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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Mar. Sci.</journal-id>
<journal-title>Frontiers in Marine Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Mar. Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-7745</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmars.2022.953895</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Marine Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>First evidence of population genetic structure of the deep-water blackmouth catshark <italic>Galeus melastomus</italic> Rafinesque, 1810</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Di Crescenzo</surname>
<given-names>Simone</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1675524"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ferrari</surname>
<given-names>Alice</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/154696"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Barr&#xed;a</surname>
<given-names>Claudio</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cannas</surname>
<given-names>Rita</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/967312"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Cariani</surname>
<given-names>Alessia</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1652352"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Drewery</surname>
<given-names>Jim</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1861399"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Fern&#xe1;ndez-Peralta</surname>
<given-names>Lourdes</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Giordano</surname>
<given-names>Daniela</given-names>
</name>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hidalgo</surname>
<given-names>Manuel</given-names>
</name>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1404986"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Kousteni</surname>
<given-names>Vasiliki</given-names>
</name>
<xref ref-type="aff" rid="aff8">
<sup>8</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Marino</surname>
<given-names>Ilaria Anna Maria</given-names>
</name>
<xref ref-type="aff" rid="aff9">
<sup>9</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/689506"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Massi</surname>
<given-names>Daniela</given-names>
</name>
<xref ref-type="aff" rid="aff10">
<sup>10</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1992707"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Moura</surname>
<given-names>Teresa</given-names>
</name>
<xref ref-type="aff" rid="aff11">
<sup>11</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Rey</surname>
<given-names>Javier</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Sartor</surname>
<given-names>Paolo</given-names>
</name>
<xref ref-type="aff" rid="aff12">
<sup>12</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Scacco</surname>
<given-names>Umberto</given-names>
</name>
<xref ref-type="aff" rid="aff13">
<sup>13</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1836076"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Serena</surname>
<given-names>Fabrizio</given-names>
</name>
<xref ref-type="aff" rid="aff10">
<sup>10</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Stagioni</surname>
<given-names>Marco</given-names>
</name>
<xref ref-type="aff" rid="aff14">
<sup>14</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/495661"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Tinti</surname>
<given-names>Fausto</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1011451"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Laboratory of Genetics and Genomics of Marine Resources and Environment, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna Ravenna</institution>, <addr-line>Ravenna</addr-line>, <country>Italy</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Life and Environmental Sciences, University of Cagliari</institution>, <addr-line>Cagliari</addr-line>, <country>Italy</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Institut de Ci&#xe8;ncies del Mar</institution>, <addr-line>Barcelona</addr-line>, <country>Spain</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Marine Laboratory, Marine Scotland Science</institution>, <addr-line>Aberdeen</addr-line>, <country>United Kingdom</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Instituto Espa&#xf1;ol de Oceanograf&#x131;a, Centro Oceanografico de Malaga, Biodiversity-Sustainability resources East-Central Atlantic Research Group</institution>, <addr-line>Malaga</addr-line>, <country>Spain</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>Institute for Marine Biological Resources and Biotechnology, National Research Council</institution>, <addr-line>Messina</addr-line>, <country>Italy</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>Instituto Espa&#xf1;ol de Oceanograf&#x131;a, Centre Oceanogr&#xe0;fic de les Balears, Ecosystem Oceanography Group</institution>, <addr-line>Palma de Mallorca</addr-line>, <country>Spain</country>
</aff>
<aff id="aff8">
<sup>8</sup>
<institution>Fisheries Research Institute, Hellenic Agricultural Organization Dimitra</institution>, <addr-line>Kavala</addr-line>, <country>Greece</country>
</aff>
<aff id="aff9">
<sup>9</sup>
<institution>Department of Biology, University of Padua</institution>, <addr-line>Padua</addr-line>, <country>Italy</country>
</aff>
<aff id="aff10">
<sup>10</sup>
<institution>Institute for Marine Biological Resources and Biotechnology, National Research Council</institution>, <addr-line>Mazara Del Vallo</addr-line>, <country>Italy</country>
</aff>
<aff id="aff11">
<sup>11</sup>
<institution>Portuguese Institute for the Ocean and Atmosphere, Division of Modelling and Management of Fishery Resources</institution>, <addr-line>Alges</addr-line>, <country>Portugal</country>
</aff>
<aff id="aff12">
<sup>12</sup>
<institution>Interuniversity Centre of Marine Biology and Applied Ecology</institution>, <addr-line>Livorno</addr-line>, <country>Italy</country>
</aff>
<aff id="aff13">
<sup>13</sup>
<institution>Italian Institute for Environmental Protection and Research</institution>, <addr-line>Rome</addr-line>, <country>Italy</country>
</aff>
<aff id="aff14">
<sup>14</sup>
<institution>Marine Biology and Fisheries Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna</institution>, <addr-line>Fano</addr-line>, <country>Italy</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Maria Lourdes D. Palomares, Institute for the Oceans and Fisheries, University of British Columbia, Canada</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Mauro Sinopoli, Stazione Zoologica Anton Dohrn Napoli, Italy; Francesco Tiralongo, University of Catania, Italy; Maria Flavia Gravina, University of Rome &#x201c;Tor Vergata&#x201d;, Italy</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Simone Di Crescenzo, <email xlink:href="mailto:simone.dicrescenzo@unica.it">simone.dicrescenzo@unica.it</email>; Alessia Cariani, <email xlink:href="mailto:alessia.cariani@unibo.it">alessia.cariani@unibo.it</email>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Marine Biology, a section of the journal Frontiers in Marine Science</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>30</day>
<month>11</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>9</volume>
<elocation-id>953895</elocation-id>
<history>
<date date-type="received">
<day>26</day>
<month>05</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>08</day>
<month>11</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Di Crescenzo, Ferrari, Barr&#xed;a, Cannas, Cariani, Drewery, Fern&#xe1;ndez-Peralta, Giordano, Hidalgo, Kousteni, Marino, Massi, Moura, Rey, Sartor, Scacco, Serena, Stagioni and Tinti</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Di Crescenzo, Ferrari, Barr&#xed;a, Cannas, Cariani, Drewery, Fern&#xe1;ndez-Peralta, Giordano, Hidalgo, Kousteni, Marino, Massi, Moura, Rey, Sartor, Scacco, Serena, Stagioni and Tinti</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Among the main measures adopted to reduce anthropogenic impacts on elasmobranch communities, understanding the ecology of deep-sea sharks is of paramount importance, especially for potentially vulnerable species highly represented in the bycatch composition of commercial fisheries such as the blackmouth catshark <italic>Galeus melastomus</italic>. In the present work, we unravelled the first indication of&#xa0;population genetic structure of <italic>G. melastomus</italic> by using a novel and effective panel of nuclear, and polymorphic DNA markers and compared our results with previous findings supporting high genetic connectivity at large spatial scales. Given the lack of species-specific nuclear markers, a total of 129 microsatellite loci (Simple Sequence Repeats, SSRs) were cross-amplified on blackmouth catshark specimens collected in eight geographically distant areas in the Mediterranean Sea and North-eastern Atlantic Ocean. A total of 13 SSRs were finally selected for genotyping, based on which the species exhibited signs of weak, but tangible genetic structure. The clearcut evidence of genetic differentiation of <italic>G. melastomus</italic> from Scottish waters from the rest of the population samples was defined, indicating that the species is genetically structured in the Mediterranean Sea and adjacent North-eastern Atlantic. Both individual and frequency-based analyses identified a genetic unit formed by the individuals collected in the Tyrrhenian Sea and the Strait of Sicily, distinguished from the rest of the Mediterranean and Portuguese samples. In addition, Bayesian analyses resolved a certain degree of separation of the easternmost Aegean sample and the admixed nature of the other Mediterranean and the Portuguese samples. Here, our results supported the hypothesis that the interaction between the ecology and biology of the species and abiotic drivers such as water circulations, temperature and bathymetry may affect the dispersion of <italic>G. melastomus</italic>, adding new information to the current knowledge of the connectivity of this deep-water species and providing powerful tools for estimating its response to anthropogenic impacts.</p>
</abstract>
<kwd-group>
<kwd>conservation</kwd>
<kwd>cross-amplification</kwd>
<kwd>deep-sea</kwd>
<kwd>microsatellite loci</kwd>
<kwd>population differentiation</kwd>
<kwd>sharks</kwd>
<kwd>North-eastern Atlantic Ocean</kwd>
<kwd>Mediterranean Sea</kwd>
</kwd-group>
<counts>
<fig-count count="4"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="107"/>
<page-count count="14"/>
<word-count count="5782"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Sharks are among the most vulnerable species inhabiting the marine realm, and although they are characterised by a long lifespan, they exhibit slow growth, late maturity and low fecundity, and other biological traits that may pose a significant threat to their populations (<xref ref-type="bibr" rid="B109">Stevens et&#xa0;al., 2000</xref>; <xref ref-type="bibr" rid="B68">Kousteni and Megalofonou, 2019</xref>). Habitat selection (<xref ref-type="bibr" rid="B28">DiGiacomo et&#xa0;al., 2020</xref>) and complex behaviours such as philopatry or site fidelity (<xref ref-type="bibr" rid="B90">Pillans et&#xa0;al., 2021</xref>) can additionally limit their capacity to recover from population declines related to overexploitation (<xref ref-type="bibr" rid="B27">Dell&#x2019;Apa et&#xa0;al., 2012</xref>) and habitat fragmentation and depletion (<xref ref-type="bibr" rid="B5">Barausse et&#xa0;al., 2014</xref>). In deep waters, these intrinsic features may be exacerbated, increasing their vulnerability to human impacts and particularly exploitation (<xref ref-type="bibr" rid="B100">Rigby and Simpfendorfer, 2015</xref>). Concerns about the overexploitation of the deep-sea waters, lead to the identification, assessment and management of stock units of several shark species in the Atlantic Ocean (<xref ref-type="bibr" rid="B114">Ver&#xed;ssimo et&#xa0;al., 2011a</xref>; <xref ref-type="bibr" rid="B24">Daley et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B59">ICES, 2021</xref>), where bottom trawling has been banned below 800 metres (<xref ref-type="bibr" rid="B96">European Parliament, Council of the European Union, 2016</xref>). Within the Mediterranean Sea, the General Fisheries Commission for the Mediterranean (GFCM) banned bottom trawling below 1,000 m depth, allowing a possible refuge zone for mature individuals of those species showing depth-dependent size segregation (<xref ref-type="bibr" rid="B51">Gouraguine et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B93">Ram&#xed;rez-Amaro et&#xa0;al., 2020</xref>). However, such measures may have likely shifted the trawling effort towards deeper waters (<xref ref-type="bibr" rid="B111">Tserpes et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B40">Farriols et&#xa0;al., 2019</xref>). On top of that, the effects of bycatch on already poorly investigated deep-water species may become even more dangerous, hindering the quantification of indirect impacts such as cascade effects on trophic interactions and loss of biomass (<xref ref-type="bibr" rid="B84">Myers et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B15">Cashion et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B86">Serena, 2021</xref>).</p>
<p>The blackmouth catshark <italic>Galeus melastomus</italic> Rafinesque, 1810 is a common benthic shark whose nominal family is still debated (<xref ref-type="bibr" rid="B60">Igl&#xe9;sias et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B83">Musick and Ellis, 2005</xref>; <xref ref-type="bibr" rid="B31">Dymek et&#xa0;al., 2021</xref>). Currently the species belongs to the family Pentachidae (<xref ref-type="bibr" rid="B85">Naylor et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B65">Kousteni et&#xa0;al., 2021</xref>) and it is widely distributed on the outer continental shelves and upper slopes in the North-eastern Atlantic Ocean and the Mediterranean Sea (<xref ref-type="bibr" rid="B62">Kallianiotis et&#xa0;al., 2000</xref>; <xref ref-type="bibr" rid="B47">Follesa et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B2">Abella et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B48">Froese and Pauly, 2019</xref>). The species shows a wide bathymetric range (from 55 to 2000&#xa0;m depth), dwelling between 200 and 500&#xa0;m depth (<xref ref-type="bibr" rid="B36">Ebert et&#xa0;al., 2021</xref>). The distribution, feeding habits and biological features of <italic>G. melastomus</italic> are well-studied and many authors have been focussing on the size at first maturity, sex ratio, sexual dimorphism, and egg deposition (<xref ref-type="bibr" rid="B23">Costa et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B92">Ragonese et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B4">Anastasopoulou et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B79">Metochis et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B32">D&#x2019;Iglio et&#xa0;al., 2021a</xref>; <xref ref-type="bibr" rid="B105">Scacco et&#xa0;al., 2022</xref>). The species has shown signs of population differentiation across its distribution range regarding the maximum body-size, the length at maturity (<xref ref-type="bibr" rid="B76">Massut&#xed; and Moranta, 2003</xref>; <xref ref-type="bibr" rid="B7">Barr&#xed;a et&#xa0;al., 2015</xref>) and sex-related body weight (<xref ref-type="bibr" rid="B33">D&#x2019;Iglio et&#xa0;al., 2021b</xref>). Data reported in literature showed differences in the maximum total length (TL) in individuals caught in the Atlantic and in the Mediterranean areas (TL 90 versus 70&#xa0;cm, respectively; <xref ref-type="bibr" rid="B76">Massut&#xed; and Moranta, 2003</xref>; <xref ref-type="bibr" rid="B7">Barr&#xed;a et&#xa0;al., 2015</xref>), with the Mediterranean Sea individuals reaching the first maturity more rapidly (<xref ref-type="bibr" rid="B76">Massut&#xed; and Moranta, 2003</xref>; <xref ref-type="bibr" rid="B81">Moore et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B79">Metochis et&#xa0;al., 2018</xref>). In general, both sexes increase in size and abundance with depth (<xref ref-type="bibr" rid="B98">Rey et&#xa0;al., 2004</xref>), with females growing larger than males and reaching sexual maturity at a larger size (<xref ref-type="bibr" rid="B81">Moore et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B79">Metochis et&#xa0;al., 2018</xref>). Reproduction through spawning was observed all over the year (<xref ref-type="bibr" rid="B13">Capap&#xe9; et&#xa0;al., 2008</xref>), and peaks were recorded in late spring-summer (<xref ref-type="bibr" rid="B92">Ragonese et&#xa0;al., 2009</xref>).</p>
<p>Little information is available about blackmouth catshark genetic diversity and population structure (<xref ref-type="bibr" rid="B43">Ferrari et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B94">Ram&#xed;rez-Amaro et&#xa0;al., 2018</xref>), being the molecular method previously applied for integrated taxonomy (<xref ref-type="bibr" rid="B17">Castilho et&#xa0;al., 2007</xref>) and food traceability (<xref ref-type="bibr" rid="B22">Clarke et&#xa0;al., 2006</xref>). With the refinement of genetic and genomic techniques, deepening the knowledge about species genetic diversity and structuring is becoming one of the pillars of elasmobranchs&#x2019; conservation (<xref ref-type="bibr" rid="B88">Ovenden et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B29">Domingues et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B26">Delaval et&#xa0;al., 2022</xref>). Finding population structure across wide geographical or global scales failed in pelagic sharks (<xref ref-type="bibr" rid="B57">Hoelzel et&#xa0;al., 2006</xref>; <xref ref-type="bibr" rid="B117">Ver&#xed;ssimo et&#xa0;al., 2017</xref>) although some exceptions are reported (<xref ref-type="bibr" rid="B69">Kraft et&#xa0;al., 2020</xref>), while the identification of isolated populations on smaller regional scales has been documented in multiple coastal species (<xref ref-type="bibr" rid="B91">Portnoy et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B18">Catalano et&#xa0;al., 2022</xref>).</p>
<p>The above-mentioned population dynamics and habitat use of the blackmouth catshark may influence gene flow, being the latter limited by hydrographic barriers (e.g., currents and frontal systems and water masses), and progressively leading to genetic differentiation (<xref ref-type="bibr" rid="B106">Shaw et&#xa0;al., 2004</xref>). Currently, estimating population fragmentation is of primary interest for the conservation of cartilaginous fish species, whose population structure must be carefully assessed. Despite a high discard rate of the species (<xref ref-type="bibr" rid="B44">Ferretti et&#xa0;al., 2005</xref>), the International Union for the Conservation of Nature (IUCN) suggested that populations of blackmouth catshark in the Alboran, Balearic, Ligurian and Tyrrhenian Seas can be considered as stable (<xref ref-type="bibr" rid="B44">Ferretti et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B93">Ram&#xed;rez-Amaro et&#xa0;al., 2020</xref>), even if the current fishing mortality does not ensure stock sustainability (<xref ref-type="bibr" rid="B2">Abella et&#xa0;al., 2017</xref>). Among the main threats, bycatch has been demonstrated to be the heaviest, leading to a steady decrease in mature individuals. According to the IUCN Red List Status, the species is characterised as Least Concern globally (<xref ref-type="bibr" rid="B45">Finucci et&#xa0;al., 2021</xref>) and in the Mediterranean Sea (<xref ref-type="bibr" rid="B1">Abella et&#xa0;al., 2016</xref>). Nevertheless, the North-eastern Atlantic Ocean and the Mediterranean Sea have been subjected to extensive and intensive deep-water fishing across much of the species&#x2019; known depth and spatial distribution (<xref ref-type="bibr" rid="B45">Finucci et&#xa0;al., 2021</xref>). Despite the management measures adopted to reduce deep-water shark fishing mortality, the species is still captured in demersal fisheries (e.g., in deep water shrimp trawl fishery), with a bycatch rate steadily increasing in some locations (<xref ref-type="bibr" rid="B89">Pauly and Zeller, 2015</xref>; <xref ref-type="bibr" rid="B82">Moura et&#xa0;al., 2018</xref>). Discard mortality of <italic>G. melastomus</italic> is unknown, but is likely to be high based on severe injuries obtained when individuals are captured (<xref ref-type="bibr" rid="B45">Finucci et&#xa0;al., 2021</xref>).</p>
<p>The present study aims at assessing the population genetic structure of <italic>G. melastomus</italic> within a large part of its range, from the North-eastern Atlantic Ocean and from the Western to the Eastern Mediterranean Sea, surveying the genetic diversity of 194 specimens collected from eight geographically distant areas at 13 cross-amplified microsatellite loci. Our findings, in conjunction with the results from previous studies that analysed the species&#x2019; genetic diversity by using mitochondrial DNA markers, will advance current knowledge about the species&#x2019; population units and contribute to future species assessment in the region.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Materials and methods</title>
<sec id="s2_1">
<title>Sampling</title>
<p>A total of 194 tissue samples (i.e., skeletal muscle or fin clips) and associated information (i.e., biological and sampling data, pictures, and size measurements) of <italic>G. melastomus</italic> were collected during scientific surveys from eight sampling areas across the North-eastern Atlantic Ocean and the Mediterranean Sea: Scotland (SCO), Portugal (POR), Spain (SPA), Italy (LIG, TYR, SIC, ADR) and Greece (AEG) (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>; <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>SM1</bold>
</xref>). Samples were collected in 2018 and 2019 except for the AEG sample that was collected in 2011. Data points were collected at depths ranging from 116 to 1060&#xa0;m. Tissue samples were stored in 96% ethanol at -20&#xb0;C until laboratory analysis.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Sampling summary and main genetic diversity statistics of <italic>Galeus melastomus</italic> geographical samples.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Area</th>
<th valign="top" align="center">Acronym</th>
<th valign="top" align="center">Year</th>
<th valign="top" align="center">N</th>
<th valign="top" align="center">Na</th>
<th valign="top" align="center">A<sub>r</sub>
</th>
<th valign="top" align="center">H<sub>ob</sub>
</th>
<th valign="top" align="center">H<sub>exp</sub>
</th>
<th valign="top" align="center">F<sub>is</sub>
</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Scottish waters</td>
<td valign="top" align="left">SCO</td>
<td valign="top" align="center">2019</td>
<td valign="top" align="center">20</td>
<td valign="top" align="center">23</td>
<td valign="top" align="center">2.077</td>
<td valign="top" align="center">0.241</td>
<td valign="top" align="center">0.228</td>
<td valign="top" align="center">-0.032</td>
</tr>
<tr>
<td valign="top" align="left">Portuguese waters</td>
<td valign="top" align="left">POR</td>
<td valign="top" align="center">2018</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">2.976</td>
<td valign="top" align="center">0.260</td>
<td valign="top" align="center">0.396</td>
<td valign="top" align="center">
<bold>0.362</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Spanish waters</td>
<td valign="top" align="left">SPA</td>
<td valign="top" align="center">2019</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">35</td>
<td valign="top" align="center">3.070</td>
<td valign="top" align="center">0.316</td>
<td valign="top" align="center">0.411</td>
<td valign="top" align="center">
<bold>0.251</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Ligurian Sea</td>
<td valign="top" align="left">LIG</td>
<td valign="top" align="center">2019</td>
<td valign="top" align="center">23</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">3.219</td>
<td valign="top" align="center">0.286</td>
<td valign="top" align="center">0.432</td>
<td valign="top" align="center">
<bold>0.341</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Tyrrhenian Sea</td>
<td valign="top" align="left">TYR</td>
<td valign="top" align="center">2018</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">2.451</td>
<td valign="top" align="center">0.280</td>
<td valign="top" align="center">0.295</td>
<td valign="top" align="center">0.075</td>
</tr>
<tr>
<td valign="top" align="left">Strait of Sicily</td>
<td valign="top" align="left">SIC</td>
<td valign="top" align="center">2018</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">33</td>
<td valign="top" align="center">2.871</td>
<td valign="top" align="center">0.274</td>
<td valign="top" align="center">0.365</td>
<td valign="top" align="center">
<bold>0.270</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Adriatic Sea</td>
<td valign="top" align="left">ADR</td>
<td valign="top" align="center">2019</td>
<td valign="top" align="center">23</td>
<td valign="top" align="center">31</td>
<td valign="top" align="center">2.770</td>
<td valign="top" align="center">0.326</td>
<td valign="top" align="center">0.414</td>
<td valign="top" align="center">
<bold>0.232</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Central Aegean Sea</td>
<td valign="top" align="left">AEG</td>
<td valign="top" align="center">2011</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">26</td>
<td valign="top" align="center">2.355</td>
<td valign="top" align="center">0.336</td>
<td valign="top" align="center">0.392</td>
<td valign="top" align="center">
<bold>0.168</bold>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>N, number of individuals genotyped; N<sub>a</sub>, mean number of alleles; A<sub>r</sub>, mean allelic richness; H<sub>obs</sub>, mean observed heterozygosity; H<sub>exp</sub>, mean expected heterozygosity; and F<sub>is</sub>, inbreeding coefficient (in bold the significant values after Benjamini-Hochberg corrections).</p>
</fn>
<fn>
<p>For detailed individual samples information and additional genetic diversity statistics see <xref ref-type="supplementary-material" rid="SM1">
<bold>SM1</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM1">
<bold>SM5</bold>
</xref> respectively.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Sampling locations of <italic>Galeus melastomus</italic>. Acronyms of geographical samples&#xa0;are given as in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>. Data points are coloured according to the DAPC scatterplot of <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-09-953895-g001.tif"/>
</fig>
<p>Specimen identification followed field marks proposed by <xref ref-type="bibr" rid="B99">Rey et&#xa0;al. (2006)</xref> and confirmed by <xref ref-type="bibr" rid="B17">Castilho et&#xa0;al. (2007)</xref>. When specimen identification between <italic>G. melastomus</italic> and <italic>Galeus atlanticus</italic> Vaillant, 1888 was ambiguous, molecular identification was performed using the DNA barcoding approach (<xref ref-type="bibr" rid="B14">Cariani et&#xa0;al., 2017</xref>). Results were cross-referenced with sequences available on the Barcode of Life Data Systems (<xref ref-type="bibr" rid="B95">Ratnasingham and Hebert, 2007</xref>).</p>
</sec>
<sec id="s2_2">
<title>DNA extraction and genotyping</title>
<p>Total genomic DNA (gDNA) was extracted from approximately 20 mg of tissue using the Wizard<sup>&#xae;</sup> SV Genomic DNA Purification System by Promega, according to the manufacturer&#x2019;s instructions. The quality of the extracted gDNA was assessed on a 0.8% agarose gel electrophoresis.</p>
<p>A total of 129 heterospecific microsatellite loci (<xref ref-type="supplementary-material" rid="SM1">
<bold>SM2</bold>
</xref>) were selected and cross-amplified on 24 individuals of <italic>G. melastomus</italic> collected from the North Atlantic, Western and Eastern Mediterranean. Thirteen loci were associated with polymorphic amplicons in individuals from all three areas and were thus selected for the genotyping of the 194 individuals. In particular, the loci tested here were initially developed for <italic>Centroscymnus crepidater</italic> Barbosa du Bocage &amp; de Brito Capello, 1864, <italic>Galeorhinus galeus</italic> Linnaeus, 1758, <italic>Hexanchus griseus</italic> Bonnaterre, 1788, <italic>Mustelus antarcticus</italic> G&#xfc;nther, 1870, <italic>Mustelus canis</italic> Mitchill, 1815, <italic>Mustelus mustelus</italic> Linnaeus, 1758 and <italic>Scyliorhinus canicula</italic> Linnaeus, 1758 (<xref ref-type="supplementary-material" rid="SM1">
<bold>SM2</bold>
</xref>).</p>
<p>The selected loci were amplified in three multiplexed PCR reactions (<xref ref-type="supplementary-material" rid="SM1">
<bold>SM2</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>SM3</bold>
</xref>). When necessary, single-locus PCR reactions were carried out following the same protocol described in <xref ref-type="supplementary-material" rid="SM1">
<bold>SM3</bold>
</xref> with a total volume of 15 &#x3bc;L. Amplicons were further sized at Macrogen Korea using the GS-500LIZ internal size standard.</p>
</sec>
<sec id="s2_3">
<title>Data analysis</title>
<p>Alleles were scored using GENEMARKER<sup>&#xae;</sup> (SOFTGENETICS<sup>&#xae;</sup>, LLC). The presence of null alleles, stuttering, and allele drop-out was tested using MICRO-CHECKER 2.2.3 (<xref ref-type="bibr" rid="B112">Van Oosterhout et&#xa0;al., 2004</xref>) using 1,000 randomisations on Bonferroni correction. The statistical power of microsatellite loci to detect population homogeneity was verified with POWSIM 4.1 by using the allele frequencies obtained from the samples in this study (<xref ref-type="bibr" rid="B103">Ryman and Palm, 2006</xref>). Both Chi-square and Fisher&#x2019;s exact tests were carried out by employing 1,000 iterations, 5,000 simulation runs, effective population (Ne) 1,000, and pairwise differentiation index (F<sub>st</sub>) between 0.025 and 0.050. Furthermore, Type I &#x3b1; error, representing the probability of rejecting the null hypothesis, was inferred setting t generations&#x2019; drift to zero.</p>
<p>Allelic frequency, measures of heterozygosity, polymorphism index and the average number of alleles per locus were calculated using the software GENETIX 4.05. (<xref ref-type="bibr" rid="B8">Belkhir et&#xa0;al., 2004</xref>). The software FSTAT 2.9.3.2 (<xref ref-type="bibr" rid="B50">Goudet, 2001</xref>) was used to compute allelic richness, gene diversity and inbreeding coefficient (F<sub>is</sub>). The Hardy-Weinberg equilibrium was assessed using the software GENEPOP 4.7.3 (<xref ref-type="bibr" rid="B102">Rousset, 2008</xref>), applying the Fisher&#x2019;s (1935) exact test. The Markov Chain Monte Carlo (MCMC) approximation involved 10,000 dememorization steps, 1,000 batches and 10,000 iterations per batch. Probability tests were also performed, and the relative values were corrected for multiple testing at alpha 0.05 using the Bonferroni correction.</p>
<p>Pairwise <italic>F</italic>
<sub>st</sub> values were calculated with ARLEQUIN v.3.5 (<xref ref-type="bibr" rid="B38">Excoffier and Lischer, 2010</xref>) with 5,000 permutations and alpha value equal to 0.05. The same software was used for the analysis of molecular variance (AMOVA; <xref ref-type="bibr" rid="B39">Excoffier et&#xa0;al., 1992</xref>), grouping the samples based on a geographical structure on three hierarchical levels: among geographical areas, among populations within geographical areas and within populations. The statistical significance of the resulting values of the pairwise fixation index was estimated by comparing the observed distribution with a null distribution generated by 5,000 permutations and the Benjamini-Hochberg method was applied for multiple test correction (<xref ref-type="bibr" rid="B9">Benjamini and Hochberg, 1995</xref>).</p>
<p>The discriminant analysis of principal components (DAPC), implemented in the <italic>adegenet</italic> R package following <xref ref-type="bibr" rid="B61">Jombart et&#xa0;al. (2010)</xref>, was used to investigate the genetic structure identified by AMOVA.</p>
<p>We investigated the underlying population genetic structure using a Bayesian clustering algorithm implemented in STRUCTURE 2.3.4 (<xref ref-type="bibr" rid="B58">Hubisz et&#xa0;al., 2009</xref>), incorporating the Admixture Model, Alleles Frequencies Correlated and sampling location as a LOCPRIOR. We performed 25 independent runs for each K (1-15) with 1,000,000 iterations and a burn-in of 100,000 generations. The optimal number of genetic clusters was inferred from the mean estimated log probability of the data and its second-order rate of change (&#x394;K) as calculated in STRUCTURE HARVESTER according to <xref ref-type="bibr" rid="B35">Earl and vonHoldt (2012)</xref>. Cluster matching and permutation were performed using CLUMPAK (<xref ref-type="bibr" rid="B64">Kopelman et&#xa0;al., 2015</xref>). In addition, we estimated the best K using four alternative statistics (medmedk, medmeak, maxmedk and maxmeak) carried out using STRUCTURESELECTOR (<xref ref-type="bibr" rid="B73">Li and Liu, 2018</xref>).</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<p>A total of 13 out of the 129 tested SSRs (10.1%) provided amplicons within the reference size and in both Atlantic and Mediterranean individuals (<xref ref-type="supplementary-material" rid="SM1">
<bold>SM2</bold>
</xref>). Considering a call rate threshold of 90%, a total of 180 individuals constituted the final dataset. Loci Gg11 and McaB28 were discarded since their amplification patterns suggested the presence of multiple genic regions. The most polymorphic locus was MaD2X (Na = 9), while the less polymorphic ones were Cc21 and MaND5 (both with Na = 2). The presence of null alleles (<xref ref-type="supplementary-material" rid="SM1">
<bold>SM4</bold>
</xref>) contributed to a moderate heterozygosity that was observed at the population level (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). The population sample from the Ligurian Sea showed the highest number of alleles (Na = 36) and the highest allelic richness (A<sub>r</sub> = 3.219), while the sample from Scottish waters showed the lowest values (Na = 23, A<sub>r</sub> = 2.077). In general, genetic diversity estimators showed samples from the Ligurian Sea and Scottish waters as the putative populations with the highest and lowest genetic variability, respectively (<xref ref-type="supplementary-material" rid="SM1">
<bold>SM4</bold>
</xref>).</p>
<p>The pattern and the success of SSRs cross-amplification followed the levels of taxonomic relatedness between species since most of the loci effectively amplified in <italic>G. melastomus</italic> were those previously developed for species of the closest family Triakidae (<italic>Galeorhinus galeus</italic> and <italic>Mustelus</italic> spp.; extensive details and analyses are reported in <xref ref-type="supplementary-material" rid="SM1">
<bold>SM5</bold>
</xref>).</p>
<p>The simulation obtained with POWSIM highlighted the high-resolution power of the dataset. Both Chi-square and Fisher&#x2019;s tests revealed genetic differentiation in most runs and were able to detect <italic>F</italic>
<sub>st</sub> values of as low as 0.025 in 100% of the runs (t<sub>100</sub>: &#x3c7;<sup>2</sup> = 1.000, <italic>F</italic> = 1.000, P<sub>value</sub> &lt; 0.05).</p>
<p>The mean pairwise <italic>F</italic>
<sub>st</sub> value among samples was 0.159 (P<sub>value</sub> &lt; 0.001) while the pairwise <italic>F</italic>
<sub>st</sub> values ranged from 0.037 (POR-ADR) to 0.348 (TYR-AEG) (<xref ref-type="supplementary-material" rid="SM1">
<bold>SM6</bold>
</xref>). All the pairwise <italic>F</italic>
<sub>st</sub> values were significant (P<sub>value</sub> &lt; 0.001) except for the comparison SPA-ADR. The AMOVA (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref> and <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>) with the highest percentage of molecular variation among groups (13.62%) and the lowest value of molecular variation among populations within group (3.99%) was the one performed with the subdivision of geographical samples into five groups (SCO; POR; SPA-LIG-ADR; SIC-TYR; AEG).</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Summary of <italic>a priori</italic> groupings tested by AMOVA analysis according to the geographic origin of the individuals.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Scenarios</th>
<th valign="top" colspan="6" align="center">Groups</th>
</tr>
<tr>
<th/>
<th valign="top" align="center">1</th>
<th valign="top" align="center">2</th>
<th valign="top" align="center">3</th>
<th valign="top" align="center">4</th>
<th valign="top" align="center">5</th>
<th valign="top" align="center">6</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">S1</td>
<td valign="top" align="left">SCO</td>
<td valign="top" align="left">POR</td>
<td valign="top" align="left">SPA-LIG</td>
<td valign="top" align="left">SIC-TYR</td>
<td valign="top" align="left">ADR</td>
<td valign="top" align="left">AEG</td>
</tr>
<tr>
<td valign="top" align="left">S2</td>
<td valign="top" align="left">SCO-POR</td>
<td valign="top" align="left">SPA-LIG</td>
<td valign="top" align="left">SIC-TYR</td>
<td valign="top" align="left">ADR-AEG</td>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
</tr>
<tr>
<td valign="top" align="left">S3</td>
<td valign="top" align="left">SCO</td>
<td valign="top" align="left">POR</td>
<td valign="top" align="left">SPA-LIG-ADR</td>
<td valign="top" align="left">SIC-TYR</td>
<td valign="top" align="left">AEG</td>
<td valign="top" align="left"/>
</tr>
<tr>
<td valign="top" align="left">S4</td>
<td valign="top" align="left">SCO</td>
<td valign="top" align="left">POR-SPA-LIG</td>
<td valign="top" align="left">SIC-TYR</td>
<td valign="top" align="left">ADR-AEG</td>
<td valign="top" align="left">&#xa0;</td>
<td valign="top" align="left">&#xa0;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Acronyms of geographical samples are given as in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Summary of the results of the AMOVA analysis conducted on the four scenarios.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Scenarios</th>
<th valign="top" align="center">Source of variation</th>
<th valign="top" align="center">PV</th>
<th valign="top" align="center">F</th>
<th valign="top" align="center">P<sub>value</sub>
</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">S1</td>
<td valign="top" align="left">Among groups</td>
<td valign="top" align="center">11.960</td>
<td valign="top" align="center">F<sub>CT</sub> = 0.166</td>
<td valign="top" align="center">0.000</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left">Among populations within groups</td>
<td valign="top" align="center">4.670</td>
<td valign="top" align="center">F<sub>SC</sub> = 0.053</td>
<td valign="top" align="center">0.000</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left">Within populations</td>
<td valign="top" align="center">83.370</td>
<td valign="top" align="center">F<sub>ST</sub> = 0.120</td>
<td valign="top" align="center">0.042</td>
</tr>
<tr>
<td valign="top" align="left">S2</td>
<td valign="top" align="left">Among groups</td>
<td valign="top" align="center">8.900</td>
<td valign="top" align="center">F<sub>CT</sub> = 0.170</td>
<td valign="top" align="center">0.000</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left">Among populations within groups</td>
<td valign="top" align="center">8.050</td>
<td valign="top" align="center">F<sub>SC</sub> = 0.088</td>
<td valign="top" align="center">0.000</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left">Within populations</td>
<td valign="top" align="center">83.050</td>
<td valign="top" align="center">F<sub>ST</sub> = 0.089</td>
<td valign="top" align="center">0.051</td>
</tr>
<tr>
<td valign="top" align="left">S3</td>
<td valign="top" align="left">Among groups</td>
<td valign="top" align="center">13.620</td>
<td valign="top" align="center">F<sub>CT</sub> = 0.176</td>
<td valign="top" align="center">0.000</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left">Among populations within groups</td>
<td valign="top" align="center">3.990</td>
<td valign="top" align="center">F<sub>SC</sub> = 0.046</td>
<td valign="top" align="center">0.000</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left">Within populations</td>
<td valign="top" align="center">82.390</td>
<td valign="top" align="center">F<sub>ST</sub> = 0.136</td>
<td valign="top" align="center">0.008</td>
</tr>
<tr>
<td valign="top" align="left">S4</td>
<td valign="top" align="left">Among groups</td>
<td valign="top" align="center">11.740</td>
<td valign="top" align="center">F<sub>CT</sub> = 0.177</td>
<td valign="top" align="center">0.000</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left">Among populations within groups</td>
<td valign="top" align="center">6.000</td>
<td valign="top" align="center">F<sub>SC</sub> = 0.068</td>
<td valign="top" align="center">0.000</td>
</tr>
<tr>
<td valign="top" align="left">&#xa0;</td>
<td valign="top" align="left">Within populations</td>
<td valign="top" align="center">82.260</td>
<td valign="top" align="center">F<sub>ST</sub> = 0.118</td>
<td valign="top" align="center">0.007</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>For each AMOVA the percentage of variation (PV), the F-statistics (F) among groups (F<sub>CT</sub>), among populations within groups (F<sub>SC</sub>), and within populations (F<sub>ST</sub>) and the relative P<sub>value</sub> are reported.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>The DAPC scatter plot showed a separation into three main groups (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). The SCO group was clearly separated from the rest of the samples along axis 2, the TYR-SIC group separated along axis 1, while the remaining samples only partially separated (e.g., POR, SPA, LIG, ADR and AEG).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>DAPC scatterplot of the <italic>Galeus melastomus</italic> samples. DAPC cluster ellipses were set to contain 95% of genotypes. Discriminant analysis (DA) eigenvalues and principal component analysis (PCA) eigenvalues were selected as displayed to avoid overfitting. Sample acronyms are given as in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-09-953895-g002.tif"/>
</fig>
<p>The STRUCTURE analyses inferred K = 2 and K = 3 as the optimal number of genetic clusters that best fitted the data with STRUCTURE HARVESTER (&#x394;K) and STRUCTURESELECTOR (K), respectively (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>, <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>SM7</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM1">
<bold>SM8</bold>
</xref>). In <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>, the barplot of K = 2 showed all individuals except one from the Mediterranean TYR and SIC assigned to a genetic cluster different with respect to that of SCO and AEG individuals. The rest of the samples (POR, SPA, LIG and ADR) were genetically admixed with different proportions of individuals assigned to the two genetic clusters. The barplot of K = 3 improved the separation of SCO from AEG, as well as the admixed composition of POR, SPA, LIG and ADR with individuals associated to the three identified clusters in different proportions.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Bayesian clustering barplot showing membership probabilities (q) for each individual after CLUMPAK analysis, see <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> for geographical location codes. For each K analysed the mean similarity score (MSS) is reported.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-09-953895-g003.tif"/>
</fig>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Graphical representation of results inferred with STRUCTURESELECTOR for each k and statistics (<bold>A</bold>: medmedk; <bold>B</bold>: medmeak; <bold>C</bold>: maxmedk; <bold>D</bold>:&#xa0;maxmeak).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-09-953895-g004.tif"/>
</fig>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>This research work revealed the first evidence of a detectable genetic structure of the necto-benthic, deep-water <italic>G. melastomus</italic> populations in the Mediterranean Sea and neighbouring North-East Atlantic areas, whose stocks are potentially affected and impacted by the demersal fishery (<xref ref-type="bibr" rid="B110">Tiralongo et&#xa0;al., 2021</xref>). Here, we described the first evidence of a weak albeit detectable genetic structure and the development of a technological tool represented by a panel of cross-specific microsatellite loci which were successful in detecting and measuring species genetic diversity and differentiation of blackmouth catshark over a large, regional geographic scale and a significant number of samples and individuals.</p>
<p>Our results are partially in contrast with previous findings obtained using multiple mitochondrial DNA markers and assessing genetic differentiation based on phylogeographic signals at a similar geographical scale, that suggested high connectivity with past population expansion of the species (<xref ref-type="bibr" rid="B43">Ferrari et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B94">Ram&#xed;rez-Amaro et&#xa0;al., 2018</xref>). Indeed, our study newly unravels the genetic complexity of <italic>G. melastomus</italic> populations on a large geographical scale by using nuclear, and polymorphic DNA markers. Such recorded genetic complexity can be attributable to i) a detectable but weak level of genetic differentiation and population structure that ii) speaks in favour of the occurrence of groups of subpopulations and environmental and/or ecological barriers to gene flow and iii) a great amount of genetic diversity represented by a high number of alleles per locus, high allelic richness and moderately high proportion of heterozygous multilocus genotypes. Given the clearcut evidence of genetic differentiation of the blackmouth sharks from Scottish waters emerged from all the tests and analyses performed, the rest of the population samples clustered depending mostly by the test and the analysis performed but, all in all, indicating that the species is genetically structured in the Mediterranean Sea and in the adjacent North-eastern Atlantic. Both the DAPC and STRUCTURE analyses identified a genetic unit formed by the individuals collected in the Tyrrhenian Sea and the Strait of Sicily, which resulted quite differentiated from the rest of the Mediterranean and Portuguese samples. In addition, the STRUCTURE analyses resolved a certain degree of separation of the easternmost Aegean sample and the admixed nature of the other Mediterranean and the Portuguese samples. The separation of the Central Southern Mediterranean samples could be a combination of different factors, related on one hand to specific environmental conditions in this area as hydrodynamic regimes and front systems limiting the species migration or, on the other hand, related to the modifications induced by the fishing pressure. Although intensive fishing currently involves the whole Mediterranean basin, the Strait of Sicily has been suffering from intense overfishing for decades (<xref ref-type="bibr" rid="B46">Fiorentino and Vitale, 2021</xref>). Such impact has been found to contribute to the modification of relevant biological traits of <italic>G. melastomus</italic> as the decrease of size at first maturity (<xref ref-type="bibr" rid="B33">D&#x2019;Iglio et&#xa0;al., 2021b</xref>). Although the species seems to be resilient and adaptable to human exploitation, mitigation measures based on population dynamics or mating success should not be excluded.</p>
<p>When looking at the interaction between some biological traits of <italic>G. melastomus</italic> and physical barriers of the marine realm, knowledge about the use of nursery areas (<xref ref-type="bibr" rid="B13">Capap&#xe9; et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B79">Metochis et&#xa0;al., 2018</xref>) and sex-based migratory behaviour should be encouraged, since this species might be an important key-taxon for understanding deep-sea ecosystems (<xref ref-type="bibr" rid="B98">Rey et&#xa0;al., 2004</xref>). Moreover, if the large geographic distance between sampling locations is not sufficient to explain the lack of connectivity in deep-sea species (<xref ref-type="bibr" rid="B115">Ver&#xed;ssimo et&#xa0;al., 2011b</xref>; <xref ref-type="bibr" rid="B19">Catarino et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B66">Kousteni et&#xa0;al., 2015a</xref>; <xref ref-type="bibr" rid="B67">Kousteni et&#xa0;al., 2015b</xref>; <xref ref-type="bibr" rid="B53">Gubili et&#xa0;al., 2016</xref>), factors as bathymetry or geomorphology (e.g., the presence of canyons; <xref ref-type="bibr" rid="B42">Fernandez-Arcaya et&#xa0;al., 2017</xref>) and temperature may be influencing the genetic structuring of the species. As a matter of fact, large adults of <italic>G. melastomus</italic> appear to undertake periodical migration from deeper waters toward shallow environments for mating (<xref ref-type="bibr" rid="B33">D&#x2019;Iglio et&#xa0;al., 2021b</xref>). It is reasonable to suppose that abiotic factors such as water circulations and bathymetry might be decreasing the contact potential between populations, contributing to the differentiation of samples from the Tyrrhenian Sea and the adjacent Strait of Sicily and to the homogenization of their genetic variability against other Mediterranean areas (Spanish, Ligurian, Adriatic and Aegean waters). As a matter of fact, within the Mediterranean Sea, the Levantine Intermediate Water and the Deep-water circulations (<xref ref-type="bibr" rid="B37">El-Geziry and Bryden, 2010</xref>) might be contributing to the differentiation of samples from the Tyrrhenian Sea and the adjacent Strait of Sicily and the homogenization of genetic variability between other sectors of the Basin (Spanish, Ligurian, Adriatic and Aegean waters). In addition, the important depth of the Strait of Sicily (over 1300&#xa0;m deep) and the Ionian Sea (average depth near to 4000&#xa0;m) can explain the very low similarity between samples from Tyrrhenian Sea and Strait of Sicily and the other groups. Specific dispersal potential related to species&#x2019; habits and life-history traits, such as the reproductive strategy, the use of mating and nursery areas and sex-based migratory behaviour, may contribute to population structuring (<xref ref-type="bibr" rid="B56">Hirschfeld et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B18">Catalano et&#xa0;al., 2022</xref>). Migration events or site fidelity may be strongly related to the optimal temperature at which the species is able to maximise growth rate and the bioenergetic efficiency, as already described in other sharks like <italic>S. canicula</italic> (<xref ref-type="bibr" rid="B107">Sims et&#xa0;al., 2006</xref>). The search for optimal temperature by <italic>G. melastomus</italic> is consistent with its reproduction hot-spot discovered in the deep waters 200 miles off the western Irish coast (<xref ref-type="bibr" rid="B87">O&#x2019;Sullivan et&#xa0;al., 2018</xref>) and agrees with similar observations for other sharks, like <italic>Negaprion brevirostris</italic> Poey, 1868 (<xref ref-type="bibr" rid="B63">Kessel et&#xa0;al., 2014</xref>). High dispersal potential and panmixia have been inferred for some migratory shark species, including <italic>Squalus acanthias</italic> Linnaeus, 1758 (<xref ref-type="bibr" rid="B113">Ver&#xed;ssimo et&#xa0;al., 2010</xref>), <italic>Squalus blainville</italic> Risso, 1827 (<xref ref-type="bibr" rid="B66">Kousteni et&#xa0;al., 2015a</xref>), <italic>Centroscymnus coelolepis</italic> Barbosa du Bocage &amp; de Brito Capello, 1864 and <italic>Centrophorus squamosus</italic> Bonnaterre, 1788 (<xref ref-type="bibr" rid="B114">Ver&#xed;ssimo et&#xa0;al., 2011a</xref>; <xref ref-type="bibr" rid="B116">Ver&#xed;ssimo et&#xa0;al., 2012</xref>). On the contrary, strong genetic differentiation has been described for the less vagile <italic>S. canicula</italic> when comparing samples from the Ionian and Aegean Seas with Atlantic, Spanish, and Algerian ones (<xref ref-type="bibr" rid="B67">Kousteni et&#xa0;al., 2015b</xref>) and within the Alboran Sea and Western Mediterranean (<xref ref-type="bibr" rid="B94">Ram&#xed;rez-Amaro et&#xa0;al., 2018</xref>). According to <xref ref-type="bibr" rid="B94">Ram&#xed;rez-Amaro et&#xa0;al. (2018)</xref>, results for <italic>G. melastomus</italic> collected in the same areas did show genetic connectivity, being the latter well supported by a high number of migrants per generation crossing the Alboran and Balearic Seas.</p>
<p>In addition, ecological traits, such as feeding habits, may also contribute to population structuring. The relationship between predator abundance and prey density has been discussed in <xref ref-type="bibr" rid="B6">Barr&#xed;a et&#xa0;al. (2018)</xref>; <xref ref-type="bibr" rid="B93">Ram&#xed;rez-Amaro et&#xa0;al. (2020)</xref> and more recently in <xref ref-type="bibr" rid="B104">Sbrana et&#xa0;al. (2022)</xref> when describing marine predators&#x2019; foraging maximisation. In their works, these authors indicated the possibility that population structure and dynamics may depend on the adoption of opportunistic habits and a highly diverse diet, a trait that may enhance their susceptibility to spatial-temporal changes in prey abundance (<xref ref-type="bibr" rid="B12">Campana and Joyce, 2004</xref>; <xref ref-type="bibr" rid="B4">Anastasopoulou et&#xa0;al., 2013</xref>).</p>
<p>For some deep-sea elasmobranch species such as <italic>C. coelolepis</italic> (<xref ref-type="bibr" rid="B19">Catarino et&#xa0;al., 2015</xref>), <italic>Etmopterus spinax</italic> Linnaeus, 1758 (<xref ref-type="bibr" rid="B53">Gubili et&#xa0;al., 2016</xref>) and hypothetically also for <italic>G. atlanticus</italic> (<xref ref-type="bibr" rid="B97">Rey et&#xa0;al., 2010</xref>), the Strait of Gibraltar represents a breakpoint in the connectivity of the species. Differently, our results did not highlight such a strong barrier to the gene flow between Mediterranean and adjacent Atlantic, since samples collected along the Portuguese coasts were strongly different from the northernmost Scottish sample but were similar to those collected in the western Mediterranean (Spanish and Ligurian) waters. These results appear discordant with the identification of water circulation assumption as a physical barrier (see <xref ref-type="bibr" rid="B101">Roque et&#xa0;al., 2019</xref> for Atlantic currents), but not with the bathymetry since these areas are divided by the Bay of Biscay characterised by an average depth of 1744&#xa0;m, much deeper than the common depths inhabited by <italic>G. melastomus</italic> and reached only occasionally (<xref ref-type="bibr" rid="B36">Ebert et&#xa0;al., 2021</xref>). In addition, in the Atlantic Ocean temperature decreases with latitude, likely limiting the migration of individuals along the Atlantic coast and influencing their spatial dispersion (<xref ref-type="bibr" rid="B55">Hemmer-Hansen et&#xa0;al., 2007</xref>). Strong genetic differences were also detected by outlier SNPs between Northern and Southern North-eastern Atlantic samples of the European hake <italic>Merluccius merluccius</italic> Linnaeus, 1758 (<xref ref-type="bibr" rid="B80">Milano et&#xa0;al., 2014</xref>), a species with several ecological traits similar to the blackmouth shark.</p>
<p>The relationship existing between sensitive ecosystems (e.g., canyons and cold-water coral habitats, nurseries and refugia) and inhabiting species, should be preserved with effective conservation strategies (<xref ref-type="bibr" rid="B16">Carluccio et&#xa0;al., 2021</xref>). In this perspective, further in-depth research focusing on the monitoring of natural populations of <italic>G. melastomus</italic> and on the comparison of the genetic variability and differentiation of populations over multiple generations are required. Over temporal replicates, any difference in allelic richness and allele frequencies could reveal the existence of a founder effect or past bottleneck events. Additionally, including individuals of <italic>G. melastomus</italic> from other areas in the Mediterranean Sea as the North African coasts, Western Mediterranean waters and the Levantine Sea could be useful to describe any further differentiation in the Basin, especially in those areas with canyon systems and other essential fish habitats. Similarly, targeting the Atlantic Iberian coasts, the Bay of Biscay, the West of Ireland and the United Kingdom and Norway waters would pinpoint the species&#x2019; connectivity in the North-eastern Atlantic Ocean.</p>
<p>Maximising the monitoring of Mediterranean and Atlantic populations of blackmouth catshark both in its temporal and spatial coverage is advisable and it could be achieved by capitalising established scientific surveys where <italic>G. melastomus</italic> represents one of the target species (i.e., MEDITS and PNAB; <xref ref-type="bibr" rid="B108">Spedicato et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B118">Vieira et&#xa0;al., 2020</xref>). In addition, the employment of non-invasive sampling protocols (i.e., environmental DNA; <xref ref-type="bibr" rid="B3">Aglieri et&#xa0;al., 2021</xref>) represent a valuable approach to obtain data without sacrificing individuals for research purposes, even though such techniques have not been extensively applied to threatened and deep water species (<xref ref-type="bibr" rid="B34">Dugal et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B78">Merten et&#xa0;al., 2021</xref>). The improvement of the genotyping approach (i.e., the application of an increased number of polymorphic microsatellite loci or the development of panels of Single Nucleotide Polymorphisms, SNPs) will provide more statistical power for the robust delineation of the genetic structure of the species. The application of high throughput sequencing techniques would likely enhance the detection of randomly distributed genomic markers. In species where large numbers of SNPs have been screened, even a small fraction of these markers has been demonstrated to be very informative for population structure analysis, sometimes outperforming highly polymorphic microsatellites (<xref ref-type="bibr" rid="B74">Liu et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B70">Lao et&#xa0;al., 2006</xref>).</p>
<p>Within the technological framework, this research work advanced by providing a new panel of 13 heterospecific microsatellite markers that were deeply verified to cross-amplify genetic loci in <italic>G. melastomus</italic>. Very positive results of cross-amplification tests confirmed that the microsatellite loci investigated in <italic>G. melastomu</italic>s are particularly well-conserved over time in related families (i.e., Triakidae with <italic>G. galeus</italic> and <italic>Mustelus</italic> spp.), but also in phylogenetically more distant families and species as <italic>Hexanchus griseus</italic>, within the family Hexanchidae, and <italic>C. crepidater</italic>, within the family Somniosidae, which are the most distant taxa from Pentachidae and <italic>G. melastomus</italic> (<xref ref-type="bibr" rid="B85">Naylor et&#xa0;al., 2012</xref>). Overall, similar rates of success in cross-amplification were reached here compared to the literature (<xref ref-type="bibr" rid="B52">Griffiths et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B54">Helyar et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B115">Ver&#xed;ssimo et&#xa0;al., 2011b</xref>; see <xref ref-type="supplementary-material" rid="SM1">
<bold>SM9</bold>
</xref> for comparison of cross-amplification results on <italic>G. melastomus</italic>). Most importantly, since these loci resulted largely polymorphic at the pan-European scale, this novel panel of microsatellites could be considered an effective analytical tool for assessing and monitoring genetic diversity and differentiation among populations and stocks either over the whole species range and at the subregional level.</p>
<p>With this research work we investigated and assessed the first evidence of genetic structure over a large, regional geographic scale of <italic>G. melastomus</italic>, a potentially vulnerable species highly represented in the bycatch composition of demersal fisheries. Understanding the intrinsic characteristics of both Mediterranean basin (e.g., bathymetry, water currents and deep-water temperature) and the species life-history traits and ecology will likely disclose the drivers influencing species differentiation, as well as the potential decline in species abundance, meaning the loss of biodiversity at a local scale with important long-term effects leading to local depletion (<xref ref-type="bibr" rid="B27">Dell&#x2019;Apa et&#xa0;al., 2012</xref>). For these reasons, the effective panel of cross-specific and polymorphic microsatellite loci developed here will enhance the monitoring of natural populations of <italic>G. melastomus.</italic> The results described enhance the refining and integration of the current knowledge on the diversity and connectivity of a key species for deep-sea ecosystems (<xref ref-type="bibr" rid="B33">D&#x2019;Iglio et&#xa0;al., 2021b</xref>). As a mesopelagic predator with a diverse diet, the blackmouth catshark is becoming one of the most important sentinels of the health of deep habitats and an indicator of human impacts on the marine environment that should be effectively managed (<xref ref-type="bibr" rid="B104">Sbrana et&#xa0;al., 2022</xref>). The improvement and employment of genetic and genomic tools coupled with wide research actions (e.g., integrating data on biology, reproductive strategies, feeding and migratory behaviours) should be directed at gathering information on spawning and nursery areas, pursuing scientific surveys at sea to detect discrete groups of populations (<xref ref-type="bibr" rid="B30">Domingues et&#xa0;al., 2018</xref>). Robust data mining along with strengthened international networks of collaborations maximising the monitoring effort, will likely fill the gaps in our knowledge of this benthic shark, and encourage effective management and conservation plans for the key species and its habitat.</p>
</sec>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The data presented in this study are included in the supplementary material (SM1; SM10), further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s6" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>Ethical review and approval was not required for the animal study because the following information was supplied relating to ethical approvals (i.e., approving body and any reference numbers): samples of shark individuals analyzed in the present work were obtained from commercial and scientific fisheries. The activity was conducted with the observation of the Regulation of the European Parliament and the Council for fishing in the General Fisheries Commission for the Mediterranean (GFCM) Agreement area and amending Council Regulation (EC) No. 1967/2006. This Regulation is de facto the unique authorization needed to conduct this type of activity.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>SC, AF, AC, and FT conceived and designed the study. SC performed the molecular and data analyses. RC and IM contributed to statistical revision. SC and AF wrote the first draft of the manuscript. CB, JD, LF-P, DG, MH, VK, DM, TM, JR, PS, US, FS, and MS provided the samples used in this work. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>This research was funded by RFO and Canziani grants given to FT and AC, and by the RFO grant of the University of Bologna for the research fellowships of AF. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</p>
</sec>
<sec id="s9" sec-type="acknowledgment">
<title>Acknowledgments</title>
<p>We thank all contributors to this research. In particular, we are grateful to all the participants in the scientific surveys, as well as the crew of each research vessel for their sampling effort.</p>
</sec>
<sec id="s10" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
<p>The reviewer FT is currently organizing a Research Topic with the author CB.</p>
</sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
</body>
<back>
<sec id="s12" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fmars.2022.953895/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fmars.2022.953895/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
</sec>
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