Whole transcriptome analysis for neurobiology

Epicenter Software, Pasadena CA

Investigators

Abstract

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.