Liao Andrew, Zhang Zehao, Sziraki Andras, Abdulraouf Abdulraouf, Xu Zihan, Lu Ziyu, Zhou Wei, Cao Junyue
Laboratory of Single Cell Genomics and Population Dynamics, The Rockefeller University, New York, NY, USA.
The Tri-Institutional M.D.-Ph.D. Program, New York, NY, USA.
bioRxiv. 2025 May 8:2025.05.02.651937. doi: 10.1101/2025.05.02.651937.
Large-scale single-cell atlas efforts have revealed many aging- or disease-associated cell types, yet these populations are often underrepresented in heterogeneous tissues, limiting detailed molecular and dynamic analyses. To address this, we developed EnrichSci-a highly scalable, microfluidics-free platform that combines Hybridization Chain Reaction RNA FISH with combinatorial indexing to profile single-nucleus transcriptomes of targeted cell types with full gene-body coverage. When applied to profile oligodendrocytes in the aging mouse brain, EnrichSci uncovered aging-associated molecular dynamics across distinct oligodendrocyte subtypes, revealing both shared and subtype-specific gene expression changes. Additionally, we identified aging-associated exon-level signatures that are missed by conventional gene-level analyses, highlighting post-transcriptional regulation as a critical dimension of cell-state dynamics in aging. By coupling transcript-guided enrichment with a scalable sequencing workflow, EnrichSci provides a versatile approach to decode dynamic regulatory landscapes in diverse cell types from complex tissues.
大规模单细胞图谱研究揭示了许多与衰老或疾病相关的细胞类型，但这些细胞群体在异质组织中往往占比不足，限制了详细的分子和动态分析。为了解决这一问题，我们开发了EnrichSci——一个高度可扩展的、无微流控的平台，该平台将杂交链式反应RNA荧光原位杂交与组合索引相结合，以全面覆盖基因全长的方式分析靶向细胞类型的单核转录组。当应用于分析衰老小鼠大脑中的少突胶质细胞时，EnrichSci揭示了不同少突胶质细胞亚型之间与衰老相关的分子动态变化，揭示了共同的和亚型特异性的基因表达变化。此外，我们还发现了传统基因水平分析遗漏的与衰老相关的外显子水平特征，突出了转录后调控是衰老过程中细胞状态动态变化的一个关键维度。通过将转录引导富集与可扩展的测序工作流程相结合，EnrichSci提供了一种通用方法，用于解码复杂组织中不同细胞类型的动态调控图谱。
