Mapping gene regulatory networks of primary CD4+ T cells using single-cell genomics and genome engineering
Gate, R. E.; Kim, M. C.; Lu, A.; Lee, D.; Shifrut, E.; Subramaniam, M.; Marson, A.; Ye, C. J.
Show abstract
Gene regulatory programs controlling the activation and polarization of CD4+ T cells are incompletely mapped and the interindividual variability in these programs remain unknown. We sequenced the transcriptomes of ~160k CD4+ T cells from 9 donors following pooled CRISPR perturbation targeting 140 regulators. We identified 134 regulators that affect T cell functionalization, including IRF2 as a positive regulator of Th2 polarization. Leveraging correlation patterns between cells, we mapped 194 pairs of interacting regulators, including known (e.g. BATF and JUN) and novel interactions (e.g. ETS1 and STAT6). Finally, we identified 80 natural genetic variants with effects on gene expression, 48 of which are modified by a perturbation. In CD4+ T cells, CRISPR perturbations can influence in vitro polarization and modify the effects of trans and cis regulatory elements on gene expression.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Impact of disease-associated chromatin accessibility QTLs across immune cell types and contexts 96%
- Gene regulatory network inference from CRISPR perturbations in primary CD4+ T cells elucidates the genomic basis of immune disease 96%
- Functional Inference of Gene Regulation using Single-Cell Multi-Omics 96%
Similar papers in this journal
- Systemic interindividual epigenetic variation in humans is associated with transposable elements and under strong genetic control 96%
- CpG island turnover events predict evolutionary changes in enhancer activity 96%
- Co-opted transposons help perpetuate conserved higher-order chromosomal structures 96%
"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.