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      The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression

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          Abstract

          Background

          Understanding how plants and pathogens modulate gene expression during the host-pathogen interaction is key to uncovering the molecular mechanisms that regulate disease progression. Recent advances in sequencing technologies have provided new opportunities to decode the complexity of such interactions. In this study, we used an RNA-based sequencing approach (RNA-seq) to assess the global expression profiles of the wheat yellow rust pathogen Puccinia striiformis f. sp. tritici (PST) and its host during infection.

          Results

          We performed a detailed RNA-seq time-course for a susceptible and a resistant wheat host infected with PST. This study (i) defined the global gene expression profiles for PST and its wheat host, (ii) substantially improved the gene models for PST, (iii) evaluated the utility of several programmes for quantification of global gene expression for PST and wheat, and (iv) identified clusters of differentially expressed genes in the host and pathogen. By focusing on components of the defence response in susceptible and resistant hosts, we were able to visualise the effect of PST infection on the expression of various defence components and host immune receptors.

          Conclusions

          Our data showed sequential, temporally coordinated activation and suppression of expression of a suite of immune-response regulators that varied between compatible and incompatible interactions. These findings provide the framework for a better understanding of how PST causes disease and support the idea that PST can suppress the expression of defence components in wheat to successfully colonize a susceptible host.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-016-2684-4) contains supplementary material, which is available to authorized users.

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          Most cited references38

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          Identification of novel transcripts in annotated genomes using RNA-Seq.

          We describe a new 'reference annotation based transcript assembly' problem for RNA-Seq data that involves assembling novel transcripts in the context of an existing annotation. This problem arises in the analysis of expression in model organisms, where it is desirable to leverage existing annotations for discovering novel transcripts. We present an algorithm for reference annotation-based transcript assembly and show how it can be used to rapidly investigate novel transcripts revealed by RNA-Seq in comparison with a reference annotation. The methods described in this article are implemented in the Cufflinks suite of software for RNA-Seq, freely available from http://bio.math.berkeley.edu/cufflinks. The software is released under the BOOST license. cole@broadinstitute.org; lpachter@math.berkeley.edu Supplementary data are available at Bioinformatics online.
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            Plant PRRs and the activation of innate immune signaling.

            Despite being sessile organisms constantly exposed to potential pathogens and pests, plants are surprisingly resilient to infections. Plants can detect invaders via the recognition of pathogen-associated molecular patterns (PAMPs) by pattern recognition receptors (PRRs). Plant PRRs are surface-localized receptor-like kinases, which comprise a ligand-binding ectodomain and an intracellular kinase domain, or receptor-like proteins, which do not exhibit any known intracellular signaling domain. In this review, we summarize recent discoveries that shed light on the molecular mechanisms underlying ligand perception and subsequent activation of plant PRRs. Notably, plant PRRs appear as central components of multiprotein complexes at the plasma membrane that contain additional transmembrane and cytosolic kinases required for the initiation and specificity of immune signaling. PRR complexes are under tight control by protein phosphatases, E3 ligases, and other regulatory proteins, illustrating the exquisite and complex regulation of these molecular machines whose proper activation underlines a crucial layer of plant immunity. Copyright © 2014 Elsevier Inc. All rights reserved.
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              Ensembl Genomes 2016: more genomes, more complexity

              Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces.
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                Author and article information

                Contributors
                diane.saunders@tgac.ac.uk
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                20 May 2016
                20 May 2016
                2016
                : 17
                : 380
                Affiliations
                [ ]John Innes Centre, Norwich Research Park, Norwich, UK
                [ ]The Genome Analysis Centre, Norwich Research Park, Norwich, UK
                [ ]The Sainsbury Laboratory, Norwich Research Park, Norwich, UK
                Article
                2684
                10.1186/s12864-016-2684-4
                4875698
                27207100
                89d33962-6285-4a22-982b-a9a47221ec53
                © Dobon et al. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 24 January 2016
                : 29 April 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/J012017/1
                Award ID: Fellowship in computational biology
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/J004553/1
                Funded by: Marie Skłodowska-Curie Intra-European Fellowship
                Award ID: 301010
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Genetics
                Genetics

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