Array-CGH in patients with a clinical diagnosis of Kabuki syndrome: identification of two cases with terminal 2q37 deletion and no other recurrent rearrangement

Background: Kabuki syndrome (KS) is a multiple congenital anomaly syndrome characterized by specific facial features, mild to moderate mental retardation, postnatal growth delay, skeletal abnormalities, and unusual dermatoglyphic patterns with prominent fingertip pads. A 3.5 Mb duplication at 8p23.1-p22 was once reported as a specific alteration in KS but has not been confirmed in other patients. The molecular basis of KS remains unknown. Methods: We have studied 16 Spanish patients with a clinical diagnosis of KS or KS-like to search for genomic imbalances using genome-wide array technologies. All putative rearrangements were confirmed by FISH, microsatellite markers and/or MLPA assays, which also determined whether the imbalance was de novo or inherited. Results: No duplication at 8p23.1-p22 was observed in our patients. We detected complex rearrangements involving 2q in two patients with Kabuki-like features: 1) a de novo inverted duplication of 11 Mb with a 4.5 Mb terminal deletion, and 2) a de novo 7.2 Mb-terminal deletion in a patient with an additional de novo 0.5 Mb interstitial deletion in 16p. Additional copy number variations (CNV), either inherited or reported in normal controls, were identified and interpreted as polymorphic variants. No specific CNV was significantly increased in the KS group. Conclusion: Our results further confirmed that genomic duplications of 8p23 region are not a common cause of KS and failed to detect other recurrent rearrangement causing this disorder. The detection of two patients with 2q37 deletions suggests that there is a phenotypic overlap between the two conditions, and screening this region in the Kabuki-like patients should be considered.

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.

Enhanced Botrytis cinerea resistance of Arabidopsis plants grown in compost may be explained by increased expression of defense-related genes, as revealed by microarray analysis

Composts are the products obtained after the aerobic degradation of different types of organic matter waste and can be used as substrates or substrate/soil amendments for plant cultivation. There is a small but increasing number of reports that suggest that foliar diseases may be reduced when using compost, rather than standard substrates, as growing medium. The purpose of this study was to examine the gene expression alteration produced by the compost to gain knowledge of the mechanisms involved in compost-induced systemic resistance. A compost from olive marc and olive tree leaves was able to induce resistance against Botrytis cinerea in Arabidopsis, unlike the standard substrate, perlite. Microarray analyses revealed that 178 genes were differently expressed, with a fold change cut-off of 1, of which 155 were up-regulated and 23 were down-regulated in compost-grown, as against perlite-grown plants. A functional enrichment study of up-regulated genes revealed that 38 Gene Ontology terms were significantly enriched. Response to stress, biotic stimulus, other organism, bacterium, fungus, chemical and abiotic stimulus, SA and ABA stimulus, oxidative stress, water, temperature and cold were significantly enriched, as were immune and defense responses, systemic acquired resistance, secondary metabolic process and oxireductase activity. Interestingly, PR1 expression, which was equally enhanced by growing the plants in compost and by B. cinerea inoculation, was further boosted in compost-grown pathogen-inoculated plants. Compost triggered a plant response that shares similarities with both systemic acquired resistance and ABA-dependent/independent abiotic stress responses.

A copula-based method for synthetic microarray data generation

In this work, we propose a copula-based method to generate synthetic gene expression data that account for marginal and joint probability distributions features captured from real data. Our method allows us to implant significant genes in the synthetic dataset in a controlled manner, giving the possibility of testing new detection algorithms under more realistic environments.

Dual activation of pathways regulated by steroid receptors and peptide growth factors in primary prostate cancer revealed by Factor Analysis of microarray data

Background: We use an approach based on Factor Analysis to analyze datasets generated for transcriptional profiling. The method groups samples into biologically relevant categories, and enables the identification of genes and pathways most significantly associated to each phenotypic group, while allowing for the participation of a given gene in more than one cluster. Genes assigned to each cluster are used for the detection of pathways predominantly activated in that cluster by finding statistically significant associated GO terms. We tested the approach with a published dataset of microarray experiments in yeast. Upon validation with the yeast dataset, we applied the technique to a prostate cancer dataset. Results: Two major pathways are shown to be activated in organ-confined, non-metastatic prostate cancer: those regulated by the androgen receptor and by receptor tyrosine kinases. A number of gene markers (HER3, IQGAP2 and POR1) highlighted by the software and related to the later pathway have been validated experimentally a posteriori on independent samples. Conclusion: Using a new microarray analysis tool followed by a posteriori experimental validation of the results, we have confirmed several putative markers of malignancy associated with peptide growth factor signalling in prostate cancer and revealed others, most notably ERRB3 (HER3). Our study suggest that, in primary prostate cancer, HER3, together or not with HER4, rather than in receptor complexes involving HER2, could play an important role in the biology of these tumors. These results provide new evidence for the role of receptor tyrosine kinases in the establishment and progression of prostate cancer.

Array de DNA per identificar espècies de Fusarium: ampliació d'un array existent per incloure espècies del Sud d'Europa

Projecte de recerca elaborat a partir d’una estada al Department for Feed and Food Hygiene del National Veterinary Institute, Noruega, entre novembre i desembre del 2006. Els grans de cereal poden estar contaminats amb diferents espècies de Fusarium capaces de produir metabolits secundaris altament tòxics com trichotecenes, fumonisines o moniliformines. La correcta identificació d’aquestes espècies és de gran importància per l’assegurament del risc en l’àmbit de la salut humana i animal. La identificació de Fusarium en base a la seva morfologia requereix coneixements taxonòmics i temps; la majoria dels mètodes moleculars permeten la identificació d’una única espècie diana. Per contra, la tecnologia de microarray ofereix l’anàlisi paral•lel d’un alt nombre de DNA dianes. En aquest treball, s’ha desenvolupat un array per a la identificació de les principals espècies de Fusarium toxigèniques del Nord i Sud d’Europa. S’ha ampliat un array ja existent, per a la detecció de les espècies de Fusarium productores de trichothecene i moniliformina (predominants al Nord d’Europa), amb l’addició de 18 sondes de DNA que permeten identificar les espècies toxigèniques més abundants al Sud d’Europa, les qual produeixen majoritàriament fumonisines. Les sondes de captura han estat dissenyades en base al factor d’elongació translació- 1 alpha (TEF-1alpha). L’anàlisi de les mostres es realitza mitjançant una única PCR que permet amplificar part del TEF-1alpha seguida de la hibridació al xip de Fusarium. Els resultats es visualitzen mitjançant un mètode de detecció colorimètric. El xip de Fusarium desenvolupat pot esdevenir una eina útil i de gran interès per a l’anàlisi de cereals presents en la cadena alimentària.

Obtenció de jerarquies d'estats cel·lulars via web

Hi ha diversos mètodes d'anàlisi que duen a terme una agrupació global de la sèries de mostres de microarrays, com SelfOrganizing Maps, o que realitzen agrupaments locals tenint en compte només un subconjunt de gens coexpressats, com Biclustering, entre d'altres. En aquest projecte s'ha desenvolupat una aplicació web: el PCOPSamplecl, és una eina que pertany als mètodes d'agrupació (clustering) local, que no busca subconjunts de gens coexpresats (anàlisi de relacions linials), si no parelles de gens que davant canvis fenotípics, la seva relació d'expressió pateix fluctuacions. El resultats del PCOPSamplecl seràn les diferents distribucions finals de clusters i les parelles de gens involucrades en aquests canvis fenotípics. Aquestes parelles de gens podràn ser estudiades per trobar la causa i efecte del canvi fenotípic. A més, l'eina facilita l'estudi de les dependències entre les diferents distribucions de clusters que proporciona l'aplicació per poder estudiar la intersecció entre clusters o l'aparició de subclusters (2 clusters d'una mateixa agrupació de clusters poden ser subclusters d'altres clusters de diferents distribucions de clusters). L'eina és disponible al servidor: http://revolutionresearch.uab.es/

Bioinformática: interfaz web para estudiar el efecto de diferentes condiciones sobre la expresión de los genes

El trabajo realizado se divide en dos bloques bien diferenciados, ambos relacionados con el análisis de microarrays. El primer bloque consiste en agrupar las condiciones muestrales de todos los genes en grupos o clústers. Estas agrupaciones se obtienen al aplicar directamente sobre la microarray los siguientes algoritmos de agrupación: SOM,PAM,SOTA,HC y al aplicar sobre la microarray escalada con PC y MDS los siguientes algoritmos: SOM,PAM,SOTA,HC y K-MEANS. El segundo bloque consiste en realizar una búsqueda de genes basada en los intervalos de confianza de cada clúster de la agrupación activa. Las condiciones de búsqueda ajustadas por el usuario se validan para cada clúster respecto el valor basal 0 y respecto el resto de clústers, para estas validaciones se usan los intervalos de confianza. Estos dos bloques se integran en una aplicación web ya existente, el applet PCOPGene, alojada en el servidor: http://revolutionresearch.uab.es.

Análisis de la expresión de las moléculas relacionadas con el complejo principal de histocompatibilidad de clase I y de NKG2D como respuesta al daño oxidativo del DNA en el cáncer urotelial de vejiga. Relación con las características clínico patológicas y supervivencia

Es tracta d'un estudi retrospectiu de casos de 280 pacients diagnosticats de tumor vesical primari amb un seguiment mínim de 8 anys. S'ha construït un Tissue microarray i mitjançant mètodes semiquantitatius d’inmunohistoquímica es determinarà l'expressió de les molècules MICA (MHC class I chain-related gene A) i del seu receptor NKG2D (Natural-Killer group 2-member D) a nivell tissular, relacionant-lo amb variables anatomopatològiques segons els grups de risc, hàbit tabàquic i sexe. Finalment valorarem l'expressió de MICA/NKG2D com a factor independent de recidiva / progressió tumoral. En la literatura només existeixen 2 treballs que relacionin MICA amb el càncer vesical.

Interfaz web para mostrar los genes según las relaciones que mantienen sus expresiones

La investigació entre les relacions dels nivells d’expressió dels gens aporta molta informació sobre els processos biològics i patològics. Mitjançant la tècnica de les microarrays es possibilita la investigació de les relacions d’expressió de milers de gens a la vegada. La finalitat d’aquest projecte es fent ús de l’aplicatiu web PCOPGene-Net, permetre la identificació dels gens per les relacions d’expressió no lineals que tenen amb la resta de gens i permetre també la identificació de les relacions d’expressió no lineals entre els gens d’una microarray.

Comparación de datos de expresión génica del servidor local con datos de una base de datos remota

En la presente memoria se detalla con precisión las diversas fases del trabajo para construir una aplicación web en el servidor http://revolutionresearch.uab.es que permite enriquecer los clusters de la microarray del usuario con información biomédica de una base de datos remota. Los clusters de origen estadístico (o no) de la microarray del usuario se enriquecen a partir de cruzar sus genes marcadores con la base de datos de genes marcadores de microarrays (base de datos remota) con clusters basados en información biomédica. La base de datos de genes marcadores de microarrays ha sido obtenida a partir de la base de datos de GEO Profiles del NCBI.

“Unmixing” Tissue Gene Expression Signatures from Tumor Biopsies

Emergent molecular measurement methods, such as DNA microarray, qRTPCR, andmany others, offer tremendous promise for the personalized treatment of cancer. Thesetechnologies measure the amount of specific proteins, RNA, DNA or other moleculartargets from tumor specimens with the goal of “fingerprinting” individual cancers. Tumorspecimens are heterogeneous; an individual specimen typically contains unknownamounts of multiple tissues types. Thus, the measured molecular concentrations resultfrom an unknown mixture of tissue types, and must be normalized to account for thecomposition of the mixture.For example, a breast tumor biopsy may contain normal, dysplastic and cancerousepithelial cells, as well as stromal components (fatty and connective tissue) and bloodand lymphatic vessels. Our diagnostic interest focuses solely on the dysplastic andcancerous epithelial cells. The remaining tissue components serve to “contaminate”the signal of interest. The proportion of each of the tissue components changes asa function of patient characteristics (e.g., age), and varies spatially across the tumorregion. Because each of the tissue components produces a different molecular signature,and the amount of each tissue type is specimen dependent, we must estimate the tissuecomposition of the specimen, and adjust the molecular signal for this composition.Using the idea of a chemical mass balance, we consider the total measured concentrationsto be a weighted sum of the individual tissue signatures, where weightsare determined by the relative amounts of the different tissue types. We develop acompositional source apportionment model to estimate the relative amounts of tissuecomponents in a tumor specimen. We then use these estimates to infer the tissuespecificconcentrations of key molecular targets for sub-typing individual tumors. Weanticipate these specific measurements will greatly improve our ability to discriminatebetween different classes of tumors, and allow more precise matching of each patient tothe appropriate treatment

Bioinformática: base de datos de matrices de expresión génica para su análisis vía web

El IBB ha desarrollado un servidor de aplicaciones: http://revolutionresearch.uab.es para el análisis de microarrays. Estas microarrays las obtienen y las suben a la base de datos local los usuarios de la aplicación. En la presente memoria se detalla el proceso realizado para automatizar la subida de microarrays públicas a la base de datos local. Estas microarrays se obtendrán del NCBI. El proceso de descarga de microarrays se realizará cada dos meses y estará sincronizado con un proceso de descarga de genes marcadores de microarrays del NCBI. En la memoria también se describen las fases realizadas para crear la interfaz web para gestionar estas microarrays públicas y las modificaciones realizadas sobre el aplicativo web para permitir realizar análisis con estas microarrays.

Conserved chromosomal clustering of genes governed by chromatin regulators in Drosophila

BACKGROUND: The trithorax group (trxG) and Polycomb group (PcG) proteins are responsible for the maintenance of stable transcriptional patterns of many developmental regulators. They bind to specific regions of DNA and direct the post-translational modifications of histones, playing a role in the dynamics of chromatin structure. RESULTS: We have performed genome-wide expression studies of trx and ash2 mutants in Drosophila melanogaster. Using computational analysis of our microarray data, we have identified 25 clusters of genes potentially regulated by TRX. Most of these clusters consist of genes that encode structural proteins involved in cuticle formation. This organization appears to be a distinctive feature of the regulatory networks of TRX and other chromatin regulators, since we have observed the same arrangement in clusters after experiments performed with ASH2, as well as in experiments performed by others with NURF, dMyc, and ASH1. We have also found many of these clusters to be significantly conserved in D. simulans, D. yakuba, D. pseudoobscura and partially in Anopheles gambiae. CONCLUSION: The analysis of genes governed by chromatin regulators has led to the identification of clusters of functionally related genes conserved in other insect species, suggesting this chromosomal organization is biologically important. Moreover, our results indicate that TRX and other chromatin regulators may act globally on chromatin domains that contain transcriptionally co-regulated genes.

Characterization of human gene expression changes after olive oil ingestion: an exploratory approach

Olive oil consumption is protective against risk factors for cardiovascular and cancer diseases. A nutrigenomic approach was performed to assess whether changes in gene expression could occur in human peripheral blood mononuclear cells after oli ve oil ingestion at postprandial state. Six healthy male volunteers ingested, at fasting state, 50 ml of olive oil. Prior to intervention a 1-week washout period with a controlled diet and sunflower oil as the only source of fat was followed. During the 3 days before and on the intervention day, a very low-phenolic compound diet was followed. At baseline (0 h) and at post-ingestion (6 h), total RNA was isolated and gene expression (29,082 genes) was evaluated by microarray. From microarray data, nutrient-gene interactions were observed in genes related to metabolism, cellular processes, cancer, and atherosclerosis (e.g. USP48 by 2.16; OGT by 1.68-fold change) and associated processes such as inflammation (e.g. AKAP13 by 2.30; IL-10 by 1.66-fold change) and DNA damage (e.g. DCLRE1C by 1.47; POLK by 1.44- fold change). When results obtained by microarray were verified by qRT-PCR in nine genes, full concordance was achieved only in the case of up-regulated genes. Changes were observed at a real-life dose of olive oil, as it is daily consumed in some Mediterranean areas. Our results support the hypothesis that postprandial protective changes related to olive oil consumption could be mediated through gene expression changes.