Building Better Genome Assemblies and Gene Models with RNA-Seq Data

该项目将产生新的和关键的生物信息学算法和工具，以改善基因组组装和注释。这些工具将免费发布，没有限制，以帮助生物学家为他们感兴趣的物种创建更好的参考基因组和基因注释。 当这些工具被整合到一个教学模块中时，还将用于加强学生的研究和教育。在外联和培训方面，该项目将与约翰霍普金斯大学青年人才中心合作，为学生，特别是来自代表性不足群体和巴尔的摩市中心高中的学生创造暑期研究实习机会，从而有助于更大程度地努力招募来自不同背景的学生从事跨学科科学工作。该项目的软件、文档、教学模块和分析数据将可从http://ccb.jhu.edu/people/florea/research/和公共知识库（如Sourceforge和iPlant Collaborative environment）获得。基因组装和基因组注释是解码生物体遗传组成的第一步，也是最重要的一步。下一代测序正在为越来越多的植物和动物物种的基因组测序工作提供动力。然而，生物信息学方法在适应速度和数据量的巨大增加方面进展缓慢。许多组装项目只是放弃了艰苦但急需的管理步骤，即使有证据表明组装质量对其注释和后续分析的影响。该项目将建立一套急需的自动化工具，以利用丰富的RNAseq资源，首先提高基因组组装的质量，其次是基因和转录本注释。第一组工具将使用RNAseq读数的邻接特性将未映射的重叠群招募到基因组组装草图中，以提高完整性并发现组装错误。第二套工具将结合联合收割机RNAseq和传统的（桑格）cDNA序列，产生一套全面的基因和转录注释沿着基因组。该研究将产生新的基于图形的算法，可供计算生物学家在未来的工具开发工作中使用，并将为NGS数据的能力和局限性提供关键见解，以帮助指导未来的植物基因组测序项目。通过将这些方法应用于正在进行的测序项目的数据，包括火炬松基因组，它将有助于为这些物种提供更好的参考基因组。

This project will produce novel and critical bioinformatics algorithms and tools to improve genome assembly and annotation. The tools will be released free of charge and without restrictions to help biologists create better reference genomes and gene annotations for their species of interest. When integrated into a teaching module, these tools will also be available to enhance student research and education. With regard to outreach and training, this project will contribute to the larger effort to recruit students from diverse backgrounds into interdisciplinary science by creating summer research internship opportunities for students, particularly those from underrepresented groups and Baltimore inner-city high-schools, in collaboration with Johns Hopkins University's Center for Talented Youth. The software, documentation, teaching module and analysis data for the project will be accessible from http://ccb.jhu.edu/people/florea/research/ and from public repositories such as Sourceforge and the iPlant Collaborative environment.Gene assembly and genome annotation are the first and most important steps in decoding the genetic makeup of an organism. Next generation sequencing is fueling a potpourri of genome sequencing efforts for a growing number of plant and animal species. However, bioinformatics methods have been slow to adapt to the tremendous increase in pace and data volume. Many assembly projects simply forego painstaking but much needed curation steps even as evidence mounts to show the consequences that the quality of assembly has on its annotations and subsequent analyses. The project will build a much-needed suite of automated tools to leverage the rich RNAseq resources to first, improve the quality of genome assembly, and second, its gene and transcript annotations. The first set of tools will use contiguity properties of RNAseq reads to recruit unmapped contigs into a draft genome assembly to improve completeness and to discover assembly errors. The second set of tools will combine RNAseq and traditional (Sanger) cDNA sequences to produce a comprehensive set of gene and transcript annotations along the genome. The research will generate new graph-based algorithms that can be used by computational biologists in their future tool development efforts and will provide critical insights into the power and limitations of NGS data to help guide future plant genome sequencing projects. By applying the methods to data from ongoing sequencing projects, including that for the loblolly pine genome, it will contribute to a better reference genome for these species.