Abstract DNA sequencing data continues to progress towards longer reads with increasingly lower sequencing error rates. We focus on the critical problem of mapping, or aligning, low-divergence sequences from long reads (PacBio HiFi) to a reference genome, which poses challenges in terms of accuracy and computational resources when using cutting-edge read mapping approaches that are designed for all types of alignments. A natural idea would be to optimize efficiency with longer seeds to reduce the probability of extraneous matches; however, contiguous exact seeds quickly reach a sensitivity limit. We introduce mapquik , a novel strategy that creates accurate longer seeds by anchoring alignments through matches of k consecutively-sampled minimizers ( k -min-mers) and only indexing k -min-mers that occur once in the reference genome, thereby unlocking ultra-fast mapping while retaining high sensitivity. We demonstrate that mapquik significantly accelerates the seeding and chaining steps — fundamental bottlenecks to read mapping — for both the human and maize genomes with &gt; 96% sensitivity and near-perfect specificity. On the human genome, mapquik achieves a 30× speed-up over the state-of-the-art tool minimap2 , and on the maize genome, a 350× speed-up over minimap2 , making mapquik the fastest mapper to date. These accelerations are enabled not only by minimizer-space seeding but also a novel heuristic 𝒪( n ) pseudo-chaining algorithm, which improves over the long-standing 𝒪( n log n ) bound. Minimizer-space computation builds the foundation for achieving real-time analysis of long-read sequencing data.

mapquik: Efficient low-divergence mapping of long reads in minimizer space