Whole transcriptome analysis for neurobiology

描述（由申请人提供）：像大脑一样复杂的器官的发育取决于数千种信号蛋白的复杂相互作用，这些信号蛋白是由相互作用的调节因子网络精心策划的。最近的 ENCODE 数据显示，内含子中和基因之间的大片所谓“垃圾”DNA 实际上正在积极转录。这些数以百万计的非编码转录本的功能实际上是未知的，尽管其中一个小的同胞类——microRNA——作为调节RNA正受到密切关注。可能由非编码转录本控制的一个过程是交替外显子的使用——一种显着增加细胞蛋白质多样性（特别是在中枢神经系统中）的机制，目前对其调节知之甚少。生成全转录组数据的最新进展提供了系统探索这两个因素的方法。然而，生物信息学的挑战是巨大的，缺乏全面、设计良好且易于使用的软件来管理、可视化、分析和解释数据可能会成为该研究领域的限制因素。我们建议开发一个专门用于整合来自两种不同技术的全转录组数据的生物信息学工具包：Affymetrix All Exon 微阵列（可进行 140 万个不同的转录本测量）和 RNASeq（可对整个转录组进行“数字”表达分析）。该工具包还将整合表观基因组数据，这对于理解转录调控至关重要。该软件的设计和开发将由从事大脑研究的著名科学家指导，并将应用于来自神经组织的样本数据集，以确保该程序包含与该领域相关的功能和注释。

DESCRIPTION (provided by applicant): Development of an organ as complex as the brain depends 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 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 advances that generate whole-transcriptome data have provided the means to systematically explore both these factors. However, the bioinformatic challenges are substantial, and the lack of comprehensive, well designed, and easily used software to manage, visualize, analyze and interpret the data will likely be the limiting factor in this field of research. We propose to develop a bioinformatics toolkit specifically to integrate whole-transcriptome data from two different technologies, the Affymetrix All Exon microarray which 1.4 million distinct transcript measurements, and RNASeq, which provides for 'digital' expression analysis of the whole transcriptome. The toolkit will also integrate epigenomic data that will be essential in the understanding of regulation of transcription. 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 datasets derived from neurological tissues, to ensure that the program incorporates functions and annotations relevant to this field.