Jump to Main Content
Breeding for biotic stress resistance in chickpea: progress and prospects
- Li, Haobing, Rodda, Matthew, Gnanasambandam, Annathurai, Aftab, Mohammad, Redden, Robert, Hobson, Kristy, Rosewarne, Garry, Materne, Michael, Kaur, Sukhjiwan, Slater, Anthony T.
- Euphytica 2015 v.204 no.2 pp. 257-288
- Ascochyta, Cicer arietinum, Fusarium wilt, Nematoda, bacterial artificial chromosomes, biotic stress, blight, chickpeas, chromosome mapping, cultivars, expressed sequence tags, fungi, gene transfer, genes, genetic markers, genetic resistance, genotype, high-throughput nucleotide sequencing, insects, landraces, loci, microarray technology, parasitic plants, phenotype, plant breeding, quantitative trait loci, screening, stress tolerance
- Chickpea (Cicer arietinum L.) is the third most economically important food legume in the world. Its yield potential is often limited by various biotic stresses, including fungal and viral diseases, insects, nematodes and parasitic weeds. Incorporating genetic resistance into cultivars is the most effective and economical way of controlling biotic stresses and this is a major objective in many breeding programs. Extensive searches for resistances have been conducted by screening commercial varieties, landraces and closely related species. Resistances to disease such as Ascochyta blight and Fusarium wilt have been identified and molecular tools are being used to increase the efficiency of gene transfer from wild species into chickpea elite genotypes. Quantitative trait loci for resistance genes have been located on linkage maps and molecular markers associated with these loci can potentially be used for efficient pyramiding of the traits. Significant chickpea genomic resources have been developed in order to investigate resistance genes. Such resources include an integrated genetic map, expressed sequence tag libraries, bacterial artificial chromosome libraries, microarrays and draft genome sequences. Although these resources have yet to be used to improve chickpea cultivars in the field, this is likely to change in the near future. These genomic resources, as well as high-resolution phenotyping tools and cutting-edge technologies such as next-generation sequencing, promise to increase efficiency as work to identify valuable candidate genes continues.