Synthetic Modeling of Emerging SARS-CoV-2 Recombinant Lineages via Markov Chain Mutation Forecasting

This dataset contains <b>18 synthetic full-length SARS-CoV-2 genomes</b> engineered using <b>Markov chain modeling</b> of Spike gene mutations derived from Nextclade TSV data. Each sequence represents a potential new PANGO lineage candidate based on unique mutation combinations not seen in current classifications.The Spike gene sequences were generated from mutation clusters and co-evolution patterns observed in recombinant <b>XFG-like variants</b>. These were back-translated and integrated into a Wuhan-Hu-1 reference backbone to create full-genome FASTA files.Also included are supporting metadata files:Mutation summary per genomeList of novel AA substitutionsThis work demonstrates how statistical modeling of mutation transitions can be used to simulate future lineages, enabling proactive genomic surveillance strategies.