Three microarray platforms: an analysis of their concordance in profiling gene expression

BACKGROUND: Microarrays for the analysis of gene expression are of three different types: short oligonucleotide (25–30 base), long oligonucleotide (50–80 base), and cDNA (highly variable in length). The short oligonucleotide and cDNA arrays have been the mainstay of expression analysis to date, but long oligonucleotide platforms are gaining in popularity and will probably replace cDNA arrays. As part of a validation study for the long oligonucleotide arrays, we compared and contrasted expression profiles from the three formats, testing RNA from six different cell lines against a universal reference standard. RESULTS: The three platforms had 6430 genes in common. In general, correlation of gene expression levels across the platforms was good when defined by concordance in the direction of expression difference (upregulation or downregulation), scatter plot analysis, principal component analysis, cell line correlation or quantitative RT-PCR. The overall correlations (r values) between platforms were in the range 0.7 to 0.8, as determined by analysis of scatter plots. When concordance was measured for expression ratios significant at p-values of <0.05 and at expression threshold levels of 1.5 and 2-fold, the agreement among the platforms was very high, ranging from 93% to 100%. CONCLUSION: Our results indicate that the long oligonucleotide platform is highly suitable for expression analysis and compares favorably with the cDNA and short oligonucleotide varieties. All three platforms can give similar and reproducible results if the criterion is the direction of change in gene expression and minimal emphasis is placed on the magnitude of change

The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

Reproducibility is a fundamental requirement in scientific experiments and clinical contexts. Recent publications raise concerns about the reliability of microarray technology because of the apparent lack of agreement between lists of differentially expressed genes (DEGs). In this study we demonstrate that (1) such discordance may stem from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion, the lists become much more reproducible, especially when fewer genes are selected; and (3) the instability of short DEG lists based on P cutoffs is an expected mathematical consequence of the high variability of the t-values. We recommend the use of FC ranking plus a non-stringent P cutoff as a baseline practice in order to generate more reproducible DEG lists. The FC criterion enhances reproducibility while the P criterion balances sensitivity and specificity

The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

<p>Abstract</p> <p>Background</p> <p>Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists.</p> <p>Results</p> <p>Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan – the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (<it>P</it>) derived from widely used simple <it>t</it>-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent <it>P</it>-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on <it>P</it>-value ranking is an expected mathematical consequence of the high variability of the <it>t</it>-values; the more stringent the <it>P</it>-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations.</p> <p>Conclusion</p> <p>We recommend the use of FC-ranking plus a non-stringent <it>P </it>cutoff as a straightforward and baseline practice in order to generate more reproducible DEG lists. Specifically, the <it>P</it>-value cutoff should not be stringent (too small) and FC should be as large as possible. Our results provide practical guidance to choose the appropriate FC and <it>P</it>-value cutoffs when selecting a given number of DEGs. The FC criterion enhances reproducibility, whereas the <it>P </it>criterion balances sensitivity and specificity.</p

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Inhibition of Mitochondrial Complex III Blocks Neuronal Differentiation and Maintains Embryonic Stem Cell Pluripotency

The mitochondrion is emerging as a key organelle in stem cell biology, acting as a regulator of stem cell pluripotency and differentiation. In this study we sought to understand the effect of mitochondrial complex III inhibition during neuronal differentiation of mouse embryonic stem cells. When exposed to antimycin A, a specific complex III inhibitor, embryonic stem cells failed to differentiate into dopaminergic neurons, maintaining high Oct4 levels even when subjected to a specific differentiation protocol. Mitochondrial inhibition affected distinct populations of cells present in culture, inducing cell loss in differentiated cells, but not inducing apoptosis in mouse embryonic stem cells. A reduction in overall proliferation rate was observed, corresponding to a slight arrest in S phase. Moreover, antimycin A treatment induced a consistent increase in HIF-1α protein levels. The present work demonstrates that mitochondrial metabolism is critical for neuronal differentiation and emphasizes that modulation of mitochondrial functions through pharmacological approaches can be useful in the context of controlling stem cell maintenance/ differentiation.Fundação para a Ciência e a Tecnologia (FCT) Portugal for grant support (PTDC/EBB-EBI/101114/2008, PTDC/EBB-EBI/ 120634/2010 and PDTC/QUI-BIQ/120652/2010 co-funded by Compete/FEDER/National Funds; and a PhD scholarship attributed to SP (SFRH/BD/ 37933/2007). Center for Neuroscience and Cell Biology (CNC) funding is also supported by FCT (PEst-C/SAU/LA0001/2011). EA’s work was supported by the Swedish Foundation for Strategic Research (SRL Program), Swedish Research Council (DBRM), Karolinska Institutet (SFO Thematic Center in Stem Cells and Regenerative Medicine), and Hjärnfonden

Identification of EpCAM as a Molecular Target of Prostate Cancer Stroma

To delineate the molecular changes that occur in the tumor microenvironment, we previously performed global transcript analysis of human prostate cancer specimens using tissue microdissection and expression microarrays. Epithelial and stromal compartments were individually studied in both tumor and normal fields. Tumor-associated stroma showed a distinctly different expression pattern compared with normal stroma, having 44 differentially expressed transcripts, the majority of which were up-regulated. In the present study, one of the up-regulated transcripts, epithelial cell adhesion activating molecule, was further evaluated at the protein level in 20 prostate cancer cases using immunohistochemistry and a histomathematical analysis strategy. The epithelial cell adhesion activating molecule showed a 76-fold expression increase in the tumor-associated stroma, as compared with matched normal stroma. Moreover, Gleason 4 or 5 tumor stroma was increased 170-fold relative to matched normal stroma, whereas the Gleason 3 tumor area showed only a 36-fold increase, indicating a positive correlation with Gleason tumor grade. Since the stromal compartment may be particularly accessible to vascular-delivered agents, epithelial cell adhesion activating molecule could become a valuable molecular target for imaging or treatment of prostate cancer