Clonal analysis at single cell level helps to understand positional codes during development
- Date: May 7, 2024
- Time: 11:00 AM - 12:00 PM (Local Time Germany)
- Speaker: Igor Adameyko
- Medical University of Vienna
- Location: MPI BI Martinsried
- Room: MPIBI, Seminar room NQ 105
- Host: Christian Mayer
- Contact: christian.mayer@bi.mpg.de
Development is a dynamic process, with cells continuously changing their
gene expression as they proliferate, differentiate, and migrate. Single-cell
transcriptomics allows for the capture of these dynamic changes in gene
expression over time, providing insights into the temporal regulation of
developmental processes and the mechanisms by which cells transition from one
state to another. The current state of single cell technology enables
reconstructing the transcriptional portraits of developing systems, including
trajectories and fate bifurcations. However, this approach is largely plagued
by our inability to discern convergent transcriptional states that belong to
different genealogical origins. In my talk, I will outline our unique machine
learning approach to clonal barcoding for eliminating this convergence
challenge and for revealing sub-trajectories with common or divergent
clonal behavior. Surprisingly, it resulted in a novel way for discovering
positional information guiding location-specific development and multipotency.