HiFine

HiFine integrates Hi-C and shotgun-based metagenomic binning to refine and merge contig bins and improve reconstruction of microbial genomes from single-sample metagenomes.

Key Features:

• Integration of Hi-C and shotgun data: Combines Hi-C proximity-contact information with composition and abundance (co-abundance) profiles from shotgun sequencing to inform binning decisions.
• Strategic fragmentation of bins: Performs fragmentation of original bin sets derived from each method to enable targeted refinement and reduce contaminant signals.
• Refinement of initial bins: Refines initial binning results to improve purity of draft genomic bins by resolving conflicting signals between methods.
• Merging of fragmented bins: Merges fragmented bins after refinement to produce more complete genomic bins.
• Recruitment of unbinned contigs: Recruits remaining unbinned contigs into merged bins to increase genome completeness.
• Handling of Hi-C ligation artifacts: Accounts for spurious inter-species contacts arising from incorrect Hi-C ligations that can compromise bin purity.
• Single-sample applicability: Operates on metagenomic contigs assembled from short reads and is applicable where co-abundance profiling across multiple samples is limited.
• Demonstrated improvement: Reported to enhance species-level genome reconstruction compared with Hi-C-only or shotgun-only binning on public datasets.

Scientific Applications:

• Metagenome-assembled genome reconstruction: Improves recovery of MAGs from complex environmental metagenomes by refining and merging contig bins.
• Resolving closely related species: Enhances discrimination of closely related taxa that are ambiguous for composition- or co-abundance-based binning.
• Contamination reduction in draft bins: Reduces inter-species contamination introduced by misbinning or spurious Hi-C contacts.
• Single-sample metagenomic analysis: Enables effective binning and genome recovery from single-sample datasets with limited co-abundance signal.

Methodology:

Integrates Hi-C-based and shotgun-based binning outputs, applies strategic fragmentation to original bins, refines bin assignments, merges fragmented bins, and recruits remaining unbinned contigs.