Intergenic and genic sequence lengths have opposite relationships with respect to gene expression.

Eukaryotic genomes are mostly composed of noncoding DNA whose role is still poorly understood. Studies in several organisms have shown correlations between the length of the intergenic and genic sequences of a gene and the expression of its corresponding mRNA transcript. Some studies have found a positive relationship between intergenic sequence length and expression diversity between tissues, and concluded that genes under greater regulatory control require more regulatory information in their intergenic sequences. Other reports found a negative relationship between expression level and gene length and the interpretation was that there is selection pressure for highly expressed genes to remain small. However, a correlation between gene sequence length and expression diversity, opposite to that observed for intergenic sequences, has also been reported, and to date there is no testable explanation for this observation. To shed light on these varied and sometimes conflicting results, we performed a thorough study of the relationships between sequence length and gene expression using cell-type (tissue) specific microarray data in Arabidopsis thaliana. We measured median gene expression across tissues (expression level), expression variability between tissues (expression pattern uniformity), and expression variability between replicates (expression noise). We found that intergenic (upstream and downstream) and genic (coding and noncoding) sequences have generally opposite relationships with respect to expression, whether it is tissue variability, median, or expression noise. To explain these results we propose a model, in which the lengths of the intergenic and genic sequences have opposite effects on the ability of the transcribed region of the gene to be epigenetically regulated for differential expression. These findings could shed light on the role and influence of noncoding sequences on gene expression.

Diagnosis of partial body radiation exposure in mice using peripheral blood gene expression profiles.

In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB) can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI). However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79-100%) compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16-43%), suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Radioactive in situ hybridization for detecting diverse gene expression patterns in tissue.

Knowing the timing, level, cellular localization, and cell type that a gene is expressed in contributes to our understanding of the function of the gene. Each of these features can be accomplished with in situ hybridization to mRNAs within cells. Here we present a radioactive in situ hybridization method modified from Clayton et al. (1988)(1) that has been working successfully in our lab for many years, especially for adult vertebrate brains(2-5). The long complementary RNA (cRNA) probes to the target sequence allows for detection of low abundance transcripts(6,7). Incorporation of radioactive nucleotides into the cRNA probes allows for further detection sensitivity of low abundance transcripts and quantitative analyses, either by light sensitive x-ray film or emulsion coated over the tissue. These detection methods provide a long-term record of target gene expression. Compared with non-radioactive probe methods, such as DIG-labeling, the radioactive probe hybridization method does not require multiple amplification steps using HRP-antibodies and/or TSA kit to detect low abundance transcripts. Therefore, this method provides a linear relation between signal intensity and targeted mRNA amounts for quantitative analysis. It allows processing 100-200 slides simultaneously. It works well for different developmental stages of embryos. Most developmental studies of gene expression use whole embryos and non-radioactive approaches(8,9), in part because embryonic tissue is more fragile than adult tissue, with less cohesion between cells, making it difficult to see boundaries between cell populations with tissue sections. In contrast, our radioactive approach, due to the larger range of sensitivity, is able to obtain higher contrast in resolution of gene expression between tissue regions, making it easier to see boundaries between populations. Using this method, researchers could reveal the possible significance of a newly identified gene, and further predict the function of the gene of interest.

Study of gene expression in thyrotropin-stimulated thyroid cells by cDNA expression array: ID3 transcription modulating factor as an early response protein and tumor marker in thyroid carcinomas.

Induction of cell proliferation by mitogen or growth factor stimulation leads to the specific induction or repression of a large number of genes. To identify genes differentially regulated by the cAMP-dependent transduction pathway, which is poorly characterized so far, we used the cDNA expression array technology. Hybridizations of Atlas human cDNA expression arrays with (32)P-labeled cDNA probes derived from control or thyrotropin (TSH)-stimulated dog thyrocytes in primary culture generated expression profiles of hundreds of genes simultaneously. Among the genes that displayed modified expression, we selected the transcription factor ID3, whose expression was increased by a cAMP-dependent stimulus. ID3 overexpression after TSH stimulation was first verified by Northern blotting analysis, and its mRNA regulation was then investigated in response to a variety of agents acting on thyrocyte proliferation and/or differentiation. We show that: (1) ID3 mRNA induction was stronger after stimulation of the cAMP cascade, but was not restricted to this signaling pathway, as phorbol myristate ester (TPA) and insulin also stimulated mRNA accumulation; (2) in contrast, powerful mitogens for thyroid cells, epidermal growth factor and hepatocyte growth factor, did not significantly modify ID3 mRNA levels; (3) ID3 protein levels closely parallelled mRNA levels, as revealed by immunofluorescence experiments showing a nuclear signal regulated by TSH; (4) in papillary thyroid carcinomas, ID3 mRNA was downregulated. Our results suggest that ID3 expression might be more related to the differentiating process induced by TSH than to the proliferative action of this hormone.

Analysis of HSC activity and compensatory Hox gene expression profile in Hoxb cluster mutant fetal liver cells

Overexpression of Hoxb4 in bone marrow cells promotes expansion of hematopoietic stem cell (HSC) populations in vivo and in vitro, indicating that this homeoprotein can activate the genetic program that determines self-renewal. However, this function cannot be solely attributed to Hoxb4 because Hoxb4(-/-) mice are viable and have an apparently normal HSC number. Quantitative polymerase chain reaction analysis showed that Hoxb4(-/-) c-Kit(+) fetal liver cells expressed moderately higher levels of several Hoxb cluster genes than control cells, raising the possibility that normal HSC activity in Hoxb4(-/-) mice is due to a compensatory up-regulation of other Hoxb genes. In this study, we investigated the competitive repopulation potential of HSCs lacking Hoxb4 alone, or in conjunction with 8 other Hoxb genes. Our results show that Hoxb4(-/-) and Hoxb1-b9(-/-) fetal liver cells retain full competitive repopulation potential and the ability to regenerate all myeloid and lymphoid lineages. Quantitative Hox gene expression profiling in purified c-KIt(+) Hoxb1-bg(-/-) fetal liver cells revealed an interaction between the Hoxa, b, and c clusters with variation in expression levels of Hoxa4, -a11, and -c4. Together, these studies show a complex network of genetic interactions between several Hox genes in primitive hematopoietic cells and demonstrate that HSCs lacking up to 30% of the active Hox genes remain fully competent.

Novel breast cancer biomarkers identified by integrative proteomic and gene expression mapping

Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.

Effects of oxidized and glycated LDL on gene expression in human retinal capillary pericytes

Modified (oxidized and/or glycated) low-density lipoproteins (LDLs) have been implicated in retinal pericyte loss, one of the major pathologic features of early-stage diabetic retinopathy. To delineate underlying molecular mechanisms, the present study was designed to explore the global effects of modified LDL on pericyte gene expression.

Identification of Gene Expression-Based Prognostic Markers in the Hematopoietic Stem Cells of Patients With Myelodysplastic Syndromes

The diagnosis of patients with myelodysplastic syndromes (MDS) is largely dependent on morphologic examination of bone marrow aspirates. Several criteria that form the basis of the classifications and scoring systems most commonly used in clinical practice are affected by operator-dependent variation. To identify standardized molecular markers that would allow prediction of prognosis, we have used gene expression profiling (GEP) data on CD34+ cells from patients with MDS to determine the relationship between gene expression levels and prognosis.

Gene expression and epigenetic discovery screen reveal methylation of SFRP2 in prostate cancer

Aberrant activation of Wnts is common in human cancers, including prostate. Hypermethylation associated transcriptional silencing of Wnt antagonist genes SFRPs (Secreted Frizzled-Related Proteins) is a frequent oncogenic event. The significance of this is not known in prostate cancer. The objectives of our study were to (i) profile Wnt signaling related gene expression and (ii) investigate methylation of Wnt antagonist genes in prostate cancer. Using TaqMan Low Density Arrays, we identified 15 Wnt signaling related genes with significantly altered expression in prostate cancer; the majority of which were upregulated in tumors. Notably, histologically benign tissue from men with prostate cancer appeared more similar to tumor (r = 0.76) than to benign prostatic hyperplasia (BPH; r = 0.57, p < 0.001). Overall, the expression profile was highly similar between tumors of high (≥ 7) and low (≤ 6) Gleason scores. Pharmacological demethylation of PC-3 cells with 5-Aza-CdR reactivated 39 genes (≥ 2-fold); 40% of which inhibit Wnt signaling. Methylation frequencies in prostate cancer were 10% (2/20) (SFRP1), 64.86% (48/74) (SFRP2), 0% (0/20) (SFRP4) and 60% (12/20) (SFRP5). SFRP2 methylation was detected at significantly lower frequencies in high-grade prostatic intraepithelial neoplasia (HGPIN; 30%, (6/20), p = 0.0096), tumor adjacent benign areas (8.82%, (7/69), p < 0.0001) and BPH (11.43% (4/35), p < 0.0001). The quantitative level of SFRP2 methylation (normalized index of methylation) was also significantly higher in tumors (116) than in the other samples (HGPIN = 7.45, HB = 0.47, and BPH = 0.12). We show that SFRP2 hypermethylation is a common event in prostate cancer. SFRP2 methylation in combination with other epigenetic markers may be a useful biomarker of prostate cancer.

Characterization of a reference material for BCR-ABL (M-BCR) mRNA quantitation by real-time amplification assays:towards new standards for gene expression measurements

Monitoring of BCR-ABL transcripts has become established practice in the management of chronic myeloid leukemia. However, nucleic acid amplification techniques are prone to variations which limit the reliability of real-time quantitative PCR (RQ-PCR) for clinical decision making, highlighting the need for standardization of assays and reporting of minimal residual disease (MRD) data. We evaluated a lyophilized preparation of a leukemic cell line (K562) as a potential quality control reagent. This was found to be relatively stable, yielding comparable respective levels of ABL, GUS and BCR-ABL transcripts as determined by RQ-PCR before and after accelerated degradation experiments as well as following 5 years storage at -20 degrees C. Vials of freeze-dried cells were sent at ambient temperature to 22 laboratories on four continents, with RQ-PCR analyses detecting BCR-ABL transcripts at levels comparable to those observed in primary patient samples. Our results suggest that freeze-dried cells can be used as quality control reagents with a range of analytical instrumentations and could enable the development of urgently needed international standards simulating clinically relevant levels of MRD.

An atlas of human gene expression from massively parallel signature sequencing (MPSS).

We have used massively parallel signature sequencing (MPSS) to sample the transcriptomes of 32 normal human tissues to an unprecedented depth, thus documenting the patterns of expression of almost 20,000 genes with high sensitivity and specificity. The data confirm the widely held belief that differences in gene expression between cell and tissue types are largely determined by transcripts derived from a limited number of tissue-specific genes, rather than by combinations of more promiscuously expressed genes. Expression of a little more than half of all known human genes seems to account for both the common requirements and the specific functions of the tissues sampled. A classification of tissues based on patterns of gene expression largely reproduces classifications based on anatomical and biochemical properties. The unbiased sampling of the human transcriptome achieved by MPSS supports the idea that most human genes have been mapped, if not functionally characterized. This data set should prove useful for the identification of tissue-specific genes, for the study of global changes induced by pathological conditions, and for the definition of a minimal set of genes necessary for basic cell maintenance. The data are available on the Web at http://mpss.licr.org and http://sgb.lynxgen.com.

Use of global gene expression patterns in mechanistic studies of oestrogen action in MCF7 human breast cancer cells

Over the years, the MCF7 human breast cancer cell line has provided a model system for the study of cellular and molecular mechanisms in oestrogen regulation of cell proliferation and in progression to oestrogen and antioestrogen independent growth. Global gene expression profiling has shown that oestrogen action in MCF7 cells involves the coordinated regulation of hundreds of genes across a wide range of functional groupings and that more genes are down regulated than upregulated. Adaptation to long-term oestrogen deprivation, which results in loss of oestrogen-responsive growth, involves alterations to gene patterns not only at early time points (0-4 weeks) but continuing through to later times (20-55 weeks), and even involves alterations to patterns of oestrogen-regulated gene expression. Only 48% of the genes which were regulated >= 2-fold by oestradiol in oestrogen-responsive cells retained this responsiveness after long-term oestrogen deprivation but other genes developed de novo oestrogen regulation. Long-term exposure to fulvestrant, which resulted in loss of growth inhibition by the antioestrogen, resulted in some very large fold changes in gene expression up to 10,000-fold. Comparison of gene profiles produced by environmental chemicals with oestrogenic properties showed that each ligand gave its own unique expression profile which suggests that environmental oestrogens entering the human breast may give rise to a more complex web of interference in cell function than simply mimicking oestrogen action at inappropriate times. (C) 2009 Elsevier Ltd. All rights reserved.

Arabidopsis thaliana Uncoupling Proteins (AtUCPs): insights into gene expression during development and stress response and epigenetic regulation

Mitochondrial inner membrane uncoupling proteins (UCP) catalyze a proton conductance that dissipates the proton electrochemical gradient established by the respiratory chain, thus affecting the yield of ATP synthesis. UCPs are involved in mitochondrial energy flow regulation and have been implicated in oxidative stress tolerance. Based on the global gene expression profiling datasets available for Arabidopsis thaliana, in this review we discuss the regulation of UCP gene expression during development and in response to stress, and provide interesting insights on the possible existence of epigenetic regulation of UCP expression.

Homeobox gene expression profile indicates HOXA5 as a candidate prognostic marker in oral squamous cell carcinoma

The search for molecular markers to improve diagnosis, individualize treatment and predict behavior of tumors has been the focus of several studies. This study aimed to analyze homeobox gene expression profile in oral squamous cell carcinoma (OSCC) as well as to investigate whether some of these genes are relevant molecular markers of prognosis and/or tumor aggressiveness. Homeobox gene expression levels were assessed by microarrays and qRT-PCR in OSCC tissues and adjacent non-cancerous matched tissues (margin), as well as in OSCC cell lines. Analysis of microarray data revealed the expression of 147 homeobox genes, including one set of six at least 2-fold up-regulated, and another set of 34 at least 2-fold down-regulated homeobox genes in OSCC. After qRT-PCR assays, the three most up-regulated homeobox genes (HOXA5, HOXD10 and HOXD11) revealed higher and statistically significant expression levels in OSCC samples when compared to margins. Patients presenting lower expression of HOXA5 had poorer prognosis compared to those with higher expression (P=0.03). Additionally, the status of HOXA5, HOXD10 and HOXD11 expression levels in OSCC cell lines also showed a significant up-regulation when compared to normal oral keratinocytes. Results confirm the presence of three significantly upregulated (>4-fold) homeobox genes (HOXA5, HOXD10 and HOXD11) in OSCC that may play a significant role in the pathogenesis of these tumors. Moreover, since lower levels of HOXA5 predict poor prognosis, this gene may be a novel candidate for development of therapeutic strategies in OSCC.