An effective virus-based gene silencing method for functional genomics studies in common bean

Here we describe the use of a bean pod mottle virus (BPMV)-based vector for silencing of endogenous genes in common bean as well as for protein expression. This BPMV-based vector was originally developed for use in soybean. It has been successfully employed for both protein expression and gene silencing in this species. We tested this vector for applications in common bean by targeting common bean genes encoding nodulin 22 and stearoyl-acyl carrier protein desaturase for silencing. Our results indicate that the BPMV vector can indeed be employed for reverse genetics studies of diverse biological processes in common bean. We also used the BPMV-based vector for expressing the green fluorescent protein (GFP) in common bean and demonstrate stable GFP expression in all common bean tissues where BPMV was detected.The availability of this vector is an important advance for the common bean research community not only because it provides a rapid means for functional studies in common bean, but also because it does so without generating genetically modified plants. Here we describe the detailed methodology and provide essential guidelines for the use of this vector for both gene silencing and protein expression in common bean. The entire VIGS procedure can be completed in 4-5 weeks.Common bean (Phaseolus vulgaris) is the world's most important food legume for direct human consumption in developing countries such as Latin America and Eastern Africa. Although common bean production occurs in a wide range of cropping systems and environments, Latin America with its 8 million hectares in common bean production is the most important region as it accounts for nearly half of the global output [1].Thus far, common bean crop improvement through biotechnological approaches has been limited due to its recalcitrance for genetic transformation. Genetic transformation of common bean has been achieved by using biolistic or Agrobacterium tumefaciens-based methods, but with low efficiency [2-