Unraveling transposable element-mediated regulatory landscape in diverse human immune cells
Du, C.; Fan, H.; Jiang, J.; Yang, J.; Chen, S.; Vorobyeva, N. E.; Zhu, C.; Mao, L.; Li, C.; Li, Y.; Bao, W.; Sun, M.-a.
Show abstract
Transposable elements (TEs) are key contributors to genetic novelty. Despite increasing evidence of their importance, their roles in shaping the regulatory landscape of diverse immune cell populations remain largely unclear. Using single-cell multiome data from human peripheral blood mononuclear cells, we annotated the cell-specific cis-regulatory elements for major immune cell populations and identified a highly cell-specific signature of the overrepresented TE families. Focusing on monocytes that bear fast-evolving transcriptomes, we found that high proportions of their enhancers are TE-derived and bound by multiple pioneer transcription factors. Among them, we confirmed that the core myeloid regulator SPI1 can bind and regulate hundreds of TE-derived enhancers, which further affect the expression of adjacent immune genes. Additionally, interspecies comparison reveals that non-conserved monocyte enhancers are frequently generated by lineage-specific TE insertions, and correlate with the evolved gene expression between human and mouse. Overall, our study supports the importance of TEs in shaping the regulatory landscape of diverse immune cell populations.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Transposable elements strongly contribute to cell-specific and species-specific looping diversity in mammalian genomes. 95%
- Regulation associated modules reflect 3D genome modularity associated with chromatin activity 95%
- Chromatin information content landscapes inform transcription factor and DNA interactions 95%
Similar papers in this journal
"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.