Search

Reeta is a popular late-maturing high-yielding rice variety recommended for cultivation in the eastern Indian states. The cultivar is highly sensitive to submergence stress. Phosphorus deficiency is an additional constraint for realizing high yield. The quantitative trait loci (QTLs), Sub1, for submergence and Pup1 for low phosphorus stress tolerance along with narrow-grained trait, GW5 were introgressed into the variety from the donor parent, Swarna-Sub1 through marker-assisted breeding. In addition, phenotypic selections for higher panicle weight, grain number, and spikelet fertility were performed in each segregating generation. Foreground selection detected the 3 target QTLs in 9, 8 and 7 progenies in the BC1F1, BC2F1, and BC3F1 generation, respectively. Recurrent parent’s genome recovery was analyzed using 168 SSR polymorphic markers. The foreground analysis in 452 BC3F2 progenies showed five pyramided lines in homozygous condition for the target QTLs. No donor fragment drag was noticed in the Sub1 and GW5 QTLs carrier while a segmentwas observed in the Pup1 carrier chromosome. The developed lines were higher yielding, had submergence, and had low phosphorus stress-tolerance alongwith similar to the recipient parent in the studied morpho-quality traits. A promising pyramided line is released in the name of Reeta-Panidhan (CR Dhan 413) for the flood-prone areas of Odisha state.

Seed vigor is the key performance parameter of good quality seed. A panel was prepared by shortlisting genotypes from all the phenotypic groups representing seedling growth parameters from a total of 278 germplasm lines. A wide variation was observed for the traits in the population. The panel was classified into four genetic structure groups. Fixation indices indicated the existence of linkage disequilibrium in the population. A moderate to high level of diversity parameters was assessed using 143 SSR markers. Principal component, coordinate, neighbor-joining tree and cluster analyses showed subpopulations with a fair degree of correspondence with the growth parameters. Marker–trait association analysis detected eight novel QTLs, namely qAGR4.1, qAGR6.1, qAGR6.2 and qAGR8.1 for absolute growth rate (AGR); qRSG6.1, qRSG7.1 and qRSG8.1 for relative shoot growth (RSG); and qRGR11.1 for relative growth rate (RGR), as analyzed by GLM and MLM. The reported QTL for germination rate (GR), qGR4-1, was validated in this population. Additionally, QTLs present on chromosome 6 controlling RSG and AGR at 221 cM and RSG and AGR on chromosome 8 at 27 cM were detected as genetic hotspots for the parameters. The QTLs identified in the study will be useful for improvement of the seed vigor trait in rice.

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.

High seed vigour ensures good quality seed and higher productivity. Early seedling growth parameters indicate seed vigour in rice. Seed vigour via physiological growth parameters is a complex trait controlled by many quantitative trait loci. A panel was prepared representing a population of 274 rice landraces by including genotypes from all the phenotypic groups of sixseedling stage physiological parameters including germination % for association mapping. Wide variations for the six studiedtraits were observed in the population. The population was classified into 3 genetic groups. Fixation indices indicated the presence of linkage disequilibrium in the population. The population was classified into subpopulations and each subpopulation showed correspondence with the 6 physiological traits. A total of 5 reported QTLs viz., qGP8.1 for germination % (GP); qSVII2.1, qSVII6.1 and qSVII6.2 for seed vigour index II (SVII), and qRSR11.1 for root-shoot ratio (RSR) were validated in this mapping population. In addition, 13 QTLs regulating the physiological parameters such as qSVI 11.1 for seed vigour index I; qSVI11.1 and qSVI12.1 for seed vigour index II; qRRG10.1, qRRG8.1, qRRG8.2, qRRG6.1 and qRRG4.1 for rate of root growth (RRG); qRSR2.1, qRSR3.1 and qRSR5.1 for root-shoot ratio (RSR) while qGP6.2 and qGP6.3 for germination %were identified. Additionally, co-localization or co-inheritance of QTLs, qGP8.1 and qSVI8.1 for GP and SVI-1; qGP6.2 and qRRG6.1 for GP and RRG, and qSVI11.1 and qRSR11.1 for SVI and RSR were detected. The QTLs identified in this study will be useful for improvement of seed vigour trait in rice.

Consumption of antioxidants rich rice has impressive health benefits. Five antioxidant traits viz., superoxide dismutase, flavonoids, anthocyanins, γ-oryzanol and ABTS were mapped in a panel population using 136 SSR markers through association mapping. A panel population containing 120 germplasm lines by including genotypes from all the phenotypic groups of the six antioxidant traits from the original shortlisted 270 rice genotypes. Donor lines rich in multiple antioxidant compounds were identified from the population. The population was classified into 4 genetic groups and showed fair degree of correspondence with the antioxidants content. A total of 14 significant marker-trait associations for antioxidants were detected of which 3 QTLs namely qANC3, qPAC12-2 for anthocyanin content and qAC12 for ABTS activity were validated in the population. Eleven putative QTLs such as qTAC1.1 and qTAC5.1 for anthocyanin content; qSOD1.1, qSOD5.1 and qSOD10.1 for SOD; qTFC6.1, qTFC11.1 and qTFC12.1 for TFC; qOZ8.1 and qOZ11.1 for γ-oryzanol and qAC11.1 for ABTS were detected to be novel loci. Co-localization of the QTLs detected for OZ11.1, TFC11.1 and AC11.1 regulating γ-oryzanol, flavonoid and anthocyanin content, respectively while PAC12.2 for anthocyanin content remained closer to TFC12.1 for flavonoid content. These QTLs will be useful in the antioxidant improvement programs in rice.

Background:Good quality seed is an important factor for a good crop. Vigor is the key performing trait of quality seed. Genomic regions controlling the physiological traits related to seed vigour are not fully reported.Results: A panel was prepared by including genotypes from all the groups of the fifteen physiological traits representing a population of 250 germplasm lines. Wide variations were observed for the 15 physiological traits in the population. The population was classified into 6 genetic groups. Presence of linkage disequilibrium (LD) was detected in the panel population based on the fixation indices of the subpopulations. Moderate values of gene diversity, polymorphic information content (PIC) and other diversity parameters were estimated from the population by genotyping with 109 SSR markers. The population was classified into subpopulations and sub-clusters showed relation with the genotypes for their physiological traits. Ten physiological traits were detected to be significantly associated with SSR markers analyzed by both the General linear model (GLM) and Mixed linear model (MLM). A total of 19 novel QTLs controlling different physiological traits namely qGP 6.2 and qGP 8.2 for germination % (GP); qGR 9.1 for germination rate (GR); qGI 1.2, qGI 6.1, qGI 8.1, qGI 11.1 and qGI 12.1 for germination index (GI); qRPE1.1 and qRPE8.1 for rate of plumule elongation (RPE); qAGR 8.1 for AGR; qRSG1.2 and qRSG12.2 for rate of shoot growth (RSG); qRGR3.1 and qRGR11.1 for relative growth rate (RGR); qSVI 1.1 for seed vigour index I (SVI I); qSVII 1.1, qSVII3.1, and qSVII12.1 for seed vigour index II (SVI II), and qRRG8.1 for relative root growth rate were identified. The reported QTL for root length, qRL11.1 was validated in this mapping population. Additionally, QTLs, qRPE8.1 and qAGR8.1 of traits, RPE and AGR; qGI 6.1 and qGP6.2 of GI and GP; qGI 11.1 and qRL11.1 of GI and RL; qAGR8.1 and qRRG8.1 of AGR and RRG, and qRSG3.1 and qRGR3.1of traits RSG and RGR were detected for co-localization or co-inheritance. Conclusion: The traits identified and markers detected in the association analysis will be useful for improvement of seed vigour trait through marker-assisted selection 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.

Good quality seed is an important factor for a good crop and harvest. Vigour is the key performing trait of quality seed. Many physiological traits influence seed vigour in rice. Association of molecular markers with eleven physiological traits were investigated in a representative population. A representative population was constituted by including genotypes from all the phenotypic groups of the 11 physiological traits from the shortlisted population of 120 genotypes. The genotypic accessions with rich in multiple physiological traits were identified from the representative population. STRUCTURE, GenAlEx and Darwin software were used to classify the population. Generalized Linear Model (GLM) and Mixed Linear Models (MLM) were used in the marker-trait association analysis using the TASSEL software. Wide variations among the genotypic accessions were observed for the physiological traits estimated from the panel population. Linkage disequilibrium was detected for the 11 physiological traits in the panel population. STRUCTURE software classified the population into two genetic structure groups. Higher values of gene diversity and polymorphic information content (PIC) were estimated from the population based on genotyping using 50 simple sequence repeat markers. Genotypes present within groups and sub-groups showed similarity for their physiological traits. Strong association of the markers with physiological parameters namely RM167 for seed vigour index-I; RM7364 and RM235 for seed vigour index-II; RM440, RM223 for seedling dry weight; RM 256,RM25181, RM6547, RM328, RM201 for rate of root growth; RM 20, RM13335, RM216 for rate of shoot growth while RM20A and RM201 for absolute growth rate were detected by both GLM and MLM analyses. Markers detected in this association analysis may be potential use for future seed vigour improvement 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.

Ninety lowland rice cultivars of the eastern region of India were collected and screened for submergence and water logging tolerance and further used for validating the efficiency of molecular markers and their combinations for submergence tolerance. Submergence tolerance and elongation ability of the tested genotypes were measured in screening tanks along with tolerant and susceptible checks. The genotypes FR13A, Khoda, CR Dhan 300, Savitri Sub1, IR64 Sub1, IC-568009 and IC-568842 exhibited high submergence tolerance may be used as donor in the breeding program. Landrace 'Khoda' showed tolerance to submergence with moderate elongation ability for adaption. Boitalpakhia, Gayatri, Atiranga, Aghonibora, Chakaakhi, Moti, IC-567993 and IC-568921 possessed both characters of moderate elongation ability and moderate tolerance to submergence. Both of these traits are required for lowland varieties of eastern India to survive under flash flood and accumulated stagnant water conditions. RM8300, Sub1A203, AEX, Sub1BC2 and Sub1C173 were employed for molecular screening to identify the submergence-tolerant genotypes. Sub1A203 was capable of differentiating the tolerant and susceptible genotypes into groups. RM8300 and Sub1BC2 could also differentiate the genotypes with inclusion of some susceptible genotypes. The AEX and Sub1C173 marker could not show discrimination among the genotypes with respect to the traits. Using Sub1A203+Sub1BC2 was better amongst the combinations studied. The results of the study indicated a trend toward a negative association of Sub1BC2 with submergence tolerance while AEX and Sub1C marker did not show any significant association. The donors identified can be useful as parental lines while the molecular markers can be used for marker-assisted breeding work.

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.

Background Jalmagna is a popular deepwater rice variety with farmers of India because of its good yield under waterlogged condition. However, the variety is highly susceptible to bacterial blight (BB) disease. The development of resistant cultivars has been the most effective and economical strategy to control the disease under deepwater situation. Three resistance genes (xa5 + xa13 + Xa21) were transferred from Swarna BB pyramid line, using a marker-assisted backcrossing (MAB) breeding strategy, into the BB-susceptible elite deepwater cultivar, Jalmagna. Results Molecular marker integrated backcross breeding program has been employed to transfer three major BB resistance genes (Xa21, xa13 and xa5) into Jalmagna variety. During backcross generations, markers closely linked to the three genes were used to select plants possessing these resistance genes and markers polymorphic between donor and recurrent parent were used to select plants that have maximum contribution from the recurrent parent genome. A selected BC3F1 plant was selfed to generate homozygous BC3F2 plants with different combinations of BB resistance genes. The three-gene pyramid and two gene pyramid lines exhibited high levels of resistance against the BB pathogen. Under conditions of BB infection, the three-gene pyramided lines exhibited a significant yield advantage over Jalmagna. The selected pyramided lines showed all agro-morphologic traits of Jalmagna without compromising the yield. Conclusion The three major BB resistance genes pyramided lines exhibited high level of resistance and are expected to provide durable resistance under deep water situation where control through chemicals is less effective. High similarity in agro-morphologic traits and absence of antagonistic effects for yield and other characters were observed in the best pyramided lines.

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.