SpBase: the sea urchin genome database and web site

SpBase is a system of databases focused on the genomic information from sea urchins and related echinoderms. It is exposed to the public through a web site served with open source software (http://spbase.org/). The enterprise was undertaken to provide an easily used collection of information to directly support experimental work on these useful research models in cell and developmental biology. The information served from the databases emerges from the draft genomic sequence of the purple sea urchin, Strongylocentrotus purpuratus and includes sequence data and genomic resource descriptions for other members of the echinoderm clade which in total span 540 million years of evolutionary time. This version of the system contains two assemblies of the purple sea urchin genome, associated expressed sequences, gene annotations and accessory resources. Search mechanisms for the sequences and the gene annotations are provided. Because the system is maintained along with the Sea Urchin Genome resource, a database of sequenced clones is also provided

Dilemmas of Development and The Reconstruction of Fashion

Sustainable development by its nature appears elusive. It seems the more we try to capture and pin it down the more it moves away from us leading us into murkier waters and all manner of contradictions. No more is this felt than in the fashion industry where we are presented with a number of oppositions. The fashion cycle renders styles obsolete before they have worn out generating waste and over-consumptive practices. But it can also bring into the fore practices that have resonance to sustainable development in terms of their location, orientation and consideration for the environment. As studies emerge considering the detrimental environmental impacts of the manufacture and consumption of new clothes, second-hand clothes have become a focus for research endeavours considering how they can be reincorporated into the fashion system and have resonance to an ever ‘fashion’ hungry consumer. This chapter discusses methods for the processing of second-hand clothes into fashionable items and, by drawing on the wealth of ‘waste’ materials through reselling, restyling and remanufacturing, argues that ways of re-appropriating them into a more environmentally focused fashion industry is possible and necessary. It sets out as it hypothesis that the global fashion system has value in its transformative powers but that damaging and exploitative forces are still preventing it from being a force for good. This is due to the nature of the items being produced, the way they are manufactured and how they are ultimately consumed and disposed of

Proteomic Analysis of Human Skin Treated with Larval Schistosome Peptidases Reveals Distinct Invasion Strategies among Species of Blood Flukes

Schistosome parasites are a major cause of disease in the developing world, but the mechanism by which these parasites first infect their host has been studied at the molecular level only for S. mansoni. In this paper, we have mined recent genome annotations of S. mansoni and S. japonicum, a zoonotic schistosome species, to identify differential expansion of peptidase gene families that may be involved in parasite invasion and subsequent migration through skin. Having identified a serine peptidase gene family in S. mansoni and a cysteine peptidase gene family in S. japonicum, we then used a comparative proteomic approach to identify potential substrates of representative members of both classes of enzymes from S. mansoni in human skin. The results of this study suggest that while these species evolved to use different classes of peptidases in host invasion, both are capable of cleaving components of the epidermis and dermal extracellular matrix, as well as proteins involved in the host immune response against the migrating parasite

Facebook's Mobile Career

At the end of its first decade, Facebook’s identity, popularity, and characteristics are shaped in important ways by its becoming a form of mobile media, as much as it as platform associated with Internet and social media. This paper seeks to explore and understand Facebook as the important force in mobile media and communication it now is. It draws upon and combines perspectives from technology production, design, and economy, as well as user adoption, consumption, practices, affect, emotion, and resistance. The paper discusses the beginnings of mobile Facebook, and the early adoption of mobile Facebook associated with the rise of smartphones. The second part of the paper explores Facebook’s integration with photography (with Instagram) and social games (such as Zynga’s Farmville). The paper argues that Facebook’s mobile career is an accomplishment that has distinctively melded evolving affordances, everyday use across a wide range of settings, as well as political economies, corporate strategy, and design.Australian Research Counci

Bovine Genome Database: integrated tools for genome annotation and discovery

The Bovine Genome Database (BGD; http://BovineGenome.org) strives to improve annotation of the bovine genome and to integrate the genome sequence with other genomics data. BGD includes GBrowse genome browsers, the Apollo Annotation Editor, a quantitative trait loci (QTL) viewer, BLAST databases and gene pages. Genome browsers, available for both scaffold and chromosome coordinate systems, display the bovine Official Gene Set (OGS), RefSeq and Ensembl gene models, non-coding RNA, repeats, pseudogenes, single-nucleotide polymorphism, markers, QTL and alignments to complementary DNAs, ESTs and protein homologs. The Bovine QTL viewer is connected to the BGD Chromosome GBrowse, allowing for the identification of candidate genes underlying QTL. The Apollo Annotation Editor connects directly to the BGD Chado database to provide researchers with remote access to gene evidence in a graphical interface that allows editing and creating new gene models. Researchers may upload their annotations to the BGD server for review and integration into the subsequent release of the OGS. Gene pages display information for individual OGS gene models, including gene structure, transcript variants, functional descriptions, gene symbols, Gene Ontology terms, annotator comments and links to National Center for Biotechnology Information and Ensembl. Each gene page is linked to a wiki page to allow input from the research community

Normalized long read RNA sequencing in chicken reveals transcriptome complexity similar to human

Background: Despite the significance of chicken as a model organism, our understanding of the chicken transcriptome is limited compared to human. This issue is common to all non-human vertebrate annotations due to the difficulty in transcript identification from short read RNAseq data. While previous studies have used single molecule long read sequencing for transcript discovery, they did not perform RNA normalization and 5'-cap selection which may have resulted in lower transcriptome coverage and truncated transcript sequences. Results: We sequenced normalised chicken brain and embryo RNA libraries with Pacific Bioscience Iso-Seq. 5' cap selection was performed on the embryo library to provide methodological comparison. From these Iso-Seq sequencing projects, we have identified 60 k transcripts and 29 k genes within the chicken transcriptome. Of these, more than 20 k are novel lncRNA transcripts with ~3 k classified as sense exonic overlapping lncRNA, which is a class that is underrepresented in many vertebrate annotations. The relative proportion of alternative transcription events revealed striking similarities between the chicken and human transcriptomes while also providing explanations for previously observed genomic differences. Conclusions: Our results indicate that the chicken transcriptome is similar in complexity compared to human, and provide insights into other vertebrate biology. Our methodology demonstrates the potential of Iso-Seq sequencing to rapidly expand our knowledge of transcriptomics

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

<p>Abstract</p> <p>Background</p> <p>Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer.</p> <p>Results</p> <p>To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage.</p> <p>Conclusions</p> <p>We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment.</p

The Consensus Coding Sequence (Ccds) Project: Identifying a Common Protein-Coding Gene Set for the Human and Mouse Genomes

Effective use of the human and mouse genomes requires reliable identification of genes and their products. Although multiple public resources provide annotation, different methods are used that can result in similar but not identical representation of genes, transcripts, and proteins. The collaborative consensus coding sequence (CCDS) project tracks identical protein annotations on the reference mouse and human genomes with a stable identifier (CCDS ID), and ensures that they are consistently represented on the NCBI, Ensembl, and UCSC Genome Browsers. Importantly, the project coordinates on manually reviewing inconsistent protein annotations between sites, as well as annotations for which new evidence suggests a revision is needed, to progressively converge on a complete protein-coding set for the human and mouse reference genomes, while maintaining a high standard of reliability and biological accuracy. To date, the project has identified 20,159 human and 17,707 mouse consensus coding regions from 17,052 human and 16,893 mouse genes. Three evaluation methods indicate that the entries in the CCDS set are highly likely to represent real proteins, more so than annotations from contributing groups not included in CCDS. The CCDS database thus centralizes the function of identifying well-supported, identically-annotated, protein-coding regions.National Human Genome Research Institute (U.S.) (Grant number 1U54HG004555-01)Wellcome Trust (London, England) (Grant number WT062023)Wellcome Trust (London, England) (Grant number WT077198