de novo Assembly of Complex Genomes Using Single Molecule Sequencing

Third generation single molecule sequencing technology from Pacific Biosciences, Moleculo, Oxford Nanopore, and other companies are revolutionizing genomics by enabling the sequencing of long, individual molecules of DNA and RNA. One major advantage of these technologies over current short read sequencing is the ability to sequence much longer molecules, thousands or tens of thousands of nucleotides instead of mere hundreds. This capacity gives researchers substantially greater power to probe into microbial, plant, and animal genomes, but it remains unknown on how to best use these data.

To answer this, we systematically evaluated the human genome and 25 other important genomes across the tree of life ranging in size from 1Mbp to 3Gbp in an attempt to answer how long the reads need to be and how much coverage is necessary to completely assemble their chromosomes with single molecule sequencing. We determine assembly quality is primarily a function of repeat composition, read length, and coverage, and develop a new data driven model using support vector regression that accurately predicts assembly performance in these and novel genomes. From this, we conclude most genomes up to 100Mbp should assemble into virtually complete chromosome arms using reads averaging at least 8kbp, as is currently available with PacBio sequencing. For larger genomes, the currently available read lengths dramatically improve the assembly, but will still need further improvement to achieve end-to-end chromosomes.

We also present a novel error correction and assembly algorithm using a combination of PacBio and pre-assembled Illumina sequencing. This new algorithm greatly outperforms other published algorithms, and using it, we have been able to achieve multi-megabase contig N50 sizes in eukaryotic genomes, as predicted by our assembly complexity model. The source code for the error correction pipeline is available open source, and the model of assembly performance is available as an interactive webapp that researchers can use to explore the tradeoffs in read length and coverage for genomes of any size.