ArticleNucleic acids research2017
The PhytoClust tool for metabolic gene clusters discovery in plant genomes.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
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50 citing papers in PubMed, 101 citations in OpenAlex.
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- Productive chaos and precision engineering: decoupling discovery from manufacturing to revolutionize plant-inspired therapeutics.Frontiers in plant science · 2026Article
- Mining Metabolic Diversities Across Genomic Neighborhoods in Plants.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Identification of Stress-Induced Biosynthetic Gene Clusters in Plants.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Resilience of Portulaca plants to environmental stresses and the economic potential of their bioactive compounds.Planta · 2025Review
- MEANtools integrates multi-omics data to identify metabolites and predict biosynthetic pathways.PLoS biology · 2025Article
- Genome-wide terpene gene clusters analysis in Euphorbiaceae.Horticulture research · 2025Article
- A SlMYB78-regulated bifunctional gene cluster for phenolamide and salicylic acid biosynthesis during tomato domestication, reducing disease resistance.Journal of integrative plant biology · 2025Article
- From data to discovery: leveraging big data in plant natural products biosynthesis research.The Plant journal : for cell and molecular biology · 2025Review
- A long road ahead to reliable and complete medicinal plant genomes.Nature communications · 2025Review
- Understanding metabolic diversification in plants: branchpoints in the evolution of specialized metabolism.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- Herbgenomics meets Papaveraceae: a promising -omics perspective on medicinal plant research.Briefings in functional genomics · 2024Review
- Cutting-edge plant natural product pathway elucidation.Current opinion in biotechnology · 2024Review
- Genetic basis and selection of glyceollin elicitation in wild soybean.Frontiers in plant science · 2024Article
- Leveraging yeast to characterize plant biosynthetic gene clusters.Current opinion in plant biology · 2023Review
- Endophytic fungi: hidden treasure chest of antimicrobial metabolites interrelationship of endophytes and metabolites.Frontiers in microbiology · 2023Review
- Genome assembly of Musa beccarii shows extensive chromosomal rearrangements and genome expansion during evolution of Musaceae genomes.GigaScience · 2022Article
- Integrative omics approaches for biosynthetic pathway discovery in plants.Natural product reports · 2022Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The existence of Metabolic Gene Clusters (MGCs) in plant genomes has recently raised increased interest. Thus far, MGCs were commonly identified for pathways of specialized metabolism, mostly those associated with terpene type products. For efficient identification of novel MGCs, computational approaches are essential. Here, we present PhytoClust; a tool for the detection of candidate MGCs in plant genomes. The algorithm employs a collection of enzyme families related to plant specialized metabolism, translated into hidden Markov models, to mine given genome sequences for physically co-localized metabolic enzymes. Our tool accurately identifies previously characterized plant MGCs. An exhaustive search of 31 plant genomes detected 1232 and 5531 putative gene cluster types and candidates, respectively. Clustering analysis of putative MGCs types by species reflected plant taxonomy. Furthermore, enrichment analysis revealed taxa- and species-specific enrichment of certain enzyme families in MGCs. When operating through our web-interface, PhytoClust users can mine a genome either based on a list of known cluster types or by defining new cluster rules. Moreover, for selected plant species, the output can be complemented by co-expression analysis. Altogether, we envisage PhytoClust to enhance novel MGCs discovery which will in turn impact the exploration of plant metabolism.
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