Journal
GENOME BIOLOGY
Volume 22, Issue 1, Pages -Publisher
BMC
DOI: 10.1186/s13059-021-02419-7
Keywords
Microbiome; Metagenome; Strains; Bayesian; Microbial community; Assembly graph
Funding
- MRC Methodology Grant `Strain resolved metagenomics for medical microbiology' [MR/S037195/1]
- MRC fellowship as part of the CLoud Infrastructure for Microbial Genomics (CLIMB) consortium [MR/M50161X/1, MR/L015080/1]
- BBSRC [BB/N023285/1, BB/L502029/1, BB/R015171/1]
- Intramural Research Program of the National Human Genome Research Institute, National Institutes of Health
- BBSRC [BB/K003240/1, BB/R015171/1, BB/K003240/2, BB/N023285/1] Funding Source: UKRI
- MRC [MR/L015080/1] Funding Source: UKRI
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STRONG is a novel method that identifies strains de novo from multiple metagenome samples by using assembly graphs to extract coverages of SCGs in each MAG and determine the number of strains, their haplotypes or sequences, and abundances. The method is validated using synthetic communities and real samples.
We introduce STrain Resolution ON assembly Graphs (STRONG), which identifies strains de novo, from multiple metagenome samples. STRONG performs coassembly, and binning into metagenome assembled genomes (MAGs), and stores the coassembly graph prior to variant simplification. This enables the subgraphs and their unitig per-sample coverages, for individual single-copy core genes (SCGs) in each MAG, to be extracted. A Bayesian algorithm, BayesPaths, determines the number of strains present, their haplotypes or sequences on the SCGs, and abundances. STRONG is validated using synthetic communities and for a real anaerobic digestor time series generates haplotypes that match those observed from long Nanopore reads.
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