Poster Presentation 43rd Lorne Genome Conference 2022

Large field-of-view, high-resolution spatially resolved transcriptomics using DNA nanoball patterned array (#256)

Stephanie Sun 1 , Longqi Liu 2
  1. BGI Australia, Brisbane, QLD, Australia
  2. BGI Research, BGI Shenzhen, Shenzhen, Guangdong, China

High-throughput profiling of in situ gene expression represents a major advance towards the systematic understanding of tissue complexity. Applied with enough capture area and high sample throughput it will help to define the spatio-temporal dynamics of gene expression in tissues and organisms. Yet, current technologies have considerable bottlenecks that limit widespread application. We have combined DNA nanoball (DNB) patterned array chips and in situ RNA capture to develop Stereo-seq (SpaTial Enhanced REsolution Omics-sequencing). This approach allows high sample throughput transcriptomic profiling of histological sections at unprecedented (nanoscale) resolution with areas expandable to centimeter scale, high sensitivity and homogenous capture rate. As proof of principle, we have applied Stereo-seq to study the kinetics and directionality of transcriptional variation in embryogenesis. We used this information to gain insight into the molecular basis of regional specification and cell fate diversification. Our panoramic atlas constitutes an essential resource to investigate longstanding questions concerning normal and abnormal development.

  1. Recent papers for reference: Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays https://www.biorxiv.org/content/10.1101/2021.01.17.427004v3
  2. High-resolution spatiotemporal transcriptomic maps of developing Drosophila embryos and larvae https://www.biorxiv.org/content/10.1101/2021.10.21.465301v1
  3. Spatiotemporal mapping of gene expression landscapes and developmental trajectories during zebrafish embryogenesis https://www.biorxiv.org/content/10.1101/2021.10.21.465298v1
  4. Single-cell Stereo-seq enables cell type-specific spatial transcriptome characterization in Arabidopsis leaves https://www.biorxiv.org/content/10.1101/2021.10.20.465066v1
  5. Spatiotemporal transcriptome at single-cell resolution reveals key radial glial cell population in axolotl telencephalon development and regeneration https://www.biorxiv.org/content/10.1101/2021.10.23.465550v2
  6. Spatially-resolved transcriptomics analyses of invasive fronts in solid tumors https://www.biorxiv.org/content/10.1101/2021.10.21.465135v1