The T7-Primer Is a Source of Experimental Bias and Introduces Variability between Microarray Platforms

Eberwine(-like) amplification of mRNA adds distinct 6–10 bp nucleotide stretches to the 5′ end of amplified RNA transcripts. Analysis of over six thousand microarrays reveals that probes containing motifs complementary to these stretches are associated with aberrantly high signals up to a hundred fold the signal observed in unaffected probes. This is not observed when total RNA is used as target source. Different T7 primer sequences are used in different laboratories and platforms and consequently different T7 primer bias is observed in different datasets. This will hamper efforts to compare data sets across platforms

Microarray comparison of prostate tumor gene expression in African-American and Caucasian American males: a pilot project study

African American Men are 65% more likely to develop prostate cancer and are twice as likely to die of prostate cancer, than are Caucasian American Males. The explanation for this glaring health disparity is still unknown; although a number of different plausible factors have been offered including genetic susceptibility and gene-environment interactions. We favor the hypothesis that altered gene expression plays a major role in the disparity observed in prostate cancer incidence and mortality between African American and Caucasian American Males. To discover genes or gene expression pattern(s) unique to African American or to Caucasian American Males that explain the observed prostate cancer health disparity in African American males, we conducted a micro array pilot project study that used prostate tumors with a Gleason score of 6. We compared gene expression profiling in tumors from African-American Males to prostate tumors in Caucasian American Males. A comparison of case-matched ratios revealed at least 67 statistically significant genes that met filtering criteria of at least +/- 4.0 fold change and p < 0.0001. Gene ontology terms prevalent in African American prostate tumor/normal ratios relative to Caucasian American prostate tumor/normal ratios included interleukins, progesterone signaling, Chromatin-mediated maintenance and myeloid dendritic cell proliferation. Functional in vitro assays are underway to determine roles that selected genes in these onotologies play in contributing to prostate cancer development and health disparity

Use of Non-Amplified RNA Samples for Microarray Analysis of Gene Expression

Demand for high quality gene expression data has driven the development of revolutionary microarray technologies. The quality of the data is affected by the performance of the microarray platform as well as how the nucleic acid targets are prepared. The most common method for target nucleic acid preparation includes in vitro transcription amplification of the sample RNA. Although this method requires a small amount of starting material and is reported to have high reproducibility, there are also technical disadvantages such as amplification bias and the long, laborious protocol. Using RNA derived from human brain, breast and colon, we demonstrate that a non-amplification method, which was previously shown to be inferior, could be transformed to a highly quantitative method with a dynamic range of five orders of magnitude. Furthermore, the correlation coefficient calculated by comparing microarray assays using non-amplified samples with qRT-PCR assays was approximately 0.9, a value much higher than when samples were prepared using amplification methods. Our results were also compared with data from various microarray platforms studied in the MicroArray Quality Control (MAQC) project. In combination with micro-columnar 3D-Gene™ microarray, this non-amplification method is applicable to a variety of genetic analyses, including biomarker screening and diagnostic tests for cancer

Circadian Cycles of Gene Expression in the Coral, Acropora millepora

Background: Circadian rhythms regulate many physiological, behavioral and reproductive processes. These rhythms are often controlled by light, and daily cycles of solar illumination entrain many clock regulated processes. In scleractinian corals a number of different processes and behaviors are associated with specific periods of solar illumination or nonillumination—for example, skeletal deposition, feeding and both brooding and broadcast spawning. Methodology/Principal Findings: We have undertaken an analysis of diurnal expression of the whole transcriptome and more focused studies on a number of candidate circadian genes in the coral Acropora millepora using deep RNA sequencing and quantitative PCR. Many examples of diurnal cycles of RNA abundance were identified, some of which are light responsive and damped quickly under constant darkness, for example, cryptochrome 1 and timeless, but others that continue to cycle in a robust manner when kept in constant darkness, for example, clock, cryptochrome 2, cycle and eyes absent, indicating that their transcription is regulated by an endogenous clock entrained to the light-dark cycle. Many other biological processes that varied between day and night were also identified by a clustering analysis of gene ontology annotations. Conclusions/Significance: Corals exhibit diurnal patterns of gene expression that may participate in the regulation of circadian biological processes. Rhythmic cycles of gene expression occur under constant darkness in both populations o

High-Throughput SuperSAGE for Digital Gene Expression Analysis of Multiple Samples Using Next Generation Sequencing

We established a protocol of the SuperSAGE technology combined with next-generation sequencing, coined “High-Throughput (HT-) SuperSAGE”. SuperSAGE is a method of digital gene expression profiling that allows isolation of 26-bp tag fragments from expressed transcripts. In the present protocol, index (barcode) sequences are employed to discriminate tags from different samples. Such barcodes allow researchers to analyze digital tags from transcriptomes of many samples in a single sequencing run by simply pooling the libraries. Here, we demonstrated that HT-SuperSAGE provided highly sensitive, reproducible and accurate digital gene expression data. By increasing throughput for analysis in HT-SuperSAGE, various applications are foreseen and several examples are provided in the present study, including analyses of laser-microdissected cells, biological replicates and tag extraction using different anchoring enzymes

An optimized protocol for microarray validation by quantitative PCR using amplified amino allyl labeled RNA

<p>Abstract</p> <p>Background</p> <p>Validation of microarrays data by quantitative real-time PCR (qPCR) is often limited by the low amount of available RNA. This raised the possibility to perform validation experiments on the amplified amino allyl labeled RNA (AA-aRNA) leftover from microarrays. To test this possibility, we used an ongoing study of our laboratory aiming at identifying new biomarkers of graft rejection by the transcriptomic analysis of blood cells from brain-dead organ donors.</p> <p>Results</p> <p>qPCR for ACTB performed on AA-aRNA from 15 donors provided Cq values 8 cycles higher than when original RNA was used (P < 0.001), suggesting a strong inhibition of qPCR performed on AA-aRNA. When expression levels of 5 other genes were measured in AA-aRNA generated from a universal reference RNA, qPCR sensitivity and efficiency were decreased. This prevented the quantification of one low-abundant gene, which was readily quantified in un-amplified and un-labeled RNA. To overcome this limitation, we modified the reverse transcription (RT) protocol that generates cDNA from AA-aRNA as follows: addition of a denaturation step and 2-min incubation at room temperature to improve random primers annealing, a transcription initiation step to improve RT, and a final treatment with RNase H to degrade remaining RNA. Tested on universal reference AA-aRNA, these modifications provided a gain of 3.4 Cq (average from 5 genes, P < 0.001) and an increase of qPCR efficiency (from -1.96 to -2.88; P = 0.02). They also allowed for the detection of a low-abundant gene that was previously undetectable. Tested on AA-aRNA from 15 brain-dead organ donors, RT optimization provided a gain of 2.7 cycles (average from 7 genes, P = 0.004). Finally, qPCR results significantly correlated with microarrays.</p> <p>Conclusion</p> <p>We present here an optimized RT protocol for validation of microarrays by qPCR from AA-aRNA. This is particularly valuable in experiments where limited amount of RNA is available.</p

Accurate Expression Profiling of Very Small Cell Populations

BACKGROUND: Expression profiling, the measurement of all transcripts of a cell or tissue type, is currently the most comprehensive method to describe their physiological states. Given that accurate profiling methods currently available require RNA amounts found in thousands to millions of cells, many fields of biology working with specialized cell types cannot use these techniques because available cell numbers are limited. Currently available alternative methods for expression profiling from nanograms of RNA or from very small cell populations lack a broad validation of results to provide accurate information about the measured transcripts. METHODS AND FINDINGS: We provide evidence that currently available methods for expression profiling of very small cell populations are prone to technical noise and therefore cannot be used efficiently as discovery tools. Furthermore, we present Pico Profiling, a new expression profiling method from as few as ten cells, and we show that this approach is as informative as standard techniques from thousands to millions of cells. The central component of Pico Profiling is Whole Transcriptome Amplification (WTA), which generates expression profiles that are highly comparable to those produced by others, at different times, by standard protocols or by Real-time PCR. We provide a complete workflow from RNA isolation to analysis of expression profiles. CONCLUSIONS: Pico Profiling, as presented here, allows generating an accurate expression profile from cell populations as small as ten cells