RESUMEN
In the current global warming scenario, it is imperative to develop crops with improved heat tolerance or acclimation, for which knowledge of major heat stress-tolerant genes or genomic regions is a prerequisite. Though several quantitative trait loci (QTLs) for heat tolerance have been mapped in rice, candidate genes from these QTLs have not been reported yet. The meta-analysis of microarray datasets for heat stress in rice can give us a better genomic resource for the dissection of QTLs and the identification of major candidate genes for heat stress tolerance. In the present study, a database, RiceMetaSys-H, comprising 4227 heat stress-responsive genes (HRGs), was created using seven publicly available microarray datasets. This included in-house-generated microarray datasets of Nagina 22 (N22) and IR64 subjected to 8 days of heat stress. The database has provisions for searching the HRGs through genotypes, growth stages, tissues, and physical intervals in the genome, as well as Locus IDs, which provide complete information on the HRGs with their annotations and fold changes, along with the experimental material used for the analysis. The up-regulation of genes involved in hormone biosynthesis and signalling, sugar metabolism, carbon fixation, and the ROS pathway were found to be the key mechanisms of enhanced heat tolerance. Integrating variant and expression analysis, the database was used for the dissection of the major effect of QTLs on chromosomes 4, 5, and 9 from the IR64/N22 mapping population. Out of the 18, 54, and 62 genes in these three QTLs, 5, 15, and 12 genes harboured non-synonymous substitutions. Fifty-seven interacting genes of the selected QTLs were identified by a network analysis of the HRGs in the QTL regions. Variant analysis revealed that the proportion of unique amino acid substitutions (between N22/IR64) in the QTL-specific genes was much higher than the common substitutions, i.e., 2.58:0.88 (2.93-fold), compared to the network genes at a 0.88:0.67 (1.313-fold) ratio. An expression analysis of these 89 genes showed 43 DEGs between IR64/N22. By integrating the expression profiles, allelic variations, and the database, four robust candidates (LOC_Os05g43870, LOC_Os09g27830, LOC_Os09g27650, andLOC_Os09g28000) for enhanced heat stress tolerance were identified. The database thus developed in rice can be used in breeding to combat high-temperature stress.
RESUMEN
Deeper Rooting 1 (DRO1) gene identified from a major QTL on chromosome 9 increases the root growth angle (RGA) and thus facilitates survival under drought and hence is an excellent candidate for rice improvement. Twenty-four major Indian upland and lowland genotypes including the 'yield under drought' (DTY) QTL donors were subjected to allele mining of DRO1 (3058 bp) using four pairs of overlapping primers. A total of 216 and 52 SNPs were identified across all genotypes in the gene and coding region (756 bp) respectively with transversions 3.6 fold more common than transitions in the gene and 2.5 times in the CDS. In 251 amino acid long protein, substitutions were found in 19 positions, wherein change in position 92 was the most frequent. Based on allele mining, the 24 genotypes can be classified into 16 primary structure variants ranging from complete functional allele (Satti, IR36 and DTY 3.1 donor, IR81896-B-B-195) to truncated non-functional alleles in PMK2, IR64, IR20 and Swarna. All the DTY donors, other than IR81896-B-B-195, and most of the upland drought tolerant cultivars (Nagina 22, Vandana and Dhagaddeshi) had accumulated 6-19 SNPs and 4-8 amino acid substitutions resulting in substantial differences in their protein structure. The expression analysis revealed that all the genotypes showed upregulation under drought stress though the degree of upregulation varied among genotypes. The information on structural variations in DRO1 gene will be very useful for the breeders, especially in the light of recent breeding programmes on improving drought tolerance using several DTY donors and upland accessions. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s12298-021-00950-2).