Welcome to the Multinational Arabidopsis Steering Committee!

 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 2017-2108 Subcommittee Report can be download here. If you require reports from each different Subcommittee then please contact the MASC secretary This email address is being protected from spambots. You need JavaScript enabled to view it..


 

  • Bioinformatics Open or Close
    Compiled by Nicholas Provart (This email address is being protected from spambots. You need JavaScript enabled to view it.) with input from MASC Bioinformatics Subcommittee members and the wider Arabidopsis community. 30 April 2019.

    Arabidopsis Informatics – TAIR: Staff at The Arabidopsis Information Resource (TAIR) have continued updating Arabidopsis gene data in TAIR from published literature over the past year.  From March 2018-Feb 2019, TAIR added 4,431 experimental Gene Ontology (GO) and Plant Ontology (PO) annotations generated by TAIR curators, TAIR community, UniProt and Gene Ontology Consortium (GOC) to the database. A total of 558 articles were used to annotate to 1,696 distinct loci. We added 3,783 articles of which 2,302 were linked to 3,921 genes. We curated 849 new gene symbols, 164 alleles, 304 phenotypes and added/updated 5,867 gene summaries. We processed 610 annotations provided by 89 community members spanning 99 papers. TAIR database is updated weekly and the most up to date annotations are accessible via TAIR’s website and tools (www.arabidopsis.org).

    TAIR also continues to provide quarterly public releases of year-old datasets (https://www.arabidopsis.org/download/index-auto.jsp?dir=/download_files/Public_Data_Releases). The 18th public release from TAIR contains cumulative curated data sets up to March 31, 2018. Educators can continue to request access to the “full” version of TAIR for teaching purposes. We look forward to integrating JBrowse into TAIR in the coming year

    Araport.org: Unfortunately, the U.S. National Science Foundation did not provide renewed funding for Araport.org, leaving its future uncertain. At a meeting Maryland in March 2019, curators and informaticians from several resources, including TAIR and the BAR met to decide a path forward. It was decided that the Thalemine functionality of Araport.org would move to the BAR, while its JBrowse instance would be moved to TAIR – stay tuned for an update to this seemingly never-ending saga.

    The BAR (Bio-Analytic Resource) received new funding from Genome Canada to expand the popular ePlant tool to incorporate ecosystem-level data.

    DNA and RNA resources: John Brown’s lab in Dundee looked at the how the Arabidopsis transcriptome responds at the level of alternative splicing, showing that hundreds of genes exhibit alternative splicing in response to cold (Calixto et al., 2018).

    Marcus Schmid’s group used INTACT to isolate phloem companion cell-specific transcriptomes and DNA for epigenomic analyses, identifying MRF1 as a regulator of flowering (You et al., 2019).
    Hiroshi Kudoh’s group (Nagano et al., 2019)used a wild Arabidopsis thaliana relative (A. halleri) to study the dynamics of variation in transcriptome expression weekly over two years (and bihourly on the four equinoxes/solstices), to identify 2,879 seasonally-oscillating genes (and 7,185 diurnally-oscillating ones).

    Kenichi Tsuda and colleagues used RNA-seq to show rapid transcriptional reprogramming mediated by phytohormone signaling in the effector-triggered immunity response (Mine et al., 2018). Last, Detlef Weigel’s group used a 16S sequencing-based approach to show stable associations between diverse Pseudomonas pathogen sublineages and wild Arabidopsis thaliana strains over evolutionary timescales (Karasov et al., 2018).

    Gene regulatory networks (GRNs)/codes: The 2019 Nucleic Acids Research database issue (Rigden and Fernández, 2019) contains updates or reports on several plant databases. Of note here: the PlantPAN database for reconstructing transcriptional regulatory networks from ChIP-seq experiments was updated to version 3.0, and now encompasses TF ChIP-seq data for 82 regulatory factors in Arabidopsis (Chow et al., 2019).

    1001 Genomes Data: The Wright Lab at Virginia Tech released ViVa: Visualizing Variation in the Arabidopsis 1001 genomes project (Hamm et al., 2018)
    http://plantsynbiolab.bse.vt.edu/ViVa.

    Protein Resources: The Plant PTM Viewer from the Gevaert’s Lab at the University of Gent (Willems et al., 2019)  permits exploration of 370,000 PTM (post-translational modification) sites for 19 types of protein modifications in proteins from five different plant species. It can be accessed and encompasses more than 100,000 PTMs in Arabidopsis!
    https://www.psb.ugent.be/webtools/ptm-viewer/

    A new Arabidopsis Interactions Viewer (AIV2) was released by the Provart Lab (Dong et al., 2019). The authors also predicted almost 10,000 protein-protein interactions (PPIs) using a docking algorithm, and have worked with BioGRID to incorporate 42,605 experimentally-determined PPIs into the new interface, along with 2.8M protein-DNA interactions. The new AIV2 is available at http://bar.utoronto.ca/interactions2.

    Georgia Drakakaki’s group published a cool study based on arrayed antibodies to identify the glycan contents of post-Golgi vesicles ((Wilkop et al., 2019). Youssef Belhkadir’s group at GMI in Austria together with a number of colleagues published a leucine-rich repeat receptor kinase cell surface interaction network (CSILRR) of 567 interactions between the extracellular domains of 225 LRR-RKs (Smakowska-Luzan et al., 2018). These data are available in the AIV2 mentioned earlier.

    New Plant Bioinformatics Course: The Provart lab released a 6 module course on Cousera.org called “Plant Bioinformatics” (https://www.coursera.org/learn/plant-bioinformatics/), which one can audit for free, or receive a certificate for, for a small fee. This hands-on course is broadly about exploring online tools for mining plant data, but given that most data come from Arabidopsis, the course provides lots of insight for this species, too. The course covers plant genomic databases, and useful sites for info about proteins; expression analysis; coexpression tools; promoter analysis; functional classification and pathway vizualization; and network exploration (PPIs, PDIs, GRNs).

    References

    Calixto, C.P.G., Guo, W., James, A.B., Tzioutziou, N.A., Entizne, J.C., Panter, P.E., Knight, H., Nimmo, H.G., Zhang, R., and Brown, J.W.S. (2018). Rapid and Dynamic Alternative Splicing Impacts the Arabidopsis Cold Response Transcriptome. Plant Cell 30: 1424–1444.

    Chow, C.-N., Lee, T.-Y., Hung, Y.-C., Li, G.-Z., Tseng, K.-C., Liu, Y.-H., Kuo, P.-L., Zheng, H.-Q., and Chang, W.-C. (2019). PlantPAN3.0: a new and updated resource for reconstructing transcriptional regulatory networks from ChIP-seq experiments in plants. Nucleic Acids Res. 47: D1155–D1163.

    Dong, S. et al. (2019). Proteome-wide, Structure-Based Prediction of Protein-Protein Interactions/New Molecular Interactions Viewer. Plant Physiol. 179: 1893–1907.

    Hamm, M.O., Moss, B.L., Leydon, A.R., Gala, H.P., Lanctot, A., Ramos, R., Klaeser, H., Lemmex, A.C., Zahler, M.L., Nemhauser, J.L., and Wright, R.C. (2018). Accelerating structure-function mapping using the ViVa webtool to mine natural variation. bioRxiv: 488395.

    Karasov, T.L. et al. (2018). Arabidopsis thaliana and Pseudomonas Pathogens Exhibit Stable Associations over Evolutionary Timescales. Cell Host Microbe 24: 168-179.e4.

    Mine, A., Seyfferth, C., Kracher, B., Berens, M.L., Becker, D., and Tsuda, K. (2018). The Defense Phytohormone Signaling Network Enables Rapid, High-Amplitude Transcriptional Reprogramming during Effector-Triggered Immunity. Plant Cell 30: 1199–1219.

    Nagano, A.J., Kawagoe, T., Sugisaka, J., Honjo, M.N., Iwayama, K., and Kudoh, H. (2019). Annual transcriptome dynamics in natural environments reveals plant seasonal adaptation. Nat. Plants 5: 74.

    Rigden, D.J. and Fernández, X.M. (2019). The 26th annual Nucleic Acids Research database issue and Molecular Biology Database Collection. Nucleic Acids Res. 47: D1–D7.

    Smakowska-Luzan, E. et al. (2018). An extracellular network of Arabidopsis leucine-rich repeat receptor kinases. Nature 553: 342–346.

    Wilkop, T., Pattathil, S., Ren, G., Davis, D.J., Bao, W., Duan, D., Peralta, A.G., Domozych, D.S., Hahn, M.G., and Drakakaki, G. (2019). A Hybrid Approach Enabling Large-Scale Glycomic Analysis of Post-Golgi Vesicles Reveals a Transport Route for Polysaccharides. Plant Cell 31: 627–644.

    Willems, P., Horne, A., Parys, T.V., Goormachtig, S., Smet, I.D., Botzki, A., Breusegem, F.V., and Gevaert, K. (2019). The Plant PTM Viewer, a central resource for exploring plant protein modifications. Plant J. ttps://doi.org/10.1111/tpj.14345

    You, Y., Sawikowska, A., Lee, J.E., Benstein, R.M., Neumann, M., Krajewski, P., and Schmid, M. (2019). Phloem Companion Cell-Specific Transcriptomic and Epigenomic Analyses Identify MRF1, a Regulator of Flowering. Plant Cell 31: 325–345.

     

  • 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

    Prepared by

    Xuehua Zhong, This email address is being protected from spambots. You need JavaScript enabled to view it., University of Wisconsin-Madison
    Robert Schmitz, This email address is being protected from spambots. You need JavaScript enabled to view it., University of Georgia
    Claudia Kohler,  This email address is being protected from spambots. You need JavaScript enabled to view it., Uppsala Centre for Plant Science
    Xiaofeng Cao, This email address is being protected from spambots. You need JavaScript enabled to view it., Chinese Academy of Sciences
    Yijun Qi, This email address is being protected from spambots. You need JavaScript enabled to view it., Tsinghua University
    Roger Deal, This email address is being protected from spambots. You need JavaScript enabled to view it., Emory University


    Open Tools and Resources for Arabidopsis Researchers

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


    Recent activities of Subcommittee members.

    The Epigenetics and Epigenomics Subcommittee members organized and participated several epigenetic sections associated with various international conferences in 2018. These were held at Plant Genomes Conference and Gordon Research Conference in US, ASPB meeting in Canada, ICAR and plant epi/genetics symposium in Finland, International Plant Molecular Biology meeting in France, Uppsala Transposable symposium in Sweden, Plant Genomes in a changing environment in UK, Agricultural Bioscience International Conference, and Cold Spring Harbor Asia meeting in China. The Subcommittee members have also organized laboratory workshop on cell type-specific nuclei purification by INTACT at Frontiers and Techniques in Plant Science at CSHL.

    The combined activities of Subcommittee members have enhanced the appreciation of the importance of epigenetic regulation in plant biology, boosted the interests, and strengthened international collaborations and coordination to understand the roles and regulation of plant epigenetics/epigenomics. The epigenetic research has also attracted a large amount of interests from the media and general public.

    Future Activities of the Subcommittee.


    The Epigenetics and Epigenomics Subcommittee members plan to organize epigenetic section in conjunction with several international meetings, including Plant & Animal Genomes Conference in San Diego, Japanese Society of Plant Physiologists 60th Annual Meeting, ICAR2019 in China, European workshop on plant chromatin in MPI Cologne, CSHL Frontiers and Techniques in Plant Science, and Symposium on Impact of Nuclear Domains On Plant Phenotypes in Spain.

    The subcommittee members will also organize the European workshop on plant chromatin and laboratory workshop on cell type-specific nuclei purification by INTACT at Frontiers and Techniques in Plant Science at CSHL in 2019.

    Conferences and Workshops

    2018

    Plant & Animal Genomes Conference, San Diego, CA, January 2018 (Session on Epigenomics of Plants International Consortium)

    Institut Jean-Pierre Bourgin symposium, Versailles, France, March 2018 (Session on Epigenomics)

    Cold Spring Harbor Asia meeting on Chromatin, Epigenetics & Transcription, Suzhou, China, April 2018 (Section on Epigenetic inheritance and Plant Epigenetics)

    Gordon Research Conference, Plant Molecular Biology. Holderness, NH, June 2018 (Session on Epigenetics)

    Midwest Chromatin & Epigenetics meeting, West Lafayette, IN, June 2018 (Session on Plant Epigenetics)

    CSHL Frontiers and Techniques in Plant Science, CSHL, NY, June 2018

    American Society for Plant Biologist, Montreal, Canada, July 2018 (Session on Plant Epigenetics)

    29th International Conference on Arabidopsis Research, Turku, Finland, June 2018 (Session on Epigenetics)

    International Plant Molecular Biology meeting, Montpellier, France, August 2018 (Session on plant Epigenetics)

    Agricultural Bioscience International Conference, Weifang, Shangdong, China, September 2018 (Session on plant Epigenetics)

    International plant epi/genetics symposium, Angers, France, October 2018

    UW-Madison Epigenetics symposium, Madison, WI, October 2018

    2nd Uppsala Transposon symposium, Uppsala, Sweden, October 2018

    Plant Genomes in a changing environment, Cambridge, UK, October 2018


    2019

    Plant & Animal Genomes Conference, San Diego, CA, January 2019 (Session on Plant Epigenetics & Epigenomics)

    Japanese Society of Plant Physiologists 60th Annual Meeting, Nagoya, Japan, March 2019 (Session on inheritance and rewriting of cellular memory in plants)

    30th International Conference on Arabidopsis Research, Wuhan, China, June 2019 (Plenary and concurrent sessions on Epigenetics)

    European workshop on plant chromatin, MPI Cologne, June 2019

    CSHL Frontiers and Techniques in Plant Science, CSHL, NY, June 2018

    Symposium on Impact of Nuclear Domains On Plant Phenotypes, Madrid, Spain, December 2019

    2020

    Plant Epigenetics, Japan (hosted by Keiko Sugimoto and Toshiro Ito) Date:TBD 2020

    Selected Publications

    1) Targeted DNA demethylation of the Arabidopsis genome using the human TET1 catalytic domain (PNAS, 2018)
    2) Paternal easiRNAs regulate parental genome dosage in Arabidopsis (Nature Genetics, 2018)
    3) Epigenetic activation of meiotic recombination near Arabidopsis thaliana centromeres via loss of H3K9me2 and non-CG DNA methylation (Genome Research, 2018)
    4) Partial maintenance of organ-specific epigenetic marks during plant asexual reproduction leads to heritable phenotypic variation (PNAS, 2018)
    5) Embryonic epigenetic reprogramming by a pioneer transcription factor in plants (Nature, 2018)

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

    Recently developed Open Tools and Resources for Arabidopsis Researchers

    http://plasma.riken.jp/
    PlaSMA – Plant Specialized Metabolome Annotation
    The comprehensive structural characterization in mass spectrometry-based plant metabolome using the advanced computational mass spectrometry with fully 13C-labeled plant materials and MS/MS spectral information.

    https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.8b04096/suppl_file/ac8b04096_si_001.pdf
    MetNet – R aiding metabolite annotation
    The metabolite network prediction from high-resolution mass spectrometry data - MetNet uses both structural and quantitative information on high-resolution mass spectrometry-based metabolomics data for network inference and enables the annotation of unknown analytes. (Naake and Fernie, 2019, Anal Chem. 91, 1768-1772)

    https://www.ebi.ac.uk/metabolights/MTBLS528
    Data resource: Metabolomics data deposited in MetaboLights (MTBLS528) - the natural variance of the Arabidopsis floral secondary metabolites (Tohge et al., 2018, Scientific Data, 5, 180051)

    Recent activities of Subcommittee members.

    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. 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 Activities of the Subcommittee.

    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. The web interface will provide user with a user-friendly tool to search for Arabidopsis thaliana metabolomics data in available databases. In addition, the people in plant metabolomics community actively provide open tools and resources useful for Arabidopsis researchers as indicated above

    Conferences, Workshops and Training events

    2018/6/18-22
    MU Metabolomics Workshop, Metabolomics Center, University of Missouri, US

    2018/6/24-28
    Metabolomics 2018 (In partnership with The Plant Metabolomics Forum), Seattle, Washington, US

    2018/7/8-13
    The 23rd International Symposium on Plant Lipids, Yokohama, Japan

    2018/11/19-20
    Multi-omics approach in plant systems biology 2018, Bangkok, Thailand

    2019/6/16-21
    Gordon Research Conference, Plant Metabolic Engineering, Castelvecchio Pascoli, Italy

    2019/6/23-27
    Metabolomics 2019, The Hague, The Netherlands

    Selected Publications

    Ohnishi, M., et al.,
    Molecular components of Arabidopsis intact vacuoles clarified with metabolomic and proteomic analyses. Plant Cell Physiol., 59, 1353–1362  (2018)

    Higashi, Y., et al.,
    HEAT INDUCIBLE LIPASE1 remodels chloroplastic monogalactosyldiacylglycerol by liberating α-linolenic acid in Arabidopsis leaves under heat stress. Plant Cell, 30, 1887-1905 (2018)

    da Fonseca-Pereira, P., et al.,
    The Mitochondrial Thioredoxin System Contributes to the Metabolic Responses Under Drought Episodes in Arabidopsis. Plant Cell Physiology, 60, 213-229 (2018)

    Wu, S., et al.,
    Mapping the Arabidopsis metabolic landscape by untargeted metabolomics at different environmental conditions. Molecular Plants, 11, 118-134 (2018)

    Tsugawa, H., et al.,
    A cheminformatics approach to characterize metabolomes in stable isotope-labeled organisms. Nature Methods, DOI : 10.1038/s41592-019-0358-2, in press (2019)

     

  • 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), University of Melbourne

    This email address is being protected from spambots. You need JavaScript enabled to view it.
    http://www.masc-proteomics.org/

    Recently developed Open Tools and Resources for Arabidopsis Researchers

    The subcommittee has been committed to the task of data centralization and visualization. Over the past year, we have transitioned the non-synonymous SNP data currently housed at 1001Proteomes to the ePlant resource.

    The SUBA database has been expanded to contain a new module (Multiple Marker Abundance Profiling) that provides an estimate of organelle distribution from a list of AGIs as the result of a proteomic survey.
    http://suba.live/toolbox-app.html

    Recent activities of Subcommittee members.

    The members of the proteomics subcommittee (MAACP) maintain a range of online resources with a focus on collating data associated with Arabidopsis proteins. Many of these resources house extensive proteomic data from experiments conducted on Arabidopsis and other species. They provide a visual interface to these data and many are linked through a central repository, the MASCP Gator.
    http://gator.masc-proteomics.org/


    Future Activities of the Subcommittee.

    As part of data and resource consolidations, the subcommittee will port proteomic data into ePlant to provide information about proteins e.g. abundance, protein evidence and post-translational modifications.

    Selected Publications

    Linthwaite VL, Janus JM, Brown AP, Wong-Pascua D, O’Donoghue AC, Porter A, Treumann A, Hodgson DRW, Cann MJ (2018) The identification of carbon dioxide mediated protein post-translational modifications. Nat Commun 9: 3092

    Pu Y, Walley JW, Shen Z, Lang M, Briggs SP, Estelle M, Kelley D (2019) Quantitative early auxin root proteomics identifies GAUT10, a galacturonosyltransferase, as a novel regulator of root meristem maintenance. Mol Cell Proteomics https://doi.org/10.1074/mcp.RA119.001378

    Van Leene J, Han C, Gadeyne A, Eeckhout D, Matthijs C, Cannoot B, De Winne N, Persiau G, Van De Slijke E, Van de Cotte B, Stes E, Van Bel M, Storme V, Impens F, Gevaert K, Vandepoele K, De Smet I, De Jaeger G (2019) Capturing the phosphorylation and protein interaction landscape of the plant TOR kinase. Nat Plants 5: 316-327

    Wong MM, Bhaskara GB, Wen TN, Lin WD, Nguyen TT, Chong GL, Verslues PE (2019) Phosphoproteomics of Arabidopsis Highly ABA-Induced1 identifies AT-Hook-Like10 phosphorylation required for stress growth regulation. Proc Natl Acad Sci USA 116: 2354-2363

    Zeng W, Ford KL, Bacic A, Heazlewood JL (2018) N-glycan micro-heterogeneity in glycoproteins of Arabidopsis. Mol Cell Proteomics 17: 413-421

     

  • Systems and Synthetic Biology Open or Close

    By Siobhan Brady (chair) with contributions from subcommittee members Gloria Coruzzi, Gabriel Krouk

    Prepared by
    Siobhan Brady, UC Davis
    This email address is being protected from spambots. You need JavaScript enabled to view it.

    Recently developed Open Tools and Resources for Arabidopsis Researchers

    - Dong et al (2018) Plant Physiology. Proteome-wide, Structure-Based Prediction of Protein-Protein Interactions/New Molecular Interactions Viewer. 1789(4):1893-1907.

    - Crozet et al(2018) ACS Synthetic Biology Birth of a Photosynthetic Chassis: A MoClo Toolkit Enabling Synthetic Biology in the Microalga Chlamydomonas reinhardtii ACS Synthetic Biology 7 (9), pp 2074–2086

    - Pollak et al (2019) Loop Assembly: a simple and open system for recursive fabrication of DNA circuits New Phytologist 222; 628-640

    - Ravendran et al (2019) CyanoGate: A modular cloning suite for engineering cyanobacteria based on the plant MoClo syntax Plant Physiology DOI: https://doi.org/10.1104/pp.18.014

    - BOOK: Plant Genome Editing with CRISPR Systems (2019)  Methods in Molecular Biology Volume 1917, Editor: Yiping Qi https://doi.org/10.1007/978-1-4939-8991-

    Conferences, Workshops and Training events

    - Gordon Conference on Plant Molecular Biology: Dynamic Plant Systems June 10-15, 2018; Chair, Gloria Coruzzi (NYU);  Vice-chair , Rob McClung (Dartmouth)

    - 1st International Plant Systems Biology Meeting: iPSB2018   https://sites.google.com/site/iplantsystemsbiol/pictures

    - EMBO Meeting: Integrating Systems Biology - From Networks to Mechanisms to Models
    Heidelberg, April 2018 - organizers: Pascal Falter-Braun, Sandra Orchard, Sorina Popescu, Luis Serrano, Claudia Falter;

    - SynBio ‘Crossing Kingdoms’, an international event bringing together scientists from the microbial, animal and plant field. 16-18 April 2018, Sainsbury Laboratory at the University of Cambridge, UK

    - Open Plant Forum. 13-26 July 2018, Norwich, UK

    - AIChE 2nd International Conference on Plant Synthetic Biology, Bioengineering, and Biotechnology. November 29
    - December 1, 2018. Clearwater, Florida, USA

    - Banbury Center: Revolutionizing Agriculture with Synthetic Biology, 2-5 December, 2018, Cold Spring Harbor, NY, USA

    - International Association for Plant Biotechnology Congress, 19-24 August, Dublin, Ireland

    Training - Plant Synthetic Biology

    - Synbiosys Summer School, Copenhagen Plant Sciences Centre, Denmark, August 2018

    - The Synthetic and Systems Biology Summer School (SSBSS) Robinson College, University of Cambridge, UK, July 2017

    - GARNet Plant gene editing workshop, March 2018, University of Bristol, UK

    - Synthetic Biology Summer School, 2-6 July 2018 University of Essex, UK

    Future Conferences or Workshops:

    The Subcommittee is planning the 2nd International Plant Systems Biology in 2020, iPSB2020 in Venice!  More details will be released shortly

    Selected Publications

    Gaudinier et al (2018) Transcriptional regulation of nitrogen-associated metabolism. Nature 563(7730):259-264

    Lai et al (2018) Building Transcription Factor Binding Site Models to Understand Gene Regulation in Plants Molecular Plant DOI:https://doi.org/10.1016/j.molp.2018.10.010

    Luo et al(2018) Dynamic DNA methylation: In the right place. At the right time. Science 361:1336-1340.

    South et al (2019) Synthetic glycolate metabolism pathways stimulate crop growth and productivity in the field Science 363; 6422

    Varala et al (2018) Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants. Proc Natl Acad Sci U S A. 115(25):6494