Single-cell RNA sequencing identifies distinct mouse medial ganglionic eminence cell types.

Many subtypes of cortical interneurons (CINs) are found in adult mouse cortices, but the mechanism generating their diversity remains elusive. We performed single-cell RNA sequencing on the mouse embryonic medial ganglionic eminence (MGE), the major birthplace for CINs, and on MGE-like cells differentiated from embryonic stem cells. Two distinct cell types were identified as proliferating neural progenitors and immature neurons, both of which comprised sub-populations. Although lineage development of MGE progenitors was reconstructed and immature neurons were characterized as GABAergic, cells that might correspond to precursors of different CINs were not identified. A few non-neuronal cell types were detected, including microglia. In vitro MGE-like cells resembled bona fide MGE cells but expressed lower levels of Foxg1 and Epha4. Together, our data provide detailed understanding of the embryonic MGE developmental program and suggest how CINs are specified

Deliverable 10.3 - Plan for the dissemination and exploitation of the results from EuroMix

This plan for the dissemination and exploitation of the results (PEDR) provides the basis for EuroMix dissemination and exploitation activities by (i) outlining the EuroMix dissemination, communication, and exploitation strategy and by (ii) defining the timeframe, roles and responsibilities of these activities. The PEDR includes information regarding; dissemination channels, timelines, exploitation roadmaps and beneficiaries responsibilities. This will allow for the systematic implementation of the EuroMix exploitation and dissemination strategy throughout the project and will maximise the impact by implementing a coherent plan for the dissemination and exploitation of the project's results during and after the project. The first version of the PEDR was finalised in October 2016, after this it will be reviewed and updated annually as the project progresses. The final version will provide a long-term strategy for post-project dissemination and exploitation that will allow the European Commission (EC) to assess the impact of the project

Data access and integration in the ISPIDER proteomics grid

Grid computing has great potential for supporting the integration of complex, fast changing biological data repositories to enable distributed data analysis. One scenario where Grid computing has such potential is provided by proteomics resources which are rapidly being developed with the emergence of affordable, reliable methods to study the proteome. The protein identifications arising from these methods derive from multiple repositories which need to be integrated to enable uniform access to them. A number of technologies exist which enable these resources to be accessed in a Grid environment, but the independent development of these resources means that significant data integration challenges, such as heterogeneity and schema evolution, have to be met. This paper presents an architecture which supports the combined use of Grid data access (OGSA-DAI), Grid distributed querying (OGSA-DQP) and data integration (AutoMed) software tools to support distributed data analysis. We discuss the application of this architecture for the integration of several autonomous proteomics data resources

genoPlotR: comparative gene and genome visualization in R

Summary: The amount of gene and genome data obtained by next-generation sequencing technologies generates a need for comparative visualization tools. Complementing existing software for comparison and exploration of genomics data, genoPlotR automatically creates publication-grade linear maps of gene and genomes, in a highly automatic, flexible and reproducible way

drawProteins: a Bioconductor/R package for reproducible and programmatic generation of protein schematics

Protein schematics are valuable for research, teaching and knowledge communication. However, the tools used to automate the process are challenging. The purpose of the drawProteins package is to enable the generation of schematics of proteins in an automated fashion that can integrate with the Bioconductor/R suite of tools for bioinformatics and statistical analysis. Using UniProt accession numbers, the package uses the UniProt API to get the features of the protein from the UniProt database. The features are assembled into a data frame and visualized using adaptations of the ggplot2 package. Visualizations can be customised in many ways including adding additional protein features information from other data frames, altering colors and protein names and adding extra layers using other ggplot2 functions. This can be completed within a script that makes the workflow reproducible and sharable

CentrosomeDB: a human centrosomal proteins database

Active research on the biology of the centrosome during the past decades has allowed the identification and characterization of many centrosomal proteins. Unfortunately, the accumulated data is still dispersed among heterogeneous sources of information. Here we present centrosome:db, which intends to compile and integrate relevant information related to the human centrosome. We have compiled a set of 383 likely human centrosomal genes and recorded the associated supporting evidences. Centrosome:db offers several perspectives to study the human centrosome including evolution, function and structure. The database contains information on the orthology relationships with other species, including fungi, nematodes, arthropods, urochordates and vertebrates. Predictions of the domain organization of centrosome:db proteins are graphically represented at different sections of the database, including sets of alternative protein isoforms, interacting proteins, groups of orthologs and the homologs identified with blast. Centrosome:db also contains information related to function, gene–disease associations, SNPs and the 3D structure of proteins. Apart from important differences in the coverage of the set of centrosomal genes, our database differentiates from other similar initiatives in the way information is treated and analyzed. Centrosome:db is publicly available at http://centrosome.dacya.ucm.es

Advancing a global pharmacy support workforce through a global strategic platform

The pharmacy support workforce (PSW) is the mid-level cadre of the global pharmacy profession, referring to pharmacy technicians, assistants and other cadres that assist in the delivery of pharmaceutical services in a variety of practice contexts. The PSW undertake technical tasks delegated under the supervision of a pharmacist or performed collaboratively. The PSW are not intended to replace pharmacists, but rather work side-by-side with the pharmacist to achieve a shared goal. However, extensive variation in the PSW exists globally, ranging from an educated, regulated, and highly effective workforce in some countries to unrecognized or non-existent in others. Vast differences in education requirements, specific roles, regulatory oversight, and need for pharmacist supervision, inhibit the development and advancement of a global PSW. As clinical care providers, pharmacists worldwide need for a competent support workforce. Without the confidence to delegate technical responsibilities to a well-trained and capable PSW, pharmacists will be unable to fully deliver advanced clinical roles. A clear vision for the role of the PSW in the expanding scope of pharmacy practice is needed. One organization working to unite global efforts in this area is the International Pharmaceutical Federation (FIP). The FIP Workforce Development Hub Pharmacy Technicians & Support Workforce Strategic Platform was established to address the pharmacy workforce shortage in low and middle-income countries. Further developments were made in 2019, with the creation of a representative global PSW advisory panel, to provide guidance towards the development of the global PSW. Provision of frameworks and strategic input to support quality in education, development of legislative frameworks, guidelines for registration and licensure, and advice on appropriate role advancement are critical to move the PSW forward. In order to produce substantial advancement of roles and recognition of the PSW and advancement of pharmacists as patient care providers, global collaborative work is needed

μ-CS: An extension of the TM4 platform to manage Affymetrix binary data

<p>Abstract</p> <p>Background</p> <p>A main goal in understanding cell mechanisms is to explain the relationship among genes and related molecular processes through the combined use of technological platforms and bioinformatics analysis. High throughput platforms, such as microarrays, enable the investigation of the whole genome in a single experiment. There exist different kind of microarray platforms, that produce different types of binary data (images and raw data). Moreover, also considering a single vendor, different chips are available. The analysis of microarray data requires an initial preprocessing phase (i.e. normalization and summarization) of raw data that makes them suitable for use on existing platforms, such as the TIGR M4 Suite. Nevertheless, the annotations of data with additional information such as gene function, is needed to perform more powerful analysis. Raw data preprocessing and annotation is often performed in a manual and error prone way. Moreover, many available preprocessing tools do not support annotation. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of microarray data are needed.</p> <p>Results</p> <p>The paper presents <it>μ</it>-CS (Microarray Cel file Summarizer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix binary data. <it>μ</it>-CS is based on a client-server architecture. The <it>μ</it>-CS client is provided both as a plug-in of the TIGR M4 platform and as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data, avoiding the manual invocation of external tools (e.g. the Affymetrix Power Tools), the manual loading of preprocessing libraries, and the management of intermediate files. The <it>μ</it>-CS server automatically updates the references to the summarization and annotation libraries that are provided to the <it>μ</it>-CS client before the preprocessing. The <it>μ</it>-CS server is based on the web services technology and can be easily extended to support more microarray vendors (e.g. Illumina).</p> <p>Conclusions</p> <p>Thus <it>μ</it>-CS users can directly manage binary data without worrying about locating and invoking the proper preprocessing tools and chip-specific libraries. Moreover, users of the <it>μ</it>-CS plugin for TM4 can manage Affymetrix binary files without using external tools, such as APT (Affymetrix Power Tools) and related libraries. Consequently, <it>μ</it>-CS offers four main advantages: (i) it avoids to waste time for searching the correct libraries, (ii) it reduces possible errors in the preprocessing and further analysis phases, e.g. due to the incorrect choice of parameters or the use of old libraries, (iii) it implements the annotation of preprocessed data, and finally, (iv) it may enhance the quality of further analysis since it provides the most updated annotation libraries. The <it>μ</it>-CS client is freely available as a plugin of the TM4 platform as well as a standalone application at the project web site (<url>http://bioingegneria.unicz.it/M-CS</url>).</p

Allele-specific miRNA-binding analysis identifies candidate target genes for breast cancer risk

Most breast cancer (BC) risk-associated single-nucleotide polymorphisms (raSNPs) identified in genome-wide association studies (GWAS) are believed to cis-regulate the expression of genes. We hypothesise that cis-regulatory variants contributing to disease risk may be affecting microRNA (miRNA) genes and/or miRNA binding. To test this, we adapted two miRNA-binding prediction algorithms-TargetScan and miRanda-to perform allele-specific queries, and integrated differential allelic expression (DAE) and expression quantitative trait loci (eQTL) data, to query 150 genome-wide significant ( P≤5×10-8 ) raSNPs, plus proxies. We found that no raSNP mapped to a miRNA gene, suggesting that altered miRNA targeting is an unlikely mechanism involved in BC risk. Also, 11.5% (6 out of 52) raSNPs located in 3'-untranslated regions of putative miRNA target genes were predicted to alter miRNA::mRNA (messenger RNA) pair binding stability in five candidate target genes. Of these, we propose RNF115, at locus 1q21.1, as a strong novel target gene associated with BC risk, and reinforce the role of miRNA-mediated cis-regulation at locus 19p13.11. We believe that integrating allele-specific querying in miRNA-binding prediction, and data supporting cis-regulation of expression, improves the identification of candidate target genes in BC risk, as well as in other common cancers and complex diseases.Funding Agency Portuguese Foundation for Science and Technology CRESC ALGARVE 2020 European Union (EU) 303745 Maratona da Saude Award DL 57/2016/CP1361/CT0042 SFRH/BPD/99502/2014 CBMR-UID/BIM/04773/2013 POCI-01-0145-FEDER-022184info:eu-repo/semantics/publishedVersio