Module 07 - An introduction to spatial transcriptomics approaches
Mariana Boroni
How to use the power of RNA-sequencing while preserving the spatial information?
Image credits: Bo Xia �https://twitter.com/BoXia7
Growth of the current era
Overview of spatial transcriptomics
Spatial transcriptomics methods
pixel-Seq
GeoMx
Visium
MerFish
https://www.sciencedirect.com/science/article/pii/S2001037022003786
Spatial transcriptomics methods
https://www.sciencedirect.com/science/article/pii/S2001037022003786
Spatial transcriptomics methods produce data at different spatial resolutions
https://www.sciencedirect.com/science/article/pii/S2001037022003786
Overview of spatial transcriptomics preprocessing and downstream analysis steps
Figure from poster ‘Anatomical and Transcriptional Characterization of Breast Tumor Heterogeneity
Using Spatial RNA Sequencing’, Ziraldo et al., 2020. 10X Genomics Inc.
Spatial gene expression workflow
© 2020 10x Genomics, Inc.
LIT000060 Rev C Inside Visium Spatial Technology Brochure
Stepwise library construction
Visium Spatial Gene Expression significantly increases spatial resolution and sensitivity
Figure from poster ‘Anatomical and Transcriptional Characterization of Breast Tumor Heterogeneity
Using Spatial RNA Sequencing’, Ziraldo et al., 2020. 10X Genomics Inc.
Visium Spatial Gene Expression
Increases spatial resolution and sensitivity
Figure from poster ‘Anatomical and Transcriptional Characterization of Breast Tumor Heterogeneity
Using Spatial RNA Sequencing’, Ziraldo et al., 2020. 10X Genomics Inc.
Bioinformatic Analysis
https://www.nature.com/articles/s41596-018-0045-2
Single-cell RNA-Seq analysis
Heumos, L., Schaar, A.C., Lance, C. et al. Best practices for single-cell analysis across modalities. Nat Rev Genet 24, 550–572 (2023). https://doi.org/10.1038/s41576-023-00586-w
Single-cell RNA-Seq analysis
Heumos, L., Schaar, A.C., Lance, C. et al. Best practices for single-cell analysis across modalities. Nat Rev Genet 24, 550–572 (2023). https://doi.org/10.1038/s41576-023-00586-w
Figure: Patrik L. Ståhl et al. Science 2016;353:78-82
Principal component analysis of tissue domains
Figure: Patrik L. Ståhl et al. Science 2016;353:78-82
Aligned the tissue image with the features of the array
Overview of spatial transcriptomics preprocessing and downstream analysis steps
Deconvolution methods – unmixing the smoothie
How many strawberries, kiwis, pineapples and oranges went into the salad?
Deconvolution of BULK RNA-Seq
Finotello, F., Trajanoski, Z. Quantifying tumor-infiltrating immune cells from transcriptomics data. Cancer Immunol Immunother 67, 1031–1040 (2018). https://doi.org/10.1007/s00262-018-2150-z
Deconvolution approach with CIBERSORT
Deconvolution approach with CIBERSORT
Approach : deconvolution of bulk RNA-Seq
Sturm, G. et al. Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology, Bioinformatics, Volume 35, Issue 14, July 2019, Pages i436–i445, https://doi.org/10.1093/bioinformatics/btz363