Evidence map›Paper›PMID 41169047›Full record

ArticlePlant communications2026

Spatiotemporal transcriptomic and metabolomic landscapes of wild soybean seed development reveal regulatory mechanisms of nutrient accumulation.

Peiyan Liu, Mingyang Li, Ping Ma, Hao Yan, Chunyan Liu, Zhenbang Hu, Mingliang Yang, Qingshan Chen, Ying Zhao

Abstract read
In one paragraph

Article in Plant communications, 2026. 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. Multi-Omics Revealed Key Pathways Related to Soybean (International journal of molecular sciences · 2026
    Article
  2. Article
  3. Review
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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

9 authors.

Peiyan LiuNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology, Chinese Education Ministry, College of Agriculture, Northeast Agricultural University, Harbin 150000, China.
Mingyang LiNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology, Chinese Education Ministry, College of Agriculture, Northeast Agricultural University, Harbin 150000, China.
Ping MaNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology, Chinese Education Ministry, College of Agriculture, Northeast Agricultural University, Harbin 150000, China.
Hao YanNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology, Chinese Education Ministry, College of Agriculture, Northeast Agricultural University, Harbin 150000, China.
Chunyan LiuNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology, Chinese Education Ministry, College of Agriculture, Northeast Agricultural University, Harbin 150000, China.
Zhenbang HuNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology, Chinese Education Ministry, College of Agriculture, Northeast Agricultural University, Harbin 150000, China.
Mingliang YangNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology, Chinese Education Ministry, College of Agriculture, Northeast Agricultural University, Harbin 150000, China.
Qingshan ChenNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology, Chinese Education Ministry, College of Agriculture, Northeast Agricultural University, Harbin 150000, China. Electronic address: qshchen@126.com.
Ying ZhaoNational Key Laboratory of Smart Farm Technology and System, Key Laboratory of Soybean Biology, Chinese Education Ministry, College of Agriculture, Northeast Agricultural University, Harbin 150000, China. Electronic address: tianshi198937@126.com.

Funding

Non-US Government Research Support type
6 · The paper itself

Abstract

Seed development is a pivotal stage of the soybean life cycle, directly determining yield and nutritional quality related to oil and protein contents. However, the spatiotemporal mechanisms underlying cell differentiation and nutrient accumulation during seed growth remain to be resolved, especially in wild soybean (Glycine soja), which harbors rich genetic diversity for quality traits. Here, spatial transcriptomics and metabolomics were combined to dissect the dynamics of cell differentiation and nutrient accumulation in G. soja seeds at the mid-maturity stage. Differential expression analysis revealed distinct patterns of accumulation in adaxial versus abaxial parenchyma cells of the embryo: abaxial cells are enriched in protein metabolism pathways, whereas adaxial cells are focused on lipid metabolism pathways, consistent with previous reports on spatial nutrient accumulation in G. soja seeds. Pseudotemporal trajectory analyses supported a sequential pattern of transcriptional regulation underlying these differences. Analysis of cell-cell communication provided insight into the interactions that may mediate cell-type-specific differences among seed cells. Key genetic regulators and differentially abundant metabolites were identified through the integration of spatial transcriptomics and metabolomics, and GsMAPK23-4 was identified as a core candidate gene linked to nutrient metabolism in the cotyledon. Functional validation confirmed that GsMAPK23-4 modulates seed quality: knockout mutants had significantly higher levels of amino acids and proteins. These findings reveal cellular characteristics and differentiation processes in G. soja seeds at the mid-maturity stage, providing a molecular basis for understanding this phase and generating targets to improve soybean yield and quality.

Indexed as

Glycine maxNutrientsSeedsTranscriptomeGene Expression ProfilingGene Expression Regulation, PlantMetabolomicsNutrientscrop wild relativeseed developmentsoybeanspatial metabolomicsspatial transcriptomics

Identifiers

PMID41169047
PMCPMC12902272

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LicenceCC BY-NC-ND
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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.