Genomics-assisted breeding in fruit trees
Identifieur interne : 000155 ( Pmc/Checkpoint ); précédent : 000154; suivant : 000156Genomics-assisted breeding in fruit trees
Auteurs : Hiroyoshi Iwata [Japon] ; Mai F. Minamikawa [Japon] ; Hiromi Kajiya-Kanegae [Japon] ; Motoyuki Ishimori [Japon] ; Takeshi Hayashi [Japon]Source :
- Breeding Science [ 1344-7610 ] ; 2016.
Abstract
Recent advancements in genomic analysis technologies have opened up new avenues to promote the efficiency of plant breeding. Novel genomics-based approaches for plant breeding and genetics research, such as genome-wide association studies (GWAS) and genomic selection (GS), are useful, especially in fruit tree breeding. The breeding of fruit trees is hindered by their long generation time, large plant size, long juvenile phase, and the necessity to wait for the physiological maturity of the plant to assess the marketable product (fruit). In this article, we describe the potential of genomics-assisted breeding, which uses these novel genomics-based approaches, to break through these barriers in conventional fruit tree breeding. We first introduce the molecular marker systems and whole-genome sequence data that are available for fruit tree breeding. Next we introduce the statistical methods for biparental linkage and quantitative trait locus (QTL) mapping as well as GWAS and GS. We then review QTL mapping, GWAS, and GS studies conducted on fruit trees. We also review novel technologies for rapid generation advancement. Finally, we note the future prospects of genomics-assisted fruit tree breeding and problems that need to be overcome in the breeding.
Url:
DOI: 10.1270/jsbbs.66.100
PubMed: 27069395
PubMed Central: 4780794
Affiliations:
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<author><name sortKey="Iwata, Hiroyoshi" sort="Iwata, Hiroyoshi" uniqKey="Iwata H" first="Hiroyoshi" last="Iwata">Hiroyoshi Iwata</name>
<affiliation wicri:level="1"><nlm:aff id="af1-66_100"><institution>Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo</institution>
,<addr-line>1-1-1 Yayoi, Bunkyo, Tokyo 113-8657</addr-line>
,<country>Japan</country>
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<country xml:lang="fr">Japon</country>
<wicri:regionArea># see nlm:aff country strict</wicri:regionArea>
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<author><name sortKey="Minamikawa, Mai F" sort="Minamikawa, Mai F" uniqKey="Minamikawa M" first="Mai F." last="Minamikawa">Mai F. Minamikawa</name>
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,<addr-line>1-1-1 Yayoi, Bunkyo, Tokyo 113-8657</addr-line>
,<country>Japan</country>
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<country xml:lang="fr">Japon</country>
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<author><name sortKey="Kajiya Kanegae, Hiromi" sort="Kajiya Kanegae, Hiromi" uniqKey="Kajiya Kanegae H" first="Hiromi" last="Kajiya-Kanegae">Hiromi Kajiya-Kanegae</name>
<affiliation wicri:level="1"><nlm:aff id="af1-66_100"><institution>Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo</institution>
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<country xml:lang="fr">Japon</country>
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<author><name sortKey="Ishimori, Motoyuki" sort="Ishimori, Motoyuki" uniqKey="Ishimori M" first="Motoyuki" last="Ishimori">Motoyuki Ishimori</name>
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,<addr-line>1-1-1 Yayoi, Bunkyo, Tokyo 113-8657</addr-line>
,<country>Japan</country>
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<country xml:lang="fr">Japon</country>
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<author><name sortKey="Hayashi, Takeshi" sort="Hayashi, Takeshi" uniqKey="Hayashi T" first="Takeshi" last="Hayashi">Takeshi Hayashi</name>
<affiliation wicri:level="1"><nlm:aff id="af2-66_100"><institution>Agroinfomatics Division, NARO Agricultural Research Center (NARC)</institution>
,<addr-line>3-1-1 Kannondai, Tsukuba, Ibaraki 305-8666</addr-line>
,<country>Japan</country>
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<country xml:lang="fr">Japon</country>
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Genomics-assisted breeding in fruit trees</title>
<author><name sortKey="Iwata, Hiroyoshi" sort="Iwata, Hiroyoshi" uniqKey="Iwata H" first="Hiroyoshi" last="Iwata">Hiroyoshi Iwata</name>
<affiliation wicri:level="1"><nlm:aff id="af1-66_100"><institution>Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo</institution>
,<addr-line>1-1-1 Yayoi, Bunkyo, Tokyo 113-8657</addr-line>
,<country>Japan</country>
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<country xml:lang="fr">Japon</country>
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<author><name sortKey="Minamikawa, Mai F" sort="Minamikawa, Mai F" uniqKey="Minamikawa M" first="Mai F." last="Minamikawa">Mai F. Minamikawa</name>
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,<addr-line>1-1-1 Yayoi, Bunkyo, Tokyo 113-8657</addr-line>
,<country>Japan</country>
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<country xml:lang="fr">Japon</country>
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<author><name sortKey="Kajiya Kanegae, Hiromi" sort="Kajiya Kanegae, Hiromi" uniqKey="Kajiya Kanegae H" first="Hiromi" last="Kajiya-Kanegae">Hiromi Kajiya-Kanegae</name>
<affiliation wicri:level="1"><nlm:aff id="af1-66_100"><institution>Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo</institution>
,<addr-line>1-1-1 Yayoi, Bunkyo, Tokyo 113-8657</addr-line>
,<country>Japan</country>
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<country xml:lang="fr">Japon</country>
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<author><name sortKey="Ishimori, Motoyuki" sort="Ishimori, Motoyuki" uniqKey="Ishimori M" first="Motoyuki" last="Ishimori">Motoyuki Ishimori</name>
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,<addr-line>1-1-1 Yayoi, Bunkyo, Tokyo 113-8657</addr-line>
,<country>Japan</country>
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<country xml:lang="fr">Japon</country>
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<author><name sortKey="Hayashi, Takeshi" sort="Hayashi, Takeshi" uniqKey="Hayashi T" first="Takeshi" last="Hayashi">Takeshi Hayashi</name>
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,<addr-line>3-1-1 Kannondai, Tsukuba, Ibaraki 305-8666</addr-line>
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<country xml:lang="fr">Japon</country>
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<front><div type="abstract" xml:lang="en"><p>Recent advancements in genomic analysis technologies have opened up new avenues to promote the efficiency of plant breeding. Novel genomics-based approaches for plant breeding and genetics research, such as genome-wide association studies (GWAS) and genomic selection (GS), are useful, especially in fruit tree breeding. The breeding of fruit trees is hindered by their long generation time, large plant size, long juvenile phase, and the necessity to wait for the physiological maturity of the plant to assess the marketable product (fruit). In this article, we describe the potential of genomics-assisted breeding, which uses these novel genomics-based approaches, to break through these barriers in conventional fruit tree breeding. We first introduce the molecular marker systems and whole-genome sequence data that are available for fruit tree breeding. Next we introduce the statistical methods for biparental linkage and quantitative trait locus (QTL) mapping as well as GWAS and GS. We then review QTL mapping, GWAS, and GS studies conducted on fruit trees. We also review novel technologies for rapid generation advancement. Finally, we note the future prospects of genomics-assisted fruit tree breeding and problems that need to be overcome in the breeding.</p>
</div>
</front>
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<pmc article-type="review-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Breed Sci</journal-id>
<journal-id journal-id-type="iso-abbrev">Breed. Sci</journal-id>
<journal-title-group><journal-title>Breeding Science</journal-title>
</journal-title-group>
<issn pub-type="ppub">1344-7610</issn>
<issn pub-type="epub">1347-3735</issn>
<publisher><publisher-name>Japanese Society of Breeding</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">27069395</article-id>
<article-id pub-id-type="pmc">4780794</article-id>
<article-id pub-id-type="doi">10.1270/jsbbs.66.100</article-id>
<article-id pub-id-type="publisher-id">66_100</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Review</subject>
</subj-group>
</article-categories>
<title-group><article-title>Genomics-assisted breeding in fruit trees</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Iwata</surname>
<given-names>Hiroyoshi</given-names>
</name>
<xref ref-type="aff" rid="af1-66_100">1</xref>
<xref rid="c1-66_100" ref-type="corresp">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Minamikawa</surname>
<given-names>Mai F.</given-names>
</name>
<xref ref-type="aff" rid="af1-66_100">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Kajiya-Kanegae</surname>
<given-names>Hiromi</given-names>
</name>
<xref ref-type="aff" rid="af1-66_100">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Ishimori</surname>
<given-names>Motoyuki</given-names>
</name>
<xref ref-type="aff" rid="af1-66_100">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Hayashi</surname>
<given-names>Takeshi</given-names>
</name>
<xref ref-type="aff" rid="af2-66_100">2</xref>
</contrib>
</contrib-group>
<aff id="af1-66_100"><label>1</label>
<institution>Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo</institution>
,<addr-line>1-1-1 Yayoi, Bunkyo, Tokyo 113-8657</addr-line>
,<country>Japan</country>
</aff>
<aff id="af2-66_100"><label>2</label>
<institution>Agroinfomatics Division, NARO Agricultural Research Center (NARC)</institution>
,<addr-line>3-1-1 Kannondai, Tsukuba, Ibaraki 305-8666</addr-line>
,<country>Japan</country>
</aff>
<author-notes><corresp id="c1-66_100"><label>*</label>
Corresponding author (e-mail: <email>aiwata@mail.ecc.u-tokyo.ac.jp</email>
)</corresp>
<fn id="fn1-66_100"><p>Communicated by T. Yamamoto</p>
</fn>
</author-notes>
<pub-date pub-type="ppub"><month>1</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub"><day>1</day>
<month>1</month>
<year>2016</year>
</pub-date>
<volume>66</volume>
<issue>1</issue>
<fpage>100</fpage>
<lpage>115</lpage>
<history><date date-type="received"><day>10</day>
<month>9</month>
<year>2015</year>
</date>
<date date-type="accepted"><day>12</day>
<month>1</month>
<year>2016</year>
</date>
</history>
<permissions><copyright-statement>Copyright © 2016 by JAPANESE SOCIETY OF BREEDING</copyright-statement>
<copyright-year>2016</copyright-year>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by-nc-nd/3.0"><license-p>This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
</license>
</permissions>
<abstract><p>Recent advancements in genomic analysis technologies have opened up new avenues to promote the efficiency of plant breeding. Novel genomics-based approaches for plant breeding and genetics research, such as genome-wide association studies (GWAS) and genomic selection (GS), are useful, especially in fruit tree breeding. The breeding of fruit trees is hindered by their long generation time, large plant size, long juvenile phase, and the necessity to wait for the physiological maturity of the plant to assess the marketable product (fruit). In this article, we describe the potential of genomics-assisted breeding, which uses these novel genomics-based approaches, to break through these barriers in conventional fruit tree breeding. We first introduce the molecular marker systems and whole-genome sequence data that are available for fruit tree breeding. Next we introduce the statistical methods for biparental linkage and quantitative trait locus (QTL) mapping as well as GWAS and GS. We then review QTL mapping, GWAS, and GS studies conducted on fruit trees. We also review novel technologies for rapid generation advancement. Finally, we note the future prospects of genomics-assisted fruit tree breeding and problems that need to be overcome in the breeding.</p>
</abstract>
<kwd-group><kwd>genome-wide association study (GWAS)</kwd>
<kwd>genomic selection (GS)</kwd>
<kwd>pseudo-testcross strategy</kwd>
<kwd>statistical model</kwd>
<kwd>generation advancement technology</kwd>
</kwd-group>
</article-meta>
</front>
<floats-group><table-wrap id="t1-66_100" orientation="portrait" position="float"><label>Table 1</label>
<caption><p>Summary of genome-wide association studies (GWAS) in fruit trees</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th valign="middle" align="left" rowspan="1" colspan="1">Species</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Population size</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Markers</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Traits</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Statistical models for GWAS</th>
<th valign="middle" align="center" rowspan="1" colspan="1">References</th>
</tr>
</thead>
<tbody><tr><td valign="top" align="left" rowspan="1" colspan="1">Apple (<italic>Malus × domestica</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">1200 seedlings</td>
<td valign="top" align="left" rowspan="1" colspan="1">2500 SNPs</td>
<td valign="top" align="left" rowspan="1" colspan="1">Six traits (fruit firmness, weighted cortical intensity, internal browning, titratable acidity, fruit splitting, bitter pit)</td>
<td valign="top" align="left" rowspan="1" colspan="1">Mixed linear model</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b84-66_100" ref-type="bibr">Kumar <italic>et al</italic>
. (2013)</xref>
</td>
</tr>
<tr><td valign="top" align="left" rowspan="1" colspan="1">Japanese pear (<italic>Pyrus pyrifolia</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">76 cultivars</td>
<td valign="top" align="left" rowspan="1" colspan="1">162 markers (155 SSRs, 4 RAPDSTS, 2 ACC synthase genes, 1 S-RNase gene)</td>
<td valign="top" align="left" rowspan="1" colspan="1">Nine traits (harvest time, resistance to black spot, firmness of fresh, fruit size, fruit shape in longitudinal selection, acid content, total soluble solid content, number of spurs, vigor of tree)</td>
<td valign="top" align="left" rowspan="1" colspan="1">Multilocus Bayesian model</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b71-66_100" ref-type="bibr">Iwata <italic>et al</italic>
. (2013a)</xref>
</td>
</tr>
<tr><td valign="top" align="left" rowspan="1" colspan="1">Peach (<italic>Prunus persica</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">104 landraces</td>
<td valign="top" align="left" rowspan="1" colspan="1">53 SSR markers</td>
<td valign="top" align="left" rowspan="1" colspan="1">10 traits (flesh color around the stone, red pigment in the flesh, flesh texture, flesh adhesion, flesh firmness, fruit weight, chilling requirement, flowering time, ripening time, and fruit development period)</td>
<td valign="top" align="left" rowspan="1" colspan="1">General linear model</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b18-66_100" ref-type="bibr">Cao <italic>et al</italic>
. (2012)</xref>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="tfn1-66_100"><p>SNP, single nucleotide polymorphism; SSR, simple sequence repeat; RAPD-STS, random amplified polymorphic DNA-sequence tagged sites; ACC, 1- aminocyclopropane-1-carboxylate.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="t2-66_100" orientation="portrait" position="float"><label>Table 2</label>
<caption><p>Summary of empirical studies of genomic selection in perennial tree species</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th valign="middle" align="left" rowspan="1" colspan="1">Species</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Population type and size</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Markers</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Traits</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Methods for building prediction models</th>
<th valign="middle" align="center" rowspan="1" colspan="1">Prediction accuracy</th>
<th valign="middle" align="center" rowspan="1" colspan="1">References</th>
</tr>
</thead>
<tbody><tr><td valign="top" align="left" rowspan="1" colspan="1">Apple (<italic>Malus × domestica</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">1120 individuals (seedlings generated from a factorial mating design of four females and two male parents)</td>
<td valign="top" align="left" rowspan="1" colspan="1">2500 SNPs</td>
<td valign="top" align="left" rowspan="1" colspan="1">Six traits (fruit firmness, soluble solids, russet coverage, weighted cortex intensity, astringency, titratable acidity)</td>
<td valign="top" align="left" rowspan="1" colspan="1">rrBLUP, Bayesian LASSO</td>
<td valign="top" align="left" rowspan="1" colspan="1">0.68 to 0.89</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b83-66_100" ref-type="bibr">Kumar <italic>et al.</italic>
(2012b)</xref>
</td>
</tr>
<tr><td valign="top" align="left" rowspan="1" colspan="1">Japanese pear (<italic>Pyrus pyrifolia</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">76 Japanese pear cultivars</td>
<td valign="top" align="left" rowspan="1" colspan="1">162 markers (155 SSRs, 4 RAPD-STS, 2 ACC synthase genes, 1 S-RNase gene)</td>
<td valign="top" align="left" rowspan="1" colspan="1">Nine traits (harvest time, resistance to black spot, firmness of flesh, fruit size, fruit shape in longitudinal section, acid content, total soluble solid content, number of spurs, vigor of tree)</td>
<td valign="top" align="left" rowspan="1" colspan="1">BayesA, BayesB</td>
<td valign="top" align="left" rowspan="1" colspan="1">−0.45 to 0.75</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b71-66_100" ref-type="bibr">Iwata <italic>et al.</italic>
(2013a)</xref>
</td>
</tr>
<tr><td valign="top" align="left" rowspan="1" colspan="1">Oil palm (<italic>Elaeis guineensis</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">262 individuals (two parental populations involved in reciprocal recurrent selection with 131 individuals each)</td>
<td valign="top" align="left" rowspan="1" colspan="1">265 SSR markers</td>
<td valign="top" align="left" rowspan="1" colspan="1">Eight traits (bunch number, average bunch weight, fruit-to-bunch, pulp-to-fruit, kernel-to-fruit, oil-to-pulp ratios, number of fruits per bunch, average fruit weight)</td>
<td valign="top" align="left" rowspan="1" colspan="1">GBLUP, Bayesian LASSO, Bayesian RR, BayesCπ, BayesDπ</td>
<td valign="top" align="left" rowspan="1" colspan="1">−0.41 to 0.94</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b28-66_100" ref-type="bibr">Cros <italic>et al.</italic>
(2015)</xref>
</td>
</tr>
<tr><td valign="top" align="left" rowspan="1" colspan="1">Loblolly pine (<italic>Pinus taeda</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">ca. 800 individuals (seedlings derived by crossing 32 parents in a circular mating design)</td>
<td valign="top" align="left" rowspan="1" colspan="1">4825 SNPs</td>
<td valign="top" align="left" rowspan="1" colspan="1">Two traits at multiple ages (3, 4, and 6 years old for diameter at breast height and 1, 2, 3, 4, and 6 years old for height)</td>
<td valign="top" align="left" rowspan="1" colspan="1">rrBLUP</td>
<td valign="top" align="left" rowspan="1" colspan="1">0.16 to 0.75 (0.63 to 0.75 at 6 years old)</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b115-66_100" ref-type="bibr">M.F.R. Resende <italic>et al.</italic>
(2012a)</xref>
</td>
</tr>
<tr><td valign="top" align="left" rowspan="1" colspan="1">Loblolly pine (<italic>P. taeda</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">951 individuals (seedlings derived by crossing 32 parents in a circular mating design)</td>
<td valign="top" align="left" rowspan="1" colspan="1">4853 SNPs</td>
<td valign="top" align="left" rowspan="1" colspan="1">17 traits (four traits related to growth, six traits related to development, two traits related to disease resistance, five traits related to wood quality)</td>
<td valign="top" align="left" rowspan="1" colspan="1">rrBLUP, BayesA, BayesCπ, Bayesian LASSO, rrBLUP B</td>
<td valign="top" align="left" rowspan="1" colspan="1">0.17 to 0.51</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b114-66_100" ref-type="bibr">M.D. Resende <italic>et al.</italic>
(2012)</xref>
</td>
</tr>
<tr><td valign="top" align="left" rowspan="1" colspan="1">Loblolly pine (<italic>P. taeda</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">149 clones (full-sib progeny derived from 13 crosses)</td>
<td valign="top" align="left" rowspan="1" colspan="1">3406 SNPs</td>
<td valign="top" align="left" rowspan="1" colspan="1">Four traits (height, volume, lignin and cellulose contents)</td>
<td valign="top" align="left" rowspan="1" colspan="1">rrBLUP including both additive and dominance effects</td>
<td valign="top" align="left" rowspan="1" colspan="1">0.30 to 0.83 when 10% of the clones were selected within each cross; 0.56 to 0.68 when 10% of the clones were selected randomly across all crosses</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b149-66_100" ref-type="bibr">Zapata-Valenzuela <italic>et al.</italic>
(2012)</xref>
</td>
</tr>
<tr><td valign="top" align="left" rowspan="1" colspan="1">Loblolly pine (<italic>P. taeda</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">165 clones (full-sib progeny from nine crosses)</td>
<td valign="top" align="left" rowspan="1" colspan="1">3461 SNPs</td>
<td valign="top" align="left" rowspan="1" colspan="1">Two traits (height, volume)</td>
<td valign="top" align="left" rowspan="1" colspan="1">GBLUP</td>
<td valign="top" align="left" rowspan="1" colspan="1">0.55 to 0.74 when 10% were selected within each cross</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b150-66_100" ref-type="bibr">Zapata-Valenzuela <italic>et al.</italic>
(2013)</xref>
</td>
</tr>
<tr><td valign="top" align="left" rowspan="1" colspan="1">Eucalyptus (<italic>E. grandis, E. urophylla</italic>
, <italic>E. globulus</italic>
and their F<sub>1</sub>
hybrids)</td>
<td valign="top" align="left" rowspan="1" colspan="1">820 individuals for one population and 920 for the other</td>
<td valign="top" align="left" rowspan="1" colspan="1">3564 SNPs for one population and 3129 for the other</td>
<td valign="top" align="left" rowspan="1" colspan="1">Four traits (tree circumference, height growth, wood specific gravity, pulp yield)</td>
<td valign="top" align="left" rowspan="1" colspan="1">rrBLUP</td>
<td valign="top" align="left" rowspan="1" colspan="1">0.55 to 0.88</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b114-66_100" ref-type="bibr">M.D. Resende <italic>et al.</italic>
(2012)</xref>
</td>
</tr>
<tr><td valign="top" align="left" rowspan="1" colspan="1">White spruce (<italic>Picea glauca</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">1694 individuals</td>
<td valign="top" align="left" rowspan="1" colspan="1">6385 SNPs</td>
<td valign="top" align="left" rowspan="1" colspan="1">12 traits (cell population, fiber coarseness, crystallite width, wood density, microfibril angle, wood stiffness, ring width, specific fiber surface, cell radial diameter, cell tangential diameter, cell wall thickness, 22-year height)</td>
<td valign="top" align="left" rowspan="1" colspan="1">rrBLUP and rrBLUP with pedigree effects</td>
<td valign="top" align="left" rowspan="1" colspan="1">0.33 to 0.44 when both training and testing data sets share individuals of the same families; 0.13 to 0.28 when training and testing data sets are made up of individuals of different families; −0.05 to 0.13 when families making up the validation data sets are from populations that are not represented in the training data sets</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b8-66_100" ref-type="bibr">Beaulieu <italic>et al.</italic>
(2014a)</xref>
</td>
</tr>
<tr><td valign="top" align="left" rowspan="1" colspan="1">White spruce (<italic>P. glauca</italic>
)</td>
<td valign="top" align="left" rowspan="1" colspan="1">1748 individuals</td>
<td valign="top" align="left" rowspan="1" colspan="1">6932 SNPs</td>
<td valign="top" align="left" rowspan="1" colspan="1">Four traits (average wood density, average microfibril angle, 17-year height, 17-year diameter at breast height)</td>
<td valign="top" align="left" rowspan="1" colspan="1">Bayesian RR, Bayesian LASSO, and those with pedigree effects</td>
<td valign="top" align="left" rowspan="1" colspan="1">0.52 to 0.79 with Bayesian RR when the validation sets were built with individuals within full-sib families and both training and testing sets were from the same breeding group; 0.29 to 0.59 with Bayesian RR when the validation sets were built with full-sib families and both training and testing sets were from the same breeding group</td>
<td valign="top" align="left" rowspan="1" colspan="1"><xref rid="b9-66_100" ref-type="bibr">Beaulieu <italic>et al.</italic>
(2014b)</xref>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="tfn2-66_100"><p>SNP, single nucleotide polymorphism; RR, ridge regression; rrBLUP, random regression best linear unbiased prediction; LASSO, least absolute shrinkage and selection operator; SSR, simple sequence repeat; RAPD-STS, random amplified polymorphic DNA-sequence tagged sites; ACC, 1- aminocyclopropane-1-carboxylate; GBLUP, genomic best linear unbiased prediction.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</floats-group>
</pmc>
<affiliations><list><country><li>Japon</li>
</country>
</list>
<tree><country name="Japon"><noRegion><name sortKey="Iwata, Hiroyoshi" sort="Iwata, Hiroyoshi" uniqKey="Iwata H" first="Hiroyoshi" last="Iwata">Hiroyoshi Iwata</name>
</noRegion>
<name sortKey="Hayashi, Takeshi" sort="Hayashi, Takeshi" uniqKey="Hayashi T" first="Takeshi" last="Hayashi">Takeshi Hayashi</name>
<name sortKey="Ishimori, Motoyuki" sort="Ishimori, Motoyuki" uniqKey="Ishimori M" first="Motoyuki" last="Ishimori">Motoyuki Ishimori</name>
<name sortKey="Kajiya Kanegae, Hiromi" sort="Kajiya Kanegae, Hiromi" uniqKey="Kajiya Kanegae H" first="Hiromi" last="Kajiya-Kanegae">Hiromi Kajiya-Kanegae</name>
<name sortKey="Minamikawa, Mai F" sort="Minamikawa, Mai F" uniqKey="Minamikawa M" first="Mai F." last="Minamikawa">Mai F. Minamikawa</name>
</country>
</tree>
</affiliations>
</record>
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