Evidence map›Paper›PMID 40971764›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Marker Metabolite-Based Multi-Omics Analysis Identifies New Loci Controlling Thousand Seed Weight in Brassica Napus.

Long Li, Zhitao Tian, Xiaowei Wu, Zengdong Tan, Xu Han, Yuyan Xiang, Jie Chen, Hu Zhao, Wei Chen, Liang Guo and 1 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. A High-Thousand-Seed-Weight Mutant ofInternational journal of molecular sciences · 2026
    Article
  4. 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

11 authors.

Long LiNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.
Zhitao TianNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.
Xiaowei WuNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.
Zengdong TanYazhouwan National Laboratory, Sanya, 572025, China.
Xu HanYazhouwan National Laboratory, Sanya, 572025, China.
Yuyan XiangNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.
Jie ChenYazhouwan National Laboratory, Sanya, 572025, China.
Hu ZhaoNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.
Wei ChenNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.
Liang GuoNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.ORCID https://orcid.org/0000-0001-7191-5062
Xuan YaoNational Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.

Funding

Basic Research Project of Yazhouwan National Laboratory 2310YGL01National Key Research and Development Plan of China 2023YFF1000700National Science Fund for Distinguished Young Scholars 32225037
6 · The paper itself

Abstract

The thousand seed weight (TSW) of Brassica napus (B. napus) is a crucial agronomic trait, and metabolites serve as a bridge between genotype and phenotype. Leveraging previously released metabolome data from a 388 B. napus population, 137 marker metabolites significantly correlated with TSW are identified, and 21 markers significantly correlate with both TSW and seed oil content. To delve deeper into the relationships between selected marker metabolites and phenotypes, a comprehensive multi-omics analysis is conducted, which unveils 734 metabolite-QTLs, 5,225 expression-QTLs, and 9,077 transcriptome-wide significantly associated genes. Employing weighted correlation network analysis, a triple-link network is constructed involving 133 metabolites, 731 QTLs, and 3,321 genes. The multi-omics analysis highlights the impact of the transcriptional factor TGACG motif-binding factor 6 (BnaA03.TGA6) on TSW. Functional validation experiments with tga6 CRISPR/Cas9 mutants demonstrate larger seeds and altered associated metabolites levels compared to the wild type. RNA Sequencing, dual-luciferase assay, Cleavage Under Targets and Tagmentation, and Electrophoretic Mobility Shift Assay results confirm that BnaA03.TGA6 activates the expression of E3 ubiquitin-protein ligase DA2. In conclusion, this study is the first marker metabolite-based multi-omics analysis in unraveling the genetic basis of TSW in crop and identifying BnaA03.TGA6 as a novel gene negatively influencing TSW in B. napus.

Indexed as

Brassica napusMetabolomeQuantitative Trait LociSeedsGene Expression Regulation, PlantMetabolomicsMultiomicsPhenotypeTranscriptomebrassica napusCUT&Tagdual‐luciferase assayEMSAmarker metabolitemetabolomemGWASmTWASthousand seed weight

Identifiers

PMID40971764
PMCPMC12622543

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.