The sequencing of the human genome is beginning to yield great insight into the role of specific genes in human diseases. Whether through the use of qPCR, microarrays or by RNAseq, the ability to monitor gene expression levels is critical to identifying the role of specific genes in disease states, identifying targets for drug development and increasingly to make clinical decisions for patient care. Because RNA is subject to degradation that can affect measured mRNA levels, researchers typically test the integrity of an RNA sample before using the sample in a downstream assay such as qPCR, microarrays or RNAseq. Widely used methods which predict mRNA integrity based on electropherograms of total RNA are imperfect predictors of the adequacy of a sample for downstream assays. This leads to greater variability in quantifying gene expression levels and increased costs associated with running degraded samples in expensive assays or wasting of good samples which are wrongly judged to be degraded. We propose to develop an improved mRNA integrity assay that yields results similar to a Northern blot but in a convenient format. The proposed assay would use fluorescently labeled probes and microelectrophoresis to monitor the degradation of a specific mRNA species. By looking at mRNA rather than total RNA and using straightforward electropherogram analysis, the new assay is expected to be a better predictor of the suitability of an RNA sample for mRNA analysis particularly for FFPE samples. Such an assay is expected to give more accurate results when mRNA levels are measured using qPCR, microarrays or RNAseq.
Measuring gene expression levels is critical to understanding disease processes. We will develop an improved method to measure the extent of RNA degradation in a sample. Use of the assay will lower the overall analysis cost and decrease the variability of downstream gene expression assays.
| Cenik, Can; Derti, Adnan; Mellor, Joseph C et al. (2010) Genome-wide functional analysis of human 5' untranslated region introns. Genome Biol 11:R29 |
