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Phylodynamics is an area of population genetics that uses genetic sequence data to estimate past population dynamics. Modern state‐of‐the‐art Bayesian nonparametric methods for recovering population size trajectories of unknown form use either change‐point models or Gaussian process priors. Change‐point models suffer from computational issues when the number of change‐points is unknown and needs to be estimated. Gaussian process‐based methods lack local adaptivity and cannot accurately recover trajectories that exhibit features such as abrupt changes in trend or varying levels of smoothness. We propose a novel, locally adaptive approach to Bayesian nonparametric phylodynamic inference that has the flexibility to accommodate a large class of functional behaviors. Local adaptivity results from modeling the log‐transformed effective population size a priori as a horseshoe Markov random field, a recently proposed statistical model that blends together the best properties of the change‐point and Gaussian process modeling paradigms. We use simulated data to assess model performance, and find that our proposed method results in reduced bias and increased precision when compared to contemporary methods. We also use our models to reconstruct past changes in genetic diversity of human hepatitis C virus in Egypt and to estimate population size changes of ancient and modern steppe bison. These analyses show that our new method captures features of the population size trajectories that were missed by the state‐of‐the‐art methods.

 

A newly described population of polar bears in southeastern Greenland suggests the potential for climate refugia. 

Many humans carry genes from Neanderthals, a legacy of past admixture. Existing methods detect this archaic hominin ancestry within human genomes using patterns of linkage disequilibrium or direct comparison to Neanderthal genomes. Each of these methods is limited in sensitivity and scalability. We describe a new ancestral recombination graph inference algorithm that scales to large genome-wide datasets and demonstrate its accuracy on real and simulated data. We then generate a genome-wide ancestral recombination graph including human and archaic hominin genomes. From this, we generate a map within human genomes of archaic ancestry and of genomic regions not shared with archaic hominins either by admixture or incomplete lineage sorting. We find that only 1.5 to 7% of the modern human genome is uniquely human. We also find evidence of multiple bursts of adaptive changes specific to modern humans within the past 600,000 years involving genes related to brain development and function. 

Abstract The Andean bear is the only extant member of the Tremarctine subfamily and the only extant ursid species to inhabit South America. Here, we present an annotated de novo assembly of a nuclear genome from a captive-born female Andean bear, Mischief, generated using a combination of short and long DNA and RNA reads. Our final assembly has a length of 2.23 Gb, and a scaffold N50 of 21.12 Mb, contig N50 of 23.5 kb, and BUSCO score of 88%. The Andean bear genome will be a useful resource for exploring the complex phylogenetic history of extinct and extant bear species and for future population genetics studies of Andean bears.