Genomes reconstruction from metagenome data
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB21507 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Comparative genomics of sponge-associated Alphaproteobacteria
| PRJEB18465 | ENA
Project description:Marine sponges are essential for coral reefs to thrive and harbour a diverse microbiome that is thought to contribute to host health. Although the overall function of sponge symbionts has been increasingly described, in-depth characterisation of each taxa remains challenging, with many sponge species hosting up to 3,000 distinct microbial species. Recently, the sponge Ianthella basta has emerged as a model organism for symbiosis research, hosting only three dominant symbionts: a Thaumarchaeotum, a Gammaproteobacterium, and an Alphaproteobacterium and a range of other minor taxa. Here, we retrieved metagenome assembled genomes (MAGs) for >90% of I. basta’s microbial community which allowed us to make a complete metabolic reconstruction of the sponge’s microbiome, identifying metabolic complementarity between microbes, as well as the importance of symbionts present in low abundance. We also mined the metagenomes for putative viral sequences, highlighting the contribution of viruses to the overall metabolism of the sponge, and complement this data with metaproteomic sequencing to identify active metabolic pathways in both prokaryotes and viruses. This data now allows us to use I. basta as a model organism for studying host-microbe interactions and provides a basis for future (genomic) manipulative experiments.
2023-02-24 | PXD032278 | Pride
Project description:Microbial communities associated with corals life stages and surrounding environment.
| PRJNA526947 | ENA
Project description:Uncultured Chloroflexi Genomic Bins Metagenomic assembly
| PRJNA356693 | ENA
Project description:Genomic Bins of different algae metagenomes
| PRJEB26345 | ENA
Project description:Ancient Genomic Changes Associated with Domestication of the Horse
| PRJEB19970 | ENA
Project description:<p>Marine sponges can host abundant and diverse microbiomes, which can largely influence the metabolism and other phenotypic traits of the host. However, information on the potential relationships between sponge microbiomes and metabolic signatures, other than secondary metabolites explored for biotechnological purposes, needs further investigation. Applying an integrated approach, we investigated the microbiomes associated with 4 ubiquitous Mediterranean sponge species (i.e., Petrosia ficiformis, Chondrosia reniformis, Crambe crambe and Chondrilla nucula), correlated with their metabolomic patterns (in terms of lipidomics) and microbial predicted functions. Microscopy observations of sponge tissues revealed differences in microbial abundances, which, however, were only partially linked to their diversity assessed through metabarcoding. The microbiomes of the 4 sponges showed a species-specific composition and a different core size, which was independent from the microbial diversity of the surrounding seawater. Predicted functions of the associated microbiomes allowed identifying 2 functional host clusters: one more related to heterotrophic pathways and the other more linked to phototrophic activities. Differences in the microbiomes were also associated with different metabolic profiles, mostly due to specific compounds characterizing the host and its microbiome. Overall, this study provides new insights on the functionality of sponges and their prokaryotic symbioses’, and in particular, it discloses a descriptive sketch of the diverse compartments forming the sponge holobiont.</p>
2024-02-21 | MTBLS5125 | MetaboLights
Project description:Studying the evolution of viruses and their molecular epidemiology relies on accurate viral sequence data, so that small differences between similar viruses can be meaningfully interpreted. Despite its higher throughput and more detailed minority variant data, next-generation sequencing has yet to be widely adopted for HIV. The difficulty of accurately reconstructing the consensus sequence of a quasispecies from reads (short fragments of DNA) in the presence of large between- and within-host diversity, including frequent indels, may have presented a barrier. In particular, mapping (aligning) reads to a reference sequence leads to biased loss of information; this bias can distort epidemiological and evolutionary conclusions. De novo assembly avoids this bias by aligning the reads to themselves, producing a set of sequences called contigs. However contigs provide only a partial summary of the reads, misassembly may result in their having an incorrect structure, and no information is available at parts of the genome where contigs could not be assembled. To address these problems we developed the tool shiver to pre-process reads for quality and contamination, then map them to a reference tailored to the sample using corrected contigs supplemented with the user's choice of existing reference sequences. Run with two commands per sample, it can easily be used for large heterogeneous data sets. We used shiver to reconstruct the consensus sequence and minority variant information from paired-end short-read whole-genome data produced with the Illumina platform, for sixty-five existing publicly available samples and fifty new samples. We show the systematic superiority of mapping to shiver's constructed reference compared with mapping the same reads to the closest of 3,249 real references: median values of 13 bases called differently and more accurately, 0 bases called differently and less accurately, and 205 bases of missing sequence recovered. We also successfully applied shiver to whole-genome samples of Hepatitis C Virus and Respiratory Syncytial Virus. shiver is publicly available from https://github.com/ChrisHIV/shiver.
| S-EPMC5961307 | biostudies-literature
Project description:Recent efforts have shown that structural variations (SVs) can disrupt three-dimensional genome organization and induce enhancer hijacking, yet no computational tools exist to identify such events from chromatin interaction data. Here, we develop NeoLoopFinder, a computational framework to identify the chromatin interactions induced by SVs, including interchromosomal translocations, large deletions and inversions. Our framework can automatically resolve complex SVs, reconstruct local Hi-C maps surrounding the breakpoints, normalize copy number variation and allele effects and predict chromatin loops induced by SVs. We applied NeoLoopFinder in Hi-C data from 50 cancer cell lines and primary tumors and identified tens of recurrent genes associated with enhancer hijacking. To experimentally validate NeoLoopFinder, we deleted the hijacked enhancers in prostate adenocarcinoma cells using CRISPR–Cas9, which significantly reduced expression of the target oncogene. In summary, NeoLoopFinder enables identification of critical oncogenic regulatory elements that can potentially reveal therapeutic targets.
2021-03-23 | GSE161493 | GEO