Tracing DNA paths and RNA profiles in cultured cells and tissues with ORCA.
Leslie J MateoNasa Sinnott-ArmstrongAlistair Nicol BoettigerPublished in: Nature protocols (2021)
Chromatin conformation capture (3C) methods and fluorescent in situ hybridization (FISH) microscopy have been used to investigate the spatial organization of the genome. Although powerful, both techniques have limitations. Hi-C is challenging for low cell numbers and requires very deep sequencing to achieve its high resolution. In contrast, FISH can be done on small cell numbers and capture rare cell populations, but typically targets pairs of loci at a lower resolution. Here we detail a protocol for optical reconstruction of chromatin architecture (ORCA), a microscopy approach to trace the 3D DNA path within the nuclei of fixed tissues and cultured cells with a genomic resolution as fine as 2 kb and a throughput of ~10,000 cells per experiment. ORCA can identify structural features with comparable resolution to Hi-C while providing single-cell resolution and multimodal measurements characteristic of microscopy. We describe how to use this DNA labeling in parallel with multiplexed labeling of dozens of RNAs to relate chromatin structure and gene expression in the same cells. Oligopaint probe design, primary probe making, sample collection, cryosectioning and RNA/DNA primary probe hybridization can be completed in 1.5 weeks, while automated RNA/DNA barcode hybridization and RNA/DNA imaging typically takes 2-6 d for data collection and 2-7 d for the automated steps of image analysis.
Keyphrases
- single molecule
- single cell
- gene expression
- high resolution
- living cells
- induced apoptosis
- nucleic acid
- circulating tumor
- cell cycle arrest
- high throughput
- cell free
- high speed
- genome wide
- dna damage
- randomized controlled trial
- machine learning
- quantum dots
- rna seq
- signaling pathway
- magnetic resonance
- transcription factor
- label free
- dna methylation
- magnetic resonance imaging
- air pollution
- computed tomography
- optical coherence tomography
- big data