SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-022-01141-3.
METHODS: In our study, we developed 290 BC1F1 backcross progenies from a cross between UKMRC2 and Tetep to introgress the QTL qSBR11-1TT into the UKMRC2 genetic background. Validation of the introgressed QTL region was performed via QTL analysis based on QTL-linked SSR marker genotyping and phenotyping against R. solani artificial field inoculation techniques.
RESULTS AND DISCUSSION: The QTL qSBR11-1TT was then authenticated with the results of LOD score (3.25) derived from composite interval mapping, percent phenotypic variance explained (14.6%), and additive effect (1.1) of the QTLs. The QTL region was accurately defined by a pair of flanking markers K39512 and RM7443 with a peak marker RM27360. We found that the presence of combination of alleles, RM224, RM27360 and K39512 demonstrate an improved resistance against the disease rather than any of the single allele. Thus, the presence of the QTL qSBR11-1TT has been validated and confirmed in the URMRC2 genetic background which reveals an opportunity to use the QTL linked with these resistance alleles opens an avenue to resume sheath blight resistance breeding in the future with marker-assisted selection program to boost up resistance in rice varieties.
METHODS: HKEx was evaluated using GC-MS and undertaken for a three-week intervention in fructose-fed STZ-induced Wistar albino rats at the doses of HKEx50, HKEx100, and HKEx200 mg/kg bw. Following intervention, blood serum was examined for biochemical markers, and liver tissue was investigated for the mRNA expression of catalase (CAT), glutathione peroxidase (GPx), and superoxide dismutase (SOD1) by RTPCR analysis. Most abundant compounds (oleanolic acid, 7α, 28-olean diol, and stigmasterol) from GC-MS were chosen for the network pharmacological assay to verify function-specific gene-compound interactions using STITCH, STRING, GSEA, and Cytoscape plugin cytoHubba.
RESULTS: In vivo results showed a significant (P < 0.05) decrease of blood sugar, aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine kinase (CK-MB), and lactate dehydrogenase (LDH) and increase of liver glycogen, glucose load, and serum insulin. Out of three antioxidative genes, catalase (CAT) and superoxide dismutase (SOD1) were found to be few fold increased. Oleanolic acid and stigmasterol were noticed to strongly interact with 27 target proteins. Oleanolic acid interacted with the proteins AKR1B10, CASP3, CASP8, CYP1A2, CYP1A2, HMGB1, NAMPT, NFE2L2, NQO1, PPARA, PTGIR, TOP1, TOP2A, UGT2B10, and UGT2B11 and stigmasterol with ABCA1, ABCG5, ABCG8, CTSE, HMGCR, IL10, CXCL8, NR1H2, NR1H3, SLCO1B1, SREBF2, and TNF. Protein-protein interaction (PPI) analysis revealed the involvement of 25 target proteins out of twenty seven. Cytoscape plugin cytoHubba identified TNF, CXCL8, CASP3, PPARA, SREBF2, and IL10 as top hub genes. Pathway analysis identified 31 KEGG metabolic, signaling, and immunogenic pathways associated with diabetes. Notable degree of PPI enrichment showed that SOD1 and CAT are responsible for controlling signaling networks and enriched pathways.
CONCLUSION: The findings show that antioxidative genes have regulatory potential, allowing the HKEx to be employed as a possible antidiabetic source pending further validation.