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Leppälä, K.

Publications and source records attributed to Leppälä, K..

2 recordsLinked to original sources

Five-leaf generalizations of the D-statistic revealthe 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 {Delta}-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 {Delta}-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 {Delta}-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.

genetics↗

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 address 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. Author SummaryOne way of summarizing historical relationships between genetic samples is by constructing an admixture graph. An admixture graph describes the demographic history of a set of populations as a directed acyclic graph representing population splits and mergers. The inference of admixture graphs is currently done via greedy search algorithms that may fail to find the global optimum. We here improve on these approaches by developing a novel MCMC sampling method, AdmixtureBayes, that can sample from the posterior distribution of admixture graphs. This enables an efficient search of the entire state space as well as the ability to report a level of confidence in the sampled graphs. We apply AdmixtureBayes to a set of Native American and Arctic genomes to reconstruct the demographic history of these populations and report posterior probabilities of specific admixture events. While some previous studies have identified the ancient Saqqaq culture as a source of introgression into Athabascans, we instead find that it is the Siberian Koryak population, not the Saqqaq, that serves as the best proxy for gene flow into Athabascans.

genetics↗