Evidence map›Paper›PMID 41133998›Full record

ArticleGigaScience2025

Ultra-deep long-read metagenomics captures diverse taxonomic and biosynthetic potential of soil microbes.

Caner Bağcı, Timo Negri, Elena Buena-Atienza, Caspar Gross, Stephan Ossowski, Nadine Ziemert

Abstract read
In one paragraph

Article in GigaScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
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  4. Review
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  6. Article
  7. Review
  8. 16S rRNA sequence captures microbial functional potential.bioRxiv : the preprint server for biology · 2026
    Article
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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

6 authors.

Caner BağcıTranslational Genome Mining for Natural Products, Interfaculty Institute of Microbiology and Infection Medicine Tübingen (IMIT), University of Tübingen, 72076 Tübingen, Baden-Württemberg, Germany.ORCID 0000-0003-4428-9515
Timo NegriTranslational Genome Mining for Natural Products, Interfaculty Institute of Microbiology and Infection Medicine Tübingen (IMIT), University of Tübingen, 72076 Tübingen, Baden-Württemberg, Germany.
Elena Buena-AtienzaInstitute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Baden-Württemberg, Germany.
Caspar GrossInstitute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Baden-Württemberg, Germany.ORCID 0000-0002-9009-5458
Stephan OssowskiInstitute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Baden-Württemberg, Germany.ORCID 0000-0002-7416-9568
Nadine ZiemertTranslational Genome Mining for Natural Products, Interfaculty Institute of Microbiology and Infection Medicine Tübingen (IMIT), University of Tübingen, 72076 Tübingen, Baden-Württemberg, Germany.ORCID 0000-0002-7264-1857

Funding

Bundesministerium für Bildung und Forschung 161L0284CDeutsche Forschungsgemeinschaft INST 37/1049-1Deutsches Zentrum für Infektionsforschung TTU09.716
6 · The paper itself

Abstract

backgroundSoil ecosystems have long been recognized as hotspots of microbial diversity, but most estimates of their microbial and functional complexity remain speculative despite decades of study, in part because conventional sequencing campaigns lack the depth and contiguity required to recover low-abundance and repetitive genomes. Here, we revisit this question using one of the deepest metagenomic sequencing efforts to date, applying 148 billion basepairs of Nanopore long-read data and 122 billion basepairs of Illumina short-read data to a single forest soil sample.

resultsOur hybrid assembly reconstructed 837 metagenome-assembled genomes, including 466 that meet high- and medium-quality standards, nearly all lacking close relatives among cultivated taxa. Rarefaction and k-mer analyses reveal that, even at this depth, we capture only a fraction of the extant diversity: nonparametric models project that more than 10 trillion basepairs of sequencing data would be required to approach saturation. These findings offer a quantitative, technology-enabled update to long-standing diversity estimates and demonstrate that conventional metagenomic sequencing efforts likely miss most microbial and biosynthetic potential in soil. We further identify more than 11,000 biosynthetic gene clusters, over 99% of which have no match in current databases, underscoring the breadth of unexplored metabolic capacity.

conclusionsTaken together, our results emphasize both the power and the present limitations of metagenomics in resolving natural microbial complexity, and they provide a new baseline for evaluating future advances in microbial genome recovery, taxonomic classification, and natural product discovery.

Indexed as

BacteriaHigh-Throughput Nucleotide SequencingMetagenomicsSoil MicrobiologyMetagenomePhylogenydiversitylong-read sequencing(meta)genome miningmetagenomicsmicrobiomenanoporenatural productssoilultra-deep

Identifiers

PMID41133998
PMCPMC12690461

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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.