Evidence map›Paper›PMID 40327676›Full record

ArticlePloS one2025

Fingerprinting and chemotyping approaches reveal a wide genetic and metabolic diversity among wild hops (Humulus lupulus L.).

Florent Ducrocq, Séverine Piutti, Alena Henychová, Jean Villerd, Alexandre Laflotte, Loïc Girardeau, Jérémy Grosjean, Josef Patzak, Alain Hehn

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 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

9 authors.

Florent DucrocqUniversité de Lorraine, INRAE, LAE, Nancy, France.ORCID https://orcid.org/0009-0006-5201-7914
Séverine PiuttiUniversité de Lorraine, INRAE, LAE, Nancy, France.
Alena HenychováHop Research Institute Co. Ltd., Žatec, Czech Republic.
Jean VillerdUniversité de Lorraine, INRAE, LAE, Nancy, France.
Alexandre LaflotteUniversité de Lorraine, Centre de Recherche et Développement de la Bouzule, Nancy, France.
Loïc GirardeauUniversité de Lorraine, INRAE, LAE, Nancy, France.
Jérémy GrosjeanUniversité de Lorraine, INRAE, LAE, Nancy, France.
Josef PatzakHop Research Institute Co. Ltd., Žatec, Czech Republic.
Alain HehnUniversité de Lorraine, INRAE, LAE, Nancy, France.ORCID https://orcid.org/0000-0003-4507-8031

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hop (Humulus lupulus L.) is an emblematic industrial crop in the French North East region that developed at the same time as the brewing activity. Presently, this sector, especially microbreweries, are interested in endemic wild hops, which give beer production a local signature. In this study, we investigated the genetic and metabolic diversity of thirty-six wild hops sampled in various ecological environments. These wild accessions were propagated aeroponically and cultivated under uniform conditions (the same soil and the same environmental factors). Our phytochemical approach based on UHPLC-ESI-MS/MS analysis led to the identification of three metabolic clusters based on leaf content and characterized by variations in the contents of twelve specialized metabolites that were identified (including xanthohumol, bitter acids, and their oxidized derivatives). Furthermore, molecular characterization was carried out using sixteen EST-SSR microsatellites, allowing a genetic affiliation of our wild hops with hop varieties cultivated worldwide and wild hops genotyped to date using this method. Genetic proximity was observed for both European wild and hop varieties, especially for Strisselspalt, the historical variety of our region. Finally, our findings collectively assessed the impact of the hop genotype on the chemical phenotype through multivariate regression tree (MRT) analysis. Our results highlighted the 'WRKY 224' allele as a key discriminator between high- and low-metabolite producers. Moreover, the model based on genetic information explained 40% of the variance in the metabolic data. However, despite this strong association, the model lacked predictive power, suggesting that its applicability may be confined to the datasets analyzed.

Indexed as

Genetic VariationHumulusChromatography, High Pressure LiquidGenotypeMicrosatellite RepeatsPhenotypePlant LeavesTandem Mass Spectrometry

Identifiers

PMID40327676
PMCPMC12054859

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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.