Evidence map›Paper›PMID 41233543›Full record

ArticleNature methods2025

Bin Chicken: targeted metagenomic coassembly for the efficient recovery of novel genomes.

Samuel T N Aroney, Rhys J P Newell, Gene W Tyson, Ben J Woodcroft

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Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Samuel T N AroneyCentre for Microbiome Research, School of Biomedical Sciences, Translational Research Institute, Queensland University of Technology, Woolloongabba, Queensland, Australia.ORCID http://orcid.org/0000-0001-9806-5846
Rhys J P NewellCentre for Microbiome Research, School of Biomedical Sciences, Translational Research Institute, Queensland University of Technology, Woolloongabba, Queensland, Australia.
Gene W TysonCentre for Microbiome Research, School of Biomedical Sciences, Translational Research Institute, Queensland University of Technology, Woolloongabba, Queensland, Australia.ORCID http://orcid.org/0000-0001-8559-9427
Ben J WoodcroftCentre for Microbiome Research, School of Biomedical Sciences, Translational Research Institute, Queensland University of Technology, Woolloongabba, Queensland, Australia. b.woodcroft@qut.edu.au.ORCID http://orcid.org/0000-0003-0670-7480

Funding

Department of Education and Training | Australian Research Council (ARC) DP230101171Department of Education and Training | Australian Research Council (ARC) FT210100521National Science Foundation (NSF) 2022070U.S. Department of Energy (DOE) DE-SC0004632U.S. Department of Energy (DOE) DE-SC0010580U.S. Department of Energy (DOE) DE-SC0016440
6 · The paper itself

Abstract

The recovery of microbial genomes from metagenomic datasets has provided genomic representation for hundreds of thousands of species from diverse biomes. However, low-abundance microorganisms are often missed due to insufficient genomic coverage. Here we present Bin Chicken, an algorithm that substantially improves genome recovery through automated, targeted selection of metagenomes for coassembly based on shared marker gene sequences derived from raw reads. Marker gene sequences that are divergent from known reference genomes can be further prioritized, providing an efficient means of recovering highly novel genomes. Applying Bin Chicken to public metagenomes and coassembling 800 sample groups recovered 77,562 microbial genomes, including the first genomic representatives of 6 phyla, 41 classes and 24,028 species. These genomes expand the genomic tree of life and uncover a wealth of novel microbial lineages for further research.

Indexed as

MetagenomeMetagenomicsAlgorithmsAnimalsChickensSequence Analysis, DNA

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.