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.     

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.     

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.     

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.     

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.     

Stimulatory effect of polyethylene glycol (PEG) on gene expression in mouse liver following hydrodynamics-based transfection

BACKGROUND: Rapid intravenous injection of a large volume of plasmid DNA (pDNA), i.e. a transfection procedure based on hydrodynamics, is known to be an efficient and liver-specific method of in vivo gene delivery. However, the gene expression is transient. METHODS: We investigated the effect of addition of polyethylene glycol (PEG) to a solution of naked pDNA (luciferase) on the expression of the gene in mouse liver following transfection by the hydrodynamics-based technique. In addition, the mechanism leading to the enhancement of the gene expression was studied. RESULTS: The addition of 1% (w/v) PEG2000 to the pDNA solution enhanced the resulting gene expression in the liver. Increasing the PEG2000 concentration to more than 1 and up to 10% (w/v) rather diminished the gene expression level. By contrast, increasing the molecular weight of PEG to over 2000 up to 10 000 did not affect the level of gene expression. Histopathological and serum-chemistry examinations indicated that hydrostatic or osmotic pressure increased tissue and hepatocellular damage in a PEG-concentration-dependent manner, and resulted in a decrease in gene expression. Quantitative evaluation showed that the enhanced gene expression resulted from stabilization of the pDNA introduced into the hepatocytes and an enhancement of the transport of intact pDNA to the nucleus. CONCLUSIONS: For most gene therapy applications and gene function studies, sustained expression of the introduced gene(s) is necessary. This simple method to achieve enhanced gene expression in liver may have a great potential for a wide variety of laboratory studies in molecular and cellular biology as well as possibly for future clinical applications in humans.     

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.     

Combining GAL4 GFP enhancer trap with split luciferase to measure spatiotemporal promoter activity in Arabidopsis

In multicellular organisms different types of tissues have distinct gene expression profiles associated with specific function or structure of the cell. Quantification of gene expression in whole organs or whole organisms can give misleading information about levels or dynamics of expression in specific cell types. Tissue‐ or cell‐specific analysis of gene expression has potential to enhance our understanding of gene regulation and interactions of cell signalling networks. The Arabidopsis circadian oscillator is a gene network which orchestrates rhythmic expression across the day/night cycle. There is heterogeneity between cell and tissue types of the composition and behaviour of the oscillator. In order to better understand the spatial and temporal patterns of gene expression, flexible tools are required. By combining a Gateway®‐compatible split luciferase construct with a GAL4 GFP enhancer trap system, we describe a tissue‐specific split luciferase assay for non‐invasive detection of spatiotemporal gene expression in Arabidopsis. We demonstrate the utility of this enhancer trap‐compatible split luciferase assay (ETSLA) system to investigate tissue‐specific dynamics of circadian gene expression. We confirm spatial heterogeneity of circadian gene expression in Arabidopsis leaves and describe the resources available to investigate any gene of interest.     

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.     

Variation in the large-scale organization of gene expression levels in the hippocampus relates to stable epigenetic variability in behavior

Background

Despite sharing the same genes, identical twins demonstrate substantial variability in behavioral traits and in their risk for disease. Epigenetic factors–DNA and chromatin modifications that affect levels of gene expression without affecting the DNA sequence–are thought to be important in establishing this variability. Epigenetically-mediated differences in the levels of gene expression that are associated with individual variability traditionally are thought to occur only in a gene-specific manner. We challenge this idea by exploring the large-scale organizational patterns of gene expression in an epigenetic model of behavioral variability.

Methodology/Findings

To study the effects of epigenetic influences on behavioral variability, we examine gene expression in genetically identical mice. Using a novel approach to microarray analysis, we show that variability in the large-scale organization of gene expression levels, rather than differences in the expression levels of specific genes, is associated with individual differences in behavior. Specifically, increased activity in the open field is associated with increased variance of log-transformed measures of gene expression in the hippocampus, a brain region involved in open field activity. Early life experience that increases adult activity in the open field also similarly modifies the variance of gene expression levels. The same association of the variance of gene expression levels with behavioral variability is found with levels of gene expression in the hippocampus of genetically heterogeneous outbred populations of mice, suggesting that variation in the large-scale organization of gene expression levels may also be relevant to phenotypic differences in outbred populations such as humans. We find that the increased variance in gene expression levels is attributable to an increasing separation of several large, log-normally distributed families of gene expression levels. We also show that the presence of these multiple log-normal distributions of gene expression levels is a universal characteristic of gene expression in eurkaryotes. We use data from the MicroArray Quality Control Project (MAQC) to demonstrate that our method is robust and that it reliably detects biological differences in the large-scale organization of gene expression levels.

Conclusions

Our results contrast with the traditional belief that epigenetic effects on gene expression occur only at the level of specific genes and suggest instead that the large-scale organization of gene expression levels provides important insights into the relationship of gene expression with behavioral variability. Understanding the epigenetic, genetic, and environmental factors that regulate the large-scale organization of gene expression levels, and how changes in this large-scale organization influences brain development and behavior will be a major future challenge in the field of behavioral genomics.     

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.     

Differential regulation of the rat phosphoenolpyruvate carboxykinase gene expression in several tissues of transgenic mice.

The selective expression of a unique copy gene in several mammalian tissues has been approached by studying the regulatory sequences needed to control expression of the rat phosphoenolpyruvate carboxykinase (PEPCK) gene in transgenic mice. A transgene containing the entire PEPCK gene, including 2.2 kb of the 5'-flanking region and 0.5 kb of the 3'-flanking region, exhibits tissue-specific expression in the liver, kidney, and adipose tissue, as well as the hormonal and developmental regulation inherent to endogenous gene expression. Deletions of the 5'-flanking region of the gene have shown the need for sequences downstream of position -540 of the PEPCK gene for expression in the liver and sequences downstream of position -362 for expression in the kidney. Additional sequences upstream of position -540 (up to -2200) are required for expression in adipose tissue. In addition, the region containing the glucocorticoid-responsive elements of the gene used by the kidney was identified. This same sequence was found to be needed specifically for developmental regulation of gene expression in the kidney and, together with upstream sequences, in the intestine. The apparently distinct sequence requirements in the various tissues indicate that the tissues use different mechanisms for expression of the same gene.     

Problems and paradigms: Induction mechanism of a single gene molecule: Stochastic or deterministic?

A new field of gene expression regulation research is emerging that has previously been overlooked. This new area is concerned with distinguishing the expression of a single gene from the averaged expression of many gene copies within the cell population. This paper reviews research focused on individual genes in inducible gene expression systems. The main experimental strategy is to measure the gene expression level of a single cell containing a single reporter gene molecule. In contrast to the commonly held belief, gene induction is found to be stochastic under certain conditions. The possible mechanisms and implications are discussed.     

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.