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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Haplotype diversity of <italic>VvTFL1A</italic> gene and association with cluster traits in
grapevine (V. <italic>vinifera)</italic></title><author><name sortKey="Fernandez, Lucie" sort="Fernandez, Lucie" uniqKey="Fernandez L" first="Lucie" last="Fernandez">Lucie Fernandez</name><affiliation><nlm:aff id="I1">Instituto de Ciencias de la Vid y del Vino (ICVV), (CSIC, Universidad de La Rioja, Gobierno de La Rioja), CCT, C/Madre de Dios 51, Logroño 26006, Spain</nlm:aff></affiliation><affiliation><nlm:aff id="I7">current address: INRA, UMR Biologie du Fruit et Pathologie, B.P. 81, Villenave-d’Ornon 33883, Cedex, France</nlm:aff></affiliation></author><author><name sortKey="Le Cunff, Loic" sort="Le Cunff, Loic" uniqKey="Le Cunff L" first="Loïc" last="Le Cunff">Loïc Le Cunff</name><affiliation><nlm:aff id="I2">UMT Geno-Vigne® (IFV- INRA-SupAgro), 2 Place P. Viala 34060, Montpellier, Cedex 1, France</nlm:aff></affiliation></author><author><name sortKey="Tello, Javier" sort="Tello, Javier" uniqKey="Tello J" first="Javier" last="Tello">Javier Tello</name><affiliation><nlm:aff id="I1">Instituto de Ciencias de la Vid y del Vino (ICVV), (CSIC, Universidad de La Rioja, Gobierno de La Rioja), CCT, C/Madre de Dios 51, Logroño 26006, Spain</nlm:aff></affiliation></author><author><name sortKey="Lacombe, Thierry" sort="Lacombe, Thierry" uniqKey="Lacombe T" first="Thierry" last="Lacombe">Thierry Lacombe</name><affiliation><nlm:aff id="I4">INRA-SupAgro, UMR AGAP, équipe Diversité et Adaptation de la Vigne, 2 Place P. Viala, Montpellier 34060, Cedex 1, France</nlm:aff></affiliation><affiliation><nlm:aff id="I6">INRA, Unité Expérimentale du Domaine de Vassal, Route de Sète, Marseillan-plage 34340, France</nlm:aff></affiliation></author><author><name sortKey="Boursiquot, Jean Michel" sort="Boursiquot, Jean Michel" uniqKey="Boursiquot J" first="Jean Michel" last="Boursiquot">Jean Michel Boursiquot</name><affiliation><nlm:aff id="I4">INRA-SupAgro, UMR AGAP, équipe Diversité et Adaptation de la Vigne, 2 Place P. Viala, Montpellier 34060, Cedex 1, France</nlm:aff></affiliation></author><author><name sortKey="Fournier Level, Alexandre" sort="Fournier Level, Alexandre" uniqKey="Fournier Level A" first="Alexandre" last="Fournier-Level">Alexandre Fournier-Level</name><affiliation><nlm:aff id="I3">Bio21 Institute, Department of Genetics, University of Melbourne, 40 Flemington road, Melbourne 3010, Australia</nlm:aff></affiliation></author><author><name sortKey="Bravo, Gema" sort="Bravo, Gema" uniqKey="Bravo G" first="Gema" last="Bravo">Gema Bravo</name><affiliation><nlm:aff id="I5">CNB-CSIC, Dpto. de Genética Molecular de Plantas, Darwin 3, Madrid 28049, Spain</nlm:aff></affiliation></author><author><name sortKey="Lalet, Sandrine" sort="Lalet, Sandrine" uniqKey="Lalet S" first="Sandrine" last="Lalet">Sandrine Lalet</name><affiliation><nlm:aff id="I6">INRA, Unité Expérimentale du Domaine de Vassal, Route de Sète, Marseillan-plage 34340, France</nlm:aff></affiliation></author><author><name sortKey="Torregrosa, Laurent" sort="Torregrosa, Laurent" uniqKey="Torregrosa L" first="Laurent" last="Torregrosa">Laurent Torregrosa</name><affiliation><nlm:aff id="I4">INRA-SupAgro, UMR AGAP, équipe Diversité et Adaptation de la Vigne, 2 Place P. Viala, Montpellier 34060, Cedex 1, France</nlm:aff></affiliation></author><author><name sortKey="This, Patrice" sort="This, Patrice" uniqKey="This P" first="Patrice" last="This">Patrice This</name><affiliation><nlm:aff id="I4">INRA-SupAgro, UMR AGAP, équipe Diversité et Adaptation de la Vigne, 2 Place P. Viala, Montpellier 34060, Cedex 1, France</nlm:aff></affiliation></author><author><name sortKey="Martinez Zapater, Jose Miguel" sort="Martinez Zapater, Jose Miguel" uniqKey="Martinez Zapater J" first="José Miguel" last="Martinez-Zapater">José Miguel Martinez-Zapater</name><affiliation><nlm:aff id="I1">Instituto de Ciencias de la Vid y del Vino (ICVV), (CSIC, Universidad de La Rioja, Gobierno de La Rioja), CCT, C/Madre de Dios 51, Logroño 26006, Spain</nlm:aff></affiliation><affiliation><nlm:aff id="I5">CNB-CSIC, Dpto. de Genética Molecular de Plantas, Darwin 3, Madrid 28049, Spain</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">25091083</idno><idno type="pmc">4243098</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4243098</idno><idno type="RBID">PMC:4243098</idno><idno type="doi">10.1186/s12870-014-0209-3</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">001612</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">001612</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Haplotype diversity of <italic>VvTFL1A</italic> gene and association with cluster traits in
grapevine (V. <italic>vinifera)</italic></title><author><name sortKey="Fernandez, Lucie" sort="Fernandez, Lucie" uniqKey="Fernandez L" first="Lucie" last="Fernandez">Lucie Fernandez</name><affiliation><nlm:aff id="I1">Instituto de Ciencias de la Vid y del Vino (ICVV), (CSIC, Universidad de La Rioja, Gobierno de La Rioja), CCT, C/Madre de Dios 51, Logroño 26006, Spain</nlm:aff></affiliation><affiliation><nlm:aff id="I7">current address: INRA, UMR Biologie du Fruit et Pathologie, B.P. 81, Villenave-d’Ornon 33883, Cedex, France</nlm:aff></affiliation></author><author><name sortKey="Le Cunff, Loic" sort="Le Cunff, Loic" uniqKey="Le Cunff L" first="Loïc" last="Le Cunff">Loïc Le Cunff</name><affiliation><nlm:aff id="I2">UMT Geno-Vigne® (IFV- INRA-SupAgro), 2 Place P. Viala 34060, Montpellier, Cedex 1, France</nlm:aff></affiliation></author><author><name sortKey="Tello, Javier" sort="Tello, Javier" uniqKey="Tello J" first="Javier" last="Tello">Javier Tello</name><affiliation><nlm:aff id="I1">Instituto de Ciencias de la Vid y del Vino (ICVV), (CSIC, Universidad de La Rioja, Gobierno de La Rioja), CCT, C/Madre de Dios 51, Logroño 26006, Spain</nlm:aff></affiliation></author><author><name sortKey="Lacombe, Thierry" sort="Lacombe, Thierry" uniqKey="Lacombe T" first="Thierry" last="Lacombe">Thierry Lacombe</name><affiliation><nlm:aff id="I4">INRA-SupAgro, UMR AGAP, équipe Diversité et Adaptation de la Vigne, 2 Place P. Viala, Montpellier 34060, Cedex 1, France</nlm:aff></affiliation><affiliation><nlm:aff id="I6">INRA, Unité Expérimentale du Domaine de Vassal, Route de Sète, Marseillan-plage 34340, France</nlm:aff></affiliation></author><author><name sortKey="Boursiquot, Jean Michel" sort="Boursiquot, Jean Michel" uniqKey="Boursiquot J" first="Jean Michel" last="Boursiquot">Jean Michel Boursiquot</name><affiliation><nlm:aff id="I4">INRA-SupAgro, UMR AGAP, équipe Diversité et Adaptation de la Vigne, 2 Place P. Viala, Montpellier 34060, Cedex 1, France</nlm:aff></affiliation></author><author><name sortKey="Fournier Level, Alexandre" sort="Fournier Level, Alexandre" uniqKey="Fournier Level A" first="Alexandre" last="Fournier-Level">Alexandre Fournier-Level</name><affiliation><nlm:aff id="I3">Bio21 Institute, Department of Genetics, University of Melbourne, 40 Flemington road, Melbourne 3010, Australia</nlm:aff></affiliation></author><author><name sortKey="Bravo, Gema" sort="Bravo, Gema" uniqKey="Bravo G" first="Gema" last="Bravo">Gema Bravo</name><affiliation><nlm:aff id="I5">CNB-CSIC, Dpto. de Genética Molecular de Plantas, Darwin 3, Madrid 28049, Spain</nlm:aff></affiliation></author><author><name sortKey="Lalet, Sandrine" sort="Lalet, Sandrine" uniqKey="Lalet S" first="Sandrine" last="Lalet">Sandrine Lalet</name><affiliation><nlm:aff id="I6">INRA, Unité Expérimentale du Domaine de Vassal, Route de Sète, Marseillan-plage 34340, France</nlm:aff></affiliation></author><author><name sortKey="Torregrosa, Laurent" sort="Torregrosa, Laurent" uniqKey="Torregrosa L" first="Laurent" last="Torregrosa">Laurent Torregrosa</name><affiliation><nlm:aff id="I4">INRA-SupAgro, UMR AGAP, équipe Diversité et Adaptation de la Vigne, 2 Place P. Viala, Montpellier 34060, Cedex 1, France</nlm:aff></affiliation></author><author><name sortKey="This, Patrice" sort="This, Patrice" uniqKey="This P" first="Patrice" last="This">Patrice This</name><affiliation><nlm:aff id="I4">INRA-SupAgro, UMR AGAP, équipe Diversité et Adaptation de la Vigne, 2 Place P. Viala, Montpellier 34060, Cedex 1, France</nlm:aff></affiliation></author><author><name sortKey="Martinez Zapater, Jose Miguel" sort="Martinez Zapater, Jose Miguel" uniqKey="Martinez Zapater J" first="José Miguel" last="Martinez-Zapater">José Miguel Martinez-Zapater</name><affiliation><nlm:aff id="I1">Instituto de Ciencias de la Vid y del Vino (ICVV), (CSIC, Universidad de La Rioja, Gobierno de La Rioja), CCT, C/Madre de Dios 51, Logroño 26006, Spain</nlm:aff></affiliation><affiliation><nlm:aff id="I5">CNB-CSIC, Dpto. de Genética Molecular de Plantas, Darwin 3, Madrid 28049, Spain</nlm:aff></affiliation></author></analytic><series><title level="j">BMC Plant Biology</title><idno type="eISSN">1471-2229</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Interaction between <italic>TERMINAL FLOWER 1</italic> (<italic>TFL1</italic>) and <italic>LEAFY</italic>(<italic>LFY</italic>) seem to determine the inflorescence architecture in
<italic>Arabidopsis</italic>. In a parallel way, overexpression of <italic>VvTFL1A</italic>, a
grapevine <italic>TFL1</italic> homolog, causes delayed flowering and production of a
ramose cluster in the reiterated reproductive meristem (RRM) somatic variant of
cultivar Carignan. To analyze the possible contribution of this gene to cluster
phenotypic variation in a diversity panel of cultivated grapevine (<italic>Vitis
vinifera</italic> L. <italic>subsp. vinifera</italic>) its nucleotide diversity was
characterized and association analyses among detected sequence polymorphisms and
phenology and cluster traits was carried out.</p></sec><sec><title>Results</title><p>A total of 3.6 kb of the <italic>VvTFL1A</italic> gene, including its promoter, was
sequenced in a core collection of 140 individuals designed to maximize phenotypic
variation at agronomical relevant traits. Nucleotide variation for
<italic>VvTFL1A</italic> within this collection was higher in the promoter and intron
sequences than in the exon regions; where few polymorphisms were located in
agreement with a high conservation of coding sequence. Characterization of the
<italic>VvTFL1A</italic> haplotype network identified three major haplogroups,
consistent with the geographic origins and the use of the cultivars that could
correspond to three major ancestral alleles or evolutionary branches, based on the
existence of mutations in linkage disequilibrium. Genetic association studies with
cluster traits revealed the presence of major INDEL polymorphisms, explaining 16%,
13% and 25% of flowering time, cluster width and berry weight, respectively, and
also structuring the three haplogroups.</p></sec><sec><title>Conclusions</title><p>At least three major <italic>VvTFL1A</italic> haplogroups are present in cultivated
grapevines, which are defined by the presence of three main polymorphism LD blocks
and associated to characteristic phenotypic values for flowering time, cluster
width and berry size. Phenotypic differences between haplogroups are consistent
with differences observed between Eastern and Western grapevine cultivars and
could result from the use of different genetic pools in the domestication process
as well as different selection pressures on the development of table and wine
cultivars, respectively. Altogether, these results are coherent with previous
classifications of grapevine phenotypic diversity mainly based on cluster and
berry morphotypes as well as with recent results on the structure of genetic
diversity in cultivated grapevine.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Mc Govern, Pe" uniqKey="Mc Govern P">PE Mc Govern</name></author><author><name sortKey="Glusker, Dl" uniqKey="Glusker D">DL Glusker</name></author><author><name sortKey="Exner, Lj" uniqKey="Exner L">LJ Exner</name></author><author><name sortKey="Voigt, Mm" uniqKey="Voigt M">MM Voigt</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Mc Govern, Pe" uniqKey="Mc Govern P">PE Mc Govern</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Bacilieri, R" uniqKey="Bacilieri R">R Bacilieri</name></author><author><name sortKey="Lacombe, T" uniqKey="Lacombe T">T Lacombe</name></author><author><name sortKey="Le Cunff, L" uniqKey="Le Cunff L">L Le Cunff</name></author><author><name sortKey="Di Vecchi Staraz, M" 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<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Plant Biol</journal-id><journal-id journal-id-type="iso-abbrev">BMC Plant Biol</journal-id><journal-title-group><journal-title>BMC Plant Biology</journal-title></journal-title-group><issn pub-type="epub">1471-2229</issn><publisher><publisher-name>BioMed Central</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">25091083</article-id><article-id pub-id-type="pmc">4243098</article-id><article-id pub-id-type="publisher-id">s12870-014-0209-3</article-id><article-id pub-id-type="doi">10.1186/s12870-014-0209-3</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title>Haplotype diversity of <italic>VvTFL1A</italic> gene and association with cluster traits in
grapevine (V. <italic>vinifera)</italic></article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" id="A1"><name><surname>Fernandez</surname><given-names>Lucie</given-names></name><xref ref-type="aff" rid="I1">1</xref><xref ref-type="aff" rid="I7">7</xref><email>lfernandez@bordeaux.inra.fr</email></contrib><contrib contrib-type="author" id="A2"><name><surname>Le Cunff</surname><given-names>Loïc</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>lecunff@supagro.inra.fr</email></contrib><contrib contrib-type="author" id="A3"><name><surname>Tello</surname><given-names>Javier</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>javier.tello@icvv.es</email></contrib><contrib contrib-type="author" id="A4"><name><surname>Lacombe</surname><given-names>Thierry</given-names></name><xref ref-type="aff" rid="I4">4</xref><xref ref-type="aff" rid="I6">6</xref><email>lacombe@supagro.inra.fr</email></contrib><contrib contrib-type="author" id="A5"><name><surname>Boursiquot</surname><given-names>Jean Michel</given-names></name><xref ref-type="aff" rid="I4">4</xref><email>boursiqu@supagro.inra.fr</email></contrib><contrib contrib-type="author" id="A6"><name><surname>Fournier-Level</surname><given-names>Alexandre</given-names></name><xref ref-type="aff" rid="I3">3</xref><email>alexandre.fournier@unimelb.edu.au</email></contrib><contrib contrib-type="author" id="A7"><name><surname>Bravo</surname><given-names>Gema</given-names></name><xref ref-type="aff" rid="I5">5</xref><email>gbravo@cnb.csic.es</email></contrib><contrib contrib-type="author" id="A8"><name><surname>Lalet</surname><given-names>Sandrine</given-names></name><xref ref-type="aff" rid="I6">6</xref><email>lalet@supagro.inra.fr</email></contrib><contrib contrib-type="author" id="A9"><name><surname>Torregrosa</surname><given-names>Laurent</given-names></name><xref ref-type="aff" rid="I4">4</xref><email>torregro@supagro.inra.fr</email></contrib><contrib contrib-type="author" id="A10"><name><surname>This</surname><given-names>Patrice</given-names></name><xref ref-type="aff" rid="I4">4</xref><email>this@supagro.inra.fr</email></contrib><contrib contrib-type="author" id="A11"><name><surname>Martinez-Zapater</surname><given-names>José Miguel</given-names></name><xref ref-type="aff" rid="I1">1</xref><xref ref-type="aff" rid="I5">5</xref><email>zapater@icvv.es</email></contrib></contrib-group><aff id="I1"><label>1</label>Instituto de Ciencias de la Vid y del Vino (ICVV), (CSIC, Universidad de La Rioja, Gobierno de La Rioja), CCT, C/Madre de Dios 51, Logroño 26006, Spain</aff><aff id="I2"><label>2</label>UMT Geno-Vigne® (IFV- INRA-SupAgro), 2 Place P. Viala 34060, Montpellier, Cedex 1, France</aff><aff id="I3"><label>3</label>Bio21 Institute, Department of Genetics, University of Melbourne, 40 Flemington road, Melbourne 3010, Australia</aff><aff id="I4"><label>4</label>INRA-SupAgro, UMR AGAP, équipe Diversité et Adaptation de la Vigne, 2 Place P. Viala, Montpellier 34060, Cedex 1, France</aff><aff id="I5"><label>5</label>CNB-CSIC, Dpto. de Genética Molecular de Plantas, Darwin 3, Madrid 28049, Spain</aff><aff id="I6"><label>6</label>INRA, Unité Expérimentale du Domaine de Vassal, Route de Sète, Marseillan-plage 34340, France</aff><aff id="I7"><label>7</label>current address: INRA, UMR Biologie du Fruit et Pathologie, B.P. 81, Villenave-d’Ornon 33883, Cedex, France</aff><pub-date pub-type="collection"><year>2014</year></pub-date><pub-date pub-type="epub"><day>5</day><month>8</month><year>2014</year></pub-date><volume>14</volume><fpage>209</fpage><lpage>209</lpage><history><date date-type="received"><day>28</day><month>3</month><year>2014</year></date><date date-type="accepted"><day>23</day><month>7</month><year>2014</year></date></history><permissions><copyright-statement>Copyright © 2014 Fernandez et al.</copyright-statement><copyright-year>2014</copyright-year><copyright-holder>Fernandez et al.</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0"><license-p>This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0">http://creativecommons.org/licenses/by/4.0</ext-link>), which
permits unrestricted use, distribution, and reproduction in any medium, provided the
original work is properly credited. The Creative Commons Public Domain Dedication waiver
(<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>) applies to the data
made available in this article, unless otherwise stated.</license-p></license></permissions><self-uri xlink:href="http://www.biomedcentral.com/1471-2229/14/209"></self-uri><abstract><sec><title>Background</title><p>Interaction between <italic>TERMINAL FLOWER 1</italic> (<italic>TFL1</italic>) and <italic>LEAFY</italic>(<italic>LFY</italic>) seem to determine the inflorescence architecture in
<italic>Arabidopsis</italic>. In a parallel way, overexpression of <italic>VvTFL1A</italic>, a
grapevine <italic>TFL1</italic> homolog, causes delayed flowering and production of a
ramose cluster in the reiterated reproductive meristem (RRM) somatic variant of
cultivar Carignan. To analyze the possible contribution of this gene to cluster
phenotypic variation in a diversity panel of cultivated grapevine (<italic>Vitis
vinifera</italic> L. <italic>subsp. vinifera</italic>) its nucleotide diversity was
characterized and association analyses among detected sequence polymorphisms and
phenology and cluster traits was carried out.</p></sec><sec><title>Results</title><p>A total of 3.6 kb of the <italic>VvTFL1A</italic> gene, including its promoter, was
sequenced in a core collection of 140 individuals designed to maximize phenotypic
variation at agronomical relevant traits. Nucleotide variation for
<italic>VvTFL1A</italic> within this collection was higher in the promoter and intron
sequences than in the exon regions; where few polymorphisms were located in
agreement with a high conservation of coding sequence. Characterization of the
<italic>VvTFL1A</italic> haplotype network identified three major haplogroups,
consistent with the geographic origins and the use of the cultivars that could
correspond to three major ancestral alleles or evolutionary branches, based on the
existence of mutations in linkage disequilibrium. Genetic association studies with
cluster traits revealed the presence of major INDEL polymorphisms, explaining 16%,
13% and 25% of flowering time, cluster width and berry weight, respectively, and
also structuring the three haplogroups.</p></sec><sec><title>Conclusions</title><p>At least three major <italic>VvTFL1A</italic> haplogroups are present in cultivated
grapevines, which are defined by the presence of three main polymorphism LD blocks
and associated to characteristic phenotypic values for flowering time, cluster
width and berry size. Phenotypic differences between haplogroups are consistent
with differences observed between Eastern and Western grapevine cultivars and
could result from the use of different genetic pools in the domestication process
as well as different selection pressures on the development of table and wine
cultivars, respectively. Altogether, these results are coherent with previous
classifications of grapevine phenotypic diversity mainly based on cluster and
berry morphotypes as well as with recent results on the structure of genetic
diversity in cultivated grapevine.</p></sec></abstract><kwd-group><kwd>Plant reproductive development</kwd><kwd>Inflorescence structure</kwd><kwd>Flowering time</kwd><kwd>Berry size</kwd><kwd>Grape domestication</kwd><kwd>Grapevine</kwd></kwd-group></article-meta></front><body><sec><title>Background</title><p>Grapevine (<italic>Vitis vinifera</italic> subsp. <italic>vinifera</italic>) was domesticated in the
Neolithic period (<italic>ca</italic>. 8500–4000 BC) [<xref ref-type="bibr" rid="B1">1</xref>] from wild populations of <italic>Vitis vinifera</italic> subsp. <italic>sylvestris</italic>[<xref ref-type="bibr" rid="B2">2</xref>]. Archaeological data traced back the location of the earliest evidence for
large-scale winemaking, likely linked to the use of domesticated plants, to the north of
Zagros Mountains and in the Caucasian region [<xref ref-type="bibr" rid="B3">3</xref>] around 6000–5000 BC which supports that geographic area as the location
for primo domestication events. From there, grapevine cuttings were widely spread: first
from North to South; and later from East to West around the Mediterranean basin pathway [<xref ref-type="bibr" rid="B3">3</xref>]. Vegetative propagation and dissemination, spontaneous events of
hybridization among cultivars, breeding with local wild plants and likely secondary
domestication events generated the pattern of admixture that is observed in current
cultivars [<xref ref-type="bibr" rid="B4">4</xref>]–[<xref ref-type="bibr" rid="B9">9</xref>]. The use of different genetic pools along the process of grapevine
domestication and human selection for different uses such as fresh consumption, raisin
or wine production have resulted in large variation for cluster size, compactness and
architecture among cultivars from different geographic locations [<xref ref-type="bibr" rid="B10">10</xref>].</p><p>The size and shape of grapevine clusters is determined by the development and growth of
inflorescences as well as the efficiency of pollination, fruit set and berry growth.
Generally, wine grape cultivars present small (150-250 g) and compact clusters with
small berries, while table grapes generally have large (300-400 g) and less compact
clusters with large berries. Some of them can even be extremely big weighting up to
1000-1500 g [<xref ref-type="bibr" rid="B11">11</xref>]. Negrul [<xref ref-type="bibr" rid="B12">12</xref>] distinguished different grape morphotypes based in part on cluster and berry
traits. Cluster architecture has implications on disease susceptibility, since cultivars
with compact clusters are more susceptible to rot by <italic>Botrytis cinerea</italic> than
those of loose clusters [<xref ref-type="bibr" rid="B10">10</xref>],[<xref ref-type="bibr" rid="B13">13</xref>],[<xref ref-type="bibr" rid="B14">14</xref>]. In spite of the relevance of cluster structure and compactness, very little
is known about its genetic control probably due in part to the complexity of the trait,
which depends on many different variables along the growth of the plant as well as the
environmental interactions during its reproductive development. There is a need to
define cluster shape and size in terms of quantitative variables to understand its
genetic determination. So far, only a few studies have tried to identify the main
variables responsible for variation in bunch compactness in grapevine. In this sense,
Vail and Marois [<xref ref-type="bibr" rid="B14">14</xref>] identified cluster weight as the main factor to explain its variation while
Shavrukov et al. [<xref ref-type="bibr" rid="B15">15</xref>] proposed total cluster length and node number per rachis as two of the main
ones. Recently, Tello and Ibañez [<xref ref-type="bibr" rid="B16">16</xref>] evaluated 19 indexes to estimate cluster compactness highlighting the role of
various cluster parameters such as branch length and number. The study proposed a fast
and good estimator for cluster compactness based on cluster weight and length.</p><p>Genetic and molecular analyses in model plants, such as <italic>Arabidopsis thaliana</italic>,
demonstrated the interaction between <italic>TERMINAL FLOWER 1</italic> (<italic>TFL1</italic>) and
<italic>LEAFY</italic> (<italic>LFY</italic>) [<xref ref-type="bibr" rid="B17">17</xref>],[<xref ref-type="bibr" rid="B18">18</xref>] in the establishment of inflorescence architecture. Their interactions
supported a simple model explaining the evolution of plants inflorescence architecture [<xref ref-type="bibr" rid="B19">19</xref>]. <italic>TFL1</italic> belongs to a small gene family first identified in mammals as
encoding phosphatidyl ethanolamine-binding proteins (PEBP) [<xref ref-type="bibr" rid="B20">20</xref>], which participates in a wide variety of biological functions in eukaryotes.
In Arabidopsis, <italic>TFL1</italic> has been shown to function in the transcriptional
repression of flower meristem identity genes [<xref ref-type="bibr" rid="B21">21</xref>]. <italic>LFY</italic> encodes a plant specific transcription factor [<xref ref-type="bibr" rid="B22">22</xref>], which serves as a flower meristem identity regulator activating the
transcription of other flower meristem identity genes [<xref ref-type="bibr" rid="B23">23</xref>]. Recently, the existence of a common genetic pathway controlling
inflorescence architecture in <italic>Arabidopsis</italic> and rice has been demonstrated
indicating that this pathway could be highly conserved in angiosperms [<xref ref-type="bibr" rid="B24">24</xref>]. Following this report, four MADS-box genes are required to suppress
<italic>TFL1</italic> in emerging floral meristems; what seems to be indispensable to
initiate their differentiation.</p><p>In grapevine, the family of PEBP encoding genes includes at least five genes; three of
them have deduced protein sequences related to Arabidopsis <italic>TFL1</italic>, being
<italic>VvTFL1A</italic> the closest homologous sequence [<xref ref-type="bibr" rid="B25">25</xref>]. In fact, over-expression of <italic>VvTFL1A</italic> in transgenic Arabidopsis
plants generates phenotypes of large and late flowering inflorescences reminding those
observed when over-expressing the endogenous Arabidopsis gene [<xref ref-type="bibr" rid="B25">25</xref>]. Likewise, recent findings show that the extreme cluster proliferation and
delayed anthesis observed in the reiterated reproductive meristems (RRM) somatic variant
of grapevine cultivar Carignan was caused by a single dominant mutation in the
<italic>VvTFL1A</italic> gene. This dominant mutation was identified as the insertion of a
class II transposable element, <italic>Hatvine1-rrm,</italic> in the <italic>VvTFL1A</italic> promoter,
triggering up-regulation of the corresponding <italic>VvTFL1A</italic> allele in reproductive
and vegetative organs of the shoot apex [<xref ref-type="bibr" rid="B26">26</xref>]. These results suggested a role for <italic>VvTFL1A</italic> in the determination of
inflorescence structure as well as on the branching pattern of the grapevine fruit
clusters and the time of anthesis.</p><p>To further analyze the contribution of <italic>VvTFL1A</italic> to the phenotypic variation
observed for reproductive and inflorescence traits in grapevine, the nucleotide
diversity shown by this gene in a core collection of grapevine accessions was analysed
and a candidate gene association approach on the variation observed for fertility index,
phenological variables as well as several inflorescence and berry related traits was
carried out. Herein the identification of <italic>VvTFL1A</italic> sequence polymorphisms
associated with flowering and cluster traits is reported, being the most relevant ones
corresponding to several INDELs in two intron regions. These INDELs are in LD with
additional SNPs defining three LD blocks, which correspond to three major haplogroups.
Interestingly, these haplogroups are characteristic of either wine or table cultivars in
agreement with the cluster and flowering phenotype to which they are associated to.</p></sec><sec sec-type="methods"><title>Methods</title><sec><title>Plant material</title><p>The plant material consisted of 140 grapevine cultivars corresponding to a core
collection of <italic>Vitis vinifera</italic> L. subsp. <italic>vinifera</italic> intended to
maximize agro-morphological diversity for 50 qualitative and quantitative traits [<xref ref-type="bibr" rid="B27">27</xref>]. All the cultivars are maintained at the INRA experimental station of
Domaine de Vassal, Marseillan-plage, France
(<ext-link ext-link-type="uri" xlink:href="http://www1.montpellier.inra.fr/vassal/">http://www1.montpellier.inra.fr/vassal/</ext-link>). The list of cultivars,
pedigree when available, classification according to use (wine, table or wine/table),
geographical group according to Bacilieri et al. [<xref ref-type="bibr" rid="B6">6</xref>], Lacombe et al. [<xref ref-type="bibr" rid="B28">28</xref>] and available data of the Vitis International Variety Catalogue
(<ext-link ext-link-type="uri" xlink:href="http://www.vivc.de/">http://www.vivc.de/</ext-link>) are shown in Additional file <xref ref-type="supplementary-material" rid="S1">1</xref>. Classification according to Eastern and Western origin was obtained
considering cultivars from the Iberian Peninsula (IBER), Western and Central Europe
(WCEUR) and the Italian Peninsula (ITAP) as occidental cultivars; whereas cultivars
from the Balkans (BALK), Russia and Ukraine (RUUK), Eastern Mediterranean and
Caucasus (EMCA), Middle and Far East (MFEAS) were considered as oriental cultivars.
For newly bred grape varieties, their pedigree was used to assess Western or Eastern
origin to classify them according to their genetic origin and not according to
breeding location. When genetic origin of pedigree was questionable, the cultivar was
considered to present mixed origin.</p></sec><sec><title>Phenotypic evaluation</title><p>Ten morphological traits related to the reproductive biology of grapevine were
considered in this study. Among them, four were related to phenology (budburst time,
flowering time, veraison time and maturity time); one to yield (fertility index); and
five to berry and cluster features (berry weight and cluster length, width, weight
and compactness). Cluster compactness was estimated from available data such as
[cluster weight/(cluster length)<sup>2</sup>] [<xref ref-type="bibr" rid="B16">16</xref>]. Principal component analysis separated on axis 2 phenological traits from
cluster size traits being fertility index opposite to all other traits on axis 1
(Additional file <xref ref-type="supplementary-material" rid="S2">2</xref>). Strongest correlations were found
between maturity and <italic>veraison</italic> time (Pearson’s r = 0.82) as
well as between cluster weight and width (Pearson’s r = 0.80). All
traits were scored at the Domaine de Vassal and were expressed as the mean value for
five plants per accession analysed a maximum of three years following the recommended
OIV descriptors as shown in Table <xref ref-type="table" rid="T1">1</xref>[<xref ref-type="bibr" rid="B11">11</xref>]. Details of phenotypic values obtained for each cultivar are given in
Additional file <xref ref-type="supplementary-material" rid="S3">3</xref>. The phenotype distribution for these
traits within the core collection is provided in Additional file <xref ref-type="supplementary-material" rid="S4">4</xref>.</p><table-wrap position="float" id="T1"><label>Table 1</label><caption><p>List of traits analysed</p></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col></colgroup><thead><tr valign="top"><th align="left" valign="top"><bold>Trait</bold></th><th align="left" valign="top"><bold>OIV code</bold></th><th align="left" valign="top"><bold>Description</bold></th><th align="left" valign="top"><bold>Units</bold></th></tr></thead><tbody><tr valign="top"><td align="left" valign="top">Budburst time<hr></hr></td><td align="left" valign="top">301<hr></hr></td><td align="left" valign="top">Mean budburst time compared with Chasselas cultivar of reference<hr></hr></td><td align="left" valign="top">Days<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">Flowering time<hr></hr></td><td align="left" valign="top">302<hr></hr></td><td align="left" valign="top">Mean flowering time (50% of open flowers) compared with Chasselas
cultivar of reference<hr></hr></td><td align="left" valign="top">Days<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"><italic>Veraison</italic> time<hr></hr></td><td align="left" valign="top">303<hr></hr></td><td align="left" valign="top">Mean <italic>veraison</italic> time (50% of turn berries) compared with
Chasselas cultivar of reference<hr></hr></td><td align="left" valign="top">Weeks<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">Maturity time<hr></hr></td><td align="left" valign="top">304<hr></hr></td><td align="left" valign="top">Mean maturity time compared with Chasselas cultivar of reference<hr></hr></td><td align="left" valign="top">Weeks<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">Yield = Fertility index<hr></hr></td><td align="left" valign="top">153<hr></hr></td><td align="left" valign="top">(Number of inflorescence / number of shoot ) per plant<hr></hr></td><td align="left" valign="top">Count<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">Berry weight<hr></hr></td><td align="left" valign="top">503<hr></hr></td><td align="left" valign="top">Average berry weight at maturity (20°Brix)<hr></hr></td><td align="left" valign="top">Gram<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">Cluster length<hr></hr></td><td align="left" valign="top">202<hr></hr></td><td align="left" valign="top">Average maximum cluster length at maturity (20°Brix)<hr></hr></td><td align="left" valign="top">Centimeter<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">Cluster width<hr></hr></td><td align="left" valign="top">203<hr></hr></td><td align="left" valign="top">Average maximum cluster width at maturity (20°Brix)<hr></hr></td><td align="left" valign="top">Centimeter<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">Cluster weight<hr></hr></td><td align="left" valign="top">502<hr></hr></td><td align="left" valign="top">Average cluster weight at maturity (20°Brix)<hr></hr></td><td align="left" valign="top">Gram<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">Cluster compactness</td><td align="left" valign="top"> </td><td align="left" valign="top">Cluster weight/(cluster length)<sup>2</sup></td><td align="left" valign="top">Gram/cm<sup>2</sup></td></tr></tbody></table></table-wrap></sec><sec><title>Genotyping</title><p>For each genotype, 3.6 kb of the <italic>VvTFL1A</italic> gene (GSVIVT01036145001,
chr6_20199669-20203319, Genoscope 12X) were amplified and sequenced using primers
listed in Fernandez et al. [<xref ref-type="bibr" rid="B26">26</xref>]. DNA was extracted from young leaves of each genotype as described in
Adam-Blondon et al. [<xref ref-type="bibr" rid="B29">29</xref>]. Amplifications were carried out using Taq DNA Polymerase (Qiagen) as
recommended by manufacturer. PCR products were treated with Exosap-IT reagent as
recommended by manufacturer and sequenced at the Genomic Service of the Parque
Cientifico de Madrid in an ABI prism 3730 (Applied Biosystems) DNA sequencer. Base
calling, quality trimming and alignment of ABI chromatograms was performed using
SeqScape v2.5 (Applied Biosystems). Sequence polymorphisms were manually verified to
establish genotypes. The nomenclature system used to name polymorphisms corresponded
to letters followed by numbers: single letter correspond to the involved nucleotide
substitution using the IUB’s conventional nomenclature and “Ins” is
used to designed INDEL; positive or negative numbers corresponded to polymorphism
position from the first base of the “ATG start codon”. Linkage
disequilibrium (LD) calculations between polymorphisms were carried out using the LD
option implemented in TASSEL v.2.1 [<xref ref-type="bibr" rid="B30">30</xref>].</p><p>Molecular diversity parameter estimates were calculated using DnaSP v4.50.2 [<xref ref-type="bibr" rid="B31">31</xref>]. Per site nucleotide diversity (π) [<xref ref-type="bibr" rid="B32">32</xref>], Watterson θ estimate [<xref ref-type="bibr" rid="B33">33</xref>] and Tajima’s D [<xref ref-type="bibr" rid="B34">34</xref>] were calculated for the whole haplotype set and separately for the three
structured sub-populations (K1, K2, K3).</p></sec><sec><title>Association tests</title><p>Knowing that population structure can bias association studies, the structured
association (SA) method [<xref ref-type="bibr" rid="B35">35</xref>] and the Mixed Linear Model MLM [<xref ref-type="bibr" rid="B36">36</xref>] were used to reduce false positives. Population structure of the core
collection was determined using 20 SSR markers well scattered throughout the 19 grape
linkage groups (LGs) [<xref ref-type="bibr" rid="B37">37</xref>] by a Bayesian clustering implemented in STRUCTURE v.2.3.4 [<xref ref-type="bibr" rid="B38">38</xref>]. The ADMIXTURE model was applied assuming that segregation of alleles was
independent. A burn-in period of 100,000 followed by 150,000 Markov Chain Monte Carlo
(MCMC) iterations with 5 replicate runs were carried out for each value of population
structure tested (1 ≤ K ≤ 10). The optimal
sub-population model was selected with the maximal likelihood
<italic>K = 3</italic> according to the <italic>ΔK</italic> method [<xref ref-type="bibr" rid="B39">39</xref>] and later corrections for <italic>ΔK</italic> artefacts [<xref ref-type="bibr" rid="B40">40</xref>]. The corresponding Q-matrix was used for structured association tests. An
arbitrary cut-off value of 50% ancestry was set to assign each individual to one of
the three sub-population clusters (Additional file <xref ref-type="supplementary-material" rid="S1">1</xref>).
Individuals not assigned in one sub-population were considered as admixed. This
structure discriminates cultivars according to their use and geographic origin with
K2 mainly constituted by western wine cultivars (78%), K3 by eastern table cultivars
(78%) and K1 composed by eastern and western wine cultivars and table cultivars
(Figure <xref ref-type="fig" rid="F1">1</xref>). The kinship matrix was calculated on the
basis of the same set of SSR markers [<xref ref-type="bibr" rid="B41">41</xref>] using TASSEL v.2.1.</p><fig id="F1" position="float"><label>Figure 1</label><caption><p><bold>Population structure of the</bold><bold><italic>V.vinifera</italic></bold><bold>core collection.</bold> Schematic representation of estimated membership was
obtained using STRUCTURE and classification of the individuals to one of the
three genetic groups (K1, K2 and K3) was obtained using 50% of ancestry.
Geographic origin <bold>(A)</bold> and fruit use <bold>(B)</bold> of each cultivar are
indicated using colour codes.</p></caption><graphic xlink:href="s12870-014-0209-3-1"></graphic></fig><p>Comparison of the naïve General Linear Model (GLM) test, the structured
association test (GLM-Q) and the structured Mixed Linear Model (MLM-Q) using TASSEL
v.3 identified the last one as the most conservative model and was therefore selected
to perform the association tests. MLM-Q association tests were carried out using the
R v.2.15 [<xref ref-type="bibr" rid="B42">42</xref>] and TASSEL v.3 software. Polymorphic sites carrying rare alleles
(frequencies <5% within the total sample) and unbalanced genotypic classes
(frequencies <5% within the total sample) were discarded to avoid biased
associations. Rare genotypic classes were in this last case replaced by missing data.
Polymorphisms were codified to test both additive and dominant effects using R to be
similar with marker model tested using TASSEL. For traits showing significant
associations after Bonferroni correction (<italic>P</italic> ≤ 0.05) using
either TASSEL or R, multi-locus mixed-models using forward-backward stepwise
regression (MLMM) were implemented using the R software to identify major
non-redundant associated markers [<xref ref-type="bibr" rid="B43">43</xref>]. Population structure and kinship were both included in the multi-locus
analysis. Best models were selected according to the extended Bayesian information
criteria (EBIC) and the multiple Bonferroni criteria (mBonf) according to Segura et
al. [<xref ref-type="bibr" rid="B43">43</xref>].</p></sec><sec><title>Haplotype reconstruction and networks</title><p>As <italic>V. vinifera</italic> genotypes are generally highly heterozygous [<xref ref-type="bibr" rid="B37">37</xref>], the unphased genotypic dataset was analysed to identify the succession of
linked polymorphisms along the sequenced DNA region. Haplotypes were reconstructed
using a PLEM algorithm [<xref ref-type="bibr" rid="B44">44</xref>] implemented in PHASE v2.1 applying default values of the iterative scheme [<xref ref-type="bibr" rid="B45">45</xref>]. Reconstructed haplotypes were submitted separately and simultaneously to
three recombination detection tests implemented in the Recombination Detection
Program v3beta41 [<xref ref-type="bibr" rid="B46">46</xref>]. Those were the MaxChi method with a window size of 12, 20, 25 or 30
variables sites [<xref ref-type="bibr" rid="B47">47</xref>], the Chimaera method with a window size of 12, 20, 25 or 30 variables
sites [<xref ref-type="bibr" rid="B48">48</xref>] and the 3SEQ method [<xref ref-type="bibr" rid="B49">49</xref>]. To ensure consistency, haplotypes showing a significant probability of
being the result of recombination (<italic>P</italic> ≤0.05) in at least two tests were
considered as recombinants and excluded from further analysis as previously done by
Fournier-Level et al. [<xref ref-type="bibr" rid="B50">50</xref>].</p><p>Network analysis was carried out using the median-joining method [<xref ref-type="bibr" rid="B51">51</xref>] implemented in Network v4.5.1.6 (Fluxus Technology, Sudbury, UK) and
fixing a weight of 99 for the polymorphisms showing best associations with traits
(Ins883, Ins422, K-737 and M-196). Three haplogroups HGA, HGB and HGC were defined
according to the three LD blocks.</p></sec></sec><sec sec-type="results"><title>Results</title><sec><title><italic>VvTFL1A</italic> structure and sequence polymorphisms</title><p>A total of 3646 bp of the <italic>VvTFL1A</italic> gene corresponding to 2442 bp
and 1204 bp before and after ATG, respectively, were sequenced in all the
individuals of the core collection. Translation of coding sequences identified the
annotated four exons in the <italic>V. vinifera</italic> PN40024 genome sequence [<xref ref-type="bibr" rid="B52">52</xref>] of 201, 62, 41 and 218 bp and three introns of 83, 467 and
107 bp (Figure <xref ref-type="fig" rid="F2">2</xref>A). Nucleotide sequence analyses
enabled the identification of 70 polymorphisms (64 SNP and 6 INDEL including 3
microsatellites). Among them, 44 polymorphisms were located in the promoter sequence,
4 in the 5’ untranslated region, and 5 and 17 polymorphisms were located in
exonic and intronic regions, respectively. INDEL Ins-2054 and Ins-1389, located in
the promoter, and Ins883 in intron 3, involved 5, 21 and 1 nucleotides, respectively;
whereas Ins-393 and Ins-3 in the promoter, and Ins422 in intron 2 represented
microsatellite variations with Ins422 being biallelic and the other two multiallelic
(Figure <xref ref-type="fig" rid="F2">2</xref>A). Out of the five exonic SNP, only three
(W13, W1087, and M1094) caused non-synonymous amino acid substitutions and are shown
in Figure <xref ref-type="fig" rid="F2">2</xref>A. Among the 70 polymorphisms, 32 (46%) were
represented by a rare allele (frequency <5%), with 10 of them grouped between
position −1079 and −1430 before ATG. The complete genotypic data set is
available in Additional file <xref ref-type="supplementary-material" rid="S5">5</xref>.</p><fig id="F2" position="float"><label>Figure 2</label><caption><p><bold>Sequence polymorphisms identified for the</bold><bold><italic>VvTFL1A</italic></bold><bold>gene sequence and their association to phenotypic traits. A</bold>.
<italic>VvTFL1A</italic> polymorphisms found in 140 <italic>V. vinifera</italic>accessions. Single-nucleotide substitutions are depicted as vertical bars,
different colours denoting allele frequency found in the collection (bottom
legend box). INDEL are indicated as vertical arrows with similar colour codes.
Amino acid changes are indicated. Polymorphisms are classified according to
three LD blocks using a colour code: <bold>B</bold>. Level of structured MLM
association detected between phenotypic traits and markers along
<italic>VvTFL1A</italic> gene using TASSEL. <italic>P</italic>-value threshold 0.05 after
Bonferroni correction is represented by the black line.</p></caption><graphic xlink:href="s12870-014-0209-3-2"></graphic></fig></sec><sec><title><italic>VvTFL1A</italic> nucleotide diversity</title><p>A total of 62 haplotypes, including 37 singletons, were identified based on phase
reconstruction using the 70 segregating polymorphisms (Additional file <xref ref-type="supplementary-material" rid="S6">6</xref>). Genetic diversity of <italic>VvTFL1A</italic> gene was estimated in
terms of number of segregating sites (S) and polymorphism (π and θ) for all
the haplotypes and according to population structure. Comparison of genetic diversity
index among the 3 genetic groups inferred within the analysed core collection (see
Material and Methods) indicated that despite K3 sub-population included a smaller
number of haplotypes than the two other K1 and K2 sub-populations; this presented a
high number of segregating sites and π and θ polymorphism indexes
(Table <xref ref-type="table" rid="T2">2</xref>). The Tajima’s <italic>D</italic>-tests showed a
general neutral value considering all haplotypes and a slight but non-significant
negative value in K1 sub-population compared with K2 sub-population, which showed a
slight positive value (Table <xref ref-type="table" rid="T2">2</xref>). When Tajima’s
<italic>D</italic>-test was estimated in sliding windows along <italic>VvTFL1A</italic>; the test
revealed a similar pattern of variation for K1 and K3 sub-populations with a general
negative value along <italic>VvTFL1A</italic> promoter (Figure <xref ref-type="fig" rid="F3">3</xref>).
In contrast, the value of <italic>D</italic> along the transcribed region in K3
sub-population increased to reach a positive value. In K2 sub-population,
Tajima’s <italic>D</italic>-test showed general positive value in both promoter and
transcribed regions. These patterns indicated different selection or demographic
events between haplotypes within the three genetic groups.</p><table-wrap position="float" id="T2"><label>Table 2</label><caption><p><bold>Pattern of diversity and neutrality tests for</bold><bold><italic>VvTFL1A</italic></bold><bold>gene</bold></p></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col></colgroup><thead><tr valign="top"><th align="left" valign="top"> </th><th align="left" valign="top"><bold>All Haplotypes</bold></th><th align="left" valign="top"><bold>K1</bold></th><th align="left" valign="top"><bold>K2</bold></th><th align="left" valign="top"><bold>K3</bold></th></tr></thead><tbody><tr valign="top"><td align="left" valign="top">S<hr></hr></td><td align="left" valign="top">70<hr></hr></td><td align="left" valign="top">62<hr></hr></td><td align="left" valign="top">50<hr></hr></td><td align="left" valign="top">48<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">H<hr></hr></td><td align="left" valign="top">62<hr></hr></td><td align="left" valign="top">37<hr></hr></td><td align="left" valign="top">35<hr></hr></td><td align="left" valign="top">16<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">π<hr></hr></td><td align="left" valign="top">0.00401<hr></hr></td><td align="left" valign="top">0.00365<hr></hr></td><td align="left" valign="top">0.00418<hr></hr></td><td align="left" valign="top">0.00412<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">θ<hr></hr></td><td align="left" valign="top">0.00439<hr></hr></td><td align="left" valign="top">0.00439<hr></hr></td><td align="left" valign="top">0.00348<hr></hr></td><td align="left" valign="top">0.00442<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">D<sub>Tajima</sub></td><td align="left" valign="top">−0.29978</td><td align="left" valign="top">−0.61965</td><td align="left" valign="top">0.72764</td><td align="left" valign="top">−0.29739</td></tr></tbody></table><table-wrap-foot><p>S indicates number of segregating sites and H haplotype number. Analysis has
been carried out in the three clusters of individuals related to the
population structure. All tests yielded non-significant <italic>P-</italic>values
(<italic>P</italic> >0.05).</p></table-wrap-foot></table-wrap><fig id="F3" position="float"><label>Figure 3</label><caption><p><bold>Pattern of Tajima’s D values along</bold><bold><italic>VvTFL1A</italic></bold><bold>gene.</bold> Neutral selection (D = 0) is represented by the grey
line. Patterns have been obtained using sliding windows option from DnaSP
(window length =500 and step size =350).</p></caption><graphic xlink:href="s12870-014-0209-3-3"></graphic></fig></sec><sec><title><italic>VvTFL1A</italic> haplotypes</title><p>In order to study relationship between <italic>VvTFL1A</italic> haplotypes, those likely
resulting from recombinant events were detected to avoid bias. Among the 62
haplotypes originally identified, 26 were considered recombinants (Additional file
<xref ref-type="supplementary-material" rid="S6">6</xref>) and were removed for haplotype network analysis.
Haplotype network was constructed using 36 non-recombinant haplotypes that included
19 singletons. Haplotype network discriminated three groups of closely related
haplotypes or haplogroups (HGA, HGB and HGC), which were clearly structured in
relation with mutations in linkage disequilibrium (LD) (Figure <xref ref-type="fig" rid="F4">4</xref>). Within HGA major part of the haplotypes (44%) were present in
cultivars of the K1 sub-population including Eastern and Western cultivars used as
table and wine grapes. The remaining haplotypes of HGA were similarly found in
cultivars of the K2 and K3 sub-population (25% and 24%, respectively). Regarding HGB
and HGC 52% and 68% of their haplotypes were detected in cultivars of the K2
sub-population mainly represented by Western wine cultivars (Figure <xref ref-type="fig" rid="F4">4</xref>).</p><fig id="F4" position="float"><label>Figure 4</label><caption><p><bold>Median joining networks derived from reconstructed DNA sequence haplotypes
of</bold><bold><italic>VvTFL1A</italic></bold><bold>.</bold> Network analysis was carried for haplotypes identified for 70
polymorphic sites in the <italic>VvTFL1A</italic> gene excluding recombined haplotypes.
Haplotypes are represented by circles with circle size proportional to
haplotype frequency (circle size corresponding to haplotype numbers of 1, 5 and
25 are illustrated). The haplotypes colours relate to the accessions
classification according to according to structured genetic groups (Additional
file <xref ref-type="supplementary-material" rid="S1">1</xref>). Black dots represent mutational steps.
Colour lines represent the mutations in LD that separated the three haplogroups
identified (HG).</p></caption><graphic xlink:href="s12870-014-0209-3-4"></graphic></fig><p>Haplotypes 32 and 3 were the most frequent (frequency >0.15 on the total haplotype
pool and >0.19 when excluding the recombinants) and belonged to HGA and HGB,
respectively. Most of the cultivars of the core collection were heterozygous for two
different haplotypes (86%) with 20% of them being heterozygous for a combination of
HGA and HGB haplotypes (Additional file <xref ref-type="supplementary-material" rid="S1">1</xref>). Only 20
cultivars were homozygous (14%) with eight and five varieties homozygous for HGA and
HGB haplotypes, respectively. Two cultivars were homozygous for haplotype 54 of HGC
and the remaining homozygous accessions presented putative recombinant
haplotypes.</p><p>Regarding the recombinant haplotypes, haplotype 18, which was the most frequent
(frequency = 0.05), corresponded to a recombination between haplotypes
from HGA and HGB (Additional file <xref ref-type="supplementary-material" rid="S6">6</xref>). Indeed, no allele
specifically assigned to HGC was present in this haplotype, which was always combined
with alleles typical of both HGA and HGB haplotypes. Interestingly; haplotype 18 was
present only in cultivars of K1 (40%) and K3 (60%) sub-populations classified mainly
as Eastern table grapes, with two cultivars being homozygous for this haplotype
(Additional file <xref ref-type="supplementary-material" rid="S1">1</xref>). Furthermore, among the individuals
that presented at least one HGC haplotype mainly composed by cultivars of the K2
sub-population, the only one Eastern table cultivar belonging to the K3
sub-population was a combination with haplotype 18.</p><p>Certainly, LD pattern along <italic>VvTFL1A</italic> gene revealed three main blocks of
linked polymorphisms (Figure <xref ref-type="fig" rid="F5">5</xref>): linked polymorphisms
specific of HGA (Ins-2054, Y-1433, K-737, S-327, S-35, W270, Ins883) located in the
promoter, the first and the third introns of <italic>VvTFL1A</italic> gene; linked
polymorphisms specific of HGB (Y-2237, K-2158, R-2124, R-2037, W-1991, R-1846, K-736,
M224, R416, Y752 and M898) identified in the distal promoter region and in the three
intron regions; and linked polymorphisms specific of HGC (K-1704, R-1507, Ins-1389,
Y-1362, Y-732, K-730, Y-19, R404, Ins422, R628) located in the promoter and the
second intron of the <italic>VvTFL1A</italic> gene. Thus, haplogroups HGA, HGB, and HGC are
consistent with the existence of three ancestral alleles or evolutionary branches
supported by polymorphisms in the three LD blocks.</p><fig id="F5" position="float"><label>Figure 5</label><caption><p><bold>Linkage disequilibrium among polymorphisms in the gene</bold><bold><italic>VvTFL1A.</italic></bold> LD plot based on R<sup>2</sup> values for SNP and INDEL with frequency
>5% were estimated according to Remington et al. [<xref ref-type="bibr" rid="B53">53</xref>]. The schematic representation of the <italic>VvTFL1A</italic> locus
indicates ATG and stop codon position, exon regions represented by yellow boxes
and UTR by grey boxes. Polymorphism classification into three LD blocks is
represented by a colour code.</p></caption><graphic xlink:href="s12870-014-0209-3-5"></graphic></fig></sec><sec><title>Candidate gene association</title><p>Considering the biological function established for the <italic>Arabidopsis TFL1</italic>gene as well as the phenological traits altered in the Carignan RRM somatic variant,
the candidate gene association study was focused on those phenological and cluster
morphological traits that could be related with its putative biological function in
grapevine. Association tests for <italic>VvTFL1A</italic> gene were run between the 38
polymorphisms showing minor allele frequency ≥5% and each phenotypic trait.
Rare genotyping classes (≤5%) were excluded from the association tests. Out of
the 38 polymorphisms, only 8 presented significant associations (adjusted
<italic>P-</italic>value ≤0.05) using either R or TASSEL with flowering time, berry
weight and cluster width (Table <xref ref-type="table" rid="T3">3</xref>, Figure <xref ref-type="fig" rid="F2">2</xref>B).</p><table-wrap position="float" id="T3"><label>Table 3</label><caption><p><bold>List of</bold><bold><italic>VvTFLlA</italic></bold><bold>polymorphisms showing significant association after Bonferroni correction
(<0.05) with flowering time, cluster width and berry weight through
structured MLM tests using either R or TASSEL</bold></p></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col></colgroup><thead><tr valign="top"><th align="left" valign="top"> <hr></hr></th><th align="left" valign="top"> <hr></hr></th><th align="left" valign="top"> <hr></hr></th><th colspan="2" align="left" valign="top"><bold>MLM-R</bold><hr></hr></th><th colspan="3" align="left" valign="top"><bold>MLM-TASSEL</bold><hr></hr></th></tr><tr valign="top"><th align="left" valign="top"><bold>Trait</bold></th><th align="left" valign="top"><bold>Marker</bold></th><th align="left" valign="top"><bold>Haplogroup</bold></th><th align="left" valign="top"><bold><italic>P-</italic></bold><bold>value</bold></th><th align="left" valign="top"><bold>Bonf corr < 0.05</bold></th><th align="left" valign="top"><bold><italic>P-</italic></bold><bold>value</bold></th><th align="left" valign="top"><bold>Bonf corr < 0.05</bold></th><th align="left" valign="top"><bold>R2 Marker</bold></th></tr></thead><tbody><tr valign="top"><td align="left" valign="top">Flowering time<hr></hr></td><td align="left" valign="top">Ins883<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">2.72E-04<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">2.19E-03<hr></hr></td><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">0.104<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">K-737<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">1.04E-03<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">6.42E-03<hr></hr></td><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">0.089<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">Ins422<hr></hr></td><td align="left" valign="top">HGC<hr></hr></td><td align="left" valign="top">1.24E-03<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">6.01E-03<hr></hr></td><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">0.089<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">Berry weight<hr></hr></td><td align="left" valign="top">M-196<hr></hr></td><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">1.47E-08<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">2.23E-06<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">0.163<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">Ins883<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">5.76E-07<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">8.40E-05<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">0.118<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">S-327<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">1.33E-06<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">3.06E-04<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">0.105<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">K-737<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">3.54E-06<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">5.83E-04<hr></hr></td><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">0.095<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">S-35<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">9.17E-06<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">4.24E-04<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">0.105<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">W270<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">1.02E-04<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">2.84E-04<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">0.112<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">Ins-2054<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">1.58E-04<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">2.16E-03<hr></hr></td><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">0.074<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">Ins422<hr></hr></td><td align="left" valign="top">HGC<hr></hr></td><td align="left" valign="top">2.32E-04<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">1.30E-02<hr></hr></td><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">0.059<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">Cluster width<hr></hr></td><td align="left" valign="top">Ins883<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">1.63E-05<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">1.72E-04<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">0.130<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">K-737<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">9.18E-05<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">1.88E-03<hr></hr></td><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">0.097<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">S-327<hr></hr></td><td align="left" valign="top">HGB<hr></hr></td><td align="left" valign="top">3.34E-04<hr></hr></td><td align="left" valign="top">*<hr></hr></td><td align="left" valign="top">3.30E-03<hr></hr></td><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">0.086<hr></hr></td></tr><tr valign="top"><td align="left" valign="top"> </td><td align="left" valign="top">Ins422</td><td align="left" valign="top">HGC</td><td align="left" valign="top">1.07E-03</td><td align="left" valign="top">*</td><td align="left" valign="top">1.34E-02</td><td align="left" valign="top"> </td><td align="left" valign="top">0.066</td></tr></tbody></table><table-wrap-foot><p>Corresponding <italic>P-</italic>value and variance explained by the marker
(R<sup>2</sup> Marker) obtained using TASSEL is indicated, *correspond to
significant adjusted <italic>P-</italic>values(<0.05).</p></table-wrap-foot></table-wrap><p>The strongest association was found between berry weight and SNP M-196
(<italic>P</italic> = 1.4E<sup>−8</sup>) explaining 16% of the trait
variation. The highest association for flowering time and cluster width was found
with Ins883 (<italic>P</italic> = 2.7E<sup>−4</sup>,
<italic>P</italic> = 1.6E<sup>−5</sup>, respectively) that explained 10%
and 13% of trait variation, respectively. Interestingly, Ins883 characteristic of HGA
also associated significantly (<italic>P</italic> ≤0.01) with berry weight
(<italic>P</italic> = 5.7E<sup>−7</sup>). At a lesser extent, Ins422
from HGC associated with the three traits explaining 9%, 6% and 7% of flowering time,
berry weight and cluster width variations, respectively.</p><p>In order to determine whether the different associations detected were only due to LD
or were the result of the particular effect of each polymorphism, the multi-locus
mixed-model analysis was carried out. Flowering time showed the strongest
associations with polymorphisms characteristic of HGA and HGC under single-locus
approaches (Table <xref ref-type="table" rid="T3">3</xref>). In the multi-locus analysis, the
best models to explain flowering time variation identified one and two polymorphisms
based on optimal mBonf and EBIC criteria, respectively (Table <xref ref-type="table" rid="T4">4</xref>). The optimal models included Ins833 from HGA specific LD block and
W1087 without LD with other polymorphisms and explained up to 16% of flowering time
variation. Association between W1087 and flowering time was not identified with the
single-locus approach; the use of Ins883 as covariate in the model revealed W1087
association. The remaining markers, not included in the model, had minor and/or
redundant effects with those ones. Similarly, the best models explaining up to 25% of
berry weight variation included M-196 and Ins883 in agreement with the highest
associations detected with the single-locus approach. Instead, cluster width
variation showing associations with polymorphisms within the three LD blocks under
single-locus approaches was only explained by polymorphism Ins883 (HGA) after the
multi-locus mixed-model analysis. The effect of polymorphisms characteristic of HGB
was minor and redundant with those of Ins883. Therefore, in addition to its high
association (<italic>P</italic> ≤0.01) in single-locus analyses with three traits
(flowering time, cluster width and berry weight), Ins883 was selected in the three
best multi-locus models explaining the variation of those traits. Besides, Ins883
explains alone cluster width variation. These results highlight the major influence
of INDEL Ins883 in the possible role of <italic>VvTFL1A</italic> on phenology and cluster
traits.</p><table-wrap position="float" id="T4"><label>Table 4</label><caption><p>MLMM results</p></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col><col align="left"></col></colgroup><thead><tr valign="top"><th align="left" valign="top"><bold>Trait</bold></th><th align="left" valign="top"><bold>Forward step</bold></th><th align="left" valign="top"><bold>mBonf <0.05</bold></th><th align="left" valign="top"><bold>EBIC</bold></th><th align="left" valign="top"><bold>Markers in the model</bold></th><th align="left" valign="top"><bold>Gene region</bold></th><th align="left" valign="top"><bold>Haplogroup</bold></th><th align="left" valign="top"><bold>R2 Markers</bold></th><th align="left" valign="top"><bold>R2 Model</bold></th></tr></thead><tbody><tr valign="top"><td rowspan="2" align="left" valign="top">Flowering time<hr></hr></td><td align="left" valign="top">1<hr></hr></td><td align="left" valign="top">8.98E-03<hr></hr></td><td align="left" valign="top">609<hr></hr></td><td align="left" valign="top">Ins883<hr></hr></td><td align="left" valign="top">Intron3<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">0.11<hr></hr></td><td align="left" valign="top">0.19<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">2<hr></hr></td><td align="left" valign="top">2.61E-01<hr></hr></td><td align="left" valign="top">603<hr></hr></td><td align="left" valign="top">+ W1087<hr></hr></td><td align="left" valign="top">Exon4<hr></hr></td><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">0.16<hr></hr></td><td align="left" valign="top">0.25<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">Cluster width<hr></hr></td><td align="left" valign="top">1<hr></hr></td><td align="left" valign="top">5.38E-04<hr></hr></td><td align="left" valign="top">492<hr></hr></td><td align="left" valign="top">Ins883<hr></hr></td><td align="left" valign="top">Intron3<hr></hr></td><td align="left" valign="top">HGA<hr></hr></td><td align="left" valign="top">0.13<hr></hr></td><td align="left" valign="top">0.34<hr></hr></td></tr><tr valign="top"><td rowspan="2" align="left" valign="top">Berry weight</td><td align="left" valign="top">1<hr></hr></td><td align="left" valign="top">1.26E-06<hr></hr></td><td align="left" valign="top">431<hr></hr></td><td align="left" valign="top">M-196<hr></hr></td><td align="left" valign="top">Promoter<hr></hr></td><td align="left" valign="top"> <hr></hr></td><td align="left" valign="top">0.21<hr></hr></td><td align="left" valign="top">0.76<hr></hr></td></tr><tr valign="top"><td align="left" valign="top">2</td><td align="left" valign="top">1.49E-01</td><td align="left" valign="top">412</td><td align="left" valign="top">+ Ins883</td><td align="left" valign="top">Intron3</td><td align="left" valign="top">HGA</td><td align="left" valign="top">0.25</td><td align="left" valign="top">0.80</td></tr></tbody></table><table-wrap-foot><p>The models presented corresponded to the optimal models, i.e., optimizing
EBIC and mBonf criteria. R2 Markers = variance explained by
polymorphisms in each model, R2 Model = cumulative variance
explained by markers and genetic variance (structure and kinship).</p></table-wrap-foot></table-wrap></sec><sec><title>Phenotypic values related to major haplotypes</title><p>Based on haplotype network and association results, two molecular polymorphisms
(Ins883 and Ins422) were selected that discriminated the three haplogroups (HGA:
Ins883(G)<sub>6</sub>-Ins422(GA)<sub>7</sub>; HGB:
Ins883(G)<sub>5</sub>-Ins422(GA)<sub>7</sub>; HGC:
Ins883(G)<sub>5</sub>-Ins422(GA)<sub>8</sub>). The (G)<sub>6</sub> allele of
Ins883 was associated with late flowering time, high berry weight and large cluster
width (Figure <xref ref-type="fig" rid="F6">6</xref>). All haplotypes in HGA presented the
(G)<sub>6</sub> allele, in contrast with haplotypes in HGB and HGC that contained
the (G)<sub>5</sub> allele Regarding Ins422, the (GA)<sub>8</sub> allele was
associated with early flowering time, low berry weight and small cluster width
(Figure <xref ref-type="fig" rid="F6">6</xref>). All haplotypes carrying the
(GA)<sub>8</sub> allele belonged to HGC, mainly represented by haplotype 60, while
haplotypes in HGA and HGB contained the (GA)<sub>7</sub> allele.</p><fig id="F6" position="float"><label>Figure 6</label><caption><p><bold>Effects of</bold><bold><italic>VvTFL1A</italic></bold><bold>INDEL Ins883 and Ins422 on flowering time, berry weight and cluster
width.</bold> Box plots represent minimum and maximum (whisker), median (square
dot), and 25th and 75th percentiles (box) values.</p></caption><graphic xlink:href="s12870-014-0209-3-6"></graphic></fig><p>As other polymorphisms appeared associated with these phenotypic traits, the
phenotypic values were also analysed considering the three major haplotypes 32, 3 and
60 from HGA, B and C, respectively. As an average, individuals presenting at least
one haplotype 32 exhibited late flowering, big berries and large cluster clearly in
contrast to the phenotypic features of individuals containing at least one haplotype
3 or 60 (Figure <xref ref-type="fig" rid="F7">7</xref>). This was more obvious when homozygous
individuals or heterozygous individuals for haplotypes 3 and 60 were taken into
account considering the absence of homozygous individuals for haplotype 60
(Figure <xref ref-type="fig" rid="F7">7</xref>). The phenotypic value for the more frequent
recombinant haplotype 18 found in Eastern table cultivars was also analysed, which
presented the (G)<sub>6</sub> allele at the major INDEL Ins883 such as haplotypes of
HGA. Phenotypic values for flowering time, berry weight and cluster width for
haplotype 18 were slightly higher than those of individuals carrying haplotype 32
(Figure <xref ref-type="fig" rid="F7">7</xref>).</p><fig id="F7" position="float"><label>Figure 7</label><caption><p><bold>Phenotypic value for flowering time, berry weight and cluster width related
to major haplotypes.</bold> Phenotypic values of individuals containing the
major haplotypes H32, H3 and H60 and for the recombinant haplotype H18 at
heterozygous or homozygous state. Box plots represent minimum and maximum
(whisker), median (square dot), and 25th and 75th percentiles (box) values.</p></caption><graphic xlink:href="s12870-014-0209-3-7"></graphic></fig></sec></sec><sec sec-type="discussion"><title>Discussion</title><p><italic>Arabidopsis TFL1</italic> plays a critical role in the specification of the
inflorescence meristem and inflorescence architecture [<xref ref-type="bibr" rid="B54">54</xref>],[<xref ref-type="bibr" rid="B55">55</xref>]. This role seems to be conserved in other plant species [<xref ref-type="bibr" rid="B56">56</xref>] likely through a conserved regulatory pathway [<xref ref-type="bibr" rid="B24">24</xref>]. In grapevine, the previous identification of misexpression of the
<italic>Arabidopsis</italic> homolog <italic>VvTFL1A</italic> as the molecular cause of the
reiteration of reproductive meristems (RRM) mutant [<xref ref-type="bibr" rid="B26">26</xref>], also supported the possible conservation of its biological function in this
species in agreement with previous results [<xref ref-type="bibr" rid="B57">57</xref>],[<xref ref-type="bibr" rid="B58">58</xref>]. Phenotypic characterization of the RRM plants showed that <italic>VvTFL1A</italic>overexpression was related to a delay in the time of anthesis and to an increase in the
size and branching pattern of the inflorescences [<xref ref-type="bibr" rid="B26">26</xref>], similar to the effects of <italic>TFL1</italic> overexpression in transgenic
Arabidopsis [<xref ref-type="bibr" rid="B21">21</xref>]. To provide additional evidence on the involvement of <italic>VvTFL1A</italic> in
natural variation for flowering time and inflorescence development and to identify
nucleotide sequence polymorphisms that could be partially responsible for those traits
in grapevine, a genetic diversity analysis of this gene sequence and genetic association
studies with those traits were carried out.</p><p>Nucleotide variations for <italic>VvTFL1A</italic> in the grapevine core collection analysed is
relatively high with an average of one polymorphic site every 50 nucleotides. However,
only five out of the 70 polymorphisms detected are located in exonic regions and only
three of them result in non-synonymous amino acid substitutions. This result is in
agreement with the slight negative Tajima’s D values observed along
<italic>VvTFL1A</italic> coding sequences and suggests that the protein structure admits few
variations. Reduction in overall level of nucleotide variation was also reported for the
Arabidopsis <italic>TFL1</italic> gene when compared with other flowering genes [<xref ref-type="bibr" rid="B59">59</xref>]. Among the three non-synonymous polymorphisms identified in <italic>VvTFL1A</italic>,
W13, located in first exon, had a very low frequency and was not considered for the
association analyses. The two other, W1087 and M1094, are located in the fourth exon in
a region of the protein responsible for the functional divergence between FT and TFL1 [<xref ref-type="bibr" rid="B60">60</xref>]; although the substituted amino acids do not correspond to conserved residues [<xref ref-type="bibr" rid="B60">60</xref>] and the SNP did not associate with inflorescence related traits under
single-locus models. However, W1087 was selected by the multi-locus mixed-model analysis
to explain part of flowering time variation together with Ins883 suggesting a possible
functional effect of this SNP in this trait. Regarding the 17 polymorphisms found in
intron regions, two INDEL (Ins422 and Ins883) showed significant association with
flowering and cluster trait variation. INDEL Ins422 is located in intron 2 and
corresponds to a microsatellite sequence of GA repetitions; while INDEL Ins883 is
located in intron 3 and corresponds to a G nucleotide repetition. The 48 remaining
<italic>VvTFL1A</italic> polymorphisms identified in the core collection were located
upstream of the translation start codon and included four INDEL. No traces of the
<italic>Hatvine1-rrm</italic> transposon were detected in the promoter of <italic>VvTFL1A</italic> in
the whole core collection which demonstrates the specificity of the insertion event
causing the Carignan RRM mutant phenotype [<xref ref-type="bibr" rid="B26">26</xref>].</p><p>Nucleotide polymorphisms in <italic>VvTFL1A</italic> LD blocks that discriminate the three
haplogroups displayed differential association with cluster traits under linear
regression models. Among all traits analysed, polymorphic sites characteristic of HGA
and HGC haplogroups explained part of the phenotypic variation for flowering time, berry
weight and cluster width. In the same way, polymorphisms specific of HGB associated with
cluster width as well as polymorphisms from HGA. These results suggest that variation at
<italic>VvTFL1A</italic> has an effect on flowering time, berry weight and cluster width with
different alleles having differential effects on the traits. Interestingly, both
flowering time delay and cluster width increase were observed in the phenotypic
characterization of the RRM somatic variant related to <italic>VvTFL1A</italic> overexpression.
Unfortunately, berry size was not measured in that study [<xref ref-type="bibr" rid="B26">26</xref>].</p><p>Among all the polymorphic sites tested, insertion Ins883 discriminating HGA from HGB and
HGC explained alone part of flowering time, berry weight and cluster width variations.
According to the multi-locus analysis, Ins833 explained up to 16%, 13% and 25% of
flowering time, cluster width and berry weight variation in the best models, being the
only polymorphism contributing to berry weight variation. INDEL occurring in
functionally important regions of genes could affect gene function, through gene
expression modification [<xref ref-type="bibr" rid="B61">61</xref>] or RNA structure alterations [<xref ref-type="bibr" rid="B62">62</xref>]. However, a preliminary <italic>VvTLF1A</italic> RT qPCR expression analysis carried
out in young inflorescences of the cultivars of the core collection did not reveal any
association between gene expression variation and the <italic>VvTFL1A</italic> polymorphisms
(data not shown). Likewise, no clear correlation (Pearson’s r <0.28) between
<italic>VvTFL1A</italic> expression and phenotypic traits was identified (data not shown).
Nevertheless, these negative results do not discard a possible role of this intron
sequences in transcriptional or posttranscriptional processes given the difficulties in
carrying out transcriptional comparisons among different genotypes with different
flowering behaviour. Analysis of maize <italic>TFL1</italic> homologs expression in different
tissues and developmental stages showed the existence of differential transcript
processing [<xref ref-type="bibr" rid="B63">63</xref>]. In fact, in a preliminary study, the existence of alternatively spliced RNA
forms was detected for the first and the second introns of <italic>VvTFL1A</italic> (data not
shown). Further research will be required to demonstrate any functional role of this
alternative splicing as well as its relationship with the described <italic>VvTFL1A</italic>Ins833 polymorphism. In any case, further association analyses using larger samples and
specific segregation analyses will be required to confirm the detected associations.</p><p>Together with Ins883, M-196 and W1087 without LD with other <italic>VvTFL1A</italic>polymorphisms explain part of berry weight and flowering time variation according to
multi-locus analysis, respectively. In contrast to Ins883 that discriminates haplotypes
of HGA from those of HGB and HGC, M-196 and W1087 corresponded to mutations
differentiating haplotypes within the HGA haplogroup (Figure <xref ref-type="fig" rid="F4">4</xref>). The M-196 base change located in the proximal promoter and the W1087
non-synonymous substitution in the fourth exon of <italic>VvTFL1A</italic> might represent
relevant structural modifications at the promoter and the protein sequence,
respectively, likely affecting <italic>VvTFL1A</italic> function in a non-redundant way with
Ins883. Moreover, in silico analysis using SIFT program
(<ext-link ext-link-type="uri" xlink:href="http://sift.jcvi.org/">http://sift.jcvi.org/</ext-link>) predicts that substitution of T by S at position
144 of the VvTFL1A sequence affects protein function with a score of 0.04 based on the
alignment of 240 closely related sequences.</p><p><italic>VvTFL1A</italic> haplotype network differentiates three haplogroups of closely related
haplotypes. Each HG is represented by a high frequency haplotype, haplotypes 32 for HGA,
3 for HGB and haplotype 60 from HGC. Consistent with the results of the association
analyses, individuals containing haplotype 32 of HGA, exhibited late flowering, large
cluster width and larger berries. Interestingly, most of the cultivars of K1 and K3
classified to table or table/wine uses, characterized by these phenotypic features [<xref ref-type="bibr" rid="B6">6</xref>], present HGA haplotypes. This relationship is also true for accessions
carrying the recombinant haplotype 18. Indeed, haplotype 18 contains Ins883 insertion
present in HGA haplotypes and mostly present in Eastern table cultivars belonging to K1
and K3 genetic groups. The fact that cultivars carrying haplotype 18 display late
flowering, large cluster width and larger berries supports a clear relationship between
Ins883 polymorphism and the eastern table cluster characteristics. In contrast,
individuals containing haplotype 60 of HGC with Ins422 insertion exhibited early
flowering, shorter cluster width and smaller berries. Consistently, HGC haplotypes are
enriched in Western wine grape cultivars mostly belonging to K2 genetic group, which are
known to display those cluster and berry features [<xref ref-type="bibr" rid="B6">6</xref>]. Finally, HGB haplotypes do not contain Ins422 or Ins883 insertions. The
phenotype of individuals containing haplotype 3 (most frequent within HGB) is similar to
some extent to that of cultivars carrying haplotype 60 (HGC). Consistently with this
phenotype, HGB haplotypes are mostly present in cultivars for wine use. Because no
homozygous individuals were observed for haplotype 60 in the core collection, the
phenotypic effect of this haplotype is supposed to be much stronger in homozygous state,
which suggests that haplotype 60, related to extreme phenology and cluster
characteristics, could be less favored in cultivars in homozygous state than haplotype
3. Interestingly, partial sequencing of <italic>VvTFL1A</italic> in 20 <italic>V.v</italic> ssp.
<italic>sylvestris</italic> plants from the Iberian Peninsula identified wild haplotypes
similar to haplotype 60 and belonging to HGC (data not shown). These data could indicate
a western origin for haplotypes of HGC.</p></sec><sec sec-type="conclusions"><title>Conclusions</title><p>Three major <italic>VvTFL1A</italic> haplogroups were identified in cultivated grapevines based
on the presence of three main polymorphism LD blocks. These haplogroups are associated
to characteristic phenotypic values for flowering time, cluster width and berry size.
Phenotypic differences between <italic>VvTFL1A</italic> haplogroups are consistent with the
classification of grapevine phenotypic diversity in three different morphotypes proposed
by Negrul [<xref ref-type="bibr" rid="B12">12</xref>] and could result from the use of different genetic pools in grapevine
domestication and/or the existence of different selection pressures on the development
of table and wine cultivars. Polymorphic markers identifying haplogroups can also be
relevant in marker-assisted breeding programs addressing the improvement of cluster
structure and berry size.</p></sec><sec><title>Competing interests</title><p>The authors declare that they have no competing interests.</p></sec><sec><title>Authors’ contributions</title><p>LF, PT, LT and JMM-Z conceived the study. LLC, TL, JMB, SL and PT created and
characterized the core collection. LF and GB generated and characterized the sequence
data. LF, LLC, JT, AFL analysed the data. LF and JMM-Z wrote the paper with the input of
all authors. All authors read and approved the final manuscript.</p></sec><sec><title>Additional files</title></sec><sec sec-type="supplementary-material"><title>Supplementary Material</title><supplementary-material content-type="local-data" id="S1"><caption><title>Additional file 1:</title><p><bold>List of the 140 individuals of the core collection used in this study.</bold>Variety name, pedigrees when available, bred cultivars and classification
according to origin and use are indicated. Classification of individuals
according to K1, K2, K3 and admixed groups is described (see materials and
methods section) as well as haplotype combination and corresponding
haplogroups. [N.D. not determined].</p></caption><media xlink:href="s12870-014-0209-3-S1.xls"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S2"><caption><title>Additional file 2:</title><p>Principal component analysis of phenotypic data.</p></caption><media xlink:href="s12870-014-0209-3-S2.jpeg"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S3"><caption><title>Additional file 3:</title><p>Phenotypic value presented by the 140 individuals of the core collection for
the 10 traits analysed in this study.</p></caption><media xlink:href="s12870-014-0209-3-S3.xls"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S4"><caption><title>Additional file 4:</title><p><bold>Distributions of the ten phenotypic traits analysed in the core
collection.</bold> Red line corresponds to the expected normal
distribution.</p></caption><media xlink:href="s12870-014-0209-3-S4.jpeg"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S5"><caption><title>Additional file 5:</title><p><bold>Genotype of the 140 core collection accessions for the 70 polymorphisms
of</bold><bold><italic>VvTFL1A.</italic></bold> The standart IUB’s nomenclature for nucleic acid has been used to
code SNPs. For INDEL A = deletion, C = insertion,
M = heterozygous, and for triallelic microsatellites third allele
has been codify as T. [n/a = not available].</p></caption><media xlink:href="s12870-014-0209-3-S5.xls"><caption><p>Click here for file</p></caption></media></supplementary-material><supplementary-material content-type="local-data" id="S6"><caption><title>Additional file 6:</title><p><bold>Sequences of the 53 haplotypes found for the</bold><bold><italic>VvTFL1A</italic></bold><bold>gene.</bold> Only polymorphic sites are indicated. Frequency and recombinant
haplotypes are indicated.</p></caption><media xlink:href="s12870-014-0209-3-S6.xls"><caption><p>Click here for file</p></caption></media></supplementary-material></sec></body><back><sec><title>Acknowledgments</title><p>We would like to thank Dr Javier Ibanez and Dr Stéphanie Mariette for helpful
discussions; Virginia Rodriguez for her assistance for DNA extraction; Dr Carlos
Alonso Blanco for his helpful comments and critical reading of the manuscript; and Dr
Vincent Segura is acknowledged for assistance using MLMM software and critical
reading of the manuscript. This work was funded by grant BIO2008-03892 and
BIO2011-026229 from the MICINN and MINECO of Spain to JMM-Z. Networking activities
were also funded by COST Action FA1003 “East–west Collaboration for
Grapevine Diversity Exploration and Mobilization of Adaptive Traits for
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