AI/ML Ready appraoches for integrative RNA processing, splicing and spatial genomics

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Project Summary/Abstract From parent grant: Cells and organisms, from simple to complex, carry the same genetic DNA sequence organized into genes. Multicellular eukaryotes transcribe and process genes into RNA isoforms through a process called alternative splicing. Alternative splicing is developmentally, and cell-type specifically regulated. It is foundational to how higher organisms’ genomes are decoded. Yet, critical, and fundamental questions regarding its regulation and the function of its output remain unanswered. For example, circRNA being a ubiquitous product of alternative splicing was only discovered in 2012, and its regulation and function remains enigmatic. circRNAs’ discovery revealed a larger critical knowledge gap in the field for “what, how and why” genes are alternatively spliced. What RNA splice variants are expressed, how splicing is regulated, and which spliced RNAs have essential functions? Answering these questions is critical for predicting which of myriad genetic variants cause disease and why they do so. Answers will also enable a new generation of digital nucleic acid biomarkers and diagnostics for disease, drug targets for correcting dysregulated splicing and identification of pathogenic protein- or non-coding products (respectively) as well as fundamental basic scientific insight into evolution and function of eukaryotic genomes.. Despite the great promise for discovering how splicing is regulated in massive single cell RNAseq experiments, the field is still lacking unbiased precise methods to address statistical and computational challenges of splicing analysis in scRNA-Seq. State-of-the-art, reproducible, statistical algorithms to achieve precise splice variant calls, detecting how they are regulated in cell types and subcellularly lag far behind the rate at which single cell RNA- seq (scRNA-seq) data is generated, limiting ML/AI readiness. Here, we will open the possibility of analyzing novel RNA regulatory biology through ML/AI-ready software and processed data to a huge community of biomedical researchers enabling new basic and translational discoveries.