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Mapping quantitative trait loci responsible for resistance to Bakanae disease in rice

Fiyaz, R. Abdul, Yadav, Ashutosh K., Krishnan, S. Gopala, Ellur, Ranjith K., Bashyal, Bishnu M., Grover, Nitasha, Bhowmick, Prolay K., Nagarajan, M., Vinod, K. K., Singh, Nagendra K., Prabhu, Kumble V., Singh, Ashok K.
Rice 2016 v.9 no.1 pp. 45
Fusarium fujikuroi, breeding, chromosome mapping, cultivars, emerging diseases, genes, inbred lines, parents, phenotypic variation, quantitative trait loci, rice, screening, seedlings, teleomorphs
BACKGROUND: Bakanae or foot rot disease caused by Fusarium fujikuroi [teleomorph: Gibberella fujikuroi (Sawada) Ito] is emerging as a serious disease in rice. The disease causes both quantitative and qualitative losses to the grains under the field conditions. Breeding for resistance to Bakanae disease is a promising strategy to manage this emerging disease. In this study, we used a population of 168 F₁₄ recombinant inbred lines (RILs) derived from two indica rice parents Pusa 1342, a highly resistant variety and Pusa Basmati 1121, a highly susceptible variety to map quantitative trait loci (QTLs) governing resistance against Bakanae disease. RESULTS: The disease reaction of 168 F₁₄ RILs were measured on the seedlings inoculated using Fusarium fujikuroi culture using high-throughput screening protocol under glasshouse conditions. Utilizing inclusive composite interval mapping, three QTLs governing resistance to Bakanae were identified, namely qBK1.1, qBK1.2 and qBK1.3 which accounted 4.76, 24.74 and 6.49 % of phenotypic variation, respectively. The major effect QTL designated qBK1.2 was mapped in 0.26 Mb region between RM5336 and RM10153. A total of 55 annotated genes were identified within the identified QTL region qBK1.2. CONCLUSIONS: The novel QTLs identified in this study are useful resource for efficiently breeding rice cultivars resistant to Bakanae disease. This is the first report on identification of QTLs governing resistance against Bakanae in rice using inclusive composite interval mapping strategy in a RIL population.