Wellcome Trust Genome Campus
Wellcome Trust Genome Campus
Ghali F.,University of Liverpool |
Krishna R.,University of Liverpool |
Lukasse P.,Wageningen University |
Lukasse P.,Netherlands Proteomics Center |
And 6 more authors.
Molecular and Cellular Proteomics | Year: 2013
The Proteomics Standards Initiative has recently released the mzIdentML data standard for representing peptide and protein identification results, for example, created by a search engine. When a new standard format is produced, it is important that software tools are available that make it straightforward for laboratory scientists to use it routinely and for bioinformaticians to embed support in their own tools. Here we report the release of several open-source Java-based software packages based on mzIdentML: ProteoIDViewer, mzidLibrary, and mzidValidator. The ProteoIDViewer is a desktop application allowing users to visualize mzIdentML-formatted results originating from any appropriate identification software; it supports visualization of all the features of the mzIdentML format. The mzidLibrary is a software library containing routines for importing data from external search engines, post-processing identification data (such as false discovery rate calculations), combining results from multiple search engines, performing protein inference, setting identification thresholds, and exporting results from mzIdentML to plain text files. The mzidValidator is able to process files and report warnings or errors if files are not correctly formatted or contain some semantic error. We anticipate that these developments will simplify adoption of the new standard in proteomics laboratories and the integration of mzIdentML into other software tools. All three tools are freely available in the public domain. © 2013 by The American Society for Biochemistry and Molecular Biology, Inc.
PubMed | University of Rome La Sapienza, University of Dschang, University of Botswana, District Hospital of Dschang and Wellcome Trust Genome Campus
Type: | Journal: Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases | Year: 2015
The prescription of patients tailored anti-infectious treatments is the ultimate goal of pharmacogenetics/genomics applied to antimicrobial treatments, providing a basis for personalized medicine. Despite the efforts to screen Africans for alleles underlying defective metabolism for a panel of different drugs, still more research is necessary to clarify the interplay between host genetic variation and treatments response. HIV is a major infectious disease in sub-Saharan African countries, and the main prescribed anti-HIV combination therapy includes efavirenz (EFV) or nevirapine (NVP). The two drugs are both mainly metabolised by cytochrome P450 2B6 liver enzyme (CYP2B6). Defective variants of CYP2B6 gene, leading to higher drug exposure with subsequent possible side effects and low compliance, are well known. However, little is known about CYP2B6 alleles in Cameroon where only one study was done on this subject. The main objective of the present work is to assess, in a subset of HIV-exposed subjects from Dschang in West Cameroon, the prevalence of two SNPs in the CYP2B6 gene: 516G>T (rs3745274) and 983T>C (rs28399499), both associated to a defective EFV and NVP metabolism. We analyzed 168 DNA samples collected during two cross-sectional surveys performed in Dschang, West Cameroon. In the population studied the observed allele frequencies of 516G>T and 983T>C were 44.35% (95%CI, 36.84-51.86%) and 12.80% (95%CI, 7.75-17.85%), respectively. Moreover, concerning the CYP2B6 expected phenotypes, 28.57% of the population showed a poor metaboliser phenotype, while 27.38% and 44.05% showed an extensive (wild-type) and an intermediate metaboliser phenotype, respectively. Here we found that an important fraction of the subjects is carrying EFV/NVP poor metaboliser alleles. Our findings could help to improve the knowledge about the previewed efficacy of anti-HIV drug therapy in Cameroon. Finally, we designed a new method of detection for the 983T>C genetic variation that can be applied in resource-limited laboratories.
Licciardello C.,Italian Agricultural Research Council |
D'Agostino N.,Italian Agricultural Research Council |
Traini A.,Wellcome Trust Genome Campus |
Recupero G.R.,Italian Agricultural Research Council |
And 2 more authors.
BMC Plant Biology | Year: 2014
Background: Glutathione S-transferases (GSTs) represent a ubiquitous gene family encoding detoxification enzymes able to recognize reactive electrophilic xenobiotic molecules as well as compounds of endogenous origin. Anthocyanin pigments require GSTs for their transport into the vacuole since their cytoplasmic retention is toxic to the cell. Anthocyanin accumulation in Citrus sinensis (L.) Osbeck fruit flesh determines different phenotypes affecting the typical pigmentation of Sicilian blood oranges. In this paper we describe: i) the characterization of the GST gene family in C. sinensis through a systematic EST analysis; ii) the validation of the EST assembly by exploiting the genome sequences of C. sinensis and C. clementina and their genome annotations; iii) GST gene expression profiling in six tissues/organs and in two different sweet orange cultivars, Cadenera (common) and Moro (pigmented).Results: We identified 61 GST transcripts, described the full- or partial-length nature of the sequences and assigned to each sequence the GST class membership exploiting a comparative approach and the classification scheme proposed for plant species. A total of 23 full-length sequences were defined. Fifty-four of the 61 transcripts were successfully aligned to the C. sinensis and C. clementina genomes. Tissue specific expression profiling demonstrated that the expression of some GST transcripts was 'tissue-affected' and cultivar specific. A comparative analysis of C. sinensis GSTs with those from other plant species was also considered. Data from the current analysis are accessible at http://biosrv.cab.unina.it/citrusGST/, with the aim to provide a reference resource for C. sinensis GSTs.Conclusions: This study aimed at the characterization of the GST gene family in C. sinensis. Based on expression patterns from two different cultivars and on sequence-comparative analyses, we also highlighted that two sequences, a Phi class GST and a Mapeg class GST, could be involved in the conjugation of anthocyanin pigments and in their transport into the vacuole, specifically in fruit flesh of the pigmented cultivar. © 2014 Licciardello et al.; licensee BioMed Central Ltd.
Zhang Y.,Leiden University |
Lameijer E.,Leiden University |
t hoen P.A.C.,Leiden University |
Ning Z.,Wellcome Trust Genome Campus |
And 3 more authors.
Bioinformatics | Year: 2012
Motivation: RNA-seq is a powerful technology for the study of transcriptome profiles that uses deep-sequencing technologies. Moreover, it may be used for cellular phenotyping and help establishing the etiology of diseases characterized by abnormal splicing patterns. In RNA-Seq, the exact nature of splicing events is buried in the reads that span exon-exon boundaries. The accurate and efficient mapping of these reads to the reference genome is a major challenge. Results: We developed PASSion, a pattern growth algorithm-based pipeline for splice site detection in paired-end RNA-Seq reads. Comparing the performance of PASSion to three existing RNA-Seq analysis pipelines, TopHat, MapSplice and HMMSplicer, revealed that PASSion is competitive with these packages. Moreover, the performance of PASSion is not affected by read length and coverage. It performs better than the other three approaches when detecting junctions in highly abundant transcripts. PASSion has the ability to detect junctions that do not have known splicing motifs, which cannot be found by the other tools. Of the two public RNA-Seq datasets, PASSion predicted ∼ 137 000 and 173 000 splicing events, of which on average 82 are known junctions annotated in the Ensembl transcript database and 18% are novel. In addition, our package can discover differential and shared splicing patterns among multiple samples. © The Author(s) 2012. Published by Oxford University Press.
Amelio I.,University of Leicester |
Gostev M.,Wellcome Trust Genome Campus |
Knight R.A.,University of Leicester |
Willis A.E.,University of Leicester |
And 3 more authors.
Cell Death and Disease | Year: 2014
The use of existing drugs for new therapeutic applications, commonly referred to as drug repositioning, is a way for fast and cost-efficient drug discovery. Drug repositioning in oncology is commonly initiated by in vitro experimental evidence that a drug exhibits anticancer cytotoxicity. Any independent verification that the observed effects in vitro may be valid in a clinical setting, and that the drug could potentially affect patient survival in vivo is of paramount importance. Despite considerable recent efforts in computational drug repositioning, none of the studies have considered patient survival information in modelling the potential of existing/new drugs in the management of cancer. Therefore, we have developed DRUGSURV; this is the first computational tool to estimate the potential effects of a drug using patient survival information derived from clinical cancer expression data sets. DRUGSURV provides statistical evidence that a drug can affect survival outcome in particular clinical conditions to justify further investigation of the drug anticancer potential and to guide clinical trial design. DRUGSURV covers both approved drugs (∼1700) as well as experimental drugs (∼5000) and is freely available at http://www.bioprofiling.de/drugsurv. © 2014 Macmillan Publishers Limited.
Tan G.C.,Imperial College London |
Tan G.C.,National University of Malaysia |
Chan E.,Imperial College London |
Molnar A.,University of Cambridge |
And 17 more authors.
Nucleic Acids Research | Year: 2014
We have sequenced miRNA libraries from human embryonic, neural and foetal mesenchymal stem cells. We report that the majority of miRNA genes encode mature isomers that vary in size by one or more bases at the 3′ and/or 5′ end of the miRNA. Northern blotting for individual miRNAs showed that the proportions of isomiRs expressed by a single miRNA gene often differ between cell and tissue types. IsomiRs were readily co-immunoprecipitated with Argonaute proteins in vivo and were active in luciferase assays, indicating that they are functional. Bioinformatics analysis predicts substantial differences in targeting between miRNAs with minor 5′ differences and in support of this we report that a 5′ isomiR-9-1 gained the ability to inhibit the expression of DNMT3B and NCAM2 but lost the ability to inhibit CDH1 in vitro. This result was confirmed by the use of isomiR-specific sponges. Our analysis of the miRGator database indicates that a small percentage of human miRNA genes express isomiRs as the dominant transcript in certain cell types and analysis ofmiRBase shows that 5′ isomiRs have replaced canonical miRNAs many times during evolution. This strongly indicates that isomiRs are of functional importance and have contributed to the evolution of miRNA genes. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Kersey P.J.,Wellcome Trust Genome Campus |
Staines D.M.,Wellcome Trust Genome Campus |
Lawson D.,Wellcome Trust Genome Campus |
Kulesha E.,Wellcome Trust Genome Campus |
And 17 more authors.
Nucleic Acids Research | Year: 2012
Ensembl Genomes (http://www.ensemblgenomes .org) is an integrative resource for genome-scale data from non-vertebrate species. The project exploits and extends technology (for genome annotation, analysis and dissemination) developed in the context of the (vertebrate-focused) Ensembl project and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. Since its launch in 2009, Ensembl Genomes has undergone rapid expansion, with the goal of providing coverage of all major experimental organisms, and additionally including taxonomic reference points to provide the evolutionary context in which genes can be understood. Against the backdrop of a continuing increase in genome sequencing activities in all parts of the tree of life, we seek to work, wherever possible, with the communities actively generating and using data, and are participants in a growing range of collaborations involved in the annotation and analysis of genomes. © The Author(s) 2011.
Marsden G.L.,University of Nottingham |
Marsden G.L.,University of London |
Davis I.J.,University of Nottingham |
Wright V.J.,University of Nottingham |
And 3 more authors.
BMC Genomics | Year: 2010
Background: Clostridium difficile is a Gram-positive, anaerobic, spore-forming bacterium that is responsible for C. difficile associated disease in humans and is currently the most common cause of nosocomial diarrhoea in the western world. This current status has been linked to the emergence of a highly virulent PCR-ribotype 027 strain. The aim of this work was to identify regions of sequence divergence that may be used as genetic markers of hypervirulent PCR-ribotype 027 strains and markers of the sequenced strain, CD630 by array comparative hybridisation.Results: In this study, we examined 94 clinical strains of the most common PCR-ribotypes isolated in mainland Europe and the UK by array comparative genomic hybridisation. Our array was comprehensive with 40,097 oligonucleotides covering the C. difficile 630 genome and revealed a core genome for all the strains of 32%. The array also covered genes unique to two PCR-ribotype 027 strains, relative to C. difficile 630 which were represented by 681 probes. All of these genes were also found in the commonly occuring PCR-ribotypes 001 and 106, and the emerging hypervirulent PCR-ribotype 078 strains, indicating that these are markers for all highly virulent strains.Conclusions: We have fulfilled the aims of this study by identifying markers for CD630 and markers associated with hypervirulence, albeit genes that are not just indicative of PCR-ribotype 027 strains. We have also extended this study and have defined a more stringent core gene set compared to those previously published due to the comprehensive array coverage. Further to this we have defined a list of genes absent from non-toxinogenic strains and defined the nature of the specific toxin deletion in the strain CD37. © 2010 Marsden et al; licensee BioMed Central Ltd.
O'Kane S.L.,University College Dublin |
O'Brien J.K.,Wellcome Trust Genome Campus |
Cahill D.J.,University College Dublin
Methods in Molecular Biology | Year: 2011
Profiling the autoantibody (AAb) repertoire in serum has been routinely used for many years for the diagnosis of autoimmune diseases, including rheumatoid arthritis, scleroderma, and lupus. In recent years, AAb profiling of cancers has become a prominent field in oncology research. Protein arrays enable high-throughput screening of clinical samples, characterising the serum profile using low volumes of samples. This chapter describes the use of a protein array comprising 37,200 redundant proteins (containing over 10,000 non-redundant human recombinant proteins) for identification of the proteins bound by the antibodies in human sera using a test set of serum samples. The proteins identified have the potential to be candidate biomarkers. These recombinant proteins are expressed, purified, and robotically spotted on microarrays or chips to facilitate the screening of additional serum samples with the aim of identifying a candidate biomarker or panel of potential biomarkers for applications in disease diagnosis, stage, progression, or response to therapy. © Springer Science+Business Media, LLC 2011.
PubMed | Wellcome Trust Genome Campus, University of Rome Tor Vergata and University of Leicester
Type: | Journal: Cell death & disease | Year: 2014
The use of existing drugs for new therapeutic applications, commonly referred to as drug repositioning, is a way for fast and cost-efficient drug discovery. Drug repositioning in oncology is commonly initiated by in vitro experimental evidence that a drug exhibits anticancer cytotoxicity. Any independent verification that the observed effects in vitro may be valid in a clinical setting, and that the drug could potentially affect patient survival in vivo is of paramount importance. Despite considerable recent efforts in computational drug repositioning, none of the studies have considered patient survival information in modelling the potential of existing/new drugs in the management of cancer. Therefore, we have developed DRUGSURV; this is the first computational tool to estimate the potential effects of a drug using patient survival information derived from clinical cancer expression data sets. DRUGSURV provides statistical evidence that a drug can affect survival outcome in particular clinical conditions to justify further investigation of the drug anticancer potential and to guide clinical trial design. DRUGSURV covers both approved drugs (1700) as well as experimental drugs (5000) and is freely available at http://www.bioprofiling.de/drugsurv.