RECYCLER: AN ALGORITHM FOR DETECTING PLASMIDS FROM DE NOVO ASSEMBLY GRAPHS

Motivation: Plasmids and other mobile elements are central contributors to microbial evolution and genome innovation. Recently, they have been found to have important roles in antibiotic resist- ance and in affecting production of metabolites used in industrial and agricultural applications. However, their characterization through deep sequencing remains challenging, in spite of rapid drops in cost and throughput increases for sequencing. Here, we attempt to ameliorate this situ- ation by introducing a new circular element assembly algorithm, leveraging assembly graphs pro- vided by a conventional de novo assembler and alignments of paired-end reads to assemble cyclic sequences likely to be plasmids, phages and other circular elements.

Results: We introduce Recycler, the first tool that can extract complete circular contigs from se- quence data of isolate microbial genomes, plasmidome and metagenome sequence data. We show that Recycler greatly increases the number of true plasmids recovered relative to other approaches while remaining highly accurate. We demonstrate this trend via simulations of plasmi- domes, comparisons of predictions with reference data for isolate samples, and assessments of an- notation accuracy on metagenome data. In addition, we provide validation by DNA amplification of 77 plasmids predicted by Recycler from the different sequenced samples in which Recycler showed mean accuracy of 89% across all data types—isolate, microbiome and plasmidome.