Ontology highlight
ABSTRACT:
PROVIDER: PRJNA305443 | ENA |
REPOSITORIES: ENA
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Project description:Morus alba L. Raw protein sequence reads and sequence
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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.
2022-09-06 | GSE186354 | GEO
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.
2021-05-17 | PXD023186 | Pride
Project description:Purpose: The goal of this study is to compare exosomal small RNA transcriptome of HCT116 cells to identify the target of PRDX3 under basal or knock down conditions by utilizing miRNA-seq. Methods: miRNA profilies of siCTL or siPRDX3 transfected HCT 116 exosoems were generated by illumina sequencing method, in triplicate. After sequencing, the raw sequence reads are filtered based on quality.Sequence reads were mapped with the bowtie2 software tool, which yielded bam files. Mature miRNA sequences were used as references for mapping. Read counts mapped to a mature miRNA sequence were extracted from the alignment file using bedtools v2.25.0 and Bioconductor, which use the R statistical programming language. Read counts were used to determine the expression level of miRNAs. The CPM+TMM normalization method was used for between-sample comparison. Results: We identified known miRNA in species (miRDeep2) in the HCT116 exosome transfected with siCTL or siPRDX3. The expression profile of mature miRNA is used to analyze differentially expressed miRNA(DE miRNA). Conclusions: Our study represents the first analysis of HCT116 exosomal miRNA profiles affected by PRDX3 knockdown with biologic replicates.
2025-01-01 | GSE247624 | GEO
Project description:A cDNA library was constructed by Novogene (CA, USA) using a Small RNA Sample Pre Kit, and Illumina sequencing was conducted according to company workflow, using 20 million reads. Raw data were filtered for quality as determined by reads with a quality score > 5, reads containing N < 10%, no 5' primer contaminants, and reads with a 3' primer and insert tag. The 3' primer sequence was trimmed and reads with a poly A/T/G/C were removed
2021-07-21 | GSE180131 | GEO
Project description:Purpose: To characterize the differential microRNA expression profiles and microRNA editing upon PRRSV infection, using NGS techonology, we sequenced small RNAs of the lungs of Tongcheng and Landrace pigs before (0 dpi) and after (3, 5, 7 dpi) infection with high-pathogenic PRRSV (HP-PRRSV). Methods: The miRNA expression profiles of the lungs of Tongcheng and Landrace pigs before (0 dpi) and after (3, 5, 7 dpi) HP-PRRSV infection were produced by using solexa platform. The raw reads with low qualities were filtered and the clean high quality reads were mapped to Ensembl Sus reference genome 10.2.71 using BWA. The unique mapped reads were retained for microRNA expression analysis. The raw reads counts of each microRNA were calculated by perl scripts and the differentially expressed microRNA (Fold change >2; FDR <0.05) were called using edgeR. The microRNA editing was identified using the methods described by Alon, S. and E. Eisenberg. Methods Mol Biol, 2013. Further analysis of microRNA editing was performed with perl scripts.
2014-10-10 | GSE58436 | GEO
Project description:Purpose: In order to understand the functional significance of sperm transcriptome in stallion fertility, the aim of this study was to generate a detailed body of knowledge about the sperm RNA profile that defines a normal fertile stallion. Methods: The 50 bp single-end ABI SOLiD raw reads were directly aligned with the horse reference sequence EcuCab2 using ABI aligner software (NovoalignCS version 1.00.09, novocraft.com) which uses multiple indexes in the reference genome, identifies candidate alignment locations for each primary read, and allows completion of the alignment. Results: Next generation sequencing (NGS) of total RNA from the sperm of two reproductively normal stallions generated about 70 million raw reads and more than 3 Gb of sequence per sample; over half of these aligned with the EcuCab2 reference genome. Altogether, 19,257 sequence tags with average coverage ?1 (normalized number of transcripts) were mapped in the horse genome. Conclusion: The sequence of stallion sperm transcriptome is an important foundation for the discovery of transcripts of known and novel genes, and non-coding RNAs, thus improving the annotation of the horse genome sequence draft and providing markers for evaluating stallion fertility. Reproductively fertile Stallion sperm transcriptome as revealed by RNA sequencing
2013-02-19 | E-GEOD-38725 | biostudies-arrayexpress
Project description:Purpose: In order to understand the functional significance of sperm transcriptome in stallion fertility, the aim of this study was to generate a detailed body of knowledge about the sperm RNA profile that defines a normal fertile stallion. Methods: The 50 bp single-end ABI SOLiD raw reads were directly aligned with the horse reference sequence EcuCab2 using ABI aligner software (NovoalignCS version 1.00.09, novocraft.com) which uses multiple indexes in the reference genome, identifies candidate alignment locations for each primary read, and allows completion of the alignment. Results: Next generation sequencing (NGS) of total RNA from the sperm of two reproductively normal stallions generated about 70 million raw reads and more than 3 Gb of sequence per sample; over half of these aligned with the EcuCab2 reference genome. Altogether, 19,257 sequence tags with average coverage ≥1 (normalized number of transcripts) were mapped in the horse genome. Conclusion: The sequence of stallion sperm transcriptome is an important foundation for the discovery of transcripts of known and novel genes, and non-coding RNAs, thus improving the annotation of the horse genome sequence draft and providing markers for evaluating stallion fertility.
2013-02-19 | GSE38725 | GEO
Project description:Purpose: The goals of this study are to use RNA-seq-derived JHH-7 cell transcriptome profiling for differentially expressed genes after PRMT5 knockdown. Methods: mRNA profiles of control and PRMT5 knockdown JHH-7 cells were generated by RNA-seq, using Illumina Novaseq 6000.The sequence reads that passed quality filters were analyzed at the transcript isoform level with TopHat2 or HISAT2. The gene expression quantification was performed using RSEM tool and generated raw count for all genes individually. qRT–PCR validation was performed using SYBR Green assays. Results: On average, we generated >200 million paired end reads for each sample, with more than 95% of the reads passed the QC.
2021-03-12 | GSE168745 | GEO
Project description:Single-cell transcriptomics (scRNA-seq) has revolutionized our understanding of cell types and states in various contexts, such as development and disease. Most methodology relies on poly(A) enrichment to selectively capture protein-coding polyadenylated transcripts, intending to exclude ribosomal transcripts that constitute >80% of the transcriptome. However, it is common for ribosomal transcripts to sneak into the library, which can add significant background by flooding libraries with irrelevant sequences. The challenge of amplifying all RNA transcripts from a single cell has motivated the development of new technologies to optimize retrieval of transcripts of interest. This problem is notable in planarians, where we find that 16S ribosomal transcripts were widely enriched (20-80%) across single-cell methods. Therefore, we adapted the Depletion of Abundant Sequences by Hybridization (DASH) to the standard 10X scRNA-seq protocol. We designed single-guide RNAs tiling the 16S sequence for CRISPR-mediated degradation, and subsequently generated untreated and DASH-treated datasets from the same libraries to enable a side-by-side comparison of the effects of DASH. DASH specifically removes 16S sequences without off-target removal of other genes. By assessing the cell barcodes shared by both libraries, DASH-treated cells have consistently higher complexity given the same amount of reads, which allows the detection of a rare cell cluster and more differentially expressed genes. In conclusion, DASH can be easily integrated into existing sequencing protocols and customized to deplete any unwanted transcripts.
2023-08-07 | GSE231548 | GEO