Literature DB >> 18323815

Rice blast infection of Brachypodium distachyon as a model system to study dynamic host/pathogen interactions.

David Parker1, Manfred Beckmann, David P Enot, David P Overy, Zaira Caracuel Rios, Martin Gilbert, Nicholas Talbot, John Draper.   

Abstract

Interactions between plants and compatible fungal pathogens are spatially and temporally dynamic, posing a major challenge for sampling and data analysis. A protocol is described for the infection of the model grass species Brachypodium distachyon with Magnaporthe grisea (rice blast), together with modifications to extend the use to rice and barley. We outline a method for the preparation of long-term stocks of virulent fungal pathogens and for the generation of fungal inoculants for challenge of host plants. Host plant growth, pathogen inoculation and plant sampling protocols are presented together with methods for assessing the efficiency of both infection and sampling procedures. Included in the anticipated results is a description of the use of metabolite fingerprinting and multivariate data analysis to assess disease synchrony and validate system reproducibility between experiments. The design concepts will have value in any studies using biological systems that contain dynamic variance associated with large compositional changes in sample matrix over time.

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Year:  2008        PMID: 18323815     DOI: 10.1038/nprot.2007.499

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  31 in total

1.  A novel blast resistance gene, Pi54rh cloned from wild species of rice, Oryza rhizomatis confers broad spectrum resistance to Magnaporthe oryzae.

Authors:  Alok Das; D Soubam; P K Singh; S Thakur; N K Singh; T R Sharma
Journal:  Funct Integr Genomics       Date:  2012-05-17       Impact factor: 3.410

Review 2.  Plant immune responses against viruses: how does a virus cause disease?

Authors:  Kranthi K Mandadi; Karen-Beth G Scholthof
Journal:  Plant Cell       Date:  2013-05-24       Impact factor: 11.277

3.  Diversity and association of phenotypic and metabolomic traits in the close model grasses Brachypodium distachyon, B. stacei and B. hybridum.

Authors:  Diana López-Álvarez; Hassan Zubair; Manfred Beckmann; John Draper; Pilar Catalán
Journal:  Ann Bot       Date:  2017-03-01       Impact factor: 4.357

4.  Developing japonica rice introgression lines with multiple resistance genes for brown planthopper, bacterial blight, rice blast, and rice stripe virus using molecular breeding.

Authors:  Russell Reinke; Suk-Man Kim; Bo-Kyeong Kim
Journal:  Mol Genet Genomics       Date:  2018-07-05       Impact factor: 3.291

Review 5.  Brachypodium as an emerging model for cereal-pathogen interactions.

Authors:  Timothy L Fitzgerald; Jonathan J Powell; Katharina Schneebeli; M Mandy Hsia; Donald M Gardiner; Jennifer N Bragg; C Lynne McIntyre; John M Manners; Mick Ayliffe; Michelle Watt; John P Vogel; Robert J Henry; Kemal Kazan
Journal:  Ann Bot       Date:  2015-04       Impact factor: 4.357

6.  Structural characterization of Brachypodium genome and its syntenic relationship with rice and wheat.

Authors:  Naxin Huo; John P Vogel; Gerard R Lazo; Frank M You; Yaqin Ma; Stephanie McMahon; Jan Dvorak; Olin D Anderson; Ming-Cheng Luo; Yong Q Gu
Journal:  Plant Mol Biol       Date:  2009-01-29       Impact factor: 4.076

Review 7.  Under pressure: investigating the biology of plant infection by Magnaporthe oryzae.

Authors:  Richard A Wilson; Nicholas J Talbot
Journal:  Nat Rev Microbiol       Date:  2009-03       Impact factor: 60.633

8.  Measurement of dietary exposure: a challenging problem which may be overcome thanks to metabolomics?

Authors:  Gaëlle Favé; M E Beckmann; J H Draper; J C Mathers
Journal:  Genes Nutr       Date:  2009-04-02       Impact factor: 5.523

9.  An efficient method for transient gene expression in monocots applied to modify the Brachypodium distachyon cell wall.

Authors:  Oksana Fursova; Gennady Pogorelko; Olga A Zabotina
Journal:  Ann Bot       Date:  2012-05-14       Impact factor: 4.357

10.  Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'.

Authors:  John Draper; David P Enot; David Parker; Manfred Beckmann; Stuart Snowdon; Wanchang Lin; Hassan Zubair
Journal:  BMC Bioinformatics       Date:  2009-07-21       Impact factor: 3.169

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