piRNA) processing and PIWI protein function. These findings demonstrate the great value and potential of accumulating NIPT data for worldwide medical and genetic analyses.

The Evolutionary Pathway to Virulence of an RNA Virus.

Paralytic polio once afflicted almost half a million children each year. The attenuated oral polio vaccine (OPV) has enabled world-wide vaccination efforts, which resulted in nearly complete control of the disease. However, poliovirus eradication is hampered globally by epidemics of vaccine-derived polio. Here, we describe a combined theoretical and experimental strategy that describes the molecular events leading from OPV to virulent strains. We discover that similar evolutionary events occur in most epidemics. The mutations and the evolutionary trajectories driving these epidemics are replicated using a simple cell-based experimental setup where the rate of evolution is intentionally accelerated. Furthermore, mutations accumulating during epidemics increase the replication fitness of the virus in cell culture and increase virulence in an animal model. Our study uncovers the evolutionary strategies by which vaccine strains become pathogenic and provides a powerful framework for rational design of safer vaccine strains and for forecasting virulence of viruses. VIDEO ABSTRACT.

Inference and applications of ancestral recombination graphs.

Ancestral recombination graphs (ARGs) summarize the complex genealogical relationships between individuals represented in a sample of DNA sequences. Their use is currently revolutionizing the field of population genetics and is leading to the development of powerful new methods to elucidate individual and population genetic processes, including population size history, migration, admixture, recombination, mutation and selection. In this Review, we introduce the readers to the structure of ARGs and discuss how they relate to processes such as recombination and genetic drift. We explore differences and similarities between methods of estimating ARGs and provide concrete illustrative examples of how ARGs can be used to elucidate population-level processes.

Early divergent strains of Yersinia pestis in Eurasia 5,000 years ago.

The bacteria Yersinia pestis is the etiological agent of plague and has caused human pandemics with millions of deaths in historic times. How and when it originated remains contentious. Here, we report the oldest direct evidence of Yersinia pestis identified by ancient DNA in human teeth from Asia and Europe dating from 2,800 to 5,000 years ago. By sequencing the genomes, we find that these ancient plague strains are basal to all known Yersinia pestis. We find the origins of the Yersinia pestis lineage to be at least two times older than previous estimates. We also identify a temporal sequence of genetic changes that lead to increased virulence and the emergence of the bubonic plague. Our results show that plague infection was endemic in the human populations of Eurasia at least 3,000 years before any historical recordings of pandemics.

Elevated genetic risk for multiple sclerosis emerged in steppe pastoralist populations.

Multiple sclerosis (MS) is a neuro-inflammatory and neurodegenerative disease that is most prevalent in Northern Europe. Although it is known that inherited risk for MS is located within or in close proximity to immune-related genes, it is unknown when, where and how this genetic risk originated1. Here, by using a large ancient genome dataset from the Mesolithic period to the Bronze Age2, along with new Medieval and post-Medieval genomes, we show that the genetic risk for MS rose among pastoralists from the Pontic steppe and was brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the steppe population and later in Europe, probably driven by pathogenic challenges coinciding with changes in diet, lifestyle and population density. This study highlights the critical importance of the Neolithic period and Bronze Age as determinants of modern immune responses and their subsequent effect on the risk of developing MS in a changing environment.

The selection landscape and genetic legacy of ancient Eurasians.

The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.

Population genomics reveal recent speciation and rapid evolutionary adaptation in polar bears.

Polar bears are uniquely adapted to life in the High Arctic and have undergone drastic physiological changes in response to Arctic climates and a hyper-lipid diet of primarily marine mammal prey. We analyzed 89 complete genomes of polar bear and brown bear using population genomic modeling and show that the species diverged only 479-343 thousand years BP. We find that genes on the polar bear lineage have been under stronger positive selection than in brown bears; nine of the top 16 genes under strong positive selection are associated with cardiomyopathy and vascular disease, implying important reorganization of the cardiovascular system. One of the genes showing the strongest evidence of selection, APOB, encodes the primary lipoprotein component of low-density lipoprotein (LDL); functional mutations in APOB may explain how polar bears are able to cope with life-long elevated LDL levels that are associated with high risk of heart disease in humans.

Skin-resident T Cells Contribute to the Dynamic Disease Manifestations of Psoriasis.

The human skin forms a dynamic barrier to physical injuries and microbial invasion. Constant interactions between stroma and tissue-confined immune cells maintain skin homeostasis. However, the cellular interactions that maintain skin health also contribute to focal immunopathology. Psoriasis is a common disease that manifests with focal pathology induced by environmental triggers in genetically susceptible individuals. Within psoriasis plaques, cross-talk between skin-resident T cells and stroma cells leads to chronic inflammation. Inflammatory cytokines such as TNF-α, IL-17, IL-22, and IL-23 amplify the local chronic inflammation and sustain the well-demarcated thick and scaly plaques that characterize the disease. In resolved lesions, T cells remain poised for IL-17 and IL-22 production, and postinflammatory epigenetic modifications lower the threshold for initiation of local relapse. This review focuses on how tissue-resident memory T cells contribute to the onset, maintenance, resolution, and relapse of psoriasis.

Massive haplotypes underlie ecotypic differentiation in sunflowers.

Species often include multiple ecotypes that are adapted to different environments1. However, it is unclear how ecotypes arise and how their distinctive combinations of adaptive alleles are maintained despite hybridization with non-adapted populations2-4. Here, by resequencing 1,506 wild sunflowers from 3 species (Helianthus annuus, Helianthus petiolaris and Helianthus argophyllus), we identify 37 large (1-100 Mbp in size), non-recombining haplotype blocks that are associated with numerous ecologically relevant traits, as well as soil and climate characteristics. Limited recombination in these haplotype blocks keeps adaptive alleles together, and these regions differentiate sunflower ecotypes. For example, haplotype blocks control a 77-day difference in flowering between ecotypes of the silverleaf sunflower H. argophyllus (probably through deletion of a homologue of FLOWERING LOCUS T (FT)), and are associated with seed size, flowering time and soil fertility in dune-adapted sunflowers. These haplotypes are highly divergent, frequently associated with structural variants and often appear to represent introgressions from other-possibly now-extinct-congeners. These results highlight a pervasive role of structural variation in ecotypic adaptation.

Bayesian inference of admixture graphs on Native American and Arctic populations.

Admixture graphs are mathematical structures that describe the ancestry of populations in terms of divergence and merging (admixing) of ancestral populations as a graph. An admixture graph consists of a graph topology, branch lengths, and admixture proportions. The branch lengths and admixture proportions can be estimated using numerous numerical optimization methods, but inferring the topology involves a combinatorial search for which no polynomial algorithm is known. In this paper, we present a reversible jump MCMC algorithm for sampling high-probability admixture graphs and show that this approach works well both as a heuristic search for a single best-fitting graph and for summarizing shared features extracted from posterior samples of graphs. We apply the method to 11 Native American and Siberian populations and exploit the shared structure of high-probability graphs to characterize the relationship between Saqqaq, Inuit, Koryaks, and Athabascans. Our analyses show that the Saqqaq is not a good proxy for the previously identified gene flow from Arctic people into the Na-Dene speaking Athabascans.

Fast and Accurate Estimation of Selection Coefficients and Allele Histories from Ancient and Modern DNA.

We here present CLUES2, a full-likelihood method to infer natural selection from sequence data that is an extension of the method CLUES. We make several substantial improvements to the CLUES method that greatly increases both its applicability and its speed. We add the ability to use ancestral recombination graphs on ancient data as emissions to the underlying hidden Markov model, which enables CLUES2 to use both temporal and linkage information to make estimates of selection coefficients. We also fully implement the ability to estimate distinct selection coefficients in different epochs, which allows for the analysis of changes in selective pressures through time, as well as selection with dominance. In addition, we greatly increase the computational efficiency of CLUES2 over CLUES using several approximations to the forward-backward algorithms and develop a new way to reconstruct historic allele frequencies by integrating over the uncertainty in the estimation of the selection coefficients. We illustrate the accuracy of CLUES2 through extensive simulations and validate the importance sampling framework for integrating over the uncertainty in the inference of gene trees. We also show that CLUES2 is well-calibrated by showing that under the null hypothesis, the distribution of log-likelihood ratios follows a χ2 distribution with the appropriate degrees of freedom. We run CLUES2 on a set of recently published ancient human data from Western Eurasia and test for evidence of changing selection coefficients through time. We find significant evidence of changing selective pressures in several genes correlated with the introduction of agriculture to Europe and the ensuing dietary and demographic shifts of that time. In particular, our analysis supports previous hypotheses of strong selection on lactase persistence during periods of ancient famines and attenuated selection in more modern periods.

Selfing Promotes Spread and Introgression of Segregation Distorters in Hermaphroditic Plants.

Segregation distorters (SDs) are genetic elements that distort the Mendelian segregation ratio to favor their own transmission and are able to spread even when they incur fitness costs on organisms carrying them. Depending on the biology of the host organisms and the genetic architecture of the SDs, the population dynamics of SDs can be highly variable. Inbreeding is considered an effective mechanism for inhibiting the spread of SDs in populations, and can evolve as a defense mechanism against SDs in some systems. However, we show that inbreeding in the form of selfing in fact promotes the spread of SDs acting as pollen killers in a toxin-antidote system in hermaphroditic plants by two mechanisms: (i) By reducing the effective recombination rate between killer and antidote loci in the two-locus system and (ii) by increasing the proportion of SD alleles in individual flowers, rather than in the general gene-pool. We also show that in rice (Oryza sativa L.), a typical hermaphroditic plant, all molecularly characterized SDs associated with pollen killing were involved in population hybridization and have introgressed across different species. Paradoxically, these loci, which are associated with hybrid incompatibility and can be thought of as Bateson-Dobzhansky-Muller incompatibility loci are expected to reduce gene-flow between species, in fact cross species boundaries more frequently than random loci, and may act as important drivers of introgression.

Deep ancestral introgressions between ovine species shape sheep genomes via argali-mediated gene flow.

Previous studies reveal extensive genetic introgression between Ovis species, which affects genetic adaptation and morphological traits. However, the exact evolutionary scenarios underlying the hybridization between sheep and allopatric wild relatives remain unknown. To address this problem, we here integrate the reference genomes of several ovine and caprine species: domestic sheep, argali, bighorn sheep, snow sheep, and domestic goats. Additionally, we use 856 whole genomes representing 169 domestic sheep populations and their 6 wild relatives: Asiatic mouflon, urial, argali, snow sheep, thinhorn sheep and bighorn sheep. We implement a comprehensive set of analyses to test introgression among these species. We infer that the argali lineage originated ca. 3.08-3.35 Mya and hybridized with the ancestor of Pachyceriforms (e.g., bighorn sheep and snow sheep) at ∼1.56 Mya. Previous studies show apparent introgression from North American Pachyceriforms into the Bashibai sheep, a Chinese native sheep breed, despite their wide geographic separation. We show here that, in fact, the apparent introgression from the Pachyceriforms into Bashibai can be explained by the old introgression from Pachyceriforms into argali, and subsequent recent introgression from argali into Bashibai. Our results illustrate the challenges of estimating complex introgression histories and provide an example of how indirect and direct introgression can be distinguished.

Publisher Correction: Natural selection on the Arabidopsis thaliana genome in present and future climates.

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.

Natural selection on the Arabidopsis thaliana genome in present and future climates.

Through the lens of evolution, climate change is an agent of natural selection that forces populations to change and adapt, or face extinction. However, current assessments of the risk of biodiversity associated with climate change1 do not typically take into account how natural selection influences populations differently depending on their genetic makeup2. Here we make use of the extensive genome information that is available for Arabidopsis thaliana and measure how manipulation of the amount of rainfall affected the fitness of 517 natural Arabidopsis lines that were grown in Spain and Germany. This allowed us to directly infer selection along the genome3. Natural selection was particularly strong in the hot-dry location in Spain, where 63% of lines were killed and where natural selection substantially changed the frequency of approximately 5% of all genome-wide variants. A significant portion of this climate-driven natural selection of variants was predictable from signatures of local adaptation (R2 = 29-52%), as genetic variants that were found in geographical areas with climates more similar to the experimental sites were positively selected. Field-validated predictions across the species range indicated that Mediterranean and western Siberian populations-at the edges of the environmental limits of this species-currently experience the strongest climate-driven selection. With more frequent droughts and rising temperatures in Europe4, we forecast an increase in directional natural selection moving northwards from the southern end of Europe, putting many native A. thaliana populations at evolutionary risk.

Estimating the timing of multiple admixture events using 3-locus linkage disequilibrium.

Estimating admixture histories is crucial for understanding the genetic diversity we see in present-day populations. Allele frequency or phylogeny-based methods are excellent for inferring the existence of admixture or its proportions. However, to estimate admixture times, spatial information from admixed chromosomes of local ancestry or the decay of admixture linkage disequilibrium (ALD) is used. One popular method, implemented in the programs ALDER and ROLLOFF, uses two-locus ALD to infer the time of a single admixture event, but is only able to estimate the time of the most recent admixture event based on this summary statistic. To address this limitation, we derive analytical expressions for the expected ALD in a three-locus system and provide a new statistical method based on these results that is able to resolve more complicated admixture histories. Using simulations, we evaluate the performance of this method on a range of different admixture histories. As an example, we apply the method to the Colombian and Mexican samples from the 1000 Genomes project. The implementation of our method is available at https://github.com/Genomics-HSE/LaNeta.

Disentangling selection on genetically correlated polygenic traits via whole-genome genealogies.

We present a full-likelihood method to infer polygenic adaptation from DNA sequence variation and GWAS summary statistics to quantify recent transient directional selection acting on a complex trait. Through simulations of polygenic trait architecture evolution and GWASs, we show the method substantially improves power over current methods. We examine the robustness of the method under stratification, uncertainty and bias in marginal effects, uncertainty in the causal SNPs, allelic heterogeneity, negative selection, and low GWAS sample size. The method can quantify selection acting on correlated traits, controlling for pleiotropy even among traits with strong genetic correlation (|rg|=80%) while retaining high power to attribute selection to the causal trait. When the causal trait is excluded from analysis, selection is attributed to its closest proxy. We discuss limitations of the method, cautioning against strongly causal interpretations of the results, and the possibility of undetectable gene-by-environment (GxE) interactions. We apply the method to 56 human polygenic traits, revealing signals of directional selection on pigmentation, life history, glycated hemoglobin (HbA1c), and other traits. We also conduct joint testing of 137 pairs of genetically correlated traits, revealing widespread correlated response acting on these traits (2.6-fold enrichment, p = 1.5 × 10-7). Signs of selection on some traits previously reported as adaptive (e.g., educational attainment and hair color) are largely attributable to correlated response (p = 2.9 × 10-6 and 1.7 × 10-4, respectively). Lastly, our joint test shows antagonistic selection has increased type 2 diabetes risk and decrease HbA1c (p = 1.5 × 10-5).