The T7-primer is a source of experimental bias and introduces variability between microarray platforms

Optimal Objective-Based Experimental Design for Uncertain Dynamical Gene Networks with Experimental Error

In systems biology, network models are often used to study interactions among cellular components, a salient aim being to develop drugs and therapeutic mechanisms to change the dynamical behavior of the network to avoid undesirable phenotypes. Owing to limited knowledge, model uncertainty is commonplace and network dynamics can be updated in different ways, thereby giving multiple dynamic trajectories, that is, dynamics uncertainty. In this manuscript, we propose an experimental design method that can effectively reduce the dynamics uncertainty and improve performance in an interaction-based network. Both dynamics uncertainty and experimental error are quantified with respect to the modeling objective, herein, therapeutic intervention. The aim of experimental design is to select among a set of candidate experiments the experiment whose outcome, when applied to the network model, maximally reduces the dynamics uncertainty pertinent to the intervention objective.

Microarray experiments and factors which affect their reliability

Oligonucleotide microarrays belong to the basic tools of molecular biology and allow for simultaneous assessment of the expression level of thousands of genes. Analysis of microarray data is however very complex, requiring sophisticated methods to control for various factors that are inherent to the procedures used. In this article we describe the individual steps of a microarray experiment, highlighting important elements and factors that may affect the processes involved and that influence the interpretation of the results. Additionally, we describe methods that can be used to estimate the influence of these factors, and to control the way in which they affect the expression estimates. A comprehensive understanding of the experimental protocol used in a microarray experiment aids the interpretation of the obtained results. By describing known factors which affect expression estimates this article provides guidelines for appropriate quality control and pre-processing of the data, additionally applicable to other transcriptome analysis methods that utilize similar sample handling protocols.

Chromatin remodelling and histone m RNA accumulation in bovine germinal vesicle oocytes

Major remodelling of the chromatin enclosed within the germinal vesicle occurs towards the end of oocyte growth in mammals, but the mechanisms involved in this process are not completely understood. In bovine, four distinct stages of chromatin compaction-ranging from a diffused state (GV0) to a fully compacted configuration (GV3)-are linked to the gradual acquisition of developmental potential. To better understand the molecular events and to identify mRNA modulations occurring in the oocyte during the GV0-to-GV3 transition, transcriptomic analysis was performed with the EmbryoGENE microarray platform. The mRNA abundance of several genes decreased as chromatin compaction increased, which correlates with progressive transcriptional silencing that is characteristic of the end of oocyte growth. On the other hand, the abundance of some transcripts increased during the same period, particularly several histone gene transcripts from the H2A, H2B, H3, H4, and linker H1 family. In silico analysis predicted RNA-protein interactions between specific histone transcripts and the bovine stem-loop binding protein 2 (SLBP2), which helps regulate the translation of histone mRNA during oogenesis. These results suggest that some histone-encoding transcripts are actively stored, possibly to sustain the needs of the embryo before genome activation. This dataset offers a unique opportunity to survey which histone mRNAs are needed to complete chromatin compaction during oocyte maturation and which are stockpiled for the first three cell cycles following fertilization.

Transcriptional analysis of micro-dissected articular cartilage in post-traumatic murine osteoarthritis

OBJECTIVE

Identify gene changes in articular cartilage of the medial tibial plateau (MTP) at 2, 4 and 8 weeks after destabilisation of the medial meniscus (DMM) in mice. Compare our data with previously published datasets to ascertain dysregulated pathways and genes in osteoarthritis (OA).

DESIGN

RNA was extracted from the ipsilateral and contralateral MTP cartilage, amplified, labelled and hybridized on Illumina WGv2 microarrays. Results were confirmed by real-time polymerase chain reaction (PCR) for selected genes.

RESULTS

Transcriptional analysis and network reconstruction revealed changes in extracellular matrix and cytoskeletal genes induced by DMM. TGFβ signalling pathway and complement and coagulation cascade genes were regulated at 2 weeks. Fibronectin (Fn1) is a hub in a reconstructed network at 2 weeks. Regulated genes decrease over time. By 8 weeks fibromodulin (Fmod) and tenascin N (Tnn) are the only dysregulated genes present in the DMM operated knees. Comparison with human and rodent published gene sets identified genes overlapping between our array and eight other studies.

CONCLUSIONS

Cartilage contributes a minute percentage to the RNA extracted from the whole joint (<0.2%), yet is sensitive to changes in gene expression post-DMM. The post-DMM transcriptional reprogramming wanes over time dissipating by 8 weeks. Common pathways between published gene sets include focal adhesion, regulation of actin cytoskeleton and TGFβ. Common genes include Jagged 1 (Jag1), Tetraspanin 2 (Tspan2), neuroblastoma, suppression of tumourigenicity 1 (Nbl1) and N-myc downstream regulated gene 2 (Ndrg2). The concomitant genes and pathways we identify may warrant further investigation as biomarkers or modulators of OA.

Sources of high variance between probe signals in Affymetrix short oligonucleotide microarrays

High density oligonucleotide microarrays present a big challenge for statistical data processing methods which aim to separate changes induced by experimental factors from those caused by artifacts and measurement inaccuracies. Despite huge advances in the field of microarray probe design methods, the signal variation between probes that target a single transcript is substantially larger than their between-replicate array variability, suggesting a large influence of various probe-specific effects that introduce bias to the data. In this work we present the influence of probe-related design variations on the expression intensities of individual probes, focusing on five potential sources of high probe signal variance: the GC composition of the probe, the distance between individual probe target sites, G-quadruplex formation in the probe sequence, the occurrence of sequence motifs complementary to the oligo(dT) primer, and the specificity of unrecognized alternative splicing probeset assignment. By focusing on two high quality microarray datasets based on two distinct array designs we show the extent of variance between probes that target a specific transcript providing guidelines for the future design of microarrays and data processing methods.

Motif effects in Affymetrix GeneChips seriously affect probe intensities

An Affymetrix GeneChip consists of an array of hundreds of thousands of probes (each a sequence of 25 bases) with the probe values being used to infer the extent to which genes are expressed in the biological material under investigation. In this article, we demonstrate that these probe values are also strongly influenced by their precise base sequence. We use data from >28 000 CEL files relating to 10 different Affymetrix GeneChip platforms and involving nearly 1000 experiments. Our results confirm known effects (those due to the T7-primer and the formation of G-quadruplexes) but reveal other effects. We show that there can be huge variations from one experiment to another, and that there may also be sizeable disparities between batches within an experiment and between CEL files within a batch.

Transcriptional profiling of serogroup B Neisseria meningitidis growing in human blood: an approach to vaccine antigen discovery

Neisseria meningitidis is a nasopharyngeal commensal of humans which occasionally invades the blood to cause septicaemia. The transcriptome of N. meningitidis strain MC58 grown in human blood for up to 4 hours was determined and around 10% of the genome was found to be differentially regulated. The nuo, pet and atp operons, involved in energy metabolism, were up-regulated, while many house-keeping genes were down-regulated. Genes encoding protein chaperones and proteases, involved in the stress response; complement resistant genes encoding enzymes for LOS sialylation and biosynthesis; and fHbp (NMB1870) and nspA (NMB0663), encoding vaccine candidates, were all up-regulated. Genes for glutamate uptake and metabolism, and biosynthesis of purine and pyrimidine were also up-regulated. Blood grown meningococci are under stress and undergo a metabolic adaptation and energy conservation strategy. The localisation of four putative outer membrane proteins encoded by genes found to be up-regulated in blood was assessed by FACS using polyclonal mouse antisera, and one (NMB0390) showed evidence of surface expression, supporting its vaccine candidacy.

Chromosome conformation capture on chip in single Drosophila melanogaster tissues

Chromosomes are protein-DNA complexes that encode life. In a cell nucleus, chromosomes are folded in a highly specific manner, which connects strongly to some of their paramount functions, such as DNA replication and gene transcription. Chromosome conformation capture methodologies allow researchers to detect chromosome folding, by quantitatively measuring which genomic sequences are in close proximity in nuclear space. Here, we describe a modified chromosome conformation capture on chip (4C) protocol, which is specifically designed for detection of chromosome folding in a single Drosophila melanogaster tissue. Our protocol enables 4C analyses on a limited number of cells, which is crucial for fly tissues, because these contain relatively low numbers of cells. We used this protocol to demonstrate that target genes of Polycomb group proteins interact with each other in nuclear space of third instar larval brain cells. Major benefits of using D. melanogaster in 4C studies are: (1) powerful and tractable genetic approaches can be incorporated; (2) short generation time allows use of complex genotypes; and (3) compact and well annotated genome. We anticipate that our sensitized 4C method will be generally applicable to detect chromosome folding in other fly tissues.

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.

A snapshot of the expression signature of androgen receptor splicing variants and their distinctive transcriptional activities

BACKGROUND

The diversity and complexity of the human androgen receptor (AR) splicing variants are well appreciated but not fully understood. The goal of this study is to generate a comprehensive expression signature of AR variants in castration-resistant prostate cancer (CRPC), and to address the relative importance of the individual variants in conferring the castration-resistant phenotype.

METHODS

A modified RNA amplification method, termed selective linear amplification of sense RNA, was developed to amplify all AR transcripts containing AR exon 3 in CRPC specimens, which were profiled using tiling expression microarrays. Coding sequences for the AR variants were cloned into expression vectors and assessed for their transcriptional activities. Quantitative RT-PCR was used to determine their in vivo expression patterns in an expanded set of clinical specimens.

RESULTS

In addition to expression peaks in AR intron 3, a novel AR exon, termed exon 9, was discovered. Exon 9 was spliced into multiple novel AR variants. Different AR splicing variants were functionally distinctive, with some demonstrating constitutive activity while others were conditionally active. Conditionally active AR-Vs may activate AR signaling depending on the cellular context. Importantly, AR variant functions did not appear to depend on the full-length AR.

CONCLUSIONS

This study provided the first unbiased snapshot of the AR variant signature consisting of multiple AR variants with distinctive functional properties, directly in CRPC specimens. Study findings suggest that the aggregate function of multiple AR variants may confer a castration-resistant phenotype independent of the full-length AR.

Technical variability is greater than biological variability in a microarray experiment but both are outweighed by changes induced by stimulation

Introduction

A central issue in the design of microarray-based analysis of global gene expression is that variability resulting from experimental processes may obscure changes resulting from the effect being investigated. This study quantified the variability in gene expression at each level of a typical in vitro stimulation experiment using human peripheral blood mononuclear cells (PBMC). The primary objective was to determine the magnitude of biological and technical variability relative to the effect being investigated, namely gene expression changes resulting from stimulation with lipopolysaccharide (LPS).

Methods and Results

Human PBMC were stimulated in vitro with LPS, with replication at 5 levels: 5 subjects each on 2 separate days with technical replication of LPS stimulation, amplification and hybridisation. RNA from samples stimulated with LPS and unstimulated samples were hybridised against common reference RNA on oligonucleotide microarrays. There was a closer correlation in gene expression between replicate hybridisations (0.86–0.93) than between different subjects (0.66–0.78). Deconstruction of the variability at each level of the experimental process showed that technical variability (standard deviation (SD) 0.16) was greater than biological variability (SD 0.06), although both were low (SD<0.1 for all individual components). There was variability in gene expression both at baseline and after stimulation with LPS and proportion of cell subsets in PBMC was likely partly responsible for this. However, gene expression changes after stimulation with LPS were much greater than the variability from any source, either individually or combined.

Conclusions

Variability in gene expression was very low and likely to improve further as technical advances are made. The finding that stimulation with LPS has a markedly greater effect on gene expression than the degree of variability provides confidence that microarray-based studies can be used to detect changes in gene expression of biological interest in infectious diseases.

Linear nicking endonuclease-mediated strand-displacement DNA amplification

We describe a method for linear isothermal DNA amplification using nicking endonuclease-mediated strand displacement by a DNA polymerase. The nicking of one strand of a DNA target by the endonuclease produces a primer for the polymerase to initiate synthesis. As the polymerization proceeds, the downstream strand is displaced into a single-stranded form while the nicking site is also regenerated. The combined continuous repetitive action of nicking by the endonuclease and strand-displacement synthesis by the polymerase results in linear amplification of one strand of the DNA molecule. We demonstrate that DNA templates up to 5000 nucleotides can be linearly amplified using a nicking endonuclease with 7-bp recognition sequence and Sequenase version 2.0 in the presence of single-stranded DNA binding proteins. We also show that a mixture of three templates of 500, 1000, and 5000 nucleotides in length is linearly amplified with the original molar ratios of the templates preserved. Moreover, we demonstrate that a complex library of hydrodynamically sheared genomic DNA from bacteriophage lambda can be amplified linearly.

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

Background

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.

Results

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.

Conclusion

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.

G-stack modulated probe intensities on expression arrays - sequence corrections and signal calibration

Background

The brightness of the probe spots on expression microarrays intends to measure the abundance of specific mRNA targets. Probes with runs of at least three guanines (G) in their sequence show abnormal high intensities which reflect rather probe effects than target concentrations. This G-bias requires correction prior to downstream expression analysis.

Results

Longer runs of three or more consecutive G along the probe sequence and in particular triple degenerated G at its solution end ((GGG)₁-effect) are associated with exceptionally large probe intensities on GeneChip expression arrays. This intensity bias is related to non-specific hybridization and affects both perfect match and mismatch probes. The (GGG)₁-effect tends to increase gradually for microarrays of later GeneChip generations. It was found for DNA/RNA as well as for DNA/DNA probe/target-hybridization chemistries. Amplification of sample RNA using T7-primers is associated with strong positive amplitudes of the G-bias whereas alternative amplification protocols using random primers give rise to much smaller and partly even negative amplitudes.

We applied positional dependent sensitivity models to analyze the specifics of probe intensities in the context of all possible short sequence motifs of one to four adjacent nucleotides along the 25meric probe sequence. Most of the longer motifs are adequately described using a nearest-neighbor (NN) model. In contrast, runs of degenerated guanines require explicit consideration of next nearest neighbors (GGG terms). Preprocessing methods such as vsn, RMA, dChip, MAS5 and gcRMA only insufficiently remove the G-bias from data.

Conclusions

Positional and motif dependent sensitivity models accounts for sequence effects of oligonucleotide probe intensities. We propose a positional dependent NN+GGG hybrid model to correct the intensity bias associated with probes containing poly-G motifs. It is implemented as a single-chip based calibration algorithm for GeneChips which can be applied in a pre-correction step prior to standard preprocessing.

Real-time monitoring of aRNA production during T7 amplification to prevent the loss of sample representation during microarray hybridization sample preparation

Gene expression analysis performed through comparative abundance of transcripts is facing a new challenge with the increasing need to compare samples of known cell number, such as early embryos or laser microbiopsies, where the RNA contents of identical cellular inputs can by nature be variable. When working with scarce tissues, the success of microarray profiling largely depends on the efficiency of the amplification step as determined by its ability to preserve the relative abundance of transcripts in the resulting amplified sample. Maintaining this initial relative abundance across samples is paramount to the generation of physiologically relevant data when comparing samples of different RNA content. The T7 RNA polymerase (T7-IVT) amplification is widely used for microarray sample preparation. Characterization of the reaction's kinetics has clearly indicated that its true linear phase is of short duration and is followed by a nonlinear phase. This second phase leads to modifications in transcript abundance that biases comparison between samples of different types. The impact assessment performed in this study has shown that the standard amplification protocol significantly lowers the quality of microarray data, rendering more than half of differentially expressed candidates undetected and distorting the true proportional differences of all candidates analyzed.

A novel approach for reliable microarray analysis of microdissected tumor cells from formalin-fixed and paraffin-embedded colorectal cancer resection specimens

We present a novel approach for microarray analysis of RNA derived from microdissected cells of routinely formalin-fixed and paraffin-embedded (FFPE) cancer resection specimens. Subsequent to RNA sample preparation and hybridization to standard GeneChips (Affymetrix), RNA samples yielded 36.43 +/- 9.60% (FFPE), 49.90 +/- 4.43% (fresh-frozen), and 53.9% (cell line) present calls. Quality control parameters and Q-RT-PCR validation demonstrated reliability of results. Microarray datasets of FFPE samples were informative and comparable to those of fresh-frozen samples. A systematic measurement difference of differentially processed tissues was eliminated by a correction step for comparative unsupervised data analysis of fresh-frozen and FFPE samples. Within FFPE samples, unsupervised clustering analyses clearly distinguished between normal and malignant tissues as well as to further separate tumor samples according to histological World Health Organization (WHO) subtypes. In summary, our approach represents a major step towards integration of microarrays into retrospective studies and enables further investigation of the relevance of microarray analysis for clinico-pathological diagnostics.