SUPR
Developing new single-cell epigenetic methods
Dnr:

NAISS 2023/22-672

Type:

NAISS Small Compute

Principal Investigator:

Letian Zhang

Affiliation:

Stockholms universitet

Start Date:

2023-06-27

End Date:

2024-07-01

Primary Classification:

30401: Medical Biotechnology (focus on Cell Biology (incl. Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)

Webpage:

Allocation

Abstract

Chromatin immunoprecipitation coupled with sequencing (ChIP-seq) has been instrumental in uncovering the genomic profiles of various histone marks and transcriptional factors. Nevertheless, ChIP-seq struggles with high background, low signal/noise ratio, and high input requirements. Cleavage Under Targets and Tagmentation (CUT&Tag) has recently emerged as an exciting alternative to ChIP-seq. The main advantage of CUT&Tag includes low input requirements, a high signal-to-noise ratio, and the ability to generate sequence-ready libraries in a day. Adaptation of CUT&Tag to the single-cell level has been demonstrated as a powerful method to create cell-type specific epigenetic profiles in heterogeneous tissues (Bartosovic et al., Nature Biotechnology, 2021). We have recently developed a variant of scCUT&Tag called nanobody-based scCUT&Tag (nano-CT), which can simultaneously map three epigenetic modalities, including chromatin accessibility (ATAC-seq), H3K27ac, and H3K27me3 in single cells of the mouse brain (Bartosovic et al., Nature Biotechnology, 2022) The current generation of single-cell methylation profiling is typically based on cytosine conversion by whole genome bisulfite sequencing (WGBS), which involves harsh bisulfite treatment that can lead to DNA degradation and make PCR amplification more challenging. To achieve comprehensive data, sc-WGBS requires a high number of reads, and the associated high costs limit widespread use. To overcome these challenges, developing CUT&Tag-based DNA methylation methods may help address this problem. We will apply the innovative technology to cell lines and compare the DNA methylation landscape to sc-WGBS.