NLM DIR Seminar Schedule
UPCOMING SEMINARS
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April 8, 2025 Jaya Srivastava
Leveraging a deep learning model to assess the impact of regulatory variants on traits and diseases -
April 15, 2025 Pascal Mutz
TBD -
April 18, 2025 Valentina Boeva, Department of Computer Science, ETH Zurich
Decoding tumor heterogeneity: computational methods for scRNA-seq and spatial omics -
April 22, 2025 Stanley Liang
TBD -
April 29, 2025 MG Hirsch
TBD
RECENT SEMINARS
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April 1, 2025 Roman Kogay
Horizontal transfer of bacterial operons into eukaryote genomes -
March 25, 2025 Yifan Yang
Adversarial Manipulation and Data Memorization in Large Language Models for Medicine -
March 11, 2025 Sofya Garushyants
Tmn – bacterial anti-phage defense system -
March 4, 2025 Sanasar Babajanyan
Evolution of antivirus defense in prokaryotes depending on the environmental virus load -
Feb. 25, 2025 Zhizheng Wang
GeneAgent: Self-verification Language Agent for Gene Set Analysis using Domain Databases
Scheduled Seminars on Dec. 20, 2022
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
Enhancers and promoters are classically considered to be bound by a small set of TFs in a sequence-specific manner. This assumption has come under increasing skepticism as the datasets of ChIP-seq assays of TFs have expanded. In particular, high-occupancy target (HOT) loci attract dozens and hundreds of TFs with seemingly no detectable correlation between TF ChIP-seq peaks and the presence of the DNA-binding motifs. In this study, we used a set of 1,003 TF ChIP-seq datasets in HepG2, K562, and H1 cells to analyze the patterns of ChIP-seq peak co-occurrence in combination with functional genomics datasets. We established that the HOT loci form at the promoter and enhancer regions, and the density of mapped TF ChIP-seq peaks across TF-bound loci correlates with sequence features and the expression level of flanking genes. HOT loci evolve under the extremes of strong negative sequence conservation and are 50 times more conserved than the coding DNA. They form the foundation of human super-enhancers. Sequence-based accurate classification of HOT loci using deep learning suggested that their formation is driven by the sequence features. We observed that HOT loci are enriched in 3D chromatin hubs and disease-causal variants. We report an abundance of HOT loci in the human genome thus challenging the classical model of enhancer activity and propose a model of HOT locus formation based on the existence of large transcriptional condensates.