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Ayala, N.

Publications and source records attributed to Ayala, N..

2 recordsLinked to original sources

Panmap: Scalable phylogeny-guided alignment, genotyping, and placement on pangenomes

Pangenomes capture population-level variation but remain computationally challenging at scale. We present Panmap, a tool that leverages evolutionary structure to place, align, and genotype sequencing reads against mutation-annotated pangenomes containing up to millions of genomes. Panmap introduces a phylogenetically compressed k-mer index that stores only sequence differences along branches, enabling efficient comparison of reads to both sampled genomes and inferred ancestors. This approach reduces index size by up to 600-fold and construction time by over three orders of magnitude relative to existing tools. Panmap places a 100x coverage SARS-CoV-2 sample onto 20,000 genomes in 0.4 seconds and onto 8 million genomes in under two minutes. Furthermore, it enables accurate haplotype identification and abundance estimation in metagenomic samples and sensitive placement of ancient environmental DNA without prior alignment. Our approach makes large-scale pangenomes directly amenable to read mapping, genome assembly, alignment-free phylogenetic placement, and metagenomic analysis.

bioinformatics↗

Pandemic-Scale Phylogenomics Reveals Elevated Recombination Rates in the SARS-CoV-2 Spike Region

Accurate and timely detection of recombinant lineages is crucial for interpreting genetic variation, reconstructing epidemic spread, identifying selection and variants of interest, and accurately performing phylogenetic analyses. During the SARS-CoV-2 pandemic, genomic data generation has exceeded the capacities of existing analysis platforms, thereby crippling real-time analysis of viral recombination. Low SARS-CoV-2 mutation rates make detecting recombination difficult. Here, we develop and apply a novel phylogenomic method to exhaustively search a nearly comprehensive SARS-CoV-2 phylogeny for recombinant lineages. We investigate a 1.6M sample tree, and identify 606 recombination events. Approximately 2.7% of sequenced SARS-CoV-2 genomes have recombinant ancestry. Recombination breakpoints occur disproportionately in the Spike protein region. Our method empowers comprehensive real time tracking of viral recombination during the SARS-CoV-2 pandemic and beyond.

evolutionary biology↗