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METAHICT enables comprehensive genome-resolved microbiome analysis with metagenomic Hi-C

Shiyuan WangiD, Zhen Qin, Hang YuiD, Ruishan LiuiD, Yong GeiD, Maitreya Dutta, Luan D. VuiD, Yuxuan DuiD

Abstract

Metagenomic Hi-C (metaHi-C) adds within-cell proximity information to shotgun sequencing, but existing analyses are fragmented and short-insert intra-contig read pairs from Hi-C libraries are often underused. Here, we present METAHICT, a modular and configurable workflow spanning read processing, metagenome-assembled genome (MAG) reconstruction, and downstream analysis. METAHICT consolidates outputs from bin3C, MetaCC, and ImputeCC and uses an expectation-maximization model of mapped insert sizes to select short-insert, shotgun-like Hi-C pairs for per-bin reassembly. Across seven datasets, binning and consolidation generally recovered more near-complete and medium-quality MAGs than individual Hi-C binners. On the sheep-gut long-read assembly, METAHICT's binning and consolidation stage recovered 929 MAGs meeting at least the medium-quality threshold, including 487 near-complete MAGs. Within the reassembly module, adding EM-selected Hi-C reads to shotgun-only inputs yielded further significant reductions in contamination across multiple environments. The workflow also integrates scaffolding, taxonomic annotation, contact-map visualization, and analysis of candidate mobile genetic element (MGE)-host pairs. Together, these capabilities provide standardized outputs for comparative and hypothesis-driven genome-resolved microbiome analysis.

PDFDOI

02 /Specification & Classification

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