Molecular Dissection and QTL Mapping of Rice Blast Disease Resistance Using Simple Sequence Repeat Markers
DNA marker technology and the mapping of the major genes have played important roles in rice (Oryza sativa L.) disease improvement. Blast caused by Magnaporthe oryzae is an important disease of rice in Malaysia and all over the world. Its frequent appearance during all the stages of plant growth gre...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/20824/1/FP_2011_25_IR.pdf |
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| Summary: | DNA marker technology and the mapping of the major genes have played important roles in rice (Oryza sativa L.) disease improvement. Blast caused by Magnaporthe oryzae is an important disease of rice in Malaysia and all over the world. Its frequent appearance during all the stages of plant growth greatly decreases yield and grain quality. Quantitative trait loci (QTL)-based resistance for rice blast disease control is becoming increasingly important in breeding rice programs. This study used molecular marker approaches in order to analyse molecular genetics of resistance in segregating populations and to identify QTL conferring resistance against two different pathotypes of M. oryzae, namely, P7.2 and P5.0, in F3 families derived from the cross of Pongsu Seribu 2 (resistant) variety and Mahsuri (susceptible) cultivar. One hundred and twenty five micro-satellite markers closely linked to the blast resistant genes (Pi-genes) distributed over 12 chromosomes of the rice genome were chosen and used in the study to determine polymorphism and potential association with blast resistance. Twenty three of polymorphic markers were used to identify blast resistant segregation ratios in 320 individuals of F2 population. Eleven markers showed a good fit to the expected segregation ratio (1:2:1) for single gene model (df = 1.0, p ≤ 0.05). The rest of the markers did not fit the expected segregating Mendelian ratios. The F3 families were grown in a greenhouse and challenged with two blast pathotypes, P7.2 and P5.0. In analysis of Chi-square tests for single gene model, two independent genes and possible different gene models of epistasis effect different segregation ratio (3R:1S) and (15R:1S) were observed for pathotypes P7.2 and P5.0 in blast lesion trait respectively. Pongsu Seribu 2 was resistant against both blast pathotypes tested. Pathotype P7.2 was found to be a high virulence blast pathotype. The plants resistant to blast pathotype P7.2 from F3 population were good linked with genotypes of four SSR markers, RM413, RM1233, RM8225 and RM5961, with observed segregation ratio of (1:2:1) for single dominant gene model. These markers were found as suitable SSR markers for use in marker assisted selection of blast resistant genes conferring resistance to Magnaporthe oryzae pathotype, P7.2. A total of 188 F3 families derived from the cross between, Pongsu Seribu 2 and Mahsuri were used in this experiment to identify QTLs for resistance to local Magnaporthe oryzae pathotypes, P7.2 and P5.0. There was a positive correlation for the three traits (BLD, BLT and % DLA) for each isolate. A trait distribution analysis did not show continuous variation with normal distribution. For both pathotypes, the distributions of disease severity (DS) were skewed towards resistance. Sixty three polymorphic SSR markers were used to construct a linkage map in 188 F3 families. The 63 SSR markers covered 3989.9 cM of the rice genome. Single marker analysis (SMA), interval mapping (IM) and composite interval mapping with permutation analysis was used for Quantitative Trait Loci (QTL) analysis. Twenty eight independent QTLs were detected to be associated with blast resistance on chromosomes 1, 2, 3, 5, 6, 8, 10, 11 and 12. Six putative QTL (qRBr 1.2, qRBr-2.1, qRBr-5.1, qRBr-6.1, qRBr-11.1 and qRBr-11.2) with Logarithmic of Odds (LOD) > 3.0.and 7 suggestive QTLs (qRBr-1.1, qRBr-3.1, qRBr-6.2, qRBr-10.1, qRBr-10.2, qRBr-11.3 and qRBr-12.1, LOD < 3.0) were detected for pathotype P7.2. Meanwhile, three putative QTLs (qRBr-6.1, qRBr-11.4, and qRBr-12.1) with Logarithmic of Odds (LOD) > 3.0 and 12 suggestive QTLs (qRBr-1.2, qRBr-2.1, qRBr-4.1, qRBr-5.1, qRBr-6.2 qRBr-6.3, qRBr-8.1, qRBr-10.1, qRBr-10.2, qRBr- 11.1, qRBr-11.2 and qRBr-11.3, LOD < 3.0) were detected for pathotype P5.0. Likelihood Ratio Statistics (LRS) for the association of the traits with locus at p ≤0.05 ranged from 4.0 to 32.4. However, only 9 putative QTLs were found with a single marker analysis and either interval mapping or composite interval mapping (atLRS up to15) on chromosomes1, 2, 5, 6, 11 and 12. The individual locus found in the population F3 for traits studied, explained 2-16% of the total phenotypic variance in resistance against blast pathotypes. QTLs that had effects on both of the two blast isolates, such QTLs may be commonly involved in the defense response against a broad range of pathogens infections and others may only be involved in limited defense responses, thus showing degrees of race specificity. Some of our identified QTL were mapped to region where previously some Pi genes for blast resistance have been reported. Such quantitative resistance genes might be defeated major Rgenes. In conclusion, from this research it was found that resistance to blast in Pongsu Seribu 2 is very complex and is composed of a combination of Pi genes as well as some unknown genes, and major and minor effects of multiple loci that appear to contribute to partial resistance to local blast isolates. |
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