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MAP kinase and plant–pathogen interactions govern male Zizania latifolia responses to Ustilago esculenta during the early stages of infection

Pengfei Guo

Pengfei Guo

Department of Vegetable Science, School of Horticulture, Anhui Agricultural UniversityHefei, Anhui, China
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Guo, Pengfei
, 
Huimin Zhou

Huimin Zhou

Department of Vegetable Science, School of Horticulture, Anhui Agricultural UniversityHefei, Anhui, China
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Zhou, Huimin
, 
Longfei Bai

Longfei Bai

Department of Vegetable Science, School of Horticulture, Anhui Agricultural UniversityHefei, Anhui, China
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Bai, Longfei
, 
Yayu Lin

Yayu Lin

Department of Vegetable Science, School of Horticulture, Anhui Agricultural UniversityHefei, Anhui, China
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Lin, Yayu
, 
Yalong Zhang

Yalong Zhang

Department of Vegetable Science, School of Horticulture, Anhui Agricultural UniversityHefei, Anhui, China
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Zhang, Yalong
, 
Bichen Wang

Bichen Wang

Department of Vegetable Science, School of Horticulture, Anhui Agricultural UniversityHefei, Anhui, China
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Wang, Bichen
, 
Xiaomei He

Xiaomei He

Department of Biotechnology, College of Biological and Pharmaceutical Engineering, West Anhui UniversityLu’an, Anhui, China
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He, Xiaomei
 und 
Defang Gan

Defang Gan

Department of Vegetable Science, School of Horticulture, Anhui Agricultural UniversityHefei, Anhui, China
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Gan, Defang
  
26. Juni 2023
MAP kinase and plant–pathogen interactions govern male Zizania latifolia responses to Ustilago esculenta during the early stages of infection's Cover Image
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Artikel-Kategorie: ORIGINAL ARTICLE
Online veröffentlicht: 26. Juni 2023
Seitenbereich: 149 - 162
Eingereicht: 01. Nov. 2022
Akzeptiert: 07. März 2023
DOI: https://doi.org/10.2478/fhort-2023-0011
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© 2023 Pengfei Guo et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Figure 1.

Clustering heat map of DEGs. (A) CK-3 hr vs. TR-3 hr; (B) CK-12 hr vs. TR-12 hr; and (C) CK-24 hr vs. TR-24 hr. Red indicates upregulation whereas green indicates downregulation, and the darker the colour, the greater the up- or downregulation. DEGs, differentially expressed genes.
Clustering heat map of DEGs. (A) CK-3 hr vs. TR-3 hr; (B) CK-12 hr vs. TR-12 hr; and (C) CK-24 hr vs. TR-24 hr. Red indicates upregulation whereas green indicates downregulation, and the darker the colour, the greater the up- or downregulation. DEGs, differentially expressed genes.

Figure 2.

qPCR verification of DEGs. (A) qPCR analysis of DEGs. Orange represents the treatment group and green represents the control group. (B) Differential gene expression heatmap of transcriptome sequencing data. Orange indicates upregulation whereas green indicates downregulation, and the darker the colour, the more obvious the greater the up or downregulation. DEGs, differentially expressed genes; qPCR, quantitative PCR.
qPCR verification of DEGs. (A) qPCR analysis of DEGs. Orange represents the treatment group and green represents the control group. (B) Differential gene expression heatmap of transcriptome sequencing data. Orange indicates upregulation whereas green indicates downregulation, and the darker the colour, the more obvious the greater the up or downregulation. DEGs, differentially expressed genes; qPCR, quantitative PCR.

Figure 3.

Correlation heatmap of the gene expression network module and different processes (A), and KEGG pathway analysis results of MEturquoise modules (B). (A) The abscissa represents samples, and the ordinate represents modules. The number of each block represents the correlation between modules and samples; the closer the value is to 1, the stronger the positive correlation between modules and samples; the closer the value is to −1, the stronger the negative correlation. The number in brackets represents the significance p-value; the lower the number, the stronger the significance. The darker the colour of the square (the redder), the stronger the correlation; the lighter the colour, the weaker the correlation. KEGG, Kyoto Encyclopedia of Genes and Genomes.
Correlation heatmap of the gene expression network module and different processes (A), and KEGG pathway analysis results of MEturquoise modules (B). (A) The abscissa represents samples, and the ordinate represents modules. The number of each block represents the correlation between modules and samples; the closer the value is to 1, the stronger the positive correlation between modules and samples; the closer the value is to −1, the stronger the negative correlation. The number in brackets represents the significance p-value; the lower the number, the stronger the significance. The darker the colour of the square (the redder), the stronger the correlation; the lighter the colour, the weaker the correlation. KEGG, Kyoto Encyclopedia of Genes and Genomes.

Figure 4.

Analysis of important pathways in CK-3 hr vs. TR-3 hr. (A) Analysis of ‘plant–pathogen interaction’ pathways. (B) Analysis of ‘MAPK signalling pathway-plant’ pathways. Red indicates the treatment group (TR-3 hr) whereas green the control group (CK-3 hr).
Analysis of important pathways in CK-3 hr vs. TR-3 hr. (A) Analysis of ‘plant–pathogen interaction’ pathways. (B) Analysis of ‘MAPK signalling pathway-plant’ pathways. Red indicates the treatment group (TR-3 hr) whereas green the control group (CK-3 hr).

Figure 5.

Analysis of differential gene expression in ‘plant–pathogen interaction’ and ‘MAPK signalling pathway-plant’ pathways. (A) qPCR verification of DEGs. Orange indicates the treatment group whereas green indicates the control group. (B) Differential gene expression heatmap of transcriptome sequencing data. Orange indicates upregulation whereas green indicates downregulation, and the darker the colour, the greater the up or downregulation. qPCR, quantitative PCR.
Analysis of differential gene expression in ‘plant–pathogen interaction’ and ‘MAPK signalling pathway-plant’ pathways. (A) qPCR verification of DEGs. Orange indicates the treatment group whereas green indicates the control group. (B) Differential gene expression heatmap of transcriptome sequencing data. Orange indicates upregulation whereas green indicates downregulation, and the darker the colour, the greater the up or downregulation. qPCR, quantitative PCR.

Figure S1.

Volcano map of DEGs at 3 hr, 12 hr and 24 hr after inoculation with U. esculenta. DEGs, differentially expressed genes.
Volcano map of DEGs at 3 hr, 12 hr and 24 hr after inoculation with U. esculenta. DEGs, differentially expressed genes.

Figure S2.

GO enrichment and KEGG pathway analyses of DEGs after inoculation. (A) GO enrichment at 3 hr after inoculation. (B) GO enrichment 12 hr after inoculation. (C) GO enrichment 24 hr after inoculation. (D) KEGG pathways at 3 hr after inoculation. (E) KEGG pathways at 12 hr after inoculation. (F) KEGG pathways at 24 hr after inoculation. DEGs, differentially expressed genes; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.
GO enrichment and KEGG pathway analyses of DEGs after inoculation. (A) GO enrichment at 3 hr after inoculation. (B) GO enrichment 12 hr after inoculation. (C) GO enrichment 24 hr after inoculation. (D) KEGG pathways at 3 hr after inoculation. (E) KEGG pathways at 12 hr after inoculation. (F) KEGG pathways at 24 hr after inoculation. DEGs, differentially expressed genes; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.

Figure S3.

Statistics of differentially expressed transcription factor after inoculation. Red indicates upregulation whereas blue indicates downregulation, and the numbers indicates the number of transcription factors. (A) 3 hr after inoculation. (B) 24 hr after inoculation.
Statistics of differentially expressed transcription factor after inoculation. Red indicates upregulation whereas blue indicates downregulation, and the numbers indicates the number of transcription factors. (A) 3 hr after inoculation. (B) 24 hr after inoculation.

Real-time fluorescence qPCR primers for candidate genes

Gene name Forward primer (5′ – 3′) Reverse primer (5′ – 3′)
Zlat_10042236 AGTGGTGACTCTGGAATTGG G-CCCATGAGTGTGTTGTGATCT
Zlat_10016445 CATGGAAGGAAGGCAGATAC CAAAGCCACCCTCACCTATT
Zlat_10028687 GAGTCAAGACAGGGAGTAAAGG CCTTCCACACAATAGCCATAAAG
Zlat_10030446 GCAGAGAATCACAGTTGAGGAG GCTTCATCTGGTCCTCGTTTAG
Zlat_10002195 TAT-CCACCTCACGCCCAGT TA-TCCTTGACGACGCCTCC
Zlat_10008237 TCCTACTCAGACTTCTCGTTCC CTGCTGCTGCTGACATCTATAC
Zlat_10020312 CACGACAACGAGAACTCC GATCTCAATCTCCGACCT
Zlat_10028790 GGATTCCAAGAGATGGAGGAAAG TCGATGTCGCTCATGGTTTG
Zlat_10045823 GC-TGACCACCAAATCTTCGACTAC GCTCATGGAGTTCTCGTTGT
Zlat_10008367 C-TATGTGCACGGCAGATGTT C-GCTTGTAATGACGCTCCTATC
Zlat_10029338 AACGTGTTGTGGCGCTTA TTGCAGCCCGTTCAAACT
Zlat_10007178 GACAAGACGGTGGTATGGTATG GGGATCTCGAAGAGAAAGAACC
Zlat_10004780 G-ACAAGGCGGGCTCTTATTT GGTACTAGGAGTTGCTGTGAAG
Zlat_10023424 CAAGTAGGTCAGGGTGGATTTG CTTGTTTGGTGCCAGGAGT
Zlat_10024926 GCAGAGAATCACAGTTGAGGAG GCTTCATCTGGTCCTCGTTTAG
Zlat_10004358 TGGGTATCAATGGCGGAAG CCTTCTTCTTCACCGGACAC
Zlat_10003815 ACGGAAGGCAACGTTTGA GGTCGAAAGCTGGGTAGTATG
ZlActin2 C-TAACCGGCCACGTGTATTT AGAGCAGAGGCATTCCAAGT

Real-time fluorescence qPCR primers for transcriptome data validation

Gene name Forward primer (5′ – 3′) Reverse primer (5′ – 3′)
Zlat_10042605 GCTTGTTCCTCCTCGTCATC TT-GACGGCGAAGGGAGGTT
Zlat_10032950 CCAACACCAACCTCAACTACG A-CGGAGATCCTGATGCCTAC
Zlat_10047488 CGTGGTATCGGAGACAGGGT CG-GAAGAGAGCGAAGAGGTACACG
Zlat_New_3742 ACCAACACGACGACCAGACT AAGAAGAGCACCGCCAATG
Zlat_10042236 AGTGGTGACTCTGGAATTGG G-CCCATGAGTGTGTTGTGATCT
Zlat_10016445 CATGGAAGGAAGGCAGATAC CAAAGCCACCCTCACCTATT
Zlat_10028687 GAGTCAAGACAGGGAGTAAAGG CCTTCCACACAATAGCCATAAAG
Zlat_10035043 CGTGGATTGGGCAACCTT CTTCTTGTTCTCCTCGCTCG
Zlat_10006234 GTGACGGCGACCAACTTCT T-GAGTGCCCGTTGATGGTG
Zlat_10018519 GTGGAAGGGTATGGCAGTG C-AGATTCGGGTTTGGTAGGC
Zlat_10014566 ATCACCGCCACCAACCT T-CCTCCCTTCTTCACGCAC
Zlat_10002874 GGAGTATCTCCACCTACCTGTCT CCGTCGTCGTATTCTTCGTCT
Zlat_10042726 TT-GGCTTCTTCCCTCTCCTCC CGGTGAAGTCAGAGGCGTT
Zlat_10026152 GTGGGTGGACGAGAAGAAGT CAGCCGATGAGGATGGAGT
Zlat_10045237 A-TGTGGCAGTCGTGTCCGT A-CGTTGAACAGGGGCTCGT
Zlat_10002801 ACGACAGAGGAACTGAAGGACT TCGTGTTGAGGATTTGGAGG
Zlat_10020429 ACGGGCTCACCTACACCAAC T-ACAGCCGACGTGGTCGAT
Zlat_10020427 T-CCTACCCTGGTGTCTCCTTC T-CCGTGGACACCTTGATGC
Zlat_10001037 T-ATTCACCTCCCACACTCAGC CCATCACCACCTATCTTCAAGC
Zlat_10009720 CATCGCCTTCTCCCTCAT GGTTCCAGGGTTGATTGC
ZlActin2 C-TAACCGGCCACGTGTATTT AGAGCAGAGGCATTCCAAGT

Information on candidate genes related to ‘plant–pathogen interaction’ and ‘MAPK signalling pathway-plant’ pathways in male Z_ latifolia in response to U_ esculenta infection

Gene ID Log2(FC) Genetic traits Homologous gene
Zlat_10029338 1.16 LRR receptor-like serine/threonine-protein kinase FLS2 AT5G46330
Zlat_10042236 1.30 LRR receptor-like serine/threonine-protein kinase FLS2 AT5G46330
Zlat_10004780 1.32 BAK1 AT4G33430
Zlat_10007178 1.10 BAK1 AT4G33430
Zlat_10016445 1.06 BAK1 AT4G33430
Zlat_10023424 1.48 BAK1 AT4G33430
Zlat_10028687 1.20 BAK1 AT4G33430
Zlat_10024926 1.02 Mitogen-activated protein kinase 3 AT3G45640
Zlat_10030446 1.49 Mitogen-activated protein kinase 3 AT3G45640
Zlat_10002195 1.24 WRKY33 AT2G38470
Zlat_10004358 2.72 WRKY33 AT2G38470
Zlat_10008237 2.02 WRKY33 AT2G38470
Zlat_10020312 1.60 WRKY33 AT2G38470
Zlat_10028790 1.85 WRKY33 AT2G38470
Zlat_10008367 1.52 WRKY33 AT2G38470
Zlat_10045823 1.59 Senescence-induced receptor-like serine/threonine-protein kinase (FRK1) AT2G19190
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