Characterization and Expression Analysis of Resistance Gene Analogues in Elite Sugarcane Genotypes - Parvaiz, Aqsa; Mustafa, Ghulam; Khan, Muhammad S.; Ali, Muhammad Amjad (Protein and Peptide Letters, 2021)
Background: Resistance Gene Analogues (RGAs) are an important source of disease resistance in crop plants and have been extensively studied for their identification, tagging and mapping of Quantitative Trait Loci (QTLs). Tracking these RGAs in sugarcane can be of great help for the selection and screening of disease resistant clones. Objective: In the present study expression of different Resistance Gene Analogues (RGAs) was assessed in indigenous elite sugarcane genotypes which include resistant, highly resistant, susceptible and highly susceptible to disease infestation. Methods: Total cellular DNA and RNA were isolated from fourteen indigenous elite sugarcane genotypes. PCR, semi-quantitative RT PCR and real time qPCR analyses were performed. The resultant amplicons were sequence characterized, chromosomal localization and phylogenetic analysis were performed. Results: All of the 15 RGA primers resulted in amplification of single or multiple fragments from genomic DNA whereas only five RGA primers resulted in amplification from cDNA. Sequence characterization of amplified fragments revealed 86-99% similarity with disease resistance proteins indicating their potential role in disease resistance response. Phylogenetic analysis also validated these findings. Further, expression of RGA-012, RGA-087, RGA-118, RGA-533 and RGA-542 appeared to be upregulated and down regulated in disease resistant and susceptible genotypes, respectively, after inoculation with Colletotrichum falcatum. Conclusion: RGAs are present in most of our indigenous genotypes. Anyhow, differential expression of five RGAs indicated that they have some critical role in disease resistance. So, the retrieved results can not only be employed to devise molecular markers for the screening of disease resistant genotypes but can also be used to develop disease resistant plants through transgenic technology.
Keywords: expression analysis