HaloClassifier: integrating coding-signature features and k-mer composition for plasmid-chromosome discrimination in haloarchaeal genomes
Lopez-Roig, L.; Gonzalez-Candelas, F.; Fillol-Salom, A.
Show abstract
Background: Plasmids are key drivers of horizontal gene transfer (HGT), enabling the dissemination of accessory traits that shape microbial adaptation and ecological interactions. In Haloarchaea-dominant members of hypersaline environments-characterizing plasmidomes remains particularly challenging because most available genomes are incomplete, leaving many contigs unassigned to either chromosomal or plasmidic origin. This limitation hampers our ability to reconstruct archaeal plasmid diversity and to evaluate how plasmid-borne genes circulate within Haloarchaea and, potentially, outside this class. Results: Here, we present HaloClassifier, the first machine-learning tool specifically designed to distinguish plasmid- and chromosome-derived contigs in haloarchaeal genomes. Unlike existing bacterial-focused approaches, HaloClassifier uniquely integrates haloarchaeal-specific genomic signatures with coding-derived features-an underused but highly informative class of predictors-and incorporates a variable-selection strategy that substantially reduces model complexity and computational cost while maintaining high predictive accuracy. When trained on simulated contigs generated from complete haloarchaeal genomes, the model achieves 96.61% accuracy on extralarge contigs (40-100 kb), increasing to 98.1% at a 0.6 classification threshold, with only 3.55% of contigs left unclassified. For small contigs (1-5 kb), the model achieves 79.51% accuracy overall and 84.42% at the 0.6 classification threshold, with 17.07% of contigs left unclassified. The model also maintains robust performance in metagenomic datasets. Conclusions: By enabling reliable plasmid identification in fragmented assemblies, HaloClassifier fills a major gap and establishes the foundation for large-scale haloarchaeal plasmidome reconstruction. This framework will support future investigations into gene mobility, ecological adaptation, and the evolutionary dynamics of plasmids and HGT in Haloarchaea.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Platon: identification and characterization of bacterial plasmid contigs in short-read draft assembliesexploiting protein-sequence-based replicon distribution scores 94%
- From defaults to databases: parameter and database choice dramatically impact the performance of metagenomic taxonomic classification tools 94%
- Whokaryote: distinguishing eukaryotic and prokaryotic contigs in metagenomes based on gene structure 93%
Similar papers in this journal
Similar papers in this journal
- LEMMIv2: Benchmarking Framework for Metagenomic and 16S Amplicon Profilers with a Catalogue of Evaluated Tools. 93%
- Assignment of virus and antimicrobial resistance genes to microbial hosts in a complex microbial community by combined long-read assembly and proximity ligation 93%
- HOPS: Automated detection and authentication of pathogen DNA in archaeological remains 92%
Similar papers in this journal
- To assemble or not to resemble -- A validated Comparative Metatranscriptomics Workflow (CoMW) 94%
- HVRLocator: A Computationally Efficient Tool for Identifying Hypervariable Regions in 16S rRNA Big Datasets 94%
- MADRe: Strain-Level Metagenomic Classification Through Assembly-Driven Database Reduction 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.