Rice Galaxy: An open resource for plant science

Background: Rice molecular genetics, breeding, genetic diversity, and allied research (such as rice-pathogen interaction) have adopted sequencing technologies and high-density genotyping platforms for genome variation analysis and gene discovery. Germplasm collections representing rice diversity, improved varieties, and elite breeding materials are accessible through rice gene banks for use in research and breeding, with many having genome sequences and high-density genotype data available. Combining phenotypic and genotypic information on these accessions enables genome-wide association analysis, which is driving quantitative trait loci discovery and molecular marker development. Comparative sequence analyses across quantitative trait loci regions facilitate the discovery of novel alleles. Analyses involving DNA sequences and large genotyping matrices for thousands of samples, however, pose a challenge to non−computer savvy rice researchers. Findings: The Rice Galaxy resource has shared datasets that include high-density genotypes from the 3,000 Rice Genomes project and sequences with corresponding annotations from 9 published rice genomes. The Rice Galaxy web server and deployment installer includes tools for designing single-nucleotide polymorphism assays, analyzing genome-wide association studies, population diversity, rice−bacterial pathogen diagnostics, and a suite of published genomic prediction methods. A prototype Rice Galaxy compliant to Open Access, Open Data, and Findable, Accessible, Interoperable, and Reproducible principles is also presented. Conclusions: Rice Galaxy is a freely available resource that empowers the plant research community to perform state-of-the-art analyses and utilize publicly available big datasets for both fundamental and applied science

Gene Expression Profiles Deciphering Rice Phenotypic Variation between Nipponbare (Japonica) and 93-11 (Indica) during Oxidative Stress

Rice is a very important food staple that feeds more than half the world's population. Two major Asian cultivated rice (Oryza sativa L.) subspecies, japonica and indica, show significant phenotypic variation in their stress responses. However, the molecular mechanisms underlying this phenotypic variation are still largely unknown. A common link among different stresses is that they produce an oxidative burst and result in an increase of reactive oxygen species (ROS). In this study, methyl viologen (MV) as a ROS agent was applied to investigate the rice oxidative stress response. We observed that 93-11 (indica) seedlings exhibited leaf senescence with severe lesions under MV treatment compared to Nipponbare (japonica). Whole-genome microarray experiments were conducted, and 1,062 probe sets were identified with gene expression level polymorphisms between the two rice cultivars in addition to differential expression under MV treatment, which were assigned as Core Intersectional Probesets (CIPs). These CIPs were analyzed by gene ontology (GO) and highlighted with enrichment GO terms related to toxin and oxidative stress responses as well as other responses. These GO term-enriched genes of the CIPs include glutathine S-transferases (GSTs), P450, plant defense genes, and secondary metabolism related genes such as chalcone synthase (CHS). Further insertion/deletion (InDel) and regulatory element analyses for these identified CIPs suggested that there may be some eQTL hotspots related to oxidative stress in the rice genome, such as GST genes encoded on chromosome 10. In addition, we identified a group of marker genes individuating the japonica and indica subspecies. In summary, we developed a new strategy combining biological experiments and data mining to study the possible molecular mechanism of phenotypic variation during oxidative stress between Nipponbare and 93-11. This study will aid in the analysis of the molecular basis of quantitative traits

SSRs for marker assisted selection for blast resistance in rice (Oryza sativa L.).

Rice blast caused by the fungus Magnaporthe oryzae is one of the most devastating diseases of rice in nearly all rice growing areas of the world including Malaysia. To develop cultivars with resistance against different races of M. oryzae, availability of molecular markers along with marker-assisted selection strategies are essential. In this study, 11 polymorphic simple sequence repeat (SSR) markers with good fit of 1:2:1 ratio for single gene model in F2 population derived from the cross of Pongsu seribu 2 (Resistant) and Mahsuri (Susceptible) rice cultivars were analysed in 296 F3 families derived from individual F2 plants to investigate association with Pi gene conferring resistance to M. oryzae pathotype. Parents and progeny were grouped into two phenotypic classes based on their blast reactions. Chi-square test for the segregation of resistance and susceptibility in F3 generation fitted a ratio of approximately 3:1. Association of SSR markers with phenotypic trait in F3 families was identified by statistical analysis. Four SSR markers (RM413, RM5961, RM1233 and RM8225) were significantly associated with blast resistance to pathotype 7.2 of M. oryzae in rice (p ≤ 0.01). These four markers accounted for about 20% of total phenotypic variation. So, these markers were confirmed as suitable markers for use in marker-assisted selection and confirmation of blast resistance genes to develop rice cultivars with durable blast resistance in Malaysian rice breeding programmes

Phenotypic and genotypic screening of rice genotypes at seedling stage for salt tolerance

Selection for salinity tolerance genotypes of rice based on phenotypic performance alone is less reliable and will delay progress in breeding. Recent advent of molecular markers, microsatellites or simple sequence repeats (SSRs) are used to find out salt tolerant rice genotypes. Three selected SSR markers; RM7075, RM336 and RM253 were used to evaluate rice genotypes for salt tolerance. Phenotypic and genotypic evaluation for salinity tolerance was done at the seedling stage. Phenotypingof 11 genotypes was done in hydroponic system using salinized (EC 12 dS/m) nutrient solution. IRRI standard protocol was followed to evaluate salinity tolerance. Large variation in salinity tolerance among the rice germplasms was detected. Plant height and total dry matter of tolerant lines were reduced by 19.0 and 40.6%, respectively under salt stress (EC 12 dS/m), whereas those of susceptible lines were reduced by 46.0 and 73.5%, respectively. The markers showed polymorphism and were ableto discriminate salt tolerant genotypes from susceptible. The genotypes having similar banding pattern with Pokkali were considered as salt tolerant. The SSR markers (RM7075, RM336 and RM253) identified8, 9 and 7 salt tolerant genotypes, respectively. Through phenotypic and genotypic study, three genotypes viz., Pokkali, TNDB-100 and THDB were identified as salt tolerant rice cultivar. These SSR markers might have sequence homology with salt tolerant rice genotypes and consequently themarkers could able to identify salt tolerant rice genotypes from susceptibles

Identification of putative candidate gene markers for grain zinc content using recombinant inbred lines (RIL) population of IRRI38 X Jeerigesanna

Nutrients in food crops can be enriched by adopting biofortification. Identifying the target quantitative trait loci (QTL) genes will help achieve biofortification with greater precision and accuracy. The objective of this experiment is to estimate grain zinc content, evaluation of candidate gene markers in recombinant inbred lines (RIL) derived from IRRI38 X Jeerigesanna and validation of putative candidate gene markers with rice accessions. Grain zinc content ranged from 16.1 to 35.5 ppm with an average of 23.7 ppm. Among twenty four candidate gene markers, eight showed polymorphism and out of three simple sequence repeats (SSR) markers, three showed polymorphism. Single marker analysis revealed that four (OsNAC, OsZIP8a, OsZIP8c and OsZIP4b) candidate gene markers showed significant variation among RIL population with a phenotypic variation of 4.5, 19.0, 5.1 and 10.2% respectively. Validation with 96 rice genotypes showed three markers (OsZIP8a, OsNAC and OsZIP4b) with phenotypic variation of 11.0, 5.8 and 4.8%, respectively.Keywords: Zinc, biofortification, single-marker analysis (SMS) and marker assisted selection (MAS)African Journal of Biotechnology, Vol. 13(5), pp. 657-663, 29 January, 201

Evaluation of rice genotypes for brown planthopper (BPH) resistance using molecular markers and phenotypic methods

Twenty eight (28) rice genotypes were used to evaluate the genetic variability based on known BPH resistant loci spread through most of the genome (chromosomes 2, 3, 4, 5, 6, 8, 10, 11 and 12), using closely linked simple sequence repeat (SSR) markers and by different phenotypic screening methods. A total number of 155 alleles were detected by 30 polymorphic markers with an average of 4.6 per locus. The genetic diversity, polymorphic information content (PIC) ranged from 0.15 to 0.89 and 0.13 to 0.88, respectively and the allele frequency ranged from 0.21 to 0.89. These microsatellite markers linked to BPH resistance loci classified rice genotypes into three clusters with additional sub groups and sub sub groups. Our study reveals high genetic variation and clear genotypic relationship for BPH resistance based on BPH resistance linked markers and known phenotypic screening methods such as standard seedbox screening technique, honey dew test and nymphal survival method. Phenotypic evaluation showed clear distinction between resistant and susceptible type by clearly revealing moderately resistant types as well. Combined use of phenotypic and genotypic evaluation methods can improve the efficiency of marker assisted selection and utilization of resistant genotypes for crop improvement by rice breeders.Keywords: Nilaparvata Lugens, microsatellite markers, polymorphism, genetic diversityAfrican Journal of Biotechnology Vol. 12(19), pp. 2515-252

Effect of rice planting date and optimal planting window for Southwest Louisiana

Rice (Oryza sativa L.) yield and grain quality are highly influenced by the planting date; thus, it is crucial to determine the optimal planting window for an area of cultivation. In this study, date of planting experiments conducted at the Louisiana State University (LSU) AgCenter Rice Research Station from 2011 to 2018 were analyzed to quantify the effect of planting date, genotype, and year on key agronomic traits. Planting date was strongly associated with yield across every year, explaining 55.6% of the overall phenotypic variation. A clear relationship was observed between later plantings and reduced yields; and the highest yields were observed during plantings between 11 and 31 March. Rice planted after the optimal planting window displays a yield reduction following a cubic regression trend. Planting date was associated with milling yield, explaining 28.6% of the phenotypic variation, however the effect size varied year to year. Milling yields were highest with the early and late planting dates, while reduced milling yields were observed in plantings between mid-April and early June. Days to heading and days to seedling emergence were strongly associated with planting date; with planting date explaining, on average, 86 and 96% of the variation, respectively. Plant height was less influenced by planting date, with genotype being the largest source of variation. The results from this study highlight the importance of choosing the optimal planting date and identifies an optimal planting window to maximize grain and milling yield for Southwest Louisiana

Genetic diversity of Myanmar rice and their implementation on management methods

Myanmar has diverse agronomic landscape and potentially preserves high level of genetic resources for important crop species. However, little study on rice landrace diversity in Myanmar has been done. Genetic and phenotypic variation to characterize rice genetic resource in Myanmar was analyzed using molecular markers as well as common garden experiments. Two populations of rice landraces, a seedbank population maintained by seed-propagation in a genebank for several generations and an “onfarm” population collected from agricultural lands were used. A functional (cytochrome P450 related PBA) and neutral (SSR) markers were used in this study. Phenotypic characteristics of representative agronomic traits in rice, such as culm length, panicle length, number of tillers and days to heading, were measured in both populations. Multivariate analysis suggested that the seed-bank and on-farm population had different genetic bases with both functional and neutral markers. There was no significant relationship between the functional and neutral markers based on Mantel test. In addition, PCA analyses of agronomic traits showed that a variation in the seed-bank population had narrower genetic bases than the on-farm population. Genetic bias caused by ‘unconscious selection’ during the genebank management processes may have occurred in the landraces. The importance of the conservation on on-farm landraces of Oryza sativa and its wild relatives was proposed in order to ensure the genetic resources for further breeding and conserve biological diversity.Key words: Oryza sativa, rice, landrace, on-farm, diversity, conservation