Characterization of Potential Virus Resistance Genes in Different Crops Through In-silico Approaches

Mehar Ali Raza; Rida Zaib; Aimen Khalid; Amna Afzal; Faheem Kanwal; Muhammad Azmat; Imran  Zafar; Shaista  Shafiq

doi:10.70749/ijbr.v3i2.648

Authors

Mehar Ali Raza Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Punjab, Pakistan.
Rida Zaib Department of Microbiology, Faculty of Science and Technology, University of Central Punjab, Lahore, Punjab, Pakistan.
Aimen Khalid Department of Zoology, Government College University Faisalabad, Faisalabad, Punjab, Pakistan.
Amna Afzal Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Punjab, Pakistan.
Faheem Kanwal Institute of Molecular Biology and Biotechnology (IMBB), University of Lahore, Punjab, Pakistan.
Muhammad Azmat Institute of Molecular Biology and Biotechnology (IMBB), University of Lahore, Punjab, Pakistan.
Imran Zafar Department of Biochemistry and Biotechnology, The University of Faisalabad (TUF), Faisalabad, Punjab, Pakistan. https://orcid.org/0000-0002-9246-0850
Shaista Shafiq Department of Biochemistry and Biotechnology, The University of Faisalabad (TUF), Faisalabad, Punjab, Pakistan.

DOI:

https://doi.org/10.70749/ijbr.v3i2.648

Keywords:

Cotton Leaf Curl Virus (CLCuV), Resistance Gene Analogs (RGAs), Gossypium Hirsutum, Molecular Modelling, Bioinformatics Analysis

Abstract

Begomoviruses, particularly the cotton leaf curl virus (CLCuV), pose significant threats to global agriculture, especially cotton production. This study identified five resistance gene analogs (RGAs)—KT250635, KT886994, KT633945, KT885194, and KT633946—in Gossypium hirsutum and evaluated their potential against CLCuV using bioinformatics and molecular modeling approaches. Structural validation through Ramachandran plot analysis demonstrated that KT250635 and KT886994 had 92.6% residues in the most favored regions, while KT633945 and KT633946 exhibited slightly lower stereochemical reliability, requiring further refinement. GMQE scores ranged from 0.48 to 0.79, with KT250635 achieving a high residue quality score of 0.90. Functional annotation revealed significant homology, with KT250635 sharing 93.1% similarity with Sorghum bicolor and 97.1% with Gossypium raimondii, suggesting broad-spectrum resistance potential. Protein modeling and validation through I-TASSER and QMEAN-Z scores demonstrated structural stability, with KT250635 emerging as the most promising candidate. Phylogenetic analysis clustered KT250635 and KT886994 closely with resistance-related genes across diverse taxa, highlighting evolutionary conservation and functional significance. Additionally, KT633945 and KT885194 exhibited genetic similarity with peach and wild legumes, suggesting potential cross-species resistance traits. Bootstrap analysis with 1000 replicates ensured the robustness of the phylogenetic clustering. These findings provide a strong foundation for breeding CLCuV-resistant cotton varieties and underscore the importance of genetic insights in sustainable crop protection. These results contribute to understanding resistance mechanisms in cotton and may aid in the genetic improvement of susceptible varieties. Future studies should explore the functional role of these genes in resistance pathways and their potential applicability in other crop species to enhance resilience against viral pathogens.

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