Allele-level visualization of transcription and chromatin by high-throughput imaging.
Faisal AlmansourAdib KeikhosraviGianluca PegoraroTom MisteliPublished in: bioRxiv : the preprint server for biology (2024)
The spatial arrangement of the genome within the nucleus is a pivotal aspect of cellular organization and function with implications for gene expression and regulation. While all genome organization features, such as loops, domains, and radial positioning, are non-random, they are characterized by a high degree of single-cell variability. Imaging approaches are ideally suited to visualize, measure, and study single-cell heterogeneity in genome organization. Here, we describe two methods for the detection of DNA and RNA of individual gene alleles by fluorescence in situ hybridization (FISH) in a high-throughput format. We have optimized combined DNA/RNA FISH approaches either using simultaneous or sequential detection. These optimized DNA and RNA FISH protocols, implemented in a 384-well plate format alongside automated image and data analysis, enable accurate detection of chromatin loci and their gene expression status across a large cell population with allele-level resolution. We successfully visualized MYC and EGFR DNA and RNA in multiple cell types, and we determined the radial position of active and inactive MYC and EGFR alleles. These optimized DNA/RNA detection approaches are versatile and sensitive tools for mapping of chromatin features and gene activity at the single-allele level and at high throughput.
Keyphrases
- single cell
- high throughput
- gene expression
- genome wide
- nucleic acid
- single molecule
- rna seq
- circulating tumor
- dna methylation
- transcription factor
- cell free
- high resolution
- loop mediated isothermal amplification
- small cell lung cancer
- real time pcr
- label free
- dna damage
- copy number
- epidermal growth factor receptor
- deep learning
- tyrosine kinase
- cell therapy
- ultrasound guided
- mass spectrometry
- stem cells
- machine learning
- mesenchymal stem cells
- sensitive detection
- high density
- genome wide association study