Long-read reconstruction of many diverse haplotypes with devider

Abstract

Reconstructing exact haplotypes is important when sequencing a mixture of similar sequences. Long-read sequencing can connect distant alleles to disentangle similar haplotypes, but handling sequencing errors requires specialized techniques. We present devider, an algorithm for haplotyping small sequences - such as viruses or genes - from long-read sequencing. devider uses a positional de Bruijn graph with sequence-to-graph alignment on an alphabet of informative alleles to provide a fast assembly-inspired approach compatible with various long-read sequencing technologies. On a synthetic Nanopore dataset containing seven HIV strains, devider recovered 97% of the haplotype content and had the most accurate abundance estimates while taking < 4 minutes and 1 GB of memory for > 8000× coverage. Benchmarking on synthetic mixtures of antimicrobial resistance (AMR) genes showed that devider recovered 83% of haplotypes, 23 percentage points higher than the next best method. On real PacBio and Nanopore datasets, devider recapitulates previously known results in seconds, disentangling a bacterial community with > 10 strains and an HIV-1 co-infection dataset. We used devider to investigate the within-host diversity of a long-read bovine gut metagenome enriched for AMR genes, discovering 13 distinct haplotypes for a tet(Q) tetracycline resistance gene with > 18,000× coverage and 6 haplotypes for a CfxA2 beta-lactamase gene. We found clear recombination blocks for these AMR gene haplotypes, showcasing devider's ability to unveil evolutionary signals for heterogeneous mixtures.