A. NAGARAJAJAYASHREE A2023-05-082023-05-082023-02-13Th-13582https://krishikosh.egranth.ac.in/handle/1/5810197141Rice blast disease caused by Magnaporthe oryzae (Hebert) Barr is one of the leading constraints to global rice production and a serious threat to food security. The present study aims to decipher the role of suppressors of plant cell death (SPD) effectors during host pathogen interaction and develop a weather driven forecasting model for rice blast disease by employing machine learning algorithms and understanding the rice defence response to high temperature upon challenge inoculation with the pathogen. In-silico identification, modelling and functional analysis of SPD effectors in M. oryzae revealed that eleven SPD effectors under study were predicted to fulfil the criteria to fit in the definition of candidate secreted effector proteins. The SPD effectors were composed of a signal peptide, ≥ 3 per cent of cysteine residues, no transmembrane domains, ≤ 250 amino acids and a low molecular weight of below 50 KDa. The majority of homologs, orthologs and paralogs identified belonged to ascomycetes. The SPD effector MG01_03488 was expressed using a pET32a (+) expression vector and the protein was purified using Ni- NTA affinity chromatography. Priming rice plants with prokaryotic expression product of MG01_03488 resulted in the suppression of reactive oxygen species and other defence related enzymes, consequently facilitating pathogen virulence. Of the six machine learning techniques employed in rice blast prediction, the artificial neural network was more efficient, with 98.84 per cent accuracy. Temperature and relative humidity were significant weather contributors in predicting rice blast through machine learning approaches. Magnaporthe oryzae inoculation and induced high temperature stress increased rice blast disease severity and resulted in a substantial reduction in the photosynthetic pigments, carotenoids and anthocyanin content and increased membrane injury index, malondialdehyde, reactive oxygen species, lipoxygenase activity, antioxidant activities and higher relative expression of Pi2 and Pi54 resistance genes as compared to non-stress rice seedlings.EnglishThesis