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      Deep connections: Divergence histories with gene flow in mesophotic Agaricia corals

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          Abstract

          Largely understudied, mesophotic coral ecosystems lie below shallow reefs (at >30 m depth) and comprise ecologically distinct communities. Brooding reproductive modes appear to predominate among mesophotic‐specialist corals and may limit genetic connectivity among populations. Using reduced representation genomic sequencing, we assessed spatial population genetic structure at 50 m depth in an ecologically important mesophotic‐specialist species Agaricia grahamae, among locations in the Southern Caribbean. We also tested for hybridisation with the closely related (but depth‐generalist) species Agaricia lamarcki, within their sympatric depth zone (50 m). In contrast to our expectations, no spatial genetic structure was detected between the reefs of Curaçao and Bonaire (~40 km apart) within A. grahamae. However, cryptic taxa were discovered within both taxonomic species, with those in A. lamarcki (incompletely) partitioned by depth and those in A. grahamae occurring sympatrically (at the same depth). Hybrid analyses and demographic modelling identified contemporary and historical gene flow among cryptic taxa, both within and between A. grahamae and A. lamarcki. These results (1) indicate that spatial connectivity and subsequent replenishment may be possible between islands of moderate geographic distances for A. grahamae, an ecologically important mesophotic species, (2) that cryptic taxa occur in the mesophotic zone and environmental selection along shallow to mesophotic depth gradients may drive divergence in depth‐generalists such as A. lamarcki, and (3) highlight that gene flow links taxa within this relativity diverse Caribbean genus.

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          The variant call format and VCFtools

          Summary: The variant call format (VCF) is a generic format for storing DNA polymorphism data such as SNPs, insertions, deletions and structural variants, together with rich annotations. VCF is usually stored in a compressed manner and can be indexed for fast data retrieval of variants from a range of positions on the reference genome. The format was developed for the 1000 Genomes Project, and has also been adopted by other projects such as UK10K, dbSNP and the NHLBI Exome Project. VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API. Availability: http://vcftools.sourceforge.net Contact: rd@sanger.ac.uk
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            Detecting the number of clusters of individuals using the software structure: a simulation study

            The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
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              Inference of Population Structure Using Multilocus Genotype Data

              We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.
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                Author and article information

                Contributors
                k.prata@uq.edu.au
                Journal
                Mol Ecol
                Mol Ecol
                10.1111/(ISSN)1365-294X
                MEC
                Molecular Ecology
                John Wiley and Sons Inc. (Hoboken )
                0962-1083
                1365-294X
                27 February 2022
                May 2022
                : 31
                : 9 ( doiID: 10.1111/mec.v31.9 )
                : 2511-2527
                Affiliations
                [ 1 ] School of Biological Sciences The University of Queensland St Lucia Queensland Australia
                [ 2 ] ringgold 7143; California Academy of Sciences San Francisco California USA
                [ 3 ] Department of Molecular and Cellular Biology University of Arizona Tuscon Arizona USA
                [ 4 ] ringgold 7143; Caribbean Research and Management of Biodiversity Foundation Willemstad Curaçao
                [ 5 ] ringgold 27991; Laboratorio de Biología Molecular Marina (BIOMMAR) Departamento de Ciencias Biológicas Universidad de los Andes Bogotá Colombia
                Author notes
                [*] [* ] Correspondence

                Katharine E. Prata, School of Biological Sciences, The University of Queensland, St Lucia, QLD, Australia.

                Email: k.prata@ 123456uq.edu.au

                Author information
                https://orcid.org/0000-0001-6679-0066
                https://orcid.org/0000-0002-5485-4197
                https://orcid.org/0000-0001-7149-8369
                Article
                MEC16391
                10.1111/mec.16391
                9303685
                35152496
                f87666e1-736e-4bb3-9b4a-c952f6ebae2c
                © 2022 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-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 26 January 2022
                : 07 June 2021
                : 31 January 2022
                Page count
                Figures: 5, Tables: 2, Pages: 17, Words: 14711
                Funding
                Funded by: Australian Research Council , doi 10.13039/501100000923;
                Award ID: DE160101433
                Funded by: Catlin Group , doi 10.13039/501100009499;
                Funded by: University of Queensland , doi 10.13039/501100001794;
                Funded by: Explorers Club , doi 10.13039/100002861;
                Funded by: The University of Queensland
                Categories
                Original Article
                ORIGINAL ARTICLES
                Population and Conservation Genetics
                Custom metadata
                2.0
                May 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.7 mode:remove_FC converted:21.07.2022

                Ecology
                cryptic species,isolation with migration,mesophotic,population genetics,scleractinia,spatial connectivity

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