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| Status |
Public on Jun 14, 2020 |
| Title |
Use of Dual RNA-seq for Systems Biology Analysis of Zea mays and Aspergillus flavus plant microbe interaction |
| Organisms |
Zea mays; Aspergillus flavus |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
The interaction between Aspergillus flavus and Zea mays is complex, and the identification of plant genes and pathways conferring resistance to the fungus has been challenging. Therefore authors undertook a systems biology approach involving dual RNA-seq to determine simultaneous response from the host and pathogen. What was dramatically highlighted in the analysis was upon infection there is uniformity in the development of the host and pathogen. This led to the development of host-pathogen index which was able to categorize the samples for down-stream system biology analysis. Additionally we were able to determine key genes in the pathways such as jasmonate, ethylene and ROS which were up-regulated in the studyThe stage of infection index used for the transcriptomic analysis revealed that A. flavus does not produce many transcripts initially during pathogenesis. It was found that when A. flavus was producing an abundance of transcripts, pathways involved the endosomal transport, aflatoxin production, sugar production and many others were up-regulated. In tandem, Z. mays had multiple resistance pathways, such as the phenylpropaniod, jasmonic acid and ethylene pathways that were up-regulated. The analysis of the gene regulatory networks revealed that multiple WRKY genes were targeting the activation of the resistance pathways. The analysis also revealed, for the first time, the activation of Z. mays resistance genes targeting A. flavus genes. Our results show that the plant-microbe interaction has multiple layers and that A. flavus transcriptionally reacts to the hostile environment of Z. mays. The interaction between Aspergillus flavus and Zea mays is complex, and the identification of plant genes and pathways conferring resistance to the fungus has been challenging. Therefore authors undertook a systems biology approach involving dual RNA-seq to determine simultaneous response from the host and pathogen. What was dramatically highlighted in the analysis was upon infection there is uniformity in the development of the host and pathogen. This led to the development of host-pathogen index which was able to categorize the samples for down-stream system biology analysis. Additionally we were able to determine key genes in the pathways such as jasmonate, ethylene and ROS which were up-regulated in the studyThe stage of infection index used for the transcriptomic analysis revealed that A. flavus does not produce many transcripts initially during pathogenesis. It was found that when A. flavus was producing an abundance of transcripts, pathways involved the endosomal transport, aflatoxin production, sugar production and many others were up-regulated. In tandem, Z. mays had multiple resistance pathways, such as the phenylpropaniod, jasmonic acid and ethylene pathways that were up-regulated. The analysis of the gene regulatory networks revealed that multiple WRKY genes were targeting the activation of the resistance pathways. The analysis also revealed, for the first time, the activation of Z. mays resistance genes targeting A. flavus genes. Our results show that the plant-microbe interaction has multiple layers and that A. flavus transcriptionally reacts to the hostile environment of Z. mays. The interaction between Aspergillus flavus and Zea mays is complex, and the identification of plant genes and pathways conferring resistance to the fungus has been challenging. Therefore authors undertook a systems biology approach involving dual RNA-seq to determine simultaneous response from the host and pathogen. What was dramatically highlighted in the analysis was upon infection there is uniformity in the development of the host and pathogen. This led to the development of host-pathogen index which was able to categorize the samples for down-stream system biology analysis. Additionally we were able to determine key genes in the pathways such as jasmonate, ethylene and ROS which were up-regulated in the studyThe stage of infection index used for the transcriptomic analysis revealed that A. flavus does not produce many transcripts initially during pathogenesis. It was found that when A. flavus was producing an abundance of transcripts, pathways involved the endosomal transport, aflatoxin production, sugar production and many others were up-regulated. In tandem, Z. mays had multiple resistance pathways, such as the phenylpropaniod, jasmonic acid and ethylene pathways that were up-regulated. The analysis of the gene regulatory networks revealed that multiple WRKY genes were targeting the activation of the resistance pathways. The analysis also revealed, for the first time, the activation of Z. mays resistance genes targeting A. flavus genes. Our results show that the plant-microbe interaction has multiple layers and that A. flavus transcriptionally reacts to the hostile environment of Z. mays.
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| Overall design |
B73 maize was innoculated with Aspergillus flavus and samples were collected at 0,4,6,8,12,18,24,30,36,42,48,72,96,120,144 hours post inoculation and analyzed using a dual RNA-seq approach
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| Contributor(s) |
Musungu B, Geisler M, Payne G, Fakhoury A, Obrien G, Bhatnagar D, Brown R |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
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| Submission date |
Jul 26, 2017 |
| Last update date |
Jul 25, 2021 |
| Contact name |
Bryan Manyasi Musungu |
| E-mail(s) |
[email protected]
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| Organization name |
Southern Illinois University Carbondale
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| Department |
Plant Biology
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| Street address |
1125 Lincoln Dr.
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| City |
Carbondale |
| State/province |
IL |
| ZIP/Postal code |
62901 |
| Country |
USA |
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| Platforms (1) |
| GPL23833 |
Illumina HiSeq 2500 (Aspergillus flavus; Zea mays) |
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| Samples (112)
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| Relations |
| BioProject |
PRJNA395908 |
| SRA |
SRP113615 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE101899_RAW.tar |
98.5 Mb |
(http)(custom) |
TAR (of CSV) |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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