Toolkit for Whole Transcriptome Analysis of Neural Tissues

神经组织全转录组分析工具包

• 批准号: 7694376
• 负责人: Jonathan Buckley
• 金额: $ 29.64万
• 依托单位: EPICENTER SOFTWARE
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-30 至 2010-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7694376
• 关键词: Analysis of Variance; Atlases; Attention; Base Sequence; Bioinformatics; Biological; Biological Neural Networks; Brain; Cell physiology; Clinical; Clinical Research; Complex; Computer software; Data; Data Analyses; Data Set; Databases; Development; Discipline; Disease; Elements; Ensure; Evaluation; Exons; Factor Analysis; Functional RNA; Gene Expression Profile; Genes; Genome; Genomics; Glioblastoma; Graph; Imagery; Individual; Informatics; Internet; Introns; Junk DNA; Link; Measures; Messenger RNA; Methods; MicroRNAs; Mining; Modeling; Neuroblastoma; Neurologic; Non-linear Models; Organ; Pattern; Phase; Principal Component Analysis; Process; Proteins; RNA Splicing; Regression Analysis; Regulation; Research; Role; Sampling; Schizophrenia; Scientist; Screening procedure; Signaling Protein; Site; Small Business Innovation Research Grant; Software Tools; Source; Technology; Time; Tissues; Transcript; Variant; base; comparison group; computer based statistical methods; data management; depression; design; digital; empowered; new technology; next generation; public health relevance; relating to nervous system; software development; tool

DESCRIPTION (provided by applicant): Development of an organ as complex as the brain must depend on an intricate interplay of thousands of signaling proteins, orchestrated by an interacting web of regulatory factors. Recent ENCODE data reveal that the large tracts of so-called `junk' DNA in introns and between genes is, in fact, actively transcribed. The functions of these non-coding transcripts, which number in the millions, are virtually unknown, although one very small sib-class - the microRNAs - is receiving close attention as regulatory RNAs. One process that may be controlled by the non-coding transcripts is alternate exon use - a mechanism that adds significantly to the diversity of cellular proteins (particularly in the CNS), the regulation of which is little understood at this time. Recent technological advances that generate whole-transcriptome data have provided the means to systematically explore both these factors - the role non-coding transcripts, and the occurrence and control of splice variation. However, the bioinformatic challenges posed by these technologies are substantial, and the lack of comprehensive, well designed, and easily used software to manage, visualize, analyze and interpret these data will likely be the limiting factor in this field of research. We propose to develop a bioinformatics toolkit specifically to mine whole-transcriptome data from two fundamentally different technologies, the Affymetrix All Exon microarray which provides measures of over 1.4 million distinct transcripts, and the Solexa ultra high throughput sequencer, which provides for `digital' expression analysis of the whole transcriptome. The design and development of the software will be guided by prominent scientists engaged in the study of the brain, and will be applied to sample data set derived from neurological tissue, to ensure that the progra incorporates functions and annotations relevant to this field. PUBLIC HEALTH RELEVANCE: While the large-scale array technologies have provided an unprecedented capability to model cellular processes in the brain, both in normal functioning and disease states, this capability is utterly dependent on the availability of complex data management, computational, statistical and informatic software tools. The utility of the next generation of arrays - which focus on critical regulation and control functions of the cell - will be stymied by an initial lack of suitable bioinformatic tools. This proposal initiates an accelerated development of an integrated software package intended to empower biologists in the application and analysis of these powerful new technologies, with broadly reaching impact at all levels of biological and clinical research, and across every discipline.

描述（由申请人提供）：像大脑这样复杂的器官的发育必须依赖于数千种信号蛋白的复杂相互作用，由相互作用的调控因子网络协调。最近的ENCODE数据显示，内含子中和基因之间的大量所谓“垃圾”DNA实际上是活跃转录的。这些非编码转录本的功能，其数量数以百万计，几乎是未知的，虽然一个非常小的兄弟类-microRNA-作为调控RNA受到密切关注。可能由非编码转录物控制的一个过程是交替外显子使用-这是一种显著增加细胞蛋白质多样性的机制（特别是在CNS中），目前对其调控知之甚少。产生全转录组数据的最新技术进步提供了系统地探索这两个因素的手段-非编码转录本的作用，以及剪接变异的发生和控制。然而，这些技术带来的生物信息学挑战是巨大的，缺乏全面的，精心设计的，易于使用的软件来管理，可视化，分析和解释这些数据可能是该研究领域的限制因素。我们建议开发一个生物信息学工具包，专门从两个根本不同的技术，Affytek全外显子微阵列，提供超过140万个不同的成绩单的措施，和Solexa超高通量测序仪，它提供了“数字”表达分析的整个转录组，挖掘全转录组数据。该软件的设计和开发将由从事大脑研究的杰出科学家指导，并将应用于来自神经组织的样本数据集，以确保程序包含与该领域相关的功能和注释。公共卫生关系：虽然大规模阵列技术提供了前所未有的能力来模拟大脑中的细胞过程，无论是在正常功能还是疾病状态下，这种能力完全依赖于复杂的数据管理，计算，统计和信息软件工具的可用性。下一代阵列的实用性-专注于细胞的关键调节和控制功能-将因最初缺乏合适的生物信息学工具而受阻。该提案启动了一个集成软件包的加速开发，旨在使生物学家能够应用和分析这些强大的新技术，对生物和临床研究的各个层面以及各个学科产生广泛的影响。