SBIR Abstract Single cell biology is a multi-disciplinary study to investigate how large amount of molecular species interact with each other in single cells and how large population of cells work together as a complex system. Identifying the difference of gene expression and the spatial organization of tissues at the single-cell level is essential to decipher tissue heterogeneity, organ development, and understand the biological systems profoundly, and ultimately benefit precision and personalized medicine. Currently, single cell RNA sequencing is widely used to analyze the gene expression patterns of single cells. However, single cell RNA sequencing has significant limitations, including lack of spatial information, low RNA detection efficiency and low cell capture efficiency. Existing multiplexed in-situ detection technologies like MERFISH and seqFISH can overcome these limitations but has long turnaround time. UltraFISH, developed by Rainbow Diagnostics, significantly improves the turnaround time for a small panel of RNA detection in-situ. High Capacity UltraFISH is to further advance the multiplex capacity of UltraFISH so that a large RNA panel such as the whole human transcriptome from a large region of tissue can be efficiently and quickly profiled in hours. With the successful outcome of this proposal, High Capacity UltraFISH will revolutionize the single cell analysis field, leading to breakthroughs in our understanding of biological and disease mechanisms in the near future.
Project Narrative: High Capacity UltraFISH is a technology that will enable researchers to profile single cell gene expression at the whole transcriptome level in a very fast and accurate way. With the coming of the spatial genomics era, High Capacity UltraFISH will become an essential research tool for a very broad range of biologists and medical scientists in both academia and the biotech industry. It will help answer fundamental questions in all aspects of biology, as well as support the in- depth gene expression profiling of single cells to identify new disease signatures.
