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Characterization and Optimization of Multiomic Single-Cell Epigenomic Profiling
- Source :
- Genes; Volume 14; Issue 6; Pages: 1245
- Publication Year :
- 2023
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2023.
-
Abstract
- The snATAC + snRNA platform allows epigenomic profiling of open chromatin and gene expression with single-cell resolution. The most critical assay step is to isolate high-quality nuclei to proceed with droplet-base single nuclei isolation and barcoding. With the increasing popularity of multiomic profiling in various fields, there is a need for optimized and reliable nuclei isolation methods, mainly for human tissue samples. Herein we compared different nuclei isolation methods for cell suspensions, such as peripheral blood mononuclear cells (PBMC, n = 18) and a solid tumor type, ovarian cancer (OC, n = 18), derived from debulking surgery. Nuclei morphology and sequencing output parameters were used to evaluate the quality of preparation. Our results show that NP-40 detergent-based nuclei isolation yields better sequencing results than collagenase tissue dissociation for OC, significantly impacting cell type identification and analysis. Given the utility of applying such techniques to frozen samples, we also tested frozen preparation and digestion (n = 6). A paired comparison between frozen and fresh samples validated the quality of both specimens. Finally, we demonstrate the reproducibility of scRNA and snATAC + snRNA platform, by comparing the gene expression profiling of PBMC. Our results highlight how the choice of nuclei isolation methods is critical for obtaining quality data in multiomic assays. It also shows that the measurement of expression between scRNA and snRNA is comparable and effective for cell type identification.
- Subjects :
- single-cell sequencing
epigenomic profiling
snATAC-seq
snRNA-seq
nuclei preparation
Subjects
Details
- Language :
- English
- ISSN :
- 20734425
- Database :
- OpenAIRE
- Journal :
- Genes; Volume 14; Issue 6; Pages: 1245
- Accession number :
- edsair.multidiscipl..2f30d1b434d7a3944ab19bc7f4c4a6f6
- Full Text :
- https://doi.org/10.3390/genes14061245