Identification of self- and pathogen-targeted miRNAs from resistant and susceptible Theobroma cacao variety to black pod disease.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
08 Feb 2024
Historique:
received: 24 07 2023
accepted: 03 02 2024
medline: 9 2 2024
pubmed: 9 2 2024
entrez: 9 2 2024
Statut: epublish

Résumé

Cacao (Theobroma cacao) is a highly valuable crop with growing demand in the global market. However, cacao farmers often face challenges posed by black pod disease caused by Phytophthora spp., with P. palmivora being the most dominant. Regulations of various gene expressions influence plant resistance to pathogens. One mechanism involves targeting the mRNA of virulence genes in the invading pathogens, suppressing their infection. However, resistance also could be suppressed by plant-derived miRNAs that target their own defence genes. The objective of this study is to identify differentially expressed miRNAs in black pod-resistant and susceptible cacao varieties and to predict their targets in T. cacao and P. palmivora transcripts. Extracted miRNA from resistant and susceptible varieties of T. Cacao was sequenced, identified, and matched to host and pathogen mRNA. In total, 54 known miRNAs from 40 miRNA families and 67 novel miRNAs were identified. Seventeen miRNAs were differentially expressed in susceptible variety compared to resistant one, with 9 miRNAs upregulated and 8 miRNAs downregulated. In T. cacao transcripts, the upregulated miRNAs were predicted to target several genes, including defence genes. The suppression of these defense genes can lead to a reduction in plant resistance against pathogen infection. In P. palmivora transcripts, the upregulated miRNAs were predicted to target several genes, including P. palmivora effector genes. In the future, limiting expression of miRNAs that target T. cacao's defence genes and applying miRNAs that target P. palmivora effector genes hold promise for enhancing cacao plant resistance against P. palmivora infection.

Identifiants

pubmed: 38332251
doi: 10.1038/s41598-024-53685-x
pii: 10.1038/s41598-024-53685-x
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

3272

Informations de copyright

© 2024. The Author(s).

Références

ICCO. Quarterly bulletin of cocoa statistics. Int. Cocoa Organ. XLIX, 1–10 (2023).
Ariningsih, E. et al. Problems and strategies in enhancing production and quality of Indonesian Cocoa. Anal. Kebijak. Pertan. 19, 89–108 (2021).
doi: 10.21082/akp.v19n1.2021.89-108
Brasier, C. M. & Griffin, M. J. Taxonomy of ‘Phytophthora palmivora’ on cocoa. Trans. Br. Mycol. Soc. 72, 111–143 (1979).
doi: 10.1016/S0007-1536(79)80015-7
Nair, K. P. Cocoa (Theobroma cacao L.). Tree Crops: Harvesting Cash from the World’s Important Cash Crops (Springer, 2020).
Karmawati, E. et al. Budidaya & Pascapanen Kakao (Pusat Penelitian dan Pengembangan Perkebunan, 2010).
Rubiyo, F. & Amaria, W. Ketahanan tanaman kakao terhadap penyakit busuk buah (Phytophthora palmivora Butl.). Perspektif 12, 23–36 (2013).
Rabuma, T., Gupta, O. P. & Chhokar, V. Genome-wide comprehensive analysis of miRNAs and their target genes expressed in resistant and susceptible Capsicum annuum landrace during Phytophthora capsici infection. BioRxiv Prepr. Serv. Biol. 298, 273–292 (2021).
Yang, X., Zhang, L., Yang, Y., Schmid, M. & Wang, Y. Mirna mediated regulation and interaction between plants and pathogens. Int. J. Mol. Sci. 22, 1–13 (2021).
Yang, L. et al. Overexpression of potato miR482e enhanced plant sensitivity to Verticillium dahliae infection. J. Integr. Plant Biol. 57, 1078–1088 (2015).
pubmed: 25735453 doi: 10.1111/jipb.12348
Ashfaq, M. A. et al. Post-transcriptional gene silencing: Basic concepts and applications. J. Biosci. 45, 1–10 (2020).
doi: 10.1007/s12038-020-00098-3
Koch, A. et al. An RNAi-based control of Fusarium graminearum infections through spraying of long dsRNAs involves a plant passage and is controlled by the fungal silencing machinery. PLoS Pathog. 12, 1–22 (2016).
doi: 10.1371/journal.ppat.1005901
Vanegtern, B., Rogers, M. & Nelson, S. Black pod rot of cacao caused by Phytophthora palmivora. Plant Dis. 1, 1–5 (2015).
Cheng, C. et al. Identification of Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4) responsive miRNAs in banana root. Sci. Rep. 9, 1–16 (2019).
doi: 10.1038/s41598-019-50130-2
Xin, M. et al. Diverse set of microRNAs are responsive to powdery mildew infection and heat stress in wheat (Triticum aestivum L.). BMC Plant Biol. 10, 1–11 (2010).
doi: 10.1186/1471-2229-10-123
Friedländer, M. R., MacKowiak, S. D., Li, N., Chen, W. & Rajewsky, N. MiRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res. 40, 37–52 (2012).
pubmed: 21911355 doi: 10.1093/nar/gkr688
Liu, Z. et al. Identification and characterization of novel microRNAs for fruit development and quality in hot pepper (Capsicum annuum L.). Gene 608, 66–72 (2017).
pubmed: 28122266 doi: 10.1016/j.gene.2017.01.020
Zhang, L. et al. Identification of differentially expressed miRNAs and their target genes in response to brassinolide treatment on flowering of tree peony (Paeonia ostii). Plant Signal. Behav. 17, 1–14 (2022).
doi: 10.1080/15592324.2022.2056364
Guo, N. et al. Genome-wide identification of Phytophthora sojae-associated microRNAs and network in a resistant and a susceptible soybean germplasm. Agronomy 12, 1–15 (2022).
doi: 10.3390/agronomy12122922
Tiwari, J. K. et al. Genome-wide identification and characterization of microRNAs by small RNA sequencing for low nitrogen stress in potato. PLoS One 15, 1–21 (2020).
doi: 10.1371/journal.pone.0233076
Pratama, S. W. & Sari, N. P. Application of lime and urea and its effect on development of Phytophthora palmivora. Pelita Perkebunan. 31, 41–48 (2015).
Hannon, G. J. FASTX-Toolkit: FASTQ/A short-reads pre-processing tools. FASTX-Toolkit. http://hannonlab.cshl.edu/fastx_toolkit/ (2010).
Rabuma, T., Gupta, O. P. & Chhokar, V. Genome-wide comprehensive analysis of miRNAs and their target genes expressed in resistant and susceptible Capsicum annuum genotypes during Phytophthora capsici infection. Mol. Genet. Genom. 298, 273–292 (2023).
doi: 10.1007/s00438-022-01979-y
Lewis, J. D., Wu, R., Guttman, D. S. & Desveaux, D. Allele-specific virulence attenuation of the Pseudomonas syringae HopZ1a type III effector via the Arabidopsis ZAR1 resistance protein. PLoS Genet. 6, 1–13 (2010).
doi: 10.1371/journal.pgen.1000894
Sekhwal, M. K. et al. Disease resistance gene analogs (RGAs) in plants. Int. J. Mol. Sci. 16, 19248–19290 (2015).
pubmed: 26287177 pmcid: 4581296 doi: 10.3390/ijms160819248
Li, N. Y. et al. Heterologous expression of the cotton NBS-LRR gene GbaNA1 enhances verticillium wilt resistance in Arabidopsis. Front. Plant Sci. 9, 1–13 (2018).
Parker, M. T. et al. Widespread premature transcription termination of Arabidopsis thaliana nlr genes by the spen protein fpa. Elife 10, 1–36 (2021).
doi: 10.7554/eLife.65537
Wang, Y., Bouwmeester, K., Beseh, P., Shan, W. & Govers, F. Phenotypic analyses of Arabidopsis T-DNA insertion lines and expression profiling reveal that multiple L-type lectin receptor kinases are involved in plant immunity. Mol. Plant-Microbe Interact. 27, 1390–1402 (2014).
pubmed: 25083911 doi: 10.1094/MPMI-06-14-0191-R
Chul, M. K. et al. OsCSLD1, a cellulose synthase-like D1 gene, is required for root hair morphogenesis in rice. Plant Physiol. 143, 1220–1230 (2007).
doi: 10.1104/pp.106.091546
Liao, L., Xie, B., Guan, P., Jiang, N. & Cui, J. New insight into the molecular mechanism of miR482/2118 during plant resistance to pathogens. Front. Plant Sci. 13, 1–7 (2022).
doi: 10.3389/fpls.2022.1026762
Hong, Y. et al. Editing mir482b and mir482c simultaneously by crispr/cas9 enhanced tomato resistance to Phytophthora infestans. Phytopathology 111, 1008–1016 (2021).
pubmed: 33258411 doi: 10.1094/PHYTO-08-20-0360-R
Hong, Y. H., Meng, J., He, X. L., Zhang, Y. Y. & Luan, Y. S. Overexpression of MiR482c in tomato induces enhanced susceptibility to late blight. Cells 8, 1–12 (2019).
doi: 10.3390/cells8080822
Cai, Q., He, B., Kogel, K. H. & Jin, H. Cross-kingdom RNA trafficking and environmental RNAi—nature’s blueprint for modern crop protection strategies. Curr. Opin. Microbiol. 46, 58–64 (2018).
pubmed: 29549797 pmcid: 6499079 doi: 10.1016/j.mib.2018.02.003
Schaefer, L. K. et al. Cross-Kingdom RNAi of pathogen effectors leads to quantitative adult plant resistance in wheat. Front. Plant Sci. 11, 1–13 (2020).
doi: 10.3389/fpls.2020.00253
Wang, M. et al. Bidirectional cross-kingdom RNAi and fungal uptake of external RNAs confer plant protection. Nat. Plants 2, 1–10 (2016).
doi: 10.1038/nplants.2016.151
Coudert, E. et al. Annotation of biologically relevant ligands in UniProtKB using ChEBI. Bioinformatics 39, 1–5 (2023).
doi: 10.1093/bioinformatics/btac793
Dou, D. & Zhou, J. M. Phytopathogen effectors subverting host immunity: Different foes, similar battleground. Cell Host Microbe 12, 484–495 (2012).
pubmed: 23084917 doi: 10.1016/j.chom.2012.09.003
Wang, Q. et al. Transcriptional programming and functional interactions within the Phytophthora sojae RXLR effector repertoire. Plant Cell 23, 2064–2086 (2011).
pubmed: 21653195 pmcid: 3160037 doi: 10.1105/tpc.111.086082
Amaro, T. M. M. M., Thilliez, G. J. A., Motion, G. B. & Huitema, E. A perspective on CRN proteins in the genomics age: Evolution, classification, delivery and function revisited. Front. Plant Sci. 8, 1–12 (2017).
doi: 10.3389/fpls.2017.00099
Haas, B. J. et al. Genome sequence and analysis of the Irish potato famine pathogen Phytophthora infestans. Nature 461, 393–398 (2009).
pubmed: 19741609 doi: 10.1038/nature08358
Hou, Y. et al. A Phytophthora effector suppresses trans-kingdom RNAi to promote disease susceptibility. Cell Host Microbe 25, 153–165 (2019).
pubmed: 30595554 doi: 10.1016/j.chom.2018.11.007
Hu, D., Chen, Z. Y., Zhang, C. & Ganiger, M. Reduction of Phakopsora pachyrhizi infection on soybean through host- and spray-induced gene silencing. Mol. Plant Pathol. 21, 794–807 (2020).
pubmed: 32196911 pmcid: 7214474 doi: 10.1111/mpp.12931
Pentimone, I. & Ciancio, A. miRNA-based approaches for sustainable control of diseases. CABI Rev. 2021, 456 (2021).
Kuo, Y. W. & Falk, B. W. RNA interference approaches for plant disease control. Biotechniques 69, 469–477 (2020).
pubmed: 33070628 doi: 10.2144/btn-2020-0098
Nogoy, F. M. et al. Plant microRNAs in molecular breeding. Plant Biotechnol. Rep. 12, 15–25 (2018).
doi: 10.1007/s11816-018-0468-9
Zhang, Y. C. et al. Overexpression of microRNA OsmiR397 improves rice yield by increasing grain size and promoting panicle branching. Nat. Biotechnol. 31, 848–852 (2013).
pubmed: 23873084 doi: 10.1038/nbt.2646
Sihag, P. et al. Discovery of miRNAs and development of heat-responsive miRNA-SSR markers for characterization of wheat germplasm for terminal heat tolerance breeding. Front. Genet. 12, 1–12 (2021).
doi: 10.3389/fgene.2021.699420
Mondal, T. K. & Ganie, S. A. Identification and characterization of salt responsive miRNA-SSR markers in rice (Oryza sativa). Gene 535, 204–209 (2014).
pubmed: 24315823 doi: 10.1016/j.gene.2013.11.033
Pruitt, K. et al. The NCBI Handbook (Springer, 2002).
Darmono, T. W., Jamil, I. & Santosa, D. A. Pengembangan penanda molekuler untuk deteksi Phytophthora palmivora pada tanaman kakao. Menara Perkeb. 74, 87–96 (2006).
Andrews, S. FastQC: A quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2010).
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
pubmed: 24695404 pmcid: 4103590 doi: 10.1093/bioinformatics/btu170
Liao, Y., Smyth, G. K. & Shi, W. The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads. Nucleic Acids Res. 47, 1–9 (2019).
doi: 10.1093/nar/gkz114
Gruber, A. R., Lorenz, R., Bernhart, S. H., Neuböck, R. & Hofacker, I. L. The Vienna RNA websuite. Nucleic Acids Res. 36, 70–74 (2008).
doi: 10.1093/nar/gkn188
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 1–21 (2014).
doi: 10.1186/s13059-014-0550-8
Blighe, K., Rana, S. & Lewis, M. EnhancedVolcano: Publication-ready volcano plots with enhanced colouring and labeling. https://github.com/kevinblighe/EnhancedVolcano (2023).
Kolde, R. pheatmap: Pretty Heatmaps. https://cran.r-project.org/web/packages/pheatmap/index.html (2019).
Dai, X., Zhuang, Z. & Zhao, P. X. PsRNATarget: A plant small RNA target analysis server (2017 release). Nucleic Acids Res. 46, 49–54 (2018).
doi: 10.1093/nar/gky316

Auteurs

Popi Septiani (P)

School of Life Sciences and Technology, Institut Teknologi Bandung, Jl. Ganesha No. 10, Bandung, 40132, Indonesia.

Yonadita Pramesti (Y)

School of Life Sciences and Technology, Institut Teknologi Bandung, Jl. Ganesha No. 10, Bandung, 40132, Indonesia.

Devi Ulfa Ningsih (DU)

School of Life Sciences and Technology, Institut Teknologi Bandung, Jl. Ganesha No. 10, Bandung, 40132, Indonesia.

Sulistyani Pancaningtyas (S)

Indonesian Coffee and Cocoa Research Institute (ICCRI), Jl. PB. Sudirman 90, Jember, 68118, Indonesia.

Karlia Meitha (K)

School of Life Sciences and Technology, Institut Teknologi Bandung, Jl. Ganesha No. 10, Bandung, 40132, Indonesia. karliameitha@itb.ac.id.

Classifications MeSH