Robustness of plant quantitative disease resistance is provided by a decentralized immune network

Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result fro...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 117; no. 30; pp. 18099 - 18109
Main Authors Delplace, Florent, Huard-Chauveau, Carine, Dubiella, Ullrich, Khafif, Mehdi, Alvarez, Eva, Langin, Gautier, Roux, Fabrice, Peyraud, Rémi, Roby, Dominique
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 28.07.2020
Subjects
Biological Sciences
Complexity
Computational Biology - methods
Deregulation
Disease resistance
Disease Resistance - immunology
Disease Susceptibility - immunology
Gene expression
Gene Expression Profiling
Gene Expression Regulation, Plant
Genes
Genes, Plant
Host-Pathogen Interactions - genetics
Host-Pathogen Interactions - immunology
Immunity
Immunomodulation
Life Sciences
Metabolism
Models, Biological
Modules
Mutation
Natural populations
Pathogens
Phenotype
Phytopathology and phytopharmacy
Plant diseases
Plant Diseases - etiology
Plant Immunity
Protein Interaction Mapping
Protein Interaction Maps
Proteins
Quantitative trait loci
Robustness
Signaling
Transcriptome
Vegetal Biology
systems biology
immunity
quantitative disease resistance
regulatory networks
plant pathogen interactions
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Abstract Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including genomics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in Arabidopsis thaliana in response to the bacterial pathogen Xanthomonas campestris. To tackle this challenge, we first performed a transcriptomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of RKS1, a gene underlying a QTL conferring quantitative and broad-spectrum resistance to X. campestris. RKS1-dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in A. thaliana. Protein–protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five genemodules. Finally, knockoutmutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules participate partially in RKS1-mediated resistance. However, these functional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR network, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides comprehensive understanding of a QDR immune network.
AbstractList Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including genomics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in Arabidopsis thaliana in response to the bacterial pathogen Xanthomonas campestris To tackle this challenge, we first performed a transcriptomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of RKS1, a gene underlying a QTL conferring quantitative and broad-spectrum resistance to XcampestrisRKS1-dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in Athaliana Protein-protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five gene modules. Finally, knockout mutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules participate partially in RKS1-mediated resistance. However, these functional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR network, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides comprehensive understanding of a QDR immune network.
Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including genomics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in in response to the bacterial pathogen To tackle this challenge, we first performed a transcriptomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of , a gene underlying a QTL conferring quantitative and broad-spectrum resistance to -dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in Protein-protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five gene modules. Finally, knockout mutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules participate partially in RKS1-mediated resistance. However, these functional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR network, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides comprehensive understanding of a QDR immune network.
Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including genomics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in Arabidopsis thaliana in response to the bacterial pathogen Xanthomonas campestris. To tackle this challenge, we first performed a transcriptomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of RKS1, a gene underlying a QTL conferring quantitative and broad-spectrum resistance to X. campestris. RKS1-dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in A. thaliana. Protein–protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five genemodules. Finally, knockoutmutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules participate partially in RKS1-mediated resistance. However, these functional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR network, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides comprehensive understanding of a QDR immune network.
Significance Molecular studies of plant immune responses have mainly focused on qualitative resistance, a form of immunity determined by a few large effect genes. In contrast, very limited information exists about quantitative disease resistance (QDR), although it is extensively observed in wild and crop species. We used systems biology approaches to describe this form of immunity in Arabidopsis thaliana . On the basis of gene regulation studies and search for protein–protein interactions, we report the reconstruction of a highly interconnected and distributed network, organized in five modules with differential robustness to genetic mutations. These studies revealed key functions of QDR, mainly distinct from those previously identified for plant immunity, and shed some light on the complexity of this plant immune response. Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including genomics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in Arabidopsis thaliana in response to the bacterial pathogen Xanthomonas campestris . To tackle this challenge, we first performed a transcriptomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of RKS1 , a gene underlying a QTL conferring quantitative and broad-spectrum resistance to X . campestris . RKS1 -dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in A . thaliana . Protein–protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five gene modules. Finally, knockout mutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules participate partially in RKS1-mediated resistance. However, these functional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR network, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides comprehensive understanding of a QDR immune network.
Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including geno-mics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in Arabidopsis thaliana in response to the bacterial pathogen Xanthomonas cam-pestris. To tackle this challenge, we first performed a transcrip-tomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of RKS1, a gene underlying a QTL conferring quantitative and broad-spectrum re-sistance to X. campestris. RKS1-dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in A. thaliana. Protein-protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five gene modules. Finally, knockout mutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules par-ticipate partially in RKS1-mediated resistance. However, these func-tional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR net-work, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides com-prehensive understanding of a QDR immune network.
Molecular studies of plant immune responses have mainly focused on qualitative resistance, a form of immunity determined by a few large effect genes. In contrast, very limited information exists about quantitative disease resistance (QDR), although it is extensively observed in wild and crop species. We used systems biology approaches to describe this form of immunity in Arabidopsis thaliana . On the basis of gene regulation studies and search for protein–protein interactions, we report the reconstruction of a highly interconnected and distributed network, organized in five modules with differential robustness to genetic mutations. These studies revealed key functions of QDR, mainly distinct from those previously identified for plant immunity, and shed some light on the complexity of this plant immune response. Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including genomics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in Arabidopsis thaliana in response to the bacterial pathogen Xanthomonas campestris . To tackle this challenge, we first performed a transcriptomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of RKS1 , a gene underlying a QTL conferring quantitative and broad-spectrum resistance to X . campestris . RKS1 -dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in A . thaliana . Protein–protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five gene modules. Finally, knockout mutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules participate partially in RKS1-mediated resistance. However, these functional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR network, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides comprehensive understanding of a QDR immune network.
Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including genomics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in Arabidopsis thaliana in response to the bacterial pathogen Xanthomonas campestris. To tackle this challenge, we first performed a transcriptomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of RKS1, a gene underlying a QTL conferring quantitative and broad-spectrum resistance to X. campestris. RKS1-dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in A. thaliana. Protein–protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five gene modules. Finally, knockout mutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules participate partially in RKS1-mediated resistance. However, these functional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR network, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides comprehensive understanding of a QDR immune network.
Author Roux, Fabrice
Peyraud, Rémi
Roby, Dominique
Dubiella, Ullrich
Langin, Gautier
Delplace, Florent
Huard-Chauveau, Carine
Khafif, Mehdi
Alvarez, Eva
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Cites_doi 10.15252/embj.201796529
10.2135/cropsci2010.08.0459
10.1126/science.aat2623
10.3389/fpls.2017.00763
10.1105/tpc.17.00970
10.1094/MPMI-20-12-1512
10.1111/tpj.13429
10.1126/science.aav5870
10.1038/417459a
10.1186/s12864-018-4513-4
10.1371/journal.ppat.1001011
10.1111/nph.15419
10.1371/journal.pgen.1000772
10.1016/j.semcdb.2016.05.015
10.1111/j.1365-313X.2005.02525.x
10.1126/science.1166453
10.1073/pnas.1009056107
10.1016/j.pbi.2004.07.013
10.1371/journal.pgen.1000894
10.1016/j.chom.2015.08.004
10.1016/j.molp.2017.07.001
10.1038/nrg.2017.82
10.1016/j.chom.2013.12.002
10.1111/mpp.12138
10.1186/s12864-018-5012-3
10.1016/j.tcb.2014.03.008
10.1002/9781119312994.apr0665
10.1111/j.1574-6968.1998.tb13045.x
10.1186/s12915-016-0235-8
10.1104/pp.114.254292
10.1042/BSR20150226
10.1038/s41467-018-04632-8
10.1111/j.1364-3703.2005.00287.x
10.1038/nrg1471
10.1371/journal.pgen.1003766
10.1371/journal.ppat.1007447
10.1146/annurev-phyto-080614-115928
10.1016/j.jsb.2014.02.005
10.1038/s41396-018-0152-7
10.1073/pnas.1502522112
10.1094/PD-64-736
10.1038/ng.3919
10.1371/journal.pgen.1006639
10.1146/annurev-arplant-050213-040012
10.1105/tpc.16.00915
10.1186/s12864-018-5072-4
10.1093/nar/gky1079
10.1371/journal.pbio.2005956
10.1101/488171
10.1371/journal.pgen.1002208
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Issue 30
Keywords systems biology
immunity
quantitative disease resistance
regulatory networks
plant pathogen interactions
Language English
License Distributed under a Creative Commons Attribution 4.0 International License: http://creativecommons.org/licenses/by/4.0
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PMCID: PMC7395444
Edited by Paul Schulze-Lefert, Max Planck Institute for Plant Breeding Research, Cologne, Germany, and approved June 15, 2020 (received for review January 3, 2020)
Author contributions: R.P. and D.R. designed research; F.D., C.H.-C., U.D., M.K., E.A., and G.L. performed research; F.D., C.H.-C., U.D., M.K., E.A., G.L., F.R., R.P., and D.R. analyzed data; and F.D., C.H.-C., F.R., R.P., and D.R. wrote the paper.
1F.D. and C.H.-C. contributed equally to this work.
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PublicationYear 2020
Publisher National Academy of Sciences
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References e_1_3_4_3_2
e_1_3_4_9_2
e_1_3_4_7_2
e_1_3_4_40_2
e_1_3_4_5_2
e_1_3_4_23_2
e_1_3_4_44_2
e_1_3_4_21_2
e_1_3_4_42_2
e_1_3_4_27_2
e_1_3_4_48_2
e_1_3_4_25_2
e_1_3_4_29_2
e_1_3_4_30_2
e_1_3_4_51_2
e_1_3_4_11_2
e_1_3_4_34_2
e_1_3_4_32_2
e_1_3_4_15_2
e_1_3_4_38_2
e_1_3_4_13_2
e_1_3_4_36_2
e_1_3_4_19_2
e_1_3_4_17_2
e_1_3_4_2_2
Poland J. A. (e_1_3_4_1_2) 2008; 14
e_1_3_4_8_2
e_1_3_4_41_2
e_1_3_4_6_2
e_1_3_4_4_2
e_1_3_4_22_2
e_1_3_4_45_2
e_1_3_4_20_2
e_1_3_4_43_2
e_1_3_4_26_2
e_1_3_4_49_2
e_1_3_4_24_2
e_1_3_4_47_2
e_1_3_4_28_2
e_1_3_4_50_2
e_1_3_4_12_2
e_1_3_4_33_2
e_1_3_4_10_2
e_1_3_4_31_2
e_1_3_4_16_2
e_1_3_4_37_2
Hammarén H. M. (e_1_3_4_46_2) 2015; 36
e_1_3_4_14_2
e_1_3_4_35_2
e_1_3_4_18_2
e_1_3_4_39_2
References_xml – ident: e_1_3_4_18_2
  doi: 10.15252/embj.201796529
– ident: e_1_3_4_13_2
  doi: 10.2135/cropsci2010.08.0459
– ident: e_1_3_4_21_2
  doi: 10.1126/science.aat2623
– ident: e_1_3_4_5_2
  doi: 10.3389/fpls.2017.00763
– ident: e_1_3_4_31_2
  doi: 10.1105/tpc.17.00970
– ident: e_1_3_4_23_2
  doi: 10.1094/MPMI-20-12-1512
– ident: e_1_3_4_19_2
  doi: 10.1111/tpj.13429
– ident: e_1_3_4_29_2
  doi: 10.1126/science.aav5870
– ident: e_1_3_4_49_2
  doi: 10.1038/417459a
– ident: e_1_3_4_14_2
  doi: 10.1186/s12864-018-4513-4
– ident: e_1_3_4_16_2
  doi: 10.1371/journal.ppat.1001011
– ident: e_1_3_4_10_2
  doi: 10.1111/nph.15419
– ident: e_1_3_4_38_2
  doi: 10.1371/journal.pgen.1000772
– ident: e_1_3_4_6_2
  doi: 10.1016/j.semcdb.2016.05.015
– ident: e_1_3_4_45_2
  doi: 10.1111/j.1365-313X.2005.02525.x
– ident: e_1_3_4_7_2
  doi: 10.1126/science.1166453
– ident: e_1_3_4_32_2
  doi: 10.1073/pnas.1009056107
– ident: e_1_3_4_15_2
  doi: 10.1016/j.pbi.2004.07.013
– ident: e_1_3_4_40_2
  doi: 10.1371/journal.pgen.1000894
– ident: e_1_3_4_28_2
  doi: 10.1016/j.chom.2015.08.004
– ident: e_1_3_4_41_2
  doi: 10.1016/j.molp.2017.07.001
– ident: e_1_3_4_4_2
  doi: 10.1038/nrg.2017.82
– ident: e_1_3_4_39_2
  doi: 10.1016/j.chom.2013.12.002
– ident: e_1_3_4_2_2
  doi: 10.1111/mpp.12138
– ident: e_1_3_4_35_2
  doi: 10.1186/s12864-018-5012-3
– ident: e_1_3_4_26_2
  doi: 10.1016/j.tcb.2014.03.008
– ident: e_1_3_4_43_2
  doi: 10.1002/9781119312994.apr0665
– ident: e_1_3_4_50_2
  doi: 10.1111/j.1574-6968.1998.tb13045.x
– ident: e_1_3_4_47_2
  doi: 10.1186/s12915-016-0235-8
– ident: e_1_3_4_12_2
  doi: 10.1104/pp.114.254292
– volume: 36
  start-page: e00282
  year: 2015
  ident: e_1_3_4_46_2
  article-title: Nucleotide-binding mechanisms in pseudokinases
  publication-title: Biosci. Rep.
  doi: 10.1042/BSR20150226
  contributor:
    fullname: Hammarén H. M.
– ident: e_1_3_4_33_2
  doi: 10.1038/s41467-018-04632-8
– ident: e_1_3_4_30_2
  doi: 10.1111/j.1364-3703.2005.00287.x
– ident: e_1_3_4_20_2
  doi: 10.1038/nrg1471
– ident: e_1_3_4_25_2
  doi: 10.1371/journal.pgen.1003766
– ident: e_1_3_4_44_2
  doi: 10.1371/journal.ppat.1007447
– ident: e_1_3_4_42_2
  doi: 10.1146/annurev-phyto-080614-115928
– ident: e_1_3_4_27_2
  doi: 10.1016/j.jsb.2014.02.005
– ident: e_1_3_4_24_2
  doi: 10.1038/s41396-018-0152-7
– ident: e_1_3_4_9_2
  doi: 10.1073/pnas.1502522112
– ident: e_1_3_4_22_2
  doi: 10.1094/PD-64-736
– ident: e_1_3_4_8_2
  doi: 10.1038/ng.3919
– ident: e_1_3_4_17_2
  doi: 10.1371/journal.pgen.1006639
– ident: e_1_3_4_48_2
  doi: 10.1146/annurev-arplant-050213-040012
– ident: e_1_3_4_3_2
  doi: 10.1105/tpc.16.00915
– ident: e_1_3_4_36_2
  doi: 10.1186/s12864-018-5072-4
– volume: 14
  start-page: 1360
  year: 2008
  ident: e_1_3_4_1_2
  article-title: Shades of gray: The world of quantitative disease resistance
  publication-title: Trends Plant Sci.
  contributor:
    fullname: Poland J. A.
– ident: e_1_3_4_51_2
  doi: 10.1093/nar/gky1079
– ident: e_1_3_4_34_2
  doi: 10.1371/journal.pbio.2005956
– ident: e_1_3_4_11_2
  doi: 10.1101/488171
– ident: e_1_3_4_37_2
  doi: 10.1371/journal.pgen.1002208
SSID ssj0009580
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Snippet Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information...
Significance Molecular studies of plant immune responses have mainly focused on qualitative resistance, a form of immunity determined by a few large effect...
Molecular studies of plant immune responses have mainly focused on qualitative resistance, a form of immunity determined by a few large effect genes. In...
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SourceType Open Access Repository
Aggregation Database
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StartPage 18099
SubjectTerms Biological Sciences
Complexity
Computational Biology - methods
Deregulation
Disease resistance
Disease Resistance - immunology
Disease Susceptibility - immunology
Gene expression
Gene Expression Profiling
Gene Expression Regulation, Plant
Genes
Genes, Plant
Host-Pathogen Interactions - genetics
Host-Pathogen Interactions - immunology
Immunity
Immunomodulation
Life Sciences
Metabolism
Models, Biological
Modules
Mutation
Natural populations
Pathogens
Phenotype
Phytopathology and phytopharmacy
Plant diseases
Plant Diseases - etiology
Plant Immunity
Protein Interaction Mapping
Protein Interaction Maps
Proteins
Quantitative trait loci
Robustness
Signaling
Transcriptome
Vegetal Biology
Title Robustness of plant quantitative disease resistance is provided by a decentralized immune network
URI https://www.jstor.org/stable/26935539
https://www.ncbi.nlm.nih.gov/pubmed/32669441
https://www.proquest.com/docview/2428559397
https://search.proquest.com/docview/2424444368
https://hal.science/hal-03006687
https://pubmed.ncbi.nlm.nih.gov/PMC7395444
Volume 117
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