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 April 16, 2024
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
Evolutionary turnover in the cis-regulatory elements (CREs) of the human genome accounts for more than 90% of the phenotypic and disease associated traits. Some CREs undergo higher rates of substitution and if mutated, may be more likely to result in phenotypic changes. Genomic substrates of novel enhancer activity can be repurposed CREs, transposable elements, or neutral sequences leading to de-novo emergence. We used a deep learning model that’s capable of correlating nucleotide changes to differential enhancer activity and found that a large majority of CREs between humans and our next closest relatives, chimpanzees, have evolved by repurposing regulatory activity from other cell types. Our results highlight a set of predisposed elements that are more suited to regulatory innovation due to their sequence composition of transcription factor binding sites (TFBSs). TFBS enrichment analysis suggests that the repurposed elements do not conform to specific transcription programs. I will discuss results of our analysis that leads us to hypothesize that the repurposed CREs may act as redundant enhancers, are inefficiently integrated into the transcriptional circuitry, and buffer the impact of unfavorable mutations to confer regulatory robustness.