ABI Innovation: Model-based Alternative Splicing Analysis Across Expression Platforms

爱荷华州州立大学获得一笔赠款，用于研究跨物种和基因表达平台的植物基因的选择性剪接。直到最近，基因编码和解码以构建蛋白质的复杂性一直被大大低估。具体来说，选择性剪接（AS）是通过将基因的不同部分混合和匹配成选择性转录物来将单个基因的DNA解码成不同蛋白质产物的过程。一种理论认为，内含子保留AS允许植物快速适应压力。该项目将利用大量现有的表达数据，以微、外显子和平铺阵列数据集的形式，并将其与大量新的短读段序列数据集相结合，以发现和确认外显子跳跃选择性剪接。 选择性剪接基因的结果将被整合到一个植物系统生物学框架的代谢途径，指定的背景和化学物种之间的相互作用。该项目的目标包括：1）整合和比较不同表达平台的可变剪接模式; 2）开发基于信号处理方法的基于模型的剪接方法; 3）整合可变剪接基因信息与调控网络模型和代谢途径信息。这项工作的关键创新来自于信号处理工程学科的整合，该学科专注于估计信号参数并将信号与噪声分离，以估计RNAseq数据中外显子和内含子表达的关键参数。这项研究将比较高度驯化的植物，玉米（玉米），葡萄（葡萄属葡萄），一个较少驯化的植物，是高度反应的环境影响。了解植物AS之间的相似性和差异对于创造能够科普极端温度，降水和病原体的未来作物可能非常重要。 所有结果都将在PLant和病原体表达数据库网站（PLEXdb.org）上公开，作为基因图谱工具的一部分，允许用户在不同的实验因素中对植物物种进行比较分析。该项目的网站是：www.eng.iastate.edu/~julied/research/AlternativeSplicing。

Iowa State University is awarded a grant to study alternative splicing in plants genes across species and gene expression platforms. Until recently, the complexity with which genes are encoded and decoded to build proteins has been greatly underestimated. Specifically, Alternative Splicing (AS) is the process of decoding a single gene's DNA into different protein products by mixing and matching different sections of the gene into alternative transcripts. One theory is that intron retention AS allows plants to rapidly adapt to stress. This project will exploit the large amount of existing expression data in the form of micro, exon, and tiling array data sets and use it to integrate with the deluge of new short-read sequence datasets to find and confirm exon skipping alternative splicing. The alternative splicing gene results will be integrated into a plant systems biology framework of metabolic pathways which specify context and interactions between chemical species. The aims of the project include: 1) Integration and comparison of alternative splicing patterns across expression platforms; 2) Development of model-based methods of splicing based on signal processing methods; 3) Integrating the alternatively spliced gene information with regulatory network models and metabolic pathway information. Key innovation in this work comes from the integration of the engineering discipline of signal processing which focuses on estimating signal parameters and separating signals from noise to the problem of estimating the key parameters of exon and intron expression in RNAseq data. The research will compare the highly-domesticated plant, maize (Zea mays), to grape (Vitis vinifera), a less domesticated plant that is highly reactive to environmental effects. Understanding the similarities and differences between plant AS may be very important in creating future crops that can cope with extremes of temperature, precipitation, and pathogens. All results will be made publicly available at the PLant and pathogen EXpression database website (PLEXdb.org) as part of the gene atlas tool that allows users to perform comparative analysis between plant species across different experimental factors. The project website is: www.eng.iastate.edu/~julied/research/AlternativeSplicing.