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Chickpea is an important crop that delivers nutritious food to the increasing global community and it will become increasingly popular as a result of climate change. Our objective was to use comprehensive data analysis to locate and identify candidate genes for fungal disease resistance. We used a comprehensive bioinformatics pipeline of sequence alignment, phylogenetic analysis, protein chemical and physical properties assessment and domain structure classification. In order to study gene evolution and genetic diversity, we compared these genes with known anti-fungal genes in different species of plants. A total of 19721 protein sequences belonging to 187 plant species have been downloaded from public databases, including the entire Chickpea genome. We have successfully identified 23 potential anti-fungal genes in 10 different chromosomes and genomic scaffolds using sequence alignment and gene annotation. Ca2 and Ca6 have the highest number of genes followed by Ca3 and Ca4. Anti-fungal chickpea proteins have been identified as cysteine-rich (10), thaumatin (6), pathogenesis (4) and plasmodesmata (3) proteins. Analysis of the chemical and physical correlation of anti-fungal proteins revealed a high correlation between different aspects of anti-fungal proteins. Five different pattern patterns have been detected in the anti-fungal chickpea proteins identified, including domain families associated with fungal resistance. The maximum-likelihood of phylogenetic analysis was successful in distinguishing between anti-fungal chickpea proteins as seen in their protein patterns/domains.

Genome-wide identification and comprehensive study of anti-fungal genes in chickpea