Evidence map›Paper›PMID 40542846›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2025

Crop wild relative populations of Beta vulgaris as source for genome-wide association mapping of complex traits.

Lisa Bertram, Friedrich Kopisch-Obuch, Matthias Frisch

Abstract read
In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Morphological and genetic diversity ofFrontiers in plant science · 2025
    Review
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

3 authors.

Lisa BertramInstitute of Agronomy and Plant Breeding II, Justus Liebig University, Giessen, Germany. lisa.bertram@kws.com.ORCID http://orcid.org/0000-0001-8055-8490
Friedrich Kopisch-ObuchKWS SAAT SE & Co. KGaA, Einbeck, Germany.ORCID http://orcid.org/0000-0002-6237-3668
Matthias FrischInstitute of Agronomy and Plant Breeding II, Justus Liebig University, Giessen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

key messageWild beet populations can be used for the detection of minor genes underlying quantitative traits Wild beet populations as valuable source for new genetic variation have so far not been used to detect minor genes underlying quantitative traits, such as drought tolerance or yield. These traits cannot be assessed in wild beets per se but require the development of a beet for phenotypic evaluation. Hence, crossing to elite genome is necessary. Our objective was to determine how QTL detection is affected by (1) the properties of the wild beet population, (2) the quantitative trait architecture, and (3) the structure of the mapping populations. Based on genotypic data of three wild beet populations, nine crossing designs to construct mapping populations were simulated and evaluated for their power to detect minor QTL and their false detection rate. Mapping populations containing 50% wild beet genome have the highest power in this study and can detect even QTL with allele frequencies of < 1% with reasonable power. However, to allow for reasonable phenotyping within field trials at least 75% elite genome in the mapping population is needed. We conclude that crossing designs based on elite x wild beet F1s are most suitable for genome-wide association mapping of complex traits in wild beet populations.

Indexed as

Beta vulgarisChromosome MappingGenome, PlantGenome-Wide Association StudyQuantitative Trait LociCrosses, GeneticGene FrequencyGenotypePhenotype

Identifiers

PMID40542846
PMCPMC12182527

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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.