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      Comparative assessment of range‐wide patterns of genetic diversity and structure with SNPs and microsatellites: A case study with Iberian amphibians

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          Abstract

          Reduced representation genome sequencing has popularized the application of single nucleotide polymorphisms (SNPs) to address evolutionary and conservation questions in nonmodel organisms. Patterns of genetic structure and diversity based on SNPs often diverge from those obtained with microsatellites to different degrees, but few studies have explicitly compared their performance under similar sampling regimes in a shared analytical framework. We compared range‐wide patterns of genetic structure and diversity in two amphibians endemic to the Iberian Peninsula: Hyla molleri and Pelobates cultripes, based on microsatellite (18 and 14 loci) and SNP (15,412 and 33,140 loci) datasets of comparable sample size and spatial extent. Model‐based clustering analyses with STRUCTURE revealed minor differences in genetic structure between marker types, but inconsistent values of the optimal number of populations (K) inferred. SNPs yielded more repeatable and less admixed ancestries with increasing K compared to microsatellites. Genetic diversity was weakly correlated between marker types, with SNPs providing a better representation of southern refugia and of gradients of genetic diversity congruent with the demographic history of both species. Our results suggest that the larger number of loci in a SNP dataset can provide more reliable inferences of patterns of genetic structure and diversity than a typical microsatellite dataset, at least at the spatial and temporal scales investigated.

          Abstract

          We compared patterns of genetic structure and diversity between microsatellites and SNPs in two amphibians from the Iberian Peninsula: Hyla molleri and Pelobates cultripes. Larger number of loci from SNP dataset can provide more reliable inferences of patterns of genetic structure and diversity than a typical microsatellite dataset (photo: Pelobates cultripes; credits: Guillermo Velo‐Antón).

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          Most cited references53

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          Inference from Iterative Simulation Using Multiple Sequences

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            Genome-wide genetic marker discovery and genotyping using next-generation sequencing.

            The advent of next-generation sequencing (NGS) has revolutionized genomic and transcriptomic approaches to biology. These new sequencing tools are also valuable for the discovery, validation and assessment of genetic markers in populations. Here we review and discuss best practices for several NGS methods for genome-wide genetic marker development and genotyping that use restriction enzyme digestion of target genomes to reduce the complexity of the target. These new methods -- which include reduced-representation sequencing using reduced-representation libraries (RRLs) or complexity reduction of polymorphic sequences (CRoPS), restriction-site-associated DNA sequencing (RAD-seq) and low coverage genotyping -- are applicable to both model organisms with high-quality reference genome sequences and, excitingly, to non-model species with no existing genomic data.
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              The program structure does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem.

              Inferences of population structure and more precisely the identification of genetically homogeneous groups of individuals are essential to the fields of ecology, evolutionary biology and conservation biology. Such population structure inferences are routinely investigated via the program structure implementing a Bayesian algorithm to identify groups of individuals at Hardy-Weinberg and linkage equilibrium. While the method is performing relatively well under various population models with even sampling between subpopulations, the robustness of the method to uneven sample size between subpopulations and/or hierarchical levels of population structure has not yet been tested despite being commonly encountered in empirical data sets. In this study, I used simulated and empirical microsatellite data sets to investigate the impact of uneven sample size between subpopulations and/or hierarchical levels of population structure on the detected population structure. The results demonstrated that uneven sampling often leads to wrong inferences on hierarchical structure and downward-biased estimates of the true number of subpopulations. Distinct subpopulations with reduced sampling tended to be merged together, while at the same time, individuals from extensively sampled subpopulations were generally split, despite belonging to the same panmictic population. Four new supervised methods to detect the number of clusters were developed and tested as part of this study and were found to outperform the existing methods using both evenly and unevenly sampled data sets. Additionally, a subsampling strategy aiming to reduce sampling unevenness between subpopulations is presented and tested. These results altogether demonstrate that when sampling evenness is accounted for, the detection of the correct population structure is greatly improved.
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                Author and article information

                Contributors
                miguelcamachosanchez@gmail.com
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                15 September 2020
                October 2020
                : 10
                : 19 ( doiID: 10.1002/ece3.v10.19 )
                : 10353-10363
                Affiliations
                [ 1 ] CIBIO/InBIO Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto Vairão Portugal
                [ 2 ] Museo Nacional de Ciencias Naturales CSIC Madrid Spain
                [ 3 ] Centre for Biodiversity Analysis and Research School of Biology The Australian National University Canberra ACT Australia
                Author notes
                [*] [* ] Correspondence

                Miguel Camacho‐Sanchez, CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto, Vairão, Portugal.

                Email: miguelcamachosanchez@ 123456gmail.com

                Author information
                https://orcid.org/0000-0002-6385-7963
                https://orcid.org/0000-0002-9483-5695
                https://orcid.org/0000-0002-4716-6134
                https://orcid.org/0000-0003-3396-9822
                https://orcid.org/0000-0002-2260-226X
                https://orcid.org/0000-0002-6070-0506
                https://orcid.org/0000-0001-5313-7279
                https://orcid.org/0000-0003-4368-4708
                Article
                ECE36670
                10.1002/ece3.6670
                7548196
                33072264
                e5824ff0-9d6e-4595-8d75-fbf3e25aeb86
                © 2020 The Authors. Ecology and Evolution 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
                : 21 July 2020
                : 22 July 2020
                Page count
                Figures: 3, Tables: 0, Pages: 11, Words: 7975
                Funding
                Funded by: Fundação para a Ciência e a Tecnologia , open-funder-registry 10.13039/501100001871;
                Award ID: CEECIND/01464/2017
                Award ID: DL57/2016
                Award ID: IF/01425/2014
                Award ID: PTDC/BIA‐BIC/3545/2014
                Funded by: Programa Operacional Temático Factores de Competitividade , open-funder-registry 10.13039/501100011929;
                Award ID: POCI‐01‐0145‐FEDER‐016853
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                October 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.2 mode:remove_FC converted:11.10.2020

                Evolutionary Biology
                dartseq,hyla molleri,iberian peninsula,pelobatescultripes,population genetics,microsatellites

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