Quality assessment of the Affymetrix U133A&B probesets by target sequence mapping and expression data analysis

Careful analysis of microarray probe design should be an obligatory component of MicroArray Quality Control (MACQ) project [Patterson et al., 2006; Shi et al., 2006] initiated by the FDA (USA) in order to provide quality control tools to researchers of gene expression profiles and to translate the microarray technology from bench to bedside. The identification and filtering of unreliable probesets are important preprocessing steps before analysis of microarray data. These steps may result in an essential improvement in the selection of differentially expressed genes, gene clustering and construction of co-regulatory expression networks. We revised genome localization of the Affymetrix U133A&B GeneChip initial (target) probe sequences, and evaluated the impact of erroneous and poorly annotated target sequences on the quality of gene expression data. We found about 25% of Affymetrix target sequences overlapping with interspersed repeats that could cause cross-hybridization effects. In total, discrepancies in target sequence annotation account for up to approximately 30% of 44692 Affymetrix probesets. We introduce a novel quality control algorithm based on target sequence mapping onto genome and GeneChip expression data analysis. To validate the quality of probesets we used expression data from large, clinically and genetically distinct groups of breast cancers (249 samples). For the first time, we quantitatively evaluated the effect of repeats and other sources of inadequate probe design on the specificity, reliability and discrimination ability of Affymetrix probesets. We propose that only functionally reliable Affymetrix probesets that passed our quality control algorithm (approximately 86%) for gene expression analysis should be utilized. The target sequence annotation and filtering is available upon request.     

The Incidence of Sexually Dimorphic Gene Expression Varies Greatly between Tissues in the Rat

The sexually dimorphic expression of genes across 26 somatic rat tissues was using Affymetrix RAE-230 genechips. We considered probesets to be sexually dimorphically expressed (SDE) if they were measurably expressed above background in at least one sex, there was at least a two-fold difference in expression (dimorphism) between the sexes, and the differences were statistically significant after correcting for false discovery. 14.5% of expressed probesets were SDE in at least one tissue, with higher expression nearly twice as prevalent in males compared to females. Most were SDE in a single tissue. Surprisingly, nearly half of the probesets that were (SDE) in multiple tissues were oppositely sex biased in different tissues, and most SDE probesets were also expressed without sex bias in other tissues. Two genes were widely SDE: Xist (female-only) and Eif2s3y (male-only). The frequency of SDE probesets varied widely between tissues, and was highest in the duodenum (6.2%), whilst less than 0.05% in over half of the surveyed tissues. The occurrence of SDE probesets was not strongly correlated between tissues. Within individual tissues, however, relational networks of SDE genes were identified. In the liver, networks relating to differential metabolism between the sexes were seen. The estrogen receptor was implicated in differential gene expression in the duodenum. To conclude, sexually dimorphic gene expression is common, but highly tissue-dependent. Sexually dimorphic gene expression may provide insights into mechanisms underlying phenotypic sex differences. Online data are provided as a resource for further analyses (GEO reference {"type":"entrez-geo","attrs":{"text":"GSE63362","term_id":"63362"}}GSE63362).     

Characterization of mismatch and high-signal intensity probes associated with Affymetrix genechips

MOTIVATION: For Affymetrix microarray platforms, gene expression is determined by computing the difference in signal intensities between perfect match (PM) and mismatch (MM) probesets. Although the use of PM is not controversial, MM probesets have been associated with variance and ultimately inaccurate gene expression calls. A principal focus of this study was to investigate the nature of the MM signal intensities and demonstrate its contribution to the experimental results. RESULTS: While most MM intensities were likely associated with random noise, a subset of approximately 20% (99,485) of the MM probes displayed relatively high signal intensities to the corresponding PM probes (MM > PM) in a non-random fashion; 13,440 of these probes demonstrated exceptionally high 'outlier' intensities. About 15,938 PM probes also demonstrated exceptionally high outlier intensities consistently across all hybridizations. About 92% of the MM > PM probes had either a dThymidine (dT) or a dCytidine (dC) at the 13th position of the probe sequence. MM and PM probes displaying extremely high outlier intensities contained high dC rich nucleotides, and low dA contents at other nucleotides positions along the 25mer probe sequence. Differentially expressed genes generated using Genechip Operating System (GCOS) or modified PM-only methods were also examined. Of those candidate genes identified in the PM-only method, 157 of them were designated by GCOS as absent across all datasets and many others contained probes with MM > PM signal intensities. Our data suggests that MM intensity from PM signal can be a major source of error analysis, leading to fewer potentially biologically important candidate genes. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

MicroRNA-125a is over-expressed in insulin target tissues in a spontaneous rat model of Type 2 Diabetes

Background

The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. The benefit gained from the higher tissue specificity realized through LCM sampling is evaluated in this study through a comparison of microarray expression profiles obtained from same-samples using bulk and LCM processing.

Methods

Expression data from ten lung adenocarcinoma samples and six adjacent normal samples were acquired using LCM and bulk sampling methods. Expression values were evaluated for correlation between sample processing methods, as well as for bias introduced by the additional linear amplification required for LCM sample profiling.

Results

The direct comparison of expression values obtained from the bulk and LCM sampled datasets reveals a large number of probesets with significantly varied expression. Many of these variations were shown to be related to bias arising from the process of linear amplification, which is required for LCM sample preparation. A comparison of differentially expressed genes (cancer vs. normal) selected in the bulk and LCM datasets also showed substantial differences. There were more than twice as many down-regulated probesets identified in the LCM data than identified in the bulk data. Controlling for the previously identified amplification bias did not have a substantial impact on the differences identified in the differentially expressed probesets found in the bulk and LCM samples.

Conclusion

LCM-coupled microarray expression profiling was shown to uniquely identify a large number of differentially expressed probesets not otherwise found using bulk tissue sampling. The information gain realized from the LCM sampling was limited to differential analysis, as the absolute expression values obtained for some probesets using this study's protocol were biased during the second round of amplification. Consequently, LCM may enable investigators to obtain additional information in microarray studies not easily found using bulk tissue samples, but it is of critical importance that potential amplification biases are controlled for.     

In GERD patients, mucosal repair associated genes are upregulated in non-inflamed oesophageal epithelium

Previous studies addressing the effects of acid reflux and PPI therapy on gene expression in oesophageal epithelium concentrated on inflamed tissue. We aimed to determine changes in gene expression in non-inflamed oesophageal epithelium of GERD patients. Therefore, we included 20 GERD patients with pathological total 24-hr acid exposure of 6–12% and SAP ≥ 95%. Ten patients discontinued PPI treatment (PPI-), 10 took pantoprazole 40 mg bid (PPI+). Ten age/sex-matched healthy controls were recruited. Biopsies were taken from non-inflamed mucosa 6 cm and 16 cm proximal to the squamocolumnar junction (SCJ). Gene expression profiling of biopsies from 6 cm was performed on Human Genome U133 Plus 2.0 arrays (Affymetrix). Genes exhibiting a fold change >1.4 (t-test P -value < 1^E– 4) were considered differentially expressed. Results were confirmed by real-time RT-PCR. In PPI- patients, 92 microarray probesets were deregulated. The majority of the corresponding genes were associated with cell–cell contacts, cytoskeletal reorganization and cellular motility, suggesting facilitation of a migratory phenotype. Genes encoding proteins with anti-apoptotic or anti-proliferative functions or stress-protective functions were also deregulated. No probesets were deregulated in PPI+ patients. QPCR analysis of 20 selected genes confirmed most of the deregulations in PPI- patients, and showed several deregulated genes in PPI+ patients as well. In the biopsies taken at 16 cm QPCR revealed no deregulations of the selected genes. We conclude that upon acid exposure, oesophageal epithelial cells activate a process globally known as epithelial restitution: up-regulation of anti-apoptotic, anti-oxidant and migration associated genes. Possibly this process helps maintaining barrier function.     

Gene expression in the hippocampus of inbred alcohol-preferring and -nonpreferring rats

The hippocampus is sensitive to the effects of ethanol and appears to have a role in the development of alcohol tolerance. The objective of this study was to test the hypothesis that there are innate differences in gene expression in the hippocampus of inbred alcohol-preferring (iP) and -nonpreferring (iNP) rats that may contribute to differences in sensitivity to ethanol and/or in the development of tolerance. Affymetrix microarrays were used to measure gene expression in the hippocampus of alcohol-naive male iP and iNP rats in two experiments (n=4 and 6 per strain in the two experiments). Combining data from the two experiments, there were 137 probesets representing 129 genes that significantly differed (P < or = 0.01); 62 probesets differed at P < or = 0.001. Among the 36% of the genes that were expressed more in the iP than iNP rat at this level of significance, many were involved in cell growth and adhesion, cellular stress reduction and anti-oxidation, protein trafficking, regulation of gene expression, synaptic function and metabolism. Among the 64% of the genes that had lower expression in the hippocampus of iP than iNP rats were genes involved in metabolic pathways, cellular signaling systems, protein trafficking, cell death and neurotransmission. Overall, the data indicate that there are significant innate differences in gene expression in the hippocampus between iP and iNP rats, some of which might contribute to the differences observed in the development of alcohol tolerance between the selectively bred P and NP lines.     

Identification of Candidate Growth Promoting Genes in Ovarian Cancer through Integrated Copy Number and Expression Analysis

Ovarian cancer is a disease characterised by complex genomic rearrangements but the majority of the genes that are the target of these alterations remain unidentified. Cataloguing these target genes will provide useful insights into the disease etiology and may provide an opportunity to develop novel diagnostic and therapeutic interventions. High resolution genome wide copy number and matching expression data from 68 primary epithelial ovarian carcinomas of various histotypes was integrated to identify genes in regions of most frequent amplification with the strongest correlation with expression and copy number. Regions on chromosomes 3, 7, 8, and 20 were most frequently increased in copy number (>40% of samples). Within these regions, 703/1370 (51%) unique gene expression probesets were differentially expressed when samples with gain were compared to samples without gain. 30% of these differentially expressed probesets also showed a strong positive correlation (r≥0.6) between expression and copy number. We also identified 21 regions of high amplitude copy number gain, in which 32 known protein coding genes showed a strong positive correlation between expression and copy number. Overall, our data validates previously known ovarian cancer genes, such as ERBB2, and also identified novel potential drivers such as MYNN, PUF60 and TPX2.     

The human immunodeficiency virus type 1 Rev protein and the Rev-responsive element counteract the effect of an inhibitory 5' splice site in a 3' untranslated region.

A 5' splice site located in a 3' untranslated region (3'UTR) has been shown previously to inhibit gene expression. Natural examples of inhibitory 5' splice sites have been identified in the late 3'UTRs of papillomaviruses and are thought to inhibit viral late gene expression at early stages of the viral life cycle. In this study, we demonstrate that the interaction of the human immunodeficiency virus type 1 Rev protein with the Rev-responsive element (RRE) overcomes the inhibitory effects of a 5' splice site located within a 3'UTR. This was studied by using both a bovine papillomavirus type 1 L1 cDNA expression vector and a chloramphenicol acetyltransferase expression vector containing a 5' splice site in the 3'UTR. In both systems, coexpression of Rev enhanced cytoplasmic expression from vectors containing the RRE even when the RRE and the inhibitory 5' splice site were separated by up to 1,000 nucleotides. In addition, multiple copies of a 5' splice site in a 3'UTR were shown to act synergistically, and this effect could also be moderated by the interaction of Rev and the RRE. These studies provide additional evidence that at least one mechanism of Rev action is through interactions with the splicing machinery. We have previously shown that base pairing between the U1 small nuclear RNA and a 3'UTR 5' splice site is required for inhibition of gene expression. However, experiments by J. Kjems and P. A. Sharp (J. Virol. 67:4769-4776, 1993) have suggested that Rev acts on spliceosome assembly at a stage after binding of the U1 small nuclear ribonucleoprotein to the 5' splice site. This finding suggests that binding of additional small nuclear ribonucleoproteins, as well as other splicing factors, may be necessary for the inhibitory action of a 3'UTR 5' splice site. These data also suggest that expression of the papillomavirus late genes in terminally differentiated keratinocytes can be regulated by a viral or cellular Rev-like activity.