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Universal Sequence Tag Array (U-STAR) platform : strategies towards the development of a universal platform for the absolute quantification of gene expression on a global scale

University of British Columbia

The advent of technologies specifically designed to capture glimpses of gene expression on a systems-wide scale has led to a revolution in our understanding of cellular dynamics, identifying the contributions and interactions of families of genes involved in cell development, dysfunction, and death. Broadly classified into count-based “digital” or signal-based “analogue” approaches, these technologies have permitted “portraits” of the transcriptome to be generated through comparative measurements of gene expression, enabling, for example, the generation of qualitative models of disease. However, truly predictive models of cellular function that can enhance our ability to discover new pharmaceuticals, detect and monitor disease, evaluate treatments, and ultimately, predict and prevent illness, require platforms that can provide detailed and accurate measurements of transcript abundances on an absolute scale. Unfortunately, inherent limitations preclude these technologies from providing this level of quantitative information. This thesis examines design issues associated with a popular digital approach to transcriptomics, serial analysis of gene expression (SAGE), that diminish us utility as a tool for absolute transcriptomics. Careful analysis of the processing steps involved in converting the starting mRNA population into short sequence tags (SST5) and subsequently into a format amenable to interrogation via sequencing technology reveals the introduction of strong biases and artifacts that limit reproducible abundance measurements in SAGE to transcripts present within the highest 2 orders of magnitude in the original sample. As a large number of steps are involved in formatting SSTs for analysis via sequencing, an alternative strategy is presented that utilizes a microarray-based analogue approach for the interrogation of SSTs. Termed the Universal Sequence Tag Array (U-STAR) platform, this platform is able to provide accurate quantitative measurements over a 3-decade range of transcript abundances by obviating sources of bias associated with both SAGE and DNA microarray technologies and eliminating the requirement for material amplification. The SAGE-like utilization of STARtags also endows this technology with the potential to be used as a universal platform, eliminating costs associated with custom microarray construction, and minimizing those associated with the preparation and large-scale sequencing of SAGE libraries. Considerations for future development are also discussed for the USTAR platform.

Thesis/Dissertation

application/pdf

2009-03-05

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/5580

Interdisciplinary Studies

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/