Evidence map›Paper›PMID 40220041›Full record

ArticleMolecular genetics and genomics : MGG2025

Soybean genome‑wide association study of seed weight, protein, and oil content in the southeastern USA.

Jinesh Patel, Sejal Patel, Lauren Cook, Benjamin D Fallen, Jenny Koebernick

Abstract read
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Article in Molecular genetics and genomics : MGG, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

7 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

5 authors.

Jinesh PatelDepartment of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, 36849, USA. jineshpatel2000@gmail.com.ORCID http://orcid.org/0000-0001-6696-2155
Sejal PatelDepartment of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, 36849, USA.
Lauren CookDepartment of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, 36849, USA.
Benjamin D FallenUSDA, Agricultural Research Service, Raleigh, NC, 27606, USA.
Jenny KoebernickDepartment of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, 36849, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soybean is a globally significant legume crop, providing essential protein and oil for human and livestock nutrition. Improving oil and protein content simultaneously without compromising yield has been challenging due to the quantitative nature of these traits and their interrelationships. This study aims to deepen our understanding of the molecular basis soybean of seed weight, protein, and oil content to facilitate marker-assisted breeding to enhance these traits. In this research, a Genome-Wide Association Study (GWAS) was conducted utilizing 285 diverse soybean accessions from maturity group V, employing genotyping through the SoySNP50K platform. These accessions were tested in three environmental conditions of the southeast US for three traits: 100-seed weight, protein, and oil content. The study identified 18, 23, and 26 SNPs significantly associated with 100-seed weight, seed oil, and protein content. Colocalized protein and oil content regions were discovered on chromosomes 15, 16, and 20. Chromosomes 15 and 20 are well documented to have pleiotropic but opposite effects on oil and protein content, but both regions contain genes that affect individual traits, such as FAD2-1 and nodulin MtN21. A 1.92 Mb region on chromosome 11 exhibits a target region to improve oil and seed weight without affecting protein content. This study highlights key genomic regions and candidate genes influencing seed weight, protein, and oil content, with some regions affecting multiple traits. Hence, these findings provide a valuable foundation for marker-assisted selection to optimize seed weight and simultaneously enhance oil and protein content in soybean breeding programs.

Indexed as

Glycine maxPlant OilsPlant ProteinsSeedsChromosome MappingChromosomes, PlantGenome, PlantGenome-Wide Association StudyGenotypePhenotypePlant BreedingPolymorphism, Single NucleotideQuantitative Trait LociSoutheastern United StatesPlant OilsPlant ProteinsGWASProteinQTLSeed oilSeed weight

Identifiers

PMID40220041
PMCPMC11993454

What OpenQuestion holds

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LicenceCC BY
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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.