Project name: Integrative dissection of gene regulatory elements at base resolution [ChIP-seq]

Description: Although vast numbers of putative gene regulatory elements have been cataloged, the sequence motifs and individual bases that underlie their functions remain largely unknown. Here we combine deep learning, epigenetic perturbations and base editing to dissect regulatory sequences within the exemplar immune locus encoding CD69. Focusing on a differentially accessible and acetylated upstream enhancer, we find that the complementary strategies converge on a ~150 base interval as critical for CD69 induction in stimulated Jurkat T cells. We pinpoint individual cytosine to thymine base edits that markedly reduce element accessibility and acetylation, with corresponding reduction of CD69 expression. The most potent base edits may be explained by their effect on binding competition between the transcriptional activator GATA3 and the repressor BHLHE40. Systematic analysis of GATA3 and BHLHE40 binding suggests that interplay between these factors plays a general role in rapid T cell transcriptional responses. Our study provides a framework for parsing gene regulatory elements in their endogenous chromatin contexts and identifying operative engineered variants.Overall design: ChIP-seq (GATA3, TAL1, BHLHE40, and H3K27ac) was performed on base edited (sg70_P260) and wild-type (sgCtrl_P258) Jurkat T lymphocytes in the resting and stimulated (PMA/ionomycin) states. ChIP-seq (BHLHE40, H3K27ac, H3K27me3) was additionally performed in BHLHE40 over-expressing (BHLHE40-OE) or BHLHE40-ctrl(Ctrl-LV) in WT Jurkats. This dataset includes the ChIP-seq data.

Data type: Epigenomics

Sample scope: Multiisolate

Relevance: Medical

Last updated: 2022-06-17