GEPIS--quantitative gene expression profiling in normal and cancer tissues

MOTIVATION: Expression profiling in diverse tissues is fundamental to understanding gene function as well as therapeutic target identification. The vast collection of expressed sequence tags (ESTs) and the associated tissue source information provides an attractive opportunity for studying gene expression. RESULTS: To facilitate EST-based expression analysis, we developed GEPIS (gene expression profiling in silico), a tool that integrates EST and tissue source information to compute gene expression patterns in a large panel of normal and tumor samples. We found EST-based expression patterns to be consistent with published papers as well as our own experimental results. We also built a GEPIS Regional Atlas that depicts expression characteristics of all genes in a selected genomic region. This program can be adapted for large-scale screening for genes with desirable expression patterns, as illustrated by our large-scale mining for tissue- and tumor-specific genes. AVAILABILITY: The email server version of the GEPIS application is freely available at http://share.gene.com/share/gepis. An interactive version of GEPIS will soon be freely available at http://www.cgl.ucsf.edu/Research/genentech/gepis/. The source code, modules, data and gene lists can be downloaded at http://share.gene.com/share/gepis.     

基于基因表达谱的疾病亚型特征基因挖掘方法

在本研究中,提出了一种基于基因表达谱的疾病亚型特征基因挖掘方法,该方法基于过滤后基因表达谱,融合无监督聚类识别疾病亚型技术和提出的衡量特征基因对疾病亚型鉴别能力的模式质量测度,以嵌入的方式实现特征基因挖掘。最后将提出的方法应用于40例结肠癌组织与22例正常结肠组织中2000个基因的表达谱实验数据,结果显示:提出的方法是一种可行的疾病亚型特征基因挖掘方法,方法的优势在于可并行实现疾病亚型划分和特征基因识别。     

Analysis of gene expression profiles of gastric normal and cancer tissues by SAGE

In an attempt to understand the molecular bases of gastric cancer progression, we have analyzed the differentially expressed genes in gastric cancer by SAGE. Four SAGE cDNA tag libraries were constructed from two sets of gastric cancer and normal tissues and 241,127 tags were obtained. By comparing the tags from cancer and normal tissues, 414 differentially expressed tags, representing 383 genes, were identified in cancer tissues (p 相似文献   

Early modifications of gene expression induced in liver by azo-dye diet

The expression and regulation of the phosphoenolpyruvate carboxykinase gene were not grossly modified by feeding rats a 3'-methyl-4-(dimethylamino)azobenzene-containing diet despite maximum expression of the L-type pyruvate kinase gene being dramatically reduced as early as the 24th hour of the carcinogenic diet. Inhibition of aldolase B mRNA synthesis occurred more slowly, being maximum at the 3rd day. After stopping administration of the carcinogen, a very rapid, but transient increase of the L-type pyruvate kinase mRNA was observed at the 24th hour, whereas aldolase B mRNA increased only slowly. The amount of aldolase A mRNA fell quickly after termination of carcinogen administration, levels being normal at the 2nd-3rd day. At this time, the histological structure of the liver was indistinguishable from that of animals still receiving the azo-dye diet. It appears, therefore, that in the rat both administration and withdrawal of the azo-dye carcinogen induce rapid modifications of the expression of some genes, before any cellular modification is distinguishable.     

Learning rule-based models of biological process from gene expression time profiles using gene ontology

MOTIVATION: Microarray technology enables large-scale inference of the participation of genes in biological process from similar expression profiles. Our aim is to induce classificatory models from expression data and biological knowledge that can automatically associate genes with novel hypotheses of biological process. RESULTS: We report a systematic supervised learning approach to predicting biological process from time series of gene expression data and biological knowledge. Biological knowledge is expressed using gene ontology and this knowledge is associated with discriminatory expression-based features to form minimal decision rules. The resulting rule model is first evaluated on genes coding for proteins with known biological process roles using cross validation. Then it is used to generate hypotheses for genes for which no knowledge of participation in biological process could be found. The theoretical foundation for the methodology based on rough sets is outlined in the paper, and its practical application demonstrated on a data set previously published by Cho et al. (Nat. Genet., 27, 48-54, 2001). AVAILABILITY: The Rosetta system is available at http://www.idi.ntnu.no/~aleks/rosetta. SUPPLEMENTARY INFORMATION: http://www.lcb.uu.se/~hvidsten/bioinf_cho/     

Finding distinct biclusters from background in gene expression matrices

Biclustering, or the discovery of subsets of samples and genes that are homogeneous and distinct from the background, has become an important technique in analyzing current microarray datasets. Most existing biclustering methods define a bicluster type as a fixed (predefined) pattern and then trying to get results in some searching process. In this work, we propose a novel method for finding biclusters or 2-dimensional patterns that are significantly distinct from the background without the need for pre-defining a pattern within the bicluster. The method named Distinct 2-Dimensional Pattern Finder (D2D) is composed of an iterative reordering step of the rows and columns in the matrix using a new similarity measure, and a flexible scanning-and-growing step to identify the biclusters. Experiments on a large variety of simulation data show that the method works consistently well under different conditions, whereas the existing methods compared may work well under some certain conditions but fail under some other conditions. The impact of noise levels, overlapping degrees between clusters and different setting of parameters were also investigated, which indicated that the D2D method is robust against these factors. The proposed D2D method can efficiently discover many different types of biclusters given that they have distinctive features from the background. The computer program is available upon request.     

Allele-specific gene expression and epigenetic modifications and their application to understanding inheritance and cancer

Epigenetic information is characterized by its plasticity during development and differentiation as well as its stable transmission during mitotic cell divisions in somatic tissues. This duality contrasts to genetic information, which is essentially static and identical in every cell in an organism with only a few exceptions such as immunoglobulin genes in lymphocytes. Epigenetics is traditionally perceived as a means to regulate gene expression without a change in DNA sequence. This, however, does not exclude a potential role for genetic variations in providing differential backgrounds on which epigenetic modulations and their regulatory consequences are achieved. An effective approach to investigating the interplay between genetic variations and epigenetic variations is through allele-specific analysis of epigenetics and gene expression. Such studies have generated many new insights into functions of genetic variations, mechanisms of gene expression regulation, and the role of mutations and epigenetic alterations in human cancer. This article is part of a Special Issue entitled: Chromatin in time and space.     

Period gene expression in mouse endocrine tissues

Circadian rhythms are generated by the oscillating expression of the Per1 and Per2 genes, which are expressed not only in the central brain pacemaker but also in peripheral tissues. Hormones are likely to coordinate physiological function in time. We performed in situ hybridization to localize mPer1 and mPer2 mRNA to particular cell types and tissue compartments in adrenal, thyroid, and testis. BALB/c mice maintained in a 12:12-h light-dark cycle expressed mPer1 in adrenal medulla, particularly in late afternoon and early night. mPer2 mRNA was more intensely expressed in adrenal cortex, especially in afternoon and evening. mPer1 mRNA was detected in thyroid. mPer1 was found in some but not all seminiferous tubules of each mouse at all times of day. Quantitation in C57BL/6 mice revealed a significant increase in the number of heavily labeled seminiferous tubules early in the night. Consistent with in situ hybridization, immunocytochemistry showed PER1 protein in spermatocytes and spermatids (spermatogenic stages VII-XII). Staining in spermatogonia and interstitial cells was inconsistent. Double labeling with 5'-bromodeoxyuridine showed PER1 expression first occurring 5 days after DNA replication. We conclude that mPeriod genes are expressed in peripheral endocrine glands. Central regulation, adenohypophyseal control, and functional importance of expression and phase remain to be elucidated.     

IL-1 gene expression in lymphoid tissues

We examined the expression of IL-1 mRNA in vivo by in situ hybridization. RNA probes for murine IL-1 alpha and IL-1 beta were used to detect IL-1 mRNA in frozen sections of spleen, lymph node, and thymus of mice injected with Salmonella typhi LPS or SRBC. No IL-1 was detected in lymphoid tissues from un-injected mice. This lack of expression correlated with the absence of IL-1 biologic activity. However, after LPS injection, IL-1 alpha and beta mRNA expression was found in macrophages of the red pulp and marginal zone of the spleen. The periarteriolar lymphoid sheath contained cells that only expressed IL-1 beta mRNA. These cells were not lymphocytes and did not stain with the macrophage marker F4/80. A similar cellular response was found after SRBC injection. Scattered macrophages in lymph nodes and thymus were positive, but only after LPS or SRBC injection. The spleens of mice injected with LPS had megakaryocytes containing IL-1 mRNA.     

Finding new posttranslational modifications in salivary proline-rich proteins

Proline-rich proteins (PRPs) are the most complex family of salivary peptides with distinct isoforms and PTMs. Up to date, only the serine phosphorylation at positions 8, 17, and 22 have been experimentally observed on acidic PRP (aPRPs), and at position 8 on basic PRP1 and 2. The presence of a glucoronyl group at Ser17 was also noticed on aPRP. The main goal of this study was to identify new PTMs and distinct isoforms of salivary PRPs using LC-MALDI-TOF/TOF. Through the salivary peptidome characterization of 20 different subjects from Control, Diabetic, and Head and Neck Cancer groups, it was possible to identify the following species: (i) N-glycosylation sites: two in basic proline-rich protein 2 (bPRP2), one in bPRP3 and one in bPRP4; (ii) O-glycosylation sites: two in bPRP2 and one in aPRP; (iii) other terminal monosaccharide sites: six in bPRP1, two in bPRP2 and two in bPRP3; (iv) other modifications such as N-terminal pyro-Glu (two in bPRP1, six in bPRP2, eight in bPRP3 and nine in bPRP4); (v) phosphorylation in serine, three in bPRP1, one in bPRP2, one in bPRP3 and one in aPRP1; (vi) bPRP1 (allele S, allele M and variant CP5) and bPRP4 (allele M). In summary, salivary peptidome data analysis allowed the identification of 45 new PRP-modified residues, mainly due to glycosylation, phosphorylation and conversion of Gln to pyro-Glu. Moreover, comparing all subject groups, it was noticed a predominance of N-acetyl hexosamine modification on bPRPs in the Head and Neck Cancer patients.     

Finding gene regulatory network candidates using the gene expression knowledge base

Background

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of ‘omics’ data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis.

Results

We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions.

Conclusions

Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0386-y) contains supplementary material, which is available to authorized users.