Strategy for Accelerated Cowpea Genetic Improvement

Cowpea (Vigna unguiculata L. Walp.) is self-pollinating, with one of the smallest genome sizes among legumes (2n = 2× = 22, ~620 Mbp). Cowpea is protein rich, and supplies grain, edible leaves and immature pods, and forage in the semi-arid tropics, mostly for substance farmers. Despite its importance, cowpea remains less exploited due to limited research attention, but interest has increased due to increasing global food and nutrition demand. Past crop genetic improvement was largely through phenotypic selection and recombination of existing natural variation. Genomics, through advances in molecular technologies and statistical capabilities, has begun to enhance plant breeding programs. Effective exploitation of this opportunity, especially in poorly-resourced breeding programs, will require innovative readjustment of breeding designs. With continued reduction in sequencing and genotyping costs, incorporation of genomic information to facilitate traditional breeding is increasingly feasible. Presented here is a conceptual design for cowpea breeding, targeting the stacking of multiple traits of agronomic significance including drought tolerance, insect pests, diseases, parasitic weeds, drought and low soil fertility, as well as farmer/consumer preferred traits. The design integrates genomics right from germplasm characterization through population development and elite-line selection. It involves extensive phenotyping and SNP genotyping of the base germplasm, using the information immediately for gene mapping through genome-wide association scans. Promising lines are channeled through rigorous researcher-managed field testing combined with participatory selection for quick release and/or use as parents in rapid-cycling hybridization to create improved breeding and gene mapping populations. These new populations are genotyped as early as resources permit and adequately phenotyped for use as training sets in developing genomic selection (GS) models. The mapped QTLs and the GS models are then deployed for routine genomic-assisted selection. This integrated strategy should lead to more rapid and cost-efficient development of higher-yielding, stress-resilient, farmer and consumer-preferred cowpea varieties.