The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

Studio della risposta compatibile di nicotina benthamiana al turnip vein-clearing virus (TVCV).

2006/2007In agricoltura, la monocoltura su vaste aree geografiche puo' portare ad una rapida diffusione di malattie. D'altro canto, l'uso di composti chimici per controllarne la diffusione puo' causare seri problemi di inquinamento e aumentare i costi di produzione. Uno studio dettagliato delle interazioni pianta-patogeno puo' contribuire a fornire soluzioni sostenibili per il controllo delle malattie che colpiscono le specie coltivate. Per queste ragioni lo scopo principale di questa tesi e' stato lo studio delle prime fasi della risposta di N. benthamiana, una pianata appartenente alla famiglia delle Solanaceae, all'infezione da parte del Turnip Vein-Clearing Virus (TVCV). Per farlo e' stato messo a punto un metodo di infezione indiretto che sfrutta la capacita' di Agrobacterium di inserire un frammento di DNA esogeno nel genoma della pianta. In questo modo la percentuale di cellule infettate ha raggiunto il 90% sul totale delle cellule del tessuto. L'analisi del profilo di espressione genica e' stata effettuata mediante l'utilizzo di una nuova piattaforma microarray contenente circa 6000 sequenze specifiche di N. benthamiana. Le ibridazioni sono state eseguite durante il periodo in cui il genoma virale aumenta la propria concentrazione all'interno della cellula fino a raggiungere il valore massimo. Complessivamente sono state fatte 30 ibridazioni con il microarray. La determinazione della concentrazione del genioma virale e' stata effettuata con l'uso della tecnica della PCR quantitativa per la quale e' stato sviluppato un nuovo metodo di analisi dei dati. I risultati delle ibridazioni dimostrano che la risposta della pinata all'infezione virale e' caratterizzata dalla presenza di due fasi distinte. Nella prima e' presente un picco di risposta durante le prime fasi dell'esperimento, quando il genoma virale non ha ancora raggiunto la fase di crescita esponenziale. La seconda, invece, coincide con il massimo della concentrazione virale all'interno delle cellule. Analisi approfondite dei geni attivati nelle due fasi lasciano ipotizzare la presenza di due risposte differenti, la prima rivolta verso Agrobacterium mentre la seconda rivolta verso l'infezione virale. Questo lavoro e' stato svolto in parte presso il laboratorio di Genetica dell'Universita' degli Studi di Trieste sotto la supervisione del Prof. Alberto Pallavicini ed in parte nel laboratorio del Prof. Andy Maule, Disease and Stress Biology, John Innes Centre, UK.XX Ciclo197

Principles of ChIP-seq Data Analysis Illustrated with Examples

Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) is a powerful method to determine how transcription factors and other chromatin-associated proteins interact with DNA in order to regulate gene transcription. A single ChIP-seq experiment produces large amounts of highly reproducible data. The challenge is to extract knowledge from the data by thoughtful application of appropriate bioinformatics tools. Here we present a concise introduction into ChIP-seq data analysis in the form of a tutorial based on tools developed by our group. We expose biological questions, explain methods and provide guidelines for the interpretation of the results. While this article focuses on ChIP-seq, most of the algorithms and tools we present are applicable to other chromatin profiling assays based on next generation sequencing (NGS) technology as well

Computational identification and experimental characterization of preferred downstream positions in human core promoters

Author summary Transcription of genes by the RNA polymerase II enzyme initiates at a genomic region termed the core promoter. The core promoter is a regulatory region that may contain diverse short DNA sequence motifs/elements that confer specific properties to it. Interestingly, core promoter motifs can be located both upstream and downstream of the transcription start site. Variable compositions of core promoter elements were identified. The initiator (Inr) motif and the downstream core promoter element (DPE) is a combination of elements that has been identified and extensively characterized in fruit flies. Although a few Inr+DPE -containing human promoters were identified, the presence of transcriptionally important downstream core promoter positions within human promoters has been a matter of controversy in the literature. Here, using a newly-designed motif discovery strategy, we discovered preferred downstream positions in human promoters that resemble fruit fly DPE. Clustering of the corresponding sequence motifs in eight additional species indicated that such promoters could be common to multicellular non-plant organisms. Importantly, functional characterization of the newly discovered preferred downstream positions supports the existence of Inr+DPE-containing promoters in human genes. Metazoan core promoters, which direct the initiation of transcription by RNA polymerase II (Pol II), may contain short sequence motifs termed core promoter elements/motifs (e.g. the TATA box, initiator (Inr) and downstream core promoter element (DPE)), which recruit Pol II via the general transcription machinery. The DPE was discovered and extensively characterized in Drosophila, where it is strictly dependent on both the presence of an Inr and the precise spacing from it. Since the Drosophila DPE is recognized by the human transcription machinery, it is most likely that some human promoters contain a downstream element that is similar, though not necessarily identical, to the Drosophila DPE. However, only a couple of human promoters were shown to contain a functional DPE, and attempts to computationally detect human DPE-containing promoters have mostly been unsuccessful. Using a newly-designed motif discovery strategy based on Expectation-Maximization probabilistic partitioning algorithms, we discovered preferred downstream positions (PDP) in human promoters that resemble the Drosophila DPE. Available chromatin accessibility footprints revealed that Drosophila and human Inr+DPE promoter classes are not only highly structured, but also similar to each other, particularly in the proximal downstream region. Clustering of the corresponding sequence motifs using a neighbor-joining algorithm strongly suggests that canonical Inr+DPE promoters could be common to metazoan species. Using reporter assays we demonstrate the contribution of the identified downstream positions to the function of multiple human promoters. Furthermore, we show that alteration of the spacing between the Inr and PDP by two nucleotides results in reduced promoter activity, suggesting a spacing dependency of the newly discovered human PDP on the Inr. Taken together, our strategy identified novel functional downstream positions within human core promoters, supporting the existence of DPE-like motifs in human promoters

A Reservoir of Pluripotent Phloem Cells Safeguards the Linear Developmental Trajectory of Protophloem Sieve Elements

Plant cells can change their identity based on positional information, a mechanism that confers developmental plasticity to plants. This ability, common to distinct multicellular organisms, is particularly relevant for plant phloem cells. Protophloem sieve elements (PSEs), one type of phloem conductive cells, act as the main organizers of the phloem pole, which comprises four distinct cell files organized in a conserved pattern. Here, we report how Arabidopsis roots generate a reservoir of meristematic phloem cells competent to swap their cell identities. Although PSE misspecification induces cell identity hybridism, the activity of RECEPTOR LIKE PROTEIN KINASE 2 (RPK2) by perceiving CLE45 peptide contributes to restrict PSE identity to the PSE position. By maintaining a spatiotemporal window when PSE and PSE-adjacent cells’ identities are interchangeable, CLE45 signaling endows phloem cells with the competence to re-pattern a functional phloem pole when protophloem fails to form.ISSN:0960-9822ISSN:1879-044

Inferring Gene Expression From Ribosomal Promoter Sequences, a Crowdsourcing Approach

The Gene Promoter Expression Prediction challenge consisted of predicting gene expression from promoter sequences in a previously unknown experimentally generated data set. The challenge was presented to the community in the framework of the sixth Dialogue for Reverse Engineering Assessments and Methods (DREAM6), a community effort to evaluate the status of systems biology modeling methodologies. Nucleotide-specific promoter activity was obtained by measuring fluorescence from promoter sequences fused upstream of a gene for yellow fluorescence protein and inserted in the same genomic site of yeast Saccharomyces cerevisiae. Twenty-one teams submitted results predicting the expression levels of 53 different promoters from yeast ribosomal protein genes. Analysis of participant predictions shows that accurate values for low-expressed and mutated promoters were difficult to obtain, although in the latter case, only when the mutation induced a large change in promoter activity compared to the wild-type sequence. As in previous DREAM challenges, we found that aggregation of participant predictions provided robust results, but did not fare better than the three best algorithms. Finally, this study not only provides a benchmark for the assessment of methods predicting activity of a specific set of promoters from their sequence, but it also shows that the top performing algorithm, which used machine-learning approaches, can be improved by the addition of biological features such as transcription factor binding sites

Critical assessment of automated flow cytometry data analysis techniques

Traditional methods for flow cytometry (FCM) data processing rely on subjective manual gating. Recently, several groups have developed computational methods for identifying cell populations in multidimensional FCM data. The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of these methods on two tasks: (i) mammalian cell population identification, to determine whether automated algorithms can reproduce expert manual gating and (ii) sample classification, to determine whether analysis pipelines can identify characteristics that correlate with external variables (such as clinical outcome). This analysis presents the results of the first FlowCAP challenges. Several methods performed well as compared to manual gating or external variables using statistical performance measures, which suggests that automated methods have reached a sufficient level of maturity and accuracy for reliable use in FCM data analysis.