Alternative splicing in single cells

Alternative pre-mRNA splicing is a tightly regulated post-transcriptional process that amplifies the coding potential of the genome by co-expressing multiple RNA variants from the same gene. Its investigation at the level of single cells have been challenging thus far due to the limitations of single-cell sequencing technology and current alternative splicing tools have inaccurately reported that most multi-exonic genes tend to express a single isoform at a time. We aim to develop new computational tools using novel statistical approaches to accurately quantify levels of exon splicing and implement it to study changes in alternative splicing during neuronal development.

Splicing regulation using network theory

The outcome of alternative splicing is tightly regulated by the activity of RNA-binding protein modules that bind onto regions close to an alternative exon. These regulators of splicing may exert opposing effects on splicing decisions and some of these proteins play different functions depending on its binding position. We aim to elucidate the underlying regulation that governs alternative splicing decisions by developing a suite of bioinformatics tools that constructs a regulatory network of RNA-binding proteins and its influence on the splicing of alternative exons.

Heterogeneity of nonsense-mediated decay (NMD) activity

NMD is a highly conserved quality control mechanism that enforces the accuracy of gene expression by clearing transcripts harboring premature termination codons. The success of many biotechnology and biomedical applications such as CRISPR-Cas9 gene knockout systems and cancer immunotherapies rely on optimal NMD activity. The efficacy of NMD is highly variable between biological systems and between individual cells but little is known about the underlying mechanism that influences this decay pathway. We aim to achieve broader understanding of the predictors of NMD activity using advanced statistical and machine learning models.