Evidence map›Paper›PMID 41331908›Full record

ArticleBMC plant biology2025

Exploring metabolite diversity in global rapeseed germplasm: insights into ecotypes, geographical influences, and correlations with diabetes.

Pei Wang, Yungu Zhai, Yongfeng Wang, Bing Zhao, Xiao Wang, Fei Liu, Cuiling Yang, Shicheng Zhang, Haojie Liu, Xuebin Zhang and 1 more

Abstract read
In one paragraph

Article in BMC plant biology, 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

11 authors.

Pei Wang *College of Agriculture; School of Mathematics and Statistics; State Key Laboratory of Crop Stress Adaption and Improvement, Henan University, Jinming Avenue, Kaifeng, Henan, 475004, China.
Yungu Zhai *College of Agriculture; School of Mathematics and Statistics; State Key Laboratory of Crop Stress Adaption and Improvement, Henan University, Jinming Avenue, Kaifeng, Henan, 475004, China.
Yongfeng WangCollege of Agriculture; School of Mathematics and Statistics; State Key Laboratory of Crop Stress Adaption and Improvement, Henan University, Jinming Avenue, Kaifeng, Henan, 475004, China.
Bing ZhaoCollege of Agriculture; School of Mathematics and Statistics; State Key Laboratory of Crop Stress Adaption and Improvement, Henan University, Jinming Avenue, Kaifeng, Henan, 475004, China.
Xiao WangCollege of Agriculture; School of Mathematics and Statistics; State Key Laboratory of Crop Stress Adaption and Improvement, Henan University, Jinming Avenue, Kaifeng, Henan, 475004, China.
Fei LiuCollege of Agriculture; School of Mathematics and Statistics; State Key Laboratory of Crop Stress Adaption and Improvement, Henan University, Jinming Avenue, Kaifeng, Henan, 475004, China.
Cuiling YangCollege of Agriculture; School of Mathematics and Statistics; State Key Laboratory of Crop Stress Adaption and Improvement, Henan University, Jinming Avenue, Kaifeng, Henan, 475004, China.
Shicheng ZhangCollege of Agriculture; School of Mathematics and Statistics; State Key Laboratory of Crop Stress Adaption and Improvement, Henan University, Jinming Avenue, Kaifeng, Henan, 475004, China.
Haojie LiuCollege of Agriculture; School of Mathematics and Statistics; State Key Laboratory of Crop Stress Adaption and Improvement, Henan University, Jinming Avenue, Kaifeng, Henan, 475004, China.
Xuebin ZhangCollege of Agriculture; School of Mathematics and Statistics; State Key Laboratory of Crop Stress Adaption and Improvement, Henan University, Jinming Avenue, Kaifeng, Henan, 475004, China.
Daojie WangCollege of Agriculture; School of Mathematics and Statistics; State Key Laboratory of Crop Stress Adaption and Improvement, Henan University, Jinming Avenue, Kaifeng, Henan, 475004, China. wangdj@henu.edu.cn.

Funding

key research and development program of Henan Province 241111112400
6 · The paper itself

Abstract

backgroundRapeseed oil is widely recognized for its health benefits; however, the relationships between its metabolites and factors such as ecotypes, geographical regions, plant traits, and diabetes risk remain poorly understood. This study delves into the metabolic diversity of rapeseed across various ecotypes and geographical origins, while also examining its potential associations with plant traits and diabetes incidence rates.

resultsComprehensive metabolomic analysis of 125 rapeseed accessions reveals substantial variations in 2,603 out of 6,048 detected metabolites, encompassing 107 fatty acyls, 124 flavonoids, and 10 phenolic compounds. These metabolic variations likely stem from the complex interplay of genetic divergence, historical selection, environmental adaptability of varieties, and other contributing factors. Penalized regression analysis reveals 24 metabolites associated with the length of the main inflorescence and 26 metabolites linked to the silique count of the main inflorescence, highlighting the possible metabolic underpinnings of these structural traits. Notably, specific metabolites-identified as docosatrienoic acid (M335T887_POS), uridine monophosphate (UMP, M340T917_NEG), and rosmarinate (M719T323_NEG)-are significantly associated with diabetes incidence. These associations suggest a potential link between the consumption of rapeseed and diabetes risk.

conclusionsOur findings illustrate the putative links between agricultural production, plant metabolism, and human health. The study emphasizes the potential to enhance rapeseed's nutritional profile and improve health outcomes through targeted breeding or metabolic engineering of specific metabolites. Further research is crucial to unravel the underlying mechanisms and to develop sustainable food strategies aimed at optimizing health benefits.

Indexed as

Brassica napusBrassica rapaDiabetes MellitusMetabolomeEcotypeGeographyHumansMetabolomicsSeedsDiabetes correlationsEcotype divergenceGeographical influencesGlobal rapeseed germplasmMetabolite diversity

Identifiers

PMID41331908
PMCPMC12776989

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.