myKaryoView: A Light-Weight Client for Visualization of Genomic Data

The Distributed Annotation System (DAS) is a protocol for easy sharing and integration of biological annotations. In order to visualize feature annotations in a genomic context a client is required. Here we present myKaryoView, a simple light-weight DAS tool for visualization of genomic annotation. myKaryoView has been specifically configured to help analyse data derived from personal genomics, although it can also be used as a generic genome browser visualization. Several well-known data sources are provided to facilitate comparison of known genes and normal variation regions. The navigation experience is enhanced by simultaneous rendering of different levels of detail across chromosomes. A simple interface is provided to allow searches for any SNP, gene or chromosomal region. User-defined DAS data sources may also be added when querying the system. We demonstrate myKaryoView capabilities for adding user-defined sources with a set of genetic profiles of family-related individuals downloaded directly from 23andMe. myKaryoView is a web tool for visualization of genomic data specifically designed for direct-to-consumer genomic data that uses publicly available data distributed throughout the Internet. It does not require data to be held locally and it is capable of rendering any feature as long as it conforms to DAS specifications. Configuration and addition of sources to myKaryoView can be done through the interface. Here we show a proof of principle of myKaryoView's ability to display personal genomics data with 23andMe genome data sources. The tool is available at: http://mykaryoview.com

A case of isolation by distance and short-term temporal stability of population structure in brown trout (Salmo trutta) within the River Dart, southwest England

This is an open access article that is freely available in ORE or from the publisher's web site. Please cite the published version.© 2009 The Authors. Journal compilation © 2009 Blackwell Publishing LtdSalmonid fishes exhibit high levels of population differentiation. In particular, the brown trout (Salmo trutta L.) demonstrates complex within river drainage genetic structure. Increasingly, these patterns can be related to the underlying evolutionary models, of which three scenarios (member-vagrant hypothesis, metapopulation model and panmixia) facilitate testable predictions for investigations into population structure. We analysed 1225 trout collected from the River Dart, a 75 km long river located in southwest England. Specimens were collected from 22 sample sites across three consecutive summers (2001–2003) and genetic variation was examined at nine microsatellite loci. A hierarchical analysis of molecular variance revealed that negligible genetic variation was attributed among temporal samples. The highest levels of differentiation occurred among samples isolated above barriers to fish movement, and once these samples were removed, a significant effect of isolation-by-distance was observed. These results suggest that, at least in the short-term, ecological events are more important in shaping the population structure of Dart trout than stochastic extinction events, and certainly do not contradict the expectations of a member-vagrant hypothesis. Furthermore, individual-level spatial autocorrelation analyses support previous recommendations for the preservation of a number of spawning sites spaced throughout the tributary system to conserve the high levels of genetic variation identified in salmonid species

Identifying Regulators for EAG1 Channels with a Novel Electrophysiology and Tryptophan Fluorescence Based Screen

Ether-à-go-go (EAG) channels are expressed throughout the central nervous system and are also crucial regulators of cell cycle and tumor progression. The large intracellular amino- and carboxy- terminal domains of EAG1 each share similarity with known ligand binding motifs in other proteins, yet EAG1 channels have no known regulatory ligands.Here we screened a library of small biologically relevant molecules against EAG1 channels with a novel two-pronged screen to identify channel regulators. In one arm of the screen we used electrophysiology to assess the functional effects of the library compounds on full-length EAG1 channels. In an orthogonal arm, we used tryptophan fluorescence to screen for binding of the library compounds to the isolated C-terminal region.Several compounds from the flavonoid, indole and benzofuran chemical families emerged as binding partners and/or regulators of EAG1 channels. The two-prong screen can aid ligand and drug discovery for ligand-binding domains of other ion channels

SNOntology: Myriads of novel snornas or just a mirage?

<p>Abstract</p> <p>Background</p> <p>Small nucleolar RNAs (snoRNAs) are a large group of non-coding RNAs (ncRNAs) that mainly guide 2'-O-methylation (C/D RNAs) and pseudouridylation (H/ACA RNAs) of ribosomal RNAs. The pattern of rRNA modifications and the set of snoRNAs that guide these modifications are conserved in vertebrates. Nearly all snoRNA genes in vertebrates are localized in introns of other genes and are processed from pre-mRNAs. Thus, the same promoter is used for the transcription of snoRNAs and host genes.</p> <p>Results</p> <p>The series of studies by Dahai Zhu and coworkers on snoRNAs and their genes were critically considered. We present evidence that dozens of species-specific snoRNAs that they described in vertebrates are experimental artifacts resulting from the improper use of Northern hybridization. The snoRNA genes with putative intrinsic promoters that were supposed to be transcribed independently proved to contain numerous substitutions and are, most likely, pseudogenes. In some cases, they are localized within introns of overlooked host genes. Finally, an increased number of snoRNA genes in mammalian genomes described by Zhu and coworkers is also an artifact resulting from two mistakes. First, numerous mammalian snoRNA pseudogenes were considered as genes, whereas most of them are localized outside of host genes and contain substitutions that question their functionality. Second, Zhu and coworkers failed to identify many snoRNA genes in non-mammalian species. As an illustration, we present 1352 C/D snoRNA genes that we have identified and annotated in vertebrates.</p> <p>Conclusions</p> <p>Our results demonstrate that conclusions based only on databases with automatically annotated ncRNAs can be erroneous. Special investigations aimed to distinguish true RNA genes from their pseudogenes should be done. Zhu and coworkers, as well as most other groups studying vertebrate snoRNAs, give new names to newly described homologs of human snoRNAs, which significantly complicates comparison between different species. It seems necessary to develop a uniform nomenclature for homologs of human snoRNAs in other vertebrates, e.g., human gene names prefixed with several-letter code denoting the vertebrate species.</p

Whole Genome Expression Array Profiling Highlights Differences in Mucosal Defense Genes in Barrett's Esophagus and Esophageal Adenocarcinoma

Esophageal adenocarcinoma (EAC) has become a major concern in Western countries due to rapid rises in incidence coupled with very poor survival rates. One of the key risk factors for the development of this cancer is the presence of Barrett's esophagus (BE), which is believed to form in response to repeated gastro-esophageal reflux. In this study we performed comparative, genome-wide expression profiling (using Illumina whole-genome Beadarrays) on total RNA extracted from esophageal biopsy tissues from individuals with EAC, BE (in the absence of EAC) and those with normal squamous epithelium. We combined these data with publically accessible raw data from three similar studies to investigate key gene and ontology differences between these three tissue states. The results support the deduction that BE is a tissue with enhanced glycoprotein synthesis machinery (DPP4, ATP2A3, AGR2) designed to provide strong mucosal defenses aimed at resisting gastro-esophageal reflux. EAC exhibits the enhanced extracellular matrix remodeling (collagens, IGFBP7, PLAU) effects expected in an aggressive form of cancer, as well as evidence of reduced expression of genes associated with mucosal (MUC6, CA2, TFF1) and xenobiotic (AKR1C2, AKR1B10) defenses. When our results are compared to previous whole-genome expression profiling studies keratin, mucin, annexin and trefoil factor gene groups are the most frequently represented differentially expressed gene families. Eleven genes identified here are also represented in at least 3 other profiling studies. We used these genes to discriminate between squamous epithelium, BE and EAC within the two largest cohorts using a support vector machine leave one out cross validation (LOOCV) analysis. While this method was satisfactory for discriminating squamous epithelium and BE, it demonstrates the need for more detailed investigations into profiling changes between BE and EAC

Mitotic Spindle Proteomics in Chinese Hamster Ovary Cells

Mitosis is a fundamental process in the development of all organisms. The mitotic spindle guides the cell through mitosis as it mediates the segregation of chromosomes, the orientation of the cleavage furrow, and the progression of cell division. Birth defects and tissue-specific cancers often result from abnormalities in mitotic events. Here, we report a proteomic study of the mitotic spindle from Chinese Hamster Ovary (CHO) cells. Four different isolations of metaphase spindles were subjected to Multi-dimensional Protein Identification Technology (MudPIT) analysis and tandem mass spectrometry. We identified 1155 proteins and used Gene Ontology (GO) analysis to categorize proteins into cellular component groups. We then compared our data to the previously published CHO midbody proteome and identified proteins that are unique to the CHO spindle. Our data represent the first mitotic spindle proteome in CHO cells, which augments the list of mitotic spindle components from mammalian cells

Massive-Scale RNA-Seq Analysis of Non Ribosomal Transcriptome in Human Trisomy 21

Hybridization- and tag-based technologies have been successfully used in Down syndrome to identify genes involved in various aspects of the pathogenesis. However, these technologies suffer from several limits and drawbacks and, to date, information about rare, even though relevant, RNA species such as long and small non-coding RNAs, is completely missing. Indeed, none of published works has still described the whole transcriptional landscape of Down syndrome. Although the recent advances in high-throughput RNA sequencing have revealed the complexity of transcriptomes, most of them rely on polyA enrichment protocols, able to detect only a small fraction of total RNA content. On the opposite end, massive-scale RNA sequencing on rRNA-depleted samples allows the survey of the complete set of coding and non-coding RNA species, now emerging as novel contributors to pathogenic mechanisms. Hence, in this work we analysed for the first time the complete transcriptome of human trisomic endothelial progenitor cells to an unprecedented level of resolution and sensitivity by RNA-sequencing. Our analysis allowed us to detect differential expression of even low expressed genes crucial for the pathogenesis, to disclose novel regions of active transcription outside yet annotated loci, and to investigate a plethora of non-polyadenilated long as well as short non coding RNAs. Novel splice isoforms for a large subset of crucial genes, and novel extended untranslated regions for known genes—possibly novel miRNA targets or regulatory sites for gene transcription—were also identified in this study. Coupling the rRNA depletion of samples, followed by high-throughput RNA-sequencing, to the easy availability of these cells renders this approach very feasible for transcriptome studies, offering the possibility of investigating in-depth blood-related pathological features of Down syndrome, as well as other genetic disorders

From protein sequences to 3D-structures and beyond: the example of the UniProt Knowledgebase

With the dramatic increase in the volume of experimental results in every domain of life sciences, assembling pertinent data and combining information from different fields has become a challenge. Information is dispersed over numerous specialized databases and is presented in many different formats. Rapid access to experiment-based information about well-characterized proteins helps predict the function of uncharacterized proteins identified by large-scale sequencing. In this context, universal knowledgebases play essential roles in providing access to data from complementary types of experiments and serving as hubs with cross-references to many specialized databases. This review outlines how the value of experimental data is optimized by combining high-quality protein sequences with complementary experimental results, including information derived from protein 3D-structures, using as an example the UniProt knowledgebase (UniProtKB) and the tools and links provided on its website (http://www.uniprot.org/). It also evokes precautions that are necessary for successful predictions and extrapolations

RNAcentral: a comprehensive database of non-coding RNA sequences

RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. The website has been subject to continuous improvements focusing on text and sequence similarity searches as well as genome browsing functionality. All RNAcentral data is provided for free and is available for browsing, bulk downloads, and programmatic access at http://rnacentral.org/.Biotechnology and Biological Sciences Research Council (BBSRC) [BB/J019232/1]