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      Measures for interoperability of phenotypic data: minimum information requirements and formatting

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          Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse.


          In this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called “Minimum Information About a Plant Phenotyping Experiment”, which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented.


          Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13007-016-0144-4) contains supplementary material, which is available to authorized users.

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          Most cited references 24

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          Genome-wide association study of 107 phenotypes in a common set of Arabidopsis thaliana inbred lines

          Although pioneered by human geneticists as a potential solution to the challenging problem of finding the genetic basis of common human diseases1,2, advances in genotyping and sequencing technology have made genome-wide association (GWA) studies an obvious general approach for studying the genetics of natural variation and traits of agricultural importance. They are particularly useful when inbred lines are available because once these lines have been genotyped, they can be phenotyped multiple times, making it possible (as well as extremely cost-effective) to study many different traits in many different environments, while replicating the phenotypic measurements to reduce environmental noise. Here we demonstrate the power of this approach by carrying out a GWA study of 107 phenotypes in Arabidopsis thaliana, a widely distributed, predominantly selfing model plant, known to harbor considerable genetic variation for many adaptively important traits3. Our results are dramatically different from those of human GWA studies in that we identify many common alleles with major effect, but they are also, in many cases, harder to interpret because confounding by complex genetics and population structure make it difficult to distinguish true from false associations. However, a priori candidates are significantly overrepresented among these associations as well, making many of them excellent candidates for follow-up experiments by the Arabidopsis community. Our study clearly demonstrates the feasibility of GWA studies in A. thaliana, and suggests that the approach will be appropriate for many other organisms.
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            New handbook for standardised measurement of plant functional traits worldwide

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              The minimum information about a proteomics experiment (MIAPE).

              Both the generation and the analysis of proteomics data are now widespread, and high-throughput approaches are commonplace. Protocols continue to increase in complexity as methods and technologies evolve and diversify. To encourage the standardized collection, integration, storage and dissemination of proteomics data, the Human Proteome Organization's Proteomics Standards Initiative develops guidance modules for reporting the use of techniques such as gel electrophoresis and mass spectrometry. This paper describes the processes and principles underpinning the development of these modules; discusses the ramifications for various interest groups such as experimentalists, funders, publishers and the private sector; addresses the issue of overlap with other reporting guidelines; and highlights the criticality of appropriate tools and resources in enabling 'MIAPE-compliant' reporting.

                Author and article information

                [1 ]Institute of Plant Genetics, Polish Academy of Sciences, ul. Strzeszyńska 34, 60-479 Poznań, Poland
                [2 ]Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), OT Gatersleben, Corrensstraße 3, 06466 Stadt Seeland, Germany
                [3 ]Bioversity International, parc Scientifique Agropolis II, 34397 Montpellier Cedex 5, France
                [4 ]Institute for Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany
                [5 ]INRA, UR1164 URGI - Research Unit in Genomics-Info, INRA de Versailles-Grignon, Route de Saint-Cyr, 78026 Versailles, France
                [6 ]Forschungszentrum Jülich GmbH, IBG-2 Plant Sciences, 52425 Jülich, Germany
                [7 ]Institute of Computing Science, Poznań University of Technology, ul. Piotrowo 3a, 60-479 Poznań, Poland
                [8 ]LemnaTec GmbH, Pascalstraße 59, 52076 Aachen, Germany
                [9 ]Poznań Supercomputing and Networking Center Affiliated to the Institute of Bioorganic Chemistry, Polish Academy of Sciences, ul. Jana Pawła II 10, 61-139 Poznań, Poland
                [10 ]UMR MISTEA, INRA SupAgro, Place Pierre Viala 2, 34060 Montpellier, France
                [11 ]Keygene N.V., Agro Business Park 90, 6708 PW Wageningen, The Netherlands
                [12 ]Oxford e-Research Centre, University of Oxford, 7 Keble Road, Oxford, OX1 3QG UK
                [13 ]Gregor Mendel Institute, Austrian Academy of Sciences, 1030 Vienna, Austria
                [14 ]Institute of Biology I, BioSC, RWTH Aachen, Worringer Weg 3, Aachen, Germany
                [15 ]The European Molecular Biology Laboratory–The European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD UK
                Plant Methods
                Plant Methods
                Plant Methods
                BioMed Central (London )
                9 November 2016
                9 November 2016
                : 12
                5103589 144 10.1186/s13007-016-0144-4
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

                Funded by: FundRef, Seventh Framework Programme;
                Award ID: 283496
                Award ID: 28443
                Award Recipient :
                Funded by: FundRef, Bundesministerium für Bildung und Forschung;
                Award ID: 031A053A/B/C
                Funded by: FundRef, Agence Nationale de la Recherche;
                Award ID: ANR-11-INBS-0012
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                © The Author(s) 2016


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