Chromosome-level de novo genome assemblies are vital for many aspects of biological research. Despite technological progress, achieving telomere-to-telomere assemblies remains challenging. Long-read data are critical for a contiguous genome assembly, since repeat regions cannot be assembled without them. Researchers typically generate substantial quantities of data from multiple sequencing platforms to achieve accurate and contiguous telomere-to-telomere (T2T) assemblies. This makes the process costly and complicated. Recent advances in algorithms designed to optimise assembly with long-read data have the potential to rectify this issue. Using only Oxford Nanopore Technology (ONT) simplex long-read data from the Sumatran tiger (Panthera tigris sumatrae), we evaluate leading methods for error correction of long-reads (NextDenovo, HERRO and hifiasm ONT) and various assembly approaches. We show that correcting errors in ONT long-reads during assembly greatly improves the quality and contiguity of the resulting assembly, suggesting these methods will make high quality genome assemblies more achievable with less data. We also present the first, almost complete, T2T, de novo genome assembly for the Sumatran tiger, with a single technology. This assembly is a novel resource for genomic research and conservation efforts.
Dean et al. (Sat,) studied this question.