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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.

Achieving the demand and supply of rice for the increasing global population will be a challenging task beyond 2040. Therefore, the yield potential of popular rice varieties needs to be increased. The production from lowland rice can be enhanced by managing the major biotic and abiotic stresses faced in the ecology. In this work, we have developed the pipelines for gene stacking of submergence tolerance, bacterial blight resistance and yield component QTLs in the popular rice variety ‘Swarna’ by marker-assisted backcross breeding approach. Genotyping results of 796 BC1F1 backcross derived lines showed the presence of GW2, OsSPL14, SCM2 yield component QTLs, Sub1A for submergence tolerance and bacterial blight resistance genes xa5 and Xa21 in the progenies. The four stacked QTLs and two resistance genes were observed in six backcrosses derived progenies only. These progenies will be used in the next generation for further selection and evaluation for enhancing submergence tolerance, yield potential and bacterial blight resistance in Swarna rice variety background.

Rice serves as one of the essential staple food for half of the global human population. However, due to rapid human population growth, there is an increase in food demand across the globe. Thus, to lessen the gap between food demand and supply, there is an urgent requirement for grain yield enhancement in various important cereals crops, including rice. In the present study, the authors attempted to characterize haplotypes and single nucleotide polymorphisms associated with Gn1a for high grain number formation in rice plants. Result obtained reveals that high grain number gene sequences are under balancing selection and four high grain number specific missense SNPs decreases the stability of Gn1a. Earlier studies have also suggested that decreases Gn1a expression causes cytokinin accretion in inflorescence meristems, which in turn led to increase in grain yield. Hence, these four SNPs may be utilized for increasing grain yield in rice plants.

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.

The ICAR-National Rice Research Institute (NRRI), Cuttack in Odisha develops varieties and agro-technologies for enhancing and sustaining rice production. The Institute so far has released 133 high-yielding varieties of rice for various ecosystems. Some of the varieties have been very popular among the farmers and even became ruling varieties in some states. However, there are no reports on the area covered by NRRI varieties and its impact on incremental gain in farm income. In the present study, area covered by NRRI varieties in the country during 2017-18 was estimated based on the amount of quality seeds provided to the farmers through various ways: breeder seed indent to the DAC; breeder seed and truthfully-labeled seed supplied by the NRRI farm; participatory seed production by NRRI; seed distributed in various programmes and projects of the Institute; front-line demonstrations and on-farm testing; seed of NRRI varieties supplied by the private entrepreneurs and disseminated from farmers to farmers etc. A validation exercise was conducted to cross-check the estimated areas under NRRI varieties. The analysis showed that currently NRRI varieties cover about 8.0 million ha (Mha) i.e., 18% of rice area of the country. West Bengal has the largest area of 2.26 Mha, followed by Odisha with 2.18 Mha. Total production of rice with NRRI varieties is 27.80 million tons (Mt) with the value of Rs.48,643 crores per annum. Further, incremental production and income with NRRI varieties considering 5% more than the existing popular varieties is estimated to be 1.39 Mt and Rs.2,432 crores per annum, respectively. Over the years, indents of breeder seed (BS) of NRRI varieties have increased considerably indicating growing popularities of NRRI varieties among the farmers in different states.

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.

Eighteen physio-biochemical traits influencing seed vigour were studied for their association with molecular markers using a mini core set constituted from 120 germplasm lines. High genetic variation was detected in the parameters namely chlrophyll a, Chlrophyll b, total chlorophyll, carotenoids, total anthocyanin content, gamma-oryzanols, total phenolics content, superoxide dismutase, catalase, guaicol peroxidase, total soluble sugar, total protein, seed vigour index -I and seed vigour index -II. Strong positive correlation of seed vigour index II was observed with amylose content, total anthocyanin content, catalase, total phenolic content and total flavonoid content while a negative association was observed for gamma-oryzanol content. High gene diversity (0.7169) and informative markers value (0.6789) were estimated from the investigation. Three genetic structure groups were observed in the panel population and genotypes were grouped in the subpopulations based on the seed vigour trait. Differences in the fixation indices of the three sub populations indicated existence of linkage disequilibrium in the studied panel population. Association of the traits namely total flavonoids, superoxide dismutase, catalase, chlorophyll a, Chlorophyll b, total chlorophyll, carotenoids, starch, amylose, total anthocyanin, gamma-oryzanol, total phenolics with the molecular markers were detected by Generalized Linear Model and Mixed Linear Model showing > 0.10 R(2) value. Association of the trait, total flavonoids with marker RM7364 located on chromosome 8 reported in earlier study was validated in this investigation. The validated markers and the novel markers detected showing higher R(2) value will be useful for improvement of seed vigour in rice. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12298-020-00879-y) contains supplementary material, which is available to authorized users.

There has been a significant advancement in the application of statistical tools in plant pathology during the past four decades. These tools include multivariate analysis of disease dynamics involving principal component analysis, cluster analysis, factor analysis, pattern analysis, discriminant analysis, multivariate analysis of variance, correspondence analysis, canonical correlation analysis, redundancy analysis, genetic diversity analysis, and stability analysis, which involve in joint regression, additive main effects and multiplicative interactions, and genotype-by-environment interaction biplot analysis. The advanced statistical tools, such as non-parametric analysis of disease association, meta-analysis, Bayesian analysis, and decision theory, take an important place in analysis of disease dynamics. Disease forecasting methods by simulation models for plant diseases have a great potentiality in practical disease control strategies. Common mathematical tools such as monomolecular, exponential, logistic, Gompertz and linked differential equations take an important place in growth curve analysis of disease epidemics. The highly informative means of displaying a range of numerical data through construction of box and whisker plots has been suggested. The probable applications of recent advanced tools of linear and non-linear mixed models like the linear mixed model, generalized linear model, and generalized linear mixed models have been presented. The most recent technologies such as micro-array analysis, though cost effective, provide estimates of gene expressions for thousands of genes simultaneously and need attention by the molecular biologists. Some of these advanced tools can be well applied in different branches of rice research, including crop improvement, crop production, crop protection, social sciences as well as agricultural engineering. The rice research scientists should take advantage of these new opportunities adequately in adoption of the new highly potential advanced technologies while planning experimental designs, data collection, analysis and interpretation of their research data sets.

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.

Bacterial blight (BB) disease and submergence due to flash flood are the two major constraints for achieving higher yield from rainfed lowland rice. Marker-assisted backcross breeding was followed to develop submergence tolerant and durable BB resistant variety in the background of popular cultivar ‘Swarna’. Four BB resistance genes viz., Xa4, xa5, xa13, Xa21 and Sub1 QTL for submergence tolerance were incorporated into the mega variety. Foreground selection for the five target genes was performed using closely linked markers and tracked in each backcross generations. Background selection in plants carrying the target genes was performed by using 100 simple sequence repeat markers. Amongst backcross derivatives, the plant carrying five target genes and maximum recurrent parent genome content was selected in each generation and hybridized with recipient parent. Eighteen BC3F2 plants were obtained by selfing the selected BC3F1 line. Amongst the pyramided lines, 3 lines were homozygous for all the target genes. Bioassay of the 18 pyramided lines containing BB resistance genes was conducted against different Xoo strains conferred very high levels of resistance to the predominant isolates. The pyramided lines also exhibited submergence tolerance for 14 days. The pyramided lines were similar to the recurrent parent in 14 morpho-quality traits.

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.

Iron (Fe) toxicity is a major abiotic stress which severely reduces rice yield in many countries of the world. Genetic variation for this stress tolerance exists in rice germplasms. Mapping of gene(s)/QTL controlling the stress tolerance and transfer of the traits into high yielding rice varieties are essential for improvement against the stress. A panel population of 119 genotypes from 352 germplasm lines was constituted for detecting the candidate gene(s)/QTL through association mapping. STRUCTURE, GenAlEx and Darwin softwares were used to classify the population. The marker-trait association was detected by considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) analyses. Wide genetic variation was observed among the genotypes present in the panel population for the stress tolerance. Linkage disequilibrium was detected in the population for iron toxicity tolerance. The population was categorized into three genetic structure groups. Marker-trait association study considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) showed significant association of leaf browning index (LBI) with markers RM471, RM3, RM590 and RM243. Three novel QTL controlling Fe-toxicity tolerance were detected and designated asqFeTox4.3,qFeTox6.1andqFeTox10.1. A QTL reported earlier in the marker interval of C955-C885 on chromosome 1 is validated using this panel population. The present study showed that QTL controlling Fe-toxicity tolerance to be co-localized with the QTL for Fe-biofortification of rice grain indicating involvement of common pathway for Fe toxicity tolerance and Fe content in rice grain. Fe-toxicity tolerance QTLqFeTox6.1was co-localized with grain Fe-biofortification QTLsqFe6.1andqFe6.2on chromosome 6, whereasqFeTox10.1was co-localized withqFe10.1on chromosome 10. The Fe-toxicity tolerance QTL detected from this mapping study will be useful in marker-assisted breeding programs.

Low light intensity is a great limitation for grain yield and quality in rice. However, yield is not significantly reduced in low light tolerant rice varieties. The work therefore planned for comparative transcriptome profiling under low light stress to decipher the genes involved and molecular mechanism of low light tolerance in rice. At active tillering stage, 50% low light exposure for 1 day, 3 days and 5 days were given to Swarnaprabha (low light tolerant) and IR8 (low light sensitive) rice varieties. Illumina (HiSeq) platform was used for transcriptome sequencing. A total of 6,652 and 12,042 genes were differentially expressed due to low light intensity in Swarnaprabha and IR8, respectively as compared to control. CAB, LRP, SBPase, MT15, TF PCL1 and Photosystem I & II complex related gene expressions were mostly increased in Swarnaprabha upon longer duration of low light exposure which was not found in IR8 as compared to control. Their expressions were validated by qRT-PCR. Overall study suggested that the maintenance of grain yield in the tolerant variety under low light might be results of accelerated expression of the genes which enable the plant to keep the photosynthetic processes moving at the same pace even under low light.

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.

The genetic improvement of rice over past decades has led to the loss of several genes which are responsible for nutrient acquisition and soil-related stresses. Phosphorus (P) is a non-renewable resource and inevitable element of metabolic functions in plants. By pedogenesis process, organic matter contributes to renewing soil P in lesser extent. Therefore, improvement of the P use efficiency is one of the most imperative traits in rice breeding program, which is governed by quantitative trait loci (QTLs). QTLs controlling low P associated morphological and physiological traits in rice were investigated mostly during last one and half decade by using diverse mapping populations. Comprehensive and meticulous survey from literature, we found that to date 133 P associated QTLs of morpho-physiological traits were reported to be distributed on twelve chromosomes and majority of these QTLs localized on chromosome 1, 2 and 12. For the first time, a complete figure is presented in this review on chromosome wise with respective QTLs associated with low P for easy understanding and selecting markers for future prospect. Further, it is necessary to understand the molecular mechanisms and regulation of genes and traits associated with low P to develop tolerant rice cultivars using functional marker-assisted selection.

Background Rice breeding program needs to focus on development of nutrient dense rice for value addition and helping in reducing malnutrition. Mineral and vitamin deficiency related problems are common in the majority of the population and more specific to developing countries as their staple food is rice. Results Genes and QTLs are recently known for the nutritional quality of rice. By comprehensive literature survey and public domain database, we provided a critical review on nutritional aspects like grain protein and amino acid content, vitamins and minerals, glycemic index value, phenolic and flavonoid compounds, phytic acid, zinc and iron content along with QTLs linked to these traits. In addition, achievements through transgenic and advanced genomic approaches have been discussed. The information available on genes and/or QTLs involved in enhancement of micronutrient element and amino acids are summarized with graphical representation. Conclusion Compatible QTLs/genes may be combined together to design a desirable genotype with superior in multiple grain quality traits. The comprehensive review will be helpful to develop nutrient dense rice cultivars by integrating molecular markers and transgenic assisted breeding approaches with classical 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.

Bacterial blight (BB) of rice caused by Xanthomonas oryzae pv. oryzae is a major disease of rice in many rice growing countries. Pyramided lines carrying two BB resistance gene combinations (Xa21+xa13 and Xa21+xa5) were developed in a lowland cultivar Jalmagna background through backcross breeding by integrating molecular markers. In each backcross generation, markers closely linked to the disease resistance genes were used to select plants possessing the target genes. Background selection was continued in those plants carrying resistant genes until BC3 generation. Plants having the maximum contribution from the recurrent parent genome were selected in each generation and hybridized with the recipient parent. The BB-pyramided line having the maximum recipient parent genome recovery of 95% was selected among BC3F1 plants and selfed to isolate homozygous BC3F2 plants with different combinations of BB resistance genes. Twenty pyramided lines with two resistance gene combinations exhibited high levels of tolerance against the BB pathogen. In order to confirm the resistance, the pyramided lines were inoculated with different X. oryzae pv. oryzae strains of Odisha for bioassay. The genotypes with combination of two BB resistance genes conferred high levels of resistance to the predominant X. oryzae pv. oryzae isolates prevalent in the region. The pyramided lines showed similarity with the recipient parent with respect to major agro-morphologic traits.

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.

Twenty four rice genotypes were analyzed under drought stress for seed proteins by SDS-PAGE to estimate their genetic diversity for the purpose of genetic improving under drought condition. The storage protein profiling banding pattern was scored based on the number and intensity of bands.A total of 90 poly peptide bands were harvested from twenty four individuals ranging from 14.3 kD to 99.0 kD. According to UPGMA dendrogram, 100% genetic similarities of protein profiling were exhibited between Basmati 370, Mahulata, Naveen and CR 143-2-2. The banding profile revealed that studied genotypes varies from each other either for total number or molecular weight or intensity of protein bands except the genotypes Naveen and CR 143-2-2. This electrophoretically detectable protein polymorphism in rice grain can be used in further breeding proposes and variety development. Our results suggest that, screening of these genotypes on the basis of variation in seed protein profile using SDS-PAGE could be highly effective tool to identify drought tolerant donors with good seed storage under drought stress.

Iron toxicity in rice field can cause abnormality in plant growth leading to yield loss of 35–45%. This is caused by microbial reduction under flooded conditions of insoluble iron-III (Fe 3+) into soluble iron-II (Fe2+). The severity and symptoms of Fe toxicity depends on the growth stage of rice plant at which it is exposed to the stress. The plant developed various mechanisms to avoid/tolerate such stress which is a complex phenomenon governed by multiple genes/QTLs. Very few chromosomal loci are reported for Fe toxicity resistance in rice. But no locus has been fine mapped or cloned yet. Association mapping provides opportunity to have a greater coverage of genetic diversity in various germplasm lines so that large number of loci can be identified for Fe toxicity in rice. In the present investigation, 71 genotypes including landraces and released varieties were screened for their Fe toxicity resistance ability. Various agro-morphologic traits were observed to be affected by Fe stress. The genotypes Dhusura, Jalapaya, Gelei, Kendrajhali, Rasapanjari, Saluagaja and Asinasita were observed to be resistant under field stress condition and controlled condition in hydroponic culture. These genotypes can be used as donor lines for improvement of Fe tolerance in rice. The marker-trait association study could identify the markers namely RM243, RM234, RM248, RM501, RM594 and RM517 to be associated with leaf bronzing index which is considered to be indicator of Fe toxicity resistance. These markers individually showed phenotypic variance ranging from 6.0–10.5%. These markers can further be used for marker assisted breeding programs to incorporate the Fe resistance genes/QTLs into susceptible high yielding popular varieties.

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.