Fan Jingwei, Shen Yanting, Chen Chuan, Chen Xi, Yang Xiaoyue, Liu Haixia, Chen Ruiying, Liu Shulin, Zhang Bohan, Zhang Min, Zhou Guoan, Wang Yu, Sun Haixi, Jiang Yuqiang, Wei Xiaofeng, Yang Tao, Liu Yucheng, Tian Dongmei, Deng Ziqing, Xu Xun, Liu Xin, Tian Zhixi
State Key Laboratory of Seed Innovation, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
State Key Laboratory of Seed Innovation, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; Yazhouwan National Laboratory, Sanya 572000, Hainan, China.
Mol Plant. 2025 Apr 7;18(4):669-689. doi: 10.1016/j.molp.2025.02.003. Epub 2025 Feb 18.
Soybean is one of the most important crops globally, and its production must be significantly increased to meet increasing demand. Elucidating the genetic regulatory networks underlying soybean organ development is essential for breeding elite and resilient varieties to ensure increased soybean production under climate change. An integrated transcriptomic atlas that leverages multiple types of transcriptomics data can facilitate the characterization of temporal-spatial expression patterns of most organ development-related genes and thereby help us to understand organ developmental processes. Here, we constructed a comprehensive, integrated transcriptomic atlas for soybeans, integrating bulk RNA sequencing (RNA-seq) datasets from 314 samples across the soybean life cycle, along with single-nucleus RNA-seq and spatially enhanced resolution omics sequencing datasets from five organs: root, nodule, shoot apex, leaf, and stem. Investigating genes related to organ specificity, blade development, and nodule formation, we demonstrate that the atlas has robust power for exploring key genes involved in organ formation. In addition, we developed a user-friendly panoramic database for the transcriptomic atlas, enabling easy access and queries, which will serve as a valuable resource to significantly advance future soybean functional studies.
大豆是全球最重要的作物之一，必须大幅提高其产量以满足不断增长的需求。阐明大豆器官发育的遗传调控网络对于培育优良且适应力强的品种至关重要，以便在气候变化的情况下确保大豆产量增加。利用多种类型转录组学数据构建的综合转录组图谱，有助于表征大多数与器官发育相关基因的时空表达模式，从而帮助我们了解器官发育过程。在此，我们构建了一个全面的大豆综合转录组图谱，整合了来自大豆生命周期中314个样本的大量RNA测序（RNA-seq）数据集，以及来自根、根瘤、茎尖、叶和茎五个器官的单核RNA-seq和空间增强分辨率组学测序数据集。通过研究与器官特异性、叶片发育和根瘤形成相关的基因，我们证明该图谱在探索参与器官形成的关键基因方面具有强大的能力。此外，我们为该转录组图谱开发了一个用户友好的全景数据库，便于访问和查询，这将成为推动未来大豆功能研究的宝贵资源。
