Evidence map›Paper›PMID 40313727›Full record

ArticleFrontiers in plant science2025

Identification of novel candidate genes for regulating oil composition in soybean seeds under environmental stresses.

Patrick Bewick, Peter Forstner, Bo Zhang, Eva Collakova

Abstract read
In one paragraph

Article in Frontiers in plant science, 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. Article
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

4 authors.

Patrick BewickSchool of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States.
Peter ForstnerSchool of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States.
Bo ZhangSchool of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States.
Eva CollakovaSchool of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A key objective of soybean breeding programs is to enhance nutritional quality for human and animal consumption, with improved fatty acid (FA) composition for health benefits, and expand soybean use for industrial applications. Methods: We conducted a metabolite genome-wide association study (mGWAS) to identify genomic regions associated with changes in FA composition and FA ratios in soybean seeds influenced by environmental factors. This mGWAS utilized 218 soybean plant introductions (PIs) grown in two field locations in Virginia over two years. Results: The mGWAS revealed that 20 SNPs were significantly associated with 21 FA ratios, while additional suggestive SNPs were found for 36 FA ratios, highlighting potential quantitative trait loci linked to FA composition. Discussion: Many of these SNPs are located near or within the genes related to phytohormone-mediated biotic and abiotic stress responses, suggesting the involvement of environmental factors in modulating FA composition in soybean seeds. Our findings provide novel insights into the genetic and environmental factors influencing FA composition in oilseeds. This research also lays the foundation for developing stable markers to develop soybean cultivars with tailored FA profiles for different practical applications under variable growth conditions.

Indexed as

abiotic and biotic stressesfatty acidsmGWASoil compositionphytohormone signalingSNPssoybean seeds

Identifiers

PMID40313727
PMCPMC12044429

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.