Abstract

Background: Plasmids play a critical role in horizontal gene transfer and the spread of antibiotic resistance. However, recovering complete plasmid sequences from metagenomic samples remains highly challenging due to extensive repeat content, structural heterogeneity, and large variation in plasmid size. Existing methods typically identify plasmids from metagenome assemblies by exploiting coverage differences or detecting minimum-weight cycles in assembly graphs. While effective for dominant plasmids, these approaches often fail to recover low-abundance and long plasmids. Results: Here we present PlasChain, a novel algorithm designed to improve plasmid assembly and identification from complex metagenomic data. Building upon the cycle-peeling strategy of SCAPP, PlasChain incorporates contig path information and a cycle-merging procedure to prevent long plasmids from being fragmented into multiple shorter cycles. In addition, PlasChain jointly leverages paired-end read alignments, sequence composition patterns, and coverage variation to filter out assembly artifacts and reduce false positives. We evaluated PlasChain against state-of-the-art plasmid assemblers, including SCAPP and metaplasmidSPAdes, using a diverse set of simulated and real metagenomic datasets. Across nearly all benchmarks, PlasChain demonstrates superior performance in recovering long plasmids while maintaining competitive accuracy in assembling short plasmids. Furthermore, analysis of real metagenomic samples shows that PlasChain is capable of assembling previously uncharacterized plasmids, including putative megaplasmids that are typically underrepresented in current plasmid databases. Conclusions: PlasChain is a novel graph-based plasmid assembler that improves the recovery of long plasmids from short-read metagenomic data. Evaluation on diverse simulated and real metagenomic datasets demonstrates that PlasChain consistently outperforms existing plasmid assemblers, especially for long plasmid reconstruction. These results highlight the potential of PlasChain to facilitate comprehensive characterization of plasmid diversity, antimicrobial resistance, and horizontal gene transfer in complex microbial communities. The source code and testing data for PlasChain are freely available at https://github.com/SDU-ACG-Lab/PlasChain.