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      Advances in Multi-Omics Approaches for Molecular Breeding of Black Rot Resistance in Brassica oleracea L.

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          Abstract

          Brassica oleracea is one of the most important species of the Brassicaceae family encompassing several economically important vegetables produced and consumed worldwide. But its sustainability is challenged by a range of pathogens, among which black rot, caused by Xanthomonas campestris pv. campestris ( Xcc), is the most serious and destructive seed borne bacterial disease, causing huge yield losses. Host-plant resistance could act as the most effective and efficient solution to curb black rot disease for sustainable production of B. oleracea. Recently, ‘omics’ technologies have emerged as promising tools to understand the host-pathogen interactions, thereby gaining a deeper insight into the resistance mechanisms. In this review, we have summarized the recent achievements made in the emerging omics technologies to tackle the black rot challenge in B. oleracea. With an integrated approach of the omics technologies such as genomics, proteomics, transcriptomics, and metabolomics, it would allow better understanding of the complex molecular mechanisms underlying black rot resistance. Due to the availability of sequencing data, genomics and transcriptomics have progressed as expected for black rot resistance, however, other omics approaches like proteomics and metabolomics are lagging behind, necessitating a holistic and targeted approach to address the complex questions of Xcc-Brassica interactions. Genomic studies revealed that the black rot resistance is a complex trait and is mostly controlled by quantitative trait locus (QTL) with minor effects. Transcriptomic analysis divulged the genes related to photosynthesis, glucosinolate biosynthesis and catabolism, phenylpropanoid biosynthesis pathway, ROS scavenging, calcium signalling, hormonal synthesis and signalling pathway are being differentially expressed upon Xcc infection. Comparative proteomic analysis in relation to susceptible and/or resistance interactions with Xcc identified the involvement of proteins related to photosynthesis, protein biosynthesis, processing and degradation, energy metabolism, innate immunity, redox homeostasis, and defence response and signalling pathways in XccBrassica interaction. Specifically, most of the studies focused on the regulation of the photosynthesis-related proteins as a resistance response in both early and later stages of infection. Metabolomic studies suggested that glucosinolates (GSLs), especially aliphatic and indolic GSLs, its subsequent hydrolysis products, and defensive metabolites synthesized by jasmonic acid (JA)-mediated phenylpropanoid biosynthesis pathway are involved in disease resistance mechanisms against Xcc in Brassica species. Multi-omics analysis showed that JA signalling pathway is regulating resistance against hemibiotrophic pathogen like Xcc. So, the bonhomie between omics technologies and plant breeding is going to trigger major breakthroughs in the field of crop improvement by developing superior cultivars with broad-spectrum resistance. If multi-omics tools are implemented at the right scale, we may be able to achieve the maximum benefits from the minimum. In this review, we have also discussed the challenges, future prospects, and the way forward in the application of omics technologies to accelerate the breeding of B. oleracea for disease resistance. A deeper insight about the current knowledge on omics can offer promising results in the breeding of high-quality disease-resistant crops.

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          Plant pathogens and integrated defence responses to infection.

          Plants cannot move to escape environmental challenges. Biotic stresses result from a battery of potential pathogens: fungi, bacteria, nematodes and insects intercept the photosynthate produced by plants, and viruses use replication machinery at the host's expense. Plants, in turn, have evolved sophisticated mechanisms to perceive such attacks, and to translate that perception into an adaptive response. Here, we review the current knowledge of recognition-dependent disease resistance in plants. We include a few crucial concepts to compare and contrast plant innate immunity with that more commonly associated with animals. There are appreciable differences, but also surprising parallels.
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            JAZ repressor proteins are targets of the SCF(COI1) complex during jasmonate signalling.

            Jasmonate and related signalling compounds have a crucial role in both host immunity and development in plants, but the molecular details of the signalling mechanism are poorly understood. Here we identify members of the jasmonate ZIM-domain (JAZ) protein family as key regulators of jasmonate signalling. JAZ1 protein acts to repress transcription of jasmonate-responsive genes. Jasmonate treatment causes JAZ1 degradation and this degradation is dependent on activities of the SCF(COI1) ubiquitin ligase and the 26S proteasome. Furthermore, the jasmonoyl-isoleucine (JA-Ile) conjugate, but not other jasmonate-derivatives such as jasmonate, 12-oxo-phytodienoic acid, or methyl-jasmonate, promotes physical interaction between COI1 and JAZ1 proteins in the absence of other plant proteins. Our results suggest a model in which jasmonate ligands promote the binding of the SCF(COI1) ubiquitin ligase to and subsequent degradation of the JAZ1 repressor protein, and implicate the SCF(COI1)-JAZ1 protein complex as a site of perception of the plant hormone JA-Ile.
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              Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets.

              Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with human complex traits. However, the genes or functional DNA elements through which these variants exert their effects on the traits are often unknown. We propose a method (called SMR) that integrates summary-level data from GWAS with data from expression quantitative trait locus (eQTL) studies to identify genes whose expression levels are associated with a complex trait because of pleiotropy. We apply the method to five human complex traits using GWAS data on up to 339,224 individuals and eQTL data on 5,311 individuals, and we prioritize 126 genes (for example, TRAF1 and ANKRD55 for rheumatoid arthritis and SNX19 and NMRAL1 for schizophrenia), of which 25 genes are new candidates; 77 genes are not the nearest annotated gene to the top associated GWAS SNP. These genes provide important leads to design future functional studies to understand the mechanism whereby DNA variation leads to complex trait variation.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                06 December 2021
                2021
                : 12
                : 742553
                Affiliations
                Institute of Vegetables, Zhejiang Academy of Agricultural Sciences , Hangzhou, China
                Author notes

                Edited by: Chunyu Zhang, Huazhong Agricultural University, China

                Reviewed by: Pilar Soengas, Misión Biológica de Galicia, Consejo Superior de Investigaciones Científicas (CSIC), Spain; Guangqin Cai, Oil Crops Research Institute, Chinese Academy of Agricultural Sciences (CAAS), China; Maoteng Li, Huazhong University of Science and Technology, China

                *Correspondence: Honghui Gu, guhh2199@ 123456163.com

                This article was submitted to Plant Breeding, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2021.742553
                8687090
                34938304
                bee6226e-b768-4462-bacc-b07e7ffb2887
                Copyright © 2021 Shaw, Shen, Wang, Sheng, Zhao, Yu and Gu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 16 July 2021
                : 20 October 2021
                Page count
                Figures: 5, Tables: 5, Equations: 0, References: 272, Pages: 34, Words: 27958
                Categories
                Plant Science
                Review

                Plant science & Botany
                brassica oleracea,black rot,xanthomonas campestris pv. campestris,omics,genomics,transcriptomics,proteomics,metabolomics

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