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Copenhagen, Denmark

Foote A.D.,Center for GeoGenetics
Evolutionary Ecology Research | Year: 2012

Background: Studies of ecological speciation tend to focus on a few model biological systems. In contrast, few studies on non-model organisms have been able to infer ecological speciation as the underlying mechanism of evolutionary divergence. Questions: What are the pitfalls in studying ecological speciation in non-model organisms that lead to this bias? What alternative approaches might redress the balance? Organism: Genetically differentiated types of the killer whale (Orcinus orca) exhibiting differences in prey preference, habitat use, morphology, and behaviour. Methods: Review of the literature on killer whale evolutionary ecology in search of any difficulty in demonstrating causal links between variation in phenotype, ecology, and reproductive isolation in this non-model organism. Results: At present, we do not have enough evidence to conclude that adaptive phenotype traits linked to ecological variation underlie reproductive isolation between sympatric killer whale types. Perhaps ecological speciation has occurred, but it is hard to prove. We will probably face this outcome whenever we wish to address non-model organisms - species in which it is not easy to apply experimental approaches and comparative studies among multiple taxon pairs. We need new genomic approaches that identify genes under selection and then link alleles to phenotypic differences and reproductive isolation. © 2012 Andrew D. Foote. Source

Fumagalli M.,University of California at Berkeley | Vieira F.G.,University of California at Berkeley | Korneliussen T.S.,Center for GeoGenetics | Korneliussen T.S.,Copenhagen University | And 5 more authors.
Genetics | Year: 2013

Over the past few years, new high-throughput DNA sequencing technologies have dramatically increased speed and reduced sequencing costs. However, the use of these sequencing technologies is often challenged by errors and biases associated with the bioinformatical methods used for analyzing the data. In particular, the use of naïve methods to identify polymorphic sites and infer genotypes can inflate downstream analyses. Recently, explicit modeling of genotype probability distributions has been proposed as a method for taking genotype call uncertainty into account. Based on this idea, we propose a novel method for quantifying population genetic differentiation from next-generation sequencing data. In addition, we present a strategy for investigating population structure via principal components analysis. Through extensive simulations, we compare the new method herein proposed to approaches based on genotype calling and demonstrate a marked improvement in estimation accuracy for a wide range of conditions. We apply the method to a large-scale genomic data set of domesticated and wild silkworms sequenced at low coverage. We find that we can infer the fine-scale genetic structure of the sampled individuals, suggesting that employing this new method is useful for investigating the genetic relationships of populations sampled at low coverage. © 2013 by the Genetics Society of America. Source

Korneliussen T.S.,Center for GeoGenetics | Moltke I.,Copenhagen University
Bioinformatics | Year: 2015

Motivation: Pairwise relatedness estimation is important in many contexts such as disease mapping and population genetics. However, all existing estimation methods are based on called genotypes, which is not ideal for next-generation sequencing (NGS) data of low depth from which genotypes cannot be called with high certainty. Results: We present a software tool, NgsRelate, for estimating pairwise relatedness from NGS data. It provides maximum likelihood estimates that are based on genotype likelihoods instead of genotypes and thereby takes the inherent uncertainty of the genotypes into account. Using both simulated and real data, we show that NgsRelate provides markedly better estimates for low-depth NGS data than two state-of-the-art genotype-based methods. © The Author 2015. Published by Oxford University Press. All rights reserved. Source

News Article
Site: http://www.treehugger.com/feeds/category/climate-change/

In 1992, Ole Karsholt and Jan Pedersen started collecting bugs in light traps on the roof of the Natural History Museum of Denmark in Copenhagen. A quarter-million bugs later, their data on 1543 species of moths and beetles provides astounding evidence that the we don't need to wait for 2°C of warming before seeing significant effects of temperature change on the insect community. As might be predicted, the insect "specialists" -- bugs that eat only a single species of plant -- experience temperature changes more dramatically than generalists. "Earlier studies have confirmed that specialist species also respond rapidly to destruction of their habitats, so we are dealing with a very sensitive group of animals” according to postdoc Philip Francis Thomsen from the Center for GeoGenetics, one of the authors of the study published in the Journal of Animal Ecology. The nut weevil, Curculio nucum, a connoisseur of the hazel nut, visited the museum roof in the early years of the study but disappeared in later years. Its place was taken by the acorn weevil, Curculio glandium, suggesting that both species are moving northwards to find cooler domains. The data on other specialist species supported the hypothesis, showing increases in populations of hot-dwelling species and decreases in those that prefer cooler climes. Insects that feed only during the non-mobile larval stage were seen to range quite widely from the habitats of their infancy at least 10 km distant from the museum roof. The team succeeded to register seven moth species and two beetles which had not previously been on record as inhabiting Denmark, including the Asian lady beetle (Harmonia axyridis) (pictured) which has now spread throughout the country and is considered an invasive species. The conversion of the data gained from the long-term voluntary monitoring project proves how invaluable such records can be. The authors hope their results will return funding for nature monitoring projects so that humanity does not have to depend on a spattering of committed enthusiasts. It seems like citizen scientists could lend a hand in the effort with a little political guidance, benefiting both the people involved and the state of scientific knowledge of our environment.

Korneliussen T.S.,Center for GeoGenetics | Albrechtsen A.,Copenhagen University | Nielsen R.,Center for GeoGenetics | Nielsen R.,University of California at Berkeley
BMC Bioinformatics | Year: 2014

Background: High-throughput DNA sequencing technologies are generating vast amounts of data. Fast, flexible and memory efficient implementations are needed in order to facilitate analyses of thousands of samples simultaneously. Results: We present a multithreaded program suite called ANGSD. This program can calculate various summary statistics, and perform association mapping and population genetic analyses utilizing the full information in next generation sequencing data by working directly on the raw sequencing data or by using genotype likelihoods. Conclusions: The open source c/c++ program ANGSD is available at . The program is tested and validated on GNU/Linux systems. The program facilitates multiple input formats including BAM and imputed beagle genotype probability files. The program allow the user to choose between combinations of existing methods and can perform analysis that is not implemented elsewhere. © 2014 Korneliussen et al. Source

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