Evidence map›Paper›PMID 41246863›Full record

ArticlePlant biotechnology journal2026

An α/β-Hydrolase GmABHD6 Controls Seed Oil Content and Yield in Soybean.

Kaixin Yu, Limin Hu, Bo Sun, Zehao Chen, Xu Li, Shiyu Zhang, Huilin Tian, Wenjing Zhang, Shimin Ren, Xue Han and 6 more

Abstract read
In one paragraph

Article in Plant biotechnology journal, 2026. 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

16 authors.

Kaixin YuNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.
Limin HuNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.
Bo SunNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.
Zehao ChenNational Coarse Cereals Engineering Research Center, Heilongjiang Bayi Agricultural University, Daqing, China.
Xu LiNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.
Shiyu ZhangNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.
Huilin TianNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.ORCID https://orcid.org/0009-0002-9448-2233
Wenjing ZhangNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.
Shimin RenNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.
Xue HanNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.
Chang XuNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.
Siming WeiNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.ORCID https://orcid.org/0000-0002-4733-9744
Mingliang YangNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.
Fanjiang KongGuangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou University, Guangzhou, China.ORCID https://orcid.org/0000-0001-7138-1478
Qingshan ChenNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.
Zhaoming QiNational Key Laboratory of Smart Farm Technology and System, National Research Center of Soybean Engineering and Technology, Northeast Agricultural University, Harbin, Heilongjiang, China.ORCID https://orcid.org/0000-0002-0657-9127

Funding

China Agriculture Research System CARS-04-PS15China Postdoctoral Science Foundation 2023MD744203Hainan Seed Industry Laboratory and China National Seed Group B23YQ1503Heilongjiang Provincial Postdoctoral Science Foundation LBH-Z23011National Key Research and Development Program of China 2021YFD1201103National Key Research and Development Program of China 2023ZD0403201-03National Natural Science Foundation of China 32201755National Natural Science Foundation of China 32472108Natural Science Foundation of Heilongjiang Province of China ZL2024C007
6 · The paper itself

Abstract

Seed oil content is a key trait in soybean, yet its genetic basis remains largely unresolved. Here, we identify GmABHD6, an α/β-hydrolase domain-containing gene, as the causal gene underlying a major quantitative trait locus (QTL) for seed oil content on chromosome 16. Through fine-mapping in a chromosome segment substitution population derived from Glycine max (SN14) and wild Glycine soja (ZYD00006), we fine-mapped the QTL to a 150-kb interval. Functional analyses reveal that overexpression of GmABHD6 significantly reduces seed oil content, whereas gene editing to truncate GmABHD6 led to increased oil accumulation. These modifications also alter seed protein levels, seed size and 100-seed weight, indicating pleiotropic effects on seed composition and yield traits. Integrated transcriptomic and metabolomic profiling of transgenic lines highlighted widespread changes in lipid metabolism and energy pathways associated with GmABHD6 activity. Further functional characterisation indicates that the ERF transcription factor GmERF physically binds to the GmABHD6 promoter region to regulate its expression. Population genetic analyses show strong signatures of selection at the GmABHD6 locus, suggesting that favourable alleles are enriched during soybean domestication and improvement. Our findings establish GmABHD6 as a domestication-related gene that negatively regulates seed oil content and provide new insights into the genetic mechanisms driving soybean seed composition and evolution.

Indexed as

Glycine maxPlant OilsPlant ProteinsSeedsChromosome MappingGene Expression Regulation, PlantPlants, Genetically ModifiedQuantitative Trait LociPlant OilsPlant Proteinsdomesticationoil contentQTLsoybeanα/β‐hydrolase

Identifiers

PMID41246863
PMCPMC13140581

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.