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Exploring Biological Systems using Spatial Transcriptomic Technologies

Time: Fri 2022-05-13 10.00

Location: Air Fire, Tomtebodavägen 23A, Solna

Video link: zoom link for online defense

Language: English

Subject area: Biotechnology

Doctoral student: Kim Thrane , Genteknologi, Science for Life Laboratory, SciLifeLab

Opponent: Prof. Ulf Gyllensten, Dept. of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden

Supervisor: Prof. Joakim Lundeberg, Science for Life Laboratory, SciLifeLab, Genteknologi; Assoc. Prof. Patrik Ståhl, Science for Life Laboratory, SciLifeLab, Genteknologi

QC 2022-04-11


The transcriptome and the cells’ spatial organization are important determinants for the functions of biological systems, such as a tumor, brain, or skin tissue. Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for profiling the transcriptome of individual cells. The nuanced characterization of cell types and states enabled by scRNA-seq has revolutionized our understanding of biological systems. However, these methods rely on the dissociation of tissues into single cells whereby spatial context is lost. Recent advancements have resulted in technologies that retain and associate spatial information with the gene expression of tissues, which has permitted the delineation of biological systems at an unprecedented level. The Spatial Transcriptomics (ST) technology offers transcriptome profiling across thousands of subareas of a tissue section by capturing mRNA in situ and sequencing ex situ.

In Paper I, ST was used to explore heterogeneity in lymph node metastases of human cutaneous malignant melanoma. A data-driven analysis approach revealed inter- and intratumor heterogeneity in the examined tumor tissue, whereas the stromal tissue exhibited similar gene expression across patients. Paper II presents an integration of ST, scRNA-seq, and spatial protein analysis to characterize human cutaneous squamous cell carcinoma. The spatial resolution of ST is not at the single-cell level; however, this multimodal approach allowed for the identification of tumor subpopulations and revealed the niches in which they reside. In Paper III, ST and scRNA-seq data were generated to build an atlas of human skin. The combined data was used to map cell-type abundance and intercellular communications in homeostasis. Moreover, cell-of-origin analysis allowed for the identification of candidate cell types accountable for human genetic skin diseases. Paper IV introduces Spatial VDJ, a technique for spatial analysis of B and T cell antigen receptor transcripts, hence determining the position of lymphocyte clones. The spatial VDJ technique was applied to human tonsil and human breast cancer tissues, and this revealed enrichment of immunoglobulin clones in distinct spatial regions. Finally, Paper V explores an alternative protocol for ST that uses long-read sequencing to enable spatial isoform profiling in tissue sections. The protocol was applied to mouse brain and identified genes with spatially distinct alternative isoform expression. Additionally, the full-length transcript information was used to explore RNA editing events across different anatomical regions of the mouse brain.