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. 2020 Nov 25;18(1):75.
doi: 10.1186/s43141-020-00076-0.

In silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars

R Chandrakanth  1 , L Sunil  2 , L Sadashivaiah  1 , N S Devaki  3
Affiliations

In silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars

R Chandrakanth et al. J Genet Eng Biotechnol. .

Abstract

Background: Nucleotide-binding site-leucine-rich repeat (NBS-LRR) resistance genes are the largest class of plant resistance genes which play an important role in the plant defense response. These genes are better conserved than others and function as a recognition-based immune system in plants through their encoded proteins.

Results: Here, we report the effect of Magnaporthe oryzae, the rice blast pathogen inoculation in resistant BR2655 and susceptible HR12 rice cultivars. Transcriptomic profiling was carried out to analyze differential gene expression in these two cultivars. A total of eight NBS-LRR uncharacterized resistance proteins (RP1, RP2, RP3, RP4, RP5, RP6, RP7, and RP8) were selected in these two cultivars for in silico modeling. Modeller 9.22 and SWISS-MODEL servers were used for the homology modeling of eight RPs. ProFunc server was utilized for the prediction of secondary structure and function. The CDvist Web server and Interpro scan server detected the motif and domains in eight RPs. Ramachandran plot of eight RPs confirmed that the modeled structures occupied favorable positions.

Conclusions: From the present study, computational analysis of these eight RPs may afford insights into their role, function, and valuable resource for studying the intricate details of the plant defense mechanism. Furthermore, the identification of resistance proteins is useful for the development of molecular markers linked to resistance genes.

Keywords: Homology modeling; In silico analysis; NBS-LRR; Resistance proteins; Rice blast.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
a Domain architecture of eight resistance proteins predicted by the Cdvist web server tool and b phylogenetic relationship among the eight rice blast resistance protein trees generated using the neighbor-joining method by MEGA.7 software with bootstrap value 1000 replications
Fig. 2
Fig. 2
Three-dimensional structures of eight resistance protein RP1-RP8 models by RaptorX
Fig. 3
Fig. 3
Secondary structures of eight resistance proteins by ProFunc server
Fig. 4
Fig. 4
Binding sites of RP1, RP2, RP3, RP4, RP5, RP6, RP7, and RP8 resistance proteins by using the COACH server based on the I-TASSER structure prediction
Fig. 5
Fig. 5
Ramachandran plot statistics of eight resistance proteins
See this image and copyright information in PMC

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