GeneAnnot: interfacing GeneCards with high-throughput gene expression compendia

Gene Expression Studies to Identify Significant Genes in AR, MTOR, MAPK Pathways and their Overlapping Regulatory Role in Prostate Cancer

Gene expression studies revealed a large degree of variability in gene expression patterns particularly in tissues even in genetically identical individuals. It helps to reveal the components majorly fluctuating during the disease condition. With the advent of gene expression studies many microarray studies have been conducted in prostate cancer, but the results have varied across different studies. To better understand the genetic and biological regulatory mechanisms of prostate cancer, we conducted a meta-analysis of three major pathways i.e. androgen receptor (AR), mechanistic target of rapamycin (mTOR) and Mitogen-Activated Protein Kinase (MAPK) on prostate cancer. Meta-analysis has been performed for the gene expression data for the human species that are exposed to prostate cancer. Twelve datasets comprising AR, mTOR, and MAPK pathways were taken for analysis, out of which thirteen potential biomarkers were identified through meta-analysis. These findings were compiled based upon the quantitative data analysis by using different tools. Also, various interconnections were found amongst the pathways in study. Our study suggests that the microarray analysis of the gene expression data and their pathway level connections allows detection of the potential predictors that can prove to be putative therapeutic targets with biological and functional significance in progression of prostate cancer.

Systematic analysis of the frequently amplified 2p15-p16.1 locus reveals PAPOLG as a potential proto-oncogene in follicular and transformed follicular lymphoma

Transformed follicular lymphoma (tFL) originates from histological transformation of follicular lymphoma (FL), which is the most common indolent non-Hodgkin lymphoma. High-resolution genomic copy-number analysis previously identified frequent amplification of the 2p15-p16.1 locus in FL and tFL cases. The genes (i.e. BCL11A, PAPOLG, PUS10, and USP34) in this amplified locus have not been systematically investigated to date in terms of their role in FL pathogenesis or transformation to tFL. Here we investigated the relationship between amplification and expression of genes in 2p15-p16.1 as well as their expression after histological transformation. NCBI GEO SNP array and gene expression profile (GEP) data of tFL cases were analyzed to evaluate the relationship between amplification and mRNA expression. Moreover, transcript levels of these four genes in FL cases were compared with those of patient-matched tFL cases and normal B-cells. Amplification of the 2p15-p16.1 locus is associated with increased transcription of BCL11A and PAPOLG in tFL cases, of which the latter showed increased expression after histological transformation. Compared with the level in normal B-cells, PAPOLG was significantly overexpressed in FL cases, but expression levels of the other three genes did not show any significant difference. Altogether these results suggest that PAPOLG may be the most critical gene in terms of transformation to tFL.

Potential role of RAB6C-AS1 long noncoding RNA in different cancers

BACKGROUND

Long noncoding RNAs (lncRNAs) refer to a group of non-protein-coding RNAs that are usually more than 200 nucleotides. These long transcripts play significant roles in diverse cellular processes, mostly through epigenetic mechanisms. Thus, dysregulation of lncRNAs is associated with various diseases, especially cancer. This study aims to investigate the probable roles of RAB6C-AS1 lncRNA in different cancers.

METHODS

Real-time quantitative reverse transcription-polymerase chain reaction was applied for the analysis of RAB6C-AS1 lncRNA amplification in gastric cancer (GC) samples compared with normal ones. Also, several online and offline data sets and tools were used to analyze the relation between RAB6C-AS1 lncRNA and different cancers.

RESULTS

The end result of our analyses indicated that RAB6C-AS1 was overexpressed in 40% of the investigated GC specimens. Also, the results demonstrated a true relation between RAB6C-AS1 overexpression and higher GC tumor grades. However, bioinformatic analyses showed that while RAB6C-AS1 possibly functions as an oncogene in some cancer types, including prostate and breast cancers, it might have a tumor suppressive function in some others including brain tumors.

CONCLUSIONS

We found that RAB6C-AS1 lncRNA is mostly overexpressed in GC. Also, based on bioinformatic and systems biology analyses, RAB6C-AS1 might function either as an oncogenic factor or tumor suppressor in a tissue-specific manner. Thus, RAB6C-AS1 could be considered as a candidate biomarker for various malignancies, especially prostate and brain cancers. According to our results, RAB6C-AS1 has a notable prognostic value for patients with brain lower grade glioma.

LocExpress: a web server for efficiently estimating expression of novel transcripts

Background

The temporal and spatial-specific expression pattern of a transcript in multiple tissues and cell types can indicate key clues about its function. While several gene atlas available online as pre-computed databases for known gene models, it’s still challenging to get expression profile for previously uncharacterized (i.e. novel) transcripts efficiently.

Results

Here we developed LocExpress, a web server for efficiently estimating expression of novel transcripts across multiple tissues and cell types in human (20 normal tissues/cells types and 14 cell lines) as well as in mouse (24 normal tissues/cell types and nine cell lines). As a wrapper to RNA-Seq quantification algorithm, LocExpress efficiently reduces the time cost by making abundance estimation calls increasingly within the minimum spanning bundle region of input transcripts. For a given novel gene model, such local context-oriented strategy allows LocExpress to estimate its FPKMs in hundreds of samples within minutes on a standard Linux box, making an online web server possible.

Conclusions

To the best of our knowledge, LocExpress is the only web server to provide nearly real-time expression estimation for novel transcripts in common tissues and cell types. The server is publicly available at http://loc-express.cbi.pku.edu.cn.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3329-3) contains supplementary material, which is available to authorized users.

Navigating public microarray databases

With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources.

Consistent annotation of gene expression arrays

Background

Gene expression arrays are valuable and widely used tools for biomedical research. Today's commercial arrays attempt to measure the expression level of all of the genes in the genome. Effectively translating the results from the microarray into a biological interpretation requires an accurate mapping between the probesets on the array and the genes that they are targeting. Although major array manufacturers provide annotations of their gene expression arrays, the methods used by various manufacturers are different and the annotations are difficult to keep up to date in the rapidly changing world of biological sequence databases.

Results

We have created a consistent microarray annotation protocol applicable to all of the major array manufacturers. We constantly keep our annotations updated with the latest Ensembl Gene predictions, and thus cross-referenced with a large number of external biomedical sequence database identifiers. We show that these annotations are accurate and address in detail reasons for the minority of probesets that cannot be annotated. Annotations are publicly accessible through the Ensembl Genome Browser and programmatically through the Ensembl Application Programming Interface. They are also seamlessly integrated into the BioMart data-mining tool and the biomaRt package of BioConductor.

Conclusions

Consistent, accurate and updated gene expression array annotations remain critical for biological research. Our annotations facilitate accurate biological interpretation of gene expression profiles.

GIFtS: annotation landscape analysis with GeneCards

BACKGROUND

Gene annotation is a pivotal component in computational genomics, encompassing prediction of gene function, expression analysis, and sequence scrutiny. Hence, quantitative measures of the annotation landscape constitute a pertinent bioinformatics tool. GeneCards is a gene-centric compendium of rich annotative information for over 50,000 human gene entries, building upon 68 data sources, including Gene Ontology (GO), pathways, interactions, phenotypes, publications and many more.

RESULTS

We present the GeneCards Inferred Functionality Score (GIFtS) which allows a quantitative assessment of a gene's annotation status, by exploiting the unique wealth and diversity of GeneCards information. The GIFtS tool, linked from the GeneCards home page, facilitates browsing the human genome by searching for the annotation level of a specified gene, retrieving a list of genes within a specified range of GIFtS value, obtaining random genes with a specific GIFtS value, and experimenting with the GIFtS weighting algorithm for a variety of annotation categories. The bimodal shape of the GIFtS distribution suggests a division of the human gene repertoire into two main groups: the high-GIFtS peak consists almost entirely of protein-coding genes; the low-GIFtS peak consists of genes from all of the categories. Cluster analysis of GIFtS annotation vectors provides the classification of gene groups by detailed positioning in the annotation arena. GIFtS also provide measures which enable the evaluation of the databases that serve as GeneCards sources. An inverse correlation is found (for GIFtS>25) between the number of genes annotated by each source, and the average GIFtS value of genes associated with that source. Three typical source prototypes are revealed by their GIFtS distribution: genome-wide sources, sources comprising mainly highly annotated genes, and sources comprising mainly poorly annotated genes. The degree of accumulated knowledge for a given gene measured by GIFtS was correlated (for GIFtS>30) with the number of publications for a gene, and with the seniority of this entry in the HGNC database.

CONCLUSION

GIFtS can be a valuable tool for computational procedures which analyze lists of large set of genes resulting from wet-lab or computational research. GIFtS may also assist the scientific community with identification of groups of uncharacterized genes for diverse applications, such as delineation of novel functions and charting unexplored areas of the human genome.

Integrative modeling of transcriptional regulation in response to antirheumatic therapy

Background

The investigation of gene regulatory networks is an important issue in molecular systems biology and significant progress has been made by combining different types of biological data. The purpose of this study was to characterize the transcriptional program induced by etanercept therapy in patients with rheumatoid arthritis (RA). Etanercept is known to reduce disease symptoms and progression in RA, but the underlying molecular mechanisms have not been fully elucidated.

Results

Using a DNA microarray dataset providing genome-wide expression profiles of 19 RA patients within the first week of therapy we identified significant transcriptional changes in 83 genes. Most of these genes are known to control the human body's immune response. A novel algorithm called TILAR was then applied to construct a linear network model of the genes' regulatory interactions. The inference method derives a model from the data based on the Least Angle Regression while incorporating DNA-binding site information. As a result we obtained a scale-free network that exhibits a self-regulating and highly parallel architecture, and reflects the pleiotropic immunological role of the therapeutic target TNF-alpha. Moreover, we could show that our integrative modeling strategy performs much better than algorithms using gene expression data alone.

Conclusion

We present TILAR, a method to deduce gene regulatory interactions from gene expression data by integrating information on transcription factor binding sites. The inferred network uncovers gene regulatory effects in response to etanercept and thus provides useful hypotheses about the drug's mechanisms of action.

Changes in red cell ion transport, reduced intratumoral neovascularization, and some mild motor function abnormalities accompany targeted disruption of the Mouse Kell gene (Kel)

Kell (ECE-3), a highly polymorphic blood group glycoprotein, displays more than 30 antigens that produce allo-antibodies and, on red blood cells (RBCs), is complexed through a single disulfide bond with the integral membrane protein, XK. XK is a putative membrane transporter whose absence results in a late onset form of neuromuscular abnormalities known as the McLeod syndrome. Although Kell glycoprotein is known to be an endothelin-3-converting enzyme, the full extent of its physiological function is unknown. To study the functions of Kell glycoprotein, we undertook targeted disruption of the murine Kel gene by homologous recombination. RBCs from Kel(-/-) mice lacked Kell glycoprotein, Kell/XK complex, and endothelin-3-converting enzyme activity and had reduced levels of XK. XK mRNA levels in spleen, brain, and testis were unchanged. In Kel(-/-) mice RBC Gardos channel activity was increased and the normal enhancement by endothelin-3 was blunted. Analysis of the microvessels of tumors produced from LL2 cells indicated that the central portion of tumors from wild-type mice were populated with many mature blood vessels, but that vessels in tumors from Kel(-/-) mice were fewer and smaller. The absence of Kell glycoprotein mildly affected some motor activities identified by foot splay on the drop tests. The targeted disruption of Kel in mouse enabled us to identify phenotypes that would not be easily detected in humans lacking Kell glycoprotein. In this regard, the Kell knockout mouse provides a good animal model for the study of normal and/or pathophysiological functions of Kell glycoprotein.

Human self-protein CD8+ T-cell epitopes are both positively and negatively selected

The cellular immune system recognizes self-epitopes in the context of MHC-I molecules. The immunological general view presumes that these self-epitopes are just a background, both positively and negatively selecting T cells. We here estimate the number of epitopes in each human protein for many frequent HLA alleles, and a score representing over or under presentation of epitopes on these proteins. We further show that there is a clear selection for the presentation of specific self-protein types. Proteins presenting many epitopes include, for example, autoimmune regulator (AIRE) upregulated tissue-specific antigens, immune system receptors and proteins with a high expression level. On the other hand, proteins that may be considered less "useful" for the immune system, such as low expression level proteins, are under-presented. We combine our epitope estimate with single nucleotide polymorphism (SNP) measures to show that this selection can be directly observed through the fraction of non-synonymous SNP (replacement fraction), which is significantly higher inside epitopes than outside.

Mechanical strain activates a program of genes functionally involved in paracrine signaling of angiogenesis

Studies were performed to examine the extent to which mechanical stimuli mediate control of angiogenesis in bladder cells both in vitro and in vivo. Differential gene expression between control nonstretched and cyclically stretched bladder smooth muscle cells was assessed using oligonucleotide microarrays and pathway analysis by the web tool Fast Assignment and Transference of Information (FatiGO). Data showed that a substantial proportion (33 of 86) of mechanically responsive genes were angiogenesis-related and include cytokines, growth-related factors, adhesion proteins, and matricellular, signal transduction, extracellular matrix (ECM), and inflammatory molecules. Integrative knowledge of protein-protein interactions revealed that 12 mechano-sensitive gene-encoded proteins have interacting partner(s) in the vascular system confirming their potential role in paracrine regulation of angiogenesis. Angiogenic genes include matricellular proteins such as Cyr61/CCN1, CTGF/CCN2 and tenascin C, components of the VEGF and IGF systems, ECM proteins such as type I collagen and proteoglycans, and matrix metalloproteinases. In an in vivo model of bladder overdistension, 5 of 11 mechano-responsive angiogenic genes, independently tested by real-time PCR, were upregulated as a result of pressure overload including Cyr61/CCN1, CTGF/CCN2, MCP-1, VEGF-A, MMP-1, and midkine. Meanwhile, the molecular anatomy of angiogenic gene promoters reveals the presence of GA box-binding for the myc-associated zinc finger protein, MAZ, often found adjacent to binding sites for mechano-responsive transcription factors (e.g., NF-kappaB), suggesting that the coordinated activity of these factors may induce selective angiogenic gene transcription. These data suggest that mechanical control of angiogenic genes is an integral part of the adaptive and plasticity responses to mechanical overload.

Genomic sequence of a clonal isolate of the vaccinia virus Lister strain employed for smallpox vaccination in France and its comparison to other orthopoxviruses

Since 1980 there has been global eradication of smallpox due to the success of the vaccination programme using vaccinia virus (VACV). During the eradication period, distinct VACV strains circulated, the Lister strain being the most commonly employed in Europe. Analysis of the safety of smallpox vaccines has suggested that they display significant heterogeneity. To gain a more detailed understanding of the diversity of VACV strains it is important to determine their genomic sequences. Although the sequences of three isolates of the Japanese Lister original strain (VACV-LO) are available, no analysis of the relationship of any Lister sequence compared to other VACV genomes has been reported. Here, we describe the sequence of a representative clonal isolate of the Lister vaccine (VACV-List) used to inoculate the French population. The coding capacity of VACV-List was compared to other VACV strains. The 201 open reading frames (ORFs) were annotated in the VACV-List genome based on protein size, genomic localization and prior characterization of many ORFs. Eleven ORFs were recognized as pseudogenes as they were truncated or fragmented counterparts of larger ORFs in other orthopoxviruses (OPVs). The VACV-List genome also contains several ORFs that have not been annotated in other VACVs but were found in other OPVs. VACV-List and VACV-LO displayed a high level of nucleotide sequence similarity. Compared to the Copenhagen strain of VACV, the VACV-List sequence diverged in three main regions, one of them corresponding to a substitution in VACV-List with coxpox virus GRI-90 strain ORFs, suggestive of prior genetic exchanges. These studies highlight the heterogeneity between VACV strains and provide a basis to better understand differences in safety and efficacy of smallpox vaccines.

Changes in the transcriptional profile of transporters in the intestine along the anterior-posterior and crypt-villus axes

Background

The purpose of this work was to characterize the expression of drug and nutrient carriers along the anterior-posterior and crypt-villus axes of the intestinal epithelium and to study the validity of utilizing whole gut tissue rather than purified epithelial cells to examine regional variations in gene expression.

Results

We have characterized the mRNA expression profiles of 76 % of all currently known transporters along the anterior-posterior axis of the gut. This is the first study to describe the expression profiles of the majority of all known transporters in the intestine. The expression profiles of transporters, as defined according to the Gene Ontology consortium, were measured in whole tissue of the murine duodenum, jejunum, ileum and colon using high-density microarrays. For nine transporters (Abca1, Abcc1, Abcc3, Abcg8, Slc10a2, Slc28a2, Slc2a1, Slc34a2 and Slc5a8), the mRNA profiles were further measured by RT-PCR in laser micro-dissected crypt and villus epithelial cells corresponding to the aforementioned intestinal regions. With respect to differentially regulated transporters, the colon had a distinct expression profile from small intestinal segments. The majority (59 % for p cutoff ≤ 0.05) of transporter mRNA levels were constant across the intestinal sections studied. For the transporter subclass "carrier activity", which contains the majority of known carriers for biologically active compounds, a significant change (p ≤ 0.05) along the anterior-posterior axis was observed.

Conclusion

All nine transporters examined in laser-dissected material demonstrated good replication of the region-specific profiles revealed by microarray. Furthermore, we suggest that the distribution characteristics of Slc5a8 along the intestinal tract render it a suitable candidate carrier for monocarboxylate drugs in the posterior portion of the intestine. Our findings also predict that there is a significant difference in the absorption of carrier-mediated compounds in the different intestinal segments. The most pronounced differences can be expected between the adjoining segments ileum and colon, but the differences between the other adjoining segments are not negligible. Finally, for the examined genes, profiles measured in whole intestinal tissue extracts are representative of epithelial cell-only gene expression.

Combining gene expression data from different generations of oligonucleotide arrays

BACKGROUND

One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform.

RESULTS

We first describe the extent of discordance between the results derived from two generations of Affymetrix oligonucleotide arrays, as revealed in cluster analysis and in identification of differentially expressed genes. We then propose a method for increasing comparability. The dataset we use consists of a set of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays. We find that the use of the probe set matching table for comparative analysis provided by Affymetrix produces better results than matching by UniGene or LocusLink identifiers but still remains inadequate. Rescaling of expression values for each gene across samples and data filtering by expression values enhance comparability but only for few specific analyses. As a generic method for improving comparability, we select a subset of probes with overlapping sequence segments in the two array types and recalculate expression values based only on the selected probes. We show that this filtering of probes significantly improves the comparability while retaining a sufficient number of probe sets for further analysis.

CONCLUSIONS

Compatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different generations of microarrays can be combined more effectively.

Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification

MOTIVATION

Genes are often characterized dichotomously as either housekeeping or single-tissue specific. We conjectured that crucial functional information resides in genes with midrange profiles of expression.

RESULTS

To obtain such novel information genome-wide, we have determined the mRNA expression levels for one of the largest hitherto analyzed set of 62 839 probesets in 12 representative normal human tissues. Indeed, when using a newly defined graded tissue specificity index tau, valued between 0 for housekeeping genes and 1 for tissue-specific genes, genes with midrange profiles having 0.15< tau<0.85 were found to constitute >50% of all expression patterns. We developed a binary classification, indicating for every gene the I(B) tissues in which it is overly expressed, and the 12-I(B) tissues in which it shows low expression. The 85 dominant midrange patterns with I(B)=2-11 were found to be bimodally distributed, and to contribute most significantly to the definition of tissue specification dendrograms. Our analyses provide a novel route to infer expression profiles for presumed ancestral nodes in the tissue dendrogram. Such definition has uncovered an unsuspected correlation, whereby de novo enhancement and diminution of gene expression go hand in hand. These findings highlight the importance of gene suppression events, with implications to the course of tissue specification in ontogeny and phylogeny.

AVAILABILITY

All data and analyses are publically available at the GeneNote website, http://genecards.weizmann.ac.il/genenote/ and, GEO accession GSE803.

CONTACT

doron.lancet@weizmann.ac.il

SUPPLEMENTARY INFORMATION

Four tables available at the above site.

ProbeLynx: a tool for updating the association of microarray probes to genes

As genome sequence data and gene prediction improve, probes developed for a given microarray experiment should be continuously re-evaluated for their specificity for given genes. ProbeLynx(www.pathogenomics.ca/probelynx) is a new web service which uses current genomic sequence information to re-examine microarray probe specificity and provide annotation updates relevant to determining which gene(s) and transcript(s) are associated with a given probe. Probe sequences (either oligonucleotide- or cDNA-based) are uploaded in FASTA format and the results returned as a tab-delimited flat file for insertion into a spreadsheet application or database management system for further analysis. ProbeLynx has been initially developed to focus on arrays derived from human, mouse, chicken and bovine genomes, but may be expanded to handle other genomic datasets. ProbeLynx offers microarray users the important ability to continuously assess the potential of a probe to cross-hybridize to paralogous genes and the suitability of a given probe to investigate a transcript of interest. By also including the latest gene function annotation information in the output, ProbeLynx provides the critical first step in updating microarray data annotation.