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Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach
Expression of quantitative disease resistance in many host–pathogen systems is controlled by genes at multiple loci, each contributing a small effect to the overall response. We used a systems genomics approach to study the molecular underpinnings of quantitative disease resistance in the soybean-Ph...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662313/ https://www.ncbi.nlm.nih.gov/pubmed/38023885 http://dx.doi.org/10.3389/fpls.2023.1277585 |
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author | Million, Cassidy R. Wijeratne, Saranga Karhoff, Stephanie Cassone, Bryan J. McHale, Leah K. Dorrance, Anne E. |
author_facet | Million, Cassidy R. Wijeratne, Saranga Karhoff, Stephanie Cassone, Bryan J. McHale, Leah K. Dorrance, Anne E. |
author_sort | Million, Cassidy R. |
collection | PubMed |
description | Expression of quantitative disease resistance in many host–pathogen systems is controlled by genes at multiple loci, each contributing a small effect to the overall response. We used a systems genomics approach to study the molecular underpinnings of quantitative disease resistance in the soybean-Phytophthora sojae pathosystem, incorporating expression quantitative trait loci (eQTL) mapping and gene co-expression network analysis to identify the genes putatively regulating transcriptional changes in response to inoculation. These findings were compared to previously mapped phenotypic (phQTL) to identify the molecular mechanisms contributing to the expression of this resistance. A subset of 93 recombinant inbred lines (RILs) from a Conrad × Sloan population were inoculated with P. sojae isolate 1.S.1.1 using the tray-test method; RNA was extracted, sequenced, and the normalized read counts were genetically mapped from tissue collected at the inoculation site 24 h after inoculation from both mock and inoculated samples. In total, more than 100,000 eQTLs were mapped. There was a switch from predominantly cis-eQTLs in the mock treatment to an almost entirely nonoverlapping set of predominantly trans-eQTLs in the inoculated treatment, where greater than 100-fold more eQTLs were mapped relative to mock, indicating vast transcriptional reprogramming due to P. sojae infection occurred. The eQTLs were organized into 36 hotspots, with the four largest hotspots from the inoculated treatment corresponding to more than 70% of the eQTLs, each enriched for genes within plant–pathogen interaction pathways. Genetic regulation of trans-eQTLs in response to the pathogen was predicted to occur through transcription factors and signaling molecules involved in plant–pathogen interactions, plant hormone signal transduction, and MAPK pathways. Network analysis identified three co-expression modules that were correlated with susceptibility to P. sojae and associated with three eQTL hotspots. Among the eQTLs co-localized with phQTLs, two cis-eQTLs with putative functions in the regulation of root architecture or jasmonic acid, as well as the putative master regulators of an eQTL hotspot nearby a phQTL, represent candidates potentially underpinning the molecular control of these phQTLs for resistance. |
format | Online Article Text |
id | pubmed-10662313 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-106623132023-01-01 Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach Million, Cassidy R. Wijeratne, Saranga Karhoff, Stephanie Cassone, Bryan J. McHale, Leah K. Dorrance, Anne E. Front Plant Sci Plant Science Expression of quantitative disease resistance in many host–pathogen systems is controlled by genes at multiple loci, each contributing a small effect to the overall response. We used a systems genomics approach to study the molecular underpinnings of quantitative disease resistance in the soybean-Phytophthora sojae pathosystem, incorporating expression quantitative trait loci (eQTL) mapping and gene co-expression network analysis to identify the genes putatively regulating transcriptional changes in response to inoculation. These findings were compared to previously mapped phenotypic (phQTL) to identify the molecular mechanisms contributing to the expression of this resistance. A subset of 93 recombinant inbred lines (RILs) from a Conrad × Sloan population were inoculated with P. sojae isolate 1.S.1.1 using the tray-test method; RNA was extracted, sequenced, and the normalized read counts were genetically mapped from tissue collected at the inoculation site 24 h after inoculation from both mock and inoculated samples. In total, more than 100,000 eQTLs were mapped. There was a switch from predominantly cis-eQTLs in the mock treatment to an almost entirely nonoverlapping set of predominantly trans-eQTLs in the inoculated treatment, where greater than 100-fold more eQTLs were mapped relative to mock, indicating vast transcriptional reprogramming due to P. sojae infection occurred. The eQTLs were organized into 36 hotspots, with the four largest hotspots from the inoculated treatment corresponding to more than 70% of the eQTLs, each enriched for genes within plant–pathogen interaction pathways. Genetic regulation of trans-eQTLs in response to the pathogen was predicted to occur through transcription factors and signaling molecules involved in plant–pathogen interactions, plant hormone signal transduction, and MAPK pathways. Network analysis identified three co-expression modules that were correlated with susceptibility to P. sojae and associated with three eQTL hotspots. Among the eQTLs co-localized with phQTLs, two cis-eQTLs with putative functions in the regulation of root architecture or jasmonic acid, as well as the putative master regulators of an eQTL hotspot nearby a phQTL, represent candidates potentially underpinning the molecular control of these phQTLs for resistance. Frontiers Media S.A. 2023-11-07 /pmc/articles/PMC10662313/ /pubmed/38023885 http://dx.doi.org/10.3389/fpls.2023.1277585 Text en Copyright © 2023 Million, Wijeratne, Karhoff, Cassone, McHale and Dorrance https://creativecommons.org/licenses/by/4.0/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. |
spellingShingle | Plant Science Million, Cassidy R. Wijeratne, Saranga Karhoff, Stephanie Cassone, Bryan J. McHale, Leah K. Dorrance, Anne E. Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach |
title | Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach |
title_full | Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach |
title_fullStr | Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach |
title_full_unstemmed | Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach |
title_short | Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach |
title_sort | molecular mechanisms underpinning quantitative resistance to phytophthora sojae in glycine max using a systems genomics approach |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10662313/ https://www.ncbi.nlm.nih.gov/pubmed/38023885 http://dx.doi.org/10.3389/fpls.2023.1277585 |
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