Current Students | Krithika Ramasamy-Subramanian
My research is to understand the crosstalk between alternative splicing and circadian rhythm. Alternative splicing is a post-transcriptional regulatory mechanism that offers diversity in proteins produced from a single transcript. This process has been proven to be important, as ~60% of genetic diseases are due to defective splicing. In humans, ~95% of multi-exonic genes undergo alternative splicing, which affects almost all the physiological processes in the system, including circadian rhythm regulation. Circadian rhythm is a 24-hour biological clock present inside all organisms and is used to anticipate environmental changes and adapt accordingly. Earlier it was believed that clock-regulated genes are regulated by transcriptional feedback loops. But recent evidence suggests that there are additional layers (including splicing) of regulation in maintaining circadian rhythm.
My research involves extensive data analysis of NGS using programming in Python and R and several bioinformatics tools to identify the important splicing events in the existing circadian datasets. Identifying these crucial events computationally and validating them in mouse intestinal enteroids improves our understanding about circadian splicing. These splicing events are not only rhythmically regulated in multiple mammalian tissues; they are closely associated with cancer pathways.
Future directions include comparing the differences in splicing between specific cancer datasets to circadian datasets for potential regulatory mechanisms. This will help us identify potential chronotherapeutic targets for treating cancer and other disorders. I am also interested in applying machine learning methods on single-cell seq data to understand the developmental aspects of stem cells and other progenitors. If feasible I would like to understand the clock function at the single-cell level.