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        <dc:title>Interpreting genotype × environment interaction in tropical maize using linked molecular markers and environmental covariables</dc:title>
        <dc:creator>Crossa, J</dc:creator>
        <dc:creator>Vargas, M</dc:creator>
        <dc:creator>Eeuwijk, F A van</dc:creator>
        <dc:creator>Jiang, C</dc:creator>
        <dc:creator>Edmeades, G O</dc:creator>
        <dc:creator>Hoisington, D A</dc:creator>
        <dc:subject>Genetics and Genomics</dc:subject>
        <dc:description>An understanding of the genetic and environmental&#13;
basis of genotype´environment interaction (GEI)&#13;
is of fundamental importance in plant breeding. In mapping&#13;
quantitative trait loci (QTLs), suitable genetic populations&#13;
are grown in different environments causing&#13;
QTLs´environment interaction (QEI). The main objective&#13;
of the present study is to show how Partial Least&#13;
Squares (PLS) regression and Factorial Regression (FR)&#13;
models using genetic markers and environmental covariables&#13;
can be used for studying QEI related to GEI. Biomass&#13;
data were analyzed from a multi-environment trial&#13;
consisting of 161 lines from a F3:4 maize segregating&#13;
population originally created with the purpose of mapping&#13;
QTLs loci and investigating adaptation differences&#13;
between highland and lowland tropical maize. PLS and&#13;
FR methods detected 30 genetic markers (out of 86) that&#13;
explained a sizeable proportion of the interaction of&#13;
maize lines over four contrasting environments involving&#13;
two low-altitude sites, one intermediate-altitude site, and&#13;
one high-altitude site for biomass production. Based on a&#13;
previous study, most of the 30 markers were associated&#13;
with QTLs for biomass and exhibited significant QEI. It&#13;
was found that marker loci in lines with positive GEI for&#13;
the highland environments contained more highland alleles,&#13;
whereas marker loci in lines with positive GEI for&#13;
intermediate and lowland environments contained more&#13;
lowland alleles. In addition, PLS and FR models identified maximum temperature as the most-important environmental&#13;
covariable for GEI. Using a stepwise variable&#13;
selection procedure, a FR model was constructed for&#13;
GEI and QEI that exclusively included cross products&#13;
between genetic markers and environmental covariables.&#13;
Higher maximum temperature in low- and intermediatealtitude&#13;
sites affected the expression of some QTLs,&#13;
while minimum temperature affected the expression of&#13;
other QTLs.</dc:description>
        <dc:publisher>Springer Verlag</dc:publisher>
        <dc:date>1999</dc:date>
        <dc:type>Article</dc:type>
        <dc:type>PeerReviewed</dc:type>
        <dc:format>application/pdf</dc:format>
        <dc:language>en</dc:language>
        <dc:identifier>http://oar.icrisat.org/5745/1/TheorApplGenet_99_611%E2%80%93625_1999.pdf</dc:identifier>
        <dc:identifier>  Crossa, J and Vargas, M and Eeuwijk, F A van and Jiang, C and Edmeades, G O and Hoisington, D A  (1999) Interpreting genotype × environment interaction in tropical maize using linked molecular markers and environmental covariables.  TAG Theoretical and Applied Genetics, 99 (3-4).  pp. 611-625.  ISSN 1432-2242     </dc:identifier>
        <dc:relation>http://dx.doi.org/10.1007/s001220051276 </dc:relation></oai_dc:dc>
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