Evidence map›Paper›PMID 42003340›Full record

ArticleMolecular ecology resources2026

ChloroScan: Recovering Plastid Genome Bins From Metagenomic Data.

Yuhao Tong, Vanessa Rossetto Marcelino, Robert Turnbull, Heroen Verbruggen

Abstract read
In one paragraph

Article in Molecular ecology resources, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 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.

Yuhao TongSchool of Computing and Information Systems, The University of Melbourne, Carlton, Victoria, Australia.ORCID https://orcid.org/0009-0001-2809-2248
Vanessa Rossetto MarcelinoInstitute of Agrochemistry and Food Technology, Spanish National Research Council (CSIC), Valencia, Spain.
Robert TurnbullMelbourne Data Analytics Platform (MDAP), The University of Melbourne, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0003-1274-6750
Heroen VerbruggenCIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal.

Funding

Australian Research Council DE220100965Fundação para a Ciência e a Tecnologia 2023.06155Ministerio de Ciencia e Innovación RYC2023-042907-IThe University of Melbourne's Research Computing Services
6 · The paper itself

Abstract

Genome-resolved metagenomics has contributed greatly to discovering prokaryotic genomes. When applied to microscopic eukaryotes (protists), challenges such as the high number of introns and repeat regions found in nuclear genomes have hampered the mining and discovery of novel protistan lineages. Organellar genomes are simpler, smaller, have higher abundance than their nuclear counterparts and contain valuable phylogenetic information, but are yet to be widely used to identify new protist lineages from metagenomes. Here we present "ChloroScan", a new bioinformatics pipeline to extract eukaryotic plastid genomes from metagenomes. It incorporates a deep learning contig classifier to identify putative plastid contigs and an automated binning module to recover bins with guidance from a curated marker gene database. Additionally, ChloroScan summarizes the results in different user-friendly formats, including annotated coding sequences and proteins for each bin. We show that ChloroScan recovers more high-quality plastid bins than MetaBAT2 for simulated metagenomes. The practical utility of ChloroScan is illustrated by recovering 16 medium to high-quality metagenome assembled genomes (MAGs) from four protist-size-fraction metagenomes, with several bins showing high taxonomic novelty. The ChloroScan code (v0.1.7) is available at https://github.com/Andyargueasae/chloroscan/tree/release_v0.1.7 under Apache-2.0 licence.

Indexed as

Computational BiologyEukaryotaGenome, PlastidMetagenomicsSoftwarealgaebioinformaticsgenome‐resolved metagenomicsmicrobiomeplastid

Identifiers

PMID42003340
PMCPMC13093128

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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.