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      Genomic patterns in the widespread Eurasian lynx shaped by Late Quaternary climatic fluctuations and anthropogenic impacts

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          Abstract

          Disentangling the contribution of long‐term evolutionary processes and recent anthropogenic impacts to current genetic patterns of wildlife species is key to assessing genetic risks and designing conservation strategies. Here, we used 80 whole nuclear genomes and 96 mitogenomes from populations of the Eurasian lynx covering a range of conservation statuses, climatic zones and subspecies across Eurasia to infer the demographic history, reconstruct genetic patterns, and discuss the influence of long‐term isolation and/or more recent human‐driven changes. Our results show that Eurasian lynx populations shared a common history until 100,000 years ago, when Asian and European populations started to diverge and both entered a period of continuous and widespread decline, with western populations, except Kirov, maintaining lower effective sizes than eastern populations. Population declines and increased isolation in more recent times probably drove the genetic differentiation between geographically and ecologically close westernmost European populations. By contrast, and despite the wide range of habitats covered, populations are quite homogeneous genetically across the Asian range, showing a pattern of isolation by distance and providing little genetic support for the several proposed subspecies. Mitogenomic and nuclear divergences and population declines starting during the Late Pleistocene can be mostly attributed to climatic fluctuations and early human influence, but the widespread and sustained decline since the Holocene is more probably the consequence of anthropogenic impacts which intensified in recent centuries, especially in western Europe. Genetic erosion in isolated European populations and lack of evidence for long‐term isolation argue for the restoration of lost population connectivity.

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          A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.

          Heng Li (2011)
          Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. http://samtools.sourceforge.net. hengli@broadinstitute.org.
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            PopGenome: An Efficient Swiss Army Knife for Population Genomic Analyses in R

            Although many computer programs can perform population genetics calculations, they are typically limited in the analyses and data input formats they offer; few applications can process the large data sets produced by whole-genome resequencing projects. Furthermore, there is no coherent framework for the easy integration of new statistics into existing pipelines, hindering the development and application of new population genetics and genomics approaches. Here, we present PopGenome, a population genomics package for the R software environment (a de facto standard for statistical analyses). PopGenome can efficiently process genome-scale data as well as large sets of individual loci. It reads DNA alignments and single-nucleotide polymorphism (SNP) data sets in most common formats, including those used by the HapMap, 1000 human genomes, and 1001 Arabidopsis genomes projects. PopGenome also reads associated annotation files in GFF format, enabling users to easily define regions or classify SNPs based on their annotation; all analyses can also be applied to sliding windows. PopGenome offers a wide range of diverse population genetics analyses, including neutrality tests as well as statistics for population differentiation, linkage disequilibrium, and recombination. PopGenome is linked to Hudson’s MS and Ewing’s MSMS programs to assess statistical significance based on coalescent simulations. PopGenome’s integration in R facilitates effortless and reproducible downstream analyses as well as the production of publication-quality graphics. Developers can easily incorporate new analyses methods into the PopGenome framework. PopGenome and R are freely available from CRAN (http://cran.r-project.org/) for all major operating systems under the GNU General Public License.
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              Genetic rescue of small inbred populations: meta-analysis reveals large and consistent benefits of gene flow.

              Many species have fragmented distribution with small isolated populations suffering inbreeding depression and/or reduced ability to evolve. Without gene flow from another population within the species (genetic rescue), these populations are likely to be extirpated. However, there have been only ~ 20 published cases of such outcrossing for conservation purposes, probably a very low proportion of populations that would potentially benefit. As one impediment to genetic rescues is the lack of an overview of the magnitude and consistency of genetic rescue effects in wild species, I carried out a meta-analysis. Outcrossing of inbred populations resulted in beneficial effects in 92.9% of 156 cases screened as having a low risk of outbreeding depression. The median increase in composite fitness (combined fecundity and survival) following outcrossing was 148% in stressful environments and 45% in benign ones. Fitness benefits also increased significantly with maternal ΔF (reduction in inbreeding coefficient due to gene flow) and for naturally outbreeding versus inbreeding species. However, benefits did not differ significantly among invertebrates, vertebrates and plants. Evolutionary potential for fitness characters in inbred populations also benefited from gene flow. There are no scientific impediments to the widespread use of outcrossing to genetically rescue inbred populations of naturally outbreeding species, provided potential crosses have a low risk of outbreeding depression. I provide revised guidelines for the management of genetic rescue attempts.
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                Author and article information

                Contributors
                godoy@ebd.csic.es
                Journal
                Mol Ecol
                Mol. Ecol
                10.1111/(ISSN)1365-294X
                MEC
                Molecular Ecology
                John Wiley and Sons Inc. (Hoboken )
                0962-1083
                1365-294X
                23 February 2020
                February 2020
                : 29
                : 4 ( doiID: 10.1111/mec.v29.4 )
                : 812-828
                Affiliations
                [ 1 ] Department of Integrative Ecology Estación Biológica de Doñana (CSIC) Seville Spain
                [ 2 ] School of Biological and Environmental Sciences Liverpool John Moores University Liverpool UK
                [ 3 ] Mammal Research Institute Polish Academy of Sciences Białowieża Poland
                [ 4 ] Department of Animal Ecology Russian Research Institute of Game Management and Fur Farming Kirov Russia
                [ 5 ] Biological Faculty of Moscow State University Moscow Russia
                [ 6 ] Laboratory of Ecology and Conservation of Animals Pacific Institute of Geography of Far East Branch of Russian Academy of Sciences Vladivostok Russia
                [ 7 ] Far Eastern Federal University Vladivostok Russia
                [ 8 ] Institute for Biological Problems of Cryolithozone Siberian Division of the Russian Academy of Sciences Yakutsk Russia
                [ 9 ] Department of Hunting Resources Russian Research Institute of Game Management and Fur Farming Kirov Russia
                [ 10 ] Department of Hunting and Wildlife Management Latvijas Valsts mežzinātnes institūts "Silava" Salaspils Latvia
                [ 11 ] Institute of General and Experimental Biology Mongolian Academy of Science Ulaanbaatar Mongolia
                [ 12 ] Natural History Museum Belgrade Serbia
                [ 13 ] Institute of Biology University of Białystok Białystok Poland
                Author notes
                [*] [* ] Correspondence

                José A. Godoy, Department of Integrative Ecology, Estación Biológica de Doñana (CSIC), C/ Américo Vespucio 26, Seville, Spain.

                Email: godoy@ 123456ebd.csic.es

                Author information
                https://orcid.org/0000-0002-9676-7155
                https://orcid.org/0000-0001-7502-9471
                Article
                MEC15366
                10.1111/mec.15366
                7064982
                31995648
                d31b9cfa-3ca3-477f-9a1c-768967ede557
                © 2020 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 05 April 2019
                : 27 December 2019
                : 16 January 2020
                Page count
                Figures: 5, Tables: 0, Pages: 17, Words: 13367
                Funding
                Funded by: Russian Science Foundation , open-funder-registry 10.13039/501100006769;
                Award ID: 18‐14‐00093
                Funded by: “la Caixa” Foundation , open-funder-registry 10.13039/100010434;
                Funded by: Ministerio de Ciencia e Innovación , open-funder-registry 10.13039/501100004837;
                Award ID: SEV‐2012‐0262
                Funded by: Narodowe Centrum Nauki , open-funder-registry 10.13039/501100004281;
                Award ID: 2014/15/B/ NZ8/00212
                Funded by: Dirección General de Investigación Científica y Técnica , open-funder-registry 10.13039/501100006527;
                Award ID: CGL2013‐47755‐P
                Funded by: FP7 People: Marie‐Curie Actions
                Award ID: PIRSES‐GA‐2009‐247652
                Categories
                Original Article
                Original Articles
                Phylogeography
                Custom metadata
                2.0
                February 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.7.7 mode:remove_FC converted:11.03.2020

                Ecology
                carnivore,eurasian lynx,lynx lynx,mitogenomes,phylogeography,population genomics
                Ecology
                carnivore, eurasian lynx, lynx lynx, mitogenomes, phylogeography, population genomics

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