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      Reference-Free Population Genomics from Next-Generation Transcriptome Data and the Vertebrate–Invertebrate Gap

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          Abstract

          In animals, the population genomic literature is dominated by two taxa, namely mammals and drosophilids, in which fully sequenced, well-annotated genomes have been available for years. Data from other metazoan phyla are scarce, probably because the vast majority of living species still lack a closely related reference genome. Here we achieve de novo, reference-free population genomic analysis from wild samples in five non-model animal species, based on next-generation sequencing transcriptome data. We introduce a pipe-line for cDNA assembly, read mapping, SNP/genotype calling, and data cleaning, with specific focus on the issue of hidden paralogy detection. In two species for which a reference genome is available, similar results were obtained whether the reference was used or not, demonstrating the robustness of our de novo inferences. The population genomic profile of a hare, a turtle, an oyster, a tunicate, and a termite were found to be intermediate between those of human and Drosophila, indicating that the discordant genomic diversity patterns that have been reported between these two species do not reflect a generalized vertebrate versus invertebrate gap. The genomic average diversity was generally higher in invertebrates than in vertebrates (with the notable exception of termite), in agreement with the notion that population size tends to be larger in the former than in the latter. The non-synonymous to synonymous ratio, however, did not differ significantly between vertebrates and invertebrates, even though it was negatively correlated with genetic diversity within each of the two groups. This study opens promising perspective regarding genome-wide population analyses of non-model organisms and the influence of population size on non-synonymous versus synonymous diversity.

          Author Summary

          The analysis of genomic variation between individuals of a given species has so far been restricted to a small number of model organisms, such as human and fruitfly, for which a fully sequenced, well-annotated reference genome was available. Here we show that, thanks to next-generation high-throughput sequencing technologies and appropriate genotype-calling methods, de novo population genomic analysis is possible in absence of a reference genome. We characterize the genomic level of neutral and selected polymorphism in five non-model animal species, two vertebrates and three invertebrates, paying particular attention to the treatment of multi-copy genes. The analyses demonstrate the influence of population size on genetic diversity in animals, the two vertebrates (hare, turtle) and the social insect (termite) being less polymorphic than the two marine invertebrates (oyster, tunicate) in our sample. Interestingly, genomic indicators of the efficiency of natural selection, both purifying and adaptive, did not vary in a simple, predictable way across organisms. These results prove the value of a diversified sampling of species when it comes to understand the determinants of genome evolutionary dynamics.

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          Most cited references63

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          Population genomics of domestic and wild yeasts

          Since the completion of the genome sequence of Saccharomyces cerevisiae in 19961,2, there has been an exponential increase in complete genome sequences accompanied by great advances in our understanding of genome evolution. Although little is known about the natural and life histories of yeasts in the wild, there are an increasing number of studies looking at ecological and geographic distributions3,4, population structure5-8, and sexual versus asexual reproduction9,10. Less well understood at the whole genome level are the evolutionary processes acting within populations and species leading to adaptation to different environments, phenotypic differences and reproductive isolation. Here we present one- to four-fold or more coverage of the genome sequences of over seventy isolates of the baker's yeast, S. cerevisiae, and its closest relative, S. paradoxus. We examine variation in gene content, SNPs, indels, copy numbers and transposable elements. We find that phenotypic variation broadly correlates with global genome-wide phylogenetic relationships. Interestingly, S. paradoxus populations are well delineated along geographic boundaries while the variation among worldwide S. cerevisiae isolates shows less differentiation and is comparable to a single S. paradoxus population. Rather than one or two domestication events leading to the extant baker's yeasts, the population structure of S. cerevisiae consists of a few well-defined geographically isolated lineages and many different mosaics of these lineages, supporting the idea that human influence provided the opportunity for cross-breeding and production of new combinations of pre-existing variation.
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            A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data

            (2013)
            Motivation: 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. Results: 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. Availability: http://samtools.sourceforge.net. Contact: hengli@broadinstitute.org.
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              Biased gene conversion and the evolution of mammalian genomic landscapes.

              Recombination is typically thought of as a symmetrical process resulting in large-scale reciprocal genetic exchanges between homologous chromosomes. Recombination events, however, are also accompanied by short-scale, unidirectional exchanges known as gene conversion in the neighborhood of the initiating double-strand break. A large body of evidence suggests that gene conversion is GC-biased in many eukaryotes, including mammals and human. AT/GC heterozygotes produce more GC- than AT-gametes, thus conferring a population advantage to GC-alleles in high-recombining regions. This apparently unimportant feature of our molecular machinery has major evolutionary consequences. Structurally, GC-biased gene conversion explains the spatial distribution of GC-content in mammalian genomes-the so-called isochore structure. Functionally, GC-biased gene conversion promotes the segregation and fixation of deleterious AT --> GC mutations, thus increasing our genomic mutation load. Here we review the recent evidence for a GC-biased gene conversion process in mammals, and its consequences for genomic landscapes, molecular evolution, and human functional genomics.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                April 2013
                April 2013
                11 April 2013
                : 9
                : 4
                : e1003457
                Affiliations
                [1 ]Université Montpellier 2, CNRS UMR 5554, Institut des Sciences de l'Evolution de Montpellier, Montpellier, France
                [2 ]Université François Rabelais, CNRS UMR 7261, Institut de Recherche sur la Biologie de l'Insecte, Faculté des Sciences et Techniques, Tours, France
                [3 ]Centro de Investigação em Biodiversidade e Recursos Genéticos (CIBIO), Universidade do Porto, InBIO Laboratório Associado, Campus Agrário de Vairão, Vairão, Portugal
                [4 ]Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
                [5 ]Wildlife Biology Program, College of Forestry and Conservation, University of Montana, Missoula, Montana, United States of America
                University of Cambridge, United Kingdom
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: NG SG PG. Performed the experiments: PG JM-F NB MB NF PCA. Analyzed the data: AB EL VC BN JM-F MC JML NG. Contributed reagents/materials/analysis tools: SG PG JM-F PCA NB BN KB. Wrote the paper: NG.

                Article
                PGENETICS-D-12-02361
                10.1371/journal.pgen.1003457
                3623758
                23593039
                72394ed3-0bb5-45ca-ba96-f78333f7fe47
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 September 2012
                : 4 March 2013
                Page count
                Pages: 15
                Funding
                This work was supported by a European Research Council (ERC) grant to NG (ERC PopPhyl 232971). Further support was obtained from the Portuguese Science and Technology Foundation, FCT (project PTDC/BIA-EVF/111931/2009, co-funded by FEDER/COMPETE; post-doc grants SFRH/BPD/43264/2008, PTDC/BIA-EVF/115069/2009 and SFRH/BPD/72343/2010 to JM-F and MC respectively, co-funded by the E. Social Fund). The work of SG and BN was supported by Agropolis Resource Centre for Crop Conservation, Adaptation and Diversity, a flagship project of the Agropolis Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Evolutionary Biology
                Evolutionary Processes
                Adaptation
                Genetic Drift
                Natural Selection
                Comparative Genomics
                Evolutionary Genetics
                Genomic Evolution
                Population Genetics
                Genomics
                Genome Evolution
                Genome Expression Analysis

                Genetics
                Genetics

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