Genome-Wide Mutational Profiling and Variant Effect Prediction in Resistant Bacterial Genomes

A comprehensive computational genomics project aimed at identifying and annotating genomic variations (SNPs and Indels) across drug-resistant bacterial isolates compared to reference strains. Raw whole-genome sequencing (WGS) data underwent quality filtering, sequence alignment using BWA-MEM, and post-alignment processing via SAMtools and Picard.

Variant calling was executed using GATK/FreeBayes pipelines to ensure high confidence in SNP identification. Variants were further annotated with SnpEff to categorize functional impacts (synonymous vs. non-synonymous mutations, frameshifts, and stop-gain mutations). The output provides a structured mutational map essential for understanding evolutionary adaptations and genetic drivers of resistance.