Identifying expressed genes

Gene Prioritization in Parkinson's Disease Using Human Protein-Protein Interaction Network

Parkinson's disease (PD) is the second-most common neurodegenerative disorder, and the actual cause of this disease is still unknown. Identifying the target genes that are associated with disease plays an essential role in the treatment of PD. Various genetic studies have determined the significant target genes for disease progression, although this continues to be challenging in the field of drug designing. In this study, we proposed a network-based approach to identify target genes for PD using gene mutation, gene expression, and gene deletion analysis. The subnetwork of PD genes was constructed from human protein-protein interaction network, and the potential genes were identified using network centrality measures. Two genes, PARK1 and PARK2, were identified as target genes by integrating gene mutation and expression data into the subnetwork. Gene deletion analysis was carried out to determine the significant target, and results revealed that VDAC1 and ATP5C1 genes were crucial for the Parkinson's subnetwork. Thus, findings from the network-based approach will provide additional insight for understanding the disease mechanism of PD. Future enhancement of this study may help in predicting disease biomarkers as well as designing novel compounds in rational drug designing.

FRAMA: from RNA-seq data to annotated mRNA assemblies

Background

Advances in second-generation sequencing of RNA made a near-complete characterization of transcriptomes affordable. However, the reconstruction of full-length mRNAs via de novo RNA-seq assembly is still difficult due to the complexity of eukaryote transcriptomes with highly similar paralogs and multiple alternative splice variants. Here, we present FRAMA, a genome-independent annotation tool for de novo mRNA assemblies that addresses several post-assembly tasks, such as reduction of contig redundancy, ortholog assignment, correction of misassembled transcripts, scaffolding of fragmented transcripts and coding sequence identification.

Results

We applied FRAMA to assemble and annotate the transcriptome of the naked mole-rat and assess the quality of the obtained compilation of transcripts with the aid of publicy available naked mole-rat gene annotations.

Based on a de novo transcriptome assembly (Trinity), FRAMA annotated 21,984 naked mole-rat mRNAs (12,100 full-length CDSs), corresponding to 16,887 genes. The scaffolding of 3488 genes increased the median sequence information 1.27-fold. In total, FRAMA detected and corrected 4774 misassembled genes, which were predominantly caused by fusion of genes. A comparison with three different sources of naked mole-rat transcripts reveals that FRAMA’s gene models are better supported by RNA-seq data than any other transcript set. Further, our results demonstrate the competitiveness of FRAMA to state of the art genome-based transcript reconstruction approaches.

Conclusion

FRAMA realizes the de novo construction of a low-redundant transcript catalog for eukaryotes, including the extension and refinement of transcripts. Thereby, results delivered by FRAMA provide the basis for comprehensive downstream analyses like gene expression studies or comparative transcriptomics. FRAMA is available at https://github.com/gengit/FRAMA.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2349-8) contains supplementary material, which is available to authorized users.

Modelling and simulating generic RNA-Seq experiments with the flux simulator

High-throughput sequencing of cDNA libraries constructed from cellular RNA complements (RNA-Seq) naturally provides a digital quantitative measurement for every expressed RNA molecule. Nature, impact and mutual interference of biases in different experimental setups are, however, still poorly understood—mostly due to the lack of data from intermediate protocol steps. We analysed multiple RNA-Seq experiments, involving different sample preparation protocols and sequencing platforms: we broke them down into their common—and currently indispensable—technical components (reverse transcription, fragmentation, adapter ligation, PCR amplification, gel segregation and sequencing), investigating how such different steps influence abundance and distribution of the sequenced reads. For each of those steps, we developed universally applicable models, which can be parameterised by empirical attributes of any experimental protocol. Our models are implemented in a computer simulation pipeline called the Flux Simulator, and we show that read distributions generated by different combinations of these models reproduce well corresponding evidence obtained from the corresponding experimental setups. We further demonstrate that our in silico RNA-Seq provides insights about hidden precursors that determine the final configuration of reads along gene bodies; enhancing or compensatory effects that explain apparently controversial observations can be observed. Moreover, our simulations identify hitherto unreported sources of systematic bias from RNA hydrolysis, a fragmentation technique currently employed by most RNA-Seq protocols.

Triazole-linked DNA as a primer surrogate in the synthesis of first-strand cDNA

A phosphate-eliminated nonnatural oligonucleotide serves as a primer surrogate in reverse transcription reaction of mRNA. Despite of the nonnatural triazole linkages in the surrogate, the reverse transcriptase effectively elongated cDNA sequences on the 3'-downstream of the primer by transcription of the complementary sequence of mRNA. A structure-activity comparison with the reference natural oligonucleotides shows the superior priming activity of the surrogate containing triazole-linkages. The nonnatural linkages also protect the transcribed cDNA from digestion reactions with 5'-exonuclease and enable us to remove noise transcripts of unknown origins.

A mathematical model for suppression subtractive hybridization

Suppression subtractive hybridization (SSH) is frequently used to unearth differentially expressed genes on a whole-genome scale. Its versatility is based on combining cDNA library subtraction and normalization, which allows the isolation of sequences of varying degrees of abundance and differential expression. SSH is a complex process with many adjustable parameters that affect the outcome of gene isolation.We present a mathematical model of SSH based on DNA hybridization kinetics for assessing the effect of various parameters to facilitate its optimization. We derive an equation for the probability that a particular differentially expressed species is successfully isolated and use this to quantify the effect of the following parameters related to the cDNA sample: (a) mRNA abundance; (b) partial sequence complementarity to other species; and (3) degree of differential expression. We also evaluate the effect of parameters related to the process, including: (a) reaction times; and (b) extent of driver excess used in the two hybridization reactions. The optimum set of process parameters for successful isolation of differentially expressed species depends on transcript abundance. We show that the reaction conditions have a significant effect on the occurrence of false-positives and formulate strategies to isolate specific subsets of differentially expressed genes. We also quantify the effect of non-specific hybridization on the false-positive results and present strategies for spiking cDNA sequences to address this problem.

Mining the gene repertoire and ESTs for G protein-coupled receptors with evolutionary perspective

The purpose of this article was to review recent progress in mining the gene repertoire and expressed sequence tags (ESTs) for the super-family of G protein-coupled receptors (GPCRs) in the form of a proceeding from the Nordic GPCR meeting held at the Nobel Forum, Karolinska Institute in August 2006. We update and give an overview of the expansion of the main families of GPCRs; Glutamate, Rhodopsin, Adhesion, Frizzled and Secretin (GRAFS) in perspective of fully sequenced genomes. We look into the most recent findings including the work that has been carried out on the spotted green puffer fish (Tetraodon nigroviridis), mouse (Mus musculus), chicken (Gallus gallus), slime mold (Dictyostelium discoideum) and the plant pathogenic fungus Magnaporthe grisea. We use examples from our recent work on chicken GPCRs to highlight the importance of detailed assembly and curation of sequences and how that can affect percentage similarity and phylogeny. ESTs can give valuable information about expression patterns. GPCRs have comparatively low numbers of EST suggesting that GPCRs are in generally expressed in lower amount than other genes. We discuss similarities in the evolution of the trace amine associated receptors with other sensory receptors.

Ubiquitous cancer genes: Multipurpose molecules for protein micro-arrays

Multipurpose genes in the human genome which are over-expressed in a large variety of different cancers have been identified. Forty-two of the 19,016 human genes annotated to date (0.2%) are ubiquitously over-expressed in half or more of the 36 investigated human cancers. Of these genes, 15 are involved in protein biosynthesis and folding, six of them in glycolysis. A group of 13 solid tumours over-express almost all (39-42 of 42) ubiquitous cancer genes, suggesting a common mechanism underlying these cancers. Others, such as endocrine cancers, have only a few over-expressed ubiquitous cancer genes. The proteins for which these genes code or the corresponding antibodies are candidates for small protein microarrays aiming at maximum information with only a limited number of proteins. Since the over-expression pattern varies from cancer to cancer, distinction between different cancer classes is possible using one single set of protein or antibody molecules.

Application of functional genomic technologies in a mouse model of retinal degeneration

Generation of tissue-specific, normalized and subtracted cDNA libraries has the potential to characterize the expression of rare transcriptional units not represented on Affymetrix GeneChips. Initial sequence analysis of our murine cDNA clone collections showed that as much as 86, 45, and 30% of clones are not represented on the Affymetrix Mu11k, MG-U74, and MG-430 chip sets, respectively. A detailed study that compared EST sequences of a subtracted library generated from mouse retina to those of MG-430 consensus sequences was undertaken, using UniGene build 124 as the common reference. A set of 1111 nonredundant transcript regions, not represented on the commercial array, was identified. These clusters were used as the primary filter for analyzing a data set produced by assaying samples from the Pde6b(rd1) mouse model of retinal degeneration on a 12,325-feature retinal cDNA microarray. QRT-PCR validated eight unique transcripts identified by microarray. Seven of the transcripts showed retina-specific expression. Full-length cloning strategies were applied to two of the ESTs. The genes discovered by this approach are the full-length mouse homologue of guanylate cyclase 2F (GUCY2F) and a carboxy-truncated splice variant of retinal S-antigen (SAG), known as regulators of the visual phototransduction G-protein-coupled receptor-mediated signaling pathway. These sequences have been assigned GenBank Accession Nos. and , respectively.

Evaluation of EST-data using the genome assembly

Using expressed sequence tag (EST) data for genomewide studies requires thorough understanding of the nature of the problems that are related to handling these sequences. We investigated how EST clustering performs when the genome is used as guidance as compared to pairwise sequence alignment methods. We show that clustering with the genome as a template outperforms sequence similarity methods used to create other EST clusters, such as the UniGene set, in respect to the extent ESTs originating from the same transcriptional unit are separated into disjunct clusters. Using our approach, approximately 80% of the RefSeq genes were represented by a single EST cluster and 20% comprised of two or more EST clusters. In contrast, approximately 25% of all RefSeq genes were found to be represented by a single cluster for the UniGene clustering method. The approach minimizes the risk for overestimations due to the amount of disjunct clusters originating from the same transcript. We have also investigated the quality of EST-data by aligning ESTs to the genome. The results show how many ESTs are not adequately trimmed in respect of vector sequences and low quality regions. Moreover, we identified important problems related to ESTs aligned to the genome using BLAT, such as inferring splice junctions, and explained this aspect by simulations with synthetic data. EST-clusters created with the method are available upon request from the authors.

Genes of glycolysis are ubiquitously overexpressed in 24 cancer classes

Using NIH's public database dbEST for expression of genes and ESTs, genes of the glycolysis pathway have been found to be overexpressed in a set of 24 cancers representing more than 70% of human cancer cases worldwide. Genes can be classified as those that are almost ubiquitously overexpressed, particularly glyceraldehyde-3-phosphate dehydrogenase, enolase 1, and also pyruvate kinase, and those that are overexpressed in less than 50% of the investigated cancers. Cancers can be classified as those with overexpression of the majority of the glycolysis genes, particularly lymph node, prostate, and brain cancer, in which essentially all glycolysis genes are overexpressed, and those with only sporadic overexpression, particularly cancers of the cartilage or bone marrow. This classification may be useful when cancer therapies aimed at the Warburg effect are designed.

The hepatocyte growth factor regulatory factors in human breast cancer

PURPOSE

Hepatocyte growth factor (HGF) stimulates tumor cell-cell interactions, matrix adhesion, migration, invasion, and angiogenesis. This factor is produced as an inactive precursor called pro-HGF, which requires proteolytic conversion, by HGF activator (HGFA) and matriptase, to evoke a biological response. Two new HGFA inhibitors, HAI-1 and HAI-2, inhibit the generation of biologically active HGF, through their interaction with HGFA. This study determined the expression of this HGF regulatory system in breast cancer. We examined HGF, the HGF receptor (c-Met), HGFA, matriptase, and the activation inhibitors (HAI-1 and HAI-2), tissues from patients with breast cancer.

EXPERIMENTAL DESIGN

Breast cancer tissue (n = 100) and normal background tissue (n = 20) was obtained immediately after surgery. The median follow-up for the patients was 72 months. HGF, c-Met, HGFA, matriptase-1, HAI-1, and HAI-2 expression was quantified using real-time quantitative PCR. The distribution of these factors in mammary tissues was also examined through immunohistochemistry.

RESULTS

The breast cancer specimens expressed a significantly higher level of HGF, c-Met, HGFA, HAI-1, and HAI-2, but not matriptase, compared with the normal background tissues. Tumor tissues from node-positive patients expressed a higher level of HGFA than from the patients without nodal involvement. Interestingly, HAI-2 was expressed to a lower degree in positive nodes than that of the node-negative breast cancer tissues. HAI-1 and HAI-2 were both significantly reduced in grade 3 tumors compared with the well-differentiated tumors. In addition, on comparison of Tumor-Node-Metastasis (TNM) classification groups, HAI-2 was also found to be statistically lower in the TNM 3 breast cancer group when compared with TNM groups 1 and 2, thus associated with a poor prognosis.

CONCLUSIONS

This study shows that there are aberrant levels of HGF, c-Met, HGFA, HAI-1, and HAI-2 expressed in breast cancer tissues compared with background breast tissue. HAI-1 and HAI-2 are expressed to a significantly lower level in poorly differentiated breast tumors, and HAI-2 is also inversely correlated with nodal involvement and tumor spread. Overall a low level of HAI-2 in the breast cancer tissues was associated with an overall poor outlook. Therefore, the HGF regulatory system may have an important role in the progression of breast cancer.

Identification of hypothalamic genes implicated in the development of obesity in Psammomys obesus using differential display PCR

The hypothalamus is a key central controller of energy homeostasis and is the source and/or site of action of many neuropeptides involved in this process. The aim of this study was to isolate hypothalamic genes differentially expressed between lean and obese Psammomys obesus, a polygenic animal model of obesity and type 2 diabetes. Differential display PCR was used to compare hypothalamic gene expression profiles of lean and healthy, obese and hyperinsulinemic, and obese, diabetic P. obesus in both the fed and fasted states. We conducted differential display with 180 separate primer combinations to amplify approximately 9,000 expressed transcripts. Sixty differentially expressed bands were excised. Taqman PCR was performed on 36 of these transcripts to confirm differential gene expression in a larger sample population. Of these 36 transcripts, 9 showed homology to known genes, and 27 were considered to be novel sequences. Gene expression profiles for two of these genes are presented here. In conclusion, differential display PCR was successfully used to isolate several transcripts that may be involved in the central regulation of energy balance. We are currently conducting numerous studies to further investigate the role of these genes in the development of obesity in P. obesus.

A sensitive transcriptome analysis method that can detect unknown transcripts

We have developed an AFLP-based gene expression profiling method called 'high coverage expression profiling' (HiCEP) analysis. By making improvements to the selective PCR technique we have reduced the rate of false positive peaks to approximately 4% and consequently the number of peaks, including overlapping peaks, has been markedly decreased. As a result we can determine the relationship between peaks and original transcripts unequivocally. This will make it practical to prepare a database of all peaks, allowing gene assignment without having to isolate individual peaks. This precise selection also enables us to easily clone peaks of interest and predict the corresponding gene for each peak in some species. The procedure is highly reproducible and sensitive enough to detect even a 1.2-fold difference in gene expression. Most importantly, the low false positive rate enables us to analyze gene expression with wide coverage by means of four instead of six nucleotide recognition site restriction enzymes for fingerprinting mRNAs. Therefore, the method detects 70-80% of all transcripts, including non-coding transcripts, unknown and known genes. Moreover, the method requires no sequence information and so is applicable even to eukaryotes for which there is no genome information available.

Systems-wide chicken DNA microarrays, gene expression profiling, and discovery of functional genes

The goal of our current consortium project is to launch a new era--functional genomics of poultry--by providing genomic resources [expressed sequence tags (EST) and DNA microarrays] and by examining global gene expression in target tissues of chickens. DNA microarray analysis has been a fruitful strategy for the identification of functional genes in several model organisms (i.e., human, rodents, fruit fly, etc.). We have constructed and normalized five tissue-specific or multiple-tissue chicken cDNA libraries [liver, fat, breast, and leg muscle/epiphyseal growth plate, pituitary/hypothalamus/pineal, and reproductive tract (oviduct/ovary/testes)] for high-throughput DNA sequencing of EST. DNA sequence clustering was used to build contigs of overlapping sequence and to identify unique, non-redundant EST clones (unigenes), which permitted printing of systems-wide chicken DNA microarrays. One of the most promising genetic resources for gene exploration and functional gene mapping is provided by two sets of experimental lines of broiler-type chickens developed at INRA, France, by divergent selection for extremes in growth traits (fast-growing versus slow-growing; fatness versus leanness at a similar growth rate). We are using DNA microarrays for global gene expression profiling to identify candidate genes and to map growth, metabolic, and regulatory pathways that control important production traits. Candidate genes will be used for functional gene mapping and QTL analysis of F2 progeny from intercrosses made between divergent genetic lines (fat x lean lines; fast-growing x slow-growing lines). Using our first chicken liver microarray, we have already identified several interesting differentially expressed genes in commercial broilers and in divergently selected broiler lines. Many of these candidate genes are involved in the lipogenic pathway and are controlled in part by the thyrotropic axis. Thus, genome-wide transcriptional profiling is a powerful tool used to visualize the cascade of genetic circuits that govern complex biological responses. Global gene expression profiling and QTL scans should enable us to functionally map the genetic pathways that control growth, development, and metabolism of chickens. This emerging technology will have broad applications for poultry breeding programs (i.e., use of molecular markers) and for future production systems (i.e., the health and welfare of birds and the quality of poultry products).

Gene expression profiling in islet biology and diabetes research

Following the sequencing of most of the human and mouse genomes, the next task for physicians and scientists will be to assess the relative levels of expression of these genes during development, following exposure to various nutritional and pharmacological conditions, and in disease states such as diabetes and related metabolic disorders. This review provides an overview of the various methodologies available for monitoring global gene expression. Use of cDNA libraries, Expressed Sequence Tag (EST) sequencing projects and databases, differential display (DD), serial analysis of gene expression (SAGE), subtractive cloning, and both cDNA and oligo microarrays are discussed, along with their merits and limitations. The Endocrine Pancreas Consortium http://www.cbil.upenn.edu/EPConDB/ has constructed mouse and human cDNA libraries from adult and various stages of embryonic development of endocrine pancreas. Over 100,000 ESTs have been deposited in public databases, and each clone is available through the IMAGE Consortium. A guide to Internet access is provided for future investigation.

Gene expression profiling in developing human hippocampus

The gene expression profile of developing human hippocampus is of particular interest and importance to neurobiologists devoted to development of the human brain and related diseases. To gain further molecular insight into the developmental and functional characteristics, we analyzed the expression profile of active genes in developing human hippocampus. Expressed sequence tags (ESTs) were selected by sequencing randomly selected clones from an original 3'-directed cDNA library of 150-day human fetal hippocampus, and a digital expression profile of 946 known genes that could be divided into 16 categories was generated. We also used for comparison 14 other expression profiles of related human neural cells/tissues, including human adult hippocampus. To yield more confidence regarding differential expression, a method was applied to attach normalized expression data to genes with a low false-positive rate (<0.05). Finally, hierarchical cluster analysis was used to exhibit related gene expression patterns. Our results are in accordance with anatomical and physiological observations made during the developmental process of the human hippocampus. Furthermore, some novel findings appeared to be unique to our results. The abundant expression of genes for cell surface components and disease-related genes drew our attention. Twenty-four genes are significantly different from adult, and 13 genes might be developing hippocampus-specific candidate genes, including wnt2b and some Alzheimer's disease-related genes. Our results could provide useful information on the ontogeny, development, and function of cells in the human hippocampus at the molecular level and underscore the utility of large-scale, parallel gene expression analyses in the study of complex biological phenomena.

Identification of differentially expressed genes in Dreissena polymorpha exposed to contaminants

Development of transcriptome analysis methods such as differential display PCR and construction of subtractive libraries now makes it possible to profile gene expression in response to xenobiotic exposure. As an example of application of these methods, zebra mussels (Dreissena polymorpha) were treated with various contaminants such as Aroclor 1254, 3-methylcholanthrene, chrysene and atrazine. A total of 242 mRNAs were identified as differentially expressed. Analysis of these mRNAs should provide valuable information regarding detoxification mechanisms in this bivalve species. In addition, the use of cDNA array technology applied to these gene products may constitute a multi-marker approach to monitor the effect of contamination on this aquatic species.

Change of gene expression profiles in the retina following optic nerve injury

The purpose of the present study was to search for changes in gene expression patterns in the retina following optic nerve injury. We conducted a subtractive hybridization for comparison of the mRNAs in those retinas receiving optic nerve crush injury and those receiving sham operation. Both forward and reverse subtractions were carried out for 8-h and 24-h time points postoperatively. Resultant subtractive cDNA for each group was re-amplified and cloned to a plasmid. After DNA sequencing, the identity of subtractive cDNA was analyzed by blasting sequences to the Nonredundant gene database, Unigene database, and dbest database at NCBI. Thirty-four known genes and 32 EST were found in the forward subtractions. Forty-two known genes and 46 EST were found in reverse subtractions. Identities of the rest could not been found in the databases. To verify the subtractive results, RT-PCR was performed to test expression patterns of eight known genes found in the above analysis. Among these eight genes, seven demonstrated a statistically significant difference between the crushed eyes and the control eyes by quantitative image analysis. Together, our data show that expression of fatso, ephrin B2, NonO, Zfx, vitronectin, and XLRS increased after optic nerve injury, and expression of stathmin exhibited reduction after injury.

Identification of genes induced in peripheral nerve after injury. Expression profiling and novel gene discovery

Peripheral nerve injury results in axonal degeneration and in phenotypic changes of the surrounding Schwann cells, whose presence is critical for nerve regeneration. To identify genes induced after nerve injury in Schwann cells, we developed a strategy that included differential screening of a subtractive library enriched for cDNAs expressed in injured nerve, sequence analysis, and expression profiling. By using real time quantitative reverse transcriptase-polymerase chain reaction, we found that injury-induced genes could be categorized into four temporal expression patterns. Among the clones we identified were a number that were homologous only to expressed sequence tags in the data base. These were stratified based on their expression profile, presence of identifiable sequence motifs, homologies to other proteins, and evolutionary conservation. We chose one representative gene, nin283, to analyze in detail. The nin283 gene encodes a 227-residue protein containing both a zinc finger and a RING finger motif. nin283 is highly expressed in the central nervous system, particularly in the developing cortical plate in embryos. It is also expressed in peripheral ganglia and is induced by nerve growth factor in PC12 cells. Subcellular localization analysis demonstrated that Nin283 is located in the endosome/lysosome compartment, suggesting that it may participate in ubiquitin-mediated protein modification.

Genes in drug abuse

Because of the genome projects it will be possible to identify the changes in gene expression that are associated with drug abuse. The ultimate goal will be to determine the role and significance of the gene products. To date about 100 genes have been found with altered expression after administration of drugs. The development of new technologies such as microarrays will greatly facilitate finding such changes in expression. The rate at which levels of some gene products change is compatible with the time course of development of dependence in animals, but we must be able to establish a cause-effect relationship between genes and drug abuse, which this will be difficult. The product of the novel cocaine and amphetamine regulated transcript (CART) gene is a useful example where a gene product has been associated with drug abuse. CART was identified as an mRNA that changed in response to psychostimulant drug administration and injection of CART peptides into the ventral tegmental area produces psychostimulant-like effects. Definitive evidence, if obtainable, that specific genes are responsible for vulnerability to drug abuse could have dramatic effects on public health policy.

Oligonucleotide microarray expression analysis of genes whose expression is correlated with tumorigenic and non-tumorigenic phenotype of HeLa x human fibroblast hybrid cells

In order to understand the differences and similarities between tumorigenic and non-tumorigenic HeLaxhuman fibroblast hybrids, gene expression profiles were examined with synthetic oligonucleotide arrays containing nearly 7000 gene probe sets. We used two pairs of genetically related hybrids, each pair representing individual clones of non-tumorigenic and tumorigenic segregant hybrids, respectively. Analysis of six possible comparisons, utilizing two algorithms, identified 204 genes with differential expression. The greater number of differentially expressed genes was observed when non-tumorigenic hybrids were compared with tumorigenic segregants. Fifteen and 14 genes, respectively, were consistently found to be differentially expressed in non-tumorigenic and tumorigenic cells. Among those 29 differentially expressed genes, three (intestinal alkaline phosphatase, caveolin-1, and solute carrier family2, member3) have been reported previously to be associated with the tumorigenic phenotype, using the same hybrid pairs. In addition, among the genes previously detected by differential display, 78% of them exhibited more than 5-fold change, demonstrating a high consistency between the two methods of differential gene expression. These findings suggest that synthetic oligonucleotide arrays are a powerful and highly reproducible tool to identify those genes whose expression is associated with certain phenotypes.

Open systems: panoramic views of gene expression

Since their development in the early 1990s, differential gene expression (DGE) technologies have been applied to a multitude of biological challenges, both for the purpose of basic biological research and as a valuable tool for the discovery and development of pharmaceuticals. In this review we survey a class of DGE technologies collectively referred to as 'open' architecture systems. These technologies are distinct from the 'closed' DGE technologies (quantitative PCR, chip technologies), in that no pre-existing biological or sequence information is necessary and they are applicable to any species. Examples of open systems include GeneCalling, SAGE, TOGA, READS, and their progenitor DGE technologies, differential display and cDNA representational difference analysis. We review these technologies and summarize a specific application using GeneCalling for novel gene discovery. Additionally, the significance of data management and experimental design in this new age of expression analysis is discussed.

Recent advances in breast cancer biology

Approximately 1 in 10 US women will be diagnosed with breast cancer in her lifetime. With such a high incidence, breast cancer is a serious health concern for all American women. Within the past year, clues about the function of genes associated with breast cancer have been garnered, and novel genes that may contribute to breast tumorigenesis have been discovered. In addition, unique animal models and improvements in gene expression profiling technology have given researchers new tools to address previously unanswerable questions about this disease.