Computational modeling of Gene Expression

        Post-transcriptional regulation is critically important in determining cellular phenotypes and behavior, particularly during early development when the genome is transcriptionally silent. One focus in our lab is to combine novel high-throughput techniques to dissect regulatory elements in the genome,  with computational analysis and modeling to dissect the various regulatory programs that control vertebrate gene expression. 

miRNA ~30%

Y          >60%

       Our most recent work in this area has identified micropeptides (upper panel) and upstream open reading frames (uORFs, lower panel), which are widespread throughout the vertebrate transcriptome. Using ribosome profiling, RNA-seq, and reporter assays, we showed that uORFs are a prevalent regulatory mechanism by which the cell represses the translation of thousands of proteins. We were also able to computationally identify the sequence features most predictive of repression, and show that the activity of uORFs is conserved across species.

Figure: Diagram of translation. Ribosome footprinting allows the isolation of RNA fragments being translated by the ribosome. Lower ribosome profiling plot RPFs and input reads mapped to a composite RefSeq transcript. RPFs mainly map to the CDS with a 3-nucleotide periodicity (blue, pink, green) colored based on the position with respect to the frame of the CDS. Input reads map to both the UTRs and CDS (gray). Combining high resolution ribosome footprinting with computational methods to detect translation has allowed us to identify of translated regions across predicted non-coding regions, including micropeptides, (small ORFs, below) and upstream ORFs (below), as well as quantification of the translation for individual mRNAs across development

     Our ultimate goal is to combine our knowledge of the various regulatory mechanisms in the early embryo, such as miRNAs, uORFs, codon optimality, RNA structure, and the RBP interactome, to form a comprehensive and predictive model of translation regulation.

       Figure: We have developed a method to determine the regulatory activity of RNA fragments in the 3‘UTR and the coding sequences, that we term RASA-seq. (RNA stability assay). This has allowed us to map regulatory sequences across the transcriptome in a quantitative manner.

Position: Computational BiologistComputationalBiology._Postdoctoral_positions_2_3.htmlComputationalBiology._Postdoctoral_positions_2_3.htmlshapeimage_5_link_0