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Browsing by Subject "Intron retention"
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Item Bioinformatics detection of modulators controlling splicing factor‐dependent intron retention in the human brain(Wiley, 2022) Chen, Steven X.; Simpson, Ed; Reiter, Jill L.; Liu, Yunlong; Medical and Molecular Genetics, School of MedicineAlternative RNA splicing is an important means of genetic control and transcriptome diversity. However, when alternative splicing events are studied independently, coordinated splicing modulated by common factors is often not recognized. As a result, the molecular mechanisms of how splicing regulators promote or repress splice site recognition in a context‐dependent manner are not well understood. The functional coupling between multiple gene regulatory layers suggests that splicing is modulated by additional genetic or epigenetic components. Here, we developed a bioinformatics approach to identify causal modulators of splicing activity based on the variation of gene expression in large RNA sequencing datasets. We applied this approach in a neurological context with hundreds of dorsolateral prefrontal cortex samples. Our model is strengthened with the incorporation of genetic variants to impute gene expression in a Mendelian randomization‐based approach. We identified novel modulators of the splicing factor SRSF1, including UIMC1 and the long noncoding RNA CBR3‐AS1, that function over dozens of SRSF1 intron retention splicing targets. This strategy can be widely used to identify modulators of RNA‐binding proteins involved in tissue‐specific alternative splicing.Item Intron Retention Induced Neoantigen as Biomarkers in Diseases(2022-08) Dong, Chuanpeng; Yan, Jingwen; Liu, Yunlong; Huang, Kun; Wan, Jun; Liu, XiaowenAlternative splicing is a regulatory mechanism that generates multiple mRNA transcripts from a single gene, allowing significant expansion in proteome diversity. Disruption of splicing mechanisms has a large impact on the transcriptome and is a significant driver of complex diseases by producing condition-specific transcripts. Recent studies have reported that mis-spliced RNA transcripts can be another major source of neoantigens directly associated with immune responses. Particularly, aberrant peptides derived from unspliced introns can be presented by the major histocompatibility complex (MHC) class I molecules on the cell surface and elicit immunogenicity. In this dissertation, we first developed an integrated computational pipeline for identifying IR-induced neoantigens (IR-neoAg) from RNA sequencing (RNA-Seq) data. Our workflow also included a random forest classifier for prioritizing the neoepitopes with the highest likelihood to induce a T cell response. Second, we analyzed IR neoantigen using RNA-Seq data for multiple myeloma patients from the MMRF study. Our results suggested that the IR-neoAg load could serve as a prognosis biomarker, and immunosuppression in the myeloma microenvironment might offset the increasing neoantigen load effect. Thirdly, we demonstrated that high IR-neoAg predicts better overall survival in TCGA pancreatic cancer patients. Moreover, our results indicated the IR-neoAg load might be useful in identifying pancreatic cancer patients who might benefit from immune checkpoint blockade (ICB) therapy. Finally, we explored the association of IR-induced neo-peptides with neurodegeneration disease pathology and susceptibility. In conclusion, we presented a state-of-art computational solution for identifying IR-neoAgs, which might aid neoantigen-based vaccine development and the prediction of patient immunotherapy responses. Our studies provide remarkable insights into the roles of alternative splicing in complex diseases by directly mediating immune responses.