Join us for the first ERGA BioGenome Analyis & Applications Seminar of 2024 featuring a talk by Stein Aerts
Wednesday, January 24th - 11:00 CET
Link to the Livestream:
Modeling and design of cell type specific enhancers using single-cell multi-omics and deep learning
Stein Aerts, Professor at University of Leuven; VIB Scientific Director & Group Leader
Single-cell transcriptomics and single-cell epigenomics allow building cell atlases of any tissue and species, providing new opportunities to predict gene regulatory networks that control the identity of cell types and cell states. I will present new computational strategies that take advantage of the joint analysis of scRNA-seq and scATAC-seq data, and that derive “enhancer-GRNs” (eGRN) with key transcription factors, genomic enhancers, and predicted target genes per cell type. In parallel, we use deep learning on the scATAC-seq topics to prioritize enhancers and decipher their regulatory grammar. I will discuss the results of several case studies where we applied these computational strategies, including the Drosophila brain and the mouse liver, and I will illustrate how evolutionary comparisons contribute to learning the gene regulatory code in the vertebrate brain. Finally, I will discuss how enhancer models based on deep learning can be exploited to design synthetic enhancers for Drosophila and human cell types.