Changes in expression have been shown to be associated with a variety of normal physiological processes as well as diseases including cancer. Studies have already shown that miRNAs may provide useful markers for the development of disease diagnostic and prognostic assays. Currently there are no discovery based, rapid-multiplexed methods available to simultaneously measure miRNA expression in several samples or tumor tissues. Next generation sequencing technologies are in principle very well suited for high- throughput sequencing of small non-coding RNAs. Despite this capacity, it is still time consuming and expensive to sequence large numbers of small RNA samples. We propose the development of a multiplex strategy to simultaneous sequence large numbers of small RNAs by indexing using sample-specific short identifying nucleotide sequences. Challenges that we propose to overcome include enzymatic sequence biases that may prefer certain transcripts over others and the extent to which indexing at different depths affects small RNA profiles. Indexing will has the advantage of measuring base error rate, allows the user to perform cross genomic studies, time courses, drug induced cellular experiments and monitor day to day expression variability between samples. The goal of this project is to create a kit for making minimally-biased, highly indexed small RNA libraries for massively parallel (""""""""next-generation"""""""") sequencing, that are constructed in such a way to allow the same libraries to be easily interrogated by real-time PCR (qPCR).
Recently there has been much interest in applying next-generation sequencing technologies for clinical use. microRNAs have been documented to behave as oncogenes or tumor suppressors in malignant tissues and cell lines, and have been shown to have potential for use as biomarkers in the progression of several cancers. By developing an efficient and non-biased barcoding method for massively parallel small RNA sequencing, unique profiles of these sequences in tissues will now be attainable.
