Massively parallel single-cell profiling of transcriptome and multiple epigenetic proteins in cell fate regulation
Xiong, H.; Wang, Q.; Li, C. C.; He, A.
Show abstract
Sculpting the epigenome with a combination of histone modifications and transcription factor (TF) occupancy determines gene transcription and cell fate specification. Here we first develop uCoTarget, utilizing a split-pool barcoding strategy for realizing ultra-high throughput single-cell joint profiling of multiple epigenetic proteins. Through extensive optimization for sensitivity and multimodality resolution, we demonstrate that uCoTarget enables simultaneous detection of five histone modifications (H3K27ac, H3K4me3, H3K4me1, H3K36me3 and H3K27me3) in 19,860 single cells. We applied uCoTarget to the in vitro generation of hematopoietic stem/progenitor cells (HSPCs) from human embryonic stem cells, presenting multimodal epigenomic profiles in 26,418 single cells. uCoTarget with high sensitivity per modality reveals establishment of pairing of HSPC enhancers (H3K27ac) and promoters (H3K4me3) along the differentiation trajectory and RUNX1 engagement priming for the H3K27ac activation along the HSPC path. We then develop uCoTargetX, an expansion of uCoTarget to simultaneously measure transcriptome and multiple epigenome targets. Together, our methods enable generalizable, versatile multi-modal profiles for reconstructing comprehensive epigenome and transcriptome landscapes and analyzing the regulatory interplay at single-cell level.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- ISSAAC-seq enables sensitive and flexible multimodal profiling of chromatin accessibility and gene expression in single cells 98%
- Single-cell joint detection of chromatin occupancy and transcriptome enables higher-dimensional epigenomic reconstructions 97%
- Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq 96%
Similar papers in this journal
- Polygenic regression uncovers trait-relevant cellular contexts through pathway activation transformation of single-cell RNA sequencing data 96%
- Atlas-scale Single-cell DNA Methylation Profiling with sciMETv3 96%
- Normal and cancer tissues are accurately characterised by intergenic transcription at RNA polymerase 2 binding sites 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.