The Illumina DNA sequencing platform generates accurate but short reads, which can be used to produce accurate but fragmented genome assemblies. Pacific Biosciences and Oxford Nanopore Technologies DNA sequencing platforms generate long reads that can produce complete genome assemblies, but the sequencing is more expensive and error-prone. There is significant interest in combining data from these complementary sequencing technologies to generate more accurate “hybrid” assemblies. However, few tools exist that truly leverage the benefits of both types of data, namely the accuracy of short reads and the structural resolving power of long reads. Here we present Unicycler, a new tool for assembling bacterial genomes from a combination of short and long reads, which produces assemblies that are accurate, complete and cost-effective. Unicycler builds an initial assembly graph from short reads using the de novo assembler SPAdes and then simplifies the graph using information from short and long reads. Unicycler uses a novel semi-global aligner to align long reads to the assembly graph. Tests on both synthetic and real reads show Unicycler can assemble larger contigs with fewer misassemblies than other hybrid assemblers, even when long-read depth and accuracy are low. Unicycler is open source (GPLv3) and available at github.com/rrwick/Unicycler.

Klebsiella pneumoniae is now recognized as an urgent threat to human health because of the emergence of multidrug-resistant strains associated with hospital outbreaks and hypervirulent strains associated with severe community-acquired infections. K. pneumoniae is ubiquitous in the environment and can colonize and infect both plants and animals. However, little is known about the population structure of K. pneumoniae, so it is difficult to recognize or understand the emergence of clinically important clones within this highly genetically diverse species. Here we present a detailed genomic framework for K. pneumoniae based on whole-genome sequencing of more than 300 human and animal isolates spanning four continents. Our data provide genome-wide support for the splitting of K. pneumoniae into three distinct species, KpI (K. pneumoniae), KpII (K. quasipneumoniae), and KpIII (K. variicola). Further, for K. pneumoniae (KpI), the entity most frequently associated with human infection, we show the existence of >150 deeply branching lineages including numerous multidrug-resistant or hypervirulent clones. We show K. pneumoniae has a large accessory genome approaching 30,000 protein-coding genes, including a number of virulence functions that are significantly associated with invasive community-acquired disease in humans. In our dataset, antimicrobial resistance genes were common among human carriage isolates and hospital-acquired infections, which generally lacked the genes associated with invasive disease. The convergence of virulence and resistance genes potentially could lead to the emergence of untreatable invasive K. pneumoniae infections; our data provide the whole-genome framework against which to track the emergence of such threats.

Summary: Although de novo assembly graphs contain assembled contigs (nodes), the connections between those contigs (edges) are difficult for users to access. Bandage (a Bioinformatics Application for Navigating De novo Assembly Graphs Easily) is a tool for visualizing assembly graphs with connections. Users can zoom in to specific areas of the graph and interact with it by moving nodes, adding labels, changing colors and extracting sequences. BLAST searches can be performed within the Bandage graphical user interface and the hits are displayed as highlights in the graph. By displaying connections between contigs, Bandage presents new possibilities for analyzing de novo assemblies that are not possible through investigation of contigs alone.Availability and implementation: Source code and binaries are freely available at https://github.com/rrwick/Bandage. Bandage is implemented in C++ and supported on Linux, OS X and Windows. A full feature list and screenshots are available at http://rrwick.github.io/Bandage.Contact: rrwick@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online.

Tuberculosis caused 20% of all human deaths in the Western world between the 17th and 19th centuries, and remains a cause of high mortality in developing countries. In analogy to other crowd diseases, the origin of human tuberculosis has been associated with the Neolithic Demographic Transition, but recent studies point to a much earlier origin. Here we used 259 whole-genome sequences to reconstruct the evolutionary history of the Mycobacterium tuberculosis complex (MTBC). Coalescent analyses indicate that MTBC emerged about 70 thousand years ago, accompanied migrations of anatomically modern humans out of Africa, and expanded as a consequence of increases in human population density during the Neolithic. This long co-evolutionary history is consistent with MTBC displaying characteristics indicative of adaptation to both low- and high host densities.