Welcome to the Multinational Arabidopsis Steering Committee!

Click on a headings below and read about the recent progress of every of the eight MASC subcommittees.

MASC subcommittees, proposed in 2002, were established to help track the progress and advances made by the international Arabidopsis community.

The requirements for a subcommittee to be considered active were formulated in 2009:

  1. Submission of an annual report
  2. Input at MASC annual meetings
  3. MASC subcommittee chair has to be nominated with a 3-year minimum term to provide continuity
  4. Co-chairs could help promote activity of the subcommittee
  5. MASC subcommittee chairs/co-chairs should confirm leadership annually, if necessary, new subcommittee chairs should be found
  6. Chair/co-chair should confirm and represent the interest of subcommittee members.

The most recent 2016/2017 Subcommittee Reports can be found within the MASC Annual Report (PDF download). If yourequire the separate Subcommittee Reports then please contact the MASC coordinator This email address is being protected from spambots. You need JavaScript enabled to view it..


 

  • Bioinformatics Open or Close
    By Nicholas Provart (chair) with contributions from subcommittee members and the wider Arabidopsis community. The subcommittee members list can be found here.

    Tools and Resources

    Compiled by Nicholas Provart with input from MASC Bioinformatics Subcommittee members and the wider Arabidopsis community. 11 Apr 2016.

    Araport.org: Work towards creating a new Arabidopsis Information Portal by the International Arabidopsis Informatics Consortium continued (International Arabidopsis Informatics Consortium, 2012), with community meetings held at ICAR in Paris in 2015, and at the PAG Conference in San Diego in January 2016. The new portal has been online since April 2014 at http://araport.org. The Araport team has also mapped 113 RNA-seq data sets from the Sequence Read Archive at NCBI in order to identify novel splice variants for the newest Arabidopsis genome release (Araport11). This release of the Araport11 protein coding gene set contains 27,655 loci with 48,359 transcripts. Of TAIR10 protein-coding gene models, 68.9% (24,385/35,385) have been updated among which 4.7% (1,191) and 95.3% (24,367) have altered CDS and UTR sequences respectively. The number of genes in Araport11 with splice variants (10,696; 38.7%) of the genes is much higher than reported in TAIR10 (20.8%). The functional annotation of over 5000 of the TAIR10 loci has been updated. In addition, a total of 747 new loci and 12,973 new splice isoforms were added in this current release.

    Eva Huala and colleagues at TAIR have successfully moved to a subscription-based model, and their non-profit organization, Phoenix Bioinformatics, continues TAIR’s annotation work (Reiser et al., 2016). They released the 5th Public Release of new annotations in January 2016, containing annotations and other data added through the end of December 2014. Data added in 2014 and publicly released in 2015 included updates to gene summaries, new allele and phenotype data, a total of 677 new gene symbols, and new GO and PO annotations for 17,876 genes (including experiment-based annotations from published research articles for 2,936 genes). In addition to freely releasing all new data after one year, TAIR also continues to provide free access for students using TAIR in their coursework upon request from the course organizer.

    Shisong Ma from the Dinesh-Kumar Lab at UC Davis published their “AtGGM2014”, a gene co-expression network, derived from ~10,000 ATH1 microarrays (Ma et al., 2015). It uses partial correlation coefficient (Pcor) to calculate co-expression patterns between genes. 651 gene modules functioning in various developmental, stress response, hormone response, or housekeeping pathways were identified. These modules can be used by plant biologists for hypothesis generation. It is accessible at http://dinesh-kumarlab.genomecenter.ucdavis.edu/atggm2014.html. In related work, but based on large numbers of CATMA array data sets, Véronique Brunaud and colleagues at INRA in France published their GEM2Net tool (Zaag et al., 2015) to identify 681 coexpression clusters under biotic and abiotic stress conditions, see http://urgv.evry.inra.fr/GEM2NET/.

    Large-scale biology (selected): Steven Clouse’s group at the NC State University published an autophosphorylation site database for leucine-rich repeat receptor-like kinases covering 592 phosphorylation events in Arabidopsis at http://www4.ncsu.edu/~sclouse/Clouse2010.htm (Mitra et al., 2015). Murray Grant’s group in Exeter published a high-resolution timecourse of RNA dynamics in Arabidopsis leaves following challenge with Pseudomonas syringae pv tomato DC3000 and the same strain lacking HrpA to tease apart events associated with microbial-associated molecular pattern-triggered immunity versus effector-triggered susceptibility (Lewis et al., 2015). John McKay’s group at Colorado State University used gene expression and epistasis to identify candidate genes for drought-associated QTLs in Arabidopsis (Lovell et al., 2015). The Gregory Lab at the University of Pennsylvania published a comprehensive data set of RNA-binding protein/RNA interactions and nuclear RNA secondary structure as determined using their nuclear PIP-seq method (Gosai et al., 2015). The data are available at http://gregorylab.bio.upenn.edu/PIPseq_AtTotalNuc/.

    In terms of large-scale image analysis, George Bassel’s group in Birmingham developed 3DCellAtlas to extract biologically relevant information from quantitative 3D image data (Montenegro-Johnson et al., 2015).

    References

    Gosai SJ, Foley SW, Wang D, Silverman IM, Selamoglu N, Nelson ADL, Beilstein MA, Daldal F, Deal RB, Gregory BD (2015) Global Analysis of the RNA-Protein Interaction and RNA Secondary Structure Landscapes of the Arabidopsis Nucleus. Molecular Cell 57: 376–388; doi: 10.1016/j.molcel.2014.12.004.
    International Arabidopsis Informatics Consortium (2012) Taking the Next Step: Building an Arabidopsis Information Portal. The Plant Cell 24: 2248-2256; doi: 10.1105/tpc.112.100669.
    Lewis LA, Polanski K, de Torres-Zabala M, Jayaraman S, Bowden L, Moore J, Penfold CA, Jenkins DJ, Hill C, Baxter L, Kulasekaran S, Truman W, Littlejohn G, Prusinska J, Mead A, Steinbrenner J, Hickman R, Rand D, Wild DL, Ott S, Buchanan-Wollaston V, Smirnoff N, Beynon J, Denby K, Grant M (2015) Transcriptional Dynamics Driving MAMP-Triggered Immunity and Pathogen Effector-Mediated Immunosuppression in Arabidopsis Leaves Following Infection with Pseudomonas syringae pv tomato DC3000. Plant Cell 27: 3038-64; doi: 10.1105/tpc.15.00471.
    Lovell JT, Mullen JL, Lowry DB, Awole K, Richards JH, Sen S, Verslues PE, Juenger TE, McKay JK (2015) Exploiting Differential Gene Expression and Epistasis to Discover Candidate Genes for Drought-Associated QTLs in Arabidopsis thaliana. Plant Cell 27: 969-83; doi: 10.1105/tpc.15.00122.
    Ma S, Bohnert HJ, Savithramma P. Dinesh-Kumar SP (2015) AtGGM2014, an Arabidopsis gene co-expression network for functional studies. Science China Life Sciences 58: 276-286.
    Mitra SK, Chen R, Dhandaydham M, Wang X, Blackburn RK, Kota U, Goshe MB, Schwartz D, Huber SC and Clouse SD (2015) An autophosphorylation site database for leucine-rich repeat receptor-like kinases in Arabidopsis thaliana. Plant Journal 82: 1042-1060; doi: 10.1111/tpj.12863.
    Montenegro-Johnson TD, Stamm P, Strauss S, Topham AT, Tsagris M, Wood ATA, Smith RS, Bassel GW (2015) Digital Single-Cell Analysis of Plant Organ Development Using 3DCellAtlas. Plant Cell 27: 1018-1033; doi:10.1105/tpc.15.00175.
    Reiser L, Berardini TZ, Li D, Muller R, Strait EM, Li Q, Mezheritsky Y, Vetushko A, Huala E (2016) Sustainable funding for biocuration: The Arabidopsis Information Resource (TAIR) as a case study of a subscription-based funding model. Database 2016: baw018; doi: 10.1093/database/baw018.
    Zaag R, Tamby JP, Guichard C, Tariq Z, Rigaill G, Delannoy E, Renou JP, Balzergue S, Mary-Huard T, Aubourg S, Martin-Magniette ML, Brunaud (2015) GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response. Nucleic Acids Res. 43: D1010-7; doi: 10.1093/nar/gku1155.

  • Clone-Based Functional Genomics Resources (ORFeomics) Open or Close
    By Motoaki Seki (Chair) and Joe Ecker (Co-Chair) with contributions from subcommittee members, Masatomo Kobayashi (RIKEN BRC), Satoshi Iuchi (RIKEN BRC), Eric Grotewold (ABRC) and Debbie Christ (ABRC). The subcommittee members list can be found here.

    Progress Towards Road Map Goals

    The subcommittee goal is to keep tracking progress made towards the production of full-length cDNAs and open reading frame (ORF) clones for all annotated Arabidopsis protein-coding genes.

    Future Goals

    To continue to keep tracking progress made towards the production of full-length cDNAs and open reading frame (ORF) clones for all annotated Arabidopsis protein-coding genes.
    The ORFeomics subcommittee would like to propose a new project to collect all ORF (full-length cDNA) clones from every Arabidopsis protein-coding gene so as to test protein-protein, protein-DNA and protein-RNA interactions.
    Our recent search showed that now about 23,000 Arabidopsis protein-coding genes have been isolated as Full-length cDNA (ORF) clones. One of the last unexplored continents of Arabidopsis are the remaining 6,000 protein-coding genes. After that, only the non-coding genes remain to be isolated.
    With the completion of isolating all 29,000 Arabidopsis protein-coding genes, comprehensive analysis of plant gene function will become possible by various functional analyses using transgenic and protein expression approaches.
    The human whole ORFeome project is already ongoing. Arabidopsis is a model plant, thus this will represent the first big plant ORFeome project. On completion it might be possible to start synthetic biology using the whole gene set of Arabidopsis to allow functional studies of corresponding proteomes.

    Tools and Resources

    We prepared the updated list of Full-length cDNA and ORF clones that are available from Resource Centers (Table 2). The revised ones are shown in italics. New clones include Gateway clones for 73 kinase genes.

    Selected Publications

    • Breton G, Kay SA, Pruneda-Paz JL. (2016) Identification of Arabidopsis Transcriptional Regulators by Yeast One-Hybrid Screens Using a Transcription Factor ORFeome. Methods Mol Biol. 2016;1398:107-18.

    • Nemoto K, Takemori N, Seki M, Shinozaki K, Sawasaki T. (2015) Members of the Plant CRK Superfamily Are Capable of Trans- and Autophosphorylation of Tyrosine Residues. J. Biol. Chem. 290(27):16665-77.

    • Ramadan A, Nemoto K, Seki M, Shinozaki K, Takeda H, Takahashi H, Sawasaki T. (2015) Wheat germ-based protein libraries for the functional characterisation of the Arabidopsis E2 ubiquitin conjugating enzymes and the RING-type E3 ubiquitin ligase enzymes. BMC Plant Biol. 15:275

  • Epigenetics and Epigenomics Open or Close
    By Doris Wagner. The subcommittee members list can be found here.

    Progress Towards Road Map Goals

    The four AIMS of the EPIC/MASC initiative were
    1. Identify intellectual questions, transformative methodologies and infrastructure required to advance plant epigenomics.
    2. Establish an international epigenomics research network to communicate and coordinate research activities in countries/regions including the US, South America, Australia, Asia, UK, and continental Europe.
    3. Coordinate access to plant epigenomics information via a central website, (to serve primarily as a resource for researchers, as well as an educational resource for teachers and students).
    4. Establish a user-friendly epigenome browser platform that allows easy upload and display of user-generated epigenomic datasets and published datasets. Develop standards for plant epigenomics data collection, deposition and display.

    The EPIC RCN ended April 2016.

    Major Activities

    The EPIC initiative organized 5 scientific symposia with associated EPIC organizational meetings. These were held at the Chinese Academy of Sciences in 2012, at the John Innes Centre in Norwich UK in 2013, at the University of Pennsylvania in 2014, in Suzhou with Cold Spring Harbor Asia in 2015 and in Taos NM with Keystone Symposia in 2016. Additional organizational meetings include one held in conjunction with PAG in 2010 and a Banbury meeting in 2011. Yearly workshops were held at PAG (2010-2016) and at ICAR (2010-2016).
    In addition EPIC, together with the Gordon and Betty Moore Foundation, iPLant and PGRP has developed a unified plant epigenome browser platform.

    Specific Objectives

    Enhance the understanding of the role and regulation of plant epigenomes.

    Significant Results

    The combined activities of EPIC have much enhanced the appreciation and understanding of plant epigenetic/epigenomics and have enabled international collaborations aimed at understanding the roles and regulation of plant epigenetics/epigenomics.
    The jbrowse EPIC CoGE browsers (Arabidopsis, maize, soybean, rice) being developed will greatly facilitate comparative plant epigenomic analyses.
    A white paper, detailing the challenges and approaches to be used to tackle understanding of the plant epigenome, was published in the Plant Cell in 2012.

    Key outcomes or Other achievements

    General awareness and interest in epigenetics and epigenomics has increased. In the last year alone Plant Physiology, the Plant Journal and Molecular Plant all had special focus issues on Plant Epigenetics. The ICAR and related conferences also now have a session on Plant Epigenetics.

    Future Goals

    EPIC will continue with a newly formed steering committee consisting of Doris Wagner (transition only), Nathan Springer (USA), Toshiro Ito (Japan) and 1-2 european members (TBA) to organize symposia and EPIC organizational meetings every 2 years. In addition this group will continue to promote development and improvement of the EPIC CoGe browser. Finally, it will strive to enhance training in plant epigenetics and help forge bridges to other plant biology disciplines as well as to breeders and to industry.

    Tools and Resources

    Arabidopsis, maize and soybean CoGe browsers - online servers for plant epigenomic data.

    Conferences and Workshops

    • The EPIC initiative organized scientific symposia with associated EPIC organizational meetings.
    • Symposium on Epigneetics and Development Suzhou China with Cold Spring Harbor Asia in 2015 (organized by Xiao Feng Cao , Justin Goodrich and Doris Wagner).
    • Symposium on Epigenetics and adaptation to the environment in Taos NM with Keystone Symposia in February 2016 (organized by Scott Michaels, Nathan Springer and Doris Wagner).
    • A workshops was held at PAG in San Diego, CA (January 2016) organized by Rob Martienssen.
    • A workshop was held at the ICAR in Paris, France (July 2015) organized by Francois Roudier and Doris Wagner.

    Selected Publications

    • Nick Provart et al. (2016). 50 years of Arabidopsis research: highlights and future directions. New Phytologist. 3 921-944. Chapter on Epigenetics by Criag Pikaard, Vincent Colot and Doris Wagner.
    • Special issue on Plant Epigenetics in Plant Physiology, edited by Anna Amtmann, Hong Ma and Doris Wagner.
  • Metabolomics Open or Close
    By Kazuki Saito (chair) and Wolfram Weckwerth (co-chair) with contributions from subcommittee members and the wider Arabidopsis community. The subcommittee members list can be found here.

    Progress Towards Road Map Goals

    Since metabolomics is an important component of Arabidopsis omics, a continuous goal of this subcommittee will be to promote metabolomics research of Arabidopsis leading to functional genomics and systems biology. For this purpose we plan to establish a website for the initial process of consolidating Arabidopsis metabolomics activities making them more visible for the community. Full integration of Arabidopsis-based metabolomics research with the activity of the Metabolomics Society (http://www.metabolomicssociety.org/) is also an important goal of this subcommittee. Several members of the subcommittee are involved in drawing up the plant biology specific documentation for the Metabolomics Society. In addition this committee will aim to establish a mechanism that allows the dissemination of metabolomics datasets to the wider Arabidopsis community and encourage and facilitate initiatives for the integration of metabolomic datasets with other omic datasets. This will involve depositing metabolomic data in a usable format for data integration.

    Future Goals

    To realize the goals, we aimed to establish the subcommittee website for more efficient exchange of information and dissemination of the subcommittee’s activity. This subcommittee website has been launched at (www.masc-metabolomics.org). The subcommittee discussion will be taken not only in the occasion of ICAR annual meeting but also in the occasions of several other metabolomics-related meetings, where the subcommittee members can join. A MASCM gator portal is under development comparable with the MASCP gator portal (http://gator.masc-proteomics.org/). The webinterface will provide user with a user-friendly tool to search for Arabidopsis thaliana metabolomics data in available databases.

    Tools and Resources

    • http://prime.psc.riken.jp/: Metabolomic characterization of 50 Arabidopsis mutants and the database as a functional genomics tool (MeKO), Arabidopsis metabolome expression databases ‘AtMetExpress development’, ‘AtMetExpress 20 ecotypes’ and ‘ReSpect for Phytochemicals’. MS-DIAL: data independent MS/MS deconvolution for comprehensive metabolome analysis.
    • www.plantmetabolomics.org: A web portal of Arabidopsis Metabolomics Consortium that contains data from an NSF-2010 funded project concerning metabolite profiling of a set of metabolic mutants.
    • http://mmcd.nmrfam.wisc.edu/: The Madison-Qingdao metabolomics consortium database has emphasis on Arabidopsis and contains both NMR and MS data of metabolites.
    • http://www.ebi.ac.uk/metabolights: MetaboLights is a database for Metabolomics experiments and derived information. The database is cross-species, cross-technique and covers metabolite structures and their reference spectra as well as their biological roles, locations and concentrations, and experimental data from metabolic experiments and is a collaborative multi-laboratory effort including groups specialising in plant metabolism.

    Conferences and Workshops

    • 015/6/29-7/2, Metabolomics 2015, San Francisco, US
    • 2015/7/19-24, Gordon Research Conference, Plant Metabolic Engineering, Waterville Valley, US
    • 2015/12/15-20, Pacifichem 2015, Genomics and Metabolomics for Phytochemical Research, Honolulu, US
    • 2016/6/27-30, Metabolomics 2016 in partnership with Plant Metabolomics Forum, Dublin, Ireland
    • 2016/7/24-27, 9th Joint Natural Products Conference 2016, Copenhagen, Denmark
    • 2016/8/6-10, 55th Annual Meeting of th Phytochemical Society of North America, Davis, US
    • 2016/11/21-24, International PSE Symposium, Plant Omics and Biotechnology for Human Health, Gent, Belgium

    Selected Publications

    • Higashi Y, Okazaki Y, Myouga F, Shinozaki K, Saito K (2015) Landscape of the lipidome and transcriptome under heat stress in Arabidopsis thaliana. Scientific Reports 5: 10533 doi:10.1038/srep10533
    • Sumner LW, Lei Z, Nikolau BJ, Saito K (2015) Modern plant metabolomics: advanced natural product gene discoveries, improved technologies, and future prospects. Natural Products Reports 32: 212-229
    • Schulz E, Tohge T, Zuther E, Fernie AR, Hincha DK (2015) Natural variation in flavonol and anthocyanin metabolism during cold acclimation in Arabidopsis thaliana accessions. Plant Cell & Environment 38: 1658–1672
  • Natural Variation and Comparative Genomics Open or Close
    By J. Chris Pires (chair) and Brian Dilkes (co-chair) with contributions from subcommittee members and the wider Arabidopsis community. The subcommittee members list can be found here.
    Progress Towards Road Map Goals

    (A) Build a predictive model of an Arabidopsis plant from its molecular parts
    Progress was made in expanding the metabolic analyses. Joseph et al. (2015) show that the metabolic network has genetically programmed stochastic variance controlled by all the genomes and is node specific. For example, a gene can control phenylalanine noise across individuals without influencing shikimate or sinapate.

    (B) Exploit the wealth of natural variation that exists in Arabidopsis and related species to further our understanding of adaptation and evolution
    Progress in comparative genomics was made in sequencing additional genomes. Major milestones were made in the economically important genus Brassica, including the publication of Brassica napus (Chalhoub et al. 2014) and Brassica oleracea (Liu et al. 2014, Parkin et al. 2014). These analyses are now being followed up with sequencing across the diversity of these important crops (canola, broccoli, cauliflower, kale, kohlrabi, Brussels sprouts, and so forth; for example Wang et al. 2014). Numerous other comparative genomic analyses are ongong across the order Brassicales (Grewe et al. 2014). These studies in comparative genomics and natural variation illuminated several aspects of Arabidopsis biology.
    Progress in the natural variation of Arabidopsis was made. The sequencing of 1000 Arabidopsis genomes is ongoing, and various studies are investigating variation within a subset of the sequenced lines (for example, Li et al. 2014). Joseph et al. (2014) show from a meta-analysis that any RIL population under 1000 lines is too small for even dissecting the genetic architecture of a biparental cross. These results indicate that much larger populations need to be developed by the community then are currently being generated for multiparental trait dissection and suggests that GWA hits will be population dependent (with no population ever being the “Best”).

    (E) Deepen international cooperation and coordination
    Progress was made toward international cooperation and coordination at various meetings, including the annual meetings of the Brassicales Map Alignment Project (BMAP, see http://www.brassica.info/resource/sequencing/bmap.php) and the Multinational Brassica Genome Project (MBGP, see http://www.brassica.info/info/about-mbgp.php#meetings).

    (F) Subcommittee specific goals (if applicable)
    Progress was made toward agreeing on gene naming conventions across the Brassica species, with planned discussions among the Arabidopsis and Brassica communities to coordinate various standards and ontologies, as well an conventions for annotation, pan-genomes, ancestral genomes, and other –omics efforts within and across species in the Brassicales.

    Future Goals

    (A) Build a predictive model of an Arabidopsis plant from its molecular parts
    Future goals include building predictive models with insights from:
    Studying natural variation within Arabidopsis and comparisons to other related species of plants.
    Developing systems biology and -omics resources parallel to those available in Arabidopsis in crops like Brassica and Camelina and phylogenetically related model species that exhibit traits not present in Arabidopsis (e.g., both C3 and C4 photosynthesis in Cleome, woodiness in Caper).

    (B) Exploit the wealth of natural variation that exists in Arabidopsis to further our understanding of adaptation and evolution
    Exploring the variation in Arabidopsis and related species at numerous levels of biological organization to infer biological networks from various –omics data sets, including genomic, epigenomic, proteomic, metabolomic, ionomic, interactomic, and phenomic.
    Analyzing Arabidopsis ecotypes and related plant species in association with their rhizosphere, endophyte and epiphyte communities in various ecological and agricultural settings.
    Integrating studies across species and environments by analyzing and classifying natural diversity in the Brassicaceae, dissecting the genomic basis of diversified traits, and developing the infrastructure to maximize common benefits from genetic, genomic, ecological and systematics tools.
    Generating a multi-locus nuclear phylogeny of all the genera and species of the Brassicales for comparative biology, and to quickly identify transcriptome variation, life history traits, and genome size for future candidates of species for genome sequencing.
    Developing computational resources to understand and utilize the natural variation of Arabidopsis and related species. This will include interactions among the all the MASC subcommittees with the 1001 Arabidopsis Genomes project, Multinational Brassica Genome Project (MBGP), and Brassicales Map Alignment Project (BMAP) to consider natural variation and comparative -omics in the road map. Ensure that the Arabidopsis Information Portal (AIP) be built to work for Brassica and other plant species.
    Creating germplasm resources that are publicly available (e.g., Brassica diversity sets) and create a database for managing diversity (e.g., Brassibase, see brassica.info)

    (C) Establish an effective knowledge exchange pipeline from the laboratory to the field and vice versa
    Pursuing systems biology research programs and analyze –omics data sets in other plant systems using key knowledge gained through the analysis of Arabidopsis, starting with the crop Brassicas (vegetables and oilseeds), biofuel crops (e.g., Camelina), and other economically important species (e.g., horseradish, wasabi, etc.).
    Establishing data standards and ontologies to provide uniform data on growth conditions and experimental metadata to enable modeling from controlled environments to the field.
    Developing high-throughput methods in the lab and the field for measuring phenotypes and identifying QTLs that have subtle effects. Develop appropriate open access informatics and data infrastructure for storage, retrieval and analysis of natural variation and QTL. Establish accessible statistical and computational methods for the analysis of natural variation and QTL data.

    (D) Build the IAIC and develop efficient informatics tools and repositories further
    Integrating -omics data and informatics infrastructure in Arabidopsis with other species.
    Developing international standards for population genomics (Arabidopsis 1001 genomes, Brassica 100 genomes) and comparative genomics (BMAP 100 genomes) to maintain high-quality reference genomes and re-sequenced genomes.
    Developing open access ontology-driven database tools and promote the adoption of uniform vocabularies and machine-readable formats for describing experimental data and metadata. Subcommittee member Nick Provart is further developing Arabidopsis-centric view of BMAP data via a tool called GeneSlider at the Bio-Analytic Resource (BAR). Updated versions of the tool will include predicted transcription factor binding sites with links to Regulome (genome-wide DNAse I sensitivity data), see http://bar.utoronto.ca/~asher/GeneSlider_New/?datasource=CNSData&agi=At1g01010&before=1000&after=1000&zoom_from=779&zoom_to=879

    (E) Deepen international cooperation and coordination
    Undertaking a coordinated analysis of natural variation and comparative -omics with the international Brassicales Map Alignment Project (BMAP), Multinational Brassica Genome Project (MBGP), International Arabidopsis Informatics Consortium (IAIC), and BrassiBase.
    Continuing BMAP workshops at international conferences to coordinate efforts, share expertise, and develop -omics standards and comparative ontologies.

    (F) Subcommittee specific goals
    Studying natural variation within Arabidopsis and comparative ‘omic and systems biology investigations in related species is central to understanding plant biology and plant environment interactions.
    Coordinating gene naming conventions across the Brassica species, with planned discussions among the Arabidopsis and Brassica communities to coordinate various standards and ontologies, as well an conventions for annotation, pan-genomes, ancestral genomes, and other –omics efforts within and across species in the Brassicales.
    Conferences and Workshops
    In addition to regular annual meetings, the following conferences are planned for 2015-2016:
    Plant Genome Evolution in Amsterdam, Netherlands will meet again in September 2015.
    The next Crucifer Genetics Workshop will be in September 2016 in Melbourne, Australia; and Brassica 2018 will meet in St. Malo, France.

    Selected Publications
    • Early allopolyploid evolution in the post-neolithic Brassica napus oilseed genome. (2014) Chalhoub B, Denoeud F, Liu S, Parkin IAP, Tang H, et al. Science. 345: 950-953.
    • Genetic Variation for Life History Sensitivity to Seasonal Warming in Arabidopsis thaliana. (2014) Li Y, Cheng R, Spokas KA, Palmer AA, and Borevitz JO. Genetics. 196: 569-577
    • The Brassica oleracea genome reveals the asymmetrical evolution of polyploid genomes. (2014) Liu S, Liu Y, Yang X, Tong C, Edwards D, et al. Nature Communications. 5: 3930.
    • Transcriptome and methylome profiling reveals relics of genome dominance in the mesopolyploid Brassica oleracea. (2014) Parkin IAP, Koh C, Tang H, Robinson SJ, Kagale S, et al. Genome Biology. 15: R77.
    • Genome-wide investigation of genetic changes during modern breeding of Brassica napus. (2014) Wang N, Li F, Chen B, Xu K, Yan G, Qiao J, Li J, Gao G, Bancroft I, Meng J, King GJ, Wu X. heoretical & Applied Genetics. 8: 1817-1829.
    References
    Chalhoub B, Denoeud F, Liu S, Parkin IAP, et al. (2014) Early allopolyploid evolution in the post-neolithic Brassica napus oilseed genome. Science 345: 950-953.
    Grewe F, Edger P, Keren I, Sultan L, et al. (2014) Comparative analysis of 11 Brassicales mitochondrial genomes and the mitochondrial transcriptome of Brassica oleracea. Mitochondrion 19 : 135-143.
    Joseph B, Corwin JA and Kliebenstein DJ. (2015) Genetic variation in the nuclear and organellar genomes control stochastic variation in the metabolome. PLoS Genetics 11(1)e1004779.
    Joseph B, Atwell S, and Kliebenstein DJ. (2014) Meta-analysis of metabolome QTLs in Arabidopsis: Can we estimate the network size controlling genetic variation of the metabolome. Frontiers in Plant Science 5(1) 461.
    Li Y, Cheng R, Spokas KA, Palmer AA, Borevitz JO. (2014) Genetic Variation for Life History Sensitivity to Seasonal Warming in Arabidopsis thaliana. Genetics 196: 569-577
    Liu S, Liu Y, Yang X, Tong C, et al. 2014. The Brassica oleracea genome reveals the asymmetrical evolution of polyploid genomes. Nature Communications 5: 3930.
    Parkin IAP, Koh C, Tang H, Robinson SJ, et al. 2014. Transcriptome and methylome profiling reveals relics of genome dominance in the mesopolyploid Brassica oleracea. Genome Biology 15: R77.
    Wang N, Li F, Chen B, Xu K, et al. (2014) Genome-wide investigation of genetic changes during modern breeding of Brassica napus. Theoretical & Applied Genetics 8: 1817-1829.
  • Phenomics Open or Close
    By Fabio Fiorani (co-chair) and Robert Furbank (former co-chair) with contribution from subcommittee members and the wider Arabidopsis community. The subcommittee members list can be found here.

    Progress Towards Road Map Goals

    • In 2015 there has been a continued development of automated platforms and methods including new software for non-invasive phenotyping of Arabidopsis and crop phenotyping, increasing the capacity and the number of research centers that are engaged in large-scale phenomics research.
    • There were significant examples of comprehensive pipeline approaches to link genome to phenome and enable multi-trait analysis towards this goal.
    • Comprehensive efforts continued in 2015 within The International Plant Phenotyping Network, the European Plant Phenotyping Network (providing access to external users), the EU COST Action Phenotyping, and the implementation of national phenotyping networks in Germany (DPPN), France (Phenome), UK (UKPPN), and Australia (APPF), in particular.
    • There were multiple training activities in phenotyping organized in Europe.

    Future Goals

    • Promote best practices in phenotyping experimentation. This includes consideration to best practices for validating the identity of genetic stocks and the effects of genetic variants as recently suggested in a letter to Plant Cell (http://www.plantcell.org/content/early/2016/03/08/tpc.15.00502.full.pdf+html?utm_content=buffer67a68&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer).
    • Coordinated efforts will be required across phenotyping centers regarding germplasm used for sequencing (e.g.1001 genome project) and mutant collections would be desirable. Notable examples include to phenotype all re-sequenced Arabidopsis accessions under a series of defined challenging environments and phenotype the “no phenotype” T-DNA knock-out mutants by subjecting the collection of homozygous T-DNA k.o. mutants, or double mutants hitherto without a discernable mutant phenotype to deep phenotyping under a series of well-defined challenging environments.
    • Continue the development of methods for phenotyping across well-defined environmental conditions.

    Tools and Resources - Development of novel phenotyping infrastructure and phenotyping pipelines

    Updates by Stijn Dhondt, Dirk Inzé (VIB, Gent, Belgium), Minami Matsui, David Gifford (RIKEN, Japan), Lukás Spíchal (Olomouc, Czech Republic), Christine Granier (INRA Montpellier), Astrid Junker and Thomas Altmann (IPK Gatersleben)

    RIKEN and University of Tokyo

    • RIPPS (RIKEN Plant Phenotyping System) (K. Shinozaki, Miki Fujita, Kaoru Urano, Takanari Tanabata) is an automated system for evaluating plant growth under environmental stress conditions developed by the Gene Discovery Research Group of CSRS. RIPPS provides high-throughput and accurate measurements of plant traits, facilitating understanding of gene function in a wide range of environmental conditions (http://bit.ly/24U4Ujx). Recent research results from RIPPS include studies of Arabidopsis transgenics that perform well under drought conditions without growth reduction. Recent research includes results from the RIPPS which helped by its ability to focus on water use efficiency, not just growth or leaf shape (Kuromori et al., 2016).
    • A phenotype analysis program was developed at the University of Tokyo to characterize the pattern of epidermal cells and guard cells of Arabidopsis leaves and seedlings. Research is funded by JST Project (http://bit.ly/22oyHC6) for evaluation of morphological measurement. CARTA (clustering-aided rapid training agent) software was developed for auto learning system (Dr. Kutsuna, N. and Hasezawa, S., University of Tokyo; Higachi et al., 2015).
    • RIKEN Arabidopsis Genome Encyclopedia II (RARGE II) is an integrated phenotype database of Arabidopsis mutant traits using controlled vocabulary, with both RIKEN RAPID and CSHL Trapper DB for Ac/Ds transposon tagged lines in Arabidopsis. (Akiyama et al., 2014; Takashi Kuromori, Tetsuya Sakurai, Kazuo Shinozaki)(http://rarge-v2.psc.riken.jp/).
    • The Chloroplast Function Database II is a comprehensive database analyzed by combining genotypic and phenotypic multiparametic analysis of Arabidopsis tagged-lines for nuclear-encoded chloroplast proteins. The phenotype and segregation data of Arabidopsis Ds/Spm and T-DNA- tagged mutants of nuclear genes encoding chloroplast proteins includes more than 300 morphological mutants and 48 transmission electron microscopic images of mutant plastid (Fumiyoshi Myouga and Kazuo Shinozaki) (http://rarge-v2.psc.riken.jp/chloroplast/).
    • PosMed Positional Medline (Y. Makita, et al. RIKEN Synthetic Genome Research Group) Semantic web association study (SWAS) search engine ranks resources including Arabidopsis genes and metabolites, using associations between user-specified phenotypic keywords and resources connected directly or inferentially via a semantic web of biological databases such as MEDLINE, OMIM, pathways, co-expressions, molecular interactions and ontology terms (http://omicspace.riken.jp/).
    • For Genome to Phenome, location information of T-DNA in the genome is available for RIKEN Arabidopsis Activation Tagging lines (Minami Matsui collaboration with NEC Soft co ltd.) (http://metadb.riken.jp/metadb/db/SciNetS_ria37i) and around 10,000 Full-length cDNA information integrated in Arabidopsis FOX (Full-length cDNA Over-eXpressing) lines is available (http://ricefox.psc.riken.jp/).
    • The RIKEN MetaDatabase portal site is used to provide information on RIKEN’s various life science databases. In this database phenotype information of Activation tagging lines, Ac/ Ds transposon lines and FOX lines are available (http://metadb.riken.jp/).
    • Phenome Analysis of Ds transposon-tagging line in Arabidopsis (RAPID) selected about 4,000 transposon insertion lines which have the Ds transposon in gene coding region, and observed visible phenotypes systematically depending on growth stage. Phenotypic descriptions were classified into eight primary and fifty secondary categories, then all recorded images can be searched by the line number or the phenotype categories (http://rarge-v2.psc.riken.jp/phenome/).

    VIB, Plant Systems Biology, Gent, Belgium

    • An integrated network of Arabidopsis growth regulators was built. Next, this network was used for gene prioritization (Sabaghian et al., 2015). Several review papers were published looking into plant growth via gene regulatory networks and how phenotypic measurements and tools can support this integrative analysis (Vanhaeren et al, 2016; Vanhaeren et al, 2015; Wuyts et al, 2015; González et al, 2015).
    • Clauw et al. (2015) analyzed leaf and rosette growth response of six Arabidopsis thaliana accessions to mild drought stress. They employed the automated phenotyping platform WIWAM, which strictly controls the applied watering regime via allowing an automated weighing, watering and imaging of the plants. Analysis of growth related phenotypes and results from genome-wide transcriptome analysis (using RNA sequencing) indicate the existence of a robust response over different genetic backgrounds to mild drought stress in developing leaves. The analysis of a larger set of natural accessions is currently ongoing.
    • Van Landeghem et al. (2016) presents a generic, ontology-driven framework to infer, visualise and analyse an arbitrary set of condition-specific responses against one reference network. To this end, they have implemented novel ontology-based algorithms that can process highly heterogeneous networks, accounting for both physical interactions and regulatory associations, symmetric and directed edges, edge weights and negation. As an illustrative application, they demonstrate its usefulness on a plant abiotic stress study and experimentally confirmed a predicted regulator.
    • Stützel et al. (2016) propose the establishment of a European Consortium for Open Field Experimentation (ECOFE) that will allow easy access of European plant and soil scientists to experimental field stations that cover all major climatological regions. Coordination and quality control of data extraction and management systems will greatly impact on our ability to cope with grand challenges such as climate change and food security.

    The Centre of the Region Haná for Biotechnological and Agricultural Research, Palacky University Olomouc, Czech Republic

    • Our department is equipped with two phenotyping systems PlantScreenTM (PSI, Brno, Czech Republic) dedicated to integrative phenotyping of shoots of various plant species (Humplík et al. 2015a). Phenotyping platform allows measurement of plant growth, chlorophyll fluorescence, leaf temperature and leaf reflectance in fully controlled environment. Experiments performed in the systems are mainly focused on the evaluation of effectivity of synthetic growth regulators or potential bio-stimulants (Bahaji et al. 2015), but the selection of mutants or cultivars can be also provided upon request. As a response on global demand we are developing protocols for assessing impact of various abiotic stresses in different plant developmental stages. One of our aims is selection of cold-tolerant cultivars of field pea (Pisum sativum L.), for which the optimized measuring protocol was developed (Humplík et al. 2015b). Another applied analysis deals with the problem of salinity in the early development of crop species. Recently, we have developed crop seedling emergence software that reveals ability of seeds to germinate and of the seedlings to reach the light before the reserves are exhausted. This high-throughput bioassay (60 variants, 6600 seeds; in one run) automatically provides information about emergence rate as well as the total number of emerged seedlings. Further standardized protocols include in vitro screening of Arabidopsis growth by RGB camera in 24-well or 6-well plates (up to 11 000 seedlings) or complex phenotyping of Micro-Tom tomatoes and baby-lettuce grown in pots.

    INRA LEPSE Montpellier, France

    • Over the past 10 years, the Phenopsis platform has proven its efficiency to disentangle the integrated phenotype of Arabidopsis thaliana under controlled environmental conditions. Phenopsis is part of the Montpellier Plant Phenotyping Platforms (M3P), including three installations PhenoArch, Phenodyn and Phenopsis, hosted and developed by the same research group, INRA-LEPSE (https://www6.montpellier.inra.fr/m3p/). The huge genetic diversity of A. thaliana already investigated in Phenopsis has still been increased with genetically modified lines (Massonnet et al., 2015), collection of accessions (Bac-Molenaar et al., 2015, 2016), populations of recombinant inbred lines (Vasseur et al., 2014) and epigenetic hybrids (Dapp et al., 2015). High-throughput phenotyping effort was combined with genetic analyses (Bac-Molenaar et al., 2015, 2016), statistical modelling (Lièvre et al., 2016) or molecular profiling know-hows (Baerenfaller et al., 2015), giving insights into the regulation of phenotypic changes under various environmental conditions. In the last years, there has been considerable effort in extending the limits for precision phenotyping and exploring the capacities for developing efficient translational biology from models to cultivated species. Beyond the consequence of a significant decrease in research funding dedicated to model species at the benefit of applied research programs it appears important to develop comparative approaches (Blonder et al. 2015). To meet this challenge, recent developments of the Phenopsis platform include the possibility to grow plants in greater soil volume without impairing automated watering and image acquisition that take into account aerial architecture. Greater effort is also put into the exploration of more diverse climatic scenarios including continuous vs. intermittent moderate and severe water deficit combined with other abiotic and biotic factors (Bresson et al. 2015). Promising results have been obtained on the plasticity of plant development in response to drought stress in canola, tomato and Brachypodium distachion.

    IPK Gaterlseben, Germany

    • The whole plant phenotyping infrastructure at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben, Germany) comprises three conveyor belt-based, automated, high throughput plant-to-sensor phenotyping facilities (Junker et al. 2015). The system for small plants such as Arabidopsis is situated inside a phyto-chamber and allows for growth and automated imaging as well as weighing/watering of up to 4608 plants in parallel under fully controlled environmental conditions. Imaging in the RGB and near-infrared wavelength ranges, imaging of static and functional fluorescence in combination with 3D surface scanning enables the quantification of a hundreds of plant features ranging from plant architectural traits (plant height and width, projected leaf area (top, side view), estimated volume, Klukas et al. 2014), through physiological traits (color-related traits, Klukas et al. 2014, CHL fluorescence-related such as Fv/Fm, Fv’/Fm’, PhiPSII, relations to moisture content by NIR), to 3D related traits (leaf angles, 3D corrected projected areas).
    • Experience cumulated since 2011 was used to establish appropriate experimental procedures and designs that support the detection of genotypic and environmental effects on plant growth, development, and performance (Junker et al. 2015). This includes procedures for estimation of variance components and appropriate correction of potential inhomogeneities of conditions in the plant growth area. To enable the logging of the environmental regime the plants are exposed to during the course of experiments, a wireless sensor network has been installed for the continuous monitoring of light intensity (PAR), air temperature, rel. air humidity, light spectrum, radiation balance, and CO2 concentration at any place inside the growth chamber. Further upgrades are intended in order to enable simultaneous root and shoot phenotyping.
    • Standard experimental procedures are implemented that enable phenotypic analyses of plants under various treatments such as drought and salt stress (Muscolo et al. 2015, Harshavardhan et al. 2014) and the assessment of specific plant traits such as flowering timepoint, water use efficiency and plant organ movements. Recent and future activities involve the phenotypic characterization of an Arabidopsis accession panel under controlled environmental variation as well as hybrids and segregating populations with respect to the detailed analysis of the genetic basis of growth and metabolism control and heterosis.
    • The existing image analysis platform (IAP, Klukas et al. 2014) is currently being extended for the integrated/combinatorial analysis of the data (projected 2D images, 3D point clouds) derived from the various camera and scanning installations of the multi-sensor setup in order to retrieve novel information and to increase the precision (spatial resolution) of phenotypic trait extraction and data interpretation.
    • Resources: IAP - Integrated Analysis Platform (http://iapg2p.sourceforge.net/), has been designed and developed to support the analysis of large-scale image data sets of different camera systems. It aims at bridging various -omics domains and offers integrated approaches for image analysis up to data post-processing. (Klukas et al. 2014); PGP - Plant Genomics and Phenomics Research Data Repository (http://edal.ipk-gatersleben.de/repos/pgp/) provides infrastructure to publish plant research data, in particular cross-domain datasets and phenomics datasets and respective metadata information, which are assigned with citable DOIs for access and reuse by the scientific community (Arend et al. 2016).

    IBG2, Forschungszentrum Jülich, Germany

    • Bühler et al. (2015) developed a new software for leaf vein segmentation and analysis named phenoVein. This is a user-friendly tool designed for automated, fast and accurate leaf vein traits including model-based vein width determination. Validation included the quantitative measurement of vein length, width and density in Arabidopsis thaliana using a set of previously described vein structure mutants (hve-2, ond3, as2-101) compared to the wild type accessions Col-0 and Ler-0. phenoVein is freely available as open source software (http://www.fz-juelich.de/ibg/ibg-2/EN/methods/phenovein/phenovein_node.html).
    • Minervini et al. (2015) presented a collection benchmark datasets for the development and evaluation of computer vision and machine learning algorithms in the context of plant phenotyping. In this paper they provide annotated imaging data and suggest suitable evaluation criteria for leaf segmentation procedures. Data sets are publicly available at http://www.plant-phenotyping.org/datasets. This effort is designed to trigger additional efforts by the general computer vision community to experiment upon.
    • Barboza-Barquero et al. (2015) investigated whether semi-dwarfism has a pleiotropic effect at the level of the root system and also whether semi-dwarfs might be more tolerant of water-limiting conditions. The root systems of different Arabidopsis semi-dwarfs and GA biosynthesis mutants were phenotyped in vitro using the GROWSCREEN-ROOT image-based software. In addition, root phenotypes were investigated in soil-filled rhizotrons. Rosette growth trajectories were analysed with the GROWSCREEN-FLUORO setup based on non-invasive imaging.
    • High throughput phenotyping experiments were also performed using RGB and fluorescence camera systems in automated climate chambers, using 80 Arabidopsis ecotypes from the 1001 genome project investigating heat stress conditions (Körber et al, unpublished).

    Conferences and Workshops

     

    • EPPN Plant Phenotyping Symposium: Next generation plant phenotyping for trait discovery, breeding, and beyond: transnational access to European platforms, 11-12 November 2015, Barcelona, Spain
    • The European Plant Phenotyping Network organized a Spring School on Plant Phenotyping, Aberystwyth, 9 -13 March, 2015
    • VIB – Ghent University organized an EMBO practical course entitled “Insights into plant biological processes through phenotyping” together with University of Louvain and University of Liège from 13-19 September 2015
    • The German Plant Phenotyping Network (DPPN) and the EURoot project co-organized a Winter School in Root Phenotyping at Forschungszentrum Jülich, IBG2 Plant Sciences, 2-6 November, 2015
    • 1st General Meeting of the COST action FA1306 “The quest for tolerant varieties - Phenotyping at plant and cellular level”, 22-24 June 2015, IPK Gatersleben, Germany
    • Recent progress in drought tolerance: from genetics to modelling, 8-9 June, 2015, Le Corum – Montpellier, France, organized by DROPS and EUCARPIA.
    • Measuring the Photosynthetic Phenome, 7-9 July, Wageningen, the Netherlands
    • International Plant and Algal Phenomics Meeting (IPAP), 27-30 June 2015, Prague, Czech Republic

     

    Selected Publications

    • JJB (2016) Genome wide association mapping of time-dependent growth responses to moderate drought stress in Arabidopsis. Plant, Cell & Environment. 39: 88-102
    • Baerenfaller K, Massonnet C, Hennig L, Russenberger D, Sulpice R, Walsh S, Stitt M, Granier C, Gruissem W (2015) A long photoperiod relaxes energy management in Arabidopsis leaf six. Current Plant Biology. 2: 34-45
    • Bühler J, Rishmawi L, Pflugfelder D, Huber G, Scharr H, Hülskamp M, Koornneef M, Schurr U, Jahnke S (2015) phenoVein - A tool for leaf vein segmentation and analysis. Plant Physiology. 169: 2359-2370
    • Clauw P, Coppens F, De Beuf K, Dhondt S, Van Daele T, Maleux K, Storme V, Clement L, Gonzalez N, Inzé D (2015) Leaf responses to mild drought stress in natural variants of Arabidopsis. Plant Physiology. 167(3):800-16
    • Higaki T, Kutsuna N, Akita K, Sato M, Sawaki F, Kobayashi M, Nagata N, Toyooka K, Hasezawa S (2015) Semi-automatic organelle detection on transmission electron microscopic images. Scientific Reports. 5:7794

    References

    T (2014) RARGE II: An Integrated Phenotype Database of Arabidopsis Mutant Traits Using a Controlled Vocabulary. Plant Cell Physiology, 55(1): e4 doi:10.1093/pcp/pct165P.
    Arend D, Junker A, Scholz U, Schüler D, Wylie J, Lange M (2016) PGP repository: A plant phenomics and genomics data publication infrastructure. Database (Accepted)
    Bac-Molenaar JA, Granier C, Vreugdenhil D, Keurentjes JJB (2016) Genome wide association mapping of time-dependent growth responses to moderate drought stress in Arabidopsis. Plant, Cell & Environment. 39: 88-102.
    Bac-Molenaar JA, Vreugdenhil D, Granier C, Keurentjes JJB (2015) Genome wide association mapping of growth dynamics detects time-specific and general QTLs. Journal of Experimental Botany. 66: (18) 5567-5580.
    Baerenfaller K, Massonnet C, Hennig L, Russenberger D, Sulpice R, Walsh S, Stitt M, Granier C, Gruissem W (2015) A long photoperiod relaxes energy management in Arabidopsis leaf six. Current Plant Biology. 2: 34-45.
    Bahaji A, Sánchez-López ÁM, De Diego N, Muñoz FJ, Baroja-Fernández E, et al. (2015) Plastidic phosphoglucose isomerase is an important determinant of starch accumulation in mesophyll cells, growth, photosynthetic capacity, and biosynthesis of plastidic cytokinins in Arabidopsis. PLoS One 10: e0119641.
    Barboza-Barquero L, Nagel KA, Jansen M, Klasen JR, Kastenholz B, Braun S, Bleise B, Brehm T, Koornneef M, Fiorani F (2015). Phenotype of Arabidopsis thaliana semi-dwarfs with deep roots and high growth rates under water-limiting conditions is independent of the GA5 loss-of-function alleles. Annals of Botany. 116: 321-331.
    Blonder B, Vasseur F, Violle C, Shipley B, Enquist B, Vile D (2015) Testing models for the origin of the leaf economics spectrum with leaf and whole-plant traits in Arabidopsis thaliana. AoB Plants. 7: DOI: 10.1093/aobpla/plv049.
    Bresson J, Vasseur F, Dauzat M, Koch G, Granier C, Vile D (2015) Quantifying spatial heterogeneity of chlorophyll fluorescence during plant growth and in response to water stress. Plant Methods. 11: 23.
    Bühler J, Rishmawi L, Pflugfelder D, Huber G, Scharr H, Hülskamp M, Koornneef M, Schurr U, Jahnke S (2015) phenoVein - A tool for leaf vein segmentation and analysis. Plant Physiology. 169: 2359-2370.
    Clauw P, Coppens F, De Beuf K, Dhondt S, Van Daele T, Maleux K, Storme V, Clement L, Gonzalez N, Inzé D (2015) Leaf responses to mild drought stress in natural variants of Arabidopsis. Plant Physiology. 167(3):800-16.
    Dapp M, Reinders J, Bédiée A, Balsera C, Bucher E, Theiler G, Granier G, Paszkowski J (2015) Heterosis and inbreeding depression of epigenetic Arabidopsis hybrids. Nature Plants. 1: 15092.
    González N, Inzé D (2015) Molecular systems governing leaf growth: from genes to networks. Journal of Experimental Botany. 66(4):1045-54.
    Harshavardhan VT, Van Son L, Seiler C, Junker A, Weigelt-Fischer K, Klukas C, Altmann T, Sreenivasulu N, Bäumlein H, Kuhlmann M (2014) AtRD22 and AtUSPL1, members of the plant-specific BURP domain family involved in Arabidopsis thaliana drought tolerance. PLoS One 9 (2014) e110065. dx.doi.org/10.1371/journal.pone.0110065
    Higaki T, Kutsuna N, Akita K, Sato M, Sawaki F, Kobayashi M, Nagata N, Toyooka K, Hasezawa S (2015) Semi-automatic organelle detection on transmission electron microscopic images. Scientific Reports. 5:7794.
    Humplík JF, Lazár D, Husičková A, Spíchal L (2015a) Automated phenotyping of plant shoots using imaging methods for analysis of plant stress responses – a review. Plant Methods 11: 29.
    Humplík JF, Lazár D, Fürst T, Husičková A, Hýbl M, Spíchal L (2015b) Automated integrative high-throughput phenotyping of plant shoots: a case study of the cold-tolerance of pea (Pisum sativum L.). Plant Methods 11: 1–11.
    Junker A, Muraya M M, Weigelt-Fischer K, Arana-Ceballos F, Klukas C, Melchinger A E, Meyer R C, Riewe D, Altmann T (2015) Optimizing experimental procedures for quantitative evaluation of crop plant performance in high throughput phenotyping systems. Frontiers Plant Science. 5: 770. dx.doi.org/10.3389/fpls.2014.00770
    Klukas C, Chen D, Pape JM (2014): Integrated Analysis Platform: An open-source information system for high-throughput plant phenotyping. Plant Physiology. 165: 506-518.
    Kuromori T, Fujita M, Urano K, Tanabata T, Sugimoto E, Shinozaki K (2016). Overexpression of AtABCG25 enhances the abscisic acid signal in guard cells and improves plant water use efficiency, Plant Science. http://dx.doi.org/10.1016/j.plantsci.2016.02.019.
    Lièvre M., Granier C., Guédon Y. (2016) Identifying developmental phases in Arabidopsis thaliana rosette using integrative segmentation models. New Phytologist. doi: 10.1111/nph.13861.
    Massonnet C, Dauzat M, Bédiée A, Vile D, Granier C (2015) Individual leaf area of early flowering arabidopsis genotypes is more affected by drought than late flowering ones: a multi-scale analysis in 35 genetically modified lines. American Journal of Plant Sciences. 6: 955-971.
    Minervini M, Fischbach A, Scharr H, Tsaftaris SA (2015). Finely-grained annotated datasets for image-based plant phenotyping, Pattern Recognition Letters, http://dx.doi.org/10.1016/j.patrec.2015.10.013.
    Muscolo A, Junker A, Klukas C, Weigelt-Fischer K, Riewe D, Altmann T (2015): Phenotypic and metabolic responses to drought and salinity of four contrasting lentil accessions. Journal of Experimental Botany. 66: 5467-5480.
    Onogi A, Watanabe M, Mochizuki T, Hayashi T, Nakagawa H, Hasegawa T, Iwata H (2016) Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates. Theoretical and Applied Genetics 129(4):805-817.
    Sabaghian E, Drebert Z, Inzé D, Saeys Y (2015) An integrated network of Arabidopsis growth regulators and its use for gene prioritization. Scientific Reports. 5:17617
    Stützel H, Brüggemann N, Inzé D (2016) The Future of Field Trials in Europe: Establishing a Network Beyond Boundaries. Trends Plant Science. 21(2):92-5.
    Sugiura R, Itoh A, Nishiwaki K, Murakami N, Shibuya Y, Hirafuji M, Nuske S (2015) Development of High-Throughput Field Phenotyping System Using Imagery from Unmanned Aerial Vehicle. ASABE Annual International Meeting 152152494.
    Vanhaeren H, Inzé D, Gonzalez N. (2016) Plant growth beyond limits. Trends Plant Science. 21(2):102-9.
    Van Landeghem S, Van Parys T, Dubois M, Inzé D, Van de Peer Y. (2016) Diffany: an ontology-driven framework to infer, visualise and analyse differential molecular networks. BMC Bioinformatics. 17(1):18.
    Vanhaeren H, Gonzalez N, Inzé D. (2015) A journey through a leaf: phenomics analysis of leaf growth in Arabidopsis thaliana. Arabidopsis Book. 13:e0181.
    Vasseur F, Bontpart T, Dauzat M, Granier C, Vile D (2014) Multivariate genetic analysis of plant responses to water deficit and high temperature revealed contrasted adaptive strategies. Journal of Experimental Botany. 65: (22) 6457-6469.
    Wuyts N, Dhondt S, Inzé D (2015) Measurement of plant growth in view of an integrative analysis of regulatory networks. Curr Opin Plant Biology. 25:90-7.

  • Proteomics Open or Close
    By Joshua Heazlewood (chair). The subcommittee members list can be found here.

    Progress Towards Road Map Goals

    (A) The subcommittee members maintain an array of Arabidopsis specific proteomic repositories. These resources currently contribute to information in the Arabidopsis Information Portal (Araport).
    (B) The 1001 Proteomes portal provides pre-computed nsSNP data from the sequenced accessions.
    (C) Members have ongoing interests in applying proteomic approaches in Arabidopsis to important crop species. A number of the on-line proteomic resources also provide proteomic datasets for agricultural relevant species.
    (D) Subcommittee members maintain extensive resources in the area of protein function in Arabidopsis, and it is expected that this information will be coordinated with the IAIC.
    (E) Subcommittee members are involved with the initiative on Multi-Organism Proteomes (iMOP) as part of the Human Proteome Organization (HUPO) and are active members of the International Plant Proteomics Organization (INPPO). As well as many serving as members of their national plant societies.
    (F) The subcommittee website has been re-launched. See http://www.masc-proteomics.org/

    Future Goals

    (A) Maintain and develop new resources for Arabidopsis focusing on protein function and proteomics.
    (B) Demonstrate applicability of 1001 proteome data to the research community. Update the data for the recently released accessions.
    (C) Highlight projects that have demonstrated translational proteomic approaches on the re-launched website.
    (D) Start to construct proteomic Apps for the Arabidopsis Information Portal.
    (E) Ensure attendance and involvement in future INPPO and HUPO activities.
    (F) Maintain an active Arabidopsis proteomics subcommittee (http://www.masc-proteomics.org/).

    Tools and Resources

    Selected Publications

    • Choudhary MK, Nomura Y, Wang L, Nakagami H, Somers DE (2015) Quantitative Circadian Phosphoproteomic Analysis of Arabidopsis Reveals Extensive Clock Control of Key Components in Physiological, Metabolic, and Signaling Pathways. Mol Cell Proteomics 14: 2243-2260
    • Szymanski WG, Zauber H, Erban A, Gorka M, Wu XN, Schulze WX (2015) Cytoskeletal Components Define Protein Location to Membrane Microdomains. Mol Cell Proteomics 14: 2493-2509
    • Heard W, Sklenar J, Tome DF, Robatzek S, Jones AM (2015) Identification of Regulatory and Cargo Proteins of Endosomal and Secretory Pathways in Arabidopsis thaliana by Proteomic Dissection. Mol Cell Proteomics 14: 1796-1813
    • Minkoff BB, Stecker KE, Sussman MR (2015) Rapid Phosphoproteomic Effects of Abscisic Acid (ABA) on Wild-Type and ABA Receptor-Deficient A. thaliana Mutants. Mol Cell Proteomics 14: 1169-1182
    • Kohorn BD, Hoon D, Minkoff BB, Sussman MR, Kohorn SL (2016) Rapid Oligo-Galacturonide Induced Changes in Protein Phosphorylation in Arabidopsis. Mol Cell Proteomics
  • Systems and Synthetic Biology Open or Close

    By Siobhan Brady (chair) and Malcolm Bennett (co-chair) with contributions from subcommittee members Pascal Braun, Gloria Coruzzi, Rodrigo A. Gutiérrez, Gabriel Krouk, Susannah Lydon, Geraint Parry (GARNET) and the wider Arabidopsis community. The subcommittee members list can be found here.

    Progress Towards Road Map Goals

    (A) Build a predictive model of an Arabidopsis plant from its molecular parts: Millennium Nucleus for Plant Systems and Synthetic Biology; The Millennium Nucleus Center for Plant Systems and Synthetic Biology (PSSB) represents a new initiative in Chile to establish a research center of excellence using cutting-edge technologies for advancing Plant Sciences and Biotechnology addressing its scientific goals by taking advantage of cutting-edge Systems and Synthetic Biology strategies. We propose to take our systems-level efforts to the next level by integrating, interpreting and modeling new high-quality data we generate with available public datasets to explore gene function in cells and in whole organisms over developmental time and after specific environmental perturbations.
    Systematic mapping of the Arabidopsis protein interaction network is continuing (Braun lab) and an expanded map covering a 12k x 12k search space (expected 12k interactions) as well as map of the phytohormone signaling network is progressing - the data will be disseminated through existing channels, including the IntAct and BioGrid databases and TAIR.

    (C) Establish an effective knowledge exchange pipeline from the laboratory to the field: EVO Net DOE, Chile & USA
    This collaborative project exploits the genomes of “extreme survivor” plants adapted to thrive in marginal, extremely Nitrogen (N) poor soils in the arid Chilean Andes. It uses a previously validated systems biology and phylogenomics approach, and a “paired species” sampling strategy, to identify the genes that distinguish these “extreme survivors” in Chile from their related species adapted to similarly dry regions in California (CA) that are not constrained by N. The Chile and California species pairings were chosen as these two regions are in same “floristic province”, comprising 2/6 of the Mediterranean provinces world-wide. These “extreme survivor” species broadly cover the main branches in flowering plants, and include 7 species in the grasses, which are of particular interest for biofuels, and a focus of our validation studies

    (D) Build the IAIC and develop efficient informatics tools and repositories further
    Araport and the Arabidopsis Interactions Viewer have tools generated by Nicholas Provart to visualize protein-protein and protein-DNA interactions.

    (E) Deepen international cooperation and coordination:
    Members of the subcommittee are in the process of raising funds to organize the first International Plant Systems Biology (iPSB) meeting. The iPSB organizing committee includes S. Brady (USA), P. Braun (DE), G. Coruzzi (US), R. Gutierrez (CH), G. Krouk (FR). Help to raise funds is also kindly provided by the co-organizers M. Gifford (UK) and R. Bastow (UK). The meeting is planned to be held in France. The dates and location of the 1st iPSB will depend on the success of diverse grant applications. The GARNet2016 meeting (www.GARNet2016.weebly.com) includes a session and a workshop focussed on ‘Plant Synthetic Biology’ and ‘Usage and Application development within Araport’ and will engage with an international group of researchers, the majority of which work in Arabidopsis.

    Future Goals

    Develop and establish improved approaches to translate network connectivity into directional and signed causality edges. There is an increasing determination within the worldwide community to add value, both in terms of discovery and translational outputs, to the knowledge on gene networks developed through systems biology approaches.

    The natural pipeline for these outputs is in the development of synthetic biology tools that will enable the predictable expression of molecular components. This has been aided by the generation of a range of molecular tools that will reduce the time that has been historically taken to make lab-specific expression constructs and encourage the use of standardised tools that have been thoroughly tested by the community. This is aided by the current revolution in DNA synthesis and in turn allows for more efficient knowledge transfer from idea to product that avoided time-consuming characterisation of regulatory elements. Work in Arabidopsis remains an important component of this pipeline given the remaining bottlenecks that exist with the transformation of many other plant species. Therefore the testing of genetic elements in Arabidopsis will remain attractive before moving work into more challenging plant chassis’. The relationship between discovery in Arabidopsis and subsequent use of transient expression in Nicotiana benthamiana offers an excellent example of why Arabidopsis will remain a key element in plant science research in both systems and synthetic biology.

    This will also involve development of both bioinformatic and experimental approaches, and requires expanded database representations. Towards this goal discussions among community members and interaction database representatives will be conducted at the HUPO-Proteomics Standards Initiative (PSI) meeting (April 18-20, 2016, Ghent, BE). The planning of a scientific meeting on the translation of network connectivity to mechanisms to quantitative models is currently in an early phase of preparation (P. Braun). The systems biology community aims to establish closer links to the phenotyping and standardization efforts and this subcommittee aims to facilitate the establishment of links through the aforementioned meetings and other venues.

    Conferences and Workshops

    • NSF-RCN Workshop: “Bioinformatics, Quantitative Techniques and Computational Skills: Current Research and Future Training Needs for 21st Century Plant Biology” ICAR 2015 Paris, France, Paris, France, July 5-9
    • Thematic Session on Systems Biology and New Approaches - ICAR 2015, Paris, France July 5-9
    • “From Systems Biology to Synthetic Biology in Plants”, organized by R. Gutierrez, G. Coruzzi, G. Krouk; ICAR 2015, Paris France, July 5-9
    • Gene Regulation and Regulatory Networks Session; FASEB Mechanisms in Plant Development, Saxton River, Vermont, USA August 2-7
    • Stefan Altmann, Siobhan Brady and Fumiaki Katagiri spoke at the Cold Spring Harbor Systems Biology: Networks Meeting, March 17-21, Cold Spring Harbor, NY, USA (co-organizer: Pascal Braun)
    • X Plant Biology Meeting, Chile, December 1-4; the first symposium of this meeting was on Systems and Synthetic biology.
    • Havana Winter School: Statistical Physics Approaches to Systems Biology, Cuba, February 23 - March 7, the School focused on the use of Statistical Physics techniques to the study of complex biological systems, with special emphasis in the understanding of metabolic, regulatory and neural networks.
    • Argentinian Conference on Bioinformatics and Computational Biology, Argentina, October 14-16; The CAB2C is a multidisciplinary forum for the presentation and discussion of research in computational biology, bioinformatics and their applications. The CAB2C welcomes academic and professional contributions, from various scientific disciplines between those Systems Biology and Networks.
    • Inaugural OpenPlant Meeting: University of Cambridge, July 27-28. This meeting brought together a worldwide selection of experts in Synthetic Biology to discuss the use of plant chassis including Arabidopsis in the growing area of plant synthetic biology.
    • Biochemical Society Meeting: Synthetic Biology UK, London, September 1-3. This general meeting included significant contributions from plant synthetic biologists.

    Selected Publications

    • Li Y, Varala K and Coruzzi GM (2015) From milliseconds to lifetimes: Tracking the dynamic behavior of transcription factors in gene networks. Trends in Genet. 31(9):509-15. Dynamic Transcriptional Networks/Hit-and-Run transcription: Transcriptional networks operate dynamically in vivo, but capturing and modeling these dynamics is an experimental and computational challenge. This piece, together with two BioEssay pieces on “ideas that push the boundaries” (Varala et al., 2015 and Charoensawan et al., 2015) highlight the importance of transient interactions between transcription factors (TFs), including Hit-and-Run transcription, and their genome-wide targets in rapid signaling in plants (Figure 1).
    • Special Issue on Transcriptional Networks in Current Plant Biology, edited by Siobhan Brady and Nicholas Provart (http://www.sciencedirect.com/science journal/22146628/3-4)
    • Lavenus J, Goh T, Guyomarc’h S, Hill K, Lucas M, VoB U, Kenobi K, Wilson MH, Farcot E, Hagen G, Guilfoyle TJ, Fukaki H, Laplaze L, Bennett MJ. (2015) Inference of the Arabidopsis lateral root gene regulatory network suggests a bifurcation mechanism that defines primordia flanking and central zones. Plant Cell. 27(5):1368-88
    • Medici A, Marshall-Colon A, Ronzier E, Szponarski W, Wang R, Gojon A, Crawford NM, Coruzzi GM, Krouk G. (2015) AtNIGT1/HRS1 integrates nitrate and phosphate signals at the Arabidopsis root tip. Nature Communications 6, Article number: 6274
    • Kim T, Dreher K, Nilo-Poyanco R, Lee I, Fiehn O, Lange BM, Nikolau BJ, Sumner L, Welti R, Wurtele ES, Rhee SY. (2015) Patterns of Metabolite Changes Identified from Large-Scale Gene Perturbations in Arabidopsis Using a Genome-Scale Metabolic Network. Plant Physiology; 167:1685-1698
    • Schaumberg KA, Antunes MS, Kassaw TK, Xu W, Zalewski CS, Medford JI, Prasad A (2016) Quantitative characterization of genetic parts and circuits for plant synthetic biology Nature Methods 13(1):94-100

     Systems synthetic Figure1

    Additional Information

    Members of the sub-committee are particularly excited about several new approaches and discoveries in 2015/2016. First CRISPR-Cas9 gene editing methods have greatly advanced and thus will likely enable increase our ability to functionally test hypotheses derived from network analyses and systems approaches. Our ability to delete or modifiy cis-regulatory elements in their natural genomic context, to alter interactions between known dimerization domains of proteins and to make systematic gene knockouts are all examples of how this approach can be utilized to perturb a biological system. Additionally, the findings from Craig Venter’s institute describing a minimal synthetic bacterial genome in Science (Hutchison et al., Science 2016) also leads us to consider the next steps with respect to considering the minimal synthetic plant genome.

    References

    Hutchison CA, Chuang R, Noskov VN, Assad-Garcia N, Deerinck TJ, Ellisman MH, Gill J, Kannan K, Karas BJ, Ma L, Pelletier JF, Qi Z, Richter RA, Strychalski EA, Sun L, Suzuki Y, Tsvetanova B, Wise KS, Smith HO, Glass JI, Merryman C, Gibson DG, Venter JC (2016) Design and synthesis of a minimal bacterial genome. Science 25;351(6280)
    Li Y, Varala K and Coruzzi GM (2015) From milliseconds to lifetimes: Tracking the dynamic behavior of transcription factors in gene networks. Trends in Genet. 31(9):509-15
    Varala K, Li Y, Marshall-Colón A, Para A and Coruzzi GM (2015) “Hit-and-Run” leaves its mark: Catalyst transcription factors and chromatin modification.” BioEssays 37(8):851-6
    Charoensawan V, Martinho C, Wigge PA. “Hit-and-run”: Transcription factors get caught in the act. Bioessays 37(7):748-54