Sean Davey

GEISHA: an in situ hybridization gene expression resource for the chicken embryo

An important and ongoing focus of biomedical and agricultural avian research is to understand gene function, which for a significant fraction of genes remains unknown. A first step is to determine when and where genes are expressed during development and in the adult. Whole mount in situ hybridization gives precise spatial and temporal resolution of gene expression throughout an embryo, and a comprehensive analysis and centralized repository of in situ hybridization information would provide a valuable research tool. The GEISHA project (<X_Underline>g</X_Underline>allus <X_Underline>e</X_Underline>xpression <X_Underline>i</X_Underline>n <X_Underline>s</X_Underline>itu <X_Underline>h</X_Underline>ybridization <X_Underline>a</X_Underline>nalysis) was initiated to explore the utility of using high-throughput in situ hybridization as a means for gene discovery and annotation in chicken embryos, and to provide a unified repository for in situ hybridization information. This report describes the design and implementation of a new GEISHA database and user interface (www.geisha.arizona.edu), and illustrates its utility for researchers in the biomedical and poultry science communities. Results obtained from a high throughput screen of microRNA expression in chicken embryos are also presented.

BioNetBuilder2.0: Bringing systems biology to chicken and other model organisms

BackgroundSystems Biology research tools, such as Cytoscape, have greatly extended the reach of genomic research. By providing platforms to integrate data with molecular interaction networks, researchers can more rapidly begin interpretation of large data sets collected for a system of interest. BioNetBuilder is an open-source client-server Cytoscape plugin that automatically integrates molecular interactions from all major public interaction databases and serves them directly to the users Cytoscape environment. Until recently however, chicken and other eukaryotic model systems had little interaction data available.ResultsVersion 2.0 of BioNetBuilder includes a redesigned synonyms resolution engine that enables transfer and integration of interactions across species; this engine translates between alternate gene names as well as between orthologs in multiple species. Additionally, BioNetBuilder is now implemented to be part of the Gaggle, thereby allowing seamless communication of interaction data to any software implementing the widely used Gaggle software. Using BioNetBuilder, we constructed a chicken interactome possessing 72,000 interactions among 8,140 genes directly in the Cytoscape environment. In this paper, we present a tutorial on how to do so and analysis of a specific use case.ConclusionBioNetBuilder 2.0 provides numerous user-friendly systems biology tools that were otherwise inaccessible to researchers in chicken genomics, as well as other model systems. We provide a detailed tutorial spanning all required steps in the analysis. BioNetBuilder 2.0, the tools for maintaining its data bases, standard operating procedures for creating local copies of its back-end data bases, as well as all of the Gaggle and Cytoscape codes required, are open-source and freely available at http://err.bio.nyu.edu/cytoscape/bionetbuilder/.

Sequenced subset operators: definition and implementation

Difference, intersection, semi join and anti-semi-join may be considered binary subset operators, in that they all return a subset of their left-hand argument. These operators are useful for implementing SQLs EXCEPT, INTERSECT, NOT IN and NOT EXISTS, distributed queries and referential integrity. Difference-all and intersection-all operate on multi-sets and track the number of duplicates in both argument relations; they are used to implement SQLs EXCEPT ALL and INTERSECT ALL. Their temporally sequenced analogues, which effectively apply the subset operator at each point in time, are needed for implementing these constructs in temporal databases. These SQL expressions are complex; most necessitate at least a three-way join, with nested NOT EXISTS clauses. We consider how to implement these operators directly in a DBMS. These operators are interesting in that they can fragment the left-hand validity periods (sequenced difference-all also fragments the right-hand periods) and thus introduce memory complications found neither in their non-temporal counterparts nor in temporal joins and semijoins. We introduce novel algorithms for implementing these operators by ordering the computation so that fragments need not be retained in main memory. We evaluate these algorithms and demonstrate that they are no more expensive than a single conventional join.

GEISHA: an evolving gene expression resource for the chicken embryo

GEISHA (Gallus Expression In Situ Hybridization Analysis; http://geisha.arizona.edu) is an in situ hybridization gene expression and genomic resource for the chicken embryo. This update describes modifications that enhance its utility to users. During the past 5 years, GEISHA has undertaken a significant restructuring to more closely conform to the data organization and formatting of Model Organism Databases in other species. This has involved migrating from an entry-centric format to one that is gene-centered. Database restructuring has enabled the inclusion of data pertaining to chicken genes and proteins and their orthologs in other species. This new information is presented through an updated user interface. In situ hybridization data in mouse, frog, zebrafish and fruitfly are integrated with chicken genomic and expression information. A resource has also been developed that integrates the GEISHA interface information with the Online Mendelian Inheritance in Man human disease gene database. Finally, the Chicken Gene Nomenclature Committee database and the GEISHA database have been integrated so that they draw from the same data resources.

CoGe LoadExp+: A web-based suite that integrates next-generation sequencing data analysis workflows and visualization

Summary To make genomic and epigenomic analyses more widely available to the biological research community, we have created LoadExp+, a suite of bioinformatics workflows integrated with the web‐based comparative genomics platform, CoGe. LoadExp+ allows users to perform transcriptomic (RNA‐seq), epigenomic (bisulfite‐seq), chromatin‐binding (ChIP‐seq), variant identification (SNPs), and population genetics analyses against any genome in CoGe, including genomes integrated by users themselves. Through LoadExp+s integration with CoGes existing features, all analyses are available for visualization and additional downstream processing, and are available for export to CyVerses data management and analysis platforms. LoadExp+ provides easy‐to‐use functionality to manage genomics and epigenomics data throughout its entire lifecycle using a publicly available web‐based platform and facilitates greater accessibility of genomics analyses to researchers of all skill levels. LoadExp+ can be accessed at https://genomevolution.org.

SynMap2 and SynMap3D: web-based whole-genome synteny browsers

Summary Current synteny visualization tools either focus on small regions of sequence and do not illustrate genome-wide trends, or are complicated to use and create visualizations that are difficult to interpret. To address this challenge, The Comparative Genomics Platform (CoGe) has developed two web-based tools to visualize synteny across whole genomes. SynMap2 and SynMap3D allow researchers to explore whole genome synteny patterns (across two or three genomes, respectively) in responsive, web-based visualization and virtual reality environments. Both tools have access to the extensive CoGe genome database (containing over 30 000 genomes) as well as the option for users to upload their own data. By leveraging modern web technologies there is no installation required, making the tools widely accessible and easy to use. Availability and Implementation Both tools are open source (MIT license) and freely available for use online through CoGe ( https://genomevolution.org ). SynMap2 and SynMap3D can be accessed at http://genomevolution.org/coge/SynMap.pl and http://genomevolution.org/coge/SynMap3D.pl , respectively. Source code is available: https://github.com/LyonsLab/coge . Contact ericlyons@email.arizona.edu. Supplementary information Supplementary data are available at Bioinformatics online.

FractBias: a graphical tool for assessing fractionation bias following polyploidy

Summary: Following polyploidy events, genomes undergo massive reduction in gene content through a process known as fractionation. Importantly, the fractionation process is not always random, and a bias as to which homeologous chromosome retains or loses more genes can be observed in some species. The process of characterizing whole genome fractionation requires identifying syntenic regions across genomes followed by post‐processing of those syntenic datasets to identify and plot gene retention patterns. We have developed a tool, FractBias, to calculate and visualize gene retention and fractionation patterns across whole genomes. Through integration with SynMap and its parent platform CoGe, assembled genomes are pre‐loaded and available for analysis, as well as letting researchers integrate their own data with security options to keep them private or make them publicly available. Availability and Implementation: FractBias is freely available as a web application at https://genomevolution.org/CoGe/SynMap.pl. The software is open source (MIT license) and executable with Python 2.7 or iPython notebook, and available on GitHub (https://goo.gl/PaAtqy). Documentation for FractBias is available on CoGepedia (https://goo.gl/ou9dt6) Contact: ericlyons@email.arizona.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Language-agnostic program rendering for presentation, debugging and visualization

We describe a language-independent and specification-driven program rendering tool that is able to produce high-quality code renderings of arbitrary complexity. The tool can incorporate arbitrary types of information together with the program code, allowing it to be used for debugging and profiling as well as for producing beautiful renderings of programs for publications. We also present a model for the rendering of programs and apply it to the design of a rendering of Java control flow.

EPIC-CoGe: managing and analyzing genomic data

Abstract Summary The EPIC-CoGe browser is a web-based genome visualization utility that integrates the GMOD JBrowse genome browser with the extensive CoGe genome database (currently containing over 30 000 genomes). In addition, the EPIC-CoGe browser boasts many additional features over basic JBrowse, including enhanced search capability and on-the-fly analyses for comparisons and analyses between all types of functional and diversity genomics data. There is no installation required and data (genome, annotation, functional genomic and diversity data) can be loaded by following a simple point and click wizard, or using a REST API, making the browser widely accessible and easy to use by researchers of all computational skill levels. In addition, EPIC-CoGe and data tracks are easily embedded in other websites and JBrowse instances. Availability and implementation EPIC-CoGe Browser is freely available for use online through CoGe (https://genomevolution.org). Source code (MIT open source) is available: https://github.com/LyonsLab/coge. Supplementary information Supplementary data are available at Bioinformatics online.