Illumina Microarray Platform Research Articles

Concordance among digital gene expression, microarrays, and qPCR when measuring differential expression of microRNAs

Profiling microRNA (miRNA) expression is of widespread interest given the critical role of miRNAs in many cellular functions. Profiling can be achieved via hybridization-based (microarrays), sequencing-based, or amplification-based (quantitative reverse transcription-PCR, qPCR) technologies. Among these, microarrays face the significant challenge of accurately distinguishing between mature and immature miRNA forms, and different vendors have developed different methods to meet this challenge. Here we measure differential miRNA expression using the Affymetrix, Agilent, and Illumina microarray platforms, as well as qPCR (Applied Biosystems) and ultra high-throughput sequencing (Illumina). We show that the differential expression measurements are more divergent when the three types of microarrays are compared than when the Agilent microarray, qPCR, and sequencing technology measurements are compared, which exhibit a good overall concordance.

Alteration of transcriptional profile in human bronchial epithelial cells induced by cigarette smoke condensate

Despite the significance of cigarette smoke for carcinogenesis, the molecular mechanisms that lead to increased susceptibility of human cancers are not well-understood. In our present study, the oncogenic transforming effects of cigarette smoke condensate (CSC) were examined using papillomavirus-immortalized human bronchial epithelial cells (BEP2D). Growth kinetics, saturation density, resistance to serum-induced terminal differentiation, anchorage-independent growth and tumorigenicity in nude mice were used to investigate the various stages of transformation in BEP2D cells. Illumina microarray platforms were used to explore the CSC-induced alteration of global mRNA expression profiles of the earlier period and the advanced stage of CSC-treated BEP2D cells. We showed here that a series of sequential steps arose among CSC-treated immortalized human bronchial epithelial cells, including altered growth kinetics, resistance to serum-induced terminal differentiation, and anchorage-independence growth. In the earlier period of CSC treatment, 265 genes were down-regulated and 63 genes were up-regulated, respectively, and in the advanced stage of CSC treatment, 313 genes were down-regulated and 145 genes were up-regulated, respectively. Notably, among those genes, the expression of some of imprinted genes such as IGF2, NDN, H19 and MEG3 were all silenced or down-regulated in CSC-treated cells. These genes reactivated after 5 μM 5-aza-2-deoxycytidine (5-aza-dC) treatment. These results demonstrated that long-term treatment of human bronchial epithelial cells with CSC may adversely affect their genetic and epigenetic integrity and lead to further transformation.

Model-based variance-stabilizing transformation for Illumina microarray data

Variance stabilization is a step in the preprocessing of microarray data that can greatly benefit the performance of subsequent statistical modeling and inference. Due to the often limited number of technical replicates for Affymetrix and cDNA arrays, achieving variance stabilization can be difficult. Although the Illumina microarray platform provides a larger number of technical replicates on each array (usually over 30 randomly distributed beads per probe), these replicates have not been leveraged in the current log2 data transformation process. We devised a variance-stabilizing transformation (VST) method that takes advantage of the technical replicates available on an Illumina microarray. We have compared VST with log2 and Variance-stabilizing normalization (VSN) by using the Kruglyak bead-level data (2006) and Barnes titration data (2005). The results of the Kruglyak data suggest that VST stabilizes variances of bead-replicates within an array. The results of the Barnes data show that VST can improve the detection of differentially expressed genes and reduce false-positive identifications. We conclude that although both VST and VSN are built upon the same model of measurement noise, VST stabilizes the variance better and more efficiently for the Illumina platform by leveraging the availability of a larger number of within-array replicates. The algorithms and Supplementary Data are included in the lumi package of Bioconductor, available at: www.bioconductor.org.

Whole genome expression profiling reveals a significant role for immune function in human abdominal aortic aneurysms

BackgroundAbdominal aortic aneurysms are a common disorder with an incompletely understood etiology. We used Illumina and Affymetrix microarray platforms to generate global gene expression profiles for both aneurysmal (AAA) and non-aneurysmal abdominal aorta, and identified genes that were significantly differentially expressed between cases and controls.ResultsAffymetrix and Illumina arrays included 18,057 genes in common; 11,542 (64%) of these genes were considered to be expressed in either aneurysmal or normal abdominal aorta. There were 3,274 differentially expressed genes with a false discovery rate (FDR) ≤ 0.05. Many of these genes were not previously known to be involved in AAA, including SOST and RUNX3, which were confirmed using Q-RT-PCR (Pearson correlation coefficient for microarray and Q-RT-PCR data = 0.89; p-values for differences in expression between AAA and controls for SOST: 4.87 × 10-4 and for RUNX3: 4.33 × 10-5). Analysis of biological pathways, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), indicated extreme overrepresentation of immune related categories. The enriched categories included the GO category Immune Response (GO:0006955; FDR = 2.1 × 10-14), and the KEGG pathways natural killer cell mediated cytotoxicity (hsa04650; FDR = 5.9 × 10-6) and leukocyte transendothelial migration (hsa04670; FDR = 1.1 × 10-5).ConclusionPrevious studies have provided evidence for the involvement of the immune system in AAA. The current expression analysis extends these findings by demonstrating broad coordinate gene expression in immunological pathways. A large number of genes involved in immune function were differentially expressed in AAA, and the pathway analysis gave these results a biological context. The data provide valuable insight for future studies to dissect the pathogenesis of human AAA. These pathways might also be used as targets for the development of therapeutic agents for AAA.