Ontology highlight
ABSTRACT:
PROVIDER: PRJNA932599 | ENA |
REPOSITORIES: ENA
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Project description:Nitrate-reducing iron(II)-oxidizing bacteria are widespread in the environment contribute to nitrate removal and influence the fate of the greenhouse gases nitrous oxide and carbon dioxide. The autotrophic growth of nitrate-reducing iron(II)-oxidizing bacteria is rarely investigated and poorly understood. The most prominent model system for this type of studies is enrichment culture KS, which originates from a freshwater sediment in Bremen, Germany. To gain insights in the metabolism of nitrate reduction coupled to iron(II) oxidation under in the absence of organic carbon and oxygen limited conditions, we performed metagenomic, metatranscriptomic and metaproteomic analyses of culture KS. Raw sequencing data of 16S rRNA amplicon sequencing, shotgun metagenomics (short reads: Illumina; long reads: Oxford Nanopore Technologies), metagenome assembly, raw sequencing data of shotgun metatranscriptomes (2 conditions, triplicates) can be found at SRA in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA682552. This dataset contains proteomics data for 2 conditions (heterotrophic and autotrophic growth conditions) in triplicates.
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Project description:Purpose: The goal of this study is to compare endothelial small RNA transcriptome to identify the target of OASL under basal or stimulated conditions by utilizing miRNA-seq. Methods: Endothelial miRNA profilies of siCTL or siOASL transfected HUVECs were generated by illumina sequencing method, in duplicate. After sequencing, the raw sequence reads are filtered based on quality. The adapter sequences are also trimmed off the raw sequence reads. rRNA removed reads are sequentially aligned to reference genome (GRCh38) and miRNA prediction is performed by miRDeep2. Results: We identified known miRNA in species (miRDeep2) in the HUVECs transfected with siCTL or siOASL. The expression profile of mature miRNA is used to analyze differentially expressed miRNA(DE miRNA). Conclusions: Our study represents the first analysis of endothelial miRNA profiles affected by OASL knockdown with biologic replicates.
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Project description:We use nucleosome maps obtained by high-throughput sequencing to study sequence specificity of intrinsic histone-DNA interactions. In contrast with previous approaches, we employ an analogy between a classical one-dimensional fluid of finite-size particles in an arbitrary external potential and arrays of DNA-bound histone octamers. We derive an analytical solution to infer free energies of nucleosome formation directly from nucleosome occupancies measured in high-throughput experiments. The sequence-specific part of free energies is then captured by fitting them to a sum of energies assigned to individual nucleotide motifs. We have developed hierarchical models of increasing complexity and spatial resolution, establishing that nucleosome occupancies can be explained by systematic differences in mono- and dinucleotide content between nucleosomal and linker DNA sequences, with periodic dinucleotide distributions and longer sequence motifs playing a secondary role. Furthermore, similar sequence signatures are exhibited by control experiments in which genomic DNA is either sonicated or digested with micrococcal nuclease in the absence of nucleosomes, making it possible that current predictions based on highthroughput nucleosome positioning maps are biased by experimental artifacts. Included are raw (eland) and mapped (wig) reads. The mapped reads are provided in eland and wiggle formats, and the raw reads are included in the eland file. This series includes only Mnase control data. The sonicated control is part of this already published accession, as is a in vitro nucleosome map: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15188 We also studied data (in vitro and in vivo maps as well as a model) from http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13622 and from: http://www.ncbi.nlm.nih.gov/sra/?term=SRA001023
2010-08-20 | E-GEOD-23712 | biostudies-arrayexpress
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2016-02-01 | E-MTAB-4313 | biostudies-arrayexpress
Project description:Deep Sequencing of protein-coding and non-protein-coding RNAs from mouse differentiated embryonic stem cells and 14.5dpc mouse fetal head Analysis of Ribominus RNA from mouse differentiated embryonic stem cells and 14.5dpc mouse fetal head There are no processed data files for GSM566806-GSM566811. There are no fastq raw data files for GSM566812 and GSM566813 since these samples are the combined reads from all sequence lanes.
2011-12-06 | E-GEOD-22959 | biostudies-arrayexpress
Project description:Label-free protein sequencing is critically enabled by bottom-up, mass spectrometry-based proteomics workflows. Applications such as antibody sequencing or antigen discovery require de novo reconstruction of peptide and protein sequences. While trypsin has long served as the gold-standard protease in proteomics, its restricted C-terminal cleavage specificity constrains peptide diversity, particularly limiting coverage in antibody hypervariable complementarity-determining regions (CDRs). As a result, current workflows yield sparse reads and sequence gaps. Although multi-protease and hybrid-fragmentation strategies can notably improve coverage, they add complexity and compromise scalability and reproducibility. Here, we present a novel approach using HyperThermoacidic Archaeal (HTA) proteases Krakatoa or Vesuvius as powerful single-enzyme solutions for de novo antibody sequencing. Each protease generated over five times more unique peptide reads than trypsin or chymotrypsin with high redundancy across CDRs. Combined with EAciD fragmentation on a ZenoTOF 7600 system, this workflow enabled complete, unambiguous antibody sequencing. Despite most de novo tools being optimized for CID/HCD-tryptic data, analysis using PEAKS/DeepNovo and Stitch softwares showed that HTA-Proteases yielded up to fourfold higher alignment scores and fewer sequence mistakes across variable regions. Redundant reads increased more than threefold compared to standard proteases, boosting confidence in amino acid assignment and reducing ambiguity in final assemblies. Our alternative HTA-EAciD approach offers short digestion times, eliminates extensive cleanup, and enables analysis in a single LC-MS/MS run. This single-protease strategy delivers sequencing performance comparable to multi-enzyme workflows, providing a scalable, efficient, and highly confident approach for de novo sequencing in antibody discovery and beyond.
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