scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells

Abstract

Parallel single-cell sequencing protocols represent powerful methods for investigating regulatory relationships, including epigenome-transcriptome interactions. Here, we report a single-cell method for parallel chromatin accessibility, DNA methylation and transcriptome profiling. scNMT-seq (single-cell nucleosome, methylation and transcription sequencing) uses a GpC methyltransferase to label open chromatin followed by bisulfite and RNA sequencing. We validate scNMT-seq by applying it to differentiating mouse embryonic stem cells, finding links between all three molecular layers and revealing dynamic coupling between epigenomic layers during differentiation.

Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets

“…As multi‐omics approaches are also beginning to emerge in single‐cell biology (Macaulay et al , ; Angermueller et al , ; Guo et al , ; Clark et al , ; Colomé‐Tatché & Theis, ), we investigated the potential of MOFA to disentangle the heterogeneity observed in such studies. We applied MOFA to a data set of 87 mouse embryonic stem cells (mESCs), comprising of 16 cells cultured in “2i” media, which induces a naive pluripotency state, and 71 serum‐grown cells, which commits cells to a primed pluripotency state poised for cellular differentiation (Angermueller et al , ).…”

“…Motivated by this, multi‐omics profiling is increasingly applied across biological domains, including cancer biology (Gerstung et al , ; Iorio et al , ; Mertins et al , ; Cancer Genome Atlas Research Network, ), regulatory genomics (Chen et al , ), microbiology (Kim et al , ) or host‐pathogen biology (Soderholm et al , ). Most recent technological advances have also enabled performing multi‐omics analyses at the single‐cell level (Macaulay et al , ; Angermueller et al , ; Guo et al , ; Clark et al , ; Colomé‐Tatché & Theis, ). A common aim of such applications is to characterize heterogeneity between samples, as manifested in one or several of the data modalities (Ritchie et al , ).…”

Using single‐cell genomics to understand developmental processes and cell fate decisions

“…For example, G&T‐seq (Macaulay et al , ) combines DNA sequencing with RNA‐seq and is adept at identifying how copy‐number changes may impact transcription. M&T‐seq (Angermueller et al , ) captures DNA methylation and transcriptome data, with NMT‐seq (preprint: Clark et al , ) further adding chromatin‐accessibility information using a GpC methyltransferase (Kelly et al , ). While these assays offer unique advantages, they are typically experimentally challenging to run, and handle many fewer cells than scRNA‐seq.…”

“…Another key area where technology is driving biological discovery is the ability to assay multiple molecular layers within the same cell. Recent advances have allowed the epigenome, transcriptome and chromatin accessibility of the same cell to be profiled (preprint: Clark et al , ), therefore allowing insight into the mechanisms driving changes in gene expression. When coupled with information about a cell's location in the embryo (and the associated signalling gradients introduced above), we will begin to move towards a holistic model of cell fate choice and, indeed, of embryogenesis itself.…”

A compendium on single‐cell analysis for the curious

“…Global analysis of RNA expression analysis is the current workhorse for most single-cell studies, serving to efficiently characterize cell identities and states. However, methods to measure DNA copy numbers and sequences, DNA methylation, chromatin accessibility, and repertoires of proteins and metabolites are rapidly developing as important tools for single-cell biology [2][3][4].…”