Table 1 Transcriptome analysis.
Open systems | Advantages | Disadvantages | Comments |
|---|---|---|---|
Representational differences analysis (RDA) | • Sensitive method • Sequence data obtained • Alternately spliced transcripts can be easily identified | • "Hit and miss" approach • Not suitable for transcriptome profiling • Sequencing intensive • Transcript representation may change and results need to be verified | • Typically used for identification of novel differentially expressed transcripts • Most commonly used variant of this method is Suppression Subtractive Hybridization (SSH) |
Differential display (DD) | • Sensitive method • Sequence data obtained | • High false positive rate • Not suitable for transcriptome profiling • Transcript representation may change and results need to be verified | • Not currently a widely favoured methodology |
Serial analysis of gene expression (SAGE) | • Transciptome profiling possible • Transcript representation retained | • Limited sequence data obtained • Sequencing intensive method • Often fails to account for transcript alternate splicing | • SAGE suitability for transciptome profiling is reliant on extensive sequencing |
Closed Systems | Advantages | Disadvantages | Comments |
Gene arrays | • Characterized target sequences on the arrays • Extremely small feature size • Very high through put methodology | • Restricted gene pool that may sample rather than profile the transcriptome • Variability • Signal amplification often needed for biopsies • Often fails to account for transcript alternate splicing • Data generated can be a bioinformatics challenge • Inconsistencies with analysis approaches | • Preferred transciptome profiling method • Gene alternate splicing can be addressed by using "tilling arrays" • MIAME is designed to overcome methodological inconsistencies |