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      Understanding Host–Pathogen Interactions in Brassica napus in the Omics Era

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          Abstract

          Brassica napus (canola/oilseed rape/rapeseed) is an economically important crop, mostly found in temperate and sub-tropical regions, that is cultivated widely for its edible oil. Major diseases of Brassica crops such as Blackleg, Clubroot, Sclerotinia Stem Rot, Downy Mildew, Alternaria Leaf Spot and White Rust have caused significant yield and economic losses in rapeseed-producing countries worldwide, exacerbated by global climate change, and, if not remedied effectively, will threaten global food security. To gain further insights into the host–pathogen interactions in relation to Brassica diseases, it is critical that we review current knowledge in this area and discuss how omics technologies can offer promising results and help to push boundaries in our understanding of the resistance mechanisms. Omics technologies, such as genomics, proteomics, transcriptomics and metabolomics approaches, allow us to understand the host and pathogen, as well as the interaction between the two species at a deeper level. With these integrated data in multi-omics and systems biology, we are able to breed high-quality disease-resistant Brassica crops in a more holistic, targeted and accurate way.

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          Most cited references233

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            SignalP 5.0 improves signal peptide predictions using deep neural networks

            Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish between various types of signal peptides. We present a deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs.
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              RNA-Seq: a revolutionary tool for transcriptomics.

              RNA-Seq is a recently developed approach to transcriptome profiling that uses deep-sequencing technologies. Studies using this method have already altered our view of the extent and complexity of eukaryotic transcriptomes. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods. This article describes the RNA-Seq approach, the challenges associated with its application, and the advances made so far in characterizing several eukaryote transcriptomes.
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                Author and article information

                Journal
                Plants (Basel)
                Plants (Basel)
                plants
                Plants
                MDPI
                2223-7747
                10 October 2020
                October 2020
                : 9
                : 10
                : 1336
                Affiliations
                [1 ]Sunway College Kuala Lumpur, Bandar Sunway 47500, Selangor, Malaysia; tingxiang@ 123456gmail.com
                [2 ]School of Biological Sciences and Institute of Agriculture, The University of Western Australia, Perth 6009, Australia; junrey.amas@ 123456research.uwa.edu.au (J.A.); dave.edwards@ 123456uwa.edu.au (D.E.)
                [3 ]School of Agriculture and Environment and Institute of Agriculture, The University of Western Australia, Perth 6009, Australia; martin.barbetti@ 123456uwa.edu.au
                Author notes
                Author information
                https://orcid.org/0000-0002-2816-0458
                https://orcid.org/0000-0001-7599-6760
                https://orcid.org/0000-0002-5391-5824
                Article
                plants-09-01336
                10.3390/plants9101336
                7599536
                33050509
                52e4cd13-a986-4c86-b82a-4ec0f21f1581
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 September 2020
                : 06 October 2020
                Categories
                Review

                brassica napus,host–pathogen interaction,pathosystems,omics,next-generation sequencing (ngs),pangenomics,secretomics,bioinformatics

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