Whole transcriptome analysis for neurobiology

描述（由申请人提供）：像大脑这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，由相互作用的调节因子网络协调。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，数量数以百万计，几乎是未知的，虽然一个小的兄弟类-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进展提供了系统地探索这两个因素的手段。然而，生物信息学的挑战是巨大的，缺乏全面的，精心设计的，易于使用的软件来管理，可视化，分析和解释数据可能是这一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，专门整合来自两种不同技术的全转录组数据，Affytek全外显子微阵列，其中140万个不同的转录本测量，和RNASeq，它提供了整个转录组的“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.