High throughput functional genomic technologies in biomedical research

After a short introduction into single cell sequencing technologies and current problems and approaches to single cell transcriptomic data analysis, we got to actively us the software Rstudio during a live guided single cell data analysis session hosted by Michael Vanlandewijck. In an attempt to answer some of the aforementioned questions and apply the knowledge we have gained thus far; we individually ran an analysis based on a raw dataset using Rstudio. Firstly, a dimensionality reduction of the large sample dataset using Uniform Manifold Approximation and Projection (UMAP) was performed. Consequently, clusters that express heterogeneity within the dataset using volcano plots and heatmaps were identified to give valuable insights into differential expression patterns within the example data set.  

To round up our seminar day, we were given a last lecture by Lars Muhl, who presented some of his ongoing research using single cell sequencing analysis for the molecular characterization of vascular and perivascular cells. Two of his projects were presented in more detail, which provided great insights into the research applications of high throughput single cell sequencing technologies to identify smooth muscle cell (SMC) subtypes and differentiate defining genes in fibroblast (FB) subtypes. As such, recent work of his group showed how the bioinformatic application of specific geoterms, i.e. extracellular matrix genes can give an indication about the origin of organotypic FB heterogeneity. Likewise, their latest work about differential expression of SMC explained the use of the learned technologies to identify crucial transcription factor pathways for SMC subtypes, as well as targeted drug discovery applications when looking for organotypic receptor expression patterns. 

All in all, the seminar familiarized us with single cell high throughput technologies to efficiently identify organotypic gene expression patterns and molecular changes along anatomical zones. Here, we were shown that even a small set of cells can give valuable and novel information about differentiated cellular subtype gene expressions, assuming that the appropriate bioinformatic tools are used. Collectively, the techniques and results we were familiarized with throughout the entire seminar displays promising targets for future research in the context of disease progression and initiation, to develop novel and/or redefine existing treatment options. Thank you, Michael and Lars, for the exciting lectures and the interactive sessions! 

The seminar was a part of the KI DevReg Doctoral Programme Course 2537, which also included an open seminar day.

Text written by guest student Carlotta Strelow.