Association mapping of candidate genes for QTLs for adaptation to environment, quality and yield in argentinean bread wheat cultivars.

BASILE S.M.L.; VANZETTI L.S.; DALLA VALLE H.R; TOGNETTI J.A.; MARTÍNEZ M.; HELGUERA M.; ROGERS W. J.

Toledo

Congreso; XXI Reunión de la Sociedad Española de Fisiología Vegetal y XIV Congreso Hispano-Luso de Fisiología Vegetal; 2015

Sociedad Española de Fisiología Vegetal

According to Gupta et al. (2005), association mapping consists on the identification of significant associations between molecular markers and the genes involved in the control of a quantitative trait, and utilises linkage disequilibrium, understood as the non-random association of two markers, of two genes/QTL or of a marker and a gene/QTL, that can have various causes involving linkage and/or population phenomena such as migration, self-fertilisation and selection (Flint-Garcia et al., 2003).The objective of this work was to perform associative mapping of quantitative trait loci (QTLs) related to components of adaptation, yield and quality in wheat, using a set of genes of known function in order to propose candidate genes for these QTLs.During 2014 a field trial was performed at the Experimental Farm of the Faculty of Agronomy of the UNCPBA (Long.: 59º50´W and 132 m Lat.: 36º45´S) Province of Buenos Aires, Argentina. The trial consisted of a random complete blocks design, in which 102 Argentine bread wheat cultivars from a mapping population developed at INTA Marcos Juárez were grown and phenotypically evaluated.The phenotypic data were linked with genotypic data via a mixed linear model using the programme TASSEL (Trait Analysis by Association, Evolution and Linkage), version 3.0.168, applied to 20 candidate genes (Glu-A1, Glu-B1, Glu-D1, Lr34, Lr24, Lr10, Vrn-A1, Vrn-B1, Vrn-D1, Ppd-D1, Ppd-B1, Rht-B1, Rht-D1, Pina-D1, Glu-A3, Wx-A1, Wx-B1, Vp1-B3, Ppo-D1 and Ppo-A1).Phenotypic variables evaluated included time to heading, to anthesis and to maturity, grain filling phase length, nutrient sufficiency index (N) in the flag and penultimate leaves, spikes per m2, harvest index, fertile tiller number per m2, plant height, spike length, grain number per m2, thousand grain weight, grain number per spike, number of total, fertile and sterile spikelets, fresh and dry biomass, spike fertility index and protein content, amongst others.Statistical analysis is currently being carried out and is expected to find several loci with direct effects on the phenotypic variables evaluated that will help identifying candidate genes for better adaptation and higher yield and quality