In silico identification of conserved intercoding sequences in Leishmania genomes: Unraveling putative cis-regulatory elements

In silico analyses of Leishmania spp. genome data are a powerful resource to improve the understanding of these pathogens' biology. Trypanosomatids such as Leishmania spp. have their protein-coding genes grouped in long polycistronic units of functionally unrelated genes. The control of gene expression happens by a variety of posttranscriptional mechanisms. The high degree of synteny among Leishmania species is accompanied by highly conserved coding sequences (CDS) and poorly conserved intercoding untranslated sequences. To identify the elements involved in the control of gene expression, we conducted an in silico investigation to find conserved intercoding sequences (CICS) in the genomes of L major, L infantum, and L braziliensis. We used a combination of computational tools, such as Linux-Shell, PERL and R languages, BLAST, MSPcrunch, SSAKE, and Pred-A-Term algorithms to construct a pipeline which was able to: (i) search for conservation in target-regions, (ii) eliminate CICS redundancy and mask repeat elements, (iii) predict the mRNA's extremities, (iv) analyze the distribution of orthologous genes within the generated LeishCICS-clusters, (v) assign GO terms to the LeishCICS-clusters. and (vi) provide statistical support for the gene-enrichment annotation. We associated the LeishCICS-cluster data, generated at the end of the pipeline, with the expression profile oft. donovani genes during promastigote-amastigote differentiation, as previously evaluated by others (GEO accession: GSE21936). A Pearson's correlation coefficient greater than 0.5 was observed for 730 LeishCICS-clusters containing from 2 to 17 genes. The designed computational pipeline is a useful tool and its application identified potential regulatory cis elements and putative regulons in Leishmania. (C) 2012 Elsevier B.V. All rights reserved.

Enrichment of pathogenic alleles in the brittle cornea gene, ZNF469, in keratoconus.

Keratoconus, a common inherited ocular disorder resulting in progressive corneal thinning, is the leading indication for corneal transplantation in the developed world. Genome-wide association studies have identified common SNPs 100 kb upstream of ZNF469 strongly associated with corneal thickness. Homozygous mutations in ZNF469 and PR domain-containing protein 5 (PRDM5) genes result in brittle cornea syndrome (BCS) Types 1 and 2, respectively. BCS is an autosomal recessive generalized connective tissue disorder associated with extreme corneal thinning and a high risk of corneal rupture. Some individuals with heterozygous PRDM5 mutations demonstrate a carrier ocular phenotype, which includes a mildly reduced corneal thickness, keratoconus and blue sclera. We hypothesized that heterozygous variants in PRDM5 and ZNF469 predispose to the development of isolated keratoconus. We found a significant enrichment of potentially pathologic heterozygous alleles in ZNF469 associated with the development of keratoconus (P = 0.00102) resulting in a relative risk of 12.0. This enrichment of rare potentially pathogenic alleles in ZNF469 in 12.5% of keratoconus patients represents a significant mutational load and highlights ZNF469 as the most significant genetic factor responsible for keratoconus identified to date.

Extensions to Gene Set Enrichment

Motivation: Gene Set Enrichment Analysis (GSEA) has been developed recently to capture moderate but coordinated changes in the expression of sets of functionally related genes. We propose number of extensions to GSEA, which uses different statistics to describe the association between genes and phenotype of interest. We make use of dimension reduction procedures, such as principle component analysis to identify gene sets containing coordinated genes. We also address the problem of overlapping among gene sets in this paper. Results: We applied our methods to the data come from a clinical trial in acute lymphoblastic leukemia (ALL) [1]. We identified interesting gene sets using different statistics. We find that gender may have effects on the gene expression in addition to the phenotype effects. Investigating overlap among interesting gene sets indicate that overlapping could alter the interpretation of the significant results.

GENE SET ENRICHMENT ANALYSIS MADE SIMPLE

Among the many applications of microarray technology, one of the most popular is the identification of genes that are differentially expressed in two conditions. A common statistical approach is to quantify the interest of each gene with a p-value, adjust these p-values for multiple comparisons, chose an appropriate cut-off, and create a list of candidate genes. This approach has been criticized for ignoring biological knowledge regarding how genes work together. Recently a series of methods, that do incorporate biological knowledge, have been proposed. However, many of these methods seem overly complicated. Furthermore, the most popular method, Gene Set Enrichment Analysis (GSEA), is based on a statistical test known for its lack of sensitivity. In this paper we compare the performance of a simple alternative to GSEA.We find that this simple solution clearly outperforms GSEA.We demonstrate this with eight different microarray datasets.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Sequential analysis of global gene expression profiles in immature and in vitro matured bovine oocytes: potential molecular markers of oocyte maturation

Background: Without intensive selection, the majority of bovine oocytes submitted to in vitro embryo production (IVP) fail to develop to the blastocyst stage. This is attributed partly to their maturation status and competences. Using the Affymetrix GeneChip Bovine Genome Array, global mRNA expression analysis of immature (GV) and in vitro matured (IVM) bovine oocytes was carried out to characterize the transcriptome of bovine oocytes and then use a variety of approaches to determine whether the observed transcriptional changes during IVM was real or an artifact of the techniques used during analysis. Results: 8489 transcripts were detected across the two oocyte groups, of which similar to 25.0% (2117 transcripts) were differentially expressed (p < 0.001); corresponding to 589 over-expressed and 1528 under-expressed transcripts in the IVM oocytes compared to their immature counterparts. Over expression of transcripts by IVM oocytes is particularly interesting, therefore, a variety of approaches were employed to determine whether the observed transcriptional changes during IVM were real or an artifact of the techniques used during analysis, including the analysis of transcript abundance in oocytes in vitro matured in the presence of a-amanitin. Subsets of the differentially expressed genes were also validated by quantitative real-time PCR (qPCR) and the gene expression data was classified according to gene ontology and pathway enrichment. Numerous cell cycle linked (CDC2, CDK5, CDK8, HSPA2, MAPK14, TXNL4B), molecular transport (STX5, STX17, SEC22A, SEC22B), and differentiation (NACA) related genes were found to be among the several over-expressed transcripts in GV oocytes compared to the matured counterparts, while ANXA1, PLAU, STC1and LUM were among the over-expressed genes after oocyte maturation. Conclusion: Using sequential experiments, we have shown and confirmed transcriptional changes during oocyte maturation. This dataset provides a unique reference resource for studies concerned with the molecular mechanisms controlling oocyte meiotic maturation in cattle, addresses the existing conflicting issue of transcription during meiotic maturation and contributes to the global goal of improving assisted reproductive technology.

A gene-rich, transcriptionally active environment and the pre-deposition of repressive marks are predictive of susceptibility to KRAB/KAP1-mediated silencing.

AbstractBACKGROUND: KRAB-ZFPs (Krüppel-associated box domain-zinc finger proteins) are vertebrate-restricted transcriptional repressors encoded in the hundreds by the mouse and human genomes. They act via an essential cofactor, KAP1, which recruits effectors responsible for the formation of facultative heterochromatin. We have recently shown that KRAB/KAP1 can mediate long-range transcriptional repression through heterochromatin spreading, but also demonstrated that this process is at times countered by endogenous influences.METHOD: To investigate this issue further we used an ectopic KRAB-based repressor. This system allowed us to tether KRAB/KAP1 to hundreds of euchromatic sites within genes, and to record its impact on gene expression. We then correlated this KRAB/KAP1-mediated transcriptional effect to pre-existing genomic and chromatin structures to identify specific characteristics making a gene susceptible to repression.RESULTS: We found that genes that were susceptible to KRAB/KAP1-mediated silencing carried higher levels of repressive histone marks both at the promoter and over the transcribed region than genes that were insensitive. In parallel, we found a high enrichment in euchromatic marks within both the close and more distant environment of these genes.CONCLUSION: Together, these data indicate that high levels of gene activity in the genomic environment and the pre-deposition of repressive histone marks within a gene increase its susceptibility to KRAB/KAP1-mediated repression.

Gene expression mapping in neuropathic pain : molecular plasticity in nociceptors and superficial dorsal horn

RESUME : La douleur neuropathique est le résultat d'une lésion ou d'un dysfonctionnement du système nerveux. Les symptômes qui suivent la douleur neuropathique sont sévères et leur traitement inefficace. Une meilleure approche thérapeutique peut être proposée en se basant sur les mécanismes pathologiques de la douleur neuropathique. Lors d'une lésion périphérique une douleur neuropathique peut se développer et affecter le territoire des nerfs lésés mais aussi les territoires adjacents des nerfs non-lésés. Une hyperexcitabilité des neurones apparaît au niveau des ganglions spinaux (DRG) et de la corne dorsale (DH) de la moelle épinière. Le but de ce travail consiste à mettre en évidence les modifications moléculaires associées aux nocicepteurs lésés et non-lésés au niveau des DRG et des laminae I et II de la corne dorsale, là où l'information nociceptive est intégrée. Pour étudier les changements moléculaires liés à la douleur neuropathique nous utilisons le modèle animal d'épargne du nerf sural (spared nerve injury model, SNI) une semaine après la lésion. Pour la sélection du tissu d'intérêt nous avons employé la technique de la microdissection au laser, afin de sélectionner une sous-population spécifique de cellules (notamment les nocicepteurs lésés ou non-lésés) mais également de prélever le tissu correspondant dans les laminae superficielles. Ce travail est couplé à l'analyse à large spectre du transcriptome par puce ADN (microarray). Par ailleurs, nous avons étudié les courants électriques et les propriétés biophysiques des canaux sodiques (Na,,ls) dans les neurones lésés et non-lésés des DRG. Aussi bien dans le système nerveux périphérique, entre les neurones lésés et non-lésés, qu'au niveau central avec les aires recevant les projections des nocicepteurs lésés ou non-lésés, l'analyse du transcriptome montre des différences de profil d'expression. En effet, nous avons constaté des changements transcriptionnels importants dans les nocicepteurs lésés (1561 gènes, > 1.5x et pairwise comparaison > 77%) ainsi que dans les laminae correspondantes (618 gènes), alors que ces modifications transcriptionelles sont mineures au niveau des nocicepteurs non-lésés (60 gènes), mais important dans leurs laminae de projection (459 gènes). Au niveau des nocicepteurs, en utilisant la classification par groupes fonctionnels (Gene Ontology), nous avons observé que plusieurs processus biologiques sont modifiés. Ainsi des fonctions telles que la traduction des signaux cellulaires, l'organisation du cytosquelette ainsi que les mécanismes de réponse au stress sont affectés. Par contre dans les neurones non-lésés seuls les processus biologiques liés au métabolisme et au développement sont modifiés. Au niveau de la corne dorsale de la moelle, nous avons observé des modifications importantes des processus immuno-inflammatoires dans l'aire affectée par les nerfs lésés et des changements associés à l'organisation et la transmission synaptique au niveau de l'aire des nerfs non-lésés. L'analyse approfondie des canaux sodiques a démontré plusieurs changements d'expression, principalement dans les neurones lésés. Les analyses fonctionnelles n'indiquent aucune différence entre les densités de courant tétrodotoxine-sensible (TTX-S) dans les neurones lésés et non-lésés même si les niveaux d'expression des ARNm des sous-unités TTX-S sont modifiés dans les neurones lésés. L'inactivation basale dépendante du voltage des canaux tétrodotoxine-insensible (TTX-R) est déplacée vers des potentiels positifs dans les cellules lésées et non-lésées. En revanche la vitesse de récupération des courants TTX-S et TTX-R après inactivation est accélérée dans les neurones lésés. Ces changements pourraient être à l'origine de l'altération de l'activité électrique des neurones sensoriels dans le contexte des douleurs neuropathiques. En résumé, ces résultats suggèrent l'existence de mécanismes différenciés affectant les neurones lésés et les neurones adjacents non-lésés lors de la mise en place la douleur neuropathique. De plus, les changements centraux au niveau de la moelle épinière qui surviennent après lésion sont probablement intégrés différemment selon la perception de signaux des neurones périphériques lésés ou non-lésés. En conclusion, ces modulations complexes et distinctes sont probablement des acteurs essentiels impliqués dans la genèse et la persistance des douleurs neuropathiques. ABSTRACT : Neuropathic pain (NP) results from damage or dysfunction of the peripheral or central nervous system. Symptoms associated with NP are severe and difficult to treat. Targeting NP mechanisms and their translation into symptoms may offer a better therapeutic approach.Hyperexcitability of the peripheral and central nervous system occurs in the dorsal root ganglia (DRG) and the dorsal horn (DH) of the spinal cord. We aimed to identify transcriptional variations in injured and in adjacent non-injured nociceptors as well as in corresponding laminae I and II of DH receiving their inputs.We investigated changes one week after the injury induced by the spared nerve injury model of NP. We employed the laser capture microdissection (LCM) for the procurement of specific cell-types (enrichment in nociceptors of injured/non-injured neurons) and laminae in combination with transcriptional analysis by microarray. In addition, we studied functionál properties and currents of sodium channels (Nav1s) in injured and neighboring non-injured DRG neurons.Microarray analysis at the periphery between injured and non-injured DRG neurons and centrally between the area of central projections from injured and non-injured neurons show significant and differential expression patterns. We reported changes in injured nociceptors (1561 genes, > 1.5 fold, >77% pairwise comparison) and in corresponding DH laminae (618 genes), while less modifications occurred in non-injured nociceptors (60 genes) and in corresponding DH laminae (459 genes). At the periphery, we observed by Gene Ontology the involvement of multiple biological processes in injured neurons such as signal transduction, cytoskeleton organization or stress responses. On contrast, functional overrepresentations in non-injured neurons were noted only in metabolic or developmentally related mechanisms. At the level of superficial laminae of the dorsal horn, we reported changes of immune and inflammatory processes in injured-related DH and changes associated with synaptic organization and transmission in DH corresponding to non-injured neurons. Further transcriptional analysis of Nav1s indicated several changes in injured neurons. Functional analyses of Nav1s have established no difference in tetrodotoxin-sensitive (TTX-S) current densities in both injured and non-injured neurons, despite changes in TTX-S Nav1s subunit mRNA levels. The tetrodotoxin-resistant (TTX-R) voltage dependence of steady state inactivation was shifted to more positive potentials in both injured and non-injured neurons, and the rate of recovery from inactivation of TTX-S and TTX-R currents was accelerated in injured neurons. These changes may lead to alterations in neuronal electrogenesis. Taken together, these findings suggest different mechanisms occurring in the injured neurons and the adjacent non-injured ones. Moreover, central changes after injury are probably driven in a different manner if they receive inputs from injured or non-injured neurons. Together, these distinct and complex modulations may contribute to NP.

Very low prevalence of meticillin-resistant Staphylococcus aureus carrying the mecC gene in western Switzerland.

We report the first case of meticillin-resistant Staphylococcus aureus (MRSA) with the mecC gene in a patient in western Switzerland. After this first identification, a polymerase chain reaction protocol was established to investigate the occurrence of this new mecC gene in the population of this region. Enrichment broths were investigated from 1062 patients screened for MRSA, meticillin-susceptible Staphylococcus aureus isolates from clinical specimens from 475 patients, and 80 MRSA isolates (from 2005 to 2011) showing discrepancies between genotypic and phenotypic meticillin resistance. None was positive for mecC, suggesting that it is rare in the patient population of this region.

GSVA: gene set variation analysis for microarray and RNA-seq data

Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.

Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer.

The recognition that colorectal cancer (CRC) is a heterogeneous disease in terms of clinical behaviour and response to therapy translates into an urgent need for robust molecular disease subclassifiers that can explain this heterogeneity beyond current parameters (MSI, KRAS, BRAF). Attempts to fill this gap are emerging. The Cancer Genome Atlas (TGCA) reported two main CRC groups, based on the incidence and spectrum of mutated genes, and another paper reported an EMT expression signature defined subgroup. We performed a prior free analysis of CRC heterogeneity on 1113 CRC gene expression profiles and confronted our findings to established molecular determinants and clinical, histopathological and survival data. Unsupervised clustering based on gene modules allowed us to distinguish at least five different gene expression CRC subtypes, which we call surface crypt-like, lower crypt-like, CIMP-H-like, mesenchymal and mixed. A gene set enrichment analysis combined with literature search of gene module members identified distinct biological motifs in different subtypes. The subtypes, which were not derived based on outcome, nonetheless showed differences in prognosis. Known gene copy number variations and mutations in key cancer-associated genes differed between subtypes, but the subtypes provided molecular information beyond that contained in these variables. Morphological features significantly differed between subtypes. The objective existence of the subtypes and their clinical and molecular characteristics were validated in an independent set of 720 CRC expression profiles. Our subtypes provide a novel perspective on the heterogeneity of CRC. The proposed subtypes should be further explored retrospectively on existing clinical trial datasets and, when sufficiently robust, be prospectively assessed for clinical relevance in terms of prognosis and treatment response predictive capacity. Original microarray data were uploaded to the ArrayExpress database (http://www.ebi.ac.uk/arrayexpress/) under Accession Nos E-MTAB-990 and E-MTAB-1026. © 2013 Swiss Institute of Bioinformatics. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

The direct effects of tacrolimus and cyclosporin A on isolated human islets: A functional, survival and gene expression study.

The use of immunosuppressive drugs in transplanted patients is associated with the development of diabetes, possibly due to β-cell toxicity. To better understand the mechanisms leading to post-transplant diabetes, we investigated the actions of prolonged exposure of isolated human islets to therapeutical levels of tacrolimus (Tac) or cyclosporin A (CsA). Islets were isolated from the pancreas of multiorgan donors by enzymatic digestion and density gradient centrifugation. Functional, survival and molecular studies were then performed after 4 days of incubation with therapeutical concentrations of Tac or  CsA. Glucose-induced insulin secretion was significantly decreased in Tac, but not in CsA exposed islets, which was associated with a reduction of the amount of insulin granules as shown by electron microscopy. The percentage of apoptotic β-cells was higher in Tac than CsA exposed islets. Microarray experiments followed by Gene Set Enrichment Analysis revealed that gene expression was more markedly affected upon Tac treatment. In conclusion, Tac and CsA affect features of beta-cell differently, with several changes occurring at the molecular level.

Learning-induced gene expression in the heads of two Nasonia species that differ in long-term memory formation.

BACKGROUND: Cellular processes underlying memory formation are evolutionary conserved, but natural variation in memory dynamics between animal species or populations is common. The genetic basis of this fascinating phenomenon is poorly understood. Closely related species of Nasonia parasitic wasps differ in long-term memory (LTM) formation: N. vitripennis will form transcription-dependent LTM after a single conditioning trial, whereas the closely-related species N. giraulti will not. Genes that were differentially expressed (DE) after conditioning in N. vitripennis, but not in N. giraulti, were identified as candidate genes that may regulate LTM formation. RESULTS: RNA was collected from heads of both species before and immediately, 4 or 24 hours after conditioning, with 3 replicates per time point. It was sequenced strand-specifically, which allows distinguishing sense from antisense transcripts and improves the quality of expression analyses. We determined conditioning-induced DE compared to naïve controls for both species. These expression patterns were then analysed with GO enrichment analyses for each species and time point, which demonstrated an enrichment of signalling-related genes immediately after conditioning in N. vitripennis only. Analyses of known LTM genes and genes with an opposing expression pattern between the two species revealed additional candidate genes for the difference in LTM formation. These include genes from various signalling cascades, including several members of the Ras and PI3 kinase signalling pathways, and glutamate receptors. Interestingly, several other known LTM genes were exclusively differentially expressed in N. giraulti, which may indicate an LTM-inhibitory mechanism. Among the DE transcripts were also antisense transcripts. Furthermore, antisense transcripts aligning to a number of known memory genes were detected, which may have a role in regulating these genes. CONCLUSION: This study is the first to describe and compare expression patterns of both protein-coding and antisense transcripts, at different time points after conditioning, of two closely related animal species that differ in LTM formation. Several candidate genes that may regulate differences in LTM have been identified. This transcriptome analysis is a valuable resource for future in-depth studies to elucidate the role of candidate genes and antisense transcription in natural variation in LTM formation.

Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics.

Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.