P0968A Novel Two-Enzyme Approach to Build High-Quality, de novo Genome Assemblies by Scaffolding Next-Generation Sequencing Data with BioNano’s Next-Generation Optical Maps
We describe a novel workflow that utilizes two nicking endonucleases to increase the information density and improve contiguity through tiling of genome maps. We generated two sets of genome maps, each with a different nicking endonuclease and developed novel algorithms that use the NGS sequences as a bridge to merge single-enzyme genome maps into combined maps that contain the sequence motif patterns from both nicking enzymes. Since the genome maps were generated independently they serve as orthogonal sources of evidences to detect and correct assembly errors in input data. The complementarity of different data also greatly improves the contiguity of the merged genome map while doubling the information density, which substantially increase the ability to anchor short NGS sequences in the final scaffold.
We first validated our approach in the well-studied human NA12878 genome. Compared to the published single-enzyme hybrid-scaffolds, the two-enzyme approach improved the scaffold contiguity by 300% and anchored 30% more sequence contigs in the final scaffolds and corrected 50% more assembly errors in NGS sequences. We then benchmarked our pipeline in a variety of animal and plant genomes and showed that it performed robustly across those.
This new approach can greatly expands the type of NGS data that can be integrated with BioNano genome maps to produce highly accurate and contiguous assemblies for complex genomes.