Morpho‐molecular diversity and avirulence genes distribution among the diverse isolates of Magnaporthe oryzae from Southern India

摘要

Abstract Aims To investigate the diversity of eco‐distinct isolates of Magnaporthe oryzae for their morphological, virulence and molecular diversity and relative distribution of five Avr genes. Methods and Results Fifty‐two M. oryzae isolates were collected from different rice ecosystems of southern India. A majority of them (n = 28) formed a circular colony on culture media. Based on the disease reaction on susceptible cultivar (cv. HR‐12), all 52 isolates were classified in to highly virulent (n = 28), moderately virulent (n = 11) and less‐virulent (13) types. Among the 52 isolates, 38 were selected for deducing internal transcribed spacer (ITS) sequence diversity. For deducing phylogeny, another set of 36 isolates from other parts of the world was included, which yielded two distinct phylogenetic clusters. We identified eight haplotype groups and 91 variable sites within the ITS sequences, and haplotype‐group‐2 (Hap_2) was predominant (n = 24). The Tajima's and Fu's Fs neutrality tests exhibited many rare alleles. Furthermore, PCR analysis for detecting the presence of five Avr genes in the different M. oryzae isolates using Avr gene‐specific primers in PCR revealed that Avr‐Piz‐t, Avr‐Pik, Avr‐Pia and Avr‐Pita were present in 73.68, 73.68, 63.16 and 47.37 of the isolates studied, respectively; whereas, Avr‐Pii was identified only in 13.16 of the isolates. Conclusions Morpho‐molecular and virulence studies revealed the significant diversity among eco‐distinct isolates. PCR detection of Avr genes among the M. oryzae population revealed the presence of five Avr genes. Among them, Avr‐Piz‐t, Avr‐Pik and Avr‐Pia were more predominant. Significance and Impact of the Study The study documented the morphological and genetic variability of eco‐distinct M. oryzae isolates. This is the first study demonstrating the distribution of the Avr genes among the eco‐distinct population of M. oryzae from southern India. The information generated will help plant breeders to select appropriate resistant gene/s combinations to develop blast disease‐resistant rice cultivars.