Soil Single Cell Assembly
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1251845 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Precipitation change is often associated with climate warming, but its effects on soil microbial community assembly remain relatively underexplored. Traditionally, it is thought that increasing the magnitude of environmental changes will increase the importance of deterministic processes in community assembly. Here, while ±30% precipitation promoted deterministic processes in the assembly of soil prokaryotic community during a five-year semiarid grassland experiment, ±60% precipitation increased the importance of stochastic processes like random birth/death, countering to conventional thinking. Similarly, analysis of a multifactorial experiment showed that +54% precipitation stimulated a random bacterial birth process while other environmental change factors did not. In addition, the increased taxonomic stochasticity under ±60% precipitation translated into functional stochasticity at the gene, protein, and enzyme levels. Our results revealed the distinctive mechanism and critical role of precipitation in determining microbial assemblages, demonstrating the need to integrate microbial taxonomic information to better predict their functional responses to precipitation changes.
2020-12-13 | PXD023103 |
Project description:The B-cell receptor (BCR) enables individual B cells to identify diverse antigens, including bacterial and viral proteins. While advances in RNA-seq have enabled high throughput profiling of transcript expression in single cells, the unique task of assembling the full-length heavy and light chain sequences from single cell RNA-sequencing (scRNA-seq) in B cells has been largely unstudied. We developed a new software tool, BASIC, which allows investigators to use scRNA-seq for assembling BCR sequences at single cell level. To demonstrate the utility of our software, we subjected single B cells from a human donor to scRNA-seq, assembled the full-length heavy and the light chains, and experimentally confirmed these results by using single cell primer based nested PCRs and Sanger sequencing.
2016-06-02 | E-MTAB-4745 | biostudies-arrayexpress
Project description:Soil Metagenome Assembly Genome sequencing and assembly
| PRJNA1251844 | ENA
Project description:<p>Single-cell metabolomics reveals cell heterogeneity and elucidates intracellular molecular mechanisms. However, general concentration measurement of metabolites can only provide a static delineation of metabolomics, lacking the metabolic activity information of biological pathways. Herein, we developed a universal system for dynamic metabolomics by stable isotope tracing at the single-cell level. This system comprises an organic mass cytometry-based single-cell metabolomic platform and an automated metabolite quantification and untargeted metabolic flux data processing platform, providing an integrated workflow for dynamic metabolomics of living single cells. As a proof-of-concept, a total of 40 labeled metabolites were tracked in single breast cancer cells, enabling the global profiling and correlation analysis of metabolic activities across various metabolic pathways, as well as flow analysis of interlaced metabolic networks. The significance of metabolic activity profiling was underscored by a 2-deoxyglucose inhibition model, demonstrating delicate metabolic alteration within single cells which cannot reflected by concentration analysis. Significantly, the system combined with a neural network model successfully enabled the metabolomic profiling of direct co-cultured tumor cells and macrophages. This revealed intricate cell-cell interaction mechanisms within the tumor microenvironment and firstly identified versatile polarization subtypes of tumor-associated macrophages based on their metabolic signatures. Importantly, these findings are in line with the renewed diversity atlas of macrophages from genome features obtained through single-cell RNA-sequencing. The developed system facilitates a comprehensive understanding and opens a new avenue of single-cell metabolomics from both static and dynamic perspectives.</p>
2025-04-14 | MTBLS11091 | MetaboLights
Project description:The soil worm Enchytraeus crypticus (oligochaete) is an ecotoxicology model species although without genome or transcriptome sequence information. The present research aimed at studying, via high-throughput pyrosequencing, the transcriptome of Enchytraeus crypticus, sampled from multiple test conditions, and the construction of a high-density microarray for functional genomic studies. A pyrosequencing run retrieved approximately 1.5 million reads representing 645 million bases. After assembly, 27,296 contigs and 87,686 singletons were obtained. from which 44% and 25% were annotated as protein-coding genes. We show that the high amount of orphan genes is not due to poor sequence or assemble quality: 84% of the contig sequences contains an open reading frame with a start codon and E. crypticus homologs were identified for 92% of the core eukaryotic genes. Moreover, 65 and 77% of the unknown singletons and contigs, respectively, showed transcriptional activity. An Agilent 180K microarray platform was designed and validated by hybridizing cDNA from 3 day zinc- exposed E. crypticus to the concentration corresponding to 50% reduction in reproduction (EC50). Overall, 70% of all probes exerted a hybridization signal above background level. More specifically, the probes derived from contigs showed a wider range of average intensities when compared to probes derived from singletons. In total, 522 significantly regulated transcripts were identifying upon zinc exposure. Several significantly regulated genes exerted predicted functions (e.g. zinc efflux, zinc transport) associated with zinc stress. Unexpectedly, the microarray data suggest that zinc exposure alters retrotransposon activity in the E. crypticus genome. In conclusion, characterization of the presented E. crypticus transcriptome and associated microarray platform is a valuable and high quality resource that permits further functional genomics experiments examining gene expression patterns underlying distinct environmental stress conditions. We show that unknown sequences are not the result of technical errors but mostly represent functional genes that are actively transcribed. The data presented in our manuscript is part of a larger experiment which was performed in single, large loop design. The analysis presented here can be replicated only by including all raw data from the larger experiment (all raw files are included in the archive linked to this submission). A single channel, interwoven loop design was used to test animals exposed to zinc EC50 on reproduction as compared to untreated controls for 4 days. 4 biological replicates per condition were used containing 25 grams of soil and 5 - 7, adult old animals per replicate. T4_con stands for untreated control soil while T4_50 are the samples exposed to EC50 of zinc on reproduction.
2014-05-01 | E-GEOD-51838 | biostudies-arrayexpress
Project description:<p class='ql-align-justify'>Megasphaera hexanoica KCCM 43214T, isolated from cow rumen, is capable of producing medium-chain carboxylic acids such as n-caproate and n-caprylate. In this study, we present a high-quality genome assembly, along with intracellular metabolomic profiling and pangenomic analysis. Illumina sequencing generated 2.3 Mbp from 15,293,634 reads with a GC content of 49.5%, while PacBio HiFi sequencing produced 331.5 Mbp across 45,266 reads, with an average read length of 7,323 bp and a HiFi read N50 of 8,214 bp. Hybrid assembly of short and long reads resulted in a single 2.88 Mbp contig, containing 2,075-2,083 unique genes. A genome-scale metabolic model was constructed, to evaluate its metabolic capabilities under specific growth conditions. Intracellular metabolomic analysis of cells grown in fructose medium and lactate medium revealed key metabolic activities associated with chain elongation. Pangenomic analysis across nine annotated genomes identified 6,721 orthologous gene using OrthoMCL, emphasizing the genetic and functional diversity within the Megasphaera genus. This dataset offers valuable insights into the metabolism and biotechnological potential of M. hexanoica KCCM 43214T.</p>
2026-04-03 | MTBLS14019 | MetaboLights
Project description:Evaluation of different strategies to interpret metaproteomics data acquired on soil samples from a floodplain along the Seine River (France) incorporating sample-specific metagenomics data, soil genome catalogue database, and generic sequence database.
2022-02-17 | PXD026798 | Pride
Project description:Accurate annotation of transcript isoforms is crucial to understand gene functions, but automated methods for reconstructing full-length transcripts from RNA sequencing (RNA-seq) data remain imprecise. We developed Bookend, a software package for transcript assembly that incorporates data from different RNA-seq techniques, with a focus on identifying and utilizing RNA 5′ and 3′ ends. Through end-guided assembly with Bookend we demonstrate that correct modeling of transcript start and end sites is essential for precise transcript assembly. Furthermore, we discovered that utilization of end-labeled reads present in full-length single-cell RNA-seq (scRNA-seq) datasets dramatically improves the precision of transcript assembly in single cells. Finally, we show that hybrid assembly across short-read, long-read, and end-capture RNA-seq datasets from Arabidopsis, as well as meta-assembly of RNA-seq from single mouse embryonic stem cells (mESCs) can produce end-to-end transcript annotations of comparable quality to reference annotations in these model organisms.
2022-01-08 | GSE189482 | GEO
Project description:The primary cell walls of land plants are composed principally of a load bearing cellulose microfibril-hemicellulose network embedded in a matrix of pectic polysaccharides. The pectic matrix is multifunctional and in additional to a directly structural role it is central to many fundamental plant processes including cell expansion, defence and cell signalling. The sequencing of the Arabidopsis genome has revealed the massive investment made by plants in modulating the pectic matrix in response to local functional requirements but despite concerted biochemical-based efforts over many years none of the genes involved in pectin biosynthesis/pectic matrix assembly have so far been identified. The pectin matrix contains some of the most complex polysaccharides found in nature and based on linkage analysis it is known that at least 53 glycosyltransferases must be involved in its construction. Our proposal to identify genes involved in pectin biosynthesis and matrix assembly exploits the well characterised phenomenon that many plants and cultured plant cells that are exposed to treatments that disrupt the synthesis of one cell wall component are capable of a compensatory increases in other components - including pectin. Specifically suspension cultured cells that are incrementally exposed to increasing concentrations of the herbicide 26-dichlorobenzonitrile (DCB) which specifically inhibits cellulose synthesis compensate for the resulting almost complete loss of cellulose from their cell walls by constructing walls made predominantly of pectin. We believe that the significant up-regulation of pectin biosynthesis in this system offers an opportunity to identify genes that function in the assembly of the pectic matrix by microarray comparison of transcripts of DCB-treated Arabidopsis cells with untreated cells. The use of Arabidopsis suspension-cultured cells rather than plants or seedlings offers the significant advantage that extracted RNA would be derived from only one cell type. It is anticipated therefore that the output from a transcriptome analysis of this system will indicate a number of genes of unknown function and lead to the identification of genes involved in pectin biosynthesis and the assembly of the pectin matrix. Experiment Overall Design: 6 samples
2008-06-14 | E-GEOD-6181 | biostudies-arrayexpress
Project description:Soil water repellency (SWR) (i.e. soil hydrophobicity or decreased soil wettability) is a major cause of global soil degradation and a key agricultural concern. This metabolomics data will support the larger effort measuring soil water repellency and soil aggregate formation caused by microbial community composition through a combination of the standard drop penetration test, transmission electron microscopy characterization and physico-chemical analyses of soil aggregates at 6 timepoints. Model soils created from clay/sand mixtures as described in Kallenbach et al. (2016, Nature Communications) with sterile, ground pine litter as a carbon/nitrogen source were inoculated with 15 different microbial communities known to have significantly different compositions based on 16S rRNA sequencing. This data will allow assessment of the direct influence of microbial community composition on soil water repellency and soil aggregate stability, which are main causes of soil degradation.
The work (proposal:https://doi.org/10.46936/10.25585/60001346) conducted by the U.S. Department of Energy Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science User Facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231.
2024-02-14 | MSV000094090 | MassIVE