Fungi
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA435582 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We investigated the transcriptional response of invasive Mediterranean (MED) species of the whitefly B. tabaci complex (commonly referred to as Q biotype) to entomopathogenic fungi Beauveria bassiana using Illumina sequencing technology. Nearly 1,000 of control whiteflies, 48h fungal-induced whiteflies and 72h fungal-induced whiteflies were collected, respectively.
2013-11-24 | E-GEOD-38108 | biostudies-arrayexpress
Project description:B. bassiana regulates transcriptional adaptation to host hemocoel, which is a determinant to the biocontrol potential of fungal entomopathogens. The global transcriptome related to fungal development in host was analyzed by using high throughput sequencing (RNA-Seq). Our transcriptional profiles revealed that majority of fungal genes are involved in fungal growth in host environmental, and are associated with various cellular processes.
2020-03-17 | GSE97042 | GEO
Project description:Amplicon-based fungal metagenomic sequencing for the identification of fungal species in brain tissue from Alzheimer's disease. The study consists in 14 samples, sequenced using Illumina's paired-end technology.
| EGAD00001003196 | EGA
Project description:Cytosine methylation is a conserved base modification, but explanations for its interspecific variation remain elusive. Only through taxonomic sampling of disparate groups can unifying explanations for interspecific variation be thoroughly tested. Here we leverage phylogenetic resolution of cytosine DNA methyltransferases (DNA MTases) and genome evolution to better understand widespread interspecific variation across 40 diverse fungal species. DNA MTase genotypes have diversified from the ancestral DNMT1+DNMT5 genotype through numerous loss events, and duplications, whereas, DIM-2 and RID-1 are more recently derived in fungi. Methylation is typically enriched at intergenic regions, which includes repeats and transposons. Unlike certain Insecta and Angiosperm species, Fungi lack canonical gene body methylation. Some fungi species possess large clusters of contiguous methylation encompassing many genes, repetitive DNA and transposons, and are not ancient in origin. Broadly, methylation is partially explained by DNA MTase genotype and repetitive DNA content. Basidiomycota on average have the highest level of methylation, and repeat content, compared to other phyla. However, exceptions exist across Fungi. Other traits, including DNA repair mechanisms, might contribute to interspecific methylation variation within Fungi. Our results show mechanism and genome evolution are unifying explanations for interspecific methylation variation across Fungi.
2019-02-18 | GSE112636 | GEO
Project description:We investigated the metabolism of six secondary metabolite producing fungi of the Penicillium genus, during nutrient depletion in the stationary phase of batch fermentations and assessed conserved metabolic responses across species using genome-wide transcriptional profiling. Coexpression analysis revealed that expression of secondary metabolite biosynthetic genes correlates with expression of genes associated with pathways responsible for generation of precursor metabolites for secondary metabolism. Our results highlight the main metabolic routes for precursor supply of the secondary metabolism during nutrient depletion, and suggests that regulation of fungal metabolism is tailored to meet the demands for secondary metabolite production. These findings can aid in identifying wild type species, which are optimized for production of specific secondary metabolites, and therefore can be utilized as high yielding cell factories.
2017-11-17 | GSE106983 | GEO
Project description:ITS2 region of fungal species on amphibian skin swabs Raw sequence reads
| PRJNA429422 | ENA
Project description:Identification of fungal species present in the central nervous system tissue from Alzheimer's disease patients by next-generation sequencing.
| EGAS00001002228 | EGA
Project description:<p>Microbial communities often undergo intricate compositional changes yet also maintain stable coexistence of diverse species. The mechanisms underlying long-term coexistence remain unclear, as system-wide studies have been largely limited to engineered communities, ex situ adapted cultures, or synthetic assemblies. Here we show how kefir, a natural milk-fermenting community of prokaryotes and yeasts, realises stable coexistence through spatiotemporal orchestration of species and metabolite dynamics. During milk fermentation, kefir grains (a polysaccharide matrix synthesized by kefir microbes) grow in mass but remain unchanged in composition. In contrast, the milk is colonized in a sequential manner in which early members open metabolic niches for followers. Through metabolomics and large-scale mapping of inter-species interactions, we show how microbes poorly suited for milk survive in, and even dominate the community, through metabolic cooperation and uneven partitioning between grain and milk. Overall, our findings reveal how inter-species interactions partitioned in space and time lead to stable coexistence.</p><p><br></p><p><strong>Linked metabolomics studies:</strong></p><p><a href='https://www.ebi.ac.uk/metabolights/MTBLS1829' rel='noopener noreferrer' target='_blank'>MTBLS1829</a> Kefir fermentation curve (FIA-MS)</p><p><a href='https://www.ebi.ac.uk/metabolights/MTBLS1830' rel='noopener noreferrer' target='_blank'>MTBLS1830</a> Interaction between the kefir isolates Lactococcus lactis and Acetobacter fabarum (GC-MS)</p><p><br></p><p><strong>Linked cross omic data:</strong></p><p>Genomes of isolated kefir species are available in the <a href='https://www.ncbi.nlm.nih.gov/' rel='noopener noreferrer' target='_blank'>NCBI database</a> under the accession: PRJNA375758 (bioproject ID: 375758).</p><p>Metatranscriptomic sequencing reads can be accessed from <a href='www.ebi.ac.uk/ena' rel='noopener noreferrer' target='_blank'>ENA</a> under the project id PRJEB37001.</p><p>Genome-scale metabolic models for kefir bacteria can be found at github.com/cdanielmachado/kefir_models.</p>
2020-11-04 | MTBLS1823 | MetaboLights