CiteULike: heliopais's Yang

Identification of transcription factor and microRNA binding sites in responsible to fetal alcohol syndrome

Guohua Wang — 2008-06-23T10:32:54-00:00

BMC Genomics, Vol. 9, No. Suppl 1. (2008)

This is a first report, using our MotifModeler informatics program, to simultaneously identify transcription factor (TF) and microRNA (miRNA) binding sites from gene expression microarray data. Based on the assumption that gene expression is controlled by combinatorial effects of transcription factors binding in the 5'-upstream regulatory region and miRNAs binding in the 3'-untranslated region (3'-UTR), we developed a model for (1) predicting the most influential cis-acting elements under a given biological condition, and (2) estimating the effects of those elements on gene expression levels. The regulatory regions, TF and miRNA, which mediate the differential genes expression in fetal alcohol syndrome were unknown; microarray data from alcohol exposure paradigm was used. The model predicted strong inhibitory effects of 5' cis-acting elements and stimulatory effects of 3'-UTR under alcohol treatment. Current predictive model derived a key hypothesis for the first time a novel role of miRNAs in gene expression changes associated with abnormal mouse embryo development after alcohol exposure. This suggests that disturbance of miRNA functions may contribute to the alcohol-induced developmental deficiencies.

A Twist Code Determines the Onset of Osteoblast Differentiation

Peter Bialek — 2008-04-25T13:17:16-00:00

Developmental Cell, Vol. 6, No. 3. (March 2004), pp. 423-435.

Runx2 is necessary and sufficient for osteoblast differentiation, yet its expression precedes the appearance of osteoblasts by 4 days. Here we show that Twist proteins transiently inhibit Runx2 function during skeletogenesis. Twist-1 and -2 are expressed in Runx2-expressing cells throughout the skeleton early during development, and osteoblast-specific gene expression occurs only after their expression decreases. Double heterozygotes for Twist-1 and Runx2 deletion have none of the skull abnormalities observed in Runx2+/- mice, a Twist-2 null background rescues the clavicle phenotype of Runx2+/- mice, and Twist-1 or -2 deficiency leads to premature osteoblast differentiation. Furthermore, Twist-1 overexpression inhibits osteoblast differentiation without affecting Runx2 expression. Twist proteins' antiosteogenic function is mediated by a novel domain, the Twist box, which interacts with the Runx2 DNA binding domain to inhibit its function. In vivo mutagenesis confirms the antiosteogenic function of the Twist box. Thus, relief of inhibition by Twist proteins is a mandatory event precluding osteoblast differentiation.

The Effect of Central Loops in miRNA:MRE Duplexes on the Efficiency of miRNA-Mediated Gene Regulation.

W Ye — 2008-03-18T02:56:30-00:00

PLoS ONE, Vol. 3, No. 3. (2008)

MicroRNAs (miRNAs) guide posttranscriptional repression of mRNAs. Hundreds of miRNAs have been identified but the target identification of mammalian mRNAs is still a difficult task due to a poor understanding of the interaction between miRNAs and the miRNA recognizing element (MRE). In recent research, the importance of the 5' end of the miRNA:MRE duplex has been emphasized and the effect of the tail region addressed, but the role of the central loop has largely remained unexplored. Here we examined the effect of the loop region in miRNA:MRE duplexes and found that the location of the central loop is one of the important factors affecting the efficiency of gene regulation mediated by miRNAs. It was further determined that the addition of a loop score combining both location and size as a new criterion for predicting MREs and their cognate miRNAs significantly decreased the false positive rates and increased the specificity of MRE prediction.

ADGO: analysis of differentially expressed gene sets using composite GO annotation

Dougu Nam — 2006-09-07T11:14:47-00:00

Bioinformatics, Vol. 22, No. 18. (15 September 2006), pp. 2249-2253.

Motivation: Genes are typically expressed in modular manners in biological processes. Recent studies reflect such features in analyzing gene expression patterns by directly scoring gene sets. Gene annotations have been used to define the gene sets, which have served to reveal specific biological themes from expression data. However, current annotations have limited analytical power, because they are classified by single categories providing only unary information for the gene sets. Results: Here we propose a method for discovering composite biological themes from expression data. We intersected two annotated gene sets from different categories of Gene Ontology (GO). We then scored the expression changes of all the single and intersected sets. In this way, we were able to uncover, for example, a gene set with the molecular function F and the cellular component C that showed significant expression change, while the changes in individual gene sets were not significant. We provided an exemplary analysis for HIV-1 immune response. In addition, we tested the method on 20 public datasets where we found many filtered' composite terms the number of which reached [~]34% (a strong criterion, 5% significance) of the number of significant unary terms on average. By using composite annotation, we can derive new and improved information about disease and biological processes from expression data. Availability: We provide a web application (ADGO: http://array.kobic.re.kr/ADGO) for the analysis of differentially expressed gene sets with composite GO annotations. The user can analyze Affymetrix and dual channel array (spotted cDNA and spotted oligo microarray) data for four species: human, mouse, rat and yeast. Contact: chu@kribb.re.kr Supplementary information: http://array.kobic.re.kr/ADGO 10.1093/bioinformatics/btl378

Within the fold: assessing differential expression measures and reproducibility in microarray assays

Ivana Yang — 2007-11-28T11:46:59-00:00

Genome Biology, Vol. 3, No. 11. (24 October 2002), pp. research0062.1-research0062.12.

BACKGROUND:'Fold-change' cutoffs have been widely used in microarray assays to identify genes that are differentially expressed between query and reference samples. More accurate measures of differential expression and effective data-normalization strategies are required to identify high-confidence sets of genes with biologically meaningful changes in transcription. Further, the analysis of a large number of expression profiles is facilitated by a common reference sample, the construction of which must be carefully addressed.RESULTS:We carried out a series of 'self-self' hybridizations in which aliquots of the same RNA sample were labeled separately with Cy3 and Cy5 fluorescent dyes and co-hybridized to the same microarray. From this, we can analyze the intensity-dependent behavior of microarray data, define a statistically significant measure of differential expression that exploits the structure of the fluorescent signals, and measure the inherent reproducibility of the technique. We also devised a simple procedure for identifying and eliminating low-quality data for replicates within and between slides. We examine the properties required of a universal reference RNA sample and show how pooling a small number of samples with a diverse representation of expressed genes can outperform more complex mixtures as a reference sample.CONCLUSION:Analysis of cell-line samples can identify systematic structure in measured gene-expression levels. A general procedure for analyzing cDNA microarray data is proposed and validated. We show that pooled reference samples should be based not only on the expression of individual genes in each cell line but also on the expression levels of genes within cell lines.