MIPS PlantsDB: a database framework forcomparative plant genome researchThomas Nussbaumer, Mihaela M. Martis, Stephan K. Roessner, Matthias Pfeifer,

Kai C. Bader, Sapna Sharma, Heidrun Gundlach and Manuel Spannagl*

Munich Information Center for Protein Sequences/Institute of Bioinformatics and Systems Biology, HelmholtzCenter Munich—German Research Center for Environmental Health, 85764 Neuherberg, Germany

Received September 15, 2012; Revised October 24, 2012; Accepted October 25, 2012

ABSTRACT

The rapidly increasing amount of plant genome(sequence) data enables powerful comparativeanalyses and integrative approaches and alsorequires structured and comprehensive informationresources. Databases are needed for both modeland crop plant organisms and both intuitivesearch/browse views and comparative genomicstools should communicate the data to researchersand help them interpret it. MIPS PlantsDB (http://mips.helmholtz-muenchen.de/plant/genomes.jsp)was initially described in NAR in 2007 [Spannagl,M.,Noubibou,O., Haase,D., Yang,L., Gundlach,H.,Hindemitt, T., Klee,K., Haberer,G., Schoof,H. andMayer,K.F. (2007) MIPSPlantsDB–plant databaseresource for integrative and comparative plantgenome research. Nucleic Acids Res., 35, D834–D840] and was set up from the start to providedata and information resources for individual plantspecies as well as a framework for integrativeand comparative plant genome research. PlantsDBcomprises database instances for tomato,Medicago, Arabidopsis, Brachypodium, Sorghum,maize, rice, barley and wheat. Building up on that,state-of-the-art comparative genomics tools suchas CrowsNest are integrated to visualize and inves-tigate syntenic relationships between monocotgenomes. Results from novel genome analysisstrategies targeting the complex and repetitivegenomes of triticeae species (wheat and barley)are provided and cross-linked with model species.The MIPS Repeat Element Database (mips-REdat)and Catalog (mips-REcat) as well as tight connec-tions to other databases, e.g. via web services, arefurther important components of PlantsDB.

INTRODUCTION

Sequencing of plant genomes has made a dramaticprogress. With new high-volume data becoming availablein ever shorter time periods, the challenges of data selec-tion, integration, analysis and representation are themajor driving forces for plant genome databases. Theavailability of plant genome sequence data from a widerange of taxa has shown to be extremely helpful in an-swering biological questions by comparative analyses(1,2). There is a need not only to store and provide bothraw data and analyses results in informative and compre-hensive structures but also to assist researches in exploringand analyzing data in up-to-date bioinformatic tools.MIPS PlantsDB is a plant database framework focusingon different core areas in plant genome research.Individual organism databases are provided for many im-portant crop and model plants and new organisms anddata are integrated in close collaboration with sequencingprojects and plant infrastructure initiatives. Beyond indi-vidual genome databases, PlantsDB resources help toaddress specific questions in comparative and integrativeplant genomics by providing tools to visualize synteny,transfer data from model systems to crops and exploresimilarities and peculiarities of different plant species.Repeat catalogs and classification systems for all plantspecies are further vital elements of PlantsDB.

MIPS PlantsDB is a member resource in the EuropeanUnion-funded transPLANT initiative, a project aimed toenhance the inter-connectivity of distributed plant genomeresources and databases within Europe and internation-ally and to support the development of plant genome re-sources as well as common standards. In this context,PlantsDB resources are complemented by BioMOBY (3)based web services that support seamless navigation andcombination of services provided by PlantsDB andpartner databases worldwide.

MIPS PlantsDB can be accessed at http://mips.helmholtz-muenchen.de/plant/genomes.jsp.

*To whom correspondence should be addressed. Tel: +49 89 3187 3581; Fax: +49 89 3187 3585; Email: manuel.spannagl@helmholtz-muenchen.de

The authors wish it to be known that, in their opinion, the first three authors should be regarded as joint First Authors.

D1144–D1151 Nucleic Acids Research, 2013, Vol. 41, Database issue Published online 29 November 2012doi:10.1093/nar/gks1153

� The Author(s) 2012. Published by Oxford University Press.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/3.0/), whichpermits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contactjournals.permissions@oup.com.

PLANTSDB—PLANT REFERENCE GENOMEDATABASES

Starting with Arabidopsis thaliana, individual plantorganism and reference databases have a long history inPlantsDB (4). Reference databases for both individualmodel and crop plant species provide researchers withhigh-quality structured and integrated data and supportnot only species-centric research but also facilitate com-parative studies and knowledge transfer if embedded in acomparative analysis framework. MIPS PlantsDB hoststhe European reference genome databases for the legumemodel organism Medicago truncatula (1), Solanumlycopersicum [tomato; (2)] and Hordeum vulgare [barley;(5)]. In close collaboration with international consortiaand the European Union Framework 6/7 programsGrainLegumes, EUSOL and TriticeaeGenome, allgenomic data generated are/were being integrated intothe respective PlantsDB organism instances and presentedto the research communities in structured formats andthrough different interfaces. In case of Medicago,tomato and barley, PlantsDB also serves as a centraldata integration hub for the structural and functionalgene annotation with active and ongoing involvement inmany aspects of the genome analysis, annotation curationand data management. PlantsDB also incorporates anumber of additional important organism databasessuch as A. thaliana, Oryza sativa (rice), Brachypodiumdistachyon, Sorghum bicolor and Zea mays (maize). Datatypes available from the individual PlantsDB organisminstances are summarized in Table 1.

MIPS PlantsDB individual organism databases areupdated regularly, e.g. if new/updated external datareleases become available or if substantial new data aregenerated or integrated through in-house analyses orwithin collaborations.

PLANTSDB—TRITICEAE INSTANCES

The family of triticeae plants includes many agronomicalimportant species such as wheat, barley and rye but their

genomes tend to be highly complex and repetitive. Wheatfor instance is allo-hexaploid with a genome size of�17Gb and barley has a genome size of �5.1Gb (6).As a result, assemblies of whole-genome sequences of

these important crop plants are extremely challengingeven with improved algorithms and the latest sequencingtechnology. Lately, new strategies have been developedand applied to disclose the gene content of wheat andbarley even in the presence of highly repetitive genomesequences (5,7).For wheat, a 5� coverage 454 sequence of bread wheat

(Chinese Spring line) was generated in UK (7). A LowCopy-number Genome assembly (LCG) was constructedby filtering out repetitive sequences and assembling the re-maining low-copy sequences de novo. To avoid the collapsingof highly similar gene sequences from the three wheatsub-genomes, a set of orthologous representative grassgenes incorporating genes from B. distachyon, S. bicolor,O. sativa andH. vulgare was generated in the first place.Wheat raw reads were mapped and assembled on each

Orthologous Group (OG) representative using stringentparameters, resulting in a large set of genic wheatsub-assemblies. Along with their linked OG representa-tive, these genic wheat sub-assemblies will provide ahelpful data foundation for researchers and breeders.We therefore developed a wheat PlantsDB instance

where both raw and processed data are available via intui-tive search and download interfaces. http://mips.helmholtz-muenchen.de/plant/wheat/uk454survey/index.jsp gives access to homologous genic wheat sub-assemblysequences for any given gene identifier from the establishedgrass reference organisms Brachypodium, Sorghum, riceand barley (as far as the gene is part of the initial clusteringand associated with wheat sequences). A dedicated BLASTserver allows users to search the orthologous representativegrass gene set for any given query sequence. A FTPdownload server gives access to bulk download files.A complimentary data resource is available from http://

www.cerealsdb.uk.net/ (8) where e.g. SNPs derived fromthe UK wheat 454 sequences can be queried.

Table 1. MIPS PlantsDB database instances and resources summary

MIPS PlantsDBinstance

Speciescommonname

Species scientificname

Genomesequence?

Geneannotations?

PlantsDB URLadd-on

Release/version Tools available

MAtDB Thale cress Arabidopsis thaliana Yes Yes . . ./athal/index.jsp TAIR10 GBr, OGTomDB Tomato Solanum lycopersicum Yes Yes . . ./tomato/index.jsp ITAG V2.40 GBr, OG, CrNb

UrMeLDB Barrel medic Medicago truncatula Yes Yes . . ./medi3/index.jsp IMGAG Mt3.5v4 GBr, OGMOsDB Rice Oryza sativa Yes Yes . . ./rice/index.jsp MSU6.1, RAP2 CrN, GBr, GZ, OGMIPS Brachypodium

DBPurple false

bromeBrachypodium

distachyonYes Yes . . ./brachypodium/

index.jspvl.2 CrN, GBr, GZ, OG

MIPS Sorghum DB Sweet sorghum Sorghum bicolor Yes Yes . . ./sorghum/index.jsp vl.4 CrN, GBr, GZ, OGMIPS triticeae DB Wheat, barley Triticum aestivum,

Hordeum vulgareYesa Yesa . . ./triticeae/index.jsp misc. CrN, GBr, GZ, OG

MGSP Maize Zea mays Yes Yes . . ./maize/index.jsp v5b.60 GBr, OG, CrNb

This table gives an overview about both species and genome resources stored in MIPS PlantsDB at this time.aWheat and barley genome sequence consists of sequence reads and partially assembled sequences. Gene annotations are also incomplete.bIn preparation.Tools abbreviations: GBr, GBrowse instance available, sometimes hosted by external partner; CrN, species computed in CrowsNest; GZ, speciesincluded in GenomeZipper analyses; OG, pre-computed orthologous groups available.MIPS PlantsDB URL: http://mips.helmholtz-muenchen.de/plant+add-on.

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Although direct assembly of triticeae sequences isusually hampered by its repetitiveness, many grassgenomes share a conserved gene order over largeportions of their chromosomes (synteny) (9,10).The GenomeZipper concept uses a novel approach that

incorporates chromosome sorting, second-generationsequencing, array hybridization and systematic exploit-ation of conserved synteny with model grasses (11,12).Recently, this strategy allowed to assign 86% of theestimated 32 000 barley genes to individual chromo-some arms. A series of bioinformatically constructed‘zippers’ integrated gene indices of rice, Sorghum andBrachypodium in a conserved synteny model andassembled 21 766 barley genes in a putative linear order.As a result, the GenomeZipper provides an ordered,information-rich scaffold of the barley genome whichcan be queried by any anchored gene model from one ofthe grass model organisms (Brachypodium, Sorghum and

rice). To assist this task, MIPS PlantsDB provides fullaccess to both the barley GenomeZipper results and rawdata through search and browse interfaces (http://mips.helmholtz-muenchen.de/plant/barley/gz/index.jsp).Figure 1 shows a screenshot of a specific chromosomeregion on the barley GenomeZipper.

In the lines of the barley zipper, a GenomeZipper forthe wheat genome is currently constructed within IWGSC(http://www.wheatgenome.org/) and will be available withthe same functionality soon.

Another triticeae data resource within PlantsDB com-plements the GenomeZipper for barley. We integratedseveral barley genetic maps with a physical map derivedfrom high information content fingerprinting of 650 000BAC sequences. A total of 570 000 (13� genomecoverage) high-quality fingerprints were selected andentered the de novo contig assembly with FPC v9.0 (5).The resulting FPcontig map ‘fpc_10’ (9435 contigs,

Figure 1. Barley GenomeZipper in MIPS PlantsDB. This figure shows a region on barley chromosome 1H, constructed with the GenomeZipperconcept. Detailed information and sequence download for anchored barley markers as well as ‘zipped’ reference organism genes, barley fl-cDNAs,ESTs and sequence reads can be obtained by clicking the individual links.

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507 688 BAC clones) is currently displayed in a dedicatedPlantsDB Gbrowse instance and positionally anchoredFPcontigs are visualized within the CrowsNest tool(http://mips.helmholtz-muenchen.de/plant/barley/fpc/index.jsp). Figure 2 shows a screenshot of a barleyFPcontig visualized within the CrowsNest tool.

PLANTSDB—COMPARATIVE GENOMICS TOOLS

Today more than ever the availability of intuitive com-parative genome mapping and visualization tools is keyto effectively address evolutionary questions, to transferknowledge from a model plant to another genome ofinterest and to anchor unfinished genomes in the courseof assembly.

Many tasks are automated processes in this area, butsome steps still require human interpretation and direc-tion. Visualization of inter- and intra-genome relation-ships, often over multiple scales, is critically importantfor these goals and also a key challenge because of thedifficulty of the graphical representation. In addition,diverse sources and different techniques of generatedgenomics data need to be taken into account. For thesereasons, a variety of highly specialized visualization toolshave been developed so far (13–21). Some of these toolsfocus more on whole-genome alignment and synteny andothers more on comparative analysis data displayed infeature tracks using either web-based or stand-aloneapproaches.

In recent years, a variety of strategies have beenexplored for graphically representing synteny at awhole-genome scale as well as at the chromosome level.

Whole-genome views are usually graphically depictedusing one of the following methods: (i) the historicallywell-known 2D ‘dot plot’, (ii) pill-shaped ideograms ofreference genome chromosomes, banded and color-codedto indicate regions of synteny to a target genome and (iii)circular representation of reference genome chromosomesas arcs in a circle depicting aligned regions either ascolor-coded arcs in outer circles or as lines across themiddle of the circle.CrowsNest, a whole-genome interactive comparative

mapping and visualization tool comparing genetic,physical and hierarchical (fingerprinted contigs) maps inthe plant kingdom, builds on top of MIPS PlantsDB. Thecomparative map viewer is a web-based communityresource and is integrated into the PlantsDB comparativegenome framework. CrowsNest is specifically designed tovisualize synteny at macro and micro levels. It allowsto intuitively explore rearrangements, inversions, deletionsat different resolutions, to transfer knowledge aboutfunction and conservation between several plant speciesand to derive evolutionary information.CrowsNest can be accessed from the MIPS PlantsDB

start page or directly at http://mips.helmholtz-muenchen.de/plant/crowsNest/index.jsp. Gene reports from includedspecies provide direct links to the micro-syntenic views ofthe corresponding regions.

CrowsNest framework components, architecture andanalysis pipeline

CrowsNest consists of two main integrated parts: (i) theweb-based user interface with the integrated comparativevisualization tool and (ii) the comparative analysis

Figure 2. Visualization of the barley physical map in CrowsNest. A fingerprinted contig (FPC; example ‘contig_20’), consisting of overlapping BACclones. The different colors depict the anchoring evidence to one of the seven (14) barley chromosomes (chromosome arms). Gray-colored elementshave no attached chromosome (arm) information. The symbols represent the different anchoring datatypes: circle=BAC hybridization data to thechromosome arms, vertical rectangle=genetic markers, square flanking the ends of a BAC=BES (BAC end sequence).

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pipeline. Putative orthologs were calculated usingBLASTP between protein sequences of respectivegenomes. A sequence identity of at least 70% along witha hit length of at least 30 amino acids was required. Thebest bidirectional hits were extracted to avoid hits toparalogs and to cope with high sequence similaritiesamong genes of the same gene family (22). For Level 1and Level 3, gene pairs were grouped into syntenicsegments. A sliding window approach with genome-specific window and shift sizes was applied (1 or 5Mbfor window size, 20% of window size used as shift). Forparalogs, an increased sequence identity of >85% wasused. All CrowsNest applications are implemented inOO Perl using wherever possible Bioperl modules foranalysis purposes and the perl GD module for servingthe map viewer with advanced graphics.

Comparative map viewer

The design of the comparative map viewer was driven bythe idea to provide all three popular and well-establishedgraphical representation methods to explore whole-genome relationships in the context of annotations andthe alignment of unfinished and reference genomes.These three views are integrated into the top level viewcalled L1. Altogether, the viewer consists of four levels(L1–L4) of different resolution ranging from whole-genome representations at L1 to specific region(<0.5Mb) representations at L4. The navigational

design is based on a top–down approach. Exploration isusually started at genome level view L1 with the option to‘drill down’ from this macroscopic view to L2, thechromosome to whole-genome view, to L3, the chromo-some to chromosome view, and then to L4. The graphicalrepresentation changes between L3 and L4 from apill-shaped vertical to a pill-shaped horizontal one. InL4, the chromosomes being compared are ‘stacked’ oneach other and with each chromosome the image map isextended vertically. The viewer has been designed todisplay a variety of features as tracks, such as thesyntenic quality index, dN/dS ratio, repeat elements,gene family loci and others. Navigation between thelevels is enabled as data are available. An exampleoverview of the different view levels of CrowsNest isgiven in Figure 3.

CrowsNest currently harbors data from the model grassorganisms—B. distachyon, S. bicolor and O. sativa (rice)—as well as from the crop plant H. vulgare (barley).

Figure 3A–E shows a whole-genome visualization ofsynteny depicting different levels of conservation.Presented are global orthologous relationships betweenthe gene maps of B. distachyon and S. bicolor in Figure3A–C. More detailed structural information together withconservation quality is illustrated in Figure 3D and Eshowing synteny to two reference chromosomes with thehighest number of relationships to each of the targetgenome chromosomes. Switching to the pill-shaped

Figure 3. (A–F) CrowsNest visualization levels L1–L4. Different visualization levels of the CrowsNest tool for the reference grass organisms—B. distachyon and S. bicolor. The syntenic regions between the organisms can be browsed in a hierarchical way from macro-synteny (A–C) down tomicro-synteny views (F). Navigation between the levels is possible by interactively selecting regions of interest in the views (‘click zoom’) or using thenavigation bar.

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ideogram-like representation, regions of high conservationcan clearly be seen. In this view, it can be switchedbetween the orthologous view and the homology view,the latter indicating regions of duplication. The circularwhole-genome view can also be used to illustrate syntenyto multiple genomes.

Exploring conserved regions from macroscopic tomicroscopic views

All whole-genome views act as a starting point to exploresynteny in a more depth investigation. Figure 3A–C illus-trates the syntenic overview and let the investigator choosea chromosome of interest to navigate to the chromosomeversus whole-genome view L2. Depending on the macrostructure, a chromosome to chromosome relationship canbe chosen to be directed to L3. By zooming, the magnifi-cation can be increased sufficiently high to displaysmall-scale events of rearrangements, inversions and dele-tions. Breakpoints are derived easily at appropriate levelsof resolution or can be compared to computational resultsfrom other sources. Below a resolution of 0.5Mb, the levelchanges to L4 (example in Figure 3F) in which furtherzooming can be done and the elements are clickable fordisplaying feature/gene details stored in MIPS PlantsDB.Thus, CrowsNest allows seamless navigation and com-parison from whole-genome views down to individualregions of interest and genetic elements located in theseregions are directly linked to element entries and informa-tion in PlantsDB.

Exploring orthologous gene families—from model tocrop genes

Complementing the more synteny-driven CrowsNest tool,MIPS PlantsDB also hosts a component for orthologousgene family construction and its comparative analysis.Orthologous gene families were computed for manyPlantsDB species (including Brachypodium, rice, barley,Sorghum, maize and Arabidopsis) using OrthoMCL (23).In a first step, pairwise sequence similarities between allinput protein sequences were calculated using BLASTPwith an e-value cut-off of 1� 10�5. Markov clustering ofthe resulting similarity matrix was used to define theortholog cluster structure, using an inflation value (�I)of 1.5 (OrthoMCL default). The results of thisorthologous gene family constructions can be accessedfrom every individual gene family report (such as fromthe gene report of a specific Brachypodium orArabidopsis gene of interest) where cross-references to allother genes in the same family are provided. Using thisinformation (the gene identifiers in the orthologous genefamily), corresponding orthologous genic sequences frombread wheat can be derived from PlantsDB using the pro-cedure outlined in the triticeae section. The sameworkflow can also be applied other way around, e.g.starting from an unknown wheat sequence. Thissequence can be searched against the wheat genic se-quences and the OG representatives (see ‘triticeae’section for details), positively resulting in a grass referencegene model and its associated wheat orthologous genicsequences. This grass reference gene model can then be

searched in PlantsDB and its gene report gives fullaccess to the containing orthologous gene family andclosely related grass genes.

MIPS REPEAT ELEMENT DATABASE (mips-REdat)AND CATALOG (mips-REcat)

Plant genomes are crowded by taxon-specific mobile elem-ents and their deteriorated remnants, with portionsbetween 20% and >90% of primarily LTR-retro-transposon insertions leading to complex and highly re-petitive structures (24). Transposons play mostly harmfuland sometimes long-term beneficial roles in evolutionaryprocesses (25). The interplay between proliferation andremoval of transposable elements greatly influencesgenome size and chromosomal architecture. Their prom-inent differential accumulations, even within closelyrelated species, pose intriguing questions about hostcontrol, transposon countermeasures and the conditionsdisturbing the balance.Our plant repeat database mips-REdat was set up in

conjunction with mips-REcat, a detailed hierarchicalrepeat classification catalog to facilitate a consistentcross-species comparative transposon annotation. Thisresource is both useful for characterizing and comparingthe transposon complements of different species orsequence sets as well as for repeat masking prior to geneannotation, to reduce computing time and to minimizeunwanted transposon-related gene calls. Initially,mips-REdat contained a compilation of publicly availableplant transposon sequences like Trep (http://wheat.pw.usda.gov/ITMI/Repeats/), TIGR repeats (26) orRepbase (27) and was rapidly filled up with up to now�37 000 de novo detected LTR-retrotransposon and�300 DNA transposon sequences from the genomespresented in MIPS PlantsDB. The REdat sequences arecharacterized by REcat keys (28), which in turn aremapped to the common transposon classifications of(29) and (30). The current public version mips-REdat_v9.0p consists of �42 000 non-redundant se-quences, which were clustered with �95% identity over�95% length coverage. They add up to �350 Mb, stemfrom 44 species and cover 20 different genera. The pub-lic release (ftp://ftpmips.helmholtz-muenchen.de/plants/REdat/) does not contain yet unpublished data or se-quences from Repbase and is subjected to regularupdates. REdat can also be accessed on our website withthe option to retrieve customized fasta files by repeat typeand taxonomy.

PLANTSDB—transPLANT

transPLANT (Trans-national Infrastructure for PlantGenomic Science) is an EU project bringing together 11institutions involved in plant data integration, manage-ment and analysis.One of the missions of transPLANT is to provide a

comprehensive set of computational and interactiveservices to the plant research community by developingdistributed but tightly connected resources.

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MIPS PlantsDB is part of that consortium and respon-sible for creating and maintaining a registry of importantsequence-based resources for species of agricultural andeconomic importance as well as model systems.We collected repository data for publicly available

plant genome database systems maintained by bothtransPLANT and non-transPLANT partners.A total of 187 distinct plant genome resources are

registered at the transPLANT data registry at this time.The registry can be queried both at MIPS PlantsDB(http://mips.helmholtz-muenchen.de/plant/transplant/index.jsp) and at the official transPLANT web hub at EBI(http://transplantdb.eu/, synchronized with PlantsDBregularly) for e.g. keywords, species names and data types.Changes and updates to the registry can be performed

by database providers soon, lowering the maintaining costand ensuring expert-curated and -driven information.

CONCLUSIONS

Since initially described in NAR in 2007 (28), MIPSPlantsDB was significantly extended both in plantgenome data and retrieval and analysis functionality.The database framework integrates genome data fromboth model and crop plants and facilitates knowledgetransfer between them using state-of-the-art comparativegenomics tools such as CrowsNest and the GenomeZipperconcept. MIPS PlantsDB is closely connected to the barleyand wheat communities and provides access to the latestdata generated within. Since much of these data arecomplex, intuitive and step-by-step interfaces and com-parative genomics tools were developed and integrated.As data curation manpower is limited and thus plantgenomic data resources risk to erode for individual dataresources below a critical size, the transPLANT projectprovides infrastructure, knowledge and logical backboneto closely connect distributed plant genome resources inEurope and in conjunction with international partners.

ACKNOWLEDGEMENTS

The authors thank all our collaboration partners and datacontributors. For barley these include IPK (Nils Stein,Uwe Scholz), FLI (Matthias Platzer), JKI (FrankOrdon), James Hutton Institute (Robbie Waugh), IEB(Jaroslav Dolezel), University of Udine (MicheleMorgante), UCR (Tim Close), ACPFG (PeterLangridge) and many more. For wheat these include:Centre for Genome Research, University of Liverpool(Neil Hall, Anthony Hall, Rachel Brenchley), School ofBiological Sciences, University of Bristol (KeithJ. Edwards, Gary L.A. Barker), John Innes Centre(Michael W. Bevan) as well as IWGSC (InternationalWheat Genome Sequencing Consortium, KellyeEversole, Catherine Feuillet, INRA, Jane Rogers, JonWright and Mario Caccamo, TGAC, Norwich, UK) andmany more. The authors also thank SGN (sol genomicsnetwork, Lukas Mueller) and ITAG (InternationalTomato Annotation Group) for collaborating in thetomato project as well as JCVI (Chris Town), Nevin

Young and IMGAG (International Medicago GenomeAnnotation Group) for collaborating in the Medicagogenome project.

FUNDING

The European Commission (framework 6 programme)within the Grain Legumes Integrated Project (GLIP)and EU-SOL project; the framework 7 programme inthe TriticeaeGenome project and transPLANT project(funded by the European Commission within its 7thFramework Programme under the thematic area‘Infrastructures’, contract number 283496); the GermanMinistry for Education and Research (BMBF) withinthe GABI and Plant for the future projects TRITEXand BARLEX. Funding for open access charge:Helmholtz Association.

Conflict of interest statement. None declared.

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Nucleic Acids Research, 2013, Vol. 41, Database issue D1151