DBG2OLC: Efficient Assembly of Large Genomes Using Long Erroneous Reads of the Third Generation Sequencing Technologies

TL;DR

This paper introduces a hybrid genome assembly method combining NGS and 3GS data, enabling efficient assembly of large genomes despite high error rates and reducing sequencing costs.

Contribution

It presents a novel hybrid assembly approach that leverages NGS and 3GS data, using a compact representation and a conversion from de Bruijn to overlap graphs.

Findings

Assembles mammalian-sized genomes efficiently and faster than existing methods.

Reduces sequencing costs by approximately 50%.

Successfully handles high-error long reads from third-generation sequencing.

Abstract

(An updated version of this manuscript has been accepted to Scientific Reports in 2016, please refer to http://www.nature.com/articles/srep31900) The highly anticipated transition from next generation sequencing (NGS) to third generation sequencing (3GS) has been difficult primarily due to high error rates and excessive sequencing cost. The high error rates make the assembly of long erroneous reads of large genomes challenging because existing software solutions are often overwhelmed by error correction tasks. Here we report a hybrid assembly approach that simultaneously utilizes NGS and 3GS data to address both issues. We gain advantages from three general and basic design principles: (i) Compact representation of the long reads lead to efficient alignments. (ii) Base-level errors can be skipped; structural errors need to be detected and corrected. (iii) Structurally correct 3GS reads are assembled and polished. In our implementation, preassembled NGS contigs are used to derive the compact representation of the long reads, which established an algorithmic conversion from a de Bruijn graph to an overlap graph, the two major assembly paradigms. Moreover, since NGS and 3GS data can compensate each other, our hybrid assembly approach reduces both of their sequencing requirements. Experiments show that our software is able to assemble mammalian-sized genomes orders of magnitude more efficiently in time than existing methods, while saving about half of the sequencing cost.