Mining co-regulated gene profiles for the detection of functional associations in gene expression data

MOTIVATION: Association pattern discovery (APD) methods have been successfully applied to gene expression data. They find groups of co-regulated genes in which the genes are either up- or down-regulated throughout the identified conditions. These methods, however, fail to identify similarly expressed genes whose expressions change between up- and down-regulation from one condition to another. In order to discover these hidden patterns, we propose the concept of mining co-regulated gene profiles. Co-regulated gene profiles contain two gene sets such that genes within the same set behave identically (up or down) while genes from different sets display contrary behavior. To reduce and group the large number of similar resulting patterns, we propose a new similarity measure that can be applied together with hierarchical clustering methods. RESULTS: We tested our proposed method on two well-known yeast microarray data sets. Our implementation mined the data effectively and discovered patterns of co-regulated genes that are hidden to traditional APD methods. The high content of biologically relevant information in these patterns is demonstrated by the significant enrichment of co-regulated genes with similar functions. Our experimental results show that the Mining Attribute Profile (MAP) method is an efficient tool for the analysis of gene expression data and competitive with bi-clustering techniques.     

Comparison of differential gene expression of hot and cold thyroid nodules with primary epithelial cell culture models by investigation of co-regulated gene sets

Both autonomously functioning thyroid nodules (AFTNs) and cold thyroid nodules (CTNs) are characterized by an increased proliferation, however, they have opposite functional activities. Therefore, with the aim to further understand the distinct molecular pathology of each entity and to discover common mechanisms like those leading to increased proliferation in both, AFTNs and CTNs, we now compared gene expression of AFTNs and CTNs with in vitro model systems (TSH-stimulated and ras-transfected primary cultures (PC)) whose gene expression patterns can be attributed to specific molecular alterations. Since combinations of co-regulated genes are more likely to reveal molecular mechanisms, we used a procedure which groups co-regulated genes within "gene sets". We found a co-regulated gene set in the AFTNs that overlaps with differential expression in TSH-stimulated PCs but not in CTNs or ras-transfected PCs. In addition to thyroid peroxidase and sialyltransferase 1, this set of co-regulated genes comprises metallothioneins and the G-protein-coupled receptor 56. Although their role in the thyroid is unknown so far, their appearance in one group indicates a functional relevance in TSH-TSH receptor-stimulated mechanisms. Furthermore, we identified down-regulated gene sets with concordant expression patterns in AFTNs, CTNs and ras-transfected PCs. However, these expression patterns are not of relevance in the TSH-stimulated PCs. These findings suggest that TSH-stimulated PCs can be used as a model of increased thyroid function (AFTNs), whereas the ras-transfected PCs better reflect the increased proliferation of both AFTNs and CTNs.     

Computational analysis of Ciona intestinalis operons

Operons are clusters of genes that are co-regulated from a common promoter. Operons are typically associated with prokaryotes, although a small number of eukaryotes have been shown to possess them. Among metazoans, operons have been extensively characterized in the nematode Caenorhabditis elegans in which ～15% of the total genes are organized into operons. The most recent genome assembly for the ascidian Ciona intestinalis placed ～20% of the genes (2909 total) into 1310 operons. The majority of these operons are composed of two genes, while the largest are composed of six. Here is reported a computational analysis of the genes that comprise the Ciona operons. Gene ontology (GO) terms were identified for about two-thirds of the operon-encoded genes. Using the extensive collection of public EST libraries, estimates of temporal patterns of gene expression were generated for the operon-encoded genes. Lastly, conservation of operons was analyzed by determining how many operon-encoded genes were present in the ascidian Ciona savignyi and whether these genes were organized in orthologous operons. Over 68% of the operon-encoded genes could be assigned one or more GO terms and 697 of the 1310 operons contained genes in which all genes had at least one GO term. Of these 697 operons, GO terms were shared by all of the genes within 146 individual operons, suggesting that most operons encode genes with unrelated functions. An analysis of operon gene expression from nine different EST libraries indicated that for 587 operons, all of the genes that comprise an individual operon were expressed together in at least one EST library, suggesting that these genes may be co-regulated. About 50% (74/146) of the operons with shared GO terms also showed evidence of gene co-regulation. Comparisons with the C. savignyi genome identified orthologs for 1907 of 2909 operon genes. About 38% (504/1310) of the operons are conserved between the two Ciona species. These results suggest that like C. elegans, operons in Ciona are comprised of a variety of genes that are not necessarily related in function. The genes in only 50% of the operons appear to be co-regulated, suggesting that more complex gene regulatory mechanisms are likely operating.     

Microarray phenotyping in Dictyostelium reveals a regulon of chemotaxis genes

MOTIVATION: Coordinate regulation of gene expression can provide information on gene function. To begin a large-scale analysis of Dictyostelium gene function, we clustered genes based on their expression in wild-type and mutant strains and analyzed their functions. RESULTS: We found 17 modes of wild-type gene expression and refined them into 57 submodes considering mutant data. Annotation analyses revealed correlations between co-expression and function and an unexpected correlation between expression and function of genes involved in various aspects of chemotaxis. Co-regulation of chemotaxis genes was also found in published data from neutrophils. To test the predictive power of the analysis, we examined the phenotypes of mutations in seven co-regulated genes that had no published role in chemotaxis. Six mutants exhibited chemotaxis defects, supporting the idea that function can be inferred from co-expression. The clustering and annotation analyses provide a public resource for Dictyostelium functional genomics.     

Combining pattern discovery and discriminant analysis to predict gene co-regulation

MOTIVATION: Several pattern discovery methods have been proposed to detect over-represented motifs in upstream sequences of co-regulated genes, and are for example used to predict cis-acting elements from clusters of co-expressed genes. The clusters to be analyzed are often noisy, containing a mixture of co-regulated and non-co-regulated genes. We propose a method to discriminate co-regulated from non-co-regulated genes on the basis of counts of pattern occurrences in their non-coding sequences. METHODS: String-based pattern discovery is combined with discriminant analysis to classify genes on the basis of putative regulatory motifs. RESULTS: The approach is evaluated by comparing the significance of patterns detected in annotated regulons (positive control), random gene selections (negative control) and high-throughput regulons (noisy data) from the yeast Saccharomyces cerevisiae. The classification is evaluated on the annotated regulons, and the robustness and rejection power is assessed with mixtures of co-regulated and random genes.     

拟南芥野生型与隐花素突变体光调节的蛋白质鉴定与聚类分析

光是控制植物生长发育十分重要的环境因子之一.隐花素是植物的蓝光受体,在植 物中调节多种光形态建成,包括抑制下胚轴的伸长、子叶的伸展和调节植物的开花时间 等,但隐花素依赖蓝光调节光形态建成的分子机制尚不清楚.本文采用比较蛋白质组学 方法研究了在持续蓝光和红光下生长的拟南芥隐花素双突变体cry1cry2和野生型幼苗的全蛋白图谱.采用基质辅助激光解吸飞行时间串联质谱(MALDI-TOF-TOF)进行肽质谱指纹图谱分析.在cry1cry2和野生型中鉴定了71个差异蛋白点.这些差异蛋白质反应光的变化可以形成6类,结果表明,光调节隐花素是通过控制许多相关基因的表达而实现的,为进一步研究拟南芥隐花素的光反应机制提供一些有用的信息.研究表明,蛋白质表达图谱可用于研究各种突变体在不同光照条件下光应答之间的关系.     

Embedding mRNA stability in correlation analysis of time-series gene expression data

Current methods for the identification of putatively co-regulated genes directly from gene expression time profiles are based on the similarity of the time profile. Such association metrics, despite their central role in gene network inference and machine learning, have largely ignored the impact of dynamics or variation in mRNA stability. Here we introduce a simple, but powerful, new similarity metric called lead-lag R(2) that successfully accounts for the properties of gene dynamics, including varying mRNA degradation and delays. Using yeast cell-cycle time-series gene expression data, we demonstrate that the predictive power of lead-lag R(2) for the identification of co-regulated genes is significantly higher than that of standard similarity measures, thus allowing the selection of a large number of entirely new putatively co-regulated genes. Furthermore, the lead-lag metric can also be used to uncover the relationship between gene expression time-series and the dynamics of formation of multiple protein complexes. Remarkably, we found a high lead-lag R(2) value among genes coding for a transient complex.     

The correlation of gene expression and co-regulated gene patterns in characteristic KEGG pathways

There is great interest in chromosome- and pathway-based techniques for genomics data analysis in the current work in order to understand the mechanism of disease. However, there are few studies addressing the abilities of machine learning methods in incorporating pathway information for analyzing microarray data. In this paper, we identified the characteristic pathways by combining the classification error rates of out-of-bag (OOB) in random forests with pathways information. At each characteristic pathway, the correlation of gene expression was studied and the co-regulated gene patterns in different biological conditions were mined by Mining Attribute Profile (MAP) algorithm. The discovered co-regulated gene patterns were clustered by the average-linkage hierarchical clustering technique. The results showed that the expression of genes at the same characteristic pathway were approximate. Furthermore, two characteristic pathways were discovered to present co-regulated gene patterns in which one contained 108 patterns and the other contained one pattern. The results of cluster analysis showed that the smallest similarity coefficient of clusters was more than 0.623, which indicated that the co-regulated patterns in different biological conditions were more approximate at the same characteristic pathway. The methods discussed in this paper can provide additional insight into the study of microarray data.