Ke Yuji, Pujol Vincent, Staut Jasper, Pollaris Lotte, Seurinck Ruth, Eekhout Thomas, Grones Carolin, Saura-Sanchez Maite, Van Bel Michiel, Vuylsteke Marnik, Ariani Andrea, Liseron-Monfils Christophe, Vandepoele Klaas, Saeys Yvan, De Rybel Bert
Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium; VIB Center for Plant Systems Biology, Ghent, Belgium.
Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium; VIB Center for Inflammation Research, Ghent, BE, Belgium.
Cell Rep. 2025 Feb 25;44(2):115240. doi: 10.1016/j.celrep.2025.115240. Epub 2025 Feb 1.
Despite the broad use of single-cell/nucleus RNA sequencing in plant research, accurate cluster annotation in less-studied plant species remains a major challenge due to the lack of validated marker genes. Here, we generated a single-cell RNA sequencing atlas of soil-grown wheat roots and annotated cluster identities by transferring annotations from publicly available datasets in wheat, rice, maize, and Arabidopsis. The predictions from our orthology-based annotation approach were next validated using untargeted spatial transcriptomics. These results allowed us to predict evolutionarily conserved tissue-specific markers and generate cell type-specific gene regulatory networks for root tissues of wheat and the other species used in our analysis. In summary, we generated a single-cell and spatial transcriptomics resource for wheat root apical meristems, including numerous known and uncharacterized cell type-specific marker genes and developmental regulators. These data and analyses will facilitate future cell type annotation in non-model plant species.
尽管单细胞/细胞核RNA测序在植物研究中得到了广泛应用,但由于缺乏经过验证的标记基因,在研究较少的植物物种中进行准确的细胞簇注释仍然是一项重大挑战。在这里,我们生成了土壤种植小麦根的单细胞RNA测序图谱,并通过从小麦、水稻、玉米和拟南芥的公开可用数据集中转移注释来注释细胞簇身份。接下来,我们使用非靶向空间转录组学验证了基于直系同源的注释方法的预测结果。这些结果使我们能够预测进化上保守的组织特异性标记,并为小麦以及我们分析中使用的其他物种的根组织生成细胞类型特异性的基因调控网络。总之,我们为小麦根尖分生组织生成了单细胞和空间转录组学资源,包括许多已知和未表征的细胞类型特异性标记基因和发育调节因子。这些数据和分析将有助于未来对非模式植物物种进行细胞类型注释。