Five-leaf generalizations of the D-statistic reveal the directionality of admixture.

Over the past 15 years, the D-statistic, a four-taxon test for organismal admixture (hybridization, or introgression) which incorporates single nucleotide polymorphism data with allelic patterns ABBA and BABA, has seen considerable use. This statistic seeks to discern significant deviation from either a given species tree assumption, or from the balanced incomplete lineage sorting that could otherwise defy this species tree. However, while the D-statistic can successfully discriminate admixture from incomplete lineage sorting, it is not a simple matter to determine the directionality of admixture using only four-leaf tree models. As such, methods have been developed that use 5 leaves to evaluate admixture. Among these, the DFOIL method, which tests allelic patterns on the "symmetric" tree S = (((1,2),(3,4)),5), succeeds in finding admixture direction for many five-taxon examples. However, DFOIL does not make full use of all symmetry, nor can DFOIL function properly when ancient samples are included because of the reliance on singleton patterns (such as BAAAA and ABAAA). Here, we take inspiration from DFOIL to develop a new and completely general family of five-leaf admixture tests, dubbed Δ-statistics, that can either incorporate or exclude the singleton allelic patterns depending on individual taxon and age sampling choices. We describe two new shapes that are also fully testable, namely the "asymmetric" tree A = ((((1,2),3),4),5) and the "quasisymmetric" tree Q = (((1,2),3),(4,5)), which can considerably supplement the "symmetric" S = (((1,2),(3,4)),5) model used by DFOIL. We demonstrate the consistency of Δ-statistics under various simulated scenarios, and provide empirical examples using data from black, brown and polar bears, the latter also including two ancient polar bear samples from previous studies. Recently DFOIL and one of these ancient samples was used to argue for a dominant polar bear → brown bear introgression direction. However, we find, using both this ancient polar bear and our own, that by far the strongest signal using both DFOIL and Δ-statistics on tree S is actually bidirectional gene flow of indistinguishable direction. Further experiments on trees A and Q instead highlight what were likely two phases of admixture: one with stronger brown bear → polar bear introgression in ancient times, and a more recent phase with predominant polar bear → brown bear directionality. Code and documentation available at https://github.com/KalleLeppala/Delta-statistics.

Sensitivity Analysis on Odds Ratios.

The classical Cornfield inequalities state that if a third confounding variable is fully responsible for an observed association between the exposure and the outcome variables, then the association between both the exposure and the confounder, and the confounder and the outcome, must be at least as strong as the association between the exposure and the outcome, as measured by the risk ratio. The work of Ding and VanderWeele on assumption-free sensitivity analysis sharpens this bound to a bivariate function of the 2 risk ratios involving the confounder. Analogous results are nonexistent for the odds ratio, even though the conversion from odds ratios to risk ratios can sometimes be problematic. We present a version of the classical Cornfield inequalities for the odds ratio. The proof is based on the mediant inequality, dating back to ancient Alexandria. We also develop several sharp bivariate bounds of the observed association, where the 2 variables are either risk ratios or odds ratios involving the confounder.

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.

Insights into bear evolution from a Pleistocene polar bear genome.

The polar bear (Ursus maritimus) has become a symbol of the threat to biodiversity from climate change. Understanding polar bear evolutionary history may provide insights into apex carnivore responses and prospects during periods of extreme environmental perturbations. In recent years, genomic studies have examined bear speciation and population history, including evidence for ancient admixture between polar bears and brown bears (Ursus arctos). Here, we extend our earlier studies of a 130,000- to 115,000-y-old polar bear from the Svalbard Archipelago using a 10× coverage genome sequence and 10 new genomes of polar and brown bears from contemporary zones of overlap in northern Alaska. We demonstrate a dramatic decline in effective population size for this ancient polar bear's lineage, followed by a modest increase just before its demise. A slightly higher genetic diversity in the ancient polar bear suggests a severe genetic erosion over a prolonged bottleneck in modern polar bears. Statistical fitting of data to alternative admixture graph scenarios favors at least one ancient introgression event from brown bears into the ancestor of polar bears, possibly dating back over 150,000 y. Gene flow was likely bidirectional, but allelic transfer from brown into polar bear is the strongest detected signal, which contrasts with other published work. These findings may have implications for our understanding of climate change impacts: Polar bears, a specialist Arctic lineage, may not only have undergone severe genetic bottlenecks but also been the recipient of generalist, boreal genetic variants from brown bears during critical phases of Northern Hemisphere glacial oscillations.

Genome-wide association study implicates CHRNA2 in cannabis use disorder.

Cannabis is the most frequently used illicit psychoactive substance worldwide; around one in ten users become dependent. The risk for cannabis use disorder (CUD) has a strong genetic component, with twin heritability estimates ranging from 51 to 70%. Here we performed a genome-wide association study of CUD in 2,387 cases and 48,985 controls, followed by replication in 5,501 cases and 301,041 controls. We report a genome-wide significant risk locus for CUD (P = 9.31 × 10-12) that replicates in an independent population (Preplication = 3.27 × 10-3, Pmeta-analysis = 9.09 × 10-12). The index variant (rs56372821) is a strong expression quantitative trait locus for cholinergic receptor nicotinic α2 subunit (CHRNA2); analyses of the genetically regulated gene expression identified a significant association of CHRNA2 expression with CUD in brain tissue. At the polygenic level, analyses revealed a significant decrease in the risk of CUD with increased load of variants associated with cognitive performance. The results provide biological insights and inform on the genetic architecture of CUD.

The comparative genomics and complex population history of Papio baboons.

Recent studies suggest that closely related species can accumulate substantial genetic and phenotypic differences despite ongoing gene flow, thus challenging traditional ideas regarding the genetics of speciation. Baboons (genus Papio) are Old World monkeys consisting of six readily distinguishable species. Baboon species hybridize in the wild, and prior data imply a complex history of differentiation and introgression. We produced a reference genome assembly for the olive baboon (Papio anubis) and whole-genome sequence data for all six extant species. We document multiple episodes of admixture and introgression during the radiation of Papio baboons, thus demonstrating their value as a model of complex evolutionary divergence, hybridization, and reticulation. These results help inform our understanding of similar cases, including modern humans, Neanderthals, Denisovans, and other ancient hominins.

Whole-genome sequencing of 175 Mongolians uncovers population-specific genetic architecture and gene flow throughout North and East Asia.

The genetic variation in Northern Asian populations is currently undersampled. To address this, we generated a new genetic variation reference panel by whole-genome sequencing of 175 ethnic Mongolians, representing six tribes. The cataloged variation in the panel shows strong population stratification among these tribes, which correlates with the diverse demographic histories in the region. Incorporating our results with the 1000 Genomes Project panel identifies derived alleles shared between Finns and Mongolians/Siberians, suggesting that substantial gene flow between northern Eurasian populations has occurred in the past. Furthermore, we highlight that North, East, and Southeast Asian populations are more aligned with each other than these groups are with South Asian and Oceanian populations.

admixturegraph: an R package for admixture graph manipulation and fitting.

SUMMARY: Admixture graphs generalize phylogenetic trees by allowing genetic lineages to merge as well as split. In this paper we present the R package admixturegraph containing tools for building and visualizing admixture graphs, for fitting graph parameters to genetic data, for visualizing goodness of fit and for evaluating the relative goodness of fit between different graphs. AVAILABILITY AND IMPLEMENTATION: GitHub: https://github.com/mailund/admixture_graph and CRAN: https://cran.r-project.org/web/packages/admixturegraph . CONTACT: mailund@birc.au.dk .