Improvement of bacterial blight resistance of the popular variety, Nellore Mahsuri (NLR34449) through marker-assisted breeding.

To combat the dreaded diseases in rice like bacterial blight (BB) and blast, host plant resistance has been advocated as the most suitable and sustainable method. Through the present study, we have successfully incorporated three major BB resistance genes, namely Xa21, xa13 and xa5 into NLR3449, a high yielding, blast resistant, fine-grain type, popular rice variety through marker-assisted backcross breeding. Foreground selection was carried out using polymerase chain reaction based, gene-specific markers, namely pTA248 (Xa21), xa13prom (xa13) and xa5FM (xa5) at each generation of backcrossing, while 127 polymorphic SSR markers spanning on 12 chromosomes were used for background selection and backcrossing was limited to two rounds. At BC2F1 generation, a single plant (NLR-87-10) with 89.9% recovery, possessing all the three BB resistance genes was forwarded to BC2F2 generation. A solitary BC2F2 plant, namely NLR-87- 10-106 possessing all the three resistance genes and 96% genome recovery was identified and advanced through selfing until BC2F4 generation by adopting pedigree-method of selection. Three best BC2F4 lines, possessing high level of resistance against BB and blast, and equivalent or superior to NLR 34449 in terms of yield, grain quality and agro-morphological traits were identified and advanced for multilocation trials.

Mapping novel QTLs for yield related traits from a popular rice hybrid KRH-2 derived doubled haploid (DH) population.

A doubled haploid (DH) population consisting of 125 DHLs derived from the popular rice hybrid, KRH-2 (IR58025A/KMR3R) was utilized for Quantitative Trait Loci (QTL) mapping to identify novel genomic regions associated with yield related traits. A genetic map was constructed with 126 polymorphic SSR and EST derived markers, which were distributed across rice genome. QTL analysis using inclusive composite interval mapping (ICIM) method identified a total of 24 major and minor effect QTLs. Among them, twelve major effect QTLs were identified for days to fifty percent flowering (qDFF12-1), total grain yield/plant (qYLD3-1 and qYLD6-1), test (1,000) grain weight (qTGW6-1 and qTGW7-1), panicle weight (qPW9-1), plant height (qPH12-1), flag leaf length (qFLL6-1), flag leaf width (qFLW4-1), panicle length (qPL3-1 and qPL6-1) and biomass (qBM4-1), explaining 29.95-56.75% of the phenotypic variability with LOD scores range of 2.72-16.51. Chromosomal regions with gene clusters were identified on chromosome 3 for total grain yield/plant (qYLD3-1) and panicle length (qPL3-1) and on chromosome 6 for total grain yield/plant (qYLD6-1), flag leaf length (qFLL6-1) and panicle length (qPL6-1). Majority of the QTLs identified were observed to be co-localized with the previously reported QTL regions. Five novel, major effect QTLs associated with panicle weight (qPW9-1), plant height (qPH12-1), flag leaf width (qFLW4-1), panicle length (qPL3-1) and biomass (qBM4-1) and three novel minor effect QTLs for panicle weight (qPW3-1 and qPW8-1) and fertile grains per panicle (qFGP5-1) were identified. These QTLs can be used in breeding programs aimed to yield improvement after their validation in alternative populations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13205-021-03045-7.

Molecular mapping of QTLs for yield related traits in recombinant inbred line (RIL) population derived from the popular rice hybrid KRH-2 and their validation through SNP genotyping.

The study was undertaken to identify the quantitative trait loci (QTLs) governing yield and its related traits using a recombinant inbred line (RIL) population derived from the popular rice hybrid, KRH-2 (IR58025A/KMR3R). A genetic map spanning 294.2 cM was constructed with 126 simple sequence repeats (SSR) loci uniformly distributed across the rice genome. QTL analysis using phenotyping and genotyping information identified a total of 22 QTLs. Of these, five major effect QTLs were identified for the following traits: total grain yield/plant (qYLD3-1), panicle weight (qPW3-1), plant height (qPH12-1), flag leaf width (qFLW4-1) and panicle length (qPL3-1), explaining 20.23-22.76% of the phenotypic variance with LOD scores range of 6.5-10.59. Few genomic regions controlling several traits (QTL hotspot) were identified on chromosome 3 for total grain yield/plant (qYLD3-1) and panicle length (qPL3-1). Significant epistatic interactions were also observed for total grain yield per plant (YLD) and panicle length (PL). While most of these QTLs were observed to be co-localized with the previously reported QTL regions, a novel, major QTL associated with panicle length (qPL3-1) was also identified. SNP genotyping of selected high and low yielding RILs and their QTL mapping with 1,082 SNPs validated most of the QTLs identified through SSR genotyping. This facilitated the identification of novel major effect QTLs with much better resolution and precision. In-silico analysis of novel QTLs revealed the biological functions of the putative candidate gene (s) associated with selected traits. Most of the high-yielding RILs possessing the major yield related QTLs were identified to be complete restorers, indicating their possible utilization in development of superior rice hybrids.