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Lee, C. N.

Publications and source records attributed to Lee, C. N..

2 recordsLinked to original sources

Spatial joint profiling of DNA methylome and transcriptome in mammalian tissues

The spatial resolution of omics dynamics is fundamental to understanding tissue biology. Spatial profiling of DNA methylation, which is a canonical epigenetic mark extensively implicated in transcriptional regulation, remains an unmet demand. Here, we introduce a method for whole genome spatial co-profiling of DNA methylation and transcriptome of the same tissue section at near single-cell resolution. Applying this technology to mouse embryogenesis and postnatal brain resulted in rich DNA-RNA bimodal tissue maps. These maps revealed the spatial context of known methylation biology and its interplay with gene expression. The two modalities concordance and distinction in spatial patterns highlighted a synergistic molecular definition of cell identity in spatial programming of mammalian development and brain function. By integrating spatial maps of mouse embryos at two different developmental stages, we reconstructed the dynamics of both epigenome and transcriptome underlying mammalian embryogenesis, revealing details in sequence, cell type, and region-specific methylation-mediated transcriptional regulation. This method extends the scope of spatial omics to DNA cytosine methylation for a more comprehensive understanding of tissue biology over development and disease.

genomics↗

Multiplexed spatial mapping of chromatin features, transcriptome, and proteins in tissues

The phenotypic and functional states of a cell are modulated by a complex interactive molecular hierarchy of multiple omics layers, involving the genome, epigenome, transcriptome, proteome, and metabolome. Spatial omics approaches have enabled the capture of information from different molecular layers directly in the tissue context. However, current technologies are limited to map one to two modalities at the same time, providing an incomplete representation of cellular identity. Such data is inadequate to fully understand complex biological systems and their underlying regulatory mechanisms. Here we present spatial-Mux-seq, a multi-modal spatial technology that allows simultaneous profiling of five different modalities, including genome-wide profiles of two histone modifications and open chromatin, whole transcriptome, and a panel of proteins at tissue scale and cellular level in a spatially resolved manner. We applied this technology to generate multi-modal tissue maps in mouse embryos and mouse brains, which discriminated more cell types and states than unimodal data. We investigated the spatiotemporal relationship between histone modifications, chromatin accessibility, gene and protein expression in neuron differentiation revealing the relationship between tissue organization, function, and gene regulatory networks. We were able to identify a radial glia spatial niche and revealed spatially changing gradient of epigenetic signals in this region. Moreover, we revealed previously unappreciated involvement of repressive histone marks in the mouse hippocampus. Collectively, the spatial multi-omics approach heralds a new era for characterizing tissue and cellular heterogeneity that single modality studies alone could not reveal.

genetics↗