The Role of Comparative Genomic Bioinformatics in Predicting and Managing Wheat Rust Disease in Wheat Crops: A Multi-Omics Approach for Pathogen Genomics and Host Resistance Identification

Abstract

The yield results of wheat (Triticum aestivum L.) suffer critical losses annually from rust diseases including yellow rust, leaf rust and stem rust. The study explores how comparative genomic bioinformatics supports wheat rust disease prevention and control by examining multiple-omic data approaches. The research demonstrates the way genomics, transcriptomics, proteomics and metabolomics assist in discovering genetic markers by presenting host-pathogen relations and producing resistant wheat varieties. This study has discussed diverse technologies such as genome-wide association studies, quantitative trait loci mapping and CRISPR/Cas9 gene editing tools that present critical results which can easily improve disease resistance. The research examines the difficulties faced through the analysis of big omics datasets while handling complex technological factors. The study explained the way multi-omics data applications work for wheat rust prediction, crop management and improvement efforts to present sustainable food production and agricultural bioinformatics progress.