ADAR-editing landscape dysregulation in neuropsychiatric disorders

项目摘要： 作用于RNA(ADAR)编辑的腺苷脱氨酶在形成转录组中起主要作用 通过创造不同的异构体来微调钙介导的兴奋性和其他信号 是大脑发育、神经可塑性和情绪调节所必需的。时空ADAR编辑 景观通过控制ADAR表达水平来严格调控，以保持优先结合和 正在编辑。以前的研究表明，天然免疫系统干扰素途径的激活- 如病毒感染中所见-导致ADAR1p150表达增加，最终导致 对ADAR编辑模式的更改。此外，天然免疫激活的常见副作用是 干扰素治疗包括增加抑郁和自杀的风险。时空的变化 编辑模式的调节可能会导致一系列神经症状，包括神经精神症状 观察到前额叶皮质5-羟色胺受体亚单位2C的ADAR编辑减少 自杀的个人)。然而，我们对ADAR编辑景观的理解仍然粗略。 高通量RNA-SEQ的进展使得能够从测序读数中更准确地调用变异体， 提供了一种在转录组中映射ADAR编辑模式的方法。然而，没有计算性的 专注于ADAR编辑的管道易于使用、可重现并可处理大规模分析。 我最近建立了一个管道来处理结合了不同调用步骤的RNA-SEQ数据的荟萃分析， 但还需要进一步的工作来验证这一工具，以确保结果的准确性和重复性。然后它就可以成为 用于绘制ADAR编辑景观的时空变化图。拟议的项目将研究ADAR 以下列方式编辑景观：(I)新的计算管道将作为基准使用VARIANT 使用模拟读取调用RNA-seq数据集，(Ii)ADAR编辑公开的景观多样性 可用的人体样本将被映射；计算预测和假设产生于 管道将使用以下方法进行验证：(Iii)使用已知的差异ADAR编辑来测量细胞中的钙通量 由PolyI：C(模拟病毒感染)治疗引起的景观。建议的工作将产生一个经过验证的 能够使用机器学习算法映射ADAR编辑景观的管道。定义ADAR 编辑景观对发现生物标记物至关重要，并可能影响精准医学在 神经精神障碍的诊断和治疗。这个项目将使我获得知识 成为一名独立研究人员所必需的基础，拥有独特的计算和 推动神经科学领域发展的钳工方法。

Project Abstract: Adenosine deaminase acting on RNA (ADAR) editing plays a major role in shaping transcriptome diversity by creating variant isoforms that enable fine-tuning of calcium-mediated excitatory and other signaling needed for brain development, neural plasticity and mood regulation. The spatio-temporal ADAR editing landscapes are tightly regulated by controlling ADAR expression levels to preserve preferential binding and editing. Previous studies have shown that activation of the interferon pathways of the innate immune system – such as those seen in viral infections - leads to increased expression of ADAR1p150, which ultimately results in changes to ADAR editing patterns. Furthermore, common side effects to innate immune activation by interferon alpha therapies include increased risk of depression and suicide. The changes in spatio-temporal regulation of editing patterns can lead to a wide spectrum of neurological symptoms, including neuropsychiatric disorders (e.g., decreased ADAR editing in the serotonin receptor subunit2C in the prefrontal cortex observed in individuals who commit suicide). Yet, our understanding of ADAR editing landscapes remain cursory. Advances in high throughput RNA-seq enable more accurate variant calling from the sequencing reads, providing a way to map ADAR editing patterns in the transcriptome. However, there are no computational pipelines focused on ADAR editing that are easy to use, are reproducible and can handle large scale analysis. I have recently built a pipeline to handle meta-analysis of RNA-seq data that incorporates variant calling steps, but further work is needed to validate this tool to assure accuracy and reproducibility of results. It can then be used to map the spatio-temporal variation of ADAR editing landscapes. The proposed project will study ADAR editing landscapes in the following ways: (i) new computational pipelines will be benchmarked to use variant calling with RNA-seq datasets using simulated reads, (ii) ADAR editing landscape diversity in the publicly available human samples will be mapped; the computational predictions and hypotheses generated from the pipeline will be validated using (iii) measuring calcium flux in cells with known differential ADAR editing landscapes caused by PolyI:C (viral infection mimic) treatment. The proposed work will yield a validated pipeline capable of mapping ADAR editing landscapes with machine learning algorithms. Defining ADAR editing landscapes is paramount to biomarker discovery and can influence precision medicine applications in diagnosis and treatment of neuropsychiatric disorders. This project will allow for me to gain the knowledge base necessary to become an independent researcher with a unique skill set of both computational and benchwork methods to advance the field of neuroscience.