P337
Detection of QTLs Controlling Time to First Anthesis in Phaseolus vulgaris L

Date: Monday, January 13, 2014
Room: Grand Exhibit Hall
Mehul Bhakta , University of Florida, Gainesville, FL
Jose Clavijo , Agronomy Department, University of Florida, Gainesville, FL
Li Zhang , University of Florida, Gainesville, FL
Subodh Acharya , Dept. Agri and Biol Engg, University of Florida, Gainesville, FL
Raphael Colbert , Plant Sciences - North Dakota State University
James Jones , University of Florida, Gainesville, FL
Melanie Correll , University of Florida, Gainesville, FL
Salvador Gezan , University of Florida, Gainesville, FL
Kenneth Boote , University of Florida, Gainesville, FL
James Beaver , University of Puerto Rico, PR
A Gonzalez , University of Puerto Rico, PR
I Rao , CIAT-International Center for Tropical Agriculture, Medley, FL
Stephen E. Beebe , CIAT-International Center for Tropical Agriculture, Medley, FL
Juan Osorno , Dept of Plant Sciences, North Dakota State University, Fargo, ND
J Ricaurte , CIAT-International Center for Tropical Agriculture, Medley, FL
Elvin Roman-Paoli , University of Puerto Rico, Mayaguez, PR
Carlos Eduardo Vallejos , University of Florida, Gainesville, FL
Fine tuning the timing of transition from vegetative and reproductive stages to suit specific environments can significantly increase yields. This can be accomplished by identifying genes that control rates of development, particularly those that are responsive to environmental factors.  The aim of this study was to identify major QTL controlling time to first anthesis (TFA) in common beans. To reach our goal, we phenotyped a RIL population [Mesoamerican x Andean] comprised of 188 individuals for TFA at five different sites with contrasting temperatures and photoperiod regimes. To facilitate mapping process, we build a dense SNP-based linkage map (1.7cM) via the genotyping-by-sequencing approach. TFA (calendar days) and genotype data allowed us to map seven QTLs regulating time to TFA in our population, some of these were site specific. We further converted the calendar days to growing degree days (GDD) to normalize temperature effects on the rate of development. GDD-based QTL analysis allowed us to identify QTLs controlling developmental rates under an optimal growth environment, as well as QTLs that control developmental rates as a function of environmental factors.