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Beier S, Himmelbach A, Colmsee C, Zhang XQ, Barrero RA, Zhang Q, Li L, Bayer M, Bolser D, Taudien S, Groth M, Felder M, Hastie A, Šimková H, Staňková H, Vrána J, Chan S, Muñoz-Amatriaín M, Ounit R, Wanamaker S, Schmutzer T, Aliyeva-Schnorr L, Grasso S, Tanskanen J, Sampath D, Heavens D, Cao S, Chapman B, Dai F, Han Y, Li H, Li X, Lin C, McCooke JK, Tan C, Wang S, Yin S, Zhou G, Poland JA, Bellgard MI, Houben A, Doležel J, Ayling S, Lonardi S, Langridge P, Muehlbauer GJ, Kersey P, Clark MD, Caccamo M, Schulman AH, Platzer M, Close TJ, Hansson M, Zhang G, Braumann I, Li C, Waugh R, Scholz U, Stein N, Mascher M. Construction of a map-based reference genome sequence for barley, Hordeum vulgare L. Sci Data 2017; 4:170044. [PMID: 28448065 PMCID: PMC5407242 DOI: 10.1038/sdata.2017.44] [Citation(s) in RCA: 105] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Accepted: 02/09/2017] [Indexed: 12/30/2022] Open
Abstract
Barley (Hordeum vulgare L.) is a cereal grass mainly used as animal fodder and raw material for the malting industry. The map-based reference genome sequence of barley cv. ‘Morex’ was constructed by the International Barley Genome Sequencing Consortium (IBSC) using hierarchical shotgun sequencing. Here, we report the experimental and computational procedures to (i) sequence and assemble more than 80,000 bacterial artificial chromosome (BAC) clones along the minimum tiling path of a genome-wide physical map, (ii) find and validate overlaps between adjacent BACs, (iii) construct 4,265 non-redundant sequence scaffolds representing clusters of overlapping BACs, and (iv) order and orient these BAC clusters along the seven barley chromosomes using positional information provided by dense genetic maps, an optical map and chromosome conformation capture sequencing (Hi-C). Integrative access to these sequence and mapping resources is provided by the barley genome explorer (BARLEX).
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Affiliation(s)
- Sebastian Beier
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Seeland, Germany
| | - Axel Himmelbach
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Seeland, Germany
| | - Christian Colmsee
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Seeland, Germany
| | - Xiao-Qi Zhang
- School of Veterinary and Life Sciences, Murdoch University, Murdoch, Western Australia 6150, Australia
| | - Roberto A Barrero
- Centre for Comparative Genomics, Murdoch University, Murdoch, Western Australia 6150, Australia
| | - Qisen Zhang
- Australian Export Grains Innovation Centre, South Perth, Western Australia 6151, Australia
| | - Lin Li
- Department of Agronomy and Plant Genetics, University of Minnesota, St Paul, Minnesota 55108, USA
| | - Micha Bayer
- The James Hutton Institute, Dundee DD2 5DA, UK
| | - Daniel Bolser
- European Molecular Biology Laboratory-The European Bioinformatics Institute, Hinxton CB10 1SD, UK
| | - Stefan Taudien
- Leibniz Institute on Aging-Fritz Lipmann Institute (FLI), 07745 Jena, Germany
| | - Marco Groth
- Leibniz Institute on Aging-Fritz Lipmann Institute (FLI), 07745 Jena, Germany
| | - Marius Felder
- Leibniz Institute on Aging-Fritz Lipmann Institute (FLI), 07745 Jena, Germany
| | - Alex Hastie
- BioNano Genomics Inc., San Diego, California 92121, USA
| | - Hana Šimková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, 78371 Olomouc, Czech Republic
| | - Helena Staňková
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, 78371 Olomouc, Czech Republic
| | - Jan Vrána
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, 78371 Olomouc, Czech Republic
| | - Saki Chan
- BioNano Genomics Inc., San Diego, California 92121, USA
| | - María Muñoz-Amatriaín
- Department of Botany &Plant Sciences, University of California, Riverside, Riverside, California 92521, USA
| | - Rachid Ounit
- Department of Computer Science and Engineering, University of California, Riverside, Riverside, California 92521, USA
| | - Steve Wanamaker
- Department of Botany &Plant Sciences, University of California, Riverside, Riverside, California 92521, USA
| | - Thomas Schmutzer
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Seeland, Germany
| | - Lala Aliyeva-Schnorr
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Seeland, Germany
| | - Stefano Grasso
- Department of Agricultural and Environmental Sciences, University of Udine, 33100 Udine, Italy
| | - Jaakko Tanskanen
- Green Technology, Natural Resources Institute (Luke), Viikki Plant Science Centre, and Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland
| | | | | | - Sujie Cao
- BGI-Shenzhen, Shenzhen 518083, China
| | - Brett Chapman
- Centre for Comparative Genomics, Murdoch University, Murdoch, Western Australia 6150, Australia
| | - Fei Dai
- College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Yong Han
- College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Hua Li
- BGI-Shenzhen, Shenzhen 518083, China
| | - Xuan Li
- BGI-Shenzhen, Shenzhen 518083, China
| | | | - John K McCooke
- Centre for Comparative Genomics, Murdoch University, Murdoch, Western Australia 6150, Australia
| | - Cong Tan
- Centre for Comparative Genomics, Murdoch University, Murdoch, Western Australia 6150, Australia
| | | | - Shuya Yin
- College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Gaofeng Zhou
- School of Veterinary and Life Sciences, Murdoch University, Murdoch, Western Australia 6150, Australia
| | - Jesse A Poland
- Kansas State University, Wheat Genetics Resource Center, Department of Plant Pathology and Department of Agronomy, Manhattan, Kansas 66506, USA
| | - Matthew I Bellgard
- Centre for Comparative Genomics, Murdoch University, Murdoch, Western Australia 6150, Australia
| | - Andreas Houben
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Seeland, Germany
| | - Jaroslav Doležel
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, 78371 Olomouc, Czech Republic
| | | | - Stefano Lonardi
- Department of Computer Science and Engineering, University of California, Riverside, Riverside, California 92521, USA
| | - Peter Langridge
- School of Agriculture, University of Adelaide, Urrbrae, South Australia 5064, Australia
| | - Gary J Muehlbauer
- Department of Agronomy and Plant Genetics, University of Minnesota, St Paul, Minnesota 55108, USA.,Department of Plant and Microbial Biology, University of Minnesota, St Paul, Minnesota 55108, USA
| | - Paul Kersey
- European Molecular Biology Laboratory-The European Bioinformatics Institute, Hinxton CB10 1SD, UK
| | - Matthew D Clark
- Earlham Institute, Norwich NR4 7UH, UK.,School of Environmental Sciences, University of East Anglia, Norwich NR4 7UH, UK
| | - Mario Caccamo
- Earlham Institute, Norwich NR4 7UH, UK.,National Institute of Agricultural Botany, Cambridge CB3 0LE, UK
| | - Alan H Schulman
- Green Technology, Natural Resources Institute (Luke), Viikki Plant Science Centre, and Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland
| | - Matthias Platzer
- Leibniz Institute on Aging-Fritz Lipmann Institute (FLI), 07745 Jena, Germany
| | - Timothy J Close
- Department of Botany &Plant Sciences, University of California, Riverside, Riverside, California 92521, USA
| | - Mats Hansson
- Department of Biology, Lund University, 22362 Lund, Sweden
| | - Guoping Zhang
- College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Ilka Braumann
- Carlsberg Research Laboratory, 1799 Copenhagen, Denmark
| | - Chengdao Li
- School of Veterinary and Life Sciences, Murdoch University, Murdoch, Western Australia 6150, Australia.,Department of Agriculture and Food, Government of Western Australia, South Perth, Western Australia 6150, Australia.,Hubei Collaborative Innovation Centre for Grain Industry, Yangtze University, Jingzhou, Hubei 434025, China
| | - Robbie Waugh
- The James Hutton Institute, Dundee DD2 5DA, UK.,School of Life Sciences, University of Dundee, Dundee DD2 5DA, UK
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Seeland, Germany
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Seeland, Germany.,School of Plant Biology, University of Western Australia, Crawley 6009, Australia
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Seeland, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany
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Mascher M, Gundlach H, Himmelbach A, Beier S, Twardziok SO, Wicker T, Radchuk V, Dockter C, Hedley PE, Russell J, Bayer M, Ramsay L, Liu H, Haberer G, Zhang XQ, Zhang Q, Barrero RA, Li L, Taudien S, Groth M, Felder M, Hastie A, Šimková H, Staňková H, Vrána J, Chan S, Muñoz-Amatriaín M, Ounit R, Wanamaker S, Bolser D, Colmsee C, Schmutzer T, Aliyeva-Schnorr L, Grasso S, Tanskanen J, Chailyan A, Sampath D, Heavens D, Clissold L, Cao S, Chapman B, Dai F, Han Y, Li H, Li X, Lin C, McCooke JK, Tan C, Wang P, Wang S, Yin S, Zhou G, Poland JA, Bellgard MI, Borisjuk L, Houben A, Doležel J, Ayling S, Lonardi S, Kersey P, Langridge P, Muehlbauer GJ, Clark MD, Caccamo M, Schulman AH, Mayer KFX, Platzer M, Close TJ, Scholz U, Hansson M, Zhang G, Braumann I, Spannagl M, Li C, Waugh R, Stein N. A chromosome conformation capture ordered sequence of the barley genome. Nature 2017; 544:427-433. [DOI: 10.1038/nature22043] [Citation(s) in RCA: 966] [Impact Index Per Article: 138.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Accepted: 03/03/2017] [Indexed: 02/06/2023]
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Spannagl M, Alaux M, Lange M, Bolser DM, Bader KC, Letellier T, Kimmel E, Flores R, Pommier C, Kerhornou A, Walts B, Nussbaumer T, Grabmuller C, Chen J, Colmsee C, Beier S, Mascher M, Schmutzer T, Arend D, Thanki A, Ramirez-Gonzalez R, Ayling M, Ayling S, Caccamo M, Mayer KFX, Scholz U, Steinbach D, Quesneville H, Kersey PJ. transPLANT Resources for Triticeae Genomic Data. Plant Genome 2016; 9. [PMID: 27898761 DOI: 10.3835/plantgenome2015.06.0038] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
The genome sequences of many important Triticeae species, including bread wheat ( L.) and barley ( L.), remained uncharacterized for a long time because their high repeat content, large sizes, and polyploidy. As a result of improvements in sequencing technologies and novel analyses strategies, several of these have recently been deciphered. These efforts have generated new insights into Triticeae biology and genome organization and have important implications for downstream usage by breeders, experimental biologists, and comparative genomicists. transPLANT () is an EU-funded project aimed at constructing hardware, software, and data infrastructure for genome-scale research in the life sciences. Since the Triticeae data are intrinsically complex, heterogenous, and distributed, the transPLANT consortium has undertaken efforts to develop common data formats and tools that enable the exchange and integration of data from distributed resources. Here we present an overview of the individual Triticeae genome resources hosted by transPLANT partners, introduce the objectives of transPLANT, and outline common developments and interfaces supporting integrated data access.
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Schmutzer T, Samans B, Dyrszka E, Ulpinnis C, Weise S, Stengel D, Colmsee C, Lespinasse D, Micic Z, Abel S, Duchscherer P, Breuer F, Abbadi A, Leckband G, Snowdon R, Scholz U. Species-wide genome sequence and nucleotide polymorphisms from the model allopolyploid plant Brassica napus. Sci Data 2015; 2:150072. [PMID: 26647166 PMCID: PMC4672681 DOI: 10.1038/sdata.2015.72] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2015] [Accepted: 11/02/2015] [Indexed: 11/09/2022] Open
Abstract
Brassica napus (oilseed rape, canola) is one of the world's most important sources of vegetable oil for human nutrition and biofuel, and also a model species for studies investigating the evolutionary consequences of polyploidisation. Strong bottlenecks during its recent origin from interspecific hybridisation, and subsequently through intensive artificial selection, have severely depleted the genetic diversity available for breeding. On the other hand, high-throughput genome profiling technologies today provide unprecedented scope to identify, characterise and utilise genetic diversity in primary and secondary crop gene pools. Such methods also enable implementation of genomic selection strategies to accelerate breeding progress. The key prerequisite is availability of high-quality sequence data and identification of high-quality, genome-wide sequence polymorphisms representing relevant gene pools. We present comprehensive genome resequencing data from a panel of 52 highly diverse natural and synthetic B. napus accessions, along with a stringently selected panel of 4.3 million high-confidence, genome-wide SNPs. The data is of great interest for genomics-assisted breeding and for evolutionary studies on the origins and consequences in allopolyploidisation in plants.
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Affiliation(s)
- Thomas Schmutzer
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Stadt Seeland 06466, Germany
| | - Birgit Samans
- Justus Liebig University, Department of Plant Breeding, Heinrich-Buff-Ring 26-32, Gießen 35392, Germany
| | | | - Chris Ulpinnis
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Stadt Seeland 06466, Germany
| | - Stephan Weise
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Stadt Seeland 06466, Germany
| | - Doreen Stengel
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Stadt Seeland 06466, Germany
| | - Christian Colmsee
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Stadt Seeland 06466, Germany
| | - Denis Lespinasse
- Syngenta France SAS, 12 chemin de l'Hobit, Saint-Sauveur 31790, France
| | - Zeljko Micic
- Deutsche Saatveredelung AG, Weissenburger Straße 5, Lippstadt 59557, Germany
| | - Stefan Abel
- Limagrain GmbH, Salder Str. 4, Peine 31226, Germany
| | - Peter Duchscherer
- Bayer Crop Science AG, Streichmühler Str. 8, Grundhof 24977, Germany
| | - Frank Breuer
- KWS Saat AG, Grimsehlstr. 31, Einbeck 37555, Germany
| | - Amine Abbadi
- NPZ Innovation GmbH, Hohenlieth-Hof, Holtsee 24363, Germany
| | - Gunhild Leckband
- German Seed Alliance GmbH, Neue Schönholzer Str. 12, Berlin 13187, Germany
| | - Rod Snowdon
- Justus Liebig University, Department of Plant Breeding, Heinrich-Buff-Ring 26-32, Gießen 35392, Germany
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Stadt Seeland 06466, Germany
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Colmsee C, Beier S, Himmelbach A, Schmutzer T, Stein N, Scholz U, Mascher M. BARLEX - the Barley Draft Genome Explorer. Mol Plant 2015; 8:964-6. [PMID: 25804976 DOI: 10.1016/j.molp.2015.03.009] [Citation(s) in RCA: 73] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2014] [Revised: 02/11/2015] [Accepted: 03/18/2015] [Indexed: 05/03/2023]
Affiliation(s)
- Christian Colmsee
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466 Stadt Seeland, Germany
| | - Sebastian Beier
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466 Stadt Seeland, Germany
| | - Axel Himmelbach
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466 Stadt Seeland, Germany
| | - Thomas Schmutzer
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466 Stadt Seeland, Germany
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466 Stadt Seeland, Germany
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466 Stadt Seeland, Germany
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466 Stadt Seeland, Germany.
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Abstract
With the number of sequenced plant genomes growing, the number of predicted genes and functional annotations is also increasing. The association between genes and phenotypic traits is currently of great interest. Unfortunately, the information available today is widely scattered over a number of different databases. Information retrieval (IR) has become an all-encompassing bioinformatics methodology for extracting knowledge from complex, heterogeneous and distributed databases, and therefore can be a useful tool for obtaining a comprehensive view of plant genomics, from genes to traits. Here we describe LAILAPS (http://lailaps.ipk-gatersleben.de), an IR system designed to link plant genomic data in the context of phenotypic attributes for a detailed forward genetic research. LAILAPS comprises around 65 million indexed documents, encompassing >13 major life science databases with around 80 million links to plant genomic resources. The LAILAPS search engine allows fuzzy querying for candidate genes linked to specific traits over a loosely integrated system of indexed and interlinked genome databases. Query assistance and an evidence-based annotation system enable time-efficient and comprehensive information retrieval. An artificial neural network incorporating user feedback and behavior tracking allows relevance sorting of results. We fully describe LAILAPS's functionality and capabilities by comparing this system's performance with other widely used systems and by reporting both a validation in maize and a knowledge discovery use-case focusing on candidate genes in barley.
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Affiliation(s)
- Maria Esch
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstr. 3, D-06466 Stadt Seeland, Germany
| | - Jinbo Chen
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstr. 3, D-06466 Stadt Seeland, Germany
| | - Christian Colmsee
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstr. 3, D-06466 Stadt Seeland, Germany
| | - Matthias Klapperstück
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstr. 3, D-06466 Stadt Seeland, Germany
| | - Eva Grafahrend-Belau
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstr. 3, D-06466 Stadt Seeland, Germany
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstr. 3, D-06466 Stadt Seeland, Germany
| | - Matthias Lange
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstr. 3, D-06466 Stadt Seeland, Germany
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Arend D, Lange M, Chen J, Colmsee C, Flemming S, Hecht D, Scholz U. e!DAL--a framework to store, share and publish research data. BMC Bioinformatics 2014; 15:214. [PMID: 24958009 PMCID: PMC4080583 DOI: 10.1186/1471-2105-15-214] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2014] [Accepted: 06/12/2014] [Indexed: 11/10/2022] Open
Abstract
Background The life-science community faces a major challenge in handling “big data”, highlighting the need for high quality infrastructures capable of sharing and publishing research data. Data preservation, analysis, and publication are the three pillars in the “big data life cycle”. The infrastructures currently available for managing and publishing data are often designed to meet domain-specific or project-specific requirements, resulting in the repeated development of proprietary solutions and lower quality data publication and preservation overall. Results e!DAL is a lightweight software framework for publishing and sharing research data. Its main features are version tracking, metadata management, information retrieval, registration of persistent identifiers (DOI), an embedded HTTP(S) server for public data access, access as a network file system, and a scalable storage backend. e!DAL is available as an API for local non-shared storage and as a remote API featuring distributed applications. It can be deployed “out-of-the-box” as an on-site repository. Conclusions e!DAL was developed based on experiences coming from decades of research data management at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK). Initially developed as a data publication and documentation infrastructure for the IPK’s role as a data center in the DataCite consortium, e!DAL has grown towards being a general data archiving and publication infrastructure. The e!DAL software has been deployed into the Maven Central Repository. Documentation and Software are also available at: http://edal.ipk-gatersleben.de.
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Affiliation(s)
- Daniel Arend
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstr, 3, 06466 Stadt Seeland, Germany.
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Schlüter U, Colmsee C, Scholz U, Bräutigam A, Weber APM, Zellerhoff N, Bucher M, Fahnenstich H, Sonnewald U. Adaptation of maize source leaf metabolism to stress related disturbances in carbon, nitrogen and phosphorus balance. BMC Genomics 2013; 14:442. [PMID: 23822863 PMCID: PMC3716532 DOI: 10.1186/1471-2164-14-442] [Citation(s) in RCA: 81] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2013] [Accepted: 06/21/2013] [Indexed: 12/01/2022] Open
Abstract
Background Abiotic stress causes disturbances in the cellular homeostasis. Re-adjustment of balance in carbon, nitrogen and phosphorus metabolism therefore plays a central role in stress adaptation. However, it is currently unknown which parts of the primary cell metabolism follow common patterns under different stress conditions and which represent specific responses. Results To address these questions, changes in transcriptome, metabolome and ionome were analyzed in maize source leaves from plants suffering low temperature, low nitrogen (N) and low phosphorus (P) stress. The selection of maize as study object provided data directly from an important crop species and the so far underexplored C4 metabolism. Growth retardation was comparable under all tested stress conditions. The only primary metabolic pathway responding similar to all stresses was nitrate assimilation, which was down-regulated. The largest group of commonly regulated transcripts followed the expression pattern: down under low temperature and low N, but up under low P. Several members of this transcript cluster could be connected to P metabolism and correlated negatively to different phosphate concentration in the leaf tissue. Accumulation of starch under low temperature and low N stress, but decrease in starch levels under low P conditions indicated that only low P treated leaves suffered carbon starvation. Conclusions Maize employs very different strategies to manage N and P metabolism under stress. While nitrate assimilation was regulated depending on demand by growth processes, phosphate concentrations changed depending on availability, thus building up reserves under excess conditions. Carbon and energy metabolism of the C4 maize leaves were particularly sensitive to P starvation.
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Affiliation(s)
- Urte Schlüter
- Department of Biology, Division of Biochemistry, Friedrich-Alexander-University Erlangen-Nuremberg, Staudtstr, 5, 91058, Erlangen, Germany
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Colmsee C, Mascher M, Czauderna T, Hartmann A, Schlüter U, Zellerhoff N, Schmitz J, Bräutigam A, Pick TR, Alter P, Gahrtz M, Witt S, Fernie AR, Börnke F, Fahnenstich H, Bucher M, Dresselhaus T, Weber APM, Schreiber F, Scholz U, Sonnewald U. OPTIMAS-DW: a comprehensive transcriptomics, metabolomics, ionomics, proteomics and phenomics data resource for maize. BMC Plant Biol 2012; 12:245. [PMID: 23272737 PMCID: PMC3577462 DOI: 10.1186/1471-2229-12-245] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2012] [Accepted: 12/12/2012] [Indexed: 05/05/2023]
Abstract
BACKGROUND Maize is a major crop plant, grown for human and animal nutrition, as well as a renewable resource for bioenergy. When looking at the problems of limited fossil fuels, the growth of the world's population or the world's climate change, it is important to find ways to increase the yield and biomass of maize and to study how it reacts to specific abiotic and biotic stress situations. Within the OPTIMAS systems biology project maize plants were grown under a large set of controlled stress conditions, phenotypically characterised and plant material was harvested to analyse the effect of specific environmental conditions or developmental stages. Transcriptomic, metabolomic, ionomic and proteomic parameters were measured from the same plant material allowing the comparison of results across different omics domains. A data warehouse was developed to store experimental data as well as analysis results of the performed experiments. DESCRIPTION The OPTIMAS Data Warehouse (OPTIMAS-DW) is a comprehensive data collection for maize and integrates data from different data domains such as transcriptomics, metabolomics, ionomics, proteomics and phenomics. Within the OPTIMAS project, a 44K oligo chip was designed and annotated to describe the functions of the selected unigenes. Several treatment- and plant growth stage experiments were performed and measured data were filled into data templates and imported into the data warehouse by a Java based import tool. A web interface allows users to browse through all stored experiment data in OPTIMAS-DW including all data domains. Furthermore, the user can filter the data to extract information of particular interest. All data can be exported into different file formats for further data analysis and visualisation. The data analysis integrates data from different data domains and enables the user to find answers to different systems biology questions. Finally, maize specific pathway information is provided. CONCLUSIONS With OPTIMAS-DW a data warehouse for maize was established, which is able to handle different data domains, comprises several analysis results that will support researchers within their work and supports systems biological research in particular. The system is available at http://www.optimas-bioenergy.org/optimas_dw.
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Affiliation(s)
- Christian Colmsee
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Corrensstr. 3
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Corrensstr. 3
| | - Tobias Czauderna
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Corrensstr. 3
| | - Anja Hartmann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Corrensstr. 3
| | - Urte Schlüter
- Department of Biology, Friedrich-Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Staudtstr. 5, Germany
| | - Nina Zellerhoff
- University of Cologne, Botanical Institute, 50923 Köln, Albertus-Magnus-Platz, Germany
| | - Jessica Schmitz
- University of Cologne, Botanical Institute, 50923 Köln, Albertus-Magnus-Platz, Germany
| | - Andrea Bräutigam
- Plant Biochemistry, Heinrich-Heine-University, Universitätsstr. 1, 40225 Düsseldorf, Germany
| | - Thea R Pick
- Plant Biochemistry, Heinrich-Heine-University, Universitätsstr. 1, 40225 Düsseldorf, Germany
- International Graduate Program for Plant Science (iGrad-plant), Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Philipp Alter
- Cell Biology and Plant Biochemistry, University of Regensburg, Universitätsstr. 31, 93040 Regensburg, Germany
| | - Manfred Gahrtz
- Cell Biology and Plant Biochemistry, University of Regensburg, Universitätsstr. 31, 93040 Regensburg, Germany
| | - Sandra Witt
- Department of Molecular Physiology, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Am Mühlenberg 1, Germany
| | - Alisdair R Fernie
- Department of Molecular Physiology, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Am Mühlenberg 1, Germany
| | - Frederik Börnke
- Department of Biology, Friedrich-Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Staudtstr. 5, Germany
| | | | - Marcel Bucher
- University of Cologne, Botanical Institute, 50923 Köln, Albertus-Magnus-Platz, Germany
| | - Thomas Dresselhaus
- Cell Biology and Plant Biochemistry, University of Regensburg, Universitätsstr. 31, 93040 Regensburg, Germany
| | - Andreas PM Weber
- Plant Biochemistry, Heinrich-Heine-University, Universitätsstr. 1, 40225 Düsseldorf, Germany
| | - Falk Schreiber
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Corrensstr. 3
- Martin Luther University Halle-Wittenberg, Institute of Computer Science, 06120 Halle, Von-Seckendorff-Platz 1, Germany
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Corrensstr. 3
| | - Uwe Sonnewald
- Department of Biology, Friedrich-Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Staudtstr. 5, Germany
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10
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Schlüter U, Mascher M, Colmsee C, Scholz U, Bräutigam A, Fahnenstich H, Sonnewald U. Maize source leaf adaptation to nitrogen deficiency affects not only nitrogen and carbon metabolism but also control of phosphate homeostasis. Plant Physiol 2012; 160:1384-406. [PMID: 22972706 PMCID: PMC3490595 DOI: 10.1104/pp.112.204420] [Citation(s) in RCA: 111] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2012] [Accepted: 09/12/2012] [Indexed: 05/18/2023]
Abstract
Crop plant development is strongly dependent on the availability of nitrogen (N) in the soil and the efficiency of N utilization for biomass production and yield. However, knowledge about molecular responses to N deprivation derives mainly from the study of model species. In this article, the metabolic adaptation of source leaves to low N was analyzed in maize (Zea mays) seedlings by parallel measurements of transcriptome and metabolome profiling. Inbred lines A188 and B73 were cultivated under sufficient (15 mM) or limiting (0.15 mM) nitrate supply for up to 30 d. Limited availability of N caused strong shifts in the metabolite profile of leaves. The transcriptome was less affected by the N stress but showed strong genotype- and age-dependent patterns. N starvation initiated the selective down-regulation of processes involved in nitrate reduction and amino acid assimilation; ammonium assimilation-related transcripts, on the other hand, were not influenced. Carbon assimilation-related transcripts were characterized by high transcriptional coordination and general down-regulation under low-N conditions. N deprivation caused a slight accumulation of starch but also directed increased amounts of carbohydrates into the cell wall and secondary metabolites. The decrease in N availability also resulted in accumulation of phosphate and strong down-regulation of genes usually involved in phosphate starvation response, underlining the great importance of phosphate homeostasis control under stress conditions.
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11
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Pick TR, Bräutigam A, Schlüter U, Denton AK, Colmsee C, Scholz U, Fahnenstich H, Pieruschka R, Rascher U, Sonnewald U, Weber APM. Systems analysis of a maize leaf developmental gradient redefines the current C4 model and provides candidates for regulation. Plant Cell 2011; 23:4208-4220. [PMID: 22186372 PMCID: PMC3051238 DOI: 10.1105/tpc.111.230110] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
We systematically analyzed a developmental gradient of the third maize (Zea mays) leaf from the point of emergence into the light to the tip in 10 continuous leaf slices to study organ development and physiological and biochemical functions. Transcriptome analysis, oxygen sensitivity of photosynthesis, and photosynthetic rate measurements showed that the maize leaf undergoes a sink-to-source transition without an intermediate phase of C(3) photosynthesis or operation of a photorespiratory carbon pump. Metabolome and transcriptome analysis, chlorophyll and protein measurements, as well as dry weight determination, showed continuous gradients for all analyzed items. The absence of binary on-off switches and regulons pointed to a morphogradient along the leaf as the determining factor of developmental stage. Analysis of transcription factors for differential expression along the leaf gradient defined a list of putative regulators orchestrating the sink-to-source transition and establishment of C(4) photosynthesis. Finally, transcriptome and metabolome analysis, as well as enzyme activity measurements, and absolute quantification of selected metabolites revised the current model of maize C(4) photosynthesis. All data sets are included within the publication to serve as a resource for maize leaf systems biology.
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Affiliation(s)
- Thea R Pick
- Plant Biochemistry, Heinrich Heine University Düsseldorf, Duesseldorf, Germany
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12
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Pick TR, Bräutigam A, Schlüter U, Denton AK, Colmsee C, Scholz U, Fahnenstich H, Pieruschka R, Rascher U, Sonnewald U, Weber AP. Systems analysis of a maize leaf developmental gradient redefines the current C4 model and provides candidates for regulation. Plant Cell 2011; 23:4208-20. [PMID: 22186372 PMCID: PMC3269860 DOI: 10.1105/tpc.111.090324] [Citation(s) in RCA: 76] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2011] [Revised: 11/23/2011] [Accepted: 12/01/2011] [Indexed: 05/18/2023]
Abstract
We systematically analyzed a developmental gradient of the third maize (Zea mays) leaf from the point of emergence into the light to the tip in 10 continuous leaf slices to study organ development and physiological and biochemical functions. Transcriptome analysis, oxygen sensitivity of photosynthesis, and photosynthetic rate measurements showed that the maize leaf undergoes a sink-to-source transition without an intermediate phase of C(3) photosynthesis or operation of a photorespiratory carbon pump. Metabolome and transcriptome analysis, chlorophyll and protein measurements, as well as dry weight determination, showed continuous gradients for all analyzed items. The absence of binary on-off switches and regulons pointed to a morphogradient along the leaf as the determining factor of developmental stage. Analysis of transcription factors for differential expression along the leaf gradient defined a list of putative regulators orchestrating the sink-to-source transition and establishment of C(4) photosynthesis. Finally, transcriptome and metabolome analysis, as well as enzyme activity measurements, and absolute quantification of selected metabolites revised the current model of maize C(4) photosynthesis. All data sets are included within the publication to serve as a resource for maize leaf systems biology.
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Affiliation(s)
- Thea R. Pick
- Plant Biochemistry, Heinrich Heine University Düsseldorf, 40225 Duesseldorf, Germany
- International Graduate Program for Plant Science (iGrad-plant), Heinrich Heine University Düsseldorf, 40225 Duesseldorf, Germany
| | - Andrea Bräutigam
- Plant Biochemistry, Heinrich Heine University Düsseldorf, 40225 Duesseldorf, Germany
| | - Urte Schlüter
- Department of Biology, Friedrich Alexander University Erlangen-Nürnberg, 91058 Erlangen, Germany
| | - Alisandra K. Denton
- Plant Biochemistry, Heinrich Heine University Düsseldorf, 40225 Duesseldorf, Germany
- International Graduate Program for Plant Science (iGrad-plant), Heinrich Heine University Düsseldorf, 40225 Duesseldorf, Germany
| | - Christian Colmsee
- Leibniz Institute of Plant Genetics and Crop Plant Research, 06466 Gatersleben, Germany
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research, 06466 Gatersleben, Germany
| | | | - Roland Pieruschka
- Forschungszentrum Jülich, Institut für Bio- und Geowissenschaften (Pflanzenwissenschaften), 52425 Juelich, Germany
| | - Uwe Rascher
- Forschungszentrum Jülich, Institut für Bio- und Geowissenschaften (Pflanzenwissenschaften), 52425 Juelich, Germany
| | - Uwe Sonnewald
- Department of Biology, Friedrich Alexander University Erlangen-Nürnberg, 91058 Erlangen, Germany
| | - Andreas P.M. Weber
- Plant Biochemistry, Heinrich Heine University Düsseldorf, 40225 Duesseldorf, Germany
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13
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Schreiber F, Colmsee C, Czauderna T, Grafahrend-Belau E, Hartmann A, Junker A, Junker BH, Klapperstück M, Scholz U, Weise S. MetaCrop 2.0: managing and exploring information about crop plant metabolism. Nucleic Acids Res 2011; 40:D1173-7. [PMID: 22086948 PMCID: PMC3245004 DOI: 10.1093/nar/gkr1004] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
MetaCrop is a manually curated repository of high-quality data about plant metabolism, providing different levels of detail from overview maps of primary metabolism to kinetic data of enzymes. It contains information about seven major crop plants with high agronomical importance and two model plants. MetaCrop is intended to support research aimed at the improvement of crops for both nutrition and industrial use. It can be accessed via web, web services and an add-on to the Vanted software. Here, we present several novel developments of the MetaCrop system and the extended database content. MetaCrop is now available in version 2.0 at http://metacrop.ipk-gatersleben.de.
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Affiliation(s)
- Falk Schreiber
- Leibniz Institute of Plant Genetics and Crop Plant Research IPK, Corrensstrasse 3, 06466 Gatersleben, Germany.
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14
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Colmsee C, Flemming S, Klapperstück M, Lange M, Scholz U. A case study for efficient management of high throughput primary lab data. BMC Res Notes 2011; 4:413. [PMID: 22005096 PMCID: PMC3217054 DOI: 10.1186/1756-0500-4-413] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2011] [Accepted: 10/17/2011] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND In modern life science research it is very important to have an efficient management of high throughput primary lab data. To realise such an efficient management, four main aspects have to be handled: (I) long term storage, (II) security, (III) upload and (IV) retrieval. FINDINGS In this paper we define central requirements for a primary lab data management and discuss aspects of best practices to realise these requirements. As a proof of concept, we introduce a pipeline that has been implemented in order to manage primary lab data at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK). It comprises: (I) a data storage implementation including a Hierarchical Storage Management system, a relational Oracle Database Management System and a BFiler package to store primary lab data and their meta information, (II) the Virtual Private Database (VPD) implementation for the realisation of data security and the LIMS Light application to (III) upload and (IV) retrieve stored primary lab data. CONCLUSIONS With the LIMS Light system we have developed a primary data management system which provides an efficient storage system with a Hierarchical Storage Management System and an Oracle relational database. With our VPD Access Control Method we can guarantee the security of the stored primary data. Furthermore the system provides high performance upload and download and efficient retrieval of data.
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Affiliation(s)
- Christian Colmsee
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr, 3, 06466 Gatersleben, Germany.
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15
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Lange M, Spies K, Colmsee C, Flemming S, Klapperstück M, Scholz U. The LAILAPS Search Engine: A Feature Model for Relevance Ranking in Life Science Databases. J Integr Bioinform 2010. [DOI: 10.1515/jib-2010-118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
SummaryEfficient and effective information retrieval in life sciences is one of the most pressing challenge in bioinformatics. The incredible growth of life science databases to a vast network of interconnected information systems is to the same extent a big challenge and a great chance for life science research. The knowledge found in the Web, in particular in life-science databases, are a valuable major resource. In order to bring it to the scientist desktop, it is essential to have well performing search engines. Thereby, not the response time nor the number of results is important. The most crucial factor for millions of query results is the relevance ranking.In this paper, we present a feature model for relevance ranking in life science databases and its implementation in the LAILAPS search engine. Motivated by the observation of user behavior during their inspection of search engine result, we condensed a set of 9 relevance discriminating features. These features are intuitively used by scientists, who briefly screen database entries for potential relevance. The features are both sufficient to estimate the potential relevance, and efficiently quantifiable.The derivation of a relevance prediction function that computes the relevance from this features constitutes a regression problem. To solve this problem, we used artificial neural networks that have been trained with a reference set of relevant database entries for 19 protein queries.Supporting a flexible text index and a simple data import format, this concepts are implemented in the LAILAPS search engine. It can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases. LAILAPS is publicly available for SWISSPROT data at http://lailaps.ipk-gatersleben.de
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