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Identification of QTLs for grain yield and grain-related traits of maize (Zeamays L.) using an AFLP map, different testers, and cofactor analysis
Authors:P. Ajmone Marsan  C. Gorni  A. Chittò  R. Redaelli  R. van Vijk  P. Stam  M. Motto
Affiliation:(1) Istituto Sperimentale per la Cerealicoltura, Via Stezzano 24, 24126 Bergamo, Italy e-mail: motto@tin.it Tel.: 0039-035 313132, Fax: 0039-035 316054, IT;(2) Keygene N.V. Agro Business Park 90, P.O. Box 216, 6700 AE Wageningen, The Netherlands, NL;(3) Laboratory of Plant Breeding, Department of Plant Sciences, Wageningen Agricultural University, P.O. Box 386, 6700 AJ Wageningen, The Netherlands, NL
Abstract:We exploited the AFLP®1(AFLP® is a registered trademark of Keygene, N.V.) technique to map and characterise quantitative trait loci (QTLs) for grain yield and two grain-related traits of a maize segregating population. Two maize elite inbred lines were crossed to produce 229 F2 individuals which were genotyped with 66 RFLP and 246 AFLP marker loci. By selfing the F2 plants 229 F3 lines were produced and subsequently crossed to two inbred testers (T1 and T2). Each series of testcrosses was evaluated in field trials for grain yield, dry matter concentration, and test weight. The efficiency of generating AFLP markers was substantially higher relative to RFLP markers in the same population, and the speed at which they were generated showed a great potential for application in marker-assisted selection. AFLP markers covered linkage group regions left uncovered by RFLPs; in particular at telomeric regions, previously almost devoided of markers. This increase of genome coverage afforded by the inclusion of the AFLPs revealed new QTL locations for all the traits investigated and allowed us to map telomeric QTLs with higher precision. The present study has also provided an opportunity to compare simple (SIM) and composite interval mapping (CIM) for QTL analysis. Our results indicated that the method of CIM employed in this study has greater power in the detection of QTLs, and provided more precise and accurate estimates of QTL positions and effects than SIM. For all traits and both testers we detected a total of 36 QTLs, of which only two were in common between testers. This suggested that the choice of a tester for identifying QTL alleles for use in improving an inbred is critical and that the expression of QTL alleles identified may be tester-specific.
Keywords:  AFLP markers  QTL mapping  Testcross performance  Composite interval mapping  Zea mays L.
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