LinkageMapView-rendering high-resolution linkage and QTL maps.

MOTIVATION: Linkage and quantitative trait loci (QTL) maps are critical tools for the study of the genetic basis of complex traits. With the advances in sequencing technology over the past decade, linkage map densities have been increasing dramatically, while the visualization tools have not kept pace. LinkageMapView is a free add-on package written in R that produces high resolution, publication-ready visualizations of linkage and QTL maps. While there is software available to generate linkage map graphics, none are freely available, produce publication quality figures, are open source and can run on all platforms. LinkageMapView can be integrated into map building pipelines as it seamlessly incorporates output from R/qtl and also accepts simple text or comma delimited files. There are numerous options within the package to build highly customizable maps, allow for linkage group comparisons, and annotate QTL regions. AVAILABILITY AND IMPLEMENTATION: https://cran.r-project.org/web/packages/LinkageMapView/.

Pathview Web: user friendly pathway visualization and data integration.

Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/.

A Consensus Map in Cultivated Hexaploid Oat Reveals Conserved Grass Synteny with Substantial Subgenome Rearrangement.

Hexaploid oat ( L., 2 = 6 = 42) is a member of the Poaceae family and has a large genome (∼12.5 Gb) containing 21 chromosome pairs from three ancestral genomes. Physical rearrangements among parental genomes have hindered the development of linkage maps in this species. The objective of this work was to develop a single high-density consensus linkage map that is representative of the majority of commonly grown oat varieties. Data from a cDNA-derived single-nucleotide polymorphism (SNP) array and genotyping-by-sequencing (GBS) were collected from the progeny of 12 biparental recombinant inbred line populations derived from 19 parents representing oat germplasm cultivated primarily in North America. Linkage groups from all mapping populations were compared to identify 21 clusters of conserved collinearity. Linkage groups within each cluster were then merged into 21 consensus chromosomes, generating a framework consensus map of 7202 markers spanning 2843 cM. An additional 9678 markers were placed on this map with a lower degree of certainty. Assignment to physical chromosomes with high confidence was made for nine chromosomes. Comparison of homeologous regions among oat chromosomes and matches to orthologous regions of rice ( L.) reveal that the hexaploid oat genome has been highly rearranged relative to its ancestral diploid genomes as a result of frequent translocations among chromosomes. Heterogeneous chromosome rearrangements among populations were also evident, probably accounting for the failure of some linkage groups to match the consensus. This work contributes to a further understanding of the organization and evolution of hexaploid grass genomes.

Genoviz Software Development Kit: Java tool kit for building genomics visualization applications.

BACKGROUND: Visualization software can expose previously undiscovered patterns in genomic data and advance biological science. RESULTS: The Genoviz Software Development Kit (SDK) is an open source, Java-based framework designed for rapid assembly of visualization software applications for genomics. The Genoviz SDK framework provides a mechanism for incorporating adaptive, dynamic zooming into applications, a desirable feature of genome viewers. Visualization capabilities of the Genoviz SDK include automated layout of features along genetic or genomic axes; support for user interactions with graphical elements (Glyphs) in a map; a variety of Glyph sub-classes that promote experimentation with new ways of representing data in graphical formats; and support for adaptive, semantic zooming, whereby objects change their appearance depending on zoom level and zooming rate adapts to the current scale. Freely available demonstration and production quality applications, including the Integrated Genome Browser, illustrate Genoviz SDK capabilities. CONCLUSION: Separation between graphics components and genomic data models makes it easy for developers to add visualization capability to pre-existing applications or build new applications using third-party data models. Source code, documentation, sample applications, and tutorials are available at http://genoviz.sourceforge.net/.

The Integrated Genome Browser: free software for distribution and exploration of genome-scale datasets.

UNLABELLED: Experimental techniques that survey an entire genome demand flexible, highly interactive visualization tools that can display new data alongside foundation datasets, such as reference gene annotations. The Integrated Genome Browser (IGB) aims to meet this need. IGB is an open source, desktop graphical display tool implemented in Java that supports real-time zooming and panning through a genome; layout of genomic features and datasets in moveable, adjustable tiers; incremental or genome-scale data loading from remote web servers or local files; and dynamic manipulation of quantitative data via genome graphs. AVAILABILITY: The application and source code are available from http://igb.bioviz.org and http://genoviz.sourceforge.net.

Subtype specific effects of peroxisome proliferator-activated receptor ligands on corepressor affinity.

Natural ligands for nuclear receptors are believed to activate gene transcription by causing dissociation of corepressors and promoting the association of coactivator proteins. Using multiple biophysical techniques, we find that peptides derived from one of the nuclear receptor interacting motifs of the corepressors nuclear receptor corepressor (NCoR) and silencing mediator of retinoid and thyroid receptors (SMRT) are able to bind the ligand binding domains (LBD) of all three PPAR (peroxisome proliferator activated receptor) subtypes. Using these peptides as tools, we find that ligands designed as selective agonists for PPAR gamma promote the association of coactivator peptides and dissociation of corepressor peptides as expected on PPAR gamma but surprisingly have varied effects on the binding of corepressor peptides to the other PPAR subtypes. In particular, some members of a class of L-tyrosine-based compounds designed as selective agonists for PPAR gamma reduce the affinity for corepressor peptides on PPAR gamma but increase the affinity for the same peptides on PPAR delta and in one case on PPAR alpha. We provide structural data that suggests that the molecular basis for these observations are variations in the ligand binding pockets of the three PPAR subtypes that are perturbed differentially by individual ligands and result in altered presentations of the overlapping coactivator/corepressor binding surfaces.

Functional consequences of cysteine modification in the ligand binding sites of peroxisome proliferator activated receptors by GW9662.

In the course of a high throughput screen to search for ligands of peroxisome proliferator activated receptor-gamma (PPARgamma), we identified GW9662 using a competition binding assay against the human ligand binding domain. GW9662 had nanomolar IC(50) versus PPARgamma and was 10- and 600-fold less potent in binding experiments using PPARalpha and PPARdelta, respectively. Pretreatment of all three PPARs with GW9662 resulted in the irreversible loss of ligand binding as assessed by scintillation proximity assay. Incubation of PPAR with GW9662 resulted in a change in the absorbance spectra of the receptors consistent with covalent modification. Mass spectrometric analysis of the PPARgamma ligand binding domain treated with GW9662 established Cys(285) as the site of covalent modification. This cysteine is conserved among all three PPARs. In cell-based reporter assays, GW9662 was a potent and selective antagonist of full-length PPARgamma. The functional activity of GW9662 as an antagonist of PPARgamma was confirmed in an assay of adipocyte differentiation. GW9662 showed essentially no effect on transcription when tested using both full-length PPARdelta and PPARalpha. Time-resolved fluorescence assays of ligand-modulated receptor heterodimerization, coactivator binding, and corepressor binding were consistent with the effects observed in the reporter gene assays. Control activators increased PPAR:RXR heterodimer formation and coactivator binding to both PPARgamma and PPARdelta. Corepressor binding was decreased. In the case of PPARalpha, GW9662 treatment did not significantly increase heterodimerization and coactivator binding or decrease corepressor binding. The experimental data indicate that GW9662 modification of each of the three PPARs results in different functional consequences. The selective and irreversible nature of GW9662 treatment, and the observation that activity is maintained in cell culture experiments, suggests that this compound may be a useful tool for elucidation of the role of PPARgamma in biological processes.