Quantitative trait loci for yield and grain plumpness relative to maturity in three populations of barley (Hordeum vulgare L.) grown in a low rain-fall environment
Identifieur interne : 002980 ( Pmc/Corpus ); précédent : 002979; suivant : 002981Quantitative trait loci for yield and grain plumpness relative to maturity in three populations of barley (Hordeum vulgare L.) grown in a low rain-fall environment
Auteurs : Bulti Tesso Obsa ; Jason Eglinton ; Stewart Coventry ; Timothy March ; Maxime Guillaume ; Thanh Phuoc Le ; Matthew Hayden ; Peter Langridge ; Delphine FleurySource :
- PLoS ONE [ 1932-6203 ] ; 2017.
Abstract
Identifying yield and grain plumpness QTL that are independent of developmental variation or phenology is of paramount importance for developing widely adapted and stable varieties through the application of marker assisted selection. The current study was designed to dissect the genetic basis of yield performance and grain plumpness in southern Australia using three doubled haploid (DH) populations developed from crosses between adapted parents that are similar in maturity and overall plant development. Three interconnected genetic populations, Commander x Fleet (CF), Commander x WI4304 (CW), and Fleet x WI4304 (FW) developed from crossing of Australian elite barley genotypes, were used to map QTL controlling yield and grain plumpness. QTL for grain plumpness and yield were analysed using genetic linkage maps made of genotyping-by-sequencing markers and major phenology genes, and field trials at three drought prone environments for two growing seasons. Seventeen QTL were detected for grain plumpness. Eighteen yield QTL explaining from 1.2% to 25.0% of the phenotypic variation were found across populations and environments. Significant QTL x environment interaction was observed for all grain plumpness and yield QTL, except
Url:
DOI: 10.1371/journal.pone.0178111
PubMed: 28542571
PubMed Central: 5441627
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PMC:5441627Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Quantitative trait loci for yield and grain plumpness relative to maturity in three populations of barley (<italic>Hordeum vulgare</italic> L.) grown in a low rain-fall environment</title><author><name sortKey="Obsa, Bulti Tesso" sort="Obsa, Bulti Tesso" uniqKey="Obsa B" first="Bulti Tesso" last="Obsa">Bulti Tesso Obsa</name><affiliation><nlm:aff id="aff001"><addr-line>Australian Centre for Plant Functional Genomics, School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Eglinton, Jason" sort="Eglinton, Jason" uniqKey="Eglinton J" first="Jason" last="Eglinton">Jason Eglinton</name><affiliation><nlm:aff id="aff002"><addr-line>School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Coventry, Stewart" sort="Coventry, Stewart" uniqKey="Coventry S" first="Stewart" last="Coventry">Stewart Coventry</name><affiliation><nlm:aff id="aff002"><addr-line>School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="March, Timothy" sort="March, Timothy" uniqKey="March T" first="Timothy" last="March">Timothy March</name><affiliation><nlm:aff id="aff002"><addr-line>School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Guillaume, Maxime" sort="Guillaume, Maxime" uniqKey="Guillaume M" first="Maxime" last="Guillaume">Maxime Guillaume</name><affiliation><nlm:aff id="aff003"><addr-line>Montpellier SupAgro, Montpellier, France</addr-line></nlm:aff></affiliation></author><author><name sortKey="Le, Thanh Phuoc" sort="Le, Thanh Phuoc" uniqKey="Le T" first="Thanh Phuoc" last="Le">Thanh Phuoc Le</name><affiliation><nlm:aff id="aff004"><addr-line>Department of Plant Protection, College of Agriculture & Applied Biology, Can Tho University, Can Tho, Vietnam</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hayden, Matthew" sort="Hayden, Matthew" uniqKey="Hayden M" first="Matthew" last="Hayden">Matthew Hayden</name><affiliation><nlm:aff id="aff005"><addr-line>Department of Economic Development, Jobs, Transport and Resources, Agribio, La Trobe University, Bundoora, Victoria, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Langridge, Peter" sort="Langridge, Peter" uniqKey="Langridge P" first="Peter" last="Langridge">Peter Langridge</name><affiliation><nlm:aff id="aff001"><addr-line>Australian Centre for Plant Functional Genomics, School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff002"><addr-line>School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Fleury, Delphine" sort="Fleury, Delphine" uniqKey="Fleury D" first="Delphine" last="Fleury">Delphine Fleury</name><affiliation><nlm:aff id="aff001"><addr-line>Australian Centre for Plant Functional Genomics, School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">28542571</idno><idno type="pmc">5441627</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5441627</idno><idno type="RBID">PMC:5441627</idno><idno type="doi">10.1371/journal.pone.0178111</idno><date when="2017">2017</date><idno type="wicri:Area/Pmc/Corpus">002980</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">002980</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Quantitative trait loci for yield and grain plumpness relative to maturity in three populations of barley (<italic>Hordeum vulgare</italic> L.) grown in a low rain-fall environment</title><author><name sortKey="Obsa, Bulti Tesso" sort="Obsa, Bulti Tesso" uniqKey="Obsa B" first="Bulti Tesso" last="Obsa">Bulti Tesso Obsa</name><affiliation><nlm:aff id="aff001"><addr-line>Australian Centre for Plant Functional Genomics, School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Eglinton, Jason" sort="Eglinton, Jason" uniqKey="Eglinton J" first="Jason" last="Eglinton">Jason Eglinton</name><affiliation><nlm:aff id="aff002"><addr-line>School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Coventry, Stewart" sort="Coventry, Stewart" uniqKey="Coventry S" first="Stewart" last="Coventry">Stewart Coventry</name><affiliation><nlm:aff id="aff002"><addr-line>School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="March, Timothy" sort="March, Timothy" uniqKey="March T" first="Timothy" last="March">Timothy March</name><affiliation><nlm:aff id="aff002"><addr-line>School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Guillaume, Maxime" sort="Guillaume, Maxime" uniqKey="Guillaume M" first="Maxime" last="Guillaume">Maxime Guillaume</name><affiliation><nlm:aff id="aff003"><addr-line>Montpellier SupAgro, Montpellier, France</addr-line></nlm:aff></affiliation></author><author><name sortKey="Le, Thanh Phuoc" sort="Le, Thanh Phuoc" uniqKey="Le T" first="Thanh Phuoc" last="Le">Thanh Phuoc Le</name><affiliation><nlm:aff id="aff004"><addr-line>Department of Plant Protection, College of Agriculture & Applied Biology, Can Tho University, Can Tho, Vietnam</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hayden, Matthew" sort="Hayden, Matthew" uniqKey="Hayden M" first="Matthew" last="Hayden">Matthew Hayden</name><affiliation><nlm:aff id="aff005"><addr-line>Department of Economic Development, Jobs, Transport and Resources, Agribio, La Trobe University, Bundoora, Victoria, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Langridge, Peter" sort="Langridge, Peter" uniqKey="Langridge P" first="Peter" last="Langridge">Peter Langridge</name><affiliation><nlm:aff id="aff001"><addr-line>Australian Centre for Plant Functional Genomics, School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation><affiliation><nlm:aff id="aff002"><addr-line>School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author><author><name sortKey="Fleury, Delphine" sort="Fleury, Delphine" uniqKey="Fleury D" first="Delphine" last="Fleury">Delphine Fleury</name><affiliation><nlm:aff id="aff001"><addr-line>Australian Centre for Plant Functional Genomics, School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></nlm:aff></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="eISSN">1932-6203</idno><imprint><date when="2017">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Identifying yield and grain plumpness QTL that are independent of developmental variation or phenology is of paramount importance for developing widely adapted and stable varieties through the application of marker assisted selection. The current study was designed to dissect the genetic basis of yield performance and grain plumpness in southern Australia using three doubled haploid (DH) populations developed from crosses between adapted parents that are similar in maturity and overall plant development. Three interconnected genetic populations, Commander x Fleet (CF), Commander x WI4304 (CW), and Fleet x WI4304 (FW) developed from crossing of Australian elite barley genotypes, were used to map QTL controlling yield and grain plumpness. QTL for grain plumpness and yield were analysed using genetic linkage maps made of genotyping-by-sequencing markers and major phenology genes, and field trials at three drought prone environments for two growing seasons. Seventeen QTL were detected for grain plumpness. Eighteen yield QTL explaining from 1.2% to 25.0% of the phenotypic variation were found across populations and environments. Significant QTL x environment interaction was observed for all grain plumpness and yield QTL, except <italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>1</italic> and <italic>QYld</italic>.<italic>FW-2H</italic>.<italic>1</italic>. Unlike previous yield QTL studies in barley, none of the major developmental genes, including <italic>Ppd-H1</italic>, <italic>Vrn-H1</italic>, <italic>Vrn-H2</italic> and <italic>Vrn-H3</italic>, that drive barley adaption significantly affected grain plumpness and yield here. Twenty-two QTL controlled yield or grain plumpness independently of known maturity QTL or genes. Adjustment for maturity effects through co-variance analysis had no major effect on these yield QTL indicating that they control yield <italic>per se</italic>.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Tester, M" uniqKey="Tester M">M Tester</name></author><author><name sortKey="Langridge, P" uniqKey="Langridge P">P Langridge</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Burger, W" uniqKey="Burger W">W Burger</name></author><author><name sortKey="Laberge, D" uniqKey="Laberge D">D LaBerge</name></author><author><name sortKey="Rasmusson, Dc" uniqKey="Rasmusson D">DC Rasmusson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Coventry, J" uniqKey="Coventry J">J Coventry</name></author><author><name sortKey="Barr, A" uniqKey="Barr A">A Barr</name></author><author><name 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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id><journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">plosone</journal-id><journal-title-group><journal-title>PLoS ONE</journal-title></journal-title-group><issn pub-type="epub">1932-6203</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, CA USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">28542571</article-id><article-id pub-id-type="pmc">5441627</article-id><article-id pub-id-type="doi">10.1371/journal.pone.0178111</article-id><article-id pub-id-type="publisher-id">PONE-D-17-01296</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Genetics</subject><subj-group><subject>Genetic Loci</subject><subj-group><subject>Quantitative Trait Loci</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Organisms</subject><subj-group><subject>Plants</subject><subj-group><subject>Grasses</subject><subj-group><subject>Barley</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Molecular Biology</subject><subj-group><subject>Molecular Biology Techniques</subject><subj-group><subject>Gene Mapping</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Research and Analysis Methods</subject><subj-group><subject>Molecular Biology Techniques</subject><subj-group><subject>Gene Mapping</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Cell Biology</subject><subj-group><subject>Chromosome Biology</subject><subj-group><subject>Chromosomes</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Organisms</subject><subj-group><subject>Animals</subject><subj-group><subject>Vertebrates</subject><subj-group><subject>Amniotes</subject><subj-group><subject>Birds</subject><subj-group><subject>Fowl</subject><subj-group><subject>Waterfowl</subject><subj-group><subject>Swans</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Evolutionary Biology</subject><subj-group><subject>Population Genetics</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Genetics</subject><subj-group><subject>Population Genetics</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Population Biology</subject><subj-group><subject>Population Genetics</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>People and Places</subject><subj-group><subject>Geographical Locations</subject><subj-group><subject>Oceania</subject><subj-group><subject>Australia</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Genetics</subject><subj-group><subject>Genetic Loci</subject></subj-group></subj-group></subj-group></article-categories><title-group><article-title>Quantitative trait loci for yield and grain plumpness relative to maturity in three populations of barley (<italic>Hordeum vulgare</italic> L.) grown in a low rain-fall environment</article-title><alt-title alt-title-type="running-head">QTL for yield and grain plumpness in three populations of barley grown in a low rain-fall environment</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Obsa</surname><given-names>Bulti Tesso</given-names></name><xref ref-type="aff" rid="aff001"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Eglinton</surname><given-names>Jason</given-names></name><xref ref-type="aff" rid="aff002"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Coventry</surname><given-names>Stewart</given-names></name><xref ref-type="aff" rid="aff002"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>March</surname><given-names>Timothy</given-names></name><xref ref-type="aff" rid="aff002"><sup>2</sup></xref></contrib><contrib contrib-type="author"><name><surname>Guillaume</surname><given-names>Maxime</given-names></name><xref ref-type="aff" rid="aff003"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Le</surname><given-names>Thanh Phuoc</given-names></name><xref ref-type="aff" rid="aff004"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Hayden</surname><given-names>Matthew</given-names></name><xref ref-type="aff" rid="aff005"><sup>5</sup></xref></contrib><contrib contrib-type="author"><name><surname>Langridge</surname><given-names>Peter</given-names></name><xref ref-type="aff" rid="aff001"><sup>1</sup></xref><xref ref-type="aff" rid="aff002"><sup>2</sup></xref></contrib><contrib contrib-type="author"><contrib-id authenticated="true" contrib-id-type="orcid">http://orcid.org/0000-0002-7077-4103</contrib-id><name><surname>Fleury</surname><given-names>Delphine</given-names></name><xref ref-type="aff" rid="aff001"><sup>1</sup></xref><xref ref-type="corresp" rid="cor001">*</xref></contrib></contrib-group><aff id="aff001"><label>1</label><addr-line>Australian Centre for Plant Functional Genomics, School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></aff><aff id="aff002"><label>2</label><addr-line>School of Agriculture, Food and Wine, Waite Research Institute, The University of Adelaide, Glen Osmond, South Australia, Australia</addr-line></aff><aff id="aff003"><label>3</label><addr-line>Montpellier SupAgro, Montpellier, France</addr-line></aff><aff id="aff004"><label>4</label><addr-line>Department of Plant Protection, College of Agriculture & Applied Biology, Can Tho University, Can Tho, Vietnam</addr-line></aff><aff id="aff005"><label>5</label><addr-line>Department of Economic Development, Jobs, Transport and Resources, Agribio, La Trobe University, Bundoora, Victoria, Australia</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Raman</surname><given-names>Harsh</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1"><addr-line>New South Wales Department of Primary Industries, AUSTRALIA</addr-line></aff><author-notes><fn fn-type="COI-statement" id="coi001"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type="con"><p><list list-type="simple"><list-item><p><bold>Conceptualization:</bold> DF JE PL.</p></list-item><list-item><p><bold>Data curation:</bold> BTO DF.</p></list-item><list-item><p><bold>Formal analysis:</bold> BTO TM SC MH.</p></list-item><list-item><p><bold>Funding acquisition:</bold> JE PL.</p></list-item><list-item><p><bold>Investigation:</bold> BTO ST MG TPL TM MH.</p></list-item><list-item><p><bold>Project administration:</bold> DF JE.</p></list-item><list-item><p><bold>Resources:</bold> SC MH.</p></list-item><list-item><p><bold>Supervision:</bold> DF.</p></list-item><list-item><p><bold>Validation:</bold> DF.</p></list-item><list-item><p><bold>Visualization:</bold> BTO DF.</p></list-item><list-item><p><bold>Writing – original draft:</bold> BTO.</p></list-item><list-item><p><bold>Writing – review & editing:</bold> DF PL JE TM.</p></list-item></list></p></fn><corresp id="cor001">* E-mail: <email>delphine.fleury@adelaide.edu.au</email></corresp></author-notes><pub-date pub-type="epub"><day>23</day><month>5</month><year>2017</year></pub-date><pub-date pub-type="collection"><year>2017</year></pub-date><volume>12</volume><issue>5</issue><elocation-id>e0178111</elocation-id><history><date date-type="received"><day>11</day><month>1</month><year>2017</year></date><date date-type="accepted"><day>6</day><month>5</month><year>2017</year></date></history><permissions><copyright-statement>© 2017 Obsa et al</copyright-statement><copyright-year>2017</copyright-year><copyright-holder>Obsa et al</copyright-holder><license xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p></license></permissions><self-uri content-type="pdf" xlink:href="pone.0178111.pdf"></self-uri><abstract><p>Identifying yield and grain plumpness QTL that are independent of developmental variation or phenology is of paramount importance for developing widely adapted and stable varieties through the application of marker assisted selection. The current study was designed to dissect the genetic basis of yield performance and grain plumpness in southern Australia using three doubled haploid (DH) populations developed from crosses between adapted parents that are similar in maturity and overall plant development. Three interconnected genetic populations, Commander x Fleet (CF), Commander x WI4304 (CW), and Fleet x WI4304 (FW) developed from crossing of Australian elite barley genotypes, were used to map QTL controlling yield and grain plumpness. QTL for grain plumpness and yield were analysed using genetic linkage maps made of genotyping-by-sequencing markers and major phenology genes, and field trials at three drought prone environments for two growing seasons. Seventeen QTL were detected for grain plumpness. Eighteen yield QTL explaining from 1.2% to 25.0% of the phenotypic variation were found across populations and environments. Significant QTL x environment interaction was observed for all grain plumpness and yield QTL, except <italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>1</italic> and <italic>QYld</italic>.<italic>FW-2H</italic>.<italic>1</italic>. Unlike previous yield QTL studies in barley, none of the major developmental genes, including <italic>Ppd-H1</italic>, <italic>Vrn-H1</italic>, <italic>Vrn-H2</italic> and <italic>Vrn-H3</italic>, that drive barley adaption significantly affected grain plumpness and yield here. Twenty-two QTL controlled yield or grain plumpness independently of known maturity QTL or genes. Adjustment for maturity effects through co-variance analysis had no major effect on these yield QTL indicating that they control yield <italic>per se</italic>.</p></abstract><funding-group><award-group id="award001"><funding-source><institution-wrap><institution-id institution-id-type="funder-id">http://dx.doi.org/10.13039/100008584</institution-id><institution>Grain Research and Development Corporation</institution></institution-wrap></funding-source><principal-award-recipient><name><surname>Obsa</surname><given-names>Bulti Tesso</given-names></name></principal-award-recipient></award-group><award-group id="award002"><funding-source><institution-wrap><institution-id institution-id-type="funder-id">http://dx.doi.org/10.13039/501100000923</institution-id><institution>Australian Research Council</institution></institution-wrap></funding-source><principal-award-recipient><name><surname>Obsa</surname><given-names>Bulti Tesso</given-names></name></principal-award-recipient></award-group><award-group id="award003"><funding-source><institution>South Australia Grain Industry Trust</institution></funding-source><principal-award-recipient><name><surname>Obsa</surname><given-names>Bulti Tesso</given-names></name></principal-award-recipient></award-group><award-group id="award004"><funding-source><institution-wrap><institution-id institution-id-type="funder-id">http://dx.doi.org/10.13039/501100001786</institution-id><institution>University of Adelaide</institution></institution-wrap></funding-source><principal-award-recipient><name><surname>Obsa</surname><given-names>Bulti Tesso</given-names></name></principal-award-recipient></award-group><award-group id="award005"><funding-source><institution-wrap><institution-id institution-id-type="funder-id">http://dx.doi.org/10.13039/501100002041</institution-id><institution>Department of Further Education, Employment, Science and Technology, Government of South Australia</institution></institution-wrap></funding-source><principal-award-recipient><name><surname>Obsa</surname><given-names>Bulti Tesso</given-names></name></principal-award-recipient></award-group><funding-statement>This work is partially funded by the South Australia Grain Industry Trust Fund (UA 1202), and by Australian Research Council, Grains Research and Development Corporation, the South Australian Government, the Department of Further Education, Employment, Science and Technology, and The University of Adelaide through the Australian Centre for Plant Functional Genomics. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement></funding-group><counts><fig-count count="1"></fig-count><table-count count="3"></table-count><page-count count="17"></page-count></counts><custom-meta-group><custom-meta id="data-availability"><meta-name>Data Availability</meta-name><meta-value>All relevant data are within the paper and its Supporting Information files.</meta-value></custom-meta></custom-meta-group></article-meta><notes><title>Data Availability</title><p>All relevant data are within the paper and its Supporting Information files.</p></notes></front><body><sec sec-type="intro" id="sec001"><title>Introduction</title><p>The average yield of Australian barley is 2 t/ha [<xref rid="pone.0178111.ref001" ref-type="bibr">1</xref>], which is below the world average of 3 t/ha [<xref rid="pone.0178111.ref002" ref-type="bibr">2</xref>]. Barley production in southern Australia is particularly constrained by cyclic and terminal drought in addition to a number of biotic, abiotic and physiochemical subsoil stresses. Yield is a complex quantitative trait whose expression is highly influenced by the environment and agronomic management. This makes phenotype-based selection slow and unreliable, especially under environments where multiple abiotic stresses prevail. Developing barley varieties with improved and stable yield in such environments is expected to be more challenging with ongoing climate change, thus requiring substantial changes in agronomic practices and crop improvement approaches [<xref rid="pone.0178111.ref003" ref-type="bibr">3</xref>].</p><p>In addition to high yield, barley varieties need to meet minimum grain plumpness standards to be marketed to different end users. Grain plumpness is the minimum retention (% by weight) of grain above a 2.5 mm slotted screen, the specifications for the MALT1, MALT2 and MALT3 grades being 70%, 62% and 58% respectively in Australia [<xref rid="pone.0178111.ref004" ref-type="bibr">4</xref>]. Increased grain plumpness is associated with important quality attributes for malting barley such as higher malt extract and moderate grain protein [<xref rid="pone.0178111.ref005" ref-type="bibr">5</xref>]. Grain plumpness is affected by the genotype and the environment [<xref rid="pone.0178111.ref006" ref-type="bibr">6</xref>] and is highly heritable with values of 88% to 96% reported under variable environments [<xref rid="pone.0178111.ref007" ref-type="bibr">7</xref>], indicating the potential for improvement. Grain plumpness is determined by pre-anthesis plant development related traits that affect assimilate accumulation and post-anthesis physiological traits affecting assimilate supply to the developing grain [<xref rid="pone.0178111.ref006" ref-type="bibr">6</xref>]. Farmers aim to maximise yield and grain plumpness agronomically by optimising pre-anthesis biomass production and flowering time for their environment. Genetics can be used to achieve this through improved water use efficiency, biomass production and partitioning to the grain, and by selecting for abiotic and biotic stress tolerance.</p><p>Quantitative trait loci (QTL) mapping is an important step towards development of reliable markers for marker assisted selection. QTL mapping studies for yield and other agronomic traits have been conducted under different environments using different genetic backgrounds in barley [<xref rid="pone.0178111.ref008" ref-type="bibr">8</xref>–<xref rid="pone.0178111.ref023" ref-type="bibr">23</xref>]. A usual problem in yield QTL studies under dry climate is the absence of consideration for phenology or maturity as a confounding factor. Plants can escape drought stress by completing its cycle before water deficit becomes severe [<xref rid="pone.0178111.ref024" ref-type="bibr">24</xref>]. A short cycle is particularly advantageous in environments with terminal drought stress as in Australian climate. As a result, plant maturity strongly influences grain yield under dry conditions. Frequently the reported yield-related QTL were associated with the major phenology genes such as the vernalization requirement genes (<italic>Vrn-H1</italic>, <italic>Vrn-H2</italic>, and <italic>Vrn-H3</italic>) [<xref rid="pone.0178111.ref025" ref-type="bibr">25</xref>], the photoperiod response genes (<italic>Ppd-H1</italic> and <italic>Ppd-H2</italic>) and the earliness <italic>per se</italic> (<italic>EPS2</italic>) locus [<xref rid="pone.0178111.ref020" ref-type="bibr">20</xref>, <xref rid="pone.0178111.ref026" ref-type="bibr">26</xref>]. QTL have been mapped for different aspects of grain size including grain weight, grain length, grain width, and grain width to length ratio [<xref rid="pone.0178111.ref011" ref-type="bibr">11</xref>, <xref rid="pone.0178111.ref021" ref-type="bibr">21</xref>]. Genomic regions affecting barley grain weight and size in different international and Australian mapping populations have been summarized in [<xref rid="pone.0178111.ref006" ref-type="bibr">6</xref>]. Most of these QTL were associated with loci influencing plant development, mainly with <italic>Ppd-H1</italic>, the <italic>Eps2</italic>, and the semi-dwarfing gene <italic>Denso</italic> (<italic>sdw1</italic>).</p><p><italic>Ppd-H1</italic> and <italic>Vrn-H1</italic> are the two major genes affecting flowering time in barley and have significant effects on agronomic traits including yield components [<xref rid="pone.0178111.ref027" ref-type="bibr">27</xref>]. An important gene family called <italic>FLOWERING LOCUS T</italic> (<italic>FT</italic>) induces or represses flowering in plants; this includes the barley genes <italic>HvFT1/Vrn-H3</italic> [<xref rid="pone.0178111.ref028" ref-type="bibr">28</xref>], <italic>HvFT3/Ppd-H2</italic>, <italic>TERMINAL FLOWER 1</italic> (<italic>HvTFL1</italic>) [<xref rid="pone.0178111.ref029" ref-type="bibr">29</xref>] and <italic>CENTRORADIALIS</italic> (<italic>HvCEN</italic>) gene, which is the candidate gene for <italic>EPS2</italic> [<xref rid="pone.0178111.ref030" ref-type="bibr">30</xref>]. <italic>EPS2</italic> affects flowering time and other agronomic traits including tiller biomass, tiller grain weight, ear grain number, and plant height [<xref rid="pone.0178111.ref031" ref-type="bibr">31</xref>]. Other phenology genes are associated with circadian rhythm such as the barley <italic>CONSTANS</italic> gene (<italic>HvCO1</italic> and <italic>HvCO2</italic>) [<xref rid="pone.0178111.ref032" ref-type="bibr">32</xref>], the <italic>GIGANTEA</italic> (<italic>HvGI</italic>) [<xref rid="pone.0178111.ref033" ref-type="bibr">33</xref>] and the red/far-red light <italic>PHYTOCHROMES</italic> with the barley genes, <italic>HvPhyA</italic>, <italic>HvPhyB</italic> and <italic>HvPhyC</italic> [<xref rid="pone.0178111.ref034" ref-type="bibr">34</xref>], and the <italic>APETALA2</italic> (<italic>HvAP2</italic>) gene that control inflorescence development [<xref rid="pone.0178111.ref035" ref-type="bibr">35</xref>].</p><p>Breeding for a shortened crop cycle has been a very successful strategy in Mediterranean climate. In Australia, barley maturity has already been optimised by breeders so that the plant’s phenology matches its environment. This study therefore aimed to identify novel QTL for yield and grain plumpness that were not due to phenology. Identifying such QTL that are independent of developmental variation or phenology is important for developing widely adapted and stable varieties through the application of marker assisted selection. The current study was designed to dissect the genetic basis of yield performance and grain plumpness in southern Australia using three doubled haploid (DH) populations developed from crosses between adapted parents that are similar in maturity and overall plant development.</p></sec><sec sec-type="materials|methods" id="sec002"><title>Materials and methods</title><sec id="sec003"><title>Plant material and phenotyping</title><p>Three doubled haploid (DH) populations of barley developed from reciprocal crosses among three Australian lines were used [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>]. The parental lines include two elite varieties (Commander and Fleet) and one advanced breeding line (WI4304). Commander (Keel/Sloop//Galaxy) is a malting variety with large grain size and is high yielding in southern Australia. WI4304 (Riviera/ (Puffin/Chebec)-50//Flagship) is a malting quality breeding line with high osmotic adjustment and high net photosynthesis under drought conditions [<xref rid="pone.0178111.ref037" ref-type="bibr">37</xref>]. Fleet (Mundah/Keel//Barque) is a feed variety characterized by high water use efficiency, long coleoptile, and adaptation to deep sandy soils. The parents have similar maturity which enable us to dissect the genetic basis of yield in the Australian environment with minimal confounding effect of phenology. The populations include 229 lines from the Commander x Fleet (CF), 228 lines from the Commander x WI4304 (CW), and 299 lines from the Fleet x WI4304 (FW).</p><p>Data were collected from six field trials in South Australia at Minnipa Research Centre (MRC), Roseworthy Campus of the University of Adelaide (RAC), and Swan Hill (SWA) in 2012 and 2013 cropping seasons. Each field trial was an un-replicated design with gridded checks of the parents and two reference varieties (Hindmarsh and Capstan) every eight plots. Plot size were 4 m<sup>2</sup> in Roseworthy, 5 m<sup>2</sup> in Minnipa and 7.5 m<sup>2</sup> in Swan Hill. The grain was machine harvested at physiological maturity from standard breeder’s plots and yields were converted into tonnes per hectare. Grain plumpness was obtained from the plot yields using a seed cleaning machine with a 2.5 mm slotted screen, and expressed as retention (% by weight) based on the specifications given by Grain Trade Australia (GTA 2014). Maturity was assessed as decimal growth stage based on Zadoks scale [<xref rid="pone.0178111.ref038" ref-type="bibr">38</xref>] which is a standardized scale of cereal development divided into ten principal growth stages from germination to ripening. Zadoks stage was recorded per plot, once per trial, when most plants were between booting and heading stages (Z41-Z59). The data for the six trials on these three barley populations were fully described in [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>].</p></sec><sec id="sec004"><title>Statistical analysis of phenotypic data</title><p>A multi-stage analysis was performed using the regular grid spatial design and Residual Maximum Likelihood (REML) variance components model in GenStat Version 17 (VSN International Ltd, UK). Spatial models (random and linear row and column effects) were fitted for each experiment using plotted variograms to identify spatial co-variance structures [<xref rid="pone.0178111.ref039" ref-type="bibr">39</xref>]. Best Linear Unbiased Predictors (BLUPs) were generated using genotype random effects to estimate the generalized heritability [<xref rid="pone.0178111.ref040" ref-type="bibr">40</xref>]. Anova and least significant difference (LSD) were used for comparing parental lines (<xref ref-type="table" rid="pone.0178111.t001">Table 1</xref>).</p><table-wrap id="pone.0178111.t001" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0178111.t001</object-id><label>Table 1</label><caption><title>Summary statistics based on BLUPs for yield and grain plumpness for three populations and variation in the parents at six different environments.</title></caption><alternatives><graphic id="pone.0178111.t001g" xlink:href="pone.0178111.t001"></graphic><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col></colgroup><thead><tr><th align="justify" rowspan="2" colspan="1"></th><th align="center" colspan="6" rowspan="1">Yield (t/ha)</th><th align="center" colspan="5" rowspan="1">Grain plumpness (% >2.5 mm)</th></tr><tr><th align="justify" rowspan="1" colspan="1">MRC12</th><th align="justify" rowspan="1" colspan="1">MRC13</th><th align="justify" rowspan="1" colspan="1">RAC12</th><th align="justify" rowspan="1" colspan="1">RAC13</th><th align="justify" rowspan="1" colspan="1">SWA12</th><th align="justify" rowspan="1" colspan="1">SWA13</th><th align="justify" rowspan="1" colspan="1">MRC13</th><th align="justify" rowspan="1" colspan="1">RAC12</th><th align="justify" rowspan="1" colspan="1">RAC13</th><th align="justify" rowspan="1" colspan="1">SWH12</th><th align="justify" rowspan="1" colspan="1">SWH13</th></tr></thead><tbody><tr><td align="justify" rowspan="1" colspan="1">Commander</td><td align="char" char="." rowspan="1" colspan="1">1.31<sup>a</sup></td><td align="char" char="." rowspan="1" colspan="1">3.83<sup>a</sup></td><td align="char" char="." rowspan="1" colspan="1">3.45</td><td align="char" char="." rowspan="1" colspan="1">3.11<sup>b</sup></td><td align="char" char="." rowspan="1" colspan="1">2.81<sup>a</sup></td><td align="char" char="." rowspan="1" colspan="1">2.61<sup>a</sup></td><td align="char" char="." rowspan="1" colspan="1">82.3<sup>b</sup></td><td align="justify" rowspan="1" colspan="1">80.6</td><td align="char" char="." rowspan="1" colspan="1">85.4<sup>c</sup></td><td align="justify" rowspan="1" colspan="1">83.9<sup>b</sup></td><td align="char" char="." rowspan="1" colspan="1">92.6<sup>b</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1">Fleet</td><td align="char" char="." rowspan="1" colspan="1">1.34<sup>a</sup></td><td align="char" char="." rowspan="1" colspan="1">3.92<sup>a</sup></td><td align="char" char="." rowspan="1" colspan="1">3.32</td><td align="char" char="." rowspan="1" colspan="1">3.33<sup>b</sup></td><td align="char" char="." rowspan="1" colspan="1">2.82<sup>a</sup></td><td align="char" char="." rowspan="1" colspan="1">2.59<sup>a</sup></td><td align="char" char="." rowspan="1" colspan="1">86.4<sup>a</sup></td><td align="justify" rowspan="1" colspan="1">82.3</td><td align="char" char="." rowspan="1" colspan="1">93.6<sup>a</sup></td><td align="justify" rowspan="1" colspan="1">90.1<sup>a</sup></td><td align="char" char="." rowspan="1" colspan="1">95.9<sup>a</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1">WI4304</td><td align="char" char="." rowspan="1" colspan="1">1.00<sup>b</sup></td><td align="char" char="." rowspan="1" colspan="1">3.54<sup>b</sup></td><td align="char" char="." rowspan="1" colspan="1">3.41</td><td align="char" char="." rowspan="1" colspan="1">3.73<sup>a</sup></td><td align="char" char="." rowspan="1" colspan="1">2.34<sup>b</sup></td><td align="char" char="." rowspan="1" colspan="1">2.15<sup>b</sup></td><td align="char" char="." rowspan="1" colspan="1">78.7<sup>c</sup></td><td align="justify" rowspan="1" colspan="1">81</td><td align="char" char="." rowspan="1" colspan="1">91.2<sup>b</sup></td><td align="justify" rowspan="1" colspan="1">77.2<sup>c</sup></td><td align="char" char="." rowspan="1" colspan="1">91.5<sup>b</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1">F-probability</td><td align="char" char="." rowspan="1" colspan="1"><bold><0.001</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold><0.001</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.54</bold><sup><bold>ns</bold></sup></td><td align="char" char="." rowspan="1" colspan="1"><bold><0.001</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold><0.001</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold><0.001</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold><0.001</bold></td><td align="justify" rowspan="1" colspan="1"><bold>0.80</bold><sup><bold>ns</bold></sup></td><td align="char" char="." rowspan="1" colspan="1"><bold><0.001</bold></td><td align="justify" rowspan="1" colspan="1"><bold><0.001</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold><0.001</bold></td></tr><tr><td align="justify" rowspan="1" colspan="1">CF mean</td><td align="char" char="." rowspan="1" colspan="1">1.26</td><td align="char" char="." rowspan="1" colspan="1">3.44</td><td align="char" char="." rowspan="1" colspan="1">3.20</td><td align="char" char="." rowspan="1" colspan="1">2.91</td><td align="char" char="." rowspan="1" colspan="1">2.69</td><td align="char" char="." rowspan="1" colspan="1">2.65</td><td align="char" char="." rowspan="1" colspan="1">82.8</td><td align="justify" rowspan="1" colspan="1">83.4</td><td align="char" char="." rowspan="1" colspan="1">93.7</td><td align="justify" rowspan="1" colspan="1">77.6</td><td align="char" char="." rowspan="1" colspan="1">89.6</td></tr><tr><td align="justify" rowspan="1" colspan="1">CF minimum</td><td align="char" char="." rowspan="1" colspan="1">0.70</td><td align="char" char="." rowspan="1" colspan="1">2.62</td><td align="char" char="." rowspan="1" colspan="1">1.80</td><td align="char" char="." rowspan="1" colspan="1">1.55</td><td align="char" char="." rowspan="1" colspan="1">1.82</td><td align="char" char="." rowspan="1" colspan="1">0.56</td><td align="char" char="." rowspan="1" colspan="1">57.8</td><td align="justify" rowspan="1" colspan="1">56.3</td><td align="char" char="." rowspan="1" colspan="1">82.5</td><td align="justify" rowspan="1" colspan="1">40.4</td><td align="char" char="." rowspan="1" colspan="1">67.4</td></tr><tr><td align="justify" rowspan="1" colspan="1">CF maximum</td><td align="char" char="." rowspan="1" colspan="1">1.62</td><td align="char" char="." rowspan="1" colspan="1">4.12</td><td align="char" char="." rowspan="1" colspan="1">4.06</td><td align="char" char="." rowspan="1" colspan="1">4.17</td><td align="char" char="." rowspan="1" colspan="1">3.25</td><td align="char" char="." rowspan="1" colspan="1">3.72</td><td align="char" char="." rowspan="1" colspan="1">96.4</td><td align="justify" rowspan="1" colspan="1">96.5</td><td align="char" char="." rowspan="1" colspan="1">98.5</td><td align="justify" rowspan="1" colspan="1">97.5</td><td align="char" char="." rowspan="1" colspan="1">97.8</td></tr><tr><td align="justify" rowspan="1" colspan="1">s.d.</td><td align="char" char="." rowspan="1" colspan="1">0.15</td><td align="char" char="." rowspan="1" colspan="1">0.26</td><td align="char" char="." rowspan="1" colspan="1">0.40</td><td align="char" char="." rowspan="1" colspan="1">0.46</td><td align="char" char="." rowspan="1" colspan="1">0.24</td><td align="char" char="." rowspan="1" colspan="1">0.38</td><td align="char" char="." rowspan="1" colspan="1">7.2</td><td align="justify" rowspan="1" colspan="1">7.7</td><td align="char" char="." rowspan="1" colspan="1">3.1</td><td align="justify" rowspan="1" colspan="1">11.5</td><td align="char" char="." rowspan="1" colspan="1">5.3</td></tr><tr><td align="justify" rowspan="1" colspan="1">Heritability</td><td align="char" char="." rowspan="1" colspan="1"><bold>0.53</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.51</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.68</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.59</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.7</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.39</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.71</bold></td><td align="justify" rowspan="1" colspan="1"><bold>0.78</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.66</bold></td><td align="justify" rowspan="1" colspan="1"><bold>0.85</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.71</bold></td></tr><tr><td align="justify" rowspan="1" colspan="1">CW mean</td><td align="char" char="." rowspan="1" colspan="1">1.10</td><td align="char" char="." rowspan="1" colspan="1">3.37</td><td align="char" char="." rowspan="1" colspan="1">3.53</td><td align="char" char="." rowspan="1" colspan="1">3.06</td><td align="char" char="." rowspan="1" colspan="1">2.49</td><td align="char" char="." rowspan="1" colspan="1">2.30</td><td align="char" char="." rowspan="1" colspan="1">78.9</td><td align="justify" rowspan="1" colspan="1">73.8</td><td align="char" char="." rowspan="1" colspan="1">91.3</td><td align="justify" rowspan="1" colspan="1">79</td><td align="char" char="." rowspan="1" colspan="1">86.7</td></tr><tr><td align="justify" rowspan="1" colspan="1">CW minimum</td><td align="char" char="." rowspan="1" colspan="1">0.56</td><td align="char" char="." rowspan="1" colspan="1">2.56</td><td align="char" char="." rowspan="1" colspan="1">2.54</td><td align="char" char="." rowspan="1" colspan="1">1.35</td><td align="char" char="." rowspan="1" colspan="1">1.58</td><td align="char" char="." rowspan="1" colspan="1">1.46</td><td align="char" char="." rowspan="1" colspan="1">48.2</td><td align="justify" rowspan="1" colspan="1">38.3</td><td align="char" char="." rowspan="1" colspan="1">76.7</td><td align="justify" rowspan="1" colspan="1">38.9</td><td align="char" char="." rowspan="1" colspan="1">53.2</td></tr><tr><td align="justify" rowspan="1" colspan="1">CW maximum</td><td align="char" char="." rowspan="1" colspan="1">1.58</td><td align="char" char="." rowspan="1" colspan="1">4.04</td><td align="char" char="." rowspan="1" colspan="1">4.40</td><td align="char" char="." rowspan="1" colspan="1">4.41</td><td align="char" char="." rowspan="1" colspan="1">3.52</td><td align="char" char="." rowspan="1" colspan="1">3.50</td><td align="char" char="." rowspan="1" colspan="1">96.2</td><td align="justify" rowspan="1" colspan="1">94.3</td><td align="char" char="." rowspan="1" colspan="1">97.9</td><td align="justify" rowspan="1" colspan="1">98.7</td><td align="char" char="." rowspan="1" colspan="1">98.2</td></tr><tr><td align="justify" rowspan="1" colspan="1">s.d.</td><td align="char" char="." rowspan="1" colspan="1">0.19</td><td align="char" char="." rowspan="1" colspan="1">0.28</td><td align="char" char="." rowspan="1" colspan="1">0.36</td><td align="char" char="." rowspan="1" colspan="1">0.51</td><td align="char" char="." rowspan="1" colspan="1">0.32</td><td align="char" char="." rowspan="1" colspan="1">0.36</td><td align="char" char="." rowspan="1" colspan="1">9.0</td><td align="justify" rowspan="1" colspan="1">11.1</td><td align="char" char="." rowspan="1" colspan="1">3.4</td><td align="justify" rowspan="1" colspan="1">11.6</td><td align="char" char="." rowspan="1" colspan="1">7.2</td></tr><tr><td align="justify" rowspan="1" colspan="1">Heritability</td><td align="char" char="." rowspan="1" colspan="1"><bold>0.71</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.76</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.86</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.59</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.82</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.65</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.83</bold></td><td align="justify" rowspan="1" colspan="1"><bold>0.82</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.76</bold></td><td align="justify" rowspan="1" colspan="1"><bold>0.85</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.78</bold></td></tr><tr><td align="justify" rowspan="1" colspan="1">FW mean</td><td align="char" char="." rowspan="1" colspan="1">1.07</td><td align="char" char="." rowspan="1" colspan="1">3.44</td><td align="char" char="." rowspan="1" colspan="1">3.13</td><td align="char" char="." rowspan="1" colspan="1">3.08</td><td align="char" char="." rowspan="1" colspan="1">2.45</td><td align="char" char="." rowspan="1" colspan="1">2.07</td><td align="char" char="." rowspan="1" colspan="1">83.7</td><td align="justify" rowspan="1" colspan="1">84.9</td><td align="char" char="." rowspan="1" colspan="1">89.4</td><td align="justify" rowspan="1" colspan="1">74.7</td><td align="char" char="." rowspan="1" colspan="1">90.9</td></tr><tr><td align="justify" rowspan="1" colspan="1">FW minimum</td><td align="char" char="." rowspan="1" colspan="1">0.25</td><td align="char" char="." rowspan="1" colspan="1">1.25</td><td align="char" char="." rowspan="1" colspan="1">0.50</td><td align="char" char="." rowspan="1" colspan="1">0.68</td><td align="char" char="." rowspan="1" colspan="1">0.58</td><td align="char" char="." rowspan="1" colspan="1">0.37</td><td align="char" char="." rowspan="1" colspan="1">65.3</td><td align="justify" rowspan="1" colspan="1">53.3</td><td align="char" char="." rowspan="1" colspan="1">60.6</td><td align="justify" rowspan="1" colspan="1">39.2</td><td align="char" char="." rowspan="1" colspan="1">71.9</td></tr><tr><td align="justify" rowspan="1" colspan="1">FW maximum</td><td align="char" char="." rowspan="1" colspan="1">1.56</td><td align="char" char="." rowspan="1" colspan="1">4.16</td><td align="char" char="." rowspan="1" colspan="1">4.25</td><td align="char" char="." rowspan="1" colspan="1">4.10</td><td align="char" char="." rowspan="1" colspan="1">3.28</td><td align="char" char="." rowspan="1" colspan="1">2.77</td><td align="char" char="." rowspan="1" colspan="1">96.7</td><td align="justify" rowspan="1" colspan="1">97.9</td><td align="char" char="." rowspan="1" colspan="1">98.0</td><td align="justify" rowspan="1" colspan="1">96.9</td><td align="char" char="." rowspan="1" colspan="1">98.9</td></tr><tr><td align="justify" rowspan="1" colspan="1">s.d.</td><td align="char" char="." rowspan="1" colspan="1">0.21</td><td align="char" char="." rowspan="1" colspan="1">0.36</td><td align="char" char="." rowspan="1" colspan="1">0.40</td><td align="char" char="." rowspan="1" colspan="1">0.39</td><td align="char" char="." rowspan="1" colspan="1">0.34</td><td align="char" char="." rowspan="1" colspan="1">0.29</td><td align="char" char="." rowspan="1" colspan="1">6.9</td><td align="justify" rowspan="1" colspan="1">7.9</td><td align="char" char="." rowspan="1" colspan="1">5.82</td><td align="justify" rowspan="1" colspan="1">12.6</td><td align="char" char="." rowspan="1" colspan="1">4.2</td></tr><tr><td align="justify" rowspan="1" colspan="1">Heritability</td><td align="char" char="." rowspan="1" colspan="1"><bold>0.74</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.75</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.77</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.65</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.57</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.67</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.64</bold></td><td align="justify" rowspan="1" colspan="1"><bold>0.87</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.65</bold></td><td align="justify" rowspan="1" colspan="1"><bold>0.79</bold></td><td align="char" char="." rowspan="1" colspan="1"><bold>0.81</bold></td></tr></tbody></table></alternatives><table-wrap-foot><fn id="t001fn001"><p>s.d. = standard deviation; <sup>a</sup>, <sup>b</sup> and <sup>c</sup> are the groups from LSD test; ns = not significant. MRC12 = Minnipa 2012, MRC13 = Minnipa 2013, RAC12 = Roseworthy 2012, RAC13 = Roseworthy 2013, SWH2 = Swan Hill 2012, SWH13 = Swan Hill 2013; CF = Commander x Fleet, CW = Commander x WI4304, FW = Fleet x WI4304.</p></fn></table-wrap-foot></table-wrap><p>Best Linear Unbiased Estimates (BLUEs) were generated using genotype fixed effects [<xref rid="pone.0178111.ref041" ref-type="bibr">41</xref>] for QTL and multi-environment analysis since BLUPs are inappropriately scaled by their individual environment heritability and variance estimates [<xref rid="pone.0178111.ref042" ref-type="bibr">42</xref>]. The inverse of the variance matrix of means from each environment was used to generate weights for use in the multi-environment analysis to account for variance heterogeneity. The best model for comparison of across environment covariation was selected based on Schwarz Information Criteria [<xref rid="pone.0178111.ref043" ref-type="bibr">43</xref>]. Genetic correlations among environments for yield were generated from the multi-environment model using the variance-covariance matrix of the selected best model [<xref rid="pone.0178111.ref042" ref-type="bibr">42</xref>]. Pearson’s correlation coefficients (r) were computed to assess the association of yield and grain plumpness with maturity as reported in [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>].</p></sec><sec id="sec005"><title>Genotyping and genetic maps</title><p>We used the genetic maps described in [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>] including 2,178 GBS markers and 7 phenology genes in CF, 2,892 GBS markers and 8 phenology genes in CW, and 2,252 GBS markers and 5 phenology genes in the FW population. The location of GBS markers on barley genome were obtained by BLASTN the tag sequences versus the IBSC barley RefSeq v1.0 of the map-based sequence of cultivar Morex (<ext-link ext-link-type="uri" xlink:href="http://webblast.ipk-gatersleben.de/registration/">http://webblast.ipk-gatersleben.de/registration/</ext-link>) [<xref rid="pone.0178111.ref044" ref-type="bibr">44</xref>, <xref rid="pone.0178111.ref045" ref-type="bibr">45</xref>] and are provided in <xref ref-type="supplementary-material" rid="pone.0178111.s007">S1 Table</xref>.</p><p>The mapped phenology genes were photoperiod response gene (<italic>Ppd-H1</italic>), vernalisation requirement gene (<italic>Vrn-H2</italic>), <italic>APETALA2</italic> (<italic>HvAP2</italic>), <italic>FLOWERING LOCUS T</italic> (<italic>HvFT5</italic>), <italic>TERMINAL FLOWER 1</italic> (<italic>HvTFL1</italic>), <italic>CONSTANS</italic> (<italic>HvCO1</italic>, <italic>HvCO2</italic>), <italic>GIGANTEA</italic> (<italic>HvGI</italic>), the red/far-red light phytochromes genes (<italic>HvPhyB</italic> and <italic>HvPhyC</italic>). The primers used for detecting presence/absence of <italic>Vrn-H2</italic> and for detecting SNP in <italic>HvCO2</italic> and <italic>Ppd-H1</italic> by high-resolution melting curve method were provided in supplementary file of [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>]. KASP assays of <italic>HvAP2</italic>, <italic>HvCO1</italic>, <italic>HvFT5</italic>, <italic>HvGI</italic>, <italic>HvPhyB</italic>, <italic>HvPhyC</italic> and <italic>HvTFL1</italic>, were provided by LGC genomics; the sequences are in supplemental file, <xref ref-type="supplementary-material" rid="pone.0178111.s006">S1 File</xref>. Polymorphism for all phenology genes among the three genetic populations are provided in <xref ref-type="supplementary-material" rid="pone.0178111.s008">S2 Table</xref>. The markers for <italic>Vrn-H1</italic>, <italic>HvFT1/Vrn-H3</italic>, <italic>HvFT2</italic>, <italic>HvFT3/Ppd-H2</italic> and <italic>HvFT4</italic> from LGC genomics were found monomorphic in the populations (data not shown).</p><p>The SNP marker P135A described in [<xref rid="pone.0178111.ref030" ref-type="bibr">30</xref>] for <italic>HvCEN</italic> was found to be monomorphic between the parental lines so we sequenced <italic>HvCEN</italic> in our material. The genomic sequence of <italic>HvCEN</italic> was retrieved from morex_contig_274284 identified by BLASTn analysis of JX648176 sequence from [<xref rid="pone.0178111.ref030" ref-type="bibr">30</xref>] versus the whole genome sequence assembly 3 of cv Morex [<xref rid="pone.0178111.ref044" ref-type="bibr">44</xref>]. Primers were designed to amplify 2,795 bp of <italic>HvCEN</italic> covering of the 5’ upstream region, exons, introns and the 3’ downstream region in Commander, Fleet and WI4304 (<xref ref-type="supplementary-material" rid="pone.0178111.s009">S3</xref> and <xref ref-type="supplementary-material" rid="pone.0178111.s010">S4</xref> Tables). The PCR fragments were sequenced using the BigDyeTM sequencing chemistry (Applied Biosystems, Perkin Elmer, Weiterstadt, Germany) followed by fluorescent Sanger capillary separation. Sanger sequences were trimmed and merged using the Pairwise Alignment tool of Geneious software (Biomatters Limited, Auckland, New Zealand) that uses the global alignment algorithm [<xref rid="pone.0178111.ref046" ref-type="bibr">46</xref>]. The <italic>HvCEN</italic> sequences were then aligned using Clustalw to identify polymorphism between parental lines. A total of 7 SNP were found between Commander or Fleet and WI4304 (<xref ref-type="supplementary-material" rid="pone.0178111.s001">S1 Fig</xref>). A KBioscience Competitive Allele-Specific Polymerase chain reaction (KASP) assay was designed using Kraken software to target the intron 3 SNP and named HvCEN_1780. CW and FW populations were genotyped using the KASP primers described in <xref ref-type="supplementary-material" rid="pone.0178111.s009">S3 Table</xref> and the protocol from LGC genomics (<ext-link ext-link-type="uri" xlink:href="http://www.lgcgroup.com/">http://www.lgcgroup.com/</ext-link>). HvCEN_1780 marker was added to the linkage maps using MSTmap for R [<xref rid="pone.0178111.ref047" ref-type="bibr">47</xref>] (<xref ref-type="supplementary-material" rid="pone.0178111.s002">S2 Fig</xref>).</p></sec><sec id="sec006"><title>QTL analysis</title><p>QTL analysis of yield and grain plumpness was performed using the generated BLUEs and the updated genetic linkage maps described above. The best variance-covariance model selected in the phenotypic analysis step was used for multi-environment QTL analysis. A genome wide scan to detect candidate QTL positions was performed using Simple Interval Mapping (SIM) [<xref rid="pone.0178111.ref048" ref-type="bibr">48</xref>] followed by Composite Interval Mapping (CIM) [<xref rid="pone.0178111.ref049" ref-type="bibr">49</xref>], in which the QTL detected by SIM were used as cofactors. A genome-wide significance level of α = 0.05 was used as a threshold to reject the null hypothesis of no QTL effect based on the method of [<xref rid="pone.0178111.ref050" ref-type="bibr">50</xref>].</p><p>Genetic predictors were estimated with a step size of 2 cM interval and the minimum distances for cofactor proximity and for declaring independent QTL were set to 30 cM and 20 cM, respectively. Repeated iterations of CIM were performed until no further change in the selected QTL was observed [<xref rid="pone.0178111.ref014" ref-type="bibr">14</xref>]. QTL main effects, QTL x Environment interaction effects, percent of phenotypic variance explained by the QTL (PVE) and the source of high value allele at each environment were determined for all significant QTL remaining in the final QTL model. Results were presented in <xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>, Tables <xref ref-type="table" rid="pone.0178111.t002">2</xref> and <xref ref-type="table" rid="pone.0178111.t003">3</xref>.</p><table-wrap id="pone.0178111.t002" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0178111.t002</object-id><label>Table 2</label><caption><title>Yield QTL in three doubled haploid populations of barley at six environments in southern Australia.</title></caption><alternatives><graphic id="pone.0178111.t002g" xlink:href="pone.0178111.t002"></graphic><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col></colgroup><thead><tr><th align="justify" rowspan="2" colspan="1">QTL</th><th align="justify" rowspan="2" colspan="1">Significant marker</th><th align="justify" rowspan="2" colspan="1">Chr.</th><th align="justify" rowspan="2" colspan="1">Position (cM)</th><th align="justify" rowspan="2" colspan="1">LOD</th><th align="justify" rowspan="2" colspan="1">QTL x E</th><th align="justify" rowspan="2" colspan="1">PVE (%)</th><th align="center" colspan="6" rowspan="1">QTL additive effects (t/ha)</th></tr><tr><th align="justify" rowspan="1" colspan="1">MRC12</th><th align="justify" rowspan="1" colspan="1">MRC13</th><th align="justify" rowspan="1" colspan="1">RAC12</th><th align="justify" rowspan="1" colspan="1">RAC13</th><th align="justify" rowspan="1" colspan="1">SWH12</th><th align="justify" rowspan="1" colspan="1">SWH13</th></tr></thead><tbody><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>CF-2H</italic></td><td align="justify" rowspan="1" colspan="1">TP10554</td><td align="justify" rowspan="1" colspan="1">2H</td><td align="char" char="." rowspan="1" colspan="1">105.9</td><td align="char" char="." rowspan="1" colspan="1">4.2</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">2.6–8.2</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.11<sup>C</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>C</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>CF-4H</italic></td><td align="justify" rowspan="1" colspan="1">TP15526</td><td align="justify" rowspan="1" colspan="1">4H</td><td align="char" char="." rowspan="1" colspan="1">67.1</td><td align="char" char="." rowspan="1" colspan="1">4.2</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">1.8–9.1</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.08<sup>C</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.05<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">0.05<sup>C</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>CF-6H</italic><xref ref-type="table-fn" rid="t002fn001">*</xref></td><td align="justify" rowspan="1" colspan="1">TP88355</td><td align="justify" rowspan="1" colspan="1">6H</td><td align="char" char="." rowspan="1" colspan="1">58.1</td><td align="char" char="." rowspan="1" colspan="1">14.7</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">6.1–25.0</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.23<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>CF-7H</italic><xref ref-type="table-fn" rid="t002fn001">*</xref></td><td align="justify" rowspan="1" colspan="1">TP81322</td><td align="justify" rowspan="1" colspan="1">7H</td><td align="char" char="." rowspan="1" colspan="1">50.2</td><td align="char" char="." rowspan="1" colspan="1">4.0</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">1.5–8.5</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">0.07<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">0.08<sup>C</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>CW-2H</italic>.<italic>1</italic></td><td align="justify" rowspan="1" colspan="1">TP23249</td><td align="justify" rowspan="1" colspan="1">2H</td><td align="char" char="." rowspan="1" colspan="1">84.2</td><td align="char" char="." rowspan="1" colspan="1">15.3</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">4.6–24.4</td><td align="char" char="." rowspan="1" colspan="1">0.04<sup>C</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.10<sup>C</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.16<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">0.08<sup>C</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>CW-2H</italic>.<italic>2</italic><xref ref-type="table-fn" rid="t002fn001">*</xref></td><td align="justify" rowspan="1" colspan="1">TP43335</td><td align="justify" rowspan="1" colspan="1">2H</td><td align="char" char="." rowspan="1" colspan="1">164.6</td><td align="char" char="." rowspan="1" colspan="1">6.9</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">4.2–9.6</td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>W</sup></td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>W</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>CW-5H</italic></td><td align="justify" rowspan="1" colspan="1">TP91995-TP83176 <xref ref-type="table-fn" rid="t002fn002"><sup>#</sup></xref></td><td align="justify" rowspan="1" colspan="1">5H</td><td align="char" char="." rowspan="1" colspan="1">173.9</td><td align="char" char="." rowspan="1" colspan="1">3.7</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">2.0–5.3</td><td align="char" char="." rowspan="1" colspan="1">0.04<sup>C</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.07<sup>W</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>CW-6H</italic>.<italic>1</italic></td><td align="justify" rowspan="1" colspan="1">TP24121</td><td align="justify" rowspan="1" colspan="1">6H</td><td align="char" char="." rowspan="1" colspan="1">62.7</td><td align="char" char="." rowspan="1" colspan="1">2.9</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">8.8</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.11<sup>W</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>CW-6H</italic>.<italic>2</italic></td><td align="justify" rowspan="1" colspan="1">TP77911</td><td align="justify" rowspan="1" colspan="1">6H</td><td align="char" char="." rowspan="1" colspan="1">83.0</td><td align="char" char="." rowspan="1" colspan="1">2.9</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">4.0–6.0</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>W</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.13<sup>W</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>CW-7H</italic><xref ref-type="table-fn" rid="t002fn001">*</xref></td><td align="justify" rowspan="1" colspan="1">TP41903- TP89783 <xref ref-type="table-fn" rid="t002fn002"><sup>#</sup></xref></td><td align="justify" rowspan="1" colspan="1">7H</td><td align="char" char="." rowspan="1" colspan="1">40.7</td><td align="char" char="." rowspan="1" colspan="1">4.2</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">2.7–6.0</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">0.09<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">0.08<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">0.07<sup>C</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>FW-1H</italic></td><td align="justify" rowspan="1" colspan="1">TP43397</td><td align="justify" rowspan="1" colspan="1">1H</td><td align="char" char="." rowspan="1" colspan="1">144.5</td><td align="char" char="." rowspan="1" colspan="1">4.8</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">4.9–5.5</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.08<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.07<sup>F</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>FW-2H</italic>.<italic>1</italic></td><td align="justify" rowspan="1" colspan="1">TP60114</td><td align="justify" rowspan="1" colspan="1">2H</td><td align="char" char="." rowspan="1" colspan="1">108.6</td><td align="char" char="." rowspan="1" colspan="1">6.0</td><td align="justify" rowspan="1" colspan="1">no</td><td align="justify" rowspan="1" colspan="1">2.6–9.3</td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>F</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>FW-2H</italic>.<italic>2</italic><xref ref-type="table-fn" rid="t002fn001">*</xref></td><td align="justify" rowspan="1" colspan="1">TP34123-TP7819 <xref ref-type="table-fn" rid="t002fn002"><sup>#</sup></xref></td><td align="justify" rowspan="1" colspan="1">2H</td><td align="char" char="." rowspan="1" colspan="1">131.8</td><td align="char" char="." rowspan="1" colspan="1">3.8</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">7.8</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.11<sup>W</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>FW-2H</italic>.<italic>3</italic></td><td align="justify" rowspan="1" colspan="1">TP78288-TP88727 <xref ref-type="table-fn" rid="t002fn002"><sup>#</sup></xref></td><td align="justify" rowspan="1" colspan="1">2H</td><td align="char" char="." rowspan="1" colspan="1">203.3</td><td align="char" char="." rowspan="1" colspan="1">7.7</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">2.2–4.0</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>W</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.07<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.05<sup>W</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>FW-4H</italic></td><td align="justify" rowspan="1" colspan="1">TP17370</td><td align="justify" rowspan="1" colspan="1">4H</td><td align="char" char="." rowspan="1" colspan="1">53.7</td><td align="char" char="." rowspan="1" colspan="1">5.3</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">1.2–5.1</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.09<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.03<sup>F</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>FW-5H</italic><xref ref-type="table-fn" rid="t002fn001">*</xref></td><td align="justify" rowspan="1" colspan="1">TP21942</td><td align="justify" rowspan="1" colspan="1">5H</td><td align="char" char="." rowspan="1" colspan="1">162.3</td><td align="char" char="." rowspan="1" colspan="1">3.5</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">4.8</td><td align="char" char="." rowspan="1" colspan="1">0.05<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>FW-6H</italic>.<italic>1</italic><xref ref-type="table-fn" rid="t002fn001">*</xref></td><td align="justify" rowspan="1" colspan="1">TP58326</td><td align="justify" rowspan="1" colspan="1">6H</td><td align="char" char="." rowspan="1" colspan="1">5.8</td><td align="char" char="." rowspan="1" colspan="1">5.3</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">2.4–7.7</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.08<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.06<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.08<sup>F</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QYld</italic>.<italic>FW-6H</italic>.<italic>2</italic><xref ref-type="table-fn" rid="t002fn001">*</xref></td><td align="justify" rowspan="1" colspan="1">TP35346-TP21790 <xref ref-type="table-fn" rid="t002fn002"><sup>#</sup></xref></td><td align="justify" rowspan="1" colspan="1">6H</td><td align="char" char="." rowspan="1" colspan="1">60.6</td><td align="char" char="." rowspan="1" colspan="1">9.1</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">10.3</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.11<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td></tr></tbody></table></alternatives><table-wrap-foot><fn id="t002fn001"><p>* QTL that don’t overlap with maturity QTL or phenology genes;</p></fn><fn id="t002fn002"><p><sup>#</sup> the QTL peak is between the indicated markers;</p></fn><fn id="t002fn003"><p>Chr. = chromosome; LOD = logarithm of the odds; QTL x E = QTL x environment interaction; PVE = percent of variance explained by the QTL; “-”: no significant QTL detected in that environment; the superscript letters represent the source of the high value allele (C = Commander, F = Fleet, W = WI4304).</p></fn></table-wrap-foot></table-wrap><table-wrap id="pone.0178111.t003" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0178111.t003</object-id><label>Table 3</label><caption><title>QTL for grain plumpness in three doubled haploid populations of barley at six environments in southern Australia.</title></caption><alternatives><graphic id="pone.0178111.t003g" xlink:href="pone.0178111.t003"></graphic><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col><col align="left" valign="middle" span="1"></col></colgroup><thead><tr><th align="justify" rowspan="2" colspan="1">QTL</th><th align="justify" rowspan="2" colspan="1">Significant marker</th><th align="justify" rowspan="2" colspan="1">Chr.</th><th align="justify" rowspan="2" colspan="1">Position (cM)</th><th align="justify" rowspan="2" colspan="1">LOD</th><th align="justify" rowspan="2" colspan="1">QTL x E</th><th align="justify" rowspan="2" colspan="1">PVE (%)</th><th align="center" colspan="5" rowspan="1">QTL additive effects (% >2.5 mm)</th></tr><tr><th align="justify" rowspan="1" colspan="1">MRC13</th><th align="justify" rowspan="1" colspan="1">RAC12</th><th align="justify" rowspan="1" colspan="1">RAC13</th><th align="justify" rowspan="1" colspan="1">SWH12</th><th align="justify" rowspan="1" colspan="1">SWH13</th></tr></thead><tbody><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>CF-4H</italic>.<italic>1*</italic></td><td align="justify" rowspan="1" colspan="1">TP4403</td><td align="justify" rowspan="1" colspan="1">4H</td><td align="char" char="." rowspan="1" colspan="1">59.5</td><td align="char" char="." rowspan="1" colspan="1">8.3</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">13.8</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">1.98<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>CF-4H</italic>.<italic>2</italic></td><td align="justify" rowspan="1" colspan="1">TP36187</td><td align="justify" rowspan="1" colspan="1">4H</td><td align="char" char="." rowspan="1" colspan="1">84.8</td><td align="char" char="." rowspan="1" colspan="1">4.8</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">5.7–9.8</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">1.27<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">2.41<sup>C</sup></td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>CF-6H*</italic></td><td align="justify" rowspan="1" colspan="1">TP14684</td><td align="justify" rowspan="1" colspan="1">6H</td><td align="char" char="." rowspan="1" colspan="1">58.4</td><td align="char" char="." rowspan="1" colspan="1">5.5</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">2.5–10.9</td><td align="char" char="." rowspan="1" colspan="1">1.14<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">2.24<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">1.76<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.54<sup>F</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>CF-7H*</italic></td><td align="justify" rowspan="1" colspan="1">TP5003</td><td align="justify" rowspan="1" colspan="1">7H</td><td align="char" char="." rowspan="1" colspan="1">160.0</td><td align="char" char="." rowspan="1" colspan="1">4.3</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">2.0–10.9</td><td align="char" char="." rowspan="1" colspan="1">1.47<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">2.55<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.76<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">2.53<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.63<sup>F</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>CW-1H*</italic></td><td align="justify" rowspan="1" colspan="1">TP45763-TP36876 <sup>#</sup></td><td align="justify" rowspan="1" colspan="1">1H</td><td align="char" char="." rowspan="1" colspan="1">39.6</td><td align="char" char="." rowspan="1" colspan="1">4.1</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">3.1–8.4</td><td align="char" char="." rowspan="1" colspan="1">2.62<sup>C</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">1.67<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">2.23<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">0.60<sup>C</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>CW-2H</italic>.<italic>1*</italic></td><td align="justify" rowspan="1" colspan="1">TP59292</td><td align="justify" rowspan="1" colspan="1">2H</td><td align="char" char="." rowspan="1" colspan="1">69.8</td><td align="char" char="." rowspan="1" colspan="1">14.2</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">3.0–8.2</td><td align="char" char="." rowspan="1" colspan="1">1.82<sup>W</sup></td><td align="char" char="." rowspan="1" colspan="1">2.11<sup>W</sup></td><td align="char" char="." rowspan="1" colspan="1">2.05<sup>W</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.60<sup>C</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>CW-2H</italic>.<italic>2*</italic></td><td align="justify" rowspan="1" colspan="1">TP6704</td><td align="justify" rowspan="1" colspan="1">2H</td><td align="char" char="." rowspan="1" colspan="1">163.4</td><td align="char" char="." rowspan="1" colspan="1">5.3</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">3.1–8.2</td><td align="char" char="." rowspan="1" colspan="1">2.58<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">2.76<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">2.06<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">2.65<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">0.60<sup>C</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>CW-2H</italic>.<italic>3*</italic></td><td align="justify" rowspan="1" colspan="1">TP82493-TP81950 <sup>#</sup></td><td align="justify" rowspan="1" colspan="1">2H</td><td align="char" char="." rowspan="1" colspan="1">209.8</td><td align="char" char="." rowspan="1" colspan="1">4.2</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">7.4</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">3.02<sup>W</sup></td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>CW-3H</italic></td><td align="justify" rowspan="1" colspan="1">TP62354-TP5718 <sup>#</sup></td><td align="justify" rowspan="1" colspan="1">3H</td><td align="char" char="." rowspan="1" colspan="1">63.1</td><td align="char" char="." rowspan="1" colspan="1">5.0</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">1.6–9.8</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.91<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">3.48<sup>C</sup></td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>CW-5H*</italic></td><td align="justify" rowspan="1" colspan="1">TP58162</td><td align="justify" rowspan="1" colspan="1">5H</td><td align="char" char="." rowspan="1" colspan="1">54.5</td><td align="char" char="." rowspan="1" colspan="1">2.8</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">2.2–6.8</td><td align="char" char="." rowspan="1" colspan="1">2.35<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">1.72<sup>C</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>CW-7H*</italic></td><td align="justify" rowspan="1" colspan="1">TP19872</td><td align="justify" rowspan="1" colspan="1">7H</td><td align="char" char="." rowspan="1" colspan="1">112.5</td><td align="char" char="." rowspan="1" colspan="1">2.5</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">1.8–3.5</td><td align="char" char="." rowspan="1" colspan="1">1.20<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">2.19<sup>C</sup></td><td align="char" char="." rowspan="1" colspan="1">1.20<sup>C</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>FW-1H*</italic></td><td align="justify" rowspan="1" colspan="1">TP92334-TP12227 <sup>#</sup></td><td align="justify" rowspan="1" colspan="1">1H</td><td align="char" char="." rowspan="1" colspan="1">194.0</td><td align="char" char="." rowspan="1" colspan="1">4.1</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">1.5–7.5</td><td align="char" char="." rowspan="1" colspan="1">1.03<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">1.83<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">0.95<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">1.60<sup>F</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>FW-2H*</italic></td><td align="justify" rowspan="1" colspan="1">TP97701-TP46704 <sup>#</sup></td><td align="justify" rowspan="1" colspan="1">2H</td><td align="char" char="." rowspan="1" colspan="1">177.3</td><td align="char" char="." rowspan="1" colspan="1">11.1</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">7.0–10.8</td><td align="char" char="." rowspan="1" colspan="1">2.28<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="char" char="." rowspan="1" colspan="1">1.19<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">2.08<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">1.81<sup>F</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>1</italic></td><td align="justify" rowspan="1" colspan="1">TP12552</td><td align="justify" rowspan="1" colspan="1">4H</td><td align="char" char="." rowspan="1" colspan="1">62.7</td><td align="char" char="." rowspan="1" colspan="1">3.1</td><td align="justify" rowspan="1" colspan="1">no</td><td align="justify" rowspan="1" colspan="1">0.3–2.8</td><td align="char" char="." rowspan="1" colspan="1">0.70<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.70<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.70<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.70<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.70<sup>F</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>2*</italic></td><td align="justify" rowspan="1" colspan="1">TP91307</td><td align="justify" rowspan="1" colspan="1">4H</td><td align="char" char="." rowspan="1" colspan="1">130.5</td><td align="char" char="." rowspan="1" colspan="1">10.8</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">2.2–13.7</td><td align="char" char="." rowspan="1" colspan="1">1.28<sup>W</sup></td><td align="char" char="." rowspan="1" colspan="1">3.48<sup>W</sup></td><td align="char" char="." rowspan="1" colspan="1">0.62<sup>W</sup></td><td align="char" char="." rowspan="1" colspan="1">2.58<sup>W</sup></td><td align="char" char="." rowspan="1" colspan="1">2.15<sup>W</sup></td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>FW-5H</italic>.<italic>1*</italic></td><td align="justify" rowspan="1" colspan="1">TP22989</td><td align="justify" rowspan="1" colspan="1">5H</td><td align="char" char="." rowspan="1" colspan="1">82.8</td><td align="char" char="." rowspan="1" colspan="1">4.4</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">3.5–5.7</td><td align="char" char="." rowspan="1" colspan="1">1.65<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">2.35<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.92<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td><td align="center" rowspan="1" colspan="1">-</td></tr><tr><td align="justify" rowspan="1" colspan="1"><italic>QPlum</italic>.<italic>FW-5H</italic>.<italic>2*</italic></td><td align="justify" rowspan="1" colspan="1">TP49510</td><td align="justify" rowspan="1" colspan="1">5H</td><td align="char" char="." rowspan="1" colspan="1">196.9</td><td align="char" char="." rowspan="1" colspan="1">5.9</td><td align="justify" rowspan="1" colspan="1">yes</td><td align="justify" rowspan="1" colspan="1">1.9–7.4</td><td align="char" char="." rowspan="1" colspan="1">1.69<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">1.76<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">0.88<sup>F</sup></td><td align="char" char="." rowspan="1" colspan="1">2.15<sup>F</sup></td><td align="center" rowspan="1" colspan="1">-</td></tr></tbody></table></alternatives><table-wrap-foot><fn id="t003fn001"><p>* QTL that don’t overlap with maturity QTL or phenology genes;</p></fn><fn id="t003fn002"><p><sup>#</sup> the QTL peak is between the indicated markers;</p></fn><fn id="t003fn003"><p>Chr. = chromosome; LOD = logarithm of the odds; QTL x E = QTL x environment interaction; PVE = percentage of variance explained by the QTL; “-” = no significant QTL detected in that environment; the superscript letters represent the source of the high value allele (C = Commander, F = Fleet, W = WI4304).</p></fn></table-wrap-foot></table-wrap><fig id="pone.0178111.g001" orientation="portrait" position="float"><object-id pub-id-type="doi">10.1371/journal.pone.0178111.g001</object-id><label>Fig 1</label><caption><title>Yield, grain plumpness and maturity QTL positions in the CF, CW and FW populations.</title><p>* = closest marker to the QTL peak. ** = markers flanking a QTL peak. Known phenology genes outside of QTL intervals are shown with pink colour, while those co-located with QTL are shown in blue.</p></caption><graphic xlink:href="pone.0178111.g001"></graphic></fig><p>An alternative QTL analysis using grain yield means adjusted for maturity was performed to detect yield QTL independent of the maturity effect. Adjustment for maturity was done by covariance analysis using the spatially adjusted BLUEs as a variate and the Zadok’s score as a covariate. Results were presented in Supplemental <xref ref-type="supplementary-material" rid="pone.0178111.s013">S7 Table</xref>.</p></sec></sec><sec sec-type="results" id="sec007"><title>Results</title><sec id="sec008"><title>Variations in grain yield and grain plumpness</title><p>Highly significant (P<0.001) yield differences were observed between the parents of the DH lines in five environments (MRC12, MRC13, RAC13, SWH12 and SWH13), while it was not significant in RAC12 (<xref ref-type="table" rid="pone.0178111.t001">Table 1</xref>). Commander and Fleet yielded equally and more than WI4304 except at RAC13 where WI4304 yield was higher (<xref ref-type="table" rid="pone.0178111.t001">Table 1</xref>). The DH lines showed transgressive segregation for yield in all the three populations (<xref ref-type="table" rid="pone.0178111.t001">Table 1</xref> and <xref ref-type="supplementary-material" rid="pone.0178111.s003">S3</xref>, <xref ref-type="supplementary-material" rid="pone.0178111.s004">S4</xref> and <xref ref-type="supplementary-material" rid="pone.0178111.s005">S5</xref> Figs). The heritability for yield ranged from 0.39 to 0.86.</p><p>MRC12 was the lowest yielding environment with the mean yield of 1.26 t/ha in the CF population, 1.00 t/ha in the CW population, and 1.07 t/ha in the FW population. MRC13 was the highest yielding environment for the CF and FW populations, the mean yields of both populations being 3.44 t/ha. RAC12 was the highest yielding environment for the CW population with a mean yield of 3.53 t/ha (<xref ref-type="table" rid="pone.0178111.t001">Table 1</xref>). The genetic correlations among environments for grain yield were positive for all populations and range from a weak correlation between RAC13 and SWH13 in the CF population (r = 0.14) to a moderate correlation between RAC12 and SWH12 in the FW population (r = 0.73) (<xref ref-type="supplementary-material" rid="pone.0178111.s011">S5 Table</xref>).</p><p>Highly significant differences (P<0.001) were observed among the parental genotypes for grain plumpness in all environments except in RAC12 (<xref ref-type="table" rid="pone.0178111.t001">Table 1</xref>). Fleet had higher grain plumpness than Commander and WI4304 in all environments. Commander had more plump grains than WI4304 in MRC13 and SWH12, while the inverse was true in RAC13, and they were equivalent in SWA13 (<xref ref-type="table" rid="pone.0178111.t001">Table 1</xref>). The DH lines in each population showed moderate to high heritability and a wide range of variation for grain plumpness (<xref ref-type="table" rid="pone.0178111.t001">Table 1</xref>).</p></sec><sec id="sec009"><title>Yield QTL</title><p>Eighteen QTL were detected for yield across the three populations. All QTL except one on chromosome 2H had significant QTL x environment interactions (<xref ref-type="table" rid="pone.0178111.t002">Table 2</xref>). Yield QTL common between two populations were found on chromosomes 2H and 7H (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>), while a yield QTL on 6H (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>) was detected in all the three populations.</p><p>Four QTL were detected in the CF population on chromosomes 2H, 4H, 6H and 7H. Commander contributed the higher value allele for all these QTL except <italic>QYld</italic>.<italic>CF-6H</italic> where the allele was contributed by Fleet. <italic>QYld</italic>.<italic>CF-2H</italic> and <italic>QYld</italic>.<italic>CF-6H</italic> were expressed in two sites while <italic>QYld</italic>.<italic>CF-4H</italic> and <italic>QYld</italic>.<italic>CF-7H</italic> were expressed at three environments, all showing QTL x environment interaction. The QTL <italic>QYld</italic>.<italic>CF-6H</italic>, with the significant marker at the peak LOD score being TP88355, explained 25% and 6.1% of the total phenotypic variance for yield in RAC13 and MRC13, respectively (<xref ref-type="table" rid="pone.0178111.t002">Table 2</xref>). In terms of the actual allele effect on phenotypic value, the Fleet allele increased yield by 3.5% and 16.6%, respectively at MRC13 and RAC13.</p><p>Six QTL were detected in the CW population on 2H, 5H, 6H and 7H. Commander contributed the high value allele for <italic>QYld</italic>.<italic>CW-2H</italic>.<italic>1</italic> and <italic>QYld</italic>.<italic>CW-7H</italic> while WI4304 was the high value allele for <italic>QYld</italic>.<italic>CW-2H</italic>.<italic>2</italic>, <italic>QYld</italic>.<italic>CW-6H</italic>.<italic>1</italic> and <italic>QYld</italic>.<italic>CW-6H</italic>.<italic>2</italic>. The QTL <italic>QYld</italic>.<italic>CW-5H</italic> was co-located with the phenology gene <italic>HvPhyC</italic> (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>). <italic>QYld</italic>.<italic>CW-2H</italic>.1 had the highest LOD score of 15.3 and was expressed in four environments (MRC12, RAC12, SWH12 and SWH13) explaining from 4.6% to 24.4% of the phenotypic variance for yield. The QTL on 7H, <italic>QYld</italic>.<italic>CW-7H</italic>, was expressed in five of the six environments with 2.7% to 6.0% of explained phenotypic variance (<xref ref-type="table" rid="pone.0178111.t002">Table 2</xref>).</p><p>Eight QTL were detected in the FW population on chromosomes 1H, 2H, 4H, 5H and 6H. The high value alleles for five of these QTL (<italic>QYld</italic>.<italic>FW-2H</italic>.<italic>1</italic>, <italic>QYld</italic>.<italic>FW-4H</italic>, <italic>QYld</italic>.<italic>FW-5H</italic>, <italic>QYld</italic>.<italic>FW-6H</italic>.<italic>1</italic> and <italic>QYld</italic>.<italic>FW-6H</italic>.<italic>2</italic>) were from Fleet while WI4304 contributed the higher value allele for <italic>QYld</italic>.<italic>FW-2H</italic>.<italic>2</italic>. Both Fleet and WI4304 contributed the higher value alleles for <italic>QYld</italic>.<italic>FW-1H</italic> and <italic>QYld</italic>.<italic>FW-2H</italic>.<italic>3</italic> at different environments. The QTL <italic>QYld</italic>.<italic>FW-2H</italic>.<italic>1</italic> at 108.6 cM on 2H, with a LOD score of 6.0, was expressed in all the six environments with no QTL x environment interaction and explained between 2.6% to 9.3% of the total phenotypic variation for yield.</p></sec><sec id="sec010"><title>Grain plumpness QTL</title><p>Seventeen QTL were detected for grain plumpness across the three populations: four QTL in CF, seven QTL in CW and six QTL in FW (<xref ref-type="table" rid="pone.0178111.t003">Table 3</xref> and <xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>). All QTL except one on 4H in the FW showed significant QTL x environment interaction (<xref ref-type="table" rid="pone.0178111.t003">Table 3</xref>).</p><p>Two QTL (<italic>QPlum</italic>.<italic>CF-4H</italic>.<italic>1</italic> and <italic>QPlum</italic>.<italic>CF-4H</italic>.<italic>2</italic>) were detected at 59.5 and 84.8 cM on 4H in CF population. <italic>QPlum</italic>.<italic>CF-4H</italic>.<italic>1</italic> was detected only at RAC13 with the higher value allele from Fleet explaining 13.8% of the phenotypic variance for grain plumpness. <italic>QPlum</italic>.<italic>CF-4H</italic>.<italic>2</italic> was detected at RAC13 and SWH12 with the higher value allele from Commander explaining 5.7% and 9.8% of phenotypic variance, respectively. <italic>QPlum</italic>.<italic>CF-6H</italic> at 58.4 cM was detected in all environments except SWH12 with the higher value allele from Fleet and explaining from 2.5% to 10.9% of the phenotypic variance. <italic>QPlum</italic>.<italic>CF-7H</italic> was detected in all environments with the higher value allele from Fleet increasing the percentage of plump grains by 0.76 to 2.55% (<xref ref-type="table" rid="pone.0178111.t003">Table 3</xref>).</p><p>Grain plumpness QTL in the CW population were detected on chromosomes 1H, 2H, 3H, 5H and 7H. <italic>QPlum</italic>.<italic>CW-1H</italic> was detected in all environments except in RAC12 with the higher value allele from Commander explaining 3.1% to 8.4% of the phenotypic variance. Three QTL on 2H (<italic>QPlum</italic>.<italic>CW-2H</italic>.<italic>1</italic>, <italic>QPlum</italic>.<italic>CW-2H</italic>.<italic>2</italic> and <italic>QPlum</italic>.<italic>CW-2H</italic>.<italic>3</italic>) were detected at 69.8 cM, 163.4 cM and 209.8 cM, respectively, and explained from 3.0% to 8.2% of the phenotypic variance (<xref ref-type="table" rid="pone.0178111.t003">Table 3</xref>). Commander contributed the higher value alleles for <italic>QPlum</italic>.<italic>CW-2H</italic>.<italic>1</italic> and <italic>QPlum</italic>.<italic>CW-2H</italic>.<italic>3</italic>, while WI4304 contributed higher value allele for <italic>QPlum</italic>.<italic>CW-2H</italic>.<italic>2</italic> (<xref ref-type="table" rid="pone.0178111.t003">Table 3</xref>). <italic>QPlum</italic>.<italic>CW-3H</italic> explained 1.6% and 9.8% of phenotypic variance at RAC13 and SWH12, respectively. <italic>QPlum</italic>.<italic>CW-5H</italic> was detected in MRC13 and RAC12, explaining 2.2% and 6.8% of phenotypic variance, respectively. <italic>QPlum</italic>.<italic>CW-7H</italic> was detected in MRC13, RAC12 and RAC13, explaining 1.8% to 3.5% of the phenotypic variance. The higher value allele for <italic>QPlum</italic>.<italic>CW-3H</italic>, <italic>QPlum</italic>.<italic>CW-5H</italic>, and <italic>QPlum</italic>.<italic>CW-7H</italic> was contributed by Commander (<xref ref-type="table" rid="pone.0178111.t003">Table 3</xref>).</p><p>QTL for grain plumpness in the FW population were detected on chromosomes 1H, 2H, 4H, and 5H, explaining from 3.1% (<italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>1</italic>) to 11.1% (<italic>QPlum</italic>.<italic>FW-2H</italic>) of the phenotypic variance. <italic>QPlum</italic>.<italic>FW-1H</italic>, <italic>QPlum</italic>.<italic>FW-2H</italic>, and <italic>QPlum</italic>.<italic>FW-5H</italic>.<italic>2</italic> were detected in four environments while <italic>QPlum</italic>.<italic>FW-5H</italic>.<italic>1</italic> was detected in three environments. <italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>1</italic> and <italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>2</italic> were detected in all five environments. <italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>1</italic> had the same additive effect across the five environments with no QTL x Environment interaction. Fleet contributed the high value allele for all QTL detected in the FW population except <italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>2</italic> (<xref ref-type="table" rid="pone.0178111.t003">Table 3</xref>).</p></sec><sec id="sec011"><title>Maturity effect on yield QTL</title><p>To evaluate the maturity effect on yield in these populations, we used the maturity data collected on the same trials [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>]. Significant correlations between yield and maturity were observed in some trials (<xref ref-type="supplementary-material" rid="pone.0178111.s012">S6 Table</xref>). Two methods were used to evaluate the independency of yield QTL toward maturity: (i) by adjusting the yield data for maturity and comparing the QTL results, and (ii) by co-mapping the QTL for maturity and those for yield or grain plumpness.</p><p>The first method used a covariance analysis to adjust the yield QTL for maturity effect. The covariance analysis did not significantly change the QTL as shown in <xref ref-type="supplementary-material" rid="pone.0178111.s013">S7 Table</xref>. Minor changes due to the adjustment QTL included a slight shift in QTL position and the number of environments where a QTL was detected. For example, in the CF population, <italic>QYld</italic>.<italic>CF-4H</italic> was detected in one more environment, while <italic>QYld</italic>.<italic>CF-6H</italic> was detected in two more environments after correction for maturity (<xref ref-type="supplementary-material" rid="pone.0178111.s013">S7 Table</xref>). In the FW population, one more QTL on 6H (<italic>QYld</italic>.<italic>FW-6H</italic>.<italic>3</italic>) was detected after correction for maturity effect (<xref ref-type="supplementary-material" rid="pone.0178111.s013">S7 Table</xref>). An important change was the disappearance of the QTL on 5H, <italic>QYld</italic>.<italic>CW-5H</italic> after the adjustment showing its dependency toward maturity. This QTL is also collocated with <italic>HvPhyC</italic> gene which is known to control the phytochrome pathway [<xref rid="pone.0178111.ref034" ref-type="bibr">34</xref>].</p><p>The second method consisted in co-mapping the QTL for yield and grain plumpness with the maturity QTL of the same barley populations [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>] (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>). Among 18 yield QTL, six loci were collocated with maturity QTL on chromosomes 1H, 2H, 4H, 5H and 6H. Four yield QTL were collocated with phenology genes, <italic>HvCEN</italic> on chromosome 2H, <italic>HvPhyB</italic> on chromosome 4H, <italic>HvPhyC</italic> on chromosome 5H and <italic>HvCO2</italic> on chromosome 6H. Among 17 QTL for grain plumpness, one QTL, <italic>QPlum</italic>.<italic>CF-4H</italic>.<italic>2</italic>, was collocated with a QTL for maturity (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>). Two other QTL were collocated with phenology genes: <italic>QPlum</italic>.<italic>CW-3H</italic> with <italic>HvGI</italic> gene, and <italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>1</italic> with <italic>HvPhyB</italic> gene (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>). In total, 8 yield QTL and 14 QTL for grain plumpness were independent on phenology (those are marked with * in Tables <xref ref-type="table" rid="pone.0178111.t002">2</xref> and <xref ref-type="table" rid="pone.0178111.t003">3</xref>).</p></sec></sec><sec sec-type="conclusions" id="sec012"><title>Discussion</title><sec id="sec013"><title>Environment effects on yield and grain plumpness</title><p>The parents of the three populations were selected based on their long-term yield performance in southern Australia. Commander and Fleet had stable yields across a range of environments, while WI4304 had low yields in drought-affected environments. In this study, Commander and Fleet had similar yields, significantly higher than WI4304 except for RAC13 where the rankings were reversed (<xref ref-type="table" rid="pone.0178111.t001">Table 1</xref>). The environments showed substantial variation for yield, which was attributed mainly to the rainfall patterns (amount and distribution), and other climatic and edaphic factors [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>]. The wide variation observed in yield and grain plumpness in all of the three populations was expected for such quantitative traits due to transgressive segregation. Except one QTL for grain plumpness (<italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>1</italic>) and one QTL for yield (<italic>QYld</italic>.<italic>FW-2H</italic>.<italic>1</italic>), which were consistent across environments, all QTL for the two traits had significant QTL x environment interactions. One QTL on chromosome 2H in CW, and one QTL on chromosome 6H in the CF population had the strongest effects, though their effects were environment specific.</p></sec><sec id="sec014"><title>QTL independent on maturity or phenology genes</title><p>Unlike previous yield QTL studies in barley (see <xref ref-type="sec" rid="sec001">Introduction</xref>), none of the major developmental genes, including <italic>Ppd-H1</italic>, <italic>Vrn-H1</italic> and <italic>Vrn-H2</italic>, that drive barley adaptation significantly affected grain plumpness and yield in this study. This could be due to the nature of the populations, which were derived from elite x elite crosses to discover QTL that could be deployed in breeding programs targeting Mediterranean type environments. The lack of significant effect on yield QTL after correction for maturity is also consistent with the nature of the populations.</p><p>Twenty-two QTL controlling yield or grain plumpness were phenology independent (see * in Tables <xref ref-type="table" rid="pone.0178111.t002">2</xref> and <xref ref-type="table" rid="pone.0178111.t003">3</xref>). Those were not affected by maturity adjustment of yield data, and not collocated with maturity QTL or phenology genes. Some of these QTL may correspond to QTL described in other populations. <italic>QPlum</italic>.<italic>FW-1H</italic>, located towards the telomere of 1HL, was in a similar position in the Galleon x Haruna Nijo barley population [<xref rid="pone.0178111.ref051" ref-type="bibr">51</xref>]. <italic>QPlum</italic>.<italic>CW-1H</italic>, which is on a different region to <italic>QPlum</italic>.<italic>FW-1H</italic>, is around the end of chromosome 1HS where grain plumpness QTL in Blenheim x E224/3, Harrington x Morex, and Chebec x Harrington populations were mapped [<xref rid="pone.0178111.ref006" ref-type="bibr">6</xref>]. The location of the other grain plumpness QTL on chromosome 2H in CW (<italic>QPlum</italic>.<italic>CW-2H</italic>.<italic>3</italic>) seems to coincide with the screenings QTL reported in the Sloop x Alexis population, and thousand grain weight QTL found in the Blenheim x E224/3 population [<xref rid="pone.0178111.ref006" ref-type="bibr">6</xref>]. The grain plumpness QTL detected in CW and FW populations on 5H seems to be at a similar position to the QTL for grain plumpness and screenings in the Chebec x Harrington population [<xref rid="pone.0178111.ref052" ref-type="bibr">52</xref>]. Some QTL were not reported in other populations and are new, such as <italic>QYld</italic>.<italic>CF-2H</italic>, <italic>QYld</italic>.<italic>FW-5H</italic>, <italic>QPlum</italic>.<italic>CW-2H</italic>.<italic>1</italic>.</p><p>The two yield QTL detected on chromosome 7H (<italic>QYld</italic>.<italic>CF-7H</italic> and <italic>QYld</italic>.<italic>CW-7H</italic>) have common markers (TP51566 and TP97439) on the genetic map (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>), though they are clearly separated on the barley cv Morex RefSeq v1.0 map (<xref ref-type="supplementary-material" rid="pone.0178111.s007">S1 Table</xref>). Other studies have reported yield QTL in the same genomic region [<xref rid="pone.0178111.ref023" ref-type="bibr">23</xref>, <xref rid="pone.0178111.ref053" ref-type="bibr">53</xref>]. Although these two QTL were located around the <italic>Vrn-H3</italic> locus, where [<xref rid="pone.0178111.ref021" ref-type="bibr">21</xref>] have also reported QTL for yield and flowering date, Vrn-H3 marker was monomorphic in our populations and cannot explain the yield QTL.</p></sec><sec id="sec015"><title>Yield and grain plumpness QTL related to maturity</title><p>By comparing the QTL for yield and grain plumpness with maturity QTL previously found in these populations [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>], we found ten QTL for yield and three QTL for grain plumpness that co-located to maturity QTL and sometimes with known phenology genes suggesting some pleiotropic effects for six regions of the genome:</p><p>The yield QTL <italic>QYld</italic>.<italic>FW-1H</italic> on chromosome 1H co-located with the maturity QTL <italic>QMat</italic>.<italic>FW-1H</italic> in the FW population. Two regions on chromosome 2H, <italic>QYld</italic>.<italic>CF-2H and QYld</italic>.<italic>FW-2H</italic>.<italic>3</italic>, also match maturity QTL in CF and FW populations [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>]. These regions are 50 Mbp apart on the barley reference genome sequence RefSeq v1.0 (<xref ref-type="supplementary-material" rid="pone.0178111.s007">S1 Table</xref>).</p><p>The peak markers for the yield QTL, <italic>QYld</italic>.<italic>FW-4H</italic> (TP17370), the grain plumpness QTL, <italic>QPlum</italic>.<italic>CF-4H</italic>.<italic>1</italic> (TP4403) and <italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>1</italic> (TP12552) on chromosome 4H are located close to each other on the barley RefSeq v1.0 (<xref ref-type="supplementary-material" rid="pone.0178111.s007">S1 Table</xref>). These markers are also co-located with TP89118 flanking the maturity QTL <italic>QMat</italic>.<italic>CW-4H</italic> reported in [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>]. This suggests this QTL might have pleiotropic effects on yield, grain plumpness and maturity. QTL for plant height, thousand-grain weight, spikes per square metre, and spike morphology were reported around the same genomic region in the Nure x Tremois population [<xref rid="pone.0178111.ref020" ref-type="bibr">20</xref>].</p><p>The yield QTL, <italic>QYld</italic>.<italic>CW-5H</italic>, on chromosome 5 disappeared after adjustment for maturity effects (<xref ref-type="supplementary-material" rid="pone.0178111.s013">S7 Table</xref>). This QTL co-locates with the maturity QTL (<italic>QMat</italic>.<italic>CW-5H</italic>) and leaf waxiness QTL (<italic>QLwax</italic>.<italic>CW-5H</italic>) [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>], and aligned on the barley RefSeq v1.0 map with the maturity QTL (<italic>QMat</italic>.<italic>CF-5H</italic>.<italic>2</italic>) in the CF population (<xref ref-type="supplementary-material" rid="pone.0178111.s007">S1 Table</xref>). In a previous study, different QTL that control reproductive development stages from awn primordia formation to anther extrusion, were mapped to this region [<xref rid="pone.0178111.ref054" ref-type="bibr">54</xref>]. Thus, it appears that this yield QTL is related to a direct effect of maturity. <italic>QYld</italic>.<italic>CW-5H</italic> is closely linked to <italic>HvPhyC</italic> locus (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>), which has a role in promoting long day flowering in barley [<xref rid="pone.0178111.ref055" ref-type="bibr">55</xref>].</p><p>On chromosome 6H, Fleet allele increased yield at <italic>QYld</italic>.<italic>CF-6H</italic> in population CF and <italic>QYld</italic>.<italic>FW-6H</italic>.<italic>2</italic> in population FW. Although these QTL don’t overlap with a maturity QTL in these populations, they shared common markers with <italic>QYld</italic>.<italic>CW-6H</italic>.<italic>1</italic> and a maturity QTL (<italic>QMat</italic>.<italic>CW-6H</italic>) in population CW (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>). Adjustment for maturity effects in the QTL analysis increased the PVE from 10.3% to 18.9% for the <italic>QYld</italic>.<italic>FW-6H</italic>.<italic>2</italic> showing a small maturity effect on this yield QTL. Further studies would be necessary to confirm that these QTL are due to the same gene in the three populations.</p></sec><sec id="sec016"><title>QTL co-located with phenology genes without affecting maturity</title><p>We identified some QTL for yield or grain plumpness that are co-located with phenology genes but not with a maturity QTL in these populations [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>] (<xref ref-type="supplementary-material" rid="pone.0178111.s007">S1 Table</xref>). Either these phenology genes affect inflorescence development with an impact on yield or grain plumpness without changing the flowering time, or there is an alternate responsible gene near the phenology gene. Such examples were found on chromosomes 2H, 3H and 4H. On chromosome 3H, <italic>QPlum</italic>.<italic>CW-3H</italic> co-located with <italic>HvGI</italic>, the barley homologue of an Arabidopsis photoperiod pathway gene [<xref rid="pone.0178111.ref033" ref-type="bibr">33</xref>]. <italic>QPlum</italic>.<italic>FW-4H</italic>.<italic>1</italic> was collocated with <italic>HvPhyB</italic> gene that control flowering time via the red/far-red light <italic>PHYTOCHROMES</italic> pathway.</p><p>We examined the colocation between <italic>HvCEN</italic> gene and the yield QTL <italic>QYld</italic>.<italic>CW-2H</italic>.<italic>1</italic> and <italic>QYld</italic>.<italic>FW-2H</italic>.<italic>1</italic> on chromosome 2H (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>). These two QTL are at the same position on chromosome 2H (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>, <xref ref-type="supplementary-material" rid="pone.0178111.s010">S4 Table</xref>) and distinct from <italic>QYld</italic>.<italic>CF-2H</italic> (<xref ref-type="fig" rid="pone.0178111.g001">Fig 1</xref>). The absence of this QTL in the CF population suggests a common haplotype between Commander and Fleet, with both parents contributing the high yield allele in the CW and FW populations where the QTL was detected. <italic>HvCEN</italic> is the gene for <italic>EPS2</italic> [<xref rid="pone.0178111.ref030" ref-type="bibr">30</xref>], which influences flowering time independently of vernalization and photoperiod [<xref rid="pone.0178111.ref026" ref-type="bibr">26</xref>]. <italic>HvCEN</italic> is associated with a phenology QTL and coincides with yield and grain size QTL [<xref rid="pone.0178111.ref006" ref-type="bibr">6</xref>, <xref rid="pone.0178111.ref014" ref-type="bibr">14</xref>, <xref rid="pone.0178111.ref020" ref-type="bibr">20</xref>, <xref rid="pone.0178111.ref023" ref-type="bibr">23</xref>]. <italic>QYld</italic>.<italic>CW-2H</italic>.<italic>1</italic> and <italic>QYld</italic>.<italic>FW-2H</italic>.<italic>1</italic> are not associated with a difference in maturity in our populations. Sequencing of <italic>HvCEN</italic> in Commander, Fleet and WI4304 revealed seven new sequence variants (<xref ref-type="supplementary-material" rid="pone.0178111.s001">S1 Fig</xref>, <xref ref-type="supplementary-material" rid="pone.0178111.s006">S1 File</xref>) that were not previously described in [<xref rid="pone.0178111.ref030" ref-type="bibr">30</xref>]. Fleet and Commander showed different haplotypes for the SNP in promoter region. The only SNP that is common to Fleet and Commander and contrasted with WI4304 is in intron 3 and unlikely to explain the QTL. The <italic>QYld</italic>.<italic>CW-2H</italic>.<italic>1</italic> and <italic>QYld</italic>.<italic>FW-2H</italic>.<italic>1</italic> might be due to another gene closely linked to <italic>HvCEN</italic>.</p></sec></sec><sec sec-type="conclusions" id="sec017"><title>Conclusions</title><p>Temperature, day length and rainfall are important climatic factors that dictate crop adaptation and distribution. Photoperiod response and vernalization requirement are the major determinants of adaptation in barley and other cereals like wheat, and major genes controlling these traits have been identified. These genes have pleiotropic effects on heading date, plant architecture, yield and other important traits and exert large effects that differentiate the different types of germplasm such as spring versus winter types. These genes tend not to vary within locally adapted elite germplasm; thus, breeding for a particular local environment requires deliberate selection of germplasm that, when crossed, would create new allelic combinations leading to superior high yielding genotypes for the target environment. The work described here was designed with a similar purpose in mind, specifically to identify novel alleles that control yield and adaptive traits of barley in the Mediterranean-type environment of South Australia. The three mapping populations used for this study were developed from inter-crossing well-characterized elite Australian genotypes. Twenty-two QTL for yield and grain plumpness were independent of maturity QTL and phenology genes. The lack of association of the major phenology genes (<italic>Ppd-H1</italic>, <italic>Ppd-H2</italic>, <italic>Vrn-H1</italic>, <italic>Vrn-H2</italic> and <italic>Vrn-H3</italic>/<italic>HvFT1</italic>) with yield and grain plumpness here supports the objective for which the parents were selected. The yield QTL on chromosomes 2H, 6H and 7H are common between these populations. Such QTL segregating in different genetic backgrounds could be valuable for marker-assisted selection. However, these QTL had their largest effects only in specific environments, which could limit their application for breeding widely adapted varieties. Marker-assisted pyramiding of the significant QTL into a common genetic background may be a useful breeding strategy to develop varieties adapted to the Australian environment.</p></sec><sec sec-type="supplementary-material" id="sec018"><title>Supporting information</title><supplementary-material content-type="local-data" id="pone.0178111.s001"><label>S1 Fig</label><caption><title>Structure of the <italic>HvCEN</italic> gene sequence of the Australian parental lines.</title><p>The grey boxes are the 5’ upstream and 3’ downstream regions. The exons are represented in green and the introns in blue. Polymorphic SNP between Fleet, Commander and WI4304 are shown by red bars. HvCEN_1780 is the SNP converted into KASP marker for genetic mapping of <italic>HvCEN</italic> gene.</p><p>(PDF)</p></caption><media xlink:href="pone.0178111.s001.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s002"><label>S2 Fig</label><caption><title>Genetic map of chromosome 2H in the CW (A) and FW (B) populations.</title><p>(PDF)</p></caption><media xlink:href="pone.0178111.s002.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s003"><label>S3 Fig</label><caption><title>Frequency distribution of yield at six environments in the CF population.</title><p>CF = Commander x Fleet, MRC12 = Minnipa 2012, MRC13 = Minnipa 2013, RAC12 = Roseworthy 2012, RAC13 = Roseworthy 2013, SWH12 = Swan Hill 2012, SWH13 = Swan Hill 2013.</p><p>(PDF)</p></caption><media xlink:href="pone.0178111.s003.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s004"><label>S4 Fig</label><caption><title>Frequency distribution of yield at six environments in the CW population.</title><p>CF = Commander x Fleet, MRC12 = Minnipa 2012, MRC13 = Minnipa 2013, RAC12 = Roseworthy 2012, RAC13 = Roseworthy 2013, SWH12 = Swan Hill 2012, SWH13 = Swan Hill 2013.</p><p>(PDF)</p></caption><media xlink:href="pone.0178111.s004.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s005"><label>S5 Fig</label><caption><title>Frequency distribution of yield at six environments in the FW population.</title><p>CF = Commander x Fleet, MRC12 = Minnipa 2012, MRC13 = Minnipa 2013, RAC12 = Roseworthy 2012, RAC13 = Roseworthy 2013, SWH12 = Swan Hill 2012, SWH13 = Swan Hill 2013.</p><p>(PDF)</p></caption><media xlink:href="pone.0178111.s005.pdf"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s006"><label>S1 File</label><caption><title>Sequences of phenology genes <italic>HvAP2</italic>, <italic>HvCO1</italic>, <italic>HvFT5</italic>, <italic>HvGI</italic>, <italic>HvPhyB</italic>, <italic>HvPhyC</italic>, <italic>HvTFL1</italic>, <italic>HvCEN</italic> showing the SNP between Commander, Fleet and WI4304 lines.</title><p>(TXT)</p></caption><media xlink:href="pone.0178111.s006.txt"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s007"><label>S1 Table</label><caption><title>Position of the GBS markers, phenology genes and QTL found in this study and [<xref rid="pone.0178111.ref036" ref-type="bibr">36</xref>] onto the barley RefSeq v1.0 of the map-based sequence of cultivar Morex.</title><p>(XLSX)</p></caption><media xlink:href="pone.0178111.s007.xlsx"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s008"><label>S2 Table</label><caption><title>Polymorphic SNP at phenology genes in the three barley mapping populations.</title><p>(DOCX)</p></caption><media xlink:href="pone.0178111.s008.docx"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s009"><label>S3 Table</label><caption><title>Primer details of <italic>HvCEN</italic> gene for sequencing and genotyping (KASP assay).</title><p>(DOCX)</p></caption><media xlink:href="pone.0178111.s009.docx"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s010"><label>S4 Table</label><caption><title>PCR mix and cycling program for amplification of <italic>HvCEN</italic>.</title><p>The enzymes used were Taq DNA polymerase (Invitrogen, CA) and Phusion High-fidelity DNA polymerase (Thermofisher Scientific, UK).</p><p>(DOCX)</p></caption><media xlink:href="pone.0178111.s010.docx"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s011"><label>S5 Table</label><caption><title>Genetic correlations among six environments for yield in CF, CW and FW populations.</title><p>(DOCX)</p></caption><media xlink:href="pone.0178111.s011.docx"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s012"><label>S6 Table</label><caption><title>Phenotypic correlations (r) between maturity and grain yield at six environments in CF, CW and FW populations.</title><p>(DOCX)</p></caption><media xlink:href="pone.0178111.s012.docx"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="pone.0178111.s013"><label>S7 Table</label><caption><title>Yield QTL after adjustment for maturity score in CF, CW and FW populations.</title><p>(DOCX)</p></caption><media xlink:href="pone.0178111.s013.docx"><caption><p>Click here for additional data file.</p></caption></media></supplementary-material></sec></body><back><ack><p>The authors would like to thank Anthony Smith, Donna Marks and the Barley Program team, University of Adelaide, and Davis Leigh from Minnipa Agricultural Research Centre for their assistance to the field trials. We also thank Priyanka Kalambettu and Florian Krimpzer for assisting in the SNP genotyping. This work is partially funded by the South Australia Grain Industry Trust Fund (UA 1202), Australian Research Council, Grains Research and Development Corporation, the South Australian Government, the Department of Further Education, Employment, Science and Technology, and The University of Adelaide. The presented results were obtained by support of the International Barley Genome Sequencing Consortium through providing pre-publication access to the annotated barley reference sequence RefSeq v1.0 (downloadable after registration).</p></ack><ref-list><title>References</title><ref id="pone.0178111.ref001"><label>1</label><mixed-citation publication-type="other">ABARES. Agricultural Commodities, Australia, 2012–2013. 2014.</mixed-citation></ref><ref id="pone.0178111.ref002"><label>2</label><mixed-citation publication-type="other">FAOSTAT. 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