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Rice is the principal food crop for people in South and South-East Asia and is life for millions of rural households worldwide. Bacterial blight (BB) is a very common, widespread, and highly destru...

BackgroundHigh yielding rice varieties are usually low in grain iron (Fe) and zinc (Zn) content. These two micronutrients are involved in many enzymatic activities, lack of which cause many disorders in human body. Bio-fortification is a cheaper and easier way to improve the content of these nutrients in rice grain.ResultsA population panel was prepared representing all the phenotypic classes for grain Fe-Zn content from 485 germplasm lines. The panel was studied for genetic diversity, population structure and association mapping of grain Fe-Zn content in the milled rice. The population showed linkage disequilibrium showing deviation of Hardy-Weinberg’s expectation for Fe-Zn content in rice. Population structure at K = 3 categorized the panel population into distinct sub-populations corroborating with their grain Fe-Zn content. STRUCTURE analysis revealed a common primary ancestor for each sub-population. Novel quantitative trait loci (QTLs) namelyqFe3.3andqFe7.3for grain Fe andqZn2.2,qZn8.3andqZn12.3for Zn content were detected using association mapping. Four QTLs, namelyqFe3.3,qFe7.3,qFe8.1andqFe12.2for grain Fe content were detected to be co-localized withqZn3.1,qZn7,qZn8.3andqZn12.3QTLs controlling grain Zn content, respectively. Additionally, some Fe-Zn controlling QTLs were co-localized with the yield component QTLs,qTBGW,OsSPL14andqPN. The QTLsqFe1.1,qFe3.1,qFe5.1, qFe7.1, qFe8.1, qZn6, qZn7 and gRMm9–1for grain Fe-Zn content reported in earlier studies were validated in this study.ConclusionNovel QTLs,qFe3.3andqFe7.3for grain Fe andqZn2.2,qZn8.3andqZn12.3for Zn content were detected for these two traits. Four Fe-Zn controlling QTLs and few yield component QTLs were detected to be co-localized. The QTLs,qFe1.1,qFe3.1,qFe5.1, qFe7.1, qFe8.1, qFe3.3, qFe7.3, qZn6, qZn7, qZn2.2, qZn8.3andqZn12.3will be useful for biofortification of the micronutrients. Simultaneous enhancement of Fe-Zn content may be possible with yield component traits in rice.

Background Drought during reproductive stage is among the main abiotic stresses responsible for drastic reduction of grain yield in rainfed rice. The genetic mechanism of reproductive stage drought tolerance is very complex. Many physiological and morphological traits are associated with this stress tolerance. Robust molecular markers are required for detection and incorporation of these correlated physiological traits into different superior genetic backgrounds. Identification of gene(s)/QTLs controlling reproductive stage drought tolerance and its deployment in rainfed rice improvement programs are very important. Results QTLs linked to physiological traits under reproductive stage drought tolerance were detected by using 190 F7 recombinant inbred lines (RIL) mapping population of CR 143–2-2 and Krishnahamsa. Wide variations were observed in the estimates of ten physiological traits studied under the drought stress. The RIL population was genotyped using the bulk- segregant analysis (BSA) approach. A total of 77 SSR polymorphic markers were obtained from the parental polymorphisms survey of 401 tested primers. QTL analysis using inclusive composite interval mapping detected a total of three QTLs for the physiological traits namely relative chlorophyll content (qRCC1.1), chlorophyll a (qCHLa1.1), and proline content (qPRO3.1) in the studied RIL population. The QTL, qPRO3.1 is found to be a novel one showing LOD value of 13.93 and phenotypic variance (PVE) of 78.19%. The QTL was located within the marker interval of RM22-RM517 on chromosome 3. Another novel QTL, qRCC1.1 was mapped on chromosome 1 at a distance of 142.8 cM and found to control relative chlorophyll content during terminal drought stress. A third novel QTL was detected in the population that controlled chlorophyll a content (qCHLa1.1) under the terminal stress period. The QTL was located on chromosome 1 at a distance of 81.8 cM and showed 64.5% phenotypic variation. Conclusions The three novel QTLs, qRCC1.1, qCHLa1.1 and qPRO3.1 controlling relative chlorophyll content, chlorophyll a and proline content, respectively were identified in the mapping population derived from CR 143–2-2 and Krishnahamsa. These 3 QTLs will be useful for enhancement of terminal drought stress tolerance through marker-assisted breeding approach in rice.

Submergence stress due to flash floods reduces rice yield drastically in sensitive varieties. Maudamani is a high yielding popular rice variety but is highly susceptible to submergence stress. The selection of progenies carrying Sub1 and GW5 (wide-grain) enhanced the submergence stress tolerance and grain yield of theMaudamani variety by following the marker-assisted backcross breeding method. Foreground screening detected 14 BC1F1, 17 BC2F1, and 12 BC3F1 backcross progenies that carried the target QTLs for submergence tolerance and grain width. Background screening was performed in the progenies carrying the target QTL and enhanced the recovery of a recipient parent’s genome by upto 96.875% in the BC3 pyramided line. The BC3F1 plant containing the highest recipient parent genome content and the target QTLs was self-pollinated. In BC3F2 generation, the target QTLs the Sub1 and GW5 (wide-grain) alleles and recipient parent’s yield component QTL OsSPL14 were tracked for homozygous states in the progenies. Seven pyramided lines showed tolerance to submergence for 14 days and higher grain yield than both the parents. The pyramided lines were similar to the recipient parent for the majority of the studied morphological and quality traits. The pyramided lines are useful as cultivars and can serve as potential donors for transfer of Sub1, OsSPL14, Gn1a, GW5 (wide-grain), and SCM2 QTLs.

Reproductive stage drought stress is an important factor for yield reduction in rice. Genetic mapping of drought responsive QTLs will help to develop cultivars suitable for drought prone environments through marker-assisted breeding. QTLs linked to morpho-physiological traits under drought stress were mapped by evaluating 190 F7 recombinant inbred lines (RIL). Significant variations were observed for eleven morpho-physiological traits involved during the stress. Bulked segregant analysis (BSA) strategy was adopted for genotyping the RIL population. A total of 401 SSR primers were tested for parental polymorphism of which 77 were polymorphic. Inclusive composite interval mapping detected a total of five consistent QTLs controlling leaf rolling (qLR9.1), leaf drying (qLD9.1), harvest index (qHI9.1), spikelet fertility (qSF9.1) and relative water content (qRWC9.1) under reproductive stage drought stress. Another two non-allelic QTLs controlling leaf rolling (qLR8.1) and leaf drying (qLD12.1) were linked in a single year. QTL controlling leaf rolling, qLR8.1 was validated in this mapping population and useful in marker-assisted breeding (MAB) programs. Out of these five consistent QTLs, four (qLR9.1, qLD9.1, qHI9.1 and qRWC9.1) were detected to be novel QTLs and useful for MAB for reproductive stage drought tolerance in rice.

Low-temperature stress is an important factor affecting the growth and development of rice in temperate and high-elevation areas. In this study, 220 germplasm lines were used for screening of tolerant genotypes, validation of molecular markers and identification of robust markers for seedling-stage chilling stress tolerance to be used in marker-assisted breeding (MAS) programme. The temperature regimes imposed in the growth chamber simulated cold-stress injuries at the seedling stages of the germplasm lines. The genotypes were classified into six classes: those having susceptible genotypes were classified into moderately and highly susceptible types, while tolerant types into moderately tolerant, tolerant, highly tolerant and very highly tolerant classes. Genotypes namely Langma, Umleng-1 and Geetanjali showed survival up to 25 d, which were better than the positive check Kalinga-III surviving up to 20 d under chilling stress. Ten simple sequence repeat (SSR) markers were tested for differentiation of genotypes. Individual use of SSR markers like RM284, RM286, RM85, RM341 and RM5746 can be applied in MAS breeding including combination use of non-pair markers like RM284, RM239 and RM85, which was even better than the combined use of RM284 and RM85. However, combined use of all ten markers can most effectively be employed for cold tolerance through MAS breeding.

Rice crop is sensitive to cold stress at seedling stage. A panel of population representing 304 shortlisted germplasm lines was studied for seedling stage chilling tolerance in indica rice. Six phenotypic classes were exposed to six low temperature stress regimes under control phenotyping facility to investigate response pattern. A panel of sixty six genotypes representing all phenotypic classes was used for ensuring genetic diversity, population structure and association mapping for the trait using 58 simple sequence repeat (SSR) and 2 direct trait linked markers. A moderate level of genetic diversity was detected in the panel population for the trait. Deviation of Hardy-Weinberg’s expectation was detected in the studied population using Wright’s F statistic. The panel showed 30% variation among population and 70% among individuals. The entire population was categorized into three sub-populations through STRUCTURE analysis. This revealed tolerance for the trait had a common primary ancestor for each sub-population with few admix individuals. The panel population showed the presence of many QTLs for cold stress tolerance in the individuals representing like genome-wide expression of the trait. Nineteen SSR markers were significantly associated at chilling stress of 80C to 40C for 7 to 21 days duration. Thus, the primers linked to the seedling stage cold tolerance QTLs namely qCTS9, qCTS-2, qCTS6.1, qSCT2, qSCT11, qSCT1a, qCTS-3.1, qCTS11.1, qCTS12.1, qCTS-1b and CTB2 need to be pyramided for development of strongly chilling tolerant variety.

Rice exhibits enormous genetic diversity, population structure and molecular marker-traits associated with abiotic stress tolerance to high temperature stress. A set of breeding lines and landraces representing 240 germplasm lines were studied. Based on spikelet fertility percent under high temperature, tolerant genotypes were broadly classified into four classes. Genetic diversity indicated a moderate level of genetic base of the population for the trait studied. Wright’s F statistic estimates showed a deviation of Hardy-Weinberg expectation in the population. The analysis of molecular variance revealed 25 percent variation between population, 61 percent among individuals and 14 percent within individuals in the set. The STRUCTURE analysis categorized the entire population into three sub-populations and suggested that most of the landraces in each sub-population had a common primary ancestor with few admix individuals. The composition of materials in the panel showed the presence of many QTLs representing the entire genome for the expression of tolerance. The strongly associated marker RM547 tagged with spikelet fertility under stress and the markers like RM228, RM205, RM247, RM242, INDEL3 and RM314 indirectly controlling the high temperature stress tolerance were detected through both mixed linear model and general linear model TASSEL analysis. These markers can be deployed as a resource for marker-assisted breeding program of high temperature stress tolerance.