Abstract

Climate change and global population increase are two converging forces that will jointly challenge researchers to design programs that ensure crop production systems meet the world's food demand. Climate change will potentially reduce productivity while a global population increase will require more food. If productivity is not improved for future climatic conditions, food insecurity may foster major economic and political uncertainty. Given the importance of grain legumes in general - common bean (Phaseolus vulgaris L.) in particular - a workshop entitled 'Improving Tolerance of Common Bean to Abiotic Stresses' was held with the goal of developing an interdisciplinary research agenda designed to take advantage of modern genotyping and breeding approaches that are coupled with large scale phenotyping efforts to improve common bean. Features of the program included a multinational phenotyping effort to evaluate the major common bean core germplasm collections and appropriate genetic populations. The phenotyping effort will emphasise the response of root and shoot traits to individual and combined stress conditions. These populations would also be genotyped using newly emerging high density single nucleotide polymorphism (SNP) marker arrays or next generation sequencing technology. Association analysis of the core collections aims to identify key loci associated with the response to the stress conditions. Companion bi-parental quantitative trait loci (QTL) experiments will act as confirmation experiments for the association analysis. The upcoming release of the genome sequence of common bean will be leveraged by utilising population genomic approaches to discover genomic regions that differentiate stress-responsive and non-responsive genotypes. The genome sequence will also enable global gene expression studies that will highlight specific molecular-based stress responses. This collective knowledge will inform the selection of parental lines to improve the efficiency of common bean improvement programs.

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