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Iannelli MA, Nicolodi C, Coraggio I, Fabriani M, Baldoni E, Frugis G. A Novel Role of Medicago truncatula KNAT3/4/5-like Class 2 KNOX Transcription Factors in Drought Stress Tolerance. Int J Mol Sci 2023; 24:12668. [PMID: 37628847 PMCID: PMC10454132 DOI: 10.3390/ijms241612668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/02/2023] [Accepted: 08/09/2023] [Indexed: 08/27/2023] Open
Abstract
Class 2 KNOX homeobox transcription factors (KNOX2) play a role in promoting cell differentiation in several plant developmental processes. In Arabidopsis, they antagonize the meristematic KNOX1 function during leaf development through the modulation of phytohormones. In Medicago truncatula, three KNOX2 genes belonging to the KNAT3/4/5-like subclass (Mt KNAT3/4/5-like or MtKNOX3-like) redundantly works upstream of a cytokinin-signaling module to control the symbiotic root nodule formation. Their possible role in the response to abiotic stress is as-of-yet unknown. We produced transgenic M. truncatula lines, in which the expression of four MtKNOX3-like genes was knocked down by RNA interference. When tested for response to water withdrawal in the soil, RNAi lines displayed a lower tolerance to drought conditions compared to the control lines, measured as increased leaf water loss, accelerated leaf wilting time, and faster chlorophyll loss. Reanalysis of a transcriptomic M. truncatula drought stress experiment via cluster analysis and gene co-expression networks pointed to a possible role of MtKNOX3-like transcription factors in repressing a proline dehydrogenase gene (MtPDH), specifically at 4 days after water withdrawal. Proline measurement and gene expression analysis of transgenic RNAi plants compared to the controls confirmed the role of KNOX3-like genes in inhibiting proline degradation through the regulation of the MtPDH gene.
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Affiliation(s)
- Maria Adelaide Iannelli
- National Research Council (CNR), Institute of Agricultural Biology and Biotechnology (IBBA), Rome Unit, Via Salaria Km. 29,300, Monterotondo Scalo, 00015 Roma, Italy; (M.A.I.); (C.N.); (I.C.); (M.F.)
| | - Chiara Nicolodi
- National Research Council (CNR), Institute of Agricultural Biology and Biotechnology (IBBA), Rome Unit, Via Salaria Km. 29,300, Monterotondo Scalo, 00015 Roma, Italy; (M.A.I.); (C.N.); (I.C.); (M.F.)
| | - Immacolata Coraggio
- National Research Council (CNR), Institute of Agricultural Biology and Biotechnology (IBBA), Rome Unit, Via Salaria Km. 29,300, Monterotondo Scalo, 00015 Roma, Italy; (M.A.I.); (C.N.); (I.C.); (M.F.)
| | - Marco Fabriani
- National Research Council (CNR), Institute of Agricultural Biology and Biotechnology (IBBA), Rome Unit, Via Salaria Km. 29,300, Monterotondo Scalo, 00015 Roma, Italy; (M.A.I.); (C.N.); (I.C.); (M.F.)
| | - Elena Baldoni
- National Research Council (CNR), Institute of Agricultural Biology and Biotechnology (IBBA), Via Alfonso Corti 12, 20133 Milan, Italy;
| | - Giovanna Frugis
- National Research Council (CNR), Institute of Agricultural Biology and Biotechnology (IBBA), Rome Unit, Via Salaria Km. 29,300, Monterotondo Scalo, 00015 Roma, Italy; (M.A.I.); (C.N.); (I.C.); (M.F.)
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Bullones A, Castro AJ, Lima-Cabello E, Fernandez-Pozo N, Bautista R, Alché JDD, Claros MG. Transcriptomic Insight into the Pollen Tube Growth of Olea europaea L. subsp. europaea Reveals Reprogramming and Pollen-Specific Genes Including New Transcription Factors. PLANTS (BASEL, SWITZERLAND) 2023; 12:2894. [PMID: 37631106 PMCID: PMC10459472 DOI: 10.3390/plants12162894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 08/01/2023] [Accepted: 08/02/2023] [Indexed: 08/27/2023]
Abstract
The pollen tube is a key innovation of land plants that is essential for successful fertilisation. Its development and growth have been profusely studied in model organisms, but in spite of the economic impact of olive trees, little is known regarding the genome-wide events underlying pollen hydration and growth in this species. To fill this gap, triplicate mRNA samples at 0, 1, 3, and 6 h of in vitro germination of olive cultivar Picual pollen were analysed by RNA-seq. A bioinformatics R workflow called RSeqFlow was developed contemplating the best practices described in the literature, covering from expression data filtering to differential expression and clustering, to finally propose hub genes. The resulting olive pollen transcriptome consisted of 22,418 reliable transcripts, where 5364 were differentially expressed, out of which 173 have no orthologue in plants and up to 3 of them might be pollen-specific transcription factors. Functional enrichment revealed a deep transcriptional reprogramming in mature olive pollen that is also dependent on protein stability and turnover to allow pollen tube emergence, with many hub genes related to heat shock proteins and F-box-containing proteins. Reprogramming extends to the first 3 h of growth, including processes consistent with studies performed in other plant species, such as global down-regulation of biosynthetic processes, vesicle/organelle trafficking and cytoskeleton remodelling. In the last stages, growth should be maintained from persistent transcripts. Mature pollen is equipped with transcripts to successfully cope with adverse environments, even though the in vitro growth seems to induce several stress responses. Finally, pollen-specific transcription factors were proposed as probable drivers of pollen germination in olive trees, which also shows an overall increased number of pollen-specific gene isoforms relative to other plants.
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Affiliation(s)
- Amanda Bullones
- Department of Molecular Biology and Biochemistry, Universidad de Málaga, 29010 Malaga, Spain;
- Institute for Mediterranean and Subtropical Horticulture “La Mayora” (IHSM-UMA-CSIC), 29010 Malaga, Spain;
| | - Antonio Jesús Castro
- Plant Reproductive Biology and Advanced Imaging Laboratory (BReMAP), Estación Experimental del Zaidín (EEZ-CSIC), 18008 Granada, Spain; (A.J.C.); (E.L.-C.); (J.d.D.A.)
| | - Elena Lima-Cabello
- Plant Reproductive Biology and Advanced Imaging Laboratory (BReMAP), Estación Experimental del Zaidín (EEZ-CSIC), 18008 Granada, Spain; (A.J.C.); (E.L.-C.); (J.d.D.A.)
| | - Noe Fernandez-Pozo
- Institute for Mediterranean and Subtropical Horticulture “La Mayora” (IHSM-UMA-CSIC), 29010 Malaga, Spain;
| | - Rocío Bautista
- Plataforma Andaluza de Bioinformática, Supercomputing and Bioinnovation Center (SCBI), Universidad de Málaga, 29590 Malaga, Spain;
| | - Juan de Dios Alché
- Plant Reproductive Biology and Advanced Imaging Laboratory (BReMAP), Estación Experimental del Zaidín (EEZ-CSIC), 18008 Granada, Spain; (A.J.C.); (E.L.-C.); (J.d.D.A.)
- University Institute of Research on Olive Grove and Olive Oils (INUO), Universidad de Jaén, 23071 Jaen, Spain
| | - Manuel Gonzalo Claros
- Department of Molecular Biology and Biochemistry, Universidad de Málaga, 29010 Malaga, Spain;
- Institute for Mediterranean and Subtropical Horticulture “La Mayora” (IHSM-UMA-CSIC), 29010 Malaga, Spain;
- CIBER de Enfermedades Raras (CIBERER) U741, 29071 Malaga, Spain
- Institute of Biomedical Research in Málaga (IBIMA), IBIMA-RARE, 29010 Malaga, Spain
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Ribone AI, Fass M, Gonzalez S, Lia V, Paniego N, Rivarola M. Co-Expression Networks in Sunflower: Harnessing the Power of Multi-Study Transcriptomic Public Data to Identify and Categorize Candidate Genes for Fungal Resistance. PLANTS (BASEL, SWITZERLAND) 2023; 12:2767. [PMID: 37570920 PMCID: PMC10421300 DOI: 10.3390/plants12152767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 07/19/2023] [Accepted: 07/21/2023] [Indexed: 08/13/2023]
Abstract
Fungal plant diseases are a major threat to food security worldwide. Current efforts to identify and list loci involved in different biological processes are more complicated than originally thought, even when complete genome assemblies are available. Despite numerous experimental and computational efforts to characterize gene functions in plants, about ~40% of protein-coding genes in the model plant Arabidopsis thaliana L. are still not categorized in the Gene Ontology (GO) Biological Process (BP) annotation. In non-model organisms, such as sunflower (Helianthus annuus L.), the number of BP term annotations is far fewer, ~22%. In the current study, we performed gene co-expression network analysis using eight terabytes of public transcriptome datasets and expression-based functional prediction to categorize and identify loci involved in the response to fungal pathogens. We were able to construct a reference gene network of healthy green tissue (GreenGCN) and a gene network of healthy and stressed root tissues (RootGCN). Both networks achieved robust, high-quality scores on the metrics of guilt-by-association and selective constraints versus gene connectivity. We were able to identify eight modules enriched in defense functions, of which two out of the three modules in the RootGCN were also conserved in the GreenGCN, suggesting similar defense-related expression patterns. We identified 16 WRKY genes involved in defense related functions and 65 previously uncharacterized loci now linked to defense response. In addition, we identified and classified 122 loci previously identified within QTLs or near candidate loci reported in GWAS studies of disease resistance in sunflower linked to defense response. All in all, we have implemented a valuable strategy to better describe genes within specific biological processes.
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Affiliation(s)
| | | | | | | | | | - Máximo Rivarola
- Instituto de Agrobiotecnología y Biología Molecular (IABIMO), CICVyA—Instituto Nacional de Tecnología Agropecuaria (INTA), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Los Reseros y Nicolás Repetto, Hurlingham 1686, Argentina; (A.I.R.); (M.F.); (S.G.); (V.L.); (N.P.)
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Cai H, Yu N, Liu Y, Wei X, Guo C. Meta-analysis of fungal plant pathogen Fusarium oxysporum infection-related gene profiles using transcriptome datasets. Front Microbiol 2022; 13:970477. [PMID: 36090060 PMCID: PMC9449528 DOI: 10.3389/fmicb.2022.970477] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
Fusarium oxysporum is a serious soil-borne fungal pathogen that affects the production of many economically important crops worldwide. Recent reports suggest that this fungus is becoming the dominant species in soil and could become the main infectious fungus in the future. However, the infection mechanisms employed by F. oxysporum are poorly understood. In the present study, using a network meta-analysis technique and public transcriptome datasets for different F. oxysporum and plant interactions, we aimed to explore the common molecular infection strategy used by this fungus and to identify vital genes involved in this process. Principle component analysis showed that all the fungal culture samples from different datasets were clustered together, and were clearly separated from the infection samples, suggesting the feasibility of an integrated analysis of heterogeneous datasets. A total of 335 common differentially expressed genes (DEGs) were identified among these samples, of which 262 were upregulated and 73 were downregulated significantly across the datasets. The most enriched functional categories of the common DEGs were carbohydrate metabolism, amino acid metabolism, and lipid metabolism. Nine co-expression modules were identified, and two modules, the turquoise module and the blue module, correlated positively and negatively with all the infection processes, respectively. Co-expression networks were constructed for these two modules and hub genes were identified and validated. Our results comprise a cross fungal-host interaction resource, highlighting the use of a network biology approach to gain molecular insights.
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Affiliation(s)
| | | | | | | | - Changhong Guo
- Key Laboratory of Molecular and Cytogenetics, Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China
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