Technique / Molecular Biology / DNA microarray gene array / mRNA amplification for microarray analysis

High-throuput microarray analysis requires large quantity of RNA. To address this issue, high-fidelity mRNA amplification technique for gene profiling was developed in 2000 by Wang E et al (Nature Biotechnology, 2000 Apr;18(4):457-9).

Despite the excellent prognosis, differentiated thyroid carcinoma (DTC) may recur in 20-40%, and prognosis is particularly related to early detection of recurrent disease. Therefore, long-term follow-up with sensitive tests is need. Serum thyroglobulin (Tg) has an established role as a tumor marker of relapse. However, there are technical limitations of Tg immunoassays, in special, the interference of anti-Tg antibodies and the method sensitivity is dependent on TSH stimulation. Detection of circulating malignant cells by amplification of tumor-specific mRNA showed initial promising results. However, almost one decade of studies of Tg mRNA detection in peripheral blood, its real contribution for DTC follow-up had not yet been established. After a critical analysis of published data, it is clear that there are many protocol differences and conflicting results. Therefore, it seems that amplification of thyroid-specific mRNAs is not superior to sensitive Tg assays and illegitimate transcription and alternative splicing of Tg are factors that may influence mRNA test specificity.

BACKGROUND: Gene expression microarray technology permits the analysis of global gene expression profiles. The amount of sample needed limits the use of small excision biopsies and/or needle biopsies from human or animal tissues. Linear amplification techniques have been developed to increase the amount of sample derived cDNA. These amplified samples can be hybridised on microarrays. However, little information is available whether microarrays based on amplified and unamplified material yield comparable results.In the present study we compared microarray data obtained from amplified mRNA derived from biopsies of rat cardiac left ventricle and non-amplified mRNA derived from the same organ. Biopsies were linearly amplified to acquire enough material for a microarray experiment. Both amplified and unamplified samples were hybridized to the Rat Expression Set 230 Array of Affymetrix. RESULTS: Analysis of the microarray data showed that unamplified material of two different left ventricles had 99.6% identical gene expression. Gene expression patterns of two biopsies obtained from the same parental organ were 96.3% identical. Similarly, gene expression pattern of two biopsies from dissimilar organs were 92.8% identical to each other.Twenty-one percent of reporters called present in parental left ventricular tissue disappeared after amplification in the biopsies. Those reporters were predominantly seen in the low intensity range.Sequence analysis showed that reporters that disappeared after amplification had a GC-content of 53.7+/-4.0%, while reporters called present in biopsy- and whole LV-samples had an average GC content of 47.8+/-5.5% (P

BACKGROUND: Global mRNA amplification has become a widely used approach to obtain gene expression profiles from limited material. An important concern is the reliable reflection of the starting material in the results obtained. This is especially important with extremely low quantities of input RNA where stochastic effects due to template dilution may be present. This aspect remains under-documented in the literature, as quantitative measures of data reliability are most often lacking. To address this issue, we examined the sensitivity levels of each transcript in 3 different cell sample sizes. ANOVA analysis was used to estimate the overall effects of reduced input RNA in our experimental design. In order to estimate the validity of decreasing sample sizes, we examined the sensitivity levels of each transcript by applying a novel model-based method, TransCount. RESULTS: From expression data, TransCount provided estimates of absolute transcript concentrations in each examined sample. The results from TransCount were used to calculate the Pearson correlation coefficient between transcript concentrations for different sample sizes. The correlations were clearly transcript copy number dependent. A critical level was observed where stochastic fluctuations became significant. The analysis allowed us to pinpoint the gene specific number of transcript templates that defined the limit of reliability with respect to number of cells from that particular source. In the sample amplifying from 1000 cells, transcripts expressed with at least 121 transcripts/cell were statistically reliable and for 250 cells, the limit was 1806 transcripts/cell. Above these thresholds, correlation between our data sets was at acceptable values for reliable interpretation. CONCLUSION: These results imply that the reliability of any amplification experiment must be validated empirically to justify that any gene exists in sufficient quantity in the input material. This finding has important implications for any experiment where only extremely small samples such as single cell analyses or laser captured microdissected cells are available.