Comparative Genomic Analysis of Coronaviruses Across 2003–2025: Insights into CpG Dynamics and Mutation Profiles Relative to Wuhan-Hu-1 (NC_045512)

This project analyzes the genomic features of coronaviruses, focusing on CpG dynamics and mutation profiles relative to the reference genome Wuhan-Hu-1 (NC_045512). Key findings include:CpG Analysis : Sliding window analysis was performed to calculate CpG counts and observed/expected (O/E) ratios across the genomes of multiple coronaviruses.Mutation Profiles : Sequences were aligned using MAFFT, and mutations relative to Wuhan-Hu-1 were identified.Visualization : Bar charts and line plots were generated to summarize CpG counts, O/E ratios, and mutation distributions.Dataset Includes:Combined FASTA file (`combined_sequences.fasta`) containing sequences from 11 coronaviruses.Aligned sequences (`aligned_sequences.fasta`) generated using MAFFT.Mutation analysis results (`mutations_analysis.txt`) showing mutations relative to Wuhan-Hu-1.- Visualizations:Bar chart showing the number of mutations per genome.Scripts used for converting GenBank files to FASTA, aligning sequences, identifying mutations, and generating visualizations.Input GenBank files.Methods:1. Converted GenBank files to FASTA format using Biopython.2. Aligned sequences using MAFFT.3. Identified mutations relative to Wuhan-Hu-1 using a custom Python script.4. Generated visualizations using Matplotlib.Implications:This work contributes to understanding the genomic architecture and evolutionary relationships of coronaviruses. The findings align with broader trends observed in coronavirus genomics, highlighting shared mechanisms of CpG depletion and mutation patterns.Published on Figshare: