Soybean is a staple food and economic crop vital to China’s food security and agricultural economy, serving as the primary global source of plant protein and edible oil and playing an indispensable role in the feed industry. Yet China imports more than 80 % of its soybeans. Overcoming this “bottleneck” demands a deeper deciphering of the crop’s “life code” and the application of cutting-edge technologies to boost yield and quality. Proteins are the direct executors of genetic blueprints; however, soybean research has long focused on DNA and RNA levels. A high-quality, whole-proteome quantitative map has been missing, severely limiting the discovery of key regulators of growth and development and stalling breeding innovation.

 

Now, a joint team led by Dr. Xiao Luo (Shandong Key Laboratory of Precision Molecular Crop Design and Breeding, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang), Dr. Long Yan (Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Science) and Dr. Zhe Liang (Biotechnology Research Institute, Chinese Academy of Agricultural Sciences) publishes in Cell Genomics the study “Landscape and m⁶A post-transcriptional regulation of soybean proteome”. Using 4D-DIA-MS, deep fractionation and high-resolution chromatography, the team quantified >12,800 proteins across 14 soybean organs, generated the first panoramic proteome atlas, revealed the decisive role of RNA N6-methyladenosine (m⁶A) in protein output, and identified a new m⁶A regulator — GmMTBa — that controls plant architecture.

 

 

First “protein map” of soybean reveals the protein basis of trait control
The atlas (Fig. 1) demonstrates that protein expression patterns across organs are far more stable and specific than transcript patterns. Many genes exhibit non-linear relationships between mRNA and protein abundance, highlighting extensive post-transcriptional regulation during soybean development.

 

Fig. 1 Soybean quantitative proteome atlas.

 

m⁶A acts as a “hidden switch” for protein output
Parallel m⁶A -seq2 profiling of the same 14 organs (Fig. 2) revealed global m⁶A distribution and function. m⁶A is the third strongest predictor of protein abundance — after codon usage and mRNA level — markedly reducing translational efficiency. This finding overturns the traditional view of gene-expression control and underscores the synergy between transcriptional and post-transcriptional regulation in soybean.

 

Fig. 2 Soybean m⁶A methylome map.

 

Mining a novel key gene for precision breeding
Integrating proteomic and m6A data pinpointed GmMTBa, a previously unknown m6A regulator. CRISPR knock-out of GmMTBa sharply reduced global m⁶A levels and produced striking developmental phenotypes, including altered plant height and architecture (Fig. 3), proving GmMTBa to be a central developmental m⁶A modulator. This discovery illustrates the power of proteomics-guided gene discovery and offers a “golden key” for breeding improved cultivars via gene editing.

 

Fig. 3 GmMTBa is a core m⁶A regulator of soybean plant height and architecture.

 

Overall, the study propels soybean multi-omics from gene expression to protein function, providing the most comprehensive quantitative proteomic resource to date and clarifying the dual regulatory roles of m⁶A. These findings furnish new perspectives and invaluable datasets for dissecting complex agronomic traits and pave the way for “smart-design breeding” in soybean.

 

Dr. Xiao Luo, Dr. Long Yan and Dr. Zhe Liang are co-corresponding authors. Co-first authors are Leili Wang (research assistant, Peking University Institute of Advanced Agricultural Sciences, now PhD candidate at Nanjing Agricultural University), Qing Yang (Hebei Academy of Agricultural and Forestry Science), Zhiyang Hou, Linxia Li (Biotechnology Research Institute, Chinese Academy of Agricultural Sciences) and Shangtong Li (Glbizzia Biosciences,). Xiaofei Ma (research assistant, Peking University Institute of Advanced Agricultural Sciences) also made important contributions to this study.

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This work was supported by the Biotech Breeding-National Science and Technology Major Project, the National Natural Science Foundation of China, the National Key R&D Program of China, the Taishan Scholars Program, the Shandong Provincial Natural Science Foundation.

 

Paper: https://www.cell.com/cell-genomics/fulltext/S2666-979X(25)00182-X