GrainGenes is the USDA-ARS database and Web resource for wheat, barley, oat, rye, and their relatives. As a community Web hub and database for small grains, GrainGenes strives to provide resources for researchers, students, and plant breeders to improve traits such as quality, yield, and disease resistance. Quantitative trait loci (QTL), genes, and genetic maps for quality attributes in GrainGenes represent the historical approach to mapping genes for groat percentage, test weight, protein, fat, and β-glucan content in oat (Avena spp.). Genetic maps are viewable in CMap, the comparative mapping tool that enables researchers to take advantage of highly populated consensus maps to increase the marker density around their genes-of-interest. GrainGenes hosts over 50 genome browsers and is launching an effort for community curation, including the manually curated tracks with beta-glucan QTL and significant markers found via GWAS and cloned cellulose synthase-like AsClF6 alleles.

We describe JBrowse Connect, an optional expansion to the JBrowse genome browser, targeted at developers. JBrowse Connect allows live messaging, notifications for new annotation tracks, heavy-duty analyses initiated by the user from within the browser, and other dynamic features. We present example applications of JBrowse Connect that allow users 1) to specify and execute BLAST searches by either running on the same host as the webserver, with a self-contained BLAST module leveraging NCBI Blast+ commands, or via a managed Galaxy instance that can optionally run on a different host, and 2) to run the primer design service Primer3. JBrowse Connect allows users to track job progress and view results in the context of the browser. The software is available under a choice of open source licenses including LGPL and the Artistic License.

Context. Researchers have been accumulating information concerning the locations of genes and quantitative trait loci (QTLs) in cultivated oat (Avena sativa L.) for more than 100 years. Aims. The aim of this work was to create an inventory of genes and QTLs found in cultivated hexaploid oat and produce tools to make this resource more useful. Methods. By using the positions of perfectly matched, single nucleotide polymorphism markers, each centimorgan (cM) location along the consensus map was assigned to a location on the OT3098 v2 physical map found on the GrainGenes database website (https://wheat.pw.usda.gov/jb/?data=/ggds/oat-ot3098v2-pepsico). This information was then used to assign physical locations to the genes and QTLs in the inventory, where possible. Key results. A table comparing the major genetic maps of hexaploid oats to each other, to the 2018 oat consensus map, and to physical chromosomes was produced. Genome browser tracks aligning the consensus map regions and the locations of the genes and QTLs to OT3098 v2 were added to GrainGenes. Conclusions. Many oat genes and QTLs identified using genetic mapping could be assigned positions on physical oat chromosomes. However, many of these assigned regions are quite long, owing to the presence of large areas of reduced recombination. Specific examples of identified patterns of recombination between the genetic and physical maps and validated gene and QTL locations are discussed. Implications. These resources will assist researchers performing comparative genetic and physical mapping in oat.

Genome annotation is the process of identifying the location and function of a genome’s encoded features. Improving the biological accuracy of annotation is a complex and iterative process requiring researchers to review and incorporate multiple sources of information such as transcriptome alignments, predictive models based on sequence profiles, and comparisons to features found in related organisms. Because rapidly decreasing costs are enabling an ever-growing number of scientists to incorporate sequencing as a routine laboratory technique, there is widespread demand for tools that can assist in the deliberative analytical review of genomic information. To this end, Apollo is an open source software package that enables researchers to efficiently inspect and refine the precise structure and role of genomic features in a graphical browser-based platform. In this paper we first outline some of Apollo’s newer user interface features, which were driven by the needs of this expanding genomics community. These include support for real-time collaboration, allowing distributed users to simultaneously edit the same encoded features while also instantly seeing the updates made by other researchers on the same region in a manner similar to Google Docs. Its technical architecture enables Apollo to be integrated into multiple existing genomic analysis pipelines and heterogeneous laboratory workflow platforms. Finally, we consider the implications that Apollo and related applications may have on how the results of genome research are published and made accessible. Source: https://github.com/GMOD/Apollo License (BSD-3): https://github.com/GMOD/Apollo/blob/master/LICENSE.md Docker: https://hub.docker.com/r/gmod/apollo/tags/ , https://github.com/GMOD/docker-apollo Requirements: JDK 1.8, Node v6.0+ User guide: http://genomearchitect.org ; technical guide: http://genomearchitect.readthedocs.io/en/latest/ Mailing list: apollo@lists.lbl.gov

Genome annotation is the process of identifying the location and function of a genome's encoded features. Improving the biological accuracy of annotation is a complex and iterative process requiring researchers to review and incorporate multiple sources of information such as transcriptome alignments, predictive models based on sequence profiles, and comparisons to features found in related organisms. Because rapidly decreasing costs are enabling an ever-growing number of scientists to incorporate sequencing as a routine laboratory technique, there is widespread demand for tools that can assist in the deliberative analytical review of genomic information. To this end, we present Apollo, an open source software package that enables researchers to efficiently inspect and refine the precise structure and role of genomic features in a graphical browser-based platform. Some of Apollo's newer user interface features include support for real-time collaboration, allowing distributed users to simultaneously edit the same encoded features while also instantly seeing the updates made by other researchers on the same region in a manner similar to Google Docs. Its technical architecture enables Apollo to be integrated into multiple existing genomic analysis pipelines and heterogeneous laboratory workflow platforms. Finally, we consider the implications that Apollo and related applications may have on how the results of genome research are published and made accessible.

Background

JBrowse is a fast and full-featured genome browser built with JavaScript and HTML5. It is easily embedded into websites or apps but can also be served as a standalone web page.

Results

Overall improvements to speed and scalability are accompanied by specific enhancements that support complex interactive queries on large track sets. Analysis functions can readily be added using the plugin framework; most visual aspects of tracks can also be customized, along with clicks, mouseovers, menus, and popup boxes. JBrowse can also be used to browse local annotation files offline and to generate high-resolution figures for publication.

Conclusions

JBrowse is a mature web application suitable for genome visualization and analysis.

As one of the US Department of Agriculture-Agricultural Research Service flagship databases, GrainGenes (https://wheat.pw.usda.gov) serves the data and community needs of globally distributed small grains researchers for the genetic improvement of the Triticeae family and Avena species that include wheat, barley, rye and oat. GrainGenes accomplishes its mission by continually enriching its cross-linked data content following the findable, accessible, interoperable and reusable principles, enhancing and maintaining an intuitive web interface, creating tools to enable easy data access and establishing data connections within and between GrainGenes and other biological databases to facilitate knowledge discovery. GrainGenes operates within the biological database community, collaborates with curators and genome sequencing groups and contributes to the AgBioData Consortium and the International Wheat Initiative through the Wheat Information System (WheatIS). Interactive and linked content is paramount for successful biological databases and GrainGenes now has 2917 manually curated gene records, including 289 genes and 254 alleles from the Wheat Gene Catalogue (WGC). There are >4.8 million gene models in 51 genome browser assemblies, 6273 quantitative trait loci and >1.4 million genetic loci on 4756 genetic and physical maps contained within 443 mapping sets, complete with standardized metadata. Most notably, 50 new genome browsers that include outputs from the Wheat and Barley PanGenome projects have been created. We provide an example of an expression quantitative trait loci track on the International Wheat Genome Sequencing Consortium Chinese Spring wheat browser to demonstrate how genome browser tracks can be adapted for different data types. To help users benefit more from its data, GrainGenes created four tutorials available on YouTube. GrainGenes is executing its vision of service by continuously responding to the needs of the global small grains community by creating a centralized, long-term, interconnected data repository. Database URL:https://wheat.pw.usda.gov.

Wheat (Triticum aestivum) is one of the most important food crops with an urgent need for increase in its production to feed the growing world. Triticum timopheevii (2n = 4x = 28) is an allotetraploid wheat wild relative species containing the A^t and G genomes that has been exploited in many pre-breeding programmes for wheat improvement. In this study, we report the generation of a chromosome-scale reference genome assembly of T. timopheevii accession PI 94760 based on PacBio HiFi reads and chromosome conformation capture (Hi-C). The assembly comprised a total size of 9.35 Gb, featuring a contig N50 of 42.4 Mb and included the mitochondrial and plastid genome sequences. Genome annotation predicted 166,325 gene models including 70,365 genes with high confidence. DNA methylation analysis showed that the G genome had on average more methylated bases than the A^t genome. In summary, the T. timopheevii genome assembly provides a valuable resource for genome-informed discovery of agronomically important genes for food security.

GrainGenes (https://wheat.pw.usda.gov or https://graingenes.org) is an international centralized repository for curated, peer-reviewed datasets useful to researchers working on wheat, barley, rye and oat. GrainGenes manages genomic, genetic, germplasm and phenotypic datasets through a dynamically generated web interface for facilitated data discovery. Since 1992, GrainGenes has served geneticists and breeders in both the public and private sectors on six continents. Recently, several new datasets were curated into the database along with new tools for analysis. The GrainGenes homepage was enhanced by making it more visually intuitive and by adding links to commonly used pages. Several genome assemblies and genomic tracks are displayed through the genome browsers at GrainGenes, including the Triticum aestivum (bread wheat) cv. 'Chinese Spring' IWGSC RefSeq v1.0 genome assembly, the Aegilops tauschii (D genome progenitor) Aet v4.0 genome assembly, the Triticum turgidum ssp. dicoccoides (wild emmer wheat) cv. 'Zavitan' WEWSeq v.1.0 genome assembly, a T. aestivum (bread wheat) pangenome, the Hordeum vulgare (barley) cv. 'Morex' IBSC genome assembly, the Secale cereale (rye) select 'Lo7' assembly, a partial hexaploid Avena sativa (oat) assembly and the Triticum durum cv. 'Svevo' (durum wheat) RefSeq Release 1.0 assembly. New genetic maps and markers were added and can be displayed through CMAP. Quantitative trait loci, genetic maps and genes from the Wheat Gene Catalogue are indexed and linked through the Wheat Information System (WheatIS) portal. Training videos were created to help users query and reach the data they need. GSP (Genome Specific Primers) and PIECE2 (Plant Intron Exon Comparison and Evolution) tools were implemented and are available to use. As more small grains reference sequences become available, GrainGenes will play an increasingly vital role in helping researchers improve crops.