Goal: Our research focuses on developing and using single-cell genomics to discover regulatory logic and mechanisms of gene expression. Single-cell transcriptomics enable transcriptional processes to be studied transcriptome-wide and with allelic resolution, providing a rich output for functional studies of transcription factors and co-factors regulating transcription. The full-length coverage in Smart-seq methods enables analyses of splicing regulation, including cell-type, clonal and connectivity patterns.

Technology: Towards this goal, we have recently developed Smart-seq3xpress that provides sensitive profiling of RNAs in cells and importantly RNA reconstruction strategy that can directly link counted RNAs to allelic origin and transcript isoforms. Additionally, using 4sU labeling of newly transcribed RNA (e.g. NASC-seq) we can monitor transcriptional dynamics at precise temporal resolution. We are increasingly developing computataional tools to more accurately capture splicing regultion from single-cell genomics data, and to use AI to model how DNA/RNA binding factors control transcriptional and post-transcriptinoal regulation.

Biology: Using these methods, we have for example demonstrated that most mammalian genes are expressed in bursts, where, as a first approximation, enhancer activities control burst frequencies and core promoter elements control burst sizes (Larsson et al. Nature 2019), and using 4sU-labeling we can decipher additional transcriptional bursting parameters to shed better light on how long each burst is, how a burst size is controlled and the general extent of co-bursting of nearby genes (Ramskold, Hendriks, Larsson et al. provisionally accepted).


If you are insterested in using technology (experimental and computational) to decipher layers of gene regulation, join our efforts!

Interested students or postdoc candidates, please email me at rickard dot sandberg at ki.se