INVESTIGADORES
GARBUS Ingrid
congresos y reuniones científicas
Título:
Identification Of Genes And Genomic Regions Associated To Color And Gluten Strength In Durum Wheat
Autor/es:
INGRID GARBUS; VERONICA CONTI; WENJUN ZHANG; AURORA M. PICCA; PABLO RONCALLO; PATRICIA GOMEZ; PAVAN CHAND AKKIRAJU; MOIRANO NATALIA; LILIANA WEHRHAHNE; CARLOS JENSEN; RUBEN MIRANDA; JOSE H. BARIFFI; CARRERA ALICIA; CERVIGNI GERARDO; MARCELO HELGUERA; ECHENIQUE VIVIANA
Lugar:
San Diego, CA
Reunión:
Congreso; Plant & Animal Genomes XVI Conference; 2008
Institución organizadora:
PAG
Resumen:
The most important traits related to pasta and semolina quality in durum wheat are gluten strength and pasta color. Using a RIL mapping population derived from cv. Kofa (excellent pasta quality) and the line UC1113 (intermediate pasta quality) lipoxygenase genes Lpx-2, Lpx-3 and two copies of Lpx-1 (Lpx-B1.1 and Lpx-B.2) were mapped and genomic regions associated to pasta and semolina color were identified. Exploring a BAC library of tetraploid wheat these three Lpx genes were identified. Lpx-B1.1 and Lpx-B1.2 loci do not seem to be linked in any clone, while both, independently, were frequently found linked to Lpx-3. This suggests that Lpx-B1.1 and Lpx-B1.2 loci are not tightly linked and Lpx-3 is probably in an intermediate position between them or a tandem duplication of Lpx-1 and Lpx-3 loci exits. In order to map QTLs associated to gluten strength, the same population was evaluated in three locations from Argentina, in 2006. The interaction genotype x environment was significant for both SDS and total grain protein content. QTLs were mapped using CIM method on a framework of 240 molecular markers map of 1373,9 cM length. Two QTLs were mapped for protein content in Barrow (1B, R2 = 20.30% and 7B, R2 = 16.51%), one in Cabildo (4A, R2 = 20.46%) and one in Balcarce (3B, R2 = 29.45%). For SDS one QTL was identified (1B) consistently in the three locations, explaining approximately 30% of phenotypic variance in each environment. Flanking markers of these QTLs could be efficient to select superior genotypes for the mentioned traits.