Genetic relationship, population structure analysis and pheno-molecular characterization of rice (Oryza sativa L.) cultivars for bacterial leaf blight resistance and submergence tolerance using trait specific STS markers.

Rice is an important source of calorie for the growing world population. Its productivity, however is affected by climatic adversities, pest attacks, diseases of bacterial, viral and fungal origin and many other threats. Developing cultivars that are high yielding and stress resilient seems a better solution to tackle global food security issues. This study investigates the potential resistance of 24 rice cultivars against Xanthomonas oryzae pv. Oryzae (Xoo) infection that causes bacterial leaf blight disease and submergence stress. Bacterial leaf blight (BLB) resistance genes (Xa4, xa5, xa13, Xa21, Xa38) and submergence tolerance (Sub1) gene specific markers were used to determine the allelic status of genotypes. The results displayed presence of Xa4 resistance allele (78.95%), xa5 (15.79%) but xa13 and Sub1 tolerance allele were not found in any genotype. However, a new allele for Xa21 (84.21%) and Xa38 (10.52%) were identified in several genotypes. Phenotypic screening for both stress conditions was done to record the cultivars response. None of the genotypes showed resistance against Xoo, although varieties viz., Tapaswini and Konark showed moderate susceptibility. Likewise, survival percentage of genotypes under submergence stress varied from 0 to 100%. Tolerant checks FR13A (100%) and Swarna Sub1 (97.78%) exhibited high survival rate, whereas among genotypes, Gayatri (57.78%) recorded high survivability even though it lacked Sub1 tolerant its genetic background. A total of six trait specific STS and two SSR markers generated an average of 2.38 allele per locus. Polymorphism information content (PIC) value ranged from 0.08 to 0.42 with an average of 0.20. Structure analysis categorized 24 genotypes into two sub-populations, which was in correspondence with Nei's genetic distance-based NJ tree and principal co-ordinate analysis (PCoA). Swarna Sub1 could be differentiated clearly from BLB resistant check, IRBB60 and other 22 genotypes without having Sub1 gene. Analysis of molecular variance (AMOVA) revealed more genetic variation within population than among population. Principal component analysis (PCA) showed that 9 morphological traits collectively explained 76.126% of total variation among all the genotypes studied. The information from this study would be useful in future breeding programs for pyramiding trait specific genes into high yielding cultivars that fall behind with respect to stress resilience. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-00951-1.

Identification of QTLs for high grain yield and component traits in new plant types of rice.

A panel of 60 genotypes comprising New Plant Types (NPTs) along with indica, tropical and temperate japonica genotypes was phenotypically evaluated for four seasons in irrigated situation for grain yield per se and component traits. Twenty NPT genotypes were found promising with an average grain yield varying from 5.45 to 8.8 t/ha. A total of 85 SSR markers were used in the study to identify QTLs associated with grain yield per se and related traits. Sixty-six (77.65%) markers were found to be polymorphic. The PIC values varied from 0.516 to 0.92 with an average of 0.704. A moderate level of genetic diversity (0.39) was detected among genotypes. Variation to the tune of 8% within genotypes, 68% among the genotypes within the population and 24% among the populations were observed (AMOVA). This information may help in identification of potential parents for development of transgressive segregants with very high yield. The association analysis using GLM and MLM models led to the identification of 30 and 10 SSR markers associated with 70 and 16 QTLs, respectively. Thirty novel QTLs linked with 16 SSRs were identified to be associated with eleven traits, namely tiller number (qTL-6.1, qTL-11.1, qTL-4.1), panicle length (qPL-1.1, qPL-5.1, qPL-7.1, qPL-8.1), flag leaf length (qFLL-8.1, qFLL-9.1), flag leaf width (qFLW-6.2, qFLW-5.1, qFLW-8.1, qFLW-7.1), total no. of grains (qTG-2.2, qTG-a7.1), thousand-grain weight (qTGW-a1.1, qTGW-a9.2, qTGW-5.1, qTGW-8.1), fertile grains (qFG-7.1), seed length-breadth ratio (qSlb-3.1), plant height (qPHT-6.1, qPHT-9.1), days to 50% flowering (qFD-1.1) and grain yield per se (qYLD-5.1, qYLD-6.1a, qYLD-11.1).Some of the SSRs were co-localized with more than two traits. The highest co-localization was identified with RM5709 linked to nine traits, followed by RM297 with five traits. Similarly, RM5575, RM204, RM168, RM112, RM26499 and RM22899 were also recorded to be co-localized with more than one trait and could be rated as important for marker-assisted backcross breeding programs, for pyramiding of these QTLs for important yield traits, to produce new-generation rice for prospective increment in yield potentiality and breaking yield ceiling.

Differential Expression of Genes at Panicle Initiation and Grain Filling Stages Implied in Heterosis of Rice Hybrids.

RNA-Seq technology was used to analyze the transcriptome of two rice hybrids, Ajay (based on wild-abortive (WA)-cytoplasm) and Rajalaxmi (based on Kalinga-cytoplasm), and their respective parents at the panicle initiation (PI) and grain filling (GF) stages. Around 293 and 302 million high quality paired-end reads of Ajay and Rajalaxmi, respectively, were generated and aligned against the Nipponbare reference genome. Transcriptome profiling of Ajay revealed 2814 and 4819 differentially expressed genes (DEGs) at the PI and GF stages, respectively, as compared to its parents. In the case of Rajalaxmi, 660 and 5264 DEGs were identified at PI and GF stages, respectively. Functionally relevant DEGs were selected for validation through qRT-PCR, which were found to be co-related with the expression patterns to RNA-seq. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated significant DEGs enriched for energy metabolism pathways, such as photosynthesis, oxidative phosphorylation, and carbon fixation, at the PI stage, while carbohydrate metabolism-related pathways, such as glycolysis and starch and sucrose metabolism, were significantly involved at the GF stage. Many genes involved in energy metabolism exhibited upregulation at the PI stage, whereas the genes involved in carbohydrate biosynthesis had higher expression at the GF stage. The majority of the DEGs were successfully mapped to know yield related rice quantitative trait loci (QTLs). A set of important transcription factors (TFs) was found to be encoded by the identified DEGs. Our results indicated that a complex interplay of several genes in different pathways contributes to higher yield and vigor in rice hybrids.