Evolutionary significance of gene expression divergence

Recent large-scale studies of evolutionary changes in gene expression among mammalian species have led to the proposal that gene expression divergence may be neutral with respect to organismic fitness. Here, we employ a comparative analysis of mammalian gene sequence divergence and gene expression divergence to test the hypothesis that the evolution of gene expression is predominantly neutral. Two models of neutral gene expression evolution are considered: 1-purely neutral evolution (i.e., no selective constraint) of gene expression levels and patterns and 2-neutral evolution accompanied by selective constraint. With respect to purely neutral evolution, levels of change in gene expression between human-mouse orthologs are correlated with levels of gene sequence divergence that are determined largely by purifying selection. In contrast, evolutionary changes of tissue-specific gene expression profiles do not show such a correlation with sequence divergence. However, divergence of both gene expression levels and profiles are significantly lower for orthologous human-mouse gene pairs than for pairs of randomly chosen human and mouse genes. These data clearly point to the action of selective constraint on gene expression divergence and are inconsistent with the purely neutral model; however, there is likely to be a neutral component in evolution of gene expression, particularly, in tissues where the expression of a given gene is low and functionally irrelevant. The model of neutral evolution with selective constraint predicts a regular, clock-like accumulation of gene expression divergence. However, relative rate tests of the divergence among human-mouse-rat orthologous gene sets reveal clock-like evolution for gene sequence divergence, and to a lesser extent for gene expression level divergence, but not for the divergence of tissue-specific gene expression profiles. Taken together, these results indicate that gene expression divergence is subject to the effects of purifying selective constraint and suggest that it might also be substantially influenced by positive Darwinian selection.     

Effect of FAK, DLC-1 gene expression on OVCAR-3 proliferation

The study investigates the effect of FAK, DLC-1 on OVCAR-3 proliferation. FAK gene siRNA vector recombinant plasmid was constructed using RNA interference technique. FAK gene-transfected OVCAR-3 cells, OVCAR-3 cells with DLC-1 gene expression, and OVCAR-3 cells with simultaneous expression of DLC-1 and FAK genes were obtained using gene transfection technology. In addition, siRNA control group and blank control were also given. Effect of FAK, DLC-1 gene expression on OVCAR-3 proliferation was examined by FCM and Cell Counting Kit-8 (CCK-8) methods. Results showed that DLC-1 gene high expression and FAK gene silencing, single silencing FAK gene, and single DLC-1 gene high expression in OVCAR-3 cells may decrease S and G2/M phase proportion of the cell cycle. Moreover, DLC-1 gene high expression and FAK gene silencing in OVCAR-3 cells can display the most significant effect. This confirmed that DLC-1 gene high expression and FAK gene silencing may significantly inhibit the OVCAR-3 cells proliferation. CCK-8 analysis showed that silence FAK gene exprssion or/and increasing DLC-1 gene expression may decrease OVCAR-3 growth rate. Moreover, simultaneous silence the exprssion of FAK gene and high expression of DLC-1 gene can display the most significant effect on OVCAR-3 growth. It can be concluded that downregulation of FAK gene expression or/and upregulation of DLC-1 gene expression can all inhibit the OVCAR-3 growth. Moreover, DLC-1 gene expression and FAK gene silencing can display the most marked inhibitory effect on the OVCAR-3 growth.     

Regulation of specific genes during the cell cycle. Utilization of homologous cDNAs and cloned sequences for studying histone gene expression in human cells

Evidence for differential gene expression during the cell cycle and approaches for studying cell-cycle-stage specific gene expression are summarized. Attention is focused on regulation of histone gene expression during the cell cycle of continuously dividing cells and after stimulation of nondividing cells to proliferate. The level(s) at which control of histone gene expression occurs and the possible involvement of chromosomal proteins in the regulation of histone gene expression are discussed. The preparation of cloned human histone sequences and their use in studying the structural and functional properties of human histone genes are presented. Index Entries: Cell cycle, gene regulation during; gene regulation, during the cell cycle; regulation of specific genes, during the cell cycle; DNAs, homologous, and histone gene expression; cloned DNAs, and histone gene expression; histone gene expression; gene expression, histone; cloned human histone sequences.     

Databases of free expression

The rapid development of microarray technologies has led to a similar progression in gene expression analysis methods, gene expression applications, and gene expression databases. Public gene expression databases enable any researcher to examine expression of their favorite genes across a wide variety of samples, download sample data for development of new analysis methods, or answer broad questions about gene expression regulation, among other applications. A wide variety of public gene expression databases exist, and they vary in their content, analysis capabilities, and ease of use. This review highlights the current features and describes examples of two broad categories of mammalian microarray databases: tissue gene expression databases and data warehouses.     

调控通路内基因表达的相关性分析

本研究从基因表达调控通路的角度分析了基因功能与基因表达之间的关系,利用7套酿酒酵母基因芯片表达谱数据和通路数据库（KEGG和CYGD）所提供的信息,应用我们研制的Genehub软件分析研究了同一基因表达调控通路内的基因在mRNA表达水平上的相关性,共涉及16条通路,495个基因。通过Pearson相关系数和Spearman相关系数两种相似性测度的分析,我们发现有94%（15条）的基因表达调控通路内的基因在大于等于4套的表达谱数据中是共表达的,以上结果从基因表达调控通路的角度,证实了基因功能与基因表达之间存在着一定的相关性。     

Low rates of expression profile divergence in highly expressed genes and tissue-specific genes during mammalian evolution

Evolutionary rates provide important information about the pattern and mechanism of evolution. Although the rate of gene sequence evolution has been well studied, the rate of gene expression evolution is poorly understood. In particular, it is unclear whether the gene expression level and tissue specificity influence the divergence of expression profiles between orthologous genes. Here we address this question using a microarray data set comprising the expression signals of 10,607 pairs of orthologous human and mouse genes from over 60 tissues per species. We show that the level of gene expression and the degree of tissue specificity are generally conserved between the human and mouse orthologs. The rate of gene expression profile change during evolution is negatively correlated with the level of gene expression, measured by either the average or the highest level among all tissues examined. This is analogous to the observation that the rate of gene (or protein) sequence evolution is negatively correlated with the gene expression level. The impacts of the degree of tissue specificity on the evolutionary rate of gene sequence and that of expression profile, however, are opposite. Highly tissue-specific genes tend to evolve rapidly at the gene sequence level but slowly at the expression profile level. Thus, different forces and selective constraints must underlie the evolution of gene sequence and that of gene expression.     

Organ-specific and dosage-dependent expression of a leaf/stem specific gene from potato after tagging and transfer into potato and tobacco plants.

ST-LS1, a single copy gene from potato displaying a leaf/stem specific gene expression, was tagged by an exon modification and introduced into both potato and tobacco cells using Agrobacterium vectors. After regeneration of whole plants, the expression of the tagged gene was analyzed with respect to its organ specificity and compared to the expression of the corresponding resident gene. The expression of the transferred gene in transgenic plants closely followed the expression of the resident gene. No marked influence of the plant species serving as host was observed. The level of expression of the introduced gene varied by a factor of at least 100 in independent transformants when normalized to the expression of the resident gene. Southern analysis performed on the transformed plants indicated a correlation between copy number of the introduced gene and its expression level. The activity of the tagged gene as well as of the resident gene was significantly inhibited by treatment of the transgenic plants with the herbicide norfluorazon, indicating that this gene activity is dependent on the presence of functional chloroplasts in the leaves.     

Triggering of apoptosis is not sufficient to induce human immunodeficiency virus gene expression

We examined whether there is any causative link between apoptosis and HIV gene expression elicited in response to ultraviolet light (UV) and ionizing radiation (IR). We found that both UV and IR activate HIV gene expression in human T lymphoblastoid 1G5 (HIVluc) cells, but with different kinetics and magnitudes. Treatment with either type of radiation resulted in increased apoptosis, which correlated closely with HIV gene expression. The involvement of caspases in the IR response was demonstrated by using zVAD-FMK and zDEVD-FMK caspase inhibitors; both apoptosis and HIV gene expression were inhibited to similar extent. Surprisingly, treatment of 1G5 cells with FAS antibody triggered apoptosis but did not increase HIV gene expression. A correlation between increased apoptosis and gene expression was also demonstrated in human carcinoma HIVcat/A549 cells with UV whereas IR triggered apoptosis but did not activate HIV gene expression. Most significantly, UV activation of HIV gene expression, and NF-kappa-B and p38 MAP kinase, both important for efficient HIV gene expression, were not affected by treatment with the zVAD-FMK and zDEVD-FMK inhibitors. Treatment of HIVcat/A549 cells with staurosporine or scrape-loading of cells with cytochrome c resulted in apoptosis but no increase in HIV gene expression. Altogether, a direct correlation exists between apoptosis and HIV gene expression in T-cells in response to both UV and IR but this is not the case in carcinoma cells. Triggering of apoptosis per se in either cell type does not necessarily result in increased HIV gene expression. Most importantly, the apoptotic and HIV gene expression responses elicited by UV are different to some extent and can be separated.     

Oligonucleotide-based strategies to reduce gene expression

Research on embryonic development and differentiation provides a sensitive, but challenging opportunity to use a variety of techniques designed to modulate gene expression. Changes in the expression of a single gene can alter levels of other genes and provide information on developmentally regulated gene expression pathways. The morphological consequences of altered gene expression can link gene expression to developmental fate. Oligonucleotide-based approaches offer a variety of means to potentially disrupt normal gene expression. The basis for some of these approaches is presented in this review.     

Wrestling with pleiotropy: genomic and topological analysis of the yeast gene expression network

The vast majority (>95%) of single-gene mutations in yeast affect not only the expression of the mutant gene, but also the expression of many other genes. These data suggest the presence of a previously uncharacterized "gene expression network"--a set of interactions between genes which dictate gene expression in the native cell environment. Here, we quantitatively analyze the gene expression network revealed by microarray expression data from 273 different yeast gene deletion mutants.(1) We find that gene expression interactions form a robust, error-tolerant "scale-free" network, similar to metabolic pathways(2) and artificial networks such as power grids and the internet.(3-5) Because the connectivity between genes in the gene expression network is unevenly distributed, a scale-free organization helps make organisms resistant to the deleterious effects of mutation, and is thus highly adaptive. The existence of a gene expression network poses practical considerations for the study of gene function, since most mutant phenotypes are the result of changes in the expression of many genes. Using principles of scale-free network topology, we propose that fragmenting the gene expression network via "genome-engineering" may be a viable and practical approach to isolating gene function.     

Monoallelic gene expression and its mechanisms

Although the majority of genes are expressed equally from both alleles, some genes are differentially expressed. Monoallelic gene expression, the differential gene expression of the alleles such as genomic imprinting, is reported in several organisms and plays significant roles in proper development and diversity in gene expression and phenotypic variation. Recent studies in flowering plants have greatly increased our understanding of the underlying mechanisms of monoallelic gene expression. They indicate that machineries of gene silencing such as DNA methylation, histone modifications, and noncoding RNAs function in monoallelic gene expression. A combination of genetics and high-throughput technologies expands the scope of study on monoallelic gene expression in flowering plants.     

Evolution of duplicate gene expression in polyploid and hybrid plants

Allopolyploidy is a prominent mode of speciation in flowering plants. On allopolyploidy, genomic changes can take place, including chromosomal rearrangement and changes in gene expression; these processes continue over evolutionary time. Recent studies of gene expression in polyploid and hybrid plants, reviewed here, have examined expression in natural polyploids and synthetic neopolyploids as well as in diploid and F(1) hybrids. Considerable changes in gene expression have been observed in allopolyploids, including up- or downregulation of expression in the polyploids compared with their parents, unequal expression of duplicated genes, and silencing of one copy. Genes in a variety of functional categories show altered expression, and the patterns vary considerably by gene. Some changes seem to be stochastic, whereas others are repeatable. Gene expression changes can be organ specific. Reciprocal silencing of duplicates in different organs has been observed, suggesting subfunctionalization and long-term retention of duplicates. It has become clear that hybridization has a much greater effect than chromosome doubling on gene expression in allopolyploids. Diploid and triploid F(1) hybrids can show alterations of expression levels compared with their parents. Parent-of-origin effects on gene expression have been examined, and loss of gene imprinting has been shown. Some gene expression changes in polyploids and hybrids can be correlated with phenotypic effects. Demonstrated mechanisms of gene expression changes include DNA methylation, histone modifications, and antisense RNA. Several hypotheses have been proposed for why gene expression is altered in allopolyploids and hybrids.     

生物信息学基因表达差异分析

基因的差异化表达由多种因素共同导致,并且与许多疾病的发生和发展有密切联系,对差异化表达的基因进行生物信息学以及生物统计学的分析对于研究细胞调节机制和疾病机理有着重要意义。目前,对差异化表达的基因有以下几种主流的研究方法：DNA微阵列（DNA microarray）,抑制性消减杂交（SSH）,基因表达连续性分析（SAGE）,代表性差异分析（RDA）,以及mRNA差异显示PCR（mRNA DDRT-PCR）。目前许多基因差异化表达数据是建立在时段（time series）基础上,因此对基于时间变化的基因差异化表达分析变得尤为重要。本文将对差异化表达基因的几种主流方法进行详细阐述,并介绍一种基于傅里叶函数的时段基因差异化表达分析。     

MATLAB 7.X生物信息工具箱的应用———基因表达图谱分析（4）*

基因表达图谱原则上可了解整体细胞基因表达的信息,是基因组功能分析的重要研究手段。MATLAB 7.X生物信息工具箱为基因表达谱数据的分析和处理提供了一个综合环境,通过众多统计函数和绘图函数的结合使用,过滤不合格的基因数据和噪声数据,从而对基因表达数据进行聚类分析和主成分分析,绘制相关的基因表达图谱,完成基因芯片数据表达图谱的分析,分析结果可视化程度高,图表清晰、直观。本文主要以酿酒酵母Saccharomyces cerevisiae为例,详细描述了利用MATLAB 7.X生物信息工具箱对其基因表达图谱进行分析的过程。     

Gene expression analysis for the identification of selection and local adaptation in fishes

In recent years, variation in gene expression has been recognized as an important component of environmental adaptation in multiple model species, including a few fish species. There is, however, still little known about the genetic basis of adaptation in gene expression resulting from variation in the aquatic environment (e.g. temperature, salinity and oxygen) and the physiological effect and costs of such differences in gene expression. This review presents and discusses progress and pitfalls of applying gene expression analyses to fishes and suggests simple frameworks to get started with gene expression analysis. It is emphasized that well-planned gene expression studies can serve as an important tool for the identification of selection in local populations of fishes, even for non-traditional model species where limited genomic information is available. Recent studies focusing on gene expression variation among natural fish populations are reviewed, highlighting the latest applications that combine genetic evidence from neutral markers and gene expression data.     

BEST: a novel computational approach for comparing gene expression patterns from early stages of Drosophila melanogaster development

Embryonic gene expression patterns are an indispensable part of modern developmental biology. Currently, investigators must visually inspect numerous images containing embryonic expression patterns to identify spatially similar patterns for inferring potential genetic interactions. The lack of a computational approach to identify pattern similarities is an impediment to advancement in developmental biology research because of the rapidly increasing amount of available embryonic gene expression data. Therefore, we have developed computational approaches to automate the comparison of gene expression patterns contained in images of early stage Drosophila melanogaster embryos (prior to the beginning of germ-band elongation); similarities and differences in gene expression patterns in these early stages have extensive developmental effects. Here we describe a basic expression search tool (BEST) to retrieve best matching expression patterns for a given query expression pattern and a computational device for gene interaction inference using gene expression pattern images and information on the associated genotypes and probes. Analysis of a prototype collection of Drosophila gene expression pattern images is presented to demonstrate the utility of these methods in identifying biologically meaningful matches and inferring gene interactions by direct image content analysis. In particular, the use of BEST searches for gene expression patterns is akin to that of BLAST searches for finding similar sequences. These computational developmental biology methodologies are likely to make the great wealth of embryonic gene expression pattern data easily accessible and to accelerate the discovery of developmental networks.