Abstract:The phenotypic diversity of Magnaporthe grisea was evaluated based on leaf samples with blast lesions collected from eight commercial fields of the upland rice cultivars 'BRS Primavera' and 'BRS Bonança', during the growing seasons of 2001/2002 and 2002/2003, in Goias State. The number of M. grisea isolates from each field utilized for virulence testing varied from 28 to 47. Three different indices were used based on reaction type in the eight standard international differentials and eight Brazilian differenti… Show more
“…The structure of the pathogen population refers to the amount of genetic and phenotypic variation among and within the populations, and it is divided in time and space and may be influenced by the cultivar origin, location, size of the planted area and field isolation by cultivar (Silva et al. ). In Brazil, phenotypic characterization studies of M. oryzae populations have been focussed on the determination of pathotypes and their frequency and respective compatibility with resistance genes in commercial cultivars and international differentials (Cornelio et al.…”
This is the first time that a sample of 847 Magnaporthe oryzae field isolates were clustered in 19 subpopulations utilizing 18 SSR Marker in Brazil.
AbstractThis study aimed to examine Brazilian M. oryzae populations using 18 microsatellites. Fifty cultivars were sown in plastic trays for the pathotyping of 847 isolates. The DNA of 494 isolates was extracted and purified using the modified Doyle and Doyle method, the genetic structure was determined by the software Structure, and the actual number was selected from the prediction method based on the K values. Nei's genetic distance among the subpopulations was determined with the aid of the program Genetix, and the AMOVA was performed with the program Arlequin. Out of 847 inoculated monosporic isolates, 528 infected their respective cultivars; of the 528 isolates pathotyped, there was a prevalence of group IA and pathotype IF-1, which was the most frequent pathotype in the rice production areas of Brazil. The Bayesian clustering analysis indicated that 19 was the optimal value of K; this value was the lowest standard deviation and log (ln K) closest to zero, which predicted the 494 isolates of M. oryzae that were selected for molecular studies to be grouped into 19 subpopulations. The AMOVA detected a 37.13% variability within the 19 subpopulations and 62.87% variability among the subpopulations. The polymorphic information content (PIC) ranged from 0 to 0.756. Thirty three rare alleles were found distributed among 15 out of 19 subpopulations. The Margalef index ranged from 38.69 to 79.21 for all 18 analysed locus. The results indicated that the identification of different blast resistance genes must consider the composition of each subpopulation and that the identification is most effective when performed within a subpopulation and then between subpopulations.Estimates indicate that by 2050, the current world production of 735 million tons (shelled basis) needs to be doubled to meet the demand. Latin America and Africa stand out as the only two regions with the potential rice production capacity to meet the growing J Phytopathol 164 (2016) 620-630 Ó
“…The structure of the pathogen population refers to the amount of genetic and phenotypic variation among and within the populations, and it is divided in time and space and may be influenced by the cultivar origin, location, size of the planted area and field isolation by cultivar (Silva et al. ). In Brazil, phenotypic characterization studies of M. oryzae populations have been focussed on the determination of pathotypes and their frequency and respective compatibility with resistance genes in commercial cultivars and international differentials (Cornelio et al.…”
This is the first time that a sample of 847 Magnaporthe oryzae field isolates were clustered in 19 subpopulations utilizing 18 SSR Marker in Brazil.
AbstractThis study aimed to examine Brazilian M. oryzae populations using 18 microsatellites. Fifty cultivars were sown in plastic trays for the pathotyping of 847 isolates. The DNA of 494 isolates was extracted and purified using the modified Doyle and Doyle method, the genetic structure was determined by the software Structure, and the actual number was selected from the prediction method based on the K values. Nei's genetic distance among the subpopulations was determined with the aid of the program Genetix, and the AMOVA was performed with the program Arlequin. Out of 847 inoculated monosporic isolates, 528 infected their respective cultivars; of the 528 isolates pathotyped, there was a prevalence of group IA and pathotype IF-1, which was the most frequent pathotype in the rice production areas of Brazil. The Bayesian clustering analysis indicated that 19 was the optimal value of K; this value was the lowest standard deviation and log (ln K) closest to zero, which predicted the 494 isolates of M. oryzae that were selected for molecular studies to be grouped into 19 subpopulations. The AMOVA detected a 37.13% variability within the 19 subpopulations and 62.87% variability among the subpopulations. The polymorphic information content (PIC) ranged from 0 to 0.756. Thirty three rare alleles were found distributed among 15 out of 19 subpopulations. The Margalef index ranged from 38.69 to 79.21 for all 18 analysed locus. The results indicated that the identification of different blast resistance genes must consider the composition of each subpopulation and that the identification is most effective when performed within a subpopulation and then between subpopulations.Estimates indicate that by 2050, the current world production of 735 million tons (shelled basis) needs to be doubled to meet the demand. Latin America and Africa stand out as the only two regions with the potential rice production capacity to meet the growing J Phytopathol 164 (2016) 620-630 Ó
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.