Automatic generation of model sequences for complex regions in assembly graphs with TTT

Recent developments have enabled the automated assembly of vertebrate chromosomes from telomere to telomere. However, for long, highly similar repeats, genome assemblers may leave tangles in the assembly graph and gaps in the assembly. In recently published genomes, such gaps are closed by manual graph curation, a process that is labor intensive, error prone, and sometimes infeasible. Consequently, important genomic regions may be misassembled or omitted. Here, we present the trivial tangle traverser (TTT) algorithm that finds optimized resolutions of assembly graph tangles. TTT uses depth of coverage and read-to-graph alignment information in a two-stage process to estimate sequence multiplicities and identify traversals that are consistent with the underlying data. We evaluate TTT traversals on the HG002 human reference genome, compare TTT with a state-of-the-art assembler on the giraffe T2T assembly, and demonstrate its use to characterize a previously unassembled amplified p21-activated serine/threonine kinase 3-like (PAK3L) gene array in the zebra finch genome.