Development and evaluation of near-isogenic lines for major blast resistance gene(s) in Basmati rice.

KEY MESSAGE: A set of NILs carrying major blast resistance genes in a Basmati rice variety has been developed. Also, the efficacy of pyramids over monogenic NILs against rice blast pathogen Magnaporthe oryzae has been demonstrated. Productivity and quality of Basmati rice is severely affected by rice blast disease. Major genes and QTLs conferring resistance to blast have been reported only in non-Basmati rice germplasm. Here, we report incorporation of seven blast resistance genes from the donor lines DHMASQ164-2a (Pi54, Pi1, Pita), IRBLz5-CA (Pi2), IRBLb-B (Pib), IRBL5-M (Pi5) and IRBL9-W (Pi9) into the genetic background of an elite Basmati rice variety Pusa Basmati 1 (PB1). A total of 36 near-isogenic lines (NILs) comprising of 14 monogenic, 16 two-gene pyramids and six three-gene pyramids were developed through marker-assisted backcross breeding (MABB). Foreground, recombinant and background selection was used to identify the plants with target gene(s), minimize the linkage drag and increase the recurrent parent genome (RPG) recovery (93.5-98.6 %), respectively, in the NILs. Comparative analysis performed using 50,051 SNPs and 500 SSR markers revealed that the SNPs provided better insight into the RPG recovery. Most of the monogenic NILs showed comparable performance in yield and quality, concomitantly, Pusa1637-18-7-6-20 (Pi9), was significantly superior in yield and stable across four different environments as compared to recurrent parent (RP) PB1. Further, among the pyramids, Pusa1930-12-6 (Pi2+Pi5) showed significantly higher yield and Pusa1633-7-8-53-6-8 (Pi54+Pi1+Pita) was superior in cooking quality as compared to RP PB1. The NILs carrying gene Pi9 were found to be the most effective against the concoction of virulent races predominant in the hotspot locations for blast disease. Conversely, when analyzed under artificial inoculation, three-gene pyramids expressed enhanced resistance as compared to the two-gene and monogenic NILs.

Integration of crop rotation and arbuscular mycorrhiza (AM) inoculum application for enhancing AM activity to improve phosphorus nutrition and yield of upland rice (Oryza sativa L.).

Upland rice (Oryza sativa L.) is a major crop of Eastern India grown during the wet season (June/July to September/October). Aerobic soils of the upland rice system, which are acidic and inherently phosphorus (P) limiting, support native arbuscular mycorrhizal (AM) activity. Attempts were made to improve P nutrition of upland rice by exploiting this natural situation through different crop rotations and application of AM fungal (AMF) inoculum. The effect of a 2-year crop rotation of maize (Zea mays L.) followed by horse gram (Dolichos biflorus L.) in the first year and upland rice in the second year on native AM activity was compared to three existing systems, with and without application of a soil-root-based inoculum. Integration of AM fungal inoculation with the maize-horse gram rotation had synergistic/additive effects in terms of AMF colonization (+22.7 to +42.7%), plant P acquisition (+11.2 to +23.7%), and grain yield of rice variety Vandana (+25.7 to +34.3%).

Accumulating candidate genes for broad-spectrum resistance to rice blast in a drought-tolerant rice cultivar.

Biotic stresses, including diseases, severely affect rice production, compromising producers' ability to meet increasing global consumption. Understanding quantitative responses for resistance to diverse pathogens can guide development of reliable molecular markers, which, combined with advanced backcross populations, can accelerate the production of more resistant varieties. A candidate gene (CG) approach was used to accumulate different disease QTL from Moroberekan, a blast-resistant rice variety, into Vandana, a drought-tolerant variety. The advanced backcross progeny were evaluated for resistance to blast and tolerance to drought at five sites in India and the Philippines. Gene-based markers were designed to determine introgression of Moroberekan alleles for 11 CGs into the progeny. Six CGs, coding for chitinase, HSP90, oxalate oxidase, germin-like proteins, peroxidase and thaumatin-like protein, and 21 SSR markers were significantly associated with resistance to blast across screening sites. Multiple lines with different combinations, classes and numbers of CGs were associated with significant levels of race non-specific resistance to rice blast and sheath blight. Overall, the level of resistance effective in multiple locations was proportional to the number of CG alleles accumulated in advanced breeding lines. These disease resistant lines maintained tolerance to drought stress at the reproductive stage under blast disease pressure.

Microbial Interactions in Plants: Perspectives and Applications of Proteomics.

The structure and function of proteins involved in plant-microbe interactions is investigated through large-scale proteomics technology in a complex biological sample. Since the whole genome sequences are now available for several plant species and microbes, proteomics study has become easier, accurate and huge amount of data can be generated and analyzed during plant-microbe interactions. Proteomics approaches are highly important and relevant in many studies and showed that only genomics approaches are not sufficient enough as much significant information are lost as the proteins and not the genes coding them are final product that is responsible for the observed phenotype. Novel approaches in proteomics are developing continuously enabling the study of the various aspects in arrangements and configuration of proteins and its functions. Its application is becoming more common and frequently used in plant-microbe interactions with the advancement in new technologies. They are more used for the portrayal of cell and extracellular destructiveness and pathogenicity variables delivered by pathogens. This distinguishes the protein level adjustments in host plants when infected with pathogens and advantageous partners. This review provides a brief overview of different proteomics technology which is currently available followed by their exploitation to study the plant-microbe interaction.

Allele Mining and Selective Patterns of Pi9 Gene in a Set of Rice Landraces from India.

Allelic variants of the broad-spectrum blast resistance gene, Pi9 (nucleotide binding site-leucine-rich repeat region) have been analyzed in Indian rice landraces. They were selected from the list of 338 rice landraces phenotyped in the rice blast nursery at central Rainfed Upland Rice Research Station, Hazaribag. Six of them were further selected on the basis of their resistance and susceptible pattern for virulence analysis and selective pattern study of Pi9 gene. The sequence analysis and phylogenetic study illustrated that such sequences are vastly homologous and clustered into two groups. All the blast resistance Pi9 alleles were grouped into one cluster, whereas Pi9 alleles of susceptible landraces formed another cluster even though these landraces have a low level of DNA polymorphisms. A total number of 136 polymorphic sites comprising of transitions, transversions, and insertion and deletions (InDels) were identified in the 2.9 kb sequence of Pi9 alleles. Lower variation in the form of mutations (77) (Transition + Transversion), and InDels (59) were observed in the Pi9 alleles isolated from rice landraces studied. The results showed that the Pi9 alleles of the selected rice landraces were less variable, suggesting that the rice landraces would have been exposed to less number of pathotypes across the country. The positive Tajima's D (0.33580), P > 0.10 (not significant) was observed among the seven rice landraces, which suggests the balancing selection of Pi9 alleles. The value of synonymous substitution (-0.43337) was less than the non-synonymous substitution (0.78808). The greater non-synonymous substitution than the synonymous means that the coding region, mainly the leucine-rich repeat domain was under diversified selection. In this study, the Pi9 gene has been subjected to balancing selection with low nucleotide diversity which is different from the earlier reports, this may be because of the closeness of the rice landraces, cultivated in the same region, and under low pathotype pressure.

Genetic, physiological, and gene expression analyses reveal that multiple QTL enhance yield of rice mega-variety IR64 under drought.

BACKGROUND: Rice (Oryza sativa L.) is a highly drought sensitive crop, and most semi dwarf rice varieties suffer severe yield losses from reproductive stage drought stress. The genetic complexity of drought tolerance has deterred the identification of agronomically relevant quantitative trait loci (QTL) that can be deployed to improve rice yield under drought in rice. Convergent evidence from physiological characterization, genetic mapping, and multi-location field evaluation was used to address this challenge. METHODOLOGY/PRINCIPAL FINDINGS: Two pairs of backcross inbred lines (BILs) from a cross between drought-tolerant donor Aday Sel and high-yielding but drought-susceptible rice variety IR64 were produced. From six BC4F3 mapping populations produced by crossing the +QTL BILs with the -QTL BILs and IR64, four major-effect QTL--one each on chromosomes 2, 4, 9, and 10--were identified. Meta-analysis of transcriptome data from the +QTL/-QTL BILs identified differentially expressed genes (DEGs) significantly associated with QTL on chromosomes 2, 4, 9, and 10. Physiological characterization of BILs showed increased water uptake ability under drought. The enrichment of DEGs associated with root traits points to differential regulation of root development and function as contributing to drought tolerance in these BILs. BC4F3-derived lines with the QTL conferred yield advantages of 528 to 1875 kg ha⁻¹ over IR64 under reproductive-stage drought stress in the targeted ecosystems of South Asia. CONCLUSIONS/SIGNIFICANCE: Given the importance of rice in daily food consumption and the popularity of IR64, the BC4F3 lines with multiple QTL could provide higher livelihood security to farmers in drought-prone environments. Candidate genes were shortlisted for further characterization to confirm their role in drought tolerance. Differential yield advantages of different combinations of the four QTL reported here indicate that future research should include optimizing QTL combinations in different genetic backgrounds to maximize yield advantage under drought.

Drought yield index to select high yielding rice lines under different drought stress severities.

BACKGROUND: Drought is the most severe abiotic stress reducing rice yield in rainfed drought prone ecosystems. Variation in intensity and severity of drought from season to season and place to place requires cultivation of rice varieties with different level of drought tolerance in different areas. Multi environment evaluation of breeding lines helps breeder to identify appropriate genotypes for areas prone to similar level of drought stress. From a set of 129 advanced rice (Oryza sativa L.) breeding lines evaluated under rainfed drought-prone situations at three locations in eastern India from 2005 to 2007, a subset of 39 genotypes that were tested for two or more years was selected to develop a drought yield index (DYI) and mean yield index (MYI) based on yield under irrigated, moderate and severe reproductive-stage drought stress to help breeders select appropriate genotypes for different environments. RESULTS: ARB 8 and IR55419-04 recorded the highest drought yield index (DYI) and are identified as the best drought-tolerant lines. The proposed DYI provides a more effective assessment as it is calculated after accounting for a significant genotype x stress-level interaction across environments. For rainfed areas with variable frequency of drought occurrence, Mean yield index (MYI) along with deviation in performance of genotypes from currently cultivated popular varieties in all situations helps to select genotypes with a superior performance across irrigated, moderate and severe reproductive-stage drought situations. IR74371-70-1-1 and DGI 75 are the two genotypes identified to have shown a superior performance over IR64 and MTU1010 under all situations. CONCLUSION: For highly drought-prone areas, a combination of DYI with deviation in performance of genotypes under irrigated situations can enable breeders to select genotypes with no reduction in yield under favorable environments compared with currently cultivated varieties. For rainfed areas with variable frequency of drought stress, use of MYI together with deviation in performance of genotypes under different situations as compared to presently cultivated varieties will help breeders to select genotypes with superior performance under all situations.