Gramene: A Resource for Comparative Grass Genomics

The rice genome is more than a resource for understanding the biology of a single species. It is a window into the structure and function of genes in other crop grasses as well. Using rice as the sequenced reference genome, researchers can identify and understand the relationships among genes, pathways and phenotypes in a wide range of grass species.Extensive work over the past two decades has shown remarkably consistent conservation of gene order within large segments of linkage groups in rice, maize, sorghum, barley, wheat, rye, sugarcane and other agriculturally important grasses. A substantial body of data supports the notion that the rice genome is substantially colinear at both large and short scales with other crop grasses, opening the possibility of using rice synteny relationships to rapidly isolate and characterize homologues in maize, wheat, barley and sorghum.

As an information resource, Gramene's purpose is to provide added value to data sets available within the public sector, which will facilitate researchers' ability to understand the rice genome and leverage the rice genomic sequence for identifying and understanding corresponding genes, pathways and phenotypes in other crop grasses. This is achieved by building automated and curated relationships between rice and other cereals for both sequence and biology. The automated and curated relationships are queried and displayed using controlled vocabularies and web-based displays. The controlled vocabularies (Ontologies), currently being utilized include Gene ontology, Plant ontology, Trait ontology, Environment ontology and Gramene Taxonomy ontology. The web-based displays for phenotypes include the Genes and Quantitative Trait Loci (QTL) modules. Sequence based relationships are displayed in the Genomes module using the genome browser adapted from Ensembl, in the Maps module using the comparative map viewer (CMap) from GMOD, and in the Proteins module displays. BLAST is used to search for similar sequences. Literature supporting all the above data is organized in the Literature database.

The technological core of Gramene is the MySQL database management system. We have developed a rational schema to represent the various biological entities of Gramene, and a middleware layer to dynamically translate this information into Web pages.

Funding

This work was initially supported (2001-2004) by the USDA Initiative for Future Agriculture and Food Systems (IFAFS) (grant no. 00-52100-9622) and a Cooperative State Research and Education Service (CSREES) agreement through the USDA Agricultural Research Service (grant no. 58-1907-0-041). For the years 2004-2007 this work was supported by the National Science Foundation (NSF) PGI grant award #0321685. Current work is being supported by the NSF Plant Genome Research Resource grant award #0703908.

Name

The name Gramene is a play on the name of the Grameen Bank which specializes in small loans to the poor (mostly women) in emerging economies.

Contact Information

Gramene list-serve

Lincoln Stein (PI)
Cold Spring Harbor Laboratory
lstein@cshl.edu

Susan McCouch (Co-PI)
Cornell University
srm4@cornell.edu

Edward Buckler (Co-PI)
Institute for Genomic Diversity, Cornell University
esb33@cornell.edu

Doreen Ware (Co-PI)
Cold Spring Harbor Laboratory
ware@cshl.edu

Pankaj Jaiswal (Co-PI)
Cornell University
pj37@cornell.edu

Other Personnel

Gramene Copyright Statement

Copyrights:

The purpose of Gramene is to work in collaboration with others on database software and planning, and to integrate contributions from researchers with publicly available genomic data to make a comprehensive cereal genomic and comparative resource available to the scientific community. The information and software used in the development and building of the Gramene database and web site is available from various sources within the public domain. Permission for reproduction has been given or implied by the researchers/institutes who contributed or published the original materials. However, there may be patents, copyrights or intellectual property rights associated with the original data, and users of the Gramene database contents are solely responsible for compliance with original restrictions and acknowledgement requirements when using original data.

Citing Gramene

Citing Gramene Data

The Gramene database is freely available for download and use as long as Gramene is cited as the source. This includes the tools available at Gramene including but not limited to RiceCyc, CMap Viewer, Gramene Mart and the Genome Browser. When using Gramene or the information derived from Gramene kindly acknowledge the Gramene project by citing the web address http://www.gramene.org/ and identifying the version of Gramene being used (identified on the Home page) and the date accessed.
For information on linking directly to particular data items, see this document.

Publications: Citing the Gramene Project:

When citing the Gramene project for other purposes, please refer to any one of the following papers:

Liang C, Jaiswal P, Hebbard C, Avraham S, Buckler ES, Casstevens T, Hurwitz B, McCouch S, Ni J, Pujar A, Ravenscroft D, Ren L, Spooner W, Tecle I, Thomason J, Tung CW, Wei X, Yap I, Youens-Clark K, Ware D, Stein L. Gramene: a growing plant comparative genomics resource. Nucleic Acids Research, 2007 Nov 4; [Epub ahead of print] PMID: 17984077 [PubMed - as supplied by publisher]. (Gramene Reference ID 11653)

Jaiswal P, Ni J, Yap I, Ware D, Spooner W, Youens-Clark K, Ren L, Liang C, Zhao W, Ratnapu K, Faga B, Canaran P, Fogleman M, Hebbard C, Avraham S, Schmidt S, Casstevens TM, Buckler ES, Stein L, McCouch S (2006)Gramene: a bird's eye view of cereal genomes. Nucleic Acids Research, 34: D717-723. (Gramene Reference ID 11021)

Ware D, Jaiswal P, Ni J, Pan X, Chang K, Clark K, Teytelman L, Schmidt S, Zhao W, Cartinhour S, McCouch S, Stein L (2002) Gramene: a resource for comparative grass genomics. Nucleic Acids Research, 30, 103-105. (Gramene Reference ID 6446)

Ware DH, Jaiswal P, Ni J, Yap IV, Pan X, Clark KY, Teytelman L, Schmidt SC, Zhao W, Chang K, Cartinhour S, Stein LD, McCouch SR (2002) Gramene, a tool for grass genomics. Plant Physiol 130: 1606-1613. (Gramene Reference ID 7071)

Citing Ontologies at Gramene:

Jaiswal P, Ware D, Ni J, Chang K, Zhao W, Schmidt S, Pan X, Clark K, Teytelman L, Cartinhour S, Stein L, McCouch S (2002) Gramene: development and integration of trait and gene ontologies for rice. Comparative and Functional Genomics 3: 132-136. (Gramene Reference ID 6902)

Yamazaki Y, Jaiswal P (2005) Biological ontologies in rice databases. An introduction to the activities in Gramene and Oryzabase. Plant Cell Physiol 46: 63-68. Epub 2005 Jan 2019. (Gramene Reference ID 9505)

Other Publications

Gramene: A Genomics and Genetics Resources for Maize.
Maize Genetics Cooperation Newsletter, Volume 80, 2006.
[Full article] or [PDF Newsletter, pp 99-107]

Gramene: A genomics and genetics resource for rice.
Rice Genetics Newsletter, 2005, Vol. 22, No. 1. 9-16.

*End Note users - Download Gramene Citations

Reporting Errors

Apart from our in-house and/or community wide quality measures that are in place, we request that users who notice inaccurate or missing data to please offer Feedback and inform us so that it can be corrected in a future version.

Employment Opportunities at Gramene

The following employment opportunities are available at Gramene:

Postdoctoral Fellow and Software developer positions in Comparative Genomics and Computational Biology

Cold Spring Harbor laboratory is seeking talented and motivated individuals for current and future job opening as postdoctoral fellows and software developers in the expanding bioinformatics program at Cold Spring Harbor Laboratory. An ideal candidate will have an interdisciplinary training with strong computational science background and biology knowledge. The successful candidates will develop a strong bioinformatics research program, collaborate with a diverse research community and contribute to an emerging community resource (www.gramene.org). Applicants should have a Ph.D. (or equivalent degree) in biology, bioinformatics, molecular biology, biochemistry, genetics, evolutionary or systematic biology, or related fields, and demonstrated experience in computer science and expertise in at least one scientific programming language and relational data management system. Experience in network analysis methods, and in the analysis of signaling processes and networks using engineering or applied mathematics approaches are strongly desired. Will consider M.S. with very good relevant experience. For more information on the projects please see the following links. .
https://www.fastlane.nsf.gov/servlet/showaward?award=0333074,
https://www.fastlane.nsf.gov/servlet/showaward?award=0321666,
https://www.fastlane.nsf.gov/servlet/showaward?award=0321467
Interested individuals should send or email curriculum vitae with names of three references and a brief description of previous experience and accomplishments to:
Doreen Ware, Ph.D., USDA ARS Research Scientist, Cold Spring Harbor Laboratory, 1 Bungtown Rd., Cold Spring Harbor, NY 11724, E-mail: ware@cshl.edu

For other job opportunities, please contact the PIs.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.