Thompson Jacqueline R, Nelson Erik D, Tippani Madhavi, Ramnauth Anthony D, Divecha Heena R, Miller Ryan A, Eagles Nicholas J, Pattie Elizabeth A, Kwon Sang Ho, Bach Svitlana V, Kaipa Uma M, Yao Jianing, Hou Christine, Kleinman Joel E, Collado-Torres Leonardo, Han Shizhong, Maynard Kristen R, Hyde Thomas M, Martinowich Keri, Page Stephanie C, Hicks Stephanie C
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
Nat Neurosci. 2025 Jul 30. doi: 10.1038/s41593-025-02022-0.
Cell types in the hippocampus with unique morphology, physiology and connectivity serve specialized functions associated with cognition and mood. These cell types are spatially organized, necessitating molecular profiling strategies that retain cytoarchitectural organization. Here we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from anterior human hippocampus in ten adult neurotypical donors. Using non-negative matrix factorization (NMF) and label transfer, we integrated these data by defining gene expression patterns within the snRNA-seq data and then inferring expression in the SRT data. These patterns captured transcriptional variation across neuronal cell types and indicated spatial organization of excitatory and inhibitory postsynaptic specializations. Leveraging the NMF and label transfer approach with rodent datasets, we identified putative patterns of activity-dependent transcription and circuit connectivity in the human SRT dataset. Finally, we characterized the spatial organization of NMF patterns corresponding to pyramidal neurons and identified regionally-specific snRNA-seq clusters of the retrohippocampus, subiculum and presubiculum. To make this molecular atlas widely accessible, raw and processed data are freely available, including through interactive web applications.
海马体中具有独特形态、生理学和连接性的细胞类型发挥着与认知和情绪相关的特殊功能。这些细胞类型在空间上是有组织的,这就需要保留细胞结构组织的分子分析策略。在这里,我们从十名成年神经典型供体的人前海马体中生成了空间分辨转录组学(SRT)和单核RNA测序(snRNA-seq)数据。使用非负矩阵分解(NMF)和标签转移,我们通过在snRNA-seq数据中定义基因表达模式,然后推断SRT数据中的表达,对这些数据进行了整合。这些模式捕捉了神经元细胞类型之间的转录变化,并表明了兴奋性和抑制性突触后特化的空间组织。利用NMF和标签转移方法以及啮齿动物数据集,我们在人类SRT数据集中确定了与活动依赖性转录和电路连接相关的假定模式。最后,我们对与锥体神经元相对应的NMF模式的空间组织进行了表征,并确定了海马后区、下托和前下托的区域特异性snRNA-seq簇。为了使这个分子图谱广泛可用,原始数据和处理后的数据都是免费提供的,包括通过交互式网络应用程序。