Differential gene expression in the developing mouse ureter

In many instances, kidney dysgenesis results as a secondary consequence to defects in the development of the ureter. Through the use of mouse genetics a number of genes associated with such malformations have been identified, however, the cause of many other abnormalities remain unknown. In order to identify novel genes involved in ureter development we compared gene expression in embryonic day (E) 12.5, E15.5 and postnatal day (P) 75 ureters using the Compugen mouse long oligo microarrays. A total of 248 genes were dynamically upregulated and 208 downregulated between E12.5 and P75. At E12.5, when the mouse ureter is comprised of a simple cuboidal epithelium surrounded by ureteric mesenchyme, genes previously reported to be expressed in the ureteric mesenchyme, foxC1 and foxC2 were upregulated. By E15.5 the epithelial layer develops into urothelium, impermeable to urine, and smooth muscle develops for the peristaltic movement of urine towards the bladder. The development of these two cell types coincided with the upregulation of UPIIIa, RAB27b and PPAR gamma reported to be expressed in the urothelium, and several muscle genes, Acta1, Tnnt2, Myocd, and Tpm2. In situ hybridization identified several novel genes with spatial expression within the smooth muscle, Acta1; ureteric mesenchyme and smooth muscle, Thbs2 and Co15a2; and urothelium, Kcnj8 and Adh1. This study marks the first known report defining global gene expression of the developing mouse ureter and will provide insight into the molecular mechanisms underlying kidney and lower urinary tract malformations. (c) 2005 Elsevier B.V. All rights reserved.

Spatial gene expression in the T-stage mouse metanephros

The E11.5 mouse metanephros is comprised of a T-stage ureteric epithelial tubule sub-divided into tip and trunk cells surrounded by metanephric mesenchyme (MM). Tip cells are induced to undergo branching morphogenesis by the MM. In contrast, signals within the mesenchyme surrounding the trunk prevent ectopic branching of this region. In order to identify novel genes involved in the molecular regulation of branching morphogenesis we compared the gene expression profiles of isolated tip, trunk and MM cells using Compugen mouse long oligo microarrays. We identified genes enriched in the tip epithelium, sim-1, Arg2, Tacstd1, Crlf-1 and BMP7; genes enriched in the trunk epithelium, Innp1, Itm2b, Mkrn1, SPARC, Emu2 and Gsta3 and genes spatially restricted to the mesenchyme surrounding the trunk, CSPG2 and CV-2, with overlapping and complimentary expression to BMP4, respectively. This study has identified genes spatially expressed in regions of the developing kidney involved in branching morphogenesis, nephrogenesis and the development of the collecting duct system, calyces, renal pelvis and ureter. (c) 2006 Elsevier B.V. All rights reserved.

Optical encoding of microbeads for gene screening: alternatives to microarrays

Rapid access to genetic information is central to the revolution presently occurring in the pharmaceutical industry, particularly In relation to novel drug target identification and drug development. Genetic variation, gene expression, gene function and gene structure are just some of the important research areas requiring efficient methods of DNA screening. Here, we highlight state-of-the-art techniques and devices for gene screening that promise cheaper and higher-throughput yields than currently achieved with DNA microarrays. We include an overview of existing and proposed bead-based strategies designed to dramatically increase the number of probes that can be interrogated in one assay. We focus, in particular, on the issue of encoding and/or decoding (bar-coding) large bead-based libraries for HTS.

Application of DNA microarrays to study human alcoholism

An emerging idea is that long-term alcohol abuse results in changes in gene expression in the brain and that these changes are responsible at least partly for alcohol tolerance, dependence and neurotoxicity, The overall goal of our research is to identify genes which are differentia[ly expressed in the brains of well-characterized human alcoholics as compared with non-alcoholics. This should identify as-yet-unknown alcohol-responsive genes, and may well confirm changes in the expression of genes which have been delineated in animal models of alcohol abuse. Cases were carefully selected and samples pooled on the basis of relevant criteria; differential expression was monitored by microarray hybridization. The inherent diversity of human alcoholics can be exploited to identify genes associated with specific pathological processes, as well as to assess the effects of concomitant disease, severity of brain damage, drinking behavior, and factors such as gender and smoking history. initial results show selective changes in gene expression in alcoholics; of particular importance is a coordinated reduction in genes coding for myelin components, Copyright (C) 2001 National Science Council, ROC and S. Karger AG, Basel.

Model-based clustering in gene expression microarrays: An application to breast cancer data

In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.

Searching oligo sets of human chromosome 12 using evolutionary strategies

DNA Microarray is a powerful tool to measure the level of a mixed population of nucleic acids at one time, which has great impact in many aspects of life sciences research. In order to distinguish nucleic acids with very similar composition by hybridization, it is necessary to design microarray probes with high specificities and sensitivities. Highly specific probes correspond to probes having unique DNA sequences; whereas highly sensitive probes correspond to those with melting temperature within a desired range and having no secondary structure. The selection of these probes from a set of functional DNA sequences (exons) constitutes a computationally expensive discrete non-linear search problem. We delegate the search task to a simple yet effective Evolution Strategy algorithm. The computational efficiency is also greatly improved by making use of an available bioinformatics tool.

The potential of microarrays to assist shrimp breeding and production: a review

The shrimp aquaculture industry is a relatively new livestock industry, having developed over the past 30 years. Thus, it is poised to take advantage of new technologies from the outset of selective breeding programs. This contrasts with long established livestock industries, where there are already highly specialised breeds. This review focuses specifically on the potential application of microarrays to shrimp breeding. Potential applications of microarrays in selective breeding programs are summarised. Microarrays can be used as a rapid means to generate molecular markers for genetic linkage mapping, and genetic maps have been constructed for yeast, Arabidopsis and barley using microarray technology. Microarrays can also be used in the hunt for candidate genes affecting particular traits, leading to development of perfect markers for these traits (i.e. causative mutations). However, this requires that microarray analysis be combined with genetic linkage mapping, and that substantial genomic information is available for the species in question. A novel application of microarrays is to treat gene expression as a quantitative trait in itself and to combine this with linkage mapping to identify quantitative trait loci controlling the levels of gene expression; this approach may identify higher level regulatory genes in specific pathways. Finally, patterns of gene expression observed using microarrays may themselves be treated as phenotypic traits in selection programs (e.g. a particular pattern of gene expression might be indicative of a disease tolerant individual). Microarrays are now being developed for a number of shrimp species in laboratories around the world, primarily with a focus on identifying genes involved in the immune response. However, at present, there is no central repository of shrimp genomic information, which limits the rate at which shrimp genomic research can be progressed. The application of microarrays to shrimp breeding will be extremely limited until there is a shared repository of genomic information for shrimp, and the collective will and resources to develop comprehensive genomic tools for shrimp.

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays

Motivation: An important problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. We provide a straightforward and easily implemented method for estimating the posterior probability that an individual gene is null. The problem can be expressed in a two-component mixture framework, using an empirical Bayes approach. Current methods of implementing this approach either have some limitations due to the minimal assumptions made or with more specific assumptions are computationally intensive. Results: By converting to a z-score the value of the test statistic used to test the significance of each gene, we propose a simple two-component normal mixture that models adequately the distribution of this score. The usefulness of our approach is demonstrated on three real datasets.

Mixture models for detecting differentially expressed genes in microarrays

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

Searching oligo sets of human chromosome 12 using evolutionary strategies

DNA microarray is a powerful tool to measure the level of a mixed population of nucleic acids at one time, which has great impact in many aspects of life sciences research. In order to distinguish nucleic acids with very similar composition by hybridization, it is necessary to design probes with high specificities, i.e. uniqueness, and also sensitivities, i.e., suitable melting temperature and no secondary structure. We make use of available biology tools to gain necessary sequence information of human chromosome 12, and combined with evolutionary strategy (ES) to find unique subsequences representing all predicted exons. The results are presented and discussed.

Enhanced downregulation of the p75 nerve growth factor receptor by cholesteryl and bis-cholesteryl antisense oligonucleotides

The effects of conjugating cholesterol to either or both ends of a phosphorothioate (PS) oligonucleotide were analyzed in terms of cellular uptake and antisense efficacy. The oligo sequence was directed against the p75 nerve growth factor receptor (p75), and was tested in differentiated PC12 cells, which express high levels of this protein. The addition of a single cholesteryl group to the 5'-end significantly increased cellular uptake and improved p75 mRNA downregulation compared with the unmodified PS oligo, However, only a minor degree of downregulation of p75 protein was obtained with 5' cholesteryl oligos, Three different linkers was used to attach the 5' cholesteryl group but were found not to have any impact on efficacy. Addition of a single cholesteryl group to the 3'-end led to greater p75 mRNA downregulation (31%) and p75 protein downregulation (28%) than occurred with the 5' cholesteryl oligos. The biggest improvement in antisense efficacy, both at the mRNA and protein levels, was obtained from the conjugation of cholesterol to both ends of the oligo. One of the bis-cholesteryl oligos was nearly as effective as cycloheximide at decreasing synthesis of p75, The bis-cholesteryl oligos also displayed significant efficacy at 1 mu M, whereas the other oligos required 5 mu M to be effective. The enhanced efficacy of bis-cholesteryl oligos is likely to be due to a combination of enhanced cellular uptake and resistance to both 5' and 3' exonucleases.

Coordinated plant defense responses in Arabidopsis revealed by microarray analysis

Disease resistance is associated with a plant defense response that involves an integrated set of signal transduction pathways. Changes in the expression patterns of 2.375 selected genes were examined simultaneously by cDNA microarray analysis in Arabidopsis thaliana after inoculation with an incompatible fungal pathogen Alternaria brassicicola or treatment with the defense-related signaling molecules salicylic acid (SA), methyl jasmonate (MJ), or ethylene, Substantial changes (up- and down-regulation) in the steady-state abundance of 705 mRNAs were observed in response to one or more of the treatments, including known and putative defense-related genes and 106 genes with no previously described function or homology, In leaf tissue inoculated with A. brassicicola, the abundance of 168 mRNAs was increased more than 2.5-fold, whereas that of 39 mRNAs was reduced. Similarly, the abundance of 192, 221, and 55 mRNAs was highly (>2.5-fold) increased after treatment with SA, MJ, and ethylene, respectively. Data analysis revealed a surprising level of coordinated defense responses, including 169 mRNAs regulated by multiple treatments/defense pathways. The largest number of genes coinduced (one of four induced genes) and corepressed was found after treatments with SA and MJ. In addition, 50% of the genes induced by ethylene treatment were also induced by MJ treatment. These results indicated the existence of a substantial network of regulatory interactions and coordination occurring during plant defense among the different defense signaling pathways, notably between the salicylate and jasmonate pathways that were previously thought to act in an antagonistic fashion.