(Mathematical modeling of mRNA m6A dynamics)Epitranscriptomics refers to modifications to RNA molecules, particularly mRNA, that influence gene expression at the post-transcriptional level. N6-methyladenosine (m6A) is the most prevalent internal modification in eukaryotic messenger RNA (mRNA) and regulates critical RNA activities including stability and translation. In cancer, it has become increasingly evident that m6A modifications significantly influence tumorigenesis, progression and metastasis by altering the expression of oncogenes and tumor suppressor genes. However, the exact mechanisms of m6A dynamic regulation are not fully understood. In this project we will develop mathematical models aimed at describing/exploring m6A dynamics and elucidating its role in cancer progression, using mechanistic biological principles as well as published data. Understanding the dynamics and role of m6A modifications in cancer will ultimately open new avenues for developing therapeutic targets and biomarkers for prognosis prediction.

Cell fate determination is influenced by a variety of genetic and epigenetic factors, metabolism, and protein reactions at both the species and individual cell level. Development within a particular species and cell type has been shown to be determined by oscillations observed in the expression of keydevelopmental genes, with time scale of these processes also taking place at species-specific and cell-autonomous level. Individual genetic and epigenetic changes, circadian rhythmicity has been shown to persist at individual cell level in-vitro, with coupling of circadian clock and cell cycle resulting in timed mitosis, rhythmic DNA replication, and circadian and cell-cycle controlled transcription. The transcription-translation clock-controlled feedback loop drives expression of clock genes with a period of ~24hrs. These clock-controlled genes have been shown to comprise from 10-50% of a tissue’s transcriptome, varying in a tissue and cell-type dependent manner. Increasing evidence suggests the cell cycle, metabolic signaling, and circadian oscillators behave as a system of coupled oscillators. This synchronization challenges regulatory network inference, as correlated transcriptional changes can confound causal gene regulation with effect on cell cycle and circadian rhythm. This project’s goal is to determine how changes in dynamics of regulatory components, along regulatory networks are responsible for the regulation of the circadian, cell cycle, and metabolic oscillators; and to elucidate how these changes can lead to both cell fate decisions and disease development, e.g. cancer development. Determining components of the regulatory networks responsible for dysregulating synchronization of cells would be necessary. We will accomplish this by leveraging single cell-RNA Seq and spatial transcriptomic data available from a variety of developmental and cancer datasets to identify molecular components responsible for cell-fate determination with the goal of identifying how particular gene expression dynamics responsible for cell-fate determination are driven by cell cycle, circadian, metabolic oscillators. We will help identify these datasets, learn to process them to infer cyclic processes, and derive regulatory networks. We hypothesize that disease states will be characterized by a lack of synchronization and loss of direct regulation amongst cell-cycle, circadian, and metabolic oscillators and will be associated with a context-dependent regulatory network.