A Novel Genome Optimization Tool for Chromosome-Level Assembly across Diverse Sequencing Techniques

This paper introduces a novel genome assembly optimization tool named LOCLA, which stands for “Local Optimization for Chromosome-Level Assembly”. It identifies reads and contigs aligned locally with high quality on gap flanks or scaffold boundaries of draft assemblies for gap filling and scaffold connection. LOCLA applies to both de novo and reference-based assemblies. It can also utilize reads produced by diverse sequencing techniques, e.g., 10x Genomics (10xG) Linked-Reads, and PacBio HiFi reads. We validated LOCLA on three human samples and one non-model organism. For the first two human samples, LLD0021C and CHM13, we generated de novo draft assemblies from 10xG Linked-Reads. On LLD0021C, LOCLA improves the draft assembly by adding 23.3 million bases using only 10xG Linked-Reads. These additional bases cover 28,746 protein-coding regions, particularly in pericentromeric and telomeric regions. On the CHM13 sample, we took 10xG Linked-Reads and PacBio HiFi reads as input. As a result, LOCLA added 46.2 million bases to the draft assembly. The increased content enables us to identify genes linked to complex diseases (e.g., ARHGAP11A) and critical biological pathways. We created two reference-guided draft assemblies on the third human sample, HG002, using contigs assembled from PacBio HiFi reads. LOCLA enhances the two draft assemblies by recovering 27.9 million bases (22.26%) and 35.7 million bases (30.93%) of the sequences discarded by the reference-guided assembly tool. The results indicate the robustness of LOCLA’s contig detection algorithm on gap flanks. Furthermore, we show that 95% of the sequences filled in by LOCLA have over 80% accuracy compared with the HG002 reference genome published by the Human Pan-genome Reference Consortium. On the non-model organism, LOCLA enhanced the genome assembly of Bruguiera sexangula (JAHLGP000000000) by decreasing 41.4% of its gaps and raising the Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis score to 98.10%. LOCLA can optimize de novo and reference-guided assemblies using varied sequencing reads. The final assemblies produced by LOCLA have improved in both quantity and quality. The increased gene content may provide a valuable resource in advancing personalized medicine. ### Competing Interest Statement The authors have declared no competing interest.