Exploring Cell Diversity in Complex Tissues through Spatial Genomics and Spatial Transcriptomics

Citation

Yang, Yujing (2025) Exploring Cell Diversity in Complex Tissues through Spatial Genomics and Spatial Transcriptomics. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/r85x-qs80. https://resolver.caltech.edu/CaltechTHESIS:05302025-191432965

Abstract

The study of cellular diversity is a fundamental requirement for understanding how multicellular organisms function. During the development of multicellular organisms, cells differentiate into various cell types with different molecular compositions, exhibit different phenotypes, and show distinct morphologies. Each single cell occupies a specific spatial location within different tissues and organs and performs a unique function. A holistic understanding of cells requires the integration of multiple “omics” modalities, including genomics, epigenomics, transcriptomics, and proteomics. Current well-established single-cell sequencing methods have been used to build enormous single-cell transcriptomic atlases. While single-cell sequencing methods are now capable of multi-omic profiling, they all require cell dissociation, during which important spatial context information is lost. To study cellular diversity within its native spatial context, our lab has developed innovative spatial genomics and transcriptomics tools that enable multi-omics profiling at single-cell resolution while preserving intact tissue organization. This thesis presents two projects that leverage these tools to investigate cellular diversity in complex tissues across different biological scales, from subnuclear to tissue-level organization. In Chapter 2, we applied spatial multi-omics to the mouse cerebellum, achieving single-cell resolution profiling of 100,049 genomic loci, 17,856 nascent transcripts, 60 mature mRNAs, and 28 immunofluorescently labeled subnuclear structures. To achieve this, we developed innovative two-layer barcodes for DNA sequential fluorescence in situ hybridization (seqFISH). Combining cell-type information from nascent and mature transcriptomes, we captured the three-dimensional genomic architecture and its interactions with subnuclear compartments in a cell-type-specific manner. Our findings show that repressive chromatin compartments have greater cell-type specificity than active chromatin compartments in the mouse cerebellum. In Chapter 3, we integrated single-cell multiome sequencing, which profiles single-nucleus RNA and chromatin accessibility (ATAC) from the same cells, with seqFISH spatial transcriptomics. This approach was applied to the 17- to 18-week-old human fetal kidney, targeting 224 marker genes. By combining sequencing and spatial profiling data, we constructed a comprehensive developmental atlas of human kidney organogenesis, providing new insights into the tissue organization and gene expression patterns during kidney development.

Thesis Files