PAG 2017 Booth

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Agricultural Biological Database Outreach Consortium Booth #407

Plant and Animal Genome 2017

Visit a collection of Plant and Animal Genomics databases and projects with resources for sequenced genomes, ontology development, genetic mapping, functional annotation of genes, mutants and phenotypes, genetic diversity, and bioinformatics tools. Representatives from the projects indicated below will be present to demonstrate tools for cutting-edge genomics and genetics research, and to answer questions.

You can find us at Booth #407 Trying to meet with a representative of one of our resources? Here is our booth schedule:

File:AgBio Database Booth Schedule 2017 FINAL.pdf




Gramene

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See Gramene's web page for more information: http://www.gramene.org

Gramene is a curated resource for comparative functional genomics in crops and model plant species currently hosting 44 complete reference genomes. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. Gene evolutionary histories are provided in phylogenetic gene trees using a method that infers orthologous relationships and complements whole genome alignments. Variation data is available for 11 species, including Arabidopsis, rice, and maize, and enriched with variant effect prediction. Gramene hosts metabolic pathways databases developed in house or by our collaborators in the BioCyc platform, which facilitates uploading, visualization and analysis. Recently, we began annotating metabolic pathways using the Reactome model, and have released a beta version of the Plant Reactome, a platform for the comparative analysis of plant metabolic and regulatory networks, featuring at present over 240 curated rice pathways and orthologous pathway projections to 66 plant species. We also host many genetic and QTL maps contributed by the broad research community. Gramene is supported by an NSF grant (IOS-1127112), and works closely with EBI-EMBL, OICR, and ASPB.

Gramene workshop: Tuesday, January 17 of 2017 1:30 - 3:40 pm PST in the California Room.

  • W480 - Overview of Gramene's Ensembl Genome Browser - Marcela Karey Tello-Ruiz
  • W481 - Mining Rice Disease Resistance Genes Using Gramene - Joshua Stein
  • W482 - Plant Reactome: A Resource for Comparative Analysis of Plant Pathways - Pankaj Jaiswal
  • W483 - High Resolution Transcriptome Analysis of Rice Salt Response Enabled by Gramene Resources - Matthew Geniza
  • W484 - Plant Gene Expression in EMBL-EBI Expression Atlas - Maria Keays

Talks:

  • W399 - Unveiling the Complexity of Maize Transcriptome Using Single-Molecule Long-Read Sequencing. Tuesday, January 17, 2017 @ 05:30 PM - 05:50 PM. Royal Palm Salon 1-2
  • W820 - The Complex Sequence Landscape of Maize Revealed by Single Molecule Technologies. Sunday, January 15, 2017 @ 04:00 PM - 04:20 PM. Golden Ballroom

Posters:

  • P0005 - The Complex Sequence Landscape of Maize Revealed By Single Molecule Technologies
  • P0447 Benchmarking Alignment and Quantification Tools on Plant RNA-Seq Data with CyVerse Cyberinfrastructure

Gramene representatives will also be available to meet with users and answer questions at booth #407 throughout the meeting.

For more information please contact: Gramene Feedback or e-mail feedback@gramene.org

Funding: Our participation at this outreach booth is being made possible thanks to the funding support of NSF award #1127112 to "Gramene - Exploring Function through Comparative Genomics and Network Analysis" and USDA-ARS #1907-21000-030-00D.


MaizeGDB

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See MaizeGDB's web page for more information: http://www.maizegdb.org/

MaizeGDB is a community-oriented, long-term informatics service to researchers focused on the crop plant and model organism Zea mays that is funded by the USDA-ARS.

Of interest to most researchers are the integration of genetics and genomics at MaizeGDB. From the MaizeGDB Genome Browser, cM estimates of genome size are available. Mechanisms to locate loci of interest on the genome are available via the Locus Lookup and Locus Pair Lookup.

Functional genomics tools at MaizeGDB with access to the eFP Browser images from the Sekhon et al. Maize Gene Expression Atlas via gene model pages (e.g., [1]) as well as comparisons and views of the same dataset via MapMan where the data can be visualized online directly.


Plant Genome DataBase Japan (PGDBj)

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A portal website, PGDBj (Plant Genome DataBase Japan; http://pgdbj.jp) has been developed to integrate a variety of information related to genomes of model and crop plants from databases (DBs) and the literature. PGDBj is comprised of three component DBs: Ortholog DB, Plant Resource DB, and DNA Marker DB; and a cross-search engine which provides a seamless search over their contents. The Ortholog DB provides gene cluster information based on the amino acid sequence similarity for over 1,000,000 amino acid sequences of 40 Viridiplantae species collected from NCBI RefSeq database. The Plant Resource DB provides information of genomic- and bio-resources distributed from DBs provided by Kazusa DNA Research Institute and SABRE DB, maintained in the RIKEN BioResource Center and National BioResource Projects Japan. The DNA Marker DB provides the information of DNA markers, quantitative trait loci (QTL) and related genetic linkage maps which were manually or automatically collected and curated from the literature and external DBs for 80 plant species. By combining these component DBs and a cross-search engine, PGDBj serves as a useful platform to study genetic systems for both fundamental and applied researches for a wide range of plant species.



Crop Ontology

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The Crop Ontology is a service of the Integrated Breeding Platform (IBP) developed in collaboration with the CGIAR centers and partners, under the leadership of Bioversity international. The Crop Ontology (www.cropontology.org) provides harmonized and validated breeders’ trait names, measurement methods, scales and standard variables for currently 19 CGIAR crops: banana, barley cassava, cowpea, chickpea, common bean, groundnut, lentil, maize, pearl millet, pigeonpea, potato, sorghum, soybean, sweet potato, rice, wheat, yam. Partners provided their ontologies for oat (Oat Global), solanaceae (SGN) and vitis (INRA).


Crop Ontology is used by the Breeding Management System (BMS) of the IBP and the Next Generation Breeding Databases developed by Boyce Thompson Institute. The Crop Ontology contributes to the content enrichment of the reference ontologies of the Planteome project (http://www.planteome.org/).


To fully understand the implications of varying factors within any cropping system, it is important to combine results of field management practices with crop traits. Therefore, an Agronomy Ontology is being developed to index key agronomic variables that will power an Agronomy Management System and Fieldbook, modeled on a CGIAR Breeding Management System and Fieldbook. The ontology development started with the compilation of existing lists of variables, factors, and methods commonly used by agronomists to described the trial management.



Solanaceae Genomics Network

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See the SGN's web page for more information: http://solgenomics.net


The SOL Genomics Network is a Clade Oriented Database (COD) containing genomic, genetic, phenotypic and taxonomic information for species in the Euasterid clade, including the families Solanaceae (e.g. tomato, potato, eggplant, pepper, petunia) and Rubiaceae (coffee). Genomic information is presented in a comparative format and tied to other important plant model species such as Arabidopsis. SGN is also one of the bioinformatics centers involved in tomato genome sequencing.

One of the major efforts at SGN is linking Solanaceae phenotype information with the underlying genes, and subsequently the genome. As part of this goal, SGN puts the control over the information in the hands of community experts. As a result, SGN annotations are more up-to-date, and richer with detailed descriptions and gene-to-phenotype cross links, than would otherwise be possible without a large curatorial staff.

For more information please contact: SGN Contact





BAR: The Bio-Analytic Resource for Plant Functional Genomics

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See BAR's web page for more information: http://www.bar.utoronto.ca


The Bio-Analytic Resource at the University of Toronto is a collection of web-based tools for exploring, visualizing and mining large-scale data sets, primarily from Arabidopsis thaliana but also from several other plant species.

These tools include:

eFP Browser (electronic Fluorescent Pictograph Browser) for painting gene expression and other information onto diagrammatic representations of the particular experimental series from which the data were generated. eFP Browsers are available for Arabidopsis, poplar, Medicago truncatula, rice, barley, soybean, maize, potato, moss and cell.

Expression Angler for identifying co-expressed, anti-correlated, or condition/tissue-specific genes using the "custom bait feature" in 5 of the gene expression data sets from the AtGenExpress Consortium, from our in-house database or from NASCArrays, or several other data sets.

Expression Browser for performing electronic northerns.

Arabidopsis Interactions Viewer for querying a database of almost 80,000 predicted and 28,566 documented protein-protein interactions in Arabidopsis.

Promomer for identifying over-represented n-mer words in the promoter of a gene of interest, or in promoters of co-expressed genes.

ePlant: A suite of interactive web-based tools that enables users to explore Arabidopsis data from the kilometre to nanometre scale, including natural variation data, organ and cell-type-specific gene expression patterns, subcellular localization, protein-protein interactions, and protein tertiary structures predicted for ~70% of the proteome.

Next-Gen Mapping: Allows for the rapid localization of recessive EMS induced mutations within an F2 mapping population that has been pooled and sequenced en masse using a next-generation sequencing platform.


Funding: The BAR is funded in part by Centre for the Analysis of Genome Evolution and Function, grants from the Canada Foundation for Innovation to NJP, and from Genome Canada to the Arabidopsis Research Group at the Department of Cell and Systems Biology, University of Toronto.


For more information please contact: Nick Provart (nicholas.provart@utoronto.ca)


Legume Information System

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See the Legume Information System page (http://legumeinfo.org).

The mission of the Legume Information System (LIS) is to facilitate basic research and its application to crop improvement in the legumes, which are critical components of global food and agriculture systems. LIS in 2017 includes:

  • Genome browsers for a dozen legume species (currently): common bean, pigeonpea, chickpea, Medicago truncatula, Lotus japonicus, narrow-leafed lupin, mungbean, adzuki bean, red clover, soybean (via SoyBase.org) and wild peanut species Arachis duranensis and Arachis ipaensis (via PeanutBase.org). These are interlinked via precomputed synteny between each browser.
  • Diverse search methods: Search by sequence (BLAST or BLAT), or by keyword, and see results against any sequenced genome. Or search in the map and trait database for QTLs, markers, traits, publications, etc.
  • Gene families: Genes from Medicago, Lotus, chickpea, common bean, pigeonpea, mungbean, soybean, and wild peanut have been placed into ~18,500 gene families – based on and linked to Phytozome gene families.
  • Functional annotations of predicted genes and domains.
  • Tools for searching and exploring germplasm, including an interactive viewer of GRIN records across global maps.
  • Multi-species synteny views using a genome “context viewer” showing genes by gene family from corresponding genomic regions.
  • Integrated QTLs: QTLs from many studies (so far in common bean and peanut) have been collected and integrated into a common database, and projected onto composite genetic maps (in CMap) when possible. Templates for collecting this data are available. Contact us if you would like your data included!

Funding: LIS is funded by the USDA-ARS, and is developed and maintained jointly by the National Center for Genome Resources (NCGR) and the USDA-ARS at Ames, Iowa.



Legume Federation

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See the Legume Federation page (http://legumefederation.org).

The "Legume Federation" (http://legumefederation.org) is an NSF project to foster data standards, distributed development, and comparative analysis, via gene families and shared phenotypes, to support research across the legume family – and to support robust agriculture for a world that is significantly legume-fed.

Participating Genomic Data Portals (GDPs) currently include, but are not limited to MedicagoGenome (http://medicagogenome.org), SoyBase (http://soybase.org), PeanutBase (http://peanutbase.org), the Legume Information System (http://legumeinfo.org), Climate Resilient Chickpea Lab (http://chickpealab.ucdavis.edu), Alfalfa Genomics Network (http://www.alfalfa-genome.org), Medicago Hapmap project (http://www.medicagohapmap.org), KnowPulse (http://knowpulse.usask.ca), and the Cool Season Food Legume Database (http://www.coolseasonfoodlegume.org). The project also has integral participation by iPlant.

The goals of the Legume Federation include

   1) sharing knowledge, development, and data sets across all legume crops;
   2) defining standards for data formats, metadata standards, Web service protocols, and ontology use;
   3) establishing an open repository for data exchange; and
   4) encouraging the use of common, open-source model organism database tools. 

Clear standards and formats, with templates and tools for data collection and submission, will enable broader participation. Although a major focus of the project is on methods for distributed development, we emphasize that the fundamental mission is to enable improved agricultural productivity for this important group of crop plants by integrating genetic, genomic, and phenotypic data across species to enable identification of common molecular bases for important traits.

Funding: The Legume Federation project is funded by NSF, award #1444806, "Federated Plant Database Initiative for the Legumes," and in-kind support from USDA-ARS #5030-21000-062-00D.


SoyBase

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SoyBase, the USDA-ARS soybean genetics and genomics database, provides a comprehensive collection of data, analysis tools and links to external resources of interest to soybean researchers. SoyBase is an actively curated database, with new data regularly being incorporated.The data in SoyBase are provided through intuitive interfaces, and are linked together wherever possible to allow easy identification and browsing of related subjects. The SoyBase home page (http://soybase.org) contains the SoyBase Toolbox, which provides quick access to a search of SoyBase, access to the data download page, a genome sequence BLAST tool, direct links to the genetic and sequence maps, and quick access to the SoyCyc metabolic pathways database. Searching at SoyBase uses an underlying trait-based approach to return all information that is related to the search term. An extensive navigation menu and site description provides facile access to all sections of SoyBase. Numerous data types are available including genetic maps, the soybean reference genome sequence with annotation tracks covering genetic markers, genome organization, gene annotation and expression, and gene knockout mutants. SoyBase includes an extensive RNA-Seq gene atlas and innovative tools for identifying fast neutron-induced mutants affecting genes or which affect traits of interest. Several “omics” tools, for example a GO Term Enrichment tool, enable sophisticated queries and reports on lists of genes.


Planteome Project

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See the Planteome web page for more information: http://planteome.org/


The Planteome project (www.planteome.org), an international collaborative effort, is a centralized online plant informatics portal where common reference ontologies (structured, controlled vocabularies) for plants are used to annotate gene expression, traits, phenotypes, genomes, and genetic diversity, across a wide range of plant taxa. The species-neutral reference ontologies are mapped to species-specific controlled vocabularies to facilitate annotation of crop plant traits and phenotypes.

In addition, the current release includes for the first time, four species-specific trait ontologies for wheat, rice, lentil and cassava, developed by the Crop Ontology (www.cropontology.org), a project of the CGIAR. These species-specific ontologies have been mapped to the relevant reference Trait Ontology terms for data integration.

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In the current release, the Planteome database includes 67,272 ontology terms with links to approximately 1.9 million (M) bioentities (data objects) including proteins, genes, RNA transcripts and gene models, germplasm, and QTLs. Bioentities were often annotated to more than one ontology term, resulting in approximately 17.2M annotations. Annotated data was sourced from 24 unique database resources and covers 86 different plant taxa. Functional GO annotations are available for 62 species, which, for many of these species, the Planteome is a unique annotation resource.

You can view or download a brochure about Planteome Project here: http://planteome.org/documents

The Planteome browser can also be accessed by visiting our mirror site at CyVerse: http://draco.cyverse.org/amigo


For more information please contact: Planteome Feedback

The Planteome Project (www.planteome.org) is funded by the National Science Foundation (NSF Award #1340112), and is accessible for use from the Planteome project website.



T3 - The Triticaceae Toolbox - Wheat, Barley & Oat

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The Triticeae Toolbox is a data repository for phenotype and genotype data to be analyzed by association mapping and genomic selection. In addition it provides some software tools for doing these analyses and for exploring the data. The data source for T3 Wheat and T3 Barley is the five-year, 50-Principal-Investigator Triticeae CAP project funded by USDA. The T3 software and database schema are open-source and are being adopted by other research projects and other crops. T3 Oat, a repository for the global oat genetics and breeding community, is one of these spinoffs.


Animal QTLdb

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The Animal Quantitative Trait Loci (QTL) Database (Animal QTLdb) strives to collect all publicly available trait mapping data, i.e. QTL (phenotype/expression, eQTL), candidate gene and association data (GWAS), and copy number variations (CNV) mapped to livestock animal genomes, in order to facilitate locating and comparing discoveries within and between species. New data and database tools are continually developed to align various trait mapping data to map-based genome features such as annotated genes. Many scientific journals require or recommend that any original QTL/association data be deposited into a public database before a paper may be accepted for publication. We provide user/curator accounts for direct data submission and supply users with a data summary link to facilitate the manuscript review process. The QTL/association data are freely accessible via online browser, download, and built-in visualization tools. In addition, the data is also ported for map viewing in GBrowse and JBrowse on AnimalGenome.org, and at NCBI, Ensembl, and UCSC using their respective web tools.

Currently, QTL/association data from the following species have been curated into the database:

  • Cattle
  • Chicken
  • Horse
  • Pig
  • Rainbow trout
  • Sheep

Work is underway to add catfish QTL/association data.

Related projects include but are not limited to:

  • Vertebrate Trait Ontology (VT)
  • Livestock Product Trait Ontology (LPT)
  • Clinical Measurement Ontology (CMO)
  • Livestock Breed Ontology (LBO)
  • Virtual Comparative Map (VCmap)

Each of these projects is closely associated with, and co-developed with, the Animal QTLdb. While they provide enhanced functionality for QTLdb, each has a wider range of applications as well.

See [2] for more information or find us at the PAG Booth #504 (Jim Reecy and Zhiliang Hu from our team are on this PAG meeting). Please feel free to talk to one of us on things you are interested).


Bovine Genome Database (BGD)

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The Bovine Genome Database (BGD, http://BovineGenome.org) provides data mining, genome navigation and annotation tools for the bovine genome. BGD catalogues genome features, including protein-coding and non-coding RNA genes from RefSeq, Ensembl and the bovine Official Gene Set version 2 (OGSv2), pseudogenes, repetitive elements, single nucleotide polymorphisms (SNP), and quantitative trait loci (QTL). Genome viewing and annotation tools are based on JBrowse and Apollo. BGD also includes BovineMine, which is based on the InterMine data warehousing system. It integrates BGD data with external sources of orthology, gene ontology, gene interaction and pathway information. BovineMine provides powerful query building tools, as well as customized query templates, and allows users to analyze and download genome-wide datasets. BovineMine allows researchers to use orthology to leverage the curated gene pathways of model organisms, such as human, mouse and rat.



Acknowledgements

The Outreach Booth was made possible thanks to volunteer organizers:

  • Marcela Karey Tello-Ruiz, Gramene (Cold Spring Harbor Laboratory)
  • Jack Gardiner, MaizeGDB (University of Missouri)