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Characterization and Optimization of Multiomic Single-Cell Epigenomic Profiling

Authors :
Gaspar-Maia, Leticia Sandoval
Wazim Mohammed Ismail
Amelia Mazzone
Mihai Dumbrava
Jenna Fernandez
Amik Munankarmy
Terra Lasho
Moritz Binder
Vernadette Simon
Kwan Hyun Kim
Nicholas Chia
Jeong-Heon Lee
S. John Weroha
Mrinal Patnaik
Alexandre
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.

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