Evidence map›Paper›PMID 41042399›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2025

Dissecting seed composition QTL from wild soybean: fine-mapping, candidate gene identification, and evaluation of introgression effects on agronomic performance.

Elizabeth De Meyer, Anser Mahmood, Mariola Usovsky, Jason Gillman, Bing Yang, Jared Decker, Qijian Song, Clinton Meinhardt, Michael Dennigmann, Asheesh K Singh and 3 more

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. 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

13 authors.

Elizabeth De MeyerDivision of Plant Science and Technology, University of Missouri, Columbia, MO, USA.
Anser MahmoodDivision of Plant Science and Technology, University of Missouri, Columbia, MO, USA.
Mariola UsovskyDivision of Plant Science and Technology, University of Missouri, Columbia, MO, USA.
Jason GillmanPlant Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, Columbia, MO, USA.
Bing YangDivision of Plant Science and Technology, University of Missouri, Columbia, MO, USA.
Jared DeckerDivision of Animal Sciences, University of Missouri, Columbia, MO, USA.
Qijian SongSoybean Genomics and Improvement Laboratory, United States Department of Agriculture-Agricultural Research Service, Beltsville, MD, USA.
Clinton MeinhardtDivision of Plant Science and Technology, University of Missouri, Columbia, MO, USA.
Michael DennigmannDivision of Plant Science and Technology, University of Missouri, Columbia, MO, USA.
Asheesh K SinghDepartment of Agronomy, Iowa State University, Ames, IA, USA.
George GraefDepartment of Agronomy and Horticulture, University of Nebraska, Lincoln, NE, USA.
Eliana MonteverdeDepartment of Crop Sciences, University of Illinois, Urbana, IL, USA.
Andrew ScabooDivision of Plant Science and Technology, University of Missouri, Columbia, MO, USA. scabooa@missouri.edu.ORCID http://orcid.org/0000-0002-9670-8446

Funding

Missouri Soybean Merchandising Council 11-340-21Missouri Soybean Merchandising Council 11-340-22Missouri Soybean Merchandising Council 11-340-23Missouri Soybean Merchandising Council 11-340-24Missouri Soybean Merchandising Council 11-340-25Missouri Soybean Merchandising Council 16-400-21Missouri Soybean Merchandising Council 16-400-22Missouri Soybean Merchandising Council 16-400-23Missouri Soybean Merchandising Council 16-400-24Missouri Soybean Merchandising Council 16-400-25
6 · The paper itself

Abstract

key messageSeed composition QTL from wild soybean were confirmed and validated in two genetic backgrounds across multiple environments, candidate genes were identified, and agronomic performance of backcross introgression lines was evaluated. Through selection for soybean yield, breeders have inadvertently reduced seed protein content and increased oil due to phenotypic and genetic correlations between these three traits. Therefore, identifying alleles that increase protein without adversely affecting oil and yield is of interest for breeders and the entire soybean value chain. Previously, a G. max × G. soja population was used to map a protein-associated region to ~ 4.6 Mbp on chromosome (Chr) 14. The G. soja allele significantly increased protein 6.5-7.2 g kg

Indexed as

Glycine maxQuantitative Trait LociSeedsAllelesChromosome MappingChromosomes, PlantCrosses, GeneticGenes, PlantPhenotypePlant Breeding

Identifiers

PMID41042399
PMCPMC12494675

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.