Explore stochasticity in transcription through this 50-minute Medical and Population Genetics Primer lecture from the Broad Institute. Delve into single-cell data analysis of immune cell types in autoimmunity, modeling dynamic regulatory elements, and identifying cell-state-dependent peaks using continuous Poisson GLM frameworks. Examine peak accessibility profiles, genome annotation based on peak sets, and the identification of peak-gene-cell state trios associated with autoimmune diseases. Investigate transcriptional bursting and how transcriptional heterogeneity propagates from transcription factors to target genes. Gain insights into cutting-edge genetics research and its applications in understanding complex traits and diseases.
Stochasticity in Transcription - MPG Primer 2023
Overview
Syllabus
Intro
Single-cell data have identified some immune cell types that are expanded or depleted in autoimmunity
Modeling dynamic regulatory elements to find disease-critical cell states
Identifying cell-state-dependent peaks within each cell type using a continuous Poisson GLM framework
Example peak accessibility profiles reflect the nature of dynamic versus invariant peaks
Annotating the genome based on peak sets of interest
We can identify peak-gene-cell state trios associated with autoimmune diseases
Once we have identified a cell state of interest, how can we systematically learn its active gene regulatory programs?
Stochasticity: transcriptional bursting
Transcriptional heterogeneity is propagated from a TF to its target genes in sequential steps, each of which creates a time delay...
Taught by
Broad Institute
