dc.creatorPastina, M. M.
dc.creatorMalosetti, M.
dc.creatorGazaffi, R.
dc.creatorMollinari, M.
dc.creatorMargarido, G. R. A.
dc.creatorOliveira, K. M.
dc.creatorPinto, L. R.
dc.creatorSouza, A. P.
dc.creatorvan Eeuwijk, F. A.
dc.creatorGarcia, A. A. F.
dc.date.accessioned2013-08-15T18:07:50Z
dc.date.accessioned2018-07-04T15:54:51Z
dc.date.available2013-08-15T18:07:50Z
dc.date.available2018-07-04T15:54:51Z
dc.date.created2013-08-15T18:07:50Z
dc.date.issued2012
dc.identifierTHEORETICAL AND APPLIED GENETICS, NEW YORK, v. 124, n. 5, supl. 4, Part 1, pp. 835-849, MAR, 2012
dc.identifier0040-5752
dc.identifierhttp://www.producao.usp.br/handle/BDPI/32568
dc.identifier10.1007/s00122-011-1748-8
dc.identifierhttp://dx.doi.org/10.1007/s00122-011-1748-8
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1629128
dc.description.abstractSugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.
dc.languageeng
dc.publisherSPRINGER
dc.publisherNEW YORK
dc.relationTHEORETICAL AND APPLIED GENETICS
dc.rightsCopyright SPRINGER
dc.rightsclosedAccess
dc.subjectPOLYPLOIDS
dc.subjectOUTCROSSING SPECIES
dc.subjectINTEGRATED LINKAGE MAP
dc.subjectQTL X E
dc.titleA mixed model QTL analysis for sugarcane multiple-harvest-location trial data
dc.typeArtículos de revistas


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