ArticleComputational and structural biotechnology journal2024
Genome mining of metabolic gene clusters in the Rubiaceae family.
Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors at 5 institutions in 3 countries.
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Abstract
The Rubiaceae plant family, comprising 3 subfamilies and over 13,000 species, is known for producing significant bioactive compounds such as caffeine and monoterpene indole alkaloids. Despite an increase in available genomes from the Rubiaceae family over the past decade, a systematic analysis of the metabolic gene clusters (MGCs) encoded by these genomes has been lacking. In this study, we aim to identify and analyze metabolic gene clusters within complete Rubiaceae genomes through a comparative analysis of eight species. Applying two bioinformatics pipelines, we identified 2372 candidate MGCs, organized into 549 gene cluster families (GCFs). To enhance the reliability of these findings, we developed coexpression networks and conducted orthology analyses. Using genomic data from
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