HGA: de novo genome assembly method for bacterial genomes using high coverage short sequencing reads

Background: Current high-throughput sequencing technologies generate large numbers of relatively short and error-prone reads, making the de novo assembly problem challenging. Although high quality assemblies can be obtained by assembling multiple paired-end libraries with both short and long insert sizes, the latter are costly to generate. Recently, GAGE-B study showed that a remarkably good assembly quality can be obtained for bacterial genomes by state-of-the-art assemblers run on a single short-insert library with very high coverage. Results: In this paper, we introduce a novel hierarchical genome assembly (HGA) methodology that takes further advantage of such very high coverage by independently assembling disjoint subsets of reads, combining assemblies of the subsets, and finally re-assembling the combined contigs along with the original reads. Conclusions: We empirically evaluated this methodology for 8 leading assemblers using 7 GAGE-B bacterial datasets consisting of 100 bp Illumina HiSeq and 250 bp Illumina MiSeq reads, with coverage ranging from 100x-similar to 200x. The results show that for all evaluated datasets and using most evaluated assemblers (that were used to assemble the disjoint subsets), HGA leads to a significant improvement in the quality of the assembly based on N50 and corrected N50 metrics.