{"id":{"repo_id":"qu-belfast","oai_identifier":"oai:pure.qub.ac.uk/portal:studenttheses/c1150fd4-c4d3-4788-bf08-760a47f47240"},"canonical_url":"https://search.dev.ndltd.org/etd/qu-belfast/oai:pure.qub.ac.uk/portal:studenttheses/c1150fd4-c4d3-4788-bf08-760a47f47240","repository":{"repo_id":"qu-belfast","name":"Queen's University Belfast","base_url":"https://pureadmin.qub.ac.uk/ws/oai"},"display":{"title":"Genomic tools for the management of European flat oyster (Ostrea edulis) stocks","abstract":"As the heritable basis for a population’s response to changing external pressures, the genetic characterization of distinct O. edulis populations is a prerequisite for effective management and conservation strategies. While previous efforts to measure genetic diversity and structure among O. edulis stocks have provided valuable insights, they have relied on a limited number of molecular markers. In an effort to expand our understanding of O. edulis genetic units and aid effective long term stock management, tissue sampled from over 1700 individuals representing the Atlantic coasts (with a focus on Irish coasts), Croatia and introduced North American O. edulis were obtained. This sample set was normalised (n = 867) across locations and used to estimate the genetic structure and diversity with existing microsatellite markers, using several analytic approaches (Chapter 2). Novel genetic clusters were identified, while also providing a point of reference for subsequent studies with new markers. A subsample (n = 364) of individuals, representing the microsatellite-inferred genetic clusters, were genotyped using an array consisting of 11,151 novel biallelic SNP loci, and genetic diversity and structure was estimated using several methods (Chapter 3). Despite the smaller sample set used, this analyses confirmed the genetic clusters previously identified by microsatellite markers with greater accuracy. The main difference in the results from both analyses was in the degree of support for the genetic clusters, which was stronger for the SNP data set. No conclusive evidence, however, was found for further substructure. We found evidence for putative adaptive differences between inferred genetic clusters. Finally, mitochondrial genome (mtDNA) resequencing of O.edulis (n = 40 ) from seven distinct locations forms the basis of Chapter 4. A preliminary analysis of molecular diversity and phylogeny among these samples was undertaken. In addition, we outline an approach to identify highly informative mtDNA regions, for marker design and more efficient application over a large sample set.","abstract_html":"As the heritable basis for a population’s response to changing external pressures, the genetic characterization of distinct O. edulis populations is a prerequisite for effective management and conservation strategies. While previous efforts to measure genetic diversity and structure among O. edulis stocks have provided valuable insights, they have relied on a limited number of molecular markers. In an effort to expand our understanding of O. edulis genetic units and aid effective long term stock management, tissue sampled from over 1700 individuals representing the Atlantic coasts (with a focus on Irish coasts), Croatia and introduced North American O. edulis were obtained. This sample set was normalised (n = 867) across locations and used to estimate the genetic structure and diversity with existing microsatellite markers, using several analytic approaches (Chapter 2). Novel genetic clusters were identified, while also providing a point of reference for subsequent studies with new markers. A subsample (n = 364) of individuals, representing the microsatellite-inferred genetic clusters, were genotyped using an array consisting of 11,151 novel biallelic SNP loci, and genetic diversity and structure was estimated using several methods (Chapter 3). Despite the smaller sample set used, this analyses confirmed the genetic clusters previously identified by microsatellite markers with greater accuracy. The main difference in the results from both analyses was in the degree of support for the genetic clusters, which was stronger for the SNP data set. No conclusive evidence, however, was found for further substructure. We found evidence for putative adaptive differences between inferred genetic clusters. Finally, mitochondrial genome (mtDNA) resequencing of O.edulis (n = 40 ) from seven distinct locations forms the basis of Chapter 4. A preliminary analysis of molecular diversity and phylogeny among these samples was undertaken. In addition, we outline an approach to identify highly informative mtDNA regions, for marker design and more efficient application over a large sample set.","abstract_has_math":false,"creators":["McCullough, Mark"],"institution":"Queen's University Belfast","degree_name":"Doctor of Philosophy","degree_level":"Doctoral Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Prodohl, Paulo"],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-7","date_published":"2020-7","updated_at":"2026-07-24T03:55:25Z","subjects":["European flat oyster","Ostrea edulis","Population Genetics","Microsatellite","Population Structure","SNP","selection detection","Mitochondria","bioinformatics","Aquaculture management"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:pure.qub.ac.uk/portal:studenttheses/c1150fd4-c4d3-4788-bf08-760a47f47240"],"render_values":[{"text":"oai:pure.qub.ac.uk/portal:studenttheses/c1150fd4-c4d3-4788-bf08-760a47f47240","href":null,"code":true}]}]},"links":{"outbound_url":"https://pure.qub.ac.uk/en/studentTheses/c1150fd4-c4d3-4788-bf08-760a47f47240","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Prodohl, Paulo"]},{"key":"dc:contributor.sponsor","label":"Sponsor","values":["INTERREG VA Programme (European Union)","University of New Brunswick"]},{"key":"dc:creator","label":"Author","values":["McCullough, Mark"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-7"]},{"key":"dc:date.issued","label":"Date","values":["2020-7"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["School of Biological Sciences"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Queen's University Belfast"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://pure.qub.ac.uk/en/studentTheses/c1150fd4-c4d3-4788-bf08-760a47f47240"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral Thesis"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctor of Philosophy"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["European flat oyster","Ostrea edulis","Population Genetics","Microsatellite","Population Structure","SNP","selection detection","Mitochondria","bioinformatics","Aquaculture management"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights.embargodate","label":"Dc Rights Embargodate","values":["2022-07-31"]},{"key":"dc:rights.embargoreason","label":"Dc Rights Embargoreason","values":["/dk/atira/pure/core/document/studentthesisembargoreason/publicationissues"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:pure.qub.ac.uk/portal:studenttheses/c1150fd4-c4d3-4788-bf08-760a47f47240","https://pure.qub.ac.uk/en/studentTheses/c1150fd4-c4d3-4788-bf08-760a47f47240"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://pure.qub.ac.uk/files/212219234/Genomic_tools_for_the_management_of_European_flat_oyster_Ostrea_edulis_stocks.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["As the heritable basis for a population’s response to changing external pressures, the genetic characterization of distinct O. edulis populations is a prerequisite for effective management and conservation strategies. While previous efforts to measure genetic diversity and structure among O. edulis stocks have provided valuable insights, they have relied on a limited number of molecular markers. In an effort to expand our understanding of O. edulis genetic units and aid effective long term stock management, tissue sampled from over 1700 individuals representing the Atlantic coasts (with a focus on Irish coasts), Croatia and introduced North American O. edulis were obtained. This sample set was normalised (n = 867) across locations and used to estimate the genetic structure and diversity with existing microsatellite markers, using several analytic approaches (Chapter 2). Novel genetic clusters were identified, while also providing a point of reference for subsequent studies with new markers. A subsample (n = 364) of individuals, representing the microsatellite-inferred genetic clusters, were genotyped using an array consisting of 11,151 novel biallelic SNP loci, and genetic diversity and structure was estimated using several methods (Chapter 3). Despite the smaller sample set used, this analyses confirmed the genetic clusters previously identified by microsatellite markers with greater accuracy. The main difference in the results from both analyses was in the degree of support for the genetic clusters, which was stronger for the SNP data set. No conclusive evidence, however, was found for further substructure. We found evidence for putative adaptive differences between inferred genetic clusters. Finally, mitochondrial genome (mtDNA) resequencing of O.edulis (n = 40 ) from seven distinct locations forms the basis of Chapter 4. A preliminary analysis of molecular diversity and phylogeny among these samples was undertaken. In addition, we outline an approach to identify highly informative mtDNA regions, for marker design and more efficient application over a large sample set."]},{"key":"dc:title","label":"Title","values":["Genomic tools for the management of European flat oyster (Ostrea edulis) stocks"]}]}],"canonical_facts":{"dc:contributor.advisor":["Prodohl, Paulo"],"dc:contributor.sponsor":["INTERREG VA Programme (European Union)","University of New Brunswick"],"dc:creator":["McCullough, Mark"],"dc:date":["2020-7"],"dc:date.issued":["2020-7"],"dc:description.abstract":["As the heritable basis for a population’s response to changing external pressures, the genetic characterization of distinct O. edulis populations is a prerequisite for effective management and conservation strategies. While previous efforts to measure genetic diversity and structure among O. edulis stocks have provided valuable insights, they have relied on a limited number of molecular markers. In an effort to expand our understanding of O. edulis genetic units and aid effective long term stock management, tissue sampled from over 1700 individuals representing the Atlantic coasts (with a focus on Irish coasts), Croatia and introduced North American O. edulis were obtained. This sample set was normalised (n = 867) across locations and used to estimate the genetic structure and diversity with existing microsatellite markers, using several analytic approaches (Chapter 2). Novel genetic clusters were identified, while also providing a point of reference for subsequent studies with new markers. A subsample (n = 364) of individuals, representing the microsatellite-inferred genetic clusters, were genotyped using an array consisting of 11,151 novel biallelic SNP loci, and genetic diversity and structure was estimated using several methods (Chapter 3). Despite the smaller sample set used, this analyses confirmed the genetic clusters previously identified by microsatellite markers with greater accuracy. The main difference in the results from both analyses was in the degree of support for the genetic clusters, which was stronger for the SNP data set. No conclusive evidence, however, was found for further substructure. We found evidence for putative adaptive differences between inferred genetic clusters. Finally, mitochondrial genome (mtDNA) resequencing of O.edulis (n = 40 ) from seven distinct locations forms the basis of Chapter 4. A preliminary analysis of molecular diversity and phylogeny among these samples was undertaken. In addition, we outline an approach to identify highly informative mtDNA regions, for marker design and more efficient application over a large sample set."],"dc:identifier":["oai:pure.qub.ac.uk/portal:studenttheses/c1150fd4-c4d3-4788-bf08-760a47f47240","https://pure.qub.ac.uk/en/studentTheses/c1150fd4-c4d3-4788-bf08-760a47f47240"],"dc:identifier.uri":["https://pure.qub.ac.uk/files/212219234/Genomic_tools_for_the_management_of_European_flat_oyster_Ostrea_edulis_stocks.pdf"],"dc:language":["eng"],"dc:publisher.department":["School of Biological Sciences"],"dc:publisher.institution":["Queen's University Belfast"],"dc:relation.isreferencedby":["https://pure.qub.ac.uk/en/studentTheses/c1150fd4-c4d3-4788-bf08-760a47f47240"],"dc:rights.embargodate":["2022-07-31"],"dc:rights.embargoreason":["/dk/atira/pure/core/document/studentthesisembargoreason/publicationissues"],"dc:subject":["European flat oyster","Ostrea edulis","Population Genetics","Microsatellite","Population Structure","SNP","selection detection","Mitochondria","bioinformatics","Aquaculture management"],"dc:title":["Genomic tools for the management of European flat oyster (Ostrea edulis) stocks"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Doctoral Thesis"],"dc:type.qualificationname":["Doctor of Philosophy"]},"updated_at":"2026-07-24T03:55:25Z"}