Differential gene expression in disease: a comparison between high-throughput studies and the literature

Background

Differential gene expression is important to understand the biological differences between healthy and diseased states. Two common sources of differential gene expression data are microarray studies and the biomedical literature.

Methods

With the aid of text mining and gene expression analysis we have examined the comparative properties of these two sources of differential gene expression data.

Results

The literature shows a preference for reporting genes associated to higher fold changes in microarray data, rather than genes that are simply significantly differentially expressed. Thus, the resemblance between the literature and microarray data increases when the fold-change threshold for microarray data is increased. Moreover, the literature has a reporting preference for differentially expressed genes that (1) are overexpressed rather than underexpressed; (2) are overexpressed in multiple diseases; and (3) are popular in the biomedical literature at large. Additionally, the degree to which diseases are similar depends on whether microarray data or the literature is used to compare them. Finally, vaguely-qualified reports of differential expression magnitudes in the literature have only small correlation with microarray fold-change data.

Conclusions

Reporting biases of differential gene expression in the literature can be affecting our appreciation of disease biology and of the degree of similarity that actually exists between different diseases.

     

Statistical analysis of fractionation resistance by functional category and expression

Background

The current literature establishes the importance of gene functional category and expression in promoting or suppressing duplicate gene loss after whole genome doubling in plants, a process known as fractionation. Inspired by studies that have reported gene expression to be the dominating factor in preventing duplicate gene loss, we analyzed the relative effect of functional category and expression.

Methods

We use multivariate methods to study data sets on gene retention, function and expression in rosids and asterids to estimate effects and assess their interaction.

Results

Our results suggest that the effect on duplicate gene retention fractionation by functional category and expression are independent and have no statistical interaction.

Conclusion

In plants, functional category is the more dominant factor in explaining duplicate gene loss.

     

Integrative pathway-based survival prediction utilizing the interaction between gene expression and DNA methylation in breast cancer

Background

Integrative analysis on multi-omics data has gained much attention recently. To investigate the interactive effect of gene expression and DNA methylation on cancer, we propose a directed random walk-based approach on an integrated gene-gene graph that is guided by pathway information.

Methods

Our approach first extracts a single pathway profile matrix out of the gene expression and DNA methylation data by performing the random walk over the integrated graph. We then apply a denoising autoencoder to the pathway profile to further identify important pathway features and genes. The extracted features are validated in the survival prediction task for breast cancer patients.

Results

The results show that the proposed method substantially improves the survival prediction performance compared to that of other pathway-based prediction methods, revealing that the combined effect of gene expression and methylation data is well reflected in the integrated gene-gene graph combined with pathway information. Furthermore, we show that our joint analysis on the methylation features and gene expression profile identifies cancer-specific pathways with genes related to breast cancer.

Conclusions

In this study, we proposed a DRW-based method on an integrated gene-gene graph with expression and methylation profiles in order to utilize the interactions between them. The results showed that the constructed integrated gene-gene graph can successfully reflect the combined effect of methylation features on gene expression profiles. We also found that the selected features by DA can effectively extract topologically important pathways and genes specifically related to breast cancer.

     

Integrated analysis of microRNA-target interactions with clinical outcomes for cancers

Background

Clinical statement alone is not enough to predict the progression of disease. Instead, the gene expression profiles have been widely used to forecast clinical outcomes. Many genes related to survival have been identified, and recently miRNA expression signatures predicting patient survival have been also investigated for several cancers. However, miRNAs and their target genes associated with clinical outcomes have remained largely unexplored.

Methods

Here, we demonstrate a survival analysis based on the regulatory relationships of miRNAs and their target genes. The patient survivals for the two major cancers, ovarian cancer and glioblastoma multiforme (GBM), are investigated through the integrated analysis of miRNA-mRNA interaction pairs.

Results

We found that there is a larger survival difference between two patient groups with an inversely correlated expression profile of miRNA and mRNA. It supports the idea that signatures of miRNAs and their targets related to cancer progression can be detected via this approach.

Conclusions

This integrated analysis can help to discover coordinated expression signatures of miRNAs and their target mRNAs that can be employed for therapeutics in human cancers.

     

Stress amplifies sex differences in primate prefrontal profiles of gene expression

Background

Stress is a recognized risk factor for mood and anxiety disorders that occur more often in women than men. Prefrontal brain regions mediate stress coping, cognitive control, and emotion. Here, we investigate sex differences and stress effects on prefrontal cortical profiles of gene expression in squirrel monkey adults.

Methods

Dorsolateral, ventrolateral, and ventromedial prefrontal cortical regions from 18 females and 12 males were collected after stress or no-stress treatment conditions. Gene expression profiles were acquired using HumanHT-12v4.0 Expression BeadChip arrays adapted for squirrel monkeys.

Results

Extensive variation between prefrontal cortical regions was discerned in the expression of numerous autosomal and sex chromosome genes. Robust sex differences were also identified across prefrontal cortical regions in the expression of mostly autosomal genes. Genes with increased expression in females compared to males were overrepresented in mitogen-activated protein kinase and neurotrophin signaling pathways. Many fewer genes with increased expression in males compared to females were discerned, and no molecular pathways were identified. Effect sizes for sex differences were greater in stress compared to no-stress conditions for ventromedial and ventrolateral prefrontal cortical regions but not dorsolateral prefrontal cortex.

Conclusions

Stress amplifies sex differences in gene expression profiles for prefrontal cortical regions involved in stress coping and emotion regulation. Results suggest molecular targets for new treatments of stress disorders in human mental health.

     

Selection and validation of reliable reference genes in <Emphasis Type="Italic">Gossypium raimondii</Emphasis>

Objective

To identify reliable reference genes for gene expression analysis in Gossypium raimondii.

Results

Five different software tools, geNorm, NormFinder, BestKeeper, ReFinder and ?Ct method were employed to analyze the qRT-PCR data systematically of 12 housekeeping genes. SAD and TUA11 showed relatively stable expression levels in all tissues (i.e. leaves, shoots, buds, and sepals). We then limited our analysis to each plant part and identified tissue-specific reference genes. Our results showed TUA11, TUB6 and EF1a, EF1a, MZA and GAPC2, MZA, GAPC2, SAD and TUA11, and UBQ and MZA were reliable reference genes in leaves, shoots, buds, and sepals, respectively.

Conclusion

Some genes were commonly identified as candidate reference genes in more than two tissue, while others were tissue-specific. Thus, our study allows choosing an appropriate control gene based on sampling for gene expression analysis.

     

The role of laterally transferred genes in adaptive evolution

Background

Bacterial genomes develop new mechanisms to tide them over the imposing conditions they encounter during the course of their evolution. Acquisition of new genes by lateral gene transfer may be one of the dominant ways of adaptation in bacterial genome evolution. Lateral gene transfer provides the bacterial genome with a new set of genes that help it to explore and adapt to new ecological niches.

Methods

A maximum likelihood analysis was done on the five sequenced corynebacterial genomes to model the rates of gene insertions/deletions at various depths of the phylogeny.

Results

The study shows that most of the laterally acquired genes are transient and the inferred rates of gene movement are higher on the external branches of the phylogeny and decrease as the phylogenetic depth increases. The newly acquired genes are under relaxed selection and evolve faster than their older counterparts. Analysis of some of the functionally characterised LGTs in each species has indicated that they may have a possible adaptive role.

Conclusion

The five Corynebacterial genomes sequenced to date have evolved by acquiring between 8 – 14% of their genomes by LGT and some of these genes may have a role in adaptation.

     

Study of the tumor microenvironment during breast cancer progression

Background

Different cells and mediators in the tumor microenvironment play important roles in the progression of breast cancer. The aim of this study was to determine the composition of the microenvironment during tumor progression in order to discover new related biomarkers and potentials for targeted therapy.

Methods

In this study, breast cancer biopsies from four different stages, and control breast biopsies were collected. Then, the mRNA expression of several markers related to different CD4⁺ T cell subsets including regulatory T cells (Treg), T helper (Th) type 1, 2 and 17 were determined. In addition, we investigated the expression of two inflammatory cytokines (TNF-α and IL-6) and inflammatory mediators including FASL, IDO, SOCS1, VEGF, and CCR7.

Results

The results showed that the expression of Th1 and Th17 genes was decreased in tumor tissues compared to control tissues. In addition, we found that the gene expression related to these two cell subsets decreased during cancer progression. Moreover, the expression level of TNF-α increased with tumor progression.

Conclusion

We conclude that the expression of genes related to immune response and inflammation is different between tumor tissues and control tissues. In addition, this difference was perpetuated through the different stages of cancer.

     

Microarray data integration for genome-wide analysis of human tissue-selective gene expression

Background

Microarray gene expression data are accumulating in public databases. The expression profiles contain valuable information for understanding human gene expression patterns. However, the effective use of public microarray data requires integrating the expression profiles from heterogeneous sources.

Results

In this study, we have compiled a compendium of microarray expression profiles of various human tissue samples. The microarray raw data generated in different research laboratories have been obtained and combined into a single dataset after data normalization and transformation. To demonstrate the usefulness of the integrated microarray data for studying human gene expression patterns, we have analyzed the dataset to identify potential tissue-selective genes. A new method has been proposed for genome-wide identification of tissue-selective gene targets using both microarray intensity values and detection calls. The candidate genes for brain, liver and testis-selective expression have been examined, and the results suggest that our approach can select some interesting gene targets for further experimental studies.

Conclusion

A computational approach has been developed in this study for combining microarray expression profiles from heterogeneous sources. The integrated microarray data can be used to investigate tissue-selective expression patterns of human genes.

     

Efficient activation of gene expression using a heat-shock inducible Gal4/Vp16-UAS system in medaka

Background

Genetic interference by DNA, mRNA or morpholino injection is a widely used approach to study gene function in developmental biology. However, the lack of temporal control over the activity of interfering molecules often hampers investigation of gene function required during later stages of embryogenesis. To elucidate the roles of genes during embryogenesis a precise temporal control of transgene expression levels in the developing organism is on demand.

Results

We have generated a transgenic Gal4/Vp16 activator line that is heat-shock inducible, thereby providing a tool to drive the expression of specific effector genes via Gal4/Vp16. Merging the Gal4/Vp16-UAS system with the I-SceI meganuclease and the Sleeping Beauty transposon system allows inducible gene expression in an entirely uniform manner without the need to generate transgenic effector lines. Combination of this system with fluorescent protein reporters furthermore facilitates the direct visualization of transgene expressing cells in live embryos.

Conclusion

The combinatorial properties of this expression system provide a powerful tool for the analysis of gene function during embryonic and larval development in fish by ectopic expression of gene products.

     

Prediction of heme binding residues from protein sequences with integrative sequence profiles

Background

The heme-protein interactions are essential for various biological processes such as electron transfer, catalysis, signal transduction and the control of gene expression. The knowledge of heme binding residues can provide crucial clues to understand these activities and aid in functional annotation, however, insufficient work has been done on the research of heme binding residues from protein sequence information.

Methods

We propose a sequence-based approach for accurate prediction of heme binding residues by a novel integrative sequence profile coupling position specific scoring matrices with heme specific physicochemical properties. In order to select the informative physicochemical properties, we design an intuitive feature selection scheme by combining a greedy strategy with correlation analysis.

Results

Our integrative sequence profile approach for prediction of heme binding residues outperforms the conventional methods using amino acid and evolutionary information on the 5-fold cross validation and the independent tests.

Conclusions

The novel feature of an integrative sequence profile achieves good performance using a reduced set of feature vector elements.

     

Squalene isolated from <Emphasis Type="Italic">Schizochytrium mangrovei</Emphasis> is a peroxisome proliferator-activated receptor-α agonist that regulates lipid metabolism in HepG2 cells

Objective

Peroxisome proliferator-activated receptor-alpha (PPARα) is a nuclear receptor that has critical roles in the treatment of atherosclerosis, hyperlipidemia and hepatic steatosis.

Results

Squalene is a novel nature PPARα agonist, identified from reporter gene assay and qPCR analysis. Cultured hepatocytes stimulated with squalene exhibited significantly decreased cellular triacylglycerols and cholesterol concentrations, while cellular uptake of fatty acids was increased. Quantitative PCR analysis revealed that expression of genes related to fatty acid uptake, fatty acid oxidation, ketogenesis and reverse cholesterol transport metabolism were upregulated, while that of genes related to fatty acid synthesis were suppressed in cell treated with squalene.

Conclusion

Squalene is hypolipidemic by activation of PPARα via a ligand-mediated mechanism that regulates the expression of lipid metabolism genes in hepatocytes.

     

Microcystin-LR regulates circadian clock and antioxidant gene expression in cultured rat cardiomyocytes

Background

Microcystins are waterborne environmental toxins that induce oxidative stress and cause injuries in the heart. On the other hand, many physiological processes, including antioxidant defense, are under precise control by the mammalian circadian clock.

Results

In the present study, we evaluated the effect of microcystin-LR (MC-LR) on the rhythmic expression patterns of circadian and antioxidant genes in rat cardiomyocytes using the serum shock technique. We found that a non-toxic dose (10 μm) of MC-LR decreased the amplitudes of rhythmic patterns of clock genes, while it increased the expression levels of antioxidant genes.

Conclusions

Our results indicate an influence of MC-LR on the circadian clock system and clock-controlled antioxidant genes, which will shed some light on the explanation of heart toxicity induced by MC-LR from the viewpoint of chronobiology.

     

Identifying functional relationships within sets of co-expressed genes by combining upstream regulatory motif analysis and gene expression information

Background

Existing clustering approaches for microarray data do not adequately differentiate between subsets of co-expressed genes. We devised a novel approach that integrates expression and sequence data in order to generate functionally coherent and biologically meaningful subclusters of genes. Specifically, the approach clusters co-expressed genes on the basis of similar content and distributions of predicted statistically significant sequence motifs in their upstream regions.

Results

We applied our method to several sets of co-expressed genes and were able to define subsets with enrichment in particular biological processes and specific upstream regulatory motifs.

Conclusions

These results show the potential of our technique for functional prediction and regulatory motif identification from microarray data.

     

DTL reconciliation repair

Background

Maximum parsimony phylogenetic tree reconciliation is an important technique for reconstructing the evolutionary histories of hosts and parasites, genes and species, and other interdependent pairs. Since the problem of finding temporally feasible maximum parsimony reconciliations is NP-complete, current methods use either exact algorithms with exponential worst-case running time or heuristics that do not guarantee optimal solutions.

Results

We offer an efficient new approach that begins with a potentially infeasible maximum parsimony reconciliation and iteratively “repairs” it until it becomes temporally feasible.

Conclusions

In a non-trivial number of cases, this approach finds solutions that are better than those found by the widely-used Jane heuristic.