Evidence map›Paper›PMID 39453979›Full record

ArticlePLoS genetics2024

Pangenome graph analysis reveals extensive effector copy-number variation in spinach downy mildew.

Petros Skiadas, Sofía Riera Vidal, Joris Dommisse, Melanie N Mendel, Joyce Elberse, Guido Van den Ackerveken, Ronnie de Jonge, Michael F Seidl

Abstract read
In one paragraph

Article in PLoS genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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

8 authors.

Petros SkiadasTheoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands.ORCID https://orcid.org/0000-0001-8577-6681
Sofía Riera VidalTheoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands.
Joris DommisseTheoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands.ORCID https://orcid.org/0009-0000-5642-0483
Melanie N MendelTranslational Plant Biology, Utrecht University, Utrecht, The Netherlands.ORCID https://orcid.org/0000-0003-2409-7479
Joyce ElberseTranslational Plant Biology, Utrecht University, Utrecht, The Netherlands.
Guido Van den AckervekenTranslational Plant Biology, Utrecht University, Utrecht, The Netherlands.ORCID https://orcid.org/0000-0002-0183-8978
Ronnie de JongePlant-Microbe Interactions, Utrecht University, Utrecht, The Netherlands.ORCID https://orcid.org/0000-0001-5065-8538
Michael F SeidlTheoretical Biology and Bioinformatics, Utrecht University, Utrecht, The Netherlands.ORCID https://orcid.org/0000-0002-5218-2083

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plant pathogens adapt at speeds that challenge contemporary disease management strategies like the deployment of disease resistance genes. The strong evolutionary pressure to adapt, shapes pathogens' genomes, and comparative genomics has been instrumental in characterizing this process. With the aim to capture genomic variation at high resolution and study the processes contributing to adaptation, we here leverage an innovative, multi-genome method to construct and annotate the first pangenome graph of an oomycete plant pathogen. We expand on this approach by analysing the graph and creating synteny based single-copy orthogroups for all genes. We generated telomere-to-telomere genome assemblies of six genetically diverse isolates of the oomycete pathogen Peronospora effusa, the economically most important disease in cultivated spinach worldwide. The pangenome graph demonstrates that P. effusa genomes are highly conserved, both in chromosomal structure and gene content, and revealed the continued activity of transposable elements which are directly responsible for 80% of the observed variation between the isolates. While most genes are generally conserved, virulence related genes are highly variable between the isolates. Most of the variation is found in large gene clusters resulting from extensive copy-number expansion. Pangenome graph-based discovery can thus be effectively used to capture genomic variation at exceptional resolution, thereby providing a framework to study the biology and evolution of plant pathogens.

Indexed as

DNA Copy Number VariationsPeronosporaPlant DiseasesSpinacia oleraceaDisease ResistanceDNA Transposable ElementsGenomicsOomycetesSyntenyVirulenceDNA Transposable Elements

Identifiers

PMID39453979
PMCPMC11540230

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Registered trials

None linked

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.