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Not AvailableRice sheath blight (ShB) disease, caused by the fungal pathogen Rhizoctonia solani AG1-IA, is one of the devastating diseases and causes severe yield losses all over the world. No completely resistant germplasm is known till now, and as a result, the progress in resistance breeding is unsatisfactory. Basic studies to identify candidate genes, QTLs, and to better understand the host–pathogen interaction are also scanty. In this study, we report the identification of a new ShB-tolerant rice germplasm, CR 1014. Further, we investigated the basis of tolerance by exploring the disease responsive differentially expressed transcriptome and comparing them with that of a susceptible variety, Swarna-Sub1. A total of 815 and 551 genes were found to be differentially regulated in CR 1014 and Swarna-Sub1, respectively, at two different time points. The result shows that the ability to upregulate genes for glycosyl hydrolase, secondary metabolite biosynthesis, cytoskeleton and membrane integrity, the glycolytic pathway, and maintaining photosynthesis make CR 1014 a superior performer in resisting the ShB pathogen. We discuss several putative candidate genes for ShB resistance. The present study, for the first time, revealed the basis of ShB tolerance in the germplasm CR1014 and should prove to be particularly valuable in understanding molecular response to ShB infection. The knowledge could be utilized to devise strategies to manage the disease better.Not Availabl

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Not AvailableSheath blight disease of rice causes substantial crop losses and resistance sources are rare. A moderately resistant genotype CR 1014 was identified and hybridized with highly susceptible genotype Swarna-Sub1. In the F2 and F2:3 generations, three QTLs (qShB-1.1, qShB-1.2 and qShB-1.3) were mapped in chromosome-1. In F5 generation of the same cross and F4 generation of an alternative mapping population (Tapaswini/CR 1014), only the major QTL qShB-1.1 was recorded consistently with high LOD score (> 5.0). This stable QTL was co-localized with qShB1 reported earlier from Oryza nivara. A typical leucine rich repeat (LRR) motif containing gene (LOC_Os01g65650) and a chitin-inducible gibberellin-responsive protein coding non-LRR gene (LOC_Os01g65900) located within qShB-1.1 with high expression levels in leaf and shoot were predicted as putative candidate genes among others. Nearly 27.8% reduction in relative lesion height was recorded among several near isogenic lines of Swarna-Sub1 carrying the QTL region from CR 1014.ICA

Development of Decadal (1985–1995–2005) Land Use and Land Cover Database for India

India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study