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      Recent advances in conservation and population genomics data analysis

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          Abstract

          New computational methods and next‐generation sequencing (NGS) approaches have enabled the use of thousands or hundreds of thousands of genetic markers to address previously intractable questions. The methods and massive marker sets present both new data analysis challenges and opportunities to visualize, understand, and apply population and conservation genomic data in novel ways. The large scale and complexity of NGS data also increases the expertise and effort required to thoroughly and thoughtfully analyze and interpret data. To aid in this endeavor, a recent workshop entitled “Population Genomic Data Analysis,” also known as “ConGen 2017,” was held at the University of Montana. The ConGen workshop brought 15 instructors together with knowledge in a wide range of topics including NGS data filtering, genome assembly, genomic monitoring of effective population size, migration modeling, detecting adaptive genomic variation, genomewide association analysis, inbreeding depression, and landscape genomics. Here, we summarize the major themes of the workshop and the important take‐home points that were offered to students throughout. We emphasize increasing participation by women in population and conservation genomics as a vital step for the advancement of science. Some important themes that emerged during the workshop included the need for data visualization and its importance in finding problematic data, the effects of data filtering choices on downstream population genomic analyses, the increasing availability of whole‐genome sequencing, and the new challenges it presents. Our goal here is to help motivate and educate a worldwide audience to improve population genomic data analysis and interpretation, and thereby advance the contribution of genomics to molecular ecology, evolutionary biology, and especially to the conservation of biodiversity.

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          Sex-dependent dominance at a single locus maintains variation in age at maturity in salmon.

          Males and females share many traits that have a common genetic basis; however, selection on these traits often differs between the sexes, leading to sexual conflict. Under such sexual antagonism, theory predicts the evolution of genetic architectures that resolve this sexual conflict. Yet, despite intense theoretical and empirical interest, the specific loci underlying sexually antagonistic phenotypes have rarely been identified, limiting our understanding of how sexual conflict impacts genome evolution and the maintenance of genetic diversity. Here we identify a large effect locus controlling age at maturity in Atlantic salmon (Salmo salar), an important fitness trait in which selection favours earlier maturation in males than females, and show it is a clear example of sex-dependent dominance that reduces intralocus sexual conflict and maintains adaptive variation in wild populations. Using high-density single nucleotide polymorphism data across 57 wild populations and whole genome re-sequencing, we find that the vestigial-like family member 3 gene (VGLL3) exhibits sex-dependent dominance in salmon, promoting earlier and later maturation in males and females, respectively. VGLL3, an adiposity regulator associated with size and age at maturity in humans, explained 39% of phenotypic variation, an unexpectedly large proportion for what is usually considered a highly polygenic trait. Such large effects are predicted under balancing selection from either sexually antagonistic or spatially varying selection. Our results provide the first empirical example of dominance reversal allowing greater optimization of phenotypes within each sex, contributing to the resolution of sexual conflict in a major and widespread evolutionary trade-off between age and size at maturity. They also provide key empirical evidence for how variation in reproductive strategies can be maintained over large geographical scales. We anticipate these findings will have a substantial impact on population management in a range of harvested species where trends towards earlier maturation have been observed.
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            Lost in parameter space: a road map for stacks

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              Genomic patterns of homozygosity in worldwide human populations.

              Genome-wide patterns of homozygosity runs and their variation across individuals provide a valuable and often untapped resource for studying human genetic diversity and evolutionary history. Using genotype data at 577,489 autosomal SNPs, we employed a likelihood-based approach to identify runs of homozygosity (ROH) in 1,839 individuals representing 64 worldwide populations, classifying them by length into three classes-short, intermediate, and long-with a model-based clustering algorithm. For each class, the number and total length of ROH per individual show considerable variation across individuals and populations. The total lengths of short and intermediate ROH per individual increase with the distance of a population from East Africa, in agreement with similar patterns previously observed for locus-wise homozygosity and linkage disequilibrium. By contrast, total lengths of long ROH show large interindividual variations that probably reflect recent inbreeding patterns, with higher values occurring more often in populations with known high frequencies of consanguineous unions. Across the genome, distributions of ROH are not uniform, and they have distinctive continental patterns. ROH frequencies across the genome are correlated with local genomic variables such as recombination rate, as well as with signals of recent positive selection. In addition, long ROH are more frequent in genomic regions harboring genes associated with autosomal-dominant diseases than in regions not implicated in Mendelian diseases. These results provide insight into the way in which homozygosity patterns are produced, and they generate baseline homozygosity patterns that can be used to aid homozygosity mapping of genes associated with recessive diseases. Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                shendri4@gmail.com
                Journal
                Evol Appl
                Evol Appl
                10.1111/(ISSN)1752-4571
                EVA
                Evolutionary Applications
                John Wiley and Sons Inc. (Hoboken )
                1752-4571
                20 August 2018
                September 2018
                : 11
                : 8 ( doiID: 10.1111/eva.2018.11.issue-8 )
                : 1197-1211
                Affiliations
                [ 1 ] Institute for Bioinformatics and Evolutionary Studies University of Idaho Moscow Idaho
                [ 2 ] Fisheries Ecology Division Southwest Fisheries Science Center National Marine Fisheries Service National Oceanic and Atmospheric Administration Santa Cruz California
                [ 3 ] University of California Santa Cruz California
                [ 4 ] Division of Biological Sciences University of Montana Missoula Montana
                [ 5 ] Département de Biologie Institut de Biologie Intégrative et des Systèmes (IBIS) Université Laval Québec Québec Canada
                [ 6 ] Department of Biology Colorado State University Fort Collins Colorado
                [ 7 ] Flathead Lake Biological Station Montana Conservation Genomics Laboratory Division of Biological Science University of Montana Missoula Montana
                [ 8 ] Wildlife Program Fish and Wildlife Genomics Group College of Forestry and Conservation University of Montana Missoula Montana
                [ 9 ] Department of Biology Centre for Biomedical Research University of Victoria Victoria British Columbia Canada
                [ 10 ] Department of Biological Sciences California State University San Marcos San Marcos California
                [ 11 ] NOAA Fisheries Northwest Fisheries Science Center Seattle Washington
                Author notes
                [*] [* ] Correspondence

                Sarah Hendricks, Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID 83844.

                Email: shendri4@ 123456gmail.com

                Author information
                http://orcid.org/0000-0001-9571-9461
                http://orcid.org/0000-0003-1326-0840
                http://orcid.org/0000-0002-7587-3004
                http://orcid.org/0000-0003-3362-7590
                Article
                EVA12659
                10.1111/eva.12659
                6099823
                4f2abbff-ef93-49a9-8048-b192baa9c666
                © 2018 The Authors. Evolutionary Applications 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
                : 20 February 2018
                : 08 May 2018
                : 21 May 2018
                Page count
                Figures: 2, Tables: 0, Pages: 12, Words: 12729
                Funding
                Funded by: Bioinformatics and Computational Biology Program, University of Idaho
                Funded by: American Genetic Association (AGA)
                Funded by: the US Geological Survey (USGS)
                Funded by: NSF grant
                Award ID: DoB‐1639014
                Award ID: DEB‐1655809
                Funded by: NASA grant
                Award ID: NNX14AB84G
                Funded by: NSF
                Award ID: DEB‐1258203
                Categories
                Meeting Report
                Meeting Report
                Custom metadata
                2.0
                eva12659
                September 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.4.4 mode:remove_FC converted:20.08.2018

                Evolutionary Biology
                bioinformatics pipeline,conservation genomics workshop,diversity in stem,landscape genomics,population genomics

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