Bridging the gap between social tagging and semantic annotation: E.D. the Entity Describer

Semantic annotation enables the development of efficient computational methods for analyzing and interacting with information, thus maximizing its value. With the already substantial and constantly expanding data generation capacity of the life sciences as well as the concomitant increase in the knowledge distributed in scientific articles, new ways to produce semantic annotations of this information are crucial. While automated techniques certainly facilitate the process, manual annotation remains the gold standard in most domains. In this manuscript, we describe a prototype mass-collaborative semantic annotation system that, by distributing the annotation workload across the broad community of biomedical researchers, may help to produce the volume of meaningful annotations needed by modern biomedical science. We present E.D., the Entity Describer, a mashup of the Connotea social tagging system, an index of semantic web-accessible controlled vocabularies, and a new public RDF database for storing social semantic annotations

Virtual in situs: Sequencing mRNA from cryo-sliced Drosophila embryos to determine genome-wide spatial patterns of gene expression

Complex spatial and temporal patterns of gene expression underlie embryo differentiation, yet methods do not yet exist for the efficient genome-wide determination of spatial expression patterns during development. In situ imaging of transcripts and proteins is the gold-standard, but it is difficult and time consuming to apply to an entire genome, even when highly automated. Sequencing, in contrast, is fast and genome-wide, but is generally applied to homogenized tissues, thereby discarding spatial information. It is likely that these methods will ultimately converge, and we will be able to sequence RNAs in situ, simultaneously determining their identity and location. As a step along this path, we developed methods to cryosection individual blastoderm stage Drosophila melanogaster embryos along the anterior-posterior axis and sequence the mRNA isolated from each 25 micron slice. The spatial patterns of gene expression we infer closely match patterns previously determined by in situ hybridization and microscopy. We applied this method to generate a genome-wide timecourse of spatial gene expression from shortly after fertilization through gastrulation. We identify numerous genes with spatial patterns that have not yet been described in the several ongoing systematic in situ based projects. This simple experiment demonstrates the potential for combining careful anatomical dissection with high-throughput sequencing to obtain spatially resolved gene expression on a genome-wide scale.Comment: 6 pages, 3 figures, 7 supplemental figures (available on request from [email protected]

The 3D Genome Browser: A web-based browser for visualizing 3D genome organization and long-range chromatin interactions

Abstract Here, we introduce the 3D Genome Browser, http://3dgenome.org, which allows users to conveniently explore both their own and over 300 publicly available chromatin interaction data of different types. We design a new binary data format for Hi-C data that reduces the file size by at least a magnitude and allows users to visualize chromatin interactions over millions of base pairs within seconds. Our browser provides multiple methods linking distal cis-regulatory elements with their potential target genes. Users can seamlessly integrate thousands of other omics data to gain a comprehensive view of both regulatory landscape and 3D genome structure

Specification of high-level application programming interfaces (SemSorGrid4Env)

This document defines an Application Tier for the SemsorGrid4Env project. Within the Application Tier we distinguish between Web Applications - which provide a User Interface atop a more traditional Service Oriented Architecture - and Mashups which are driven by a REST API and a Resource Oriented Architecture. A pragmatic boundary is set to enable initial development of Web Applications and Mashups; as the project progresses an evaluation and comparison of the two paradigms may lead to a reassessment of where each can be applied within the project, with the experience gained providing a basis for general guidelines and best practice. Both Web Applications and Mashups are designed and delivered through an iterative user-centric process; requirements generated by the project case studies are a key element of this approach

Genome-Wide Association Study and Subsequent Exclusion of ATCAY as a Candidate Gene Involved in Equine Neuroaxonal Dystrophy Using Two Animal Models.

Equine neuroaxonal dystrophy/equine degenerative myeloencephalopathy (eNAD/EDM) is an inherited neurodegenerative disorder of unknown etiology. Clinical signs of neurological deficits develop within the first year of life in vitamin E (vitE) deficient horses. A genome-wide association study (GWAS) was carried out using 670,000 SNP markers in 27 case and 42 control Quarter Horses. Two markers, encompassing a 2.5 Mb region on ECA7, were associated with the phenotype (p = 2.05 × 10-7 and 4.72 × 10-6). Within this region, caytaxin (ATCAY) was identified as a candidate gene due to its known role in Cayman Ataxia and ataxic/dystonic phenotypes in mouse models. Whole-genome sequence data in four eNAD/EDM and five unaffected horses identified 199 associated variants within the ECA7 region. MassARRAY® genotyping was performed on these variants within the GWAS population. The three variants within ATCAY were not concordant with the disease phenotype. No difference in expression or alternative splicing was identified using qRT-PCR in brainstem across the ATCAY transcript. Atcayji-hes mice were then used to conduct functional analysis in a second animal model. Histologic lesions were not identified in the central nervous system of Atcayji-hes mice. Additionally, supplementation of homozygous Atcayji-hes mice with 600 IU/day of dl-α-tocopheryl acetate (vitE) during gestation, lactation, and adulthood did not improve the phenotype. ATCAY has therefore been excluded as a candidate gene for eNAD/EDM

Keemei: cloud-based validation of tabular bioinformatics file formats in Google Sheets.

BackgroundBioinformatics software often requires human-generated tabular text files as input and has specific requirements for how those data are formatted. Users frequently manage these data in spreadsheet programs, which is convenient for researchers who are compiling the requisite information because the spreadsheet programs can easily be used on different platforms including laptops and tablets, and because they provide a familiar interface. It is increasingly common for many different researchers to be involved in compiling these data, including study coordinators, clinicians, lab technicians and bioinformaticians. As a result, many research groups are shifting toward using cloud-based spreadsheet programs, such as Google Sheets, which support the concurrent editing of a single spreadsheet by different users working on different platforms. Most of the researchers who enter data are not familiar with the formatting requirements of the bioinformatics programs that will be used, so validating and correcting file formats is often a bottleneck prior to beginning bioinformatics analysis.Main textWe present Keemei, a Google Sheets Add-on, for validating tabular files used in bioinformatics analyses. Keemei is available free of charge from Google's Chrome Web Store. Keemei can be installed and run on any web browser supported by Google Sheets. Keemei currently supports the validation of two widely used tabular bioinformatics formats, the Quantitative Insights into Microbial Ecology (QIIME) sample metadata mapping file format and the Spatially Referenced Genetic Data (SRGD) format, but is designed to easily support the addition of others.ConclusionsKeemei will save researchers time and frustration by providing a convenient interface for tabular bioinformatics file format validation. By allowing everyone involved with data entry for a project to easily validate their data, it will reduce the validation and formatting bottlenecks that are commonly encountered when human-generated data files are first used with a bioinformatics system. Simplifying the validation of essential tabular data files, such as sample metadata, will reduce common errors and thereby improve the quality and reliability of research outcomes

Global Functional Atlas of \u3cem\u3eEscherichia coli\u3c/em\u3e Encompassing Previously Uncharacterized Proteins

One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans’ biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a “systems-wide” functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins