Research Keyword: bioinformatics

Investigating fungal diversity through metabarcoding for environmental samples: assessment of ITS1 and ITS2 Illumina sequencing using multiple defined mock communities with different classification methods and reference databases

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Scientists developed a comprehensive method for identifying different fungi in environmental samples using DNA sequencing technology called metabarcoding. They tested 37 mixtures of known fungi species to compare different approaches, including which DNA markers to use, which reference databases to search, and which computer analysis methods to apply. The study found that the choice of method significantly affects results, with some approaches better at genus-level identification and others at species identification, helping researchers select the best approach for their specific needs.

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De novo genome sequencing and comparative analyses of the clinically relevant species Mucor ardhlaengiktus, Mucor circinelloides, Mucor griseocyanus, and Mucor janssenii

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Scientists have sequenced and analyzed the complete genomes of four species of Mucor fungus that cause serious infections in humans. Using advanced long-read sequencing technology, they created high-quality genetic blueprints for these organisms, which will help doctors better identify which Mucor species is causing infections and enable faster diagnosis and treatment of these dangerous fungal infections.

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Myco-Ed: Mycological curriculum for education and discovery

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Myco-Ed is an educational program that teaches students about fungi while helping scientists create reference genomes for understudied fungal species. Students collect fungi from their local environments, identify them, and prepare samples for advanced genome sequencing through partnerships with major research institutions. This program solves two problems at once: training the next generation of fungal researchers and filling critical gaps in our knowledge of fungal genetics and diversity.

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Global Analysis of microRNA-like RNAs Reveals Differential Regulation of Pathogenicity and Development in Fusarium oxysporum HS2 Causing Apple Replant Disease

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Apple replant disease is caused by a fungus that damages apple tree roots and reduces fruit production. Researchers discovered that this fungus uses special regulatory molecules called microRNA-like RNAs to control its growth and disease-causing abilities, especially during the spore stage. These findings could help scientists develop new ways to control the disease using RNA-based treatments.

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Advances in Fungal Natural Products: Insights into Bioactivity and Therapeutic Potential

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Medicinal mushrooms and fungi contain powerful natural chemicals that can boost immunity, reduce inflammation, fight cancer, and protect the brain. Scientists are now better able to identify and study these compounds using advanced techniques, and some are being tested as supplements or alongside traditional medicines. This research shows that mushrooms could become important tools in treating diseases like inflammatory bowel disease, rheumatoid arthritis, and cancer.

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Identification and virulence factors prediction of Didymella segeticola causing leaf spot disease in Asarum heterotropoides in China

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This research identifies a fungal disease causing serious damage to Chinese wild ginger crops in northeastern China. Scientists found that the fungus Didymella segeticola causes leaf spot disease and identified 87 proteins that help the fungus harm the plants. The study provides important information for developing strategies to prevent this disease and protect this valuable medicinal herb crop.

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Contamination of fungal genomes of Onygenaceae (Phylum Ascomycota) in public databases: incidence, detection, and impact

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Scientists found that many fungal genome sequences stored in public databases contain unwanted bacterial DNA that can interfere with research results. They developed a method to identify and remove this contamination using related high-quality fungal genomes as reference. After cleaning four contaminated genomes, the quality improved significantly and the contamination dropped from 5-12% to below 3%, demonstrating that careful screening is essential for reliable genetic research.

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