Abstract:
The complexity of any infectious disease is primarily due to the complicated interactions between the sets of genes involved in the process. There are several host proteins and genes in the case of cotton leaf curl virus disease (CLCuD) that interact with viral proteins and control the integration of disease. Widely cultivated cotton species, Gossypium hirsutum, is generally susceptible to CLCuD, while the diploid species G. arboreum is a natural source for resistance while Mac-7, an accession of G. hirsutum, is reported to be tolerance against CLCuD. In this study, RNA-Seq-based study is used to explore differential gene expression patterns in cotton plants of different species under CLCuD infestation. Comparative transcriptomics analysis aided in selection of bunch of genes from the whole cotton transcriptome. The KEEG pathway analysis for reported genes, exploring motif pattern and evolutionary analysis based on structural algorithms helped in connecting dots to confirmation. The protein encoded by beta DNA, ßC1, is the determinant of both pathogenicity and suppression of gene silencing. Therefore, protein modelling was performed and to assess actual protein structure among the CLCuV strains. Protein docking procedures were opted to identify set of host proteins interactions with ßC1. In addition to prediction of binding affinity, we used multiple binding site prediction. Snapping methods such as CLUSPRO and Pymol predicted ten patterns along with their predicted confidence values. To validate the output of insilco framework, RNA was extracted from the leaves of representative cotton plants. Gene expression values confirmed that genes identified in host plant After finding genes involved in cotton immunity. This work could contribute towards development of more resistant varieties through genetic engineering of plant-pathogen molecular mechanisms can be prepared in future. Methods based on protein sequence and structure.
Page(s):
113-113
DOI:
DOI not available
Published:
Journal: Abstract Book on Global Science Technology and Management Conference, Volume: 0, Issue: 0, Year: 2023