SNPPar

SNPPar detects homoplasic single nucleotide polymorphisms (SNPs) in large bacterial whole-genome sequence datasets to identify and characterize parallel, convergent, and revertant mutations associated with adaptive evolution such as antibiotic resistance and virulence.

Key Features:

• Detection of homoplasies: Identifies parallel, convergent, and revertant SNPs (e.g., parallel: A -> T; convergent: A -> T and C -> T; revertant: A -> T -> A).
• Input requirements: Operates from a SNP alignment, a phylogenetic tree, and an annotated reference genome.
• Ancestral state reconstruction with monophyly tests: Combines monophyly tests with ancestral state reconstruction (ASR) to assign mutation events on the phylogeny.
• Codon- and gene-level annotation: Annotates mutations at codon and gene levels to support analysis of convergent evolution and functional impacts.
• Performance and scalability: Reports zero false-positives across tests, an 89% rate of zero false-negatives, and example performance of ~64,000 SNPs from 2,000 Mycobacterium tuberculosis genomes in ~23 minutes using ~2.6 GB RAM.

Scientific Applications:

• Homoplasy analysis: Quantifies and classifies homoplasic SNPs to study parallel and convergent evolution at nucleotide, codon, and gene levels.
• Antibiotic resistance evolution: Identifies recurrent mutations associated with the emergence and spread of antibiotic resistance in bacterial pathogens.
• Virulence and clinically relevant trait studies: Detects adaptive mutations linked to virulence and other clinically relevant phenotypes.
• Pathogen surveillance: Supports long-term surveillance of bacterial populations by highlighting recurrent adaptive changes.

Methodology:

Uses monophyly tests combined with ancestral state reconstruction (ASR) via TreeTime to assign mutation events and annotates mutations at codon and gene levels.