Evidence map›Paper›PMID 42477785›Full record

ArticleGenome biology2026

Dissecting the genetic basis of yield stability in faba bean by multi-environment analysis.

Elesandro Bornhofen, Troels W Mouritzen, Sheila Alves, Thomas Ramsay Robertson-Shersby-Harvie, Cathrine Kiel Skovbjerg, Alex Windhorst, Hailin Zhang, Thilani Bhagya Jayakody, Jing Zhang, Marcin Nadzieja and 18 more

Abstract read
In one paragraph

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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

28 authors.

Elesandro BornhofenCenter for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark. bornhofen@qgg.au.dk.ORCID http://orcid.org/0000-0002-7447-6226
Troels W MouritzenDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Sheila AlvesTeagasc, Crops Research, Oak Park, Carlow, Ireland.
Thomas Ramsay Robertson-Shersby-HarvieSchool of Agriculture, Policy and Development, University of Reading, Reading, UK.
Cathrine Kiel SkovbjergDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Alex WindhorstDivision of Plant Breeding Methodology, Georg-August-University Goettingen, Goettingen, Germany.
Hailin ZhangLeibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany.
Thilani Bhagya JayakodyDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Jing ZhangDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Marcin NadziejaDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
Hyeonah ShimLeibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany.
Jean-Bernard Magnin-RobertUniversité Bourgogne Europe, Institut Agro Dijon, INRAE, Agroécologie, Dijon, France.
Grégoire AubertUniversité Bourgogne Europe, Institut Agro Dijon, INRAE, Agroécologie, Dijon, France.
Matthieu FloriotAgri Obtentions, Guyancourt, France.
Camille GuiziouAgri Obtentions, Guyancourt, France.
Olaf SassNorddeutsche Pflanzenzucht Hans-Georg Lembke KG, Holtsee, Germany.
Gregor WelnaNorddeutsche Pflanzenzucht Hans-Georg Lembke KG, Holtsee, Germany.
Ignacio Solís, Agrovegetal, Seville, Spain.
Linda Kærgaard NielsenSejet Plant Breeding, Horsens, Denmark.
Natalia GutiérrezÁrea de Mejora Vegetal y Biotecnología, IFAPA, Córdoba, Spain.
Murukarthick JayakodiDepartment of Soil and Crop Sciences, Texas A&M AgriLife Research Dallas Center, Dallas, TX, USA.
Frederick L StoddardDepartment of Agricultural Sciences, University of Helsinki, Helsinki, Finland.
Donal Martin O'SullivanSchool of Agriculture, Policy and Development, University of Reading, Reading, UK.
Ana M TorresÁrea de Mejora Vegetal y Biotecnología, IFAPA, Córdoba, Spain.
Wolfgang LinkDivision of Plant Breeding Methodology, Georg-August-University Goettingen, Goettingen, Germany.
Nadim TayehUniversité Bourgogne Europe, Institut Agro Dijon, INRAE, Agroécologie, Dijon, France.
Luc JanssCenter for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark. luc.janss@qgg.au.dk.
Stig Uggerhøj AndersenDepartment of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark. sua@mbg.au.dk.ORCID http://orcid.org/0000-0002-1096-1468

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFaba bean is a globally adapted legume protein crop with a high yield potential. Currently, yield variation across environments limits more widespread cultivation, and the underlying genetics remain poorly understood.

resultsHere, we identify major QTL for faba bean yield and yield stability. We genotype the ProFaba diversity panel with high resolution and carry out coordinated multi-year/location trials across Europe. Based on these data, we identify more than one hundred loci associated with mean performance and stability for 14 complex traits, including yield. Experimental validation supports the involvement of the candidate gene Vfaba.Hedin2.R2.1g002122 in plant architecture, with gene expression significantly associated with first pod position and plant height. Furthermore, we introduce a method for integrating environmental data in the analysis of trait stability based on a random regression mixed model, which enables prediction of performance in untested environments.

conclusionsOur study provides insights into the genetic architecture of yield, yield stability, and genotype-by-environment interaction in faba bean. The genomic resources, candidate loci, and weather-informed analytical framework provide practical tools for predicting performance across environments and accelerating breeding of resilient, high-yielding protein crops.

Indexed as

Gene-Environment InteractionQuantitative Trait LociVicia fabaEnvironmentGenotypePhenotype

Identifiers

PMID42477785
PMCPMC13383516

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.