ABI Innovation: Creating Complete and Accurate Alternative Splicing Repertoires from RNA-seq Data

该项目旨在生产一套生物信息学工具，以准确和全面地识别可选择的剪接变异，并通过网络可访问的数据库将这些信息呈现给研究人员。选择性剪接是真核生物基因的固有特性。一个基因可以通过多种方式拼接产生不同的变体，这取决于组织、发育阶段或疾病与正常状况，每种变体都有不同的功能。因此，创建一个基因的可变剪接变异库对于理解一个物种的生物学是至关重要的。最近，快速和低成本的下一代测序使得探索各种物种的基因库及其剪接变化成为可能。然而，将短测序读数解释为基因和备选剪接注释存在重大挑战，现有工具并不总是能够高精度地重建备选剪接模式。首先，该项目寻求生产一种生物信息学工具，以比以前更详细、更准确地从测序读数中识别可选择的剪接变化。其次，利用不断增长的数据量，将这些方法应用于建立几个植物物种的备选剪接事件的综合目录。该项目将生产可供生物学家用于研究和教育的开源软件，并将通过夏季实习为本科生和高中生创造研究机会，为招收来自不同背景的学生进入跨学科科学做出更大的贡献。选择性剪接（AS）是一种广泛存在的机制，在基因和功能多样性的形成中起着重要作用。下一代细胞RNA测序（RNA-seq）使探索细胞类型或物种中的剪接变体库成为可能。然而，目前的生物信息学工具在详细捕获AS变化方面存在困难，并且在典型实验中不能随着样本数量的增加而扩大。为了满足这些需求，第一个目标是开发一种首创的下一代工具，用于同时从大量样本中从短rna序列读取重建基因和剪接变体。它将比目前的程序更全面、更准确地捕获AS变化，包括精细变化和难以检测的变化类型。该方法将线性规划技术与RNA-seq“噪声”统计模型以及基因的可扩展剪接图表示相结合，并利用相关样本表达谱之间的相似性来提高效率。第二个目标是在剪接图模型作为基因的紧凑表示的基础上，利用基于网络的可视化和分析能力，生成植物物种中AS事件的第一个综合目录。所有软件都将是开源的，所有人都可以无限制地使用，用于研究和教育。此外，该项目还将通过暑期实习，为培训和招募下一代科学家创造新的教材和机会，特别是在代表性不足的群体和巴尔的摩市中心的高中生中。所有的软件、教材和数据库都可以从http://ccb.jhu.edu/people/florea/research/访问。

The project aims to produce a suite of bioinformatics tools to accurately and comprehensively identify alternative splicing variation and present this information to researchers through a web accessible database. Alternative splicing is an intrinsic property of eukaryotic genes. A gene can be spliced in multiple ways to produce different variants depending on the tissue, developmental stage, or disease versus normal condition, with each variant having a distinct function. Creating a repertoire of alternative splicing variations of genes is therefore critical for understanding the biology of a species. Recently, fast and cost-effective next generation sequencing has made it possible to explore the repertoire of genes and their splicing variations in a wide variety of species. However, interpreting the short sequencing reads into gene and alternative splicing annotations has significant challenges, and existing tools cannot always reconstruct alternative splicing patterns with high accuracy. The project seeks to produce, first, a bioinformatics tool to identify alternative splicing variations from sequencing reads in more detail and more accurately than previously possible. Secondly, the methods will be applied to build a comprehensive catalog of alternative splicing events in several plant species, taking advantage of the growing amounts of data being generated. The project will produce open source software that can be used by biologists for both research and education, and will contribute to the larger effort to recruit students from diverse backgrounds into interdisciplinary science, by creating research opportunities for undergraduate and high-school students through summer internships.Alternative splicing (AS) is a widespread mechanism with an important role in creating gene and functional diversity. Next generation sequencing of cellular RNA (RNA-seq) has made it possible to explore the repertoire of splice variants in a cell type or species. However, current bioinformatics tools have difficulty in capturing AS variation in detail, and have not scaled up with the increasing number of samples in a typical experiment. To answer these needs, the first aim is to develop a first-of-its-kind next-generation tool for reconstructing gene and splice variants from short RNA-seq reads, simultaneously from large numbers of samples. It will capture AS variation both more fully and more accurately than current programs, including fine variations and hard-to-detect types of variations. The approach is to combine linear programming techniques, with statistical models of RNA-seq "noise", and with scalable splice graph representations of genes, and exploits similarity between expression profiles of related samples to increase efficiency. The second aim is to produce the first comprehensive catalog of AS events in plant species, with web-based visualizations and analysis capabilities, building on the splice graph model as a compact representation of genes. All software will be open source and available without restrictions for all, for research and education. Additionally, the project will create new teaching materials and opportunities for training and recruiting the next generation of scientists, in particular from among under-represented groups and Baltimore inner-city high-schools students, through Summer internships. All software, teaching materials, and the database will be accessible from http://ccb.jhu.edu/people/florea/research/ .