Seq-Scope Protocol: Repurposing Illumina Sequencing Flow Cells for High-Resolution Spatial Transcriptomics.
Yongsung KimWeiqiu ChengChun-Seok ChoYongha HwangYichen SiAnna ParkMitchell SchrankJer-En HsuJingyue XiMyungjin KimEllen PedersenOlivia I KouesThomas WilsonGoo JunHyun-Min KangJun Hee LeePublished in: bioRxiv : the preprint server for biology (2024)
Spatial transcriptomics (ST) technologies represent a significant advance in gene expression studies, aiming to profile the entire transcriptome from a single histological slide. These techniques are designed to overcome the constraints faced by traditional methods such as immunostaining and RNA in situ hybridization, which are capable of analyzing only a few target genes simultaneously. However, the application of ST in histopathological analysis is also limited by several factors, including low resolution, a limited range of genes, scalability issues, high cost, and the need for sophisticated equipment and complex methodologies. Seq-Scope-a recently developed novel technology-repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, thereby overcoming these limitations. Here we provide a detailed step-by-step protocol to implement Seq-Scope with an Illumina NovaSeq 6000 sequencing flow cell that allows for the profiling of multiple tissue sections in an area of 7 mm × 7 mm or larger. In addition to detailing how to prepare a frozen tissue section for both histological imaging and sequencing library preparation, we provide comprehensive instructions and a streamlined computational pipeline to integrate histological and transcriptomic data for high-resolution spatial analysis. This includes the use of conventional software tools for single cell and spatial analysis, as well as our recently developed segmentation-free method for analyzing spatial data at submicrometer resolution. Given its adaptability across various biological tissues, Seq-Scope establishes itself as an invaluable tool for researchers in molecular biology and histology.
Keyphrases
- single cell
- rna seq
- high resolution
- high throughput
- gene expression
- genome wide
- randomized controlled trial
- dna methylation
- mass spectrometry
- deep learning
- induced apoptosis
- single molecule
- stem cells
- signaling pathway
- cell proliferation
- genome wide identification
- photodynamic therapy
- fluorescence imaging
- endoplasmic reticulum stress
- molecularly imprinted