Ontology highlight
ABSTRACT:
PROVIDER: PRJNA554940 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Morus alba L. Raw protein sequence reads and sequence
2024-02-08 | PXD049451 | iProX
Project description:We report the application of ChIP-Seq technology for analyzing the DNA binding sites of SOD1 in the nucleus of HeLa cells. By obtaining a plenty of sequence from chromatin immunoprecipitated DNA, we generated genome-wide DNA binding sites of SOD1. After sequencing of ChIP samples, 42,737,195, 49,950,032, and 38,825,768 clean reads for control group, H2O2 treated group and LD100 (a specific inhibitor of SOD1) treated group were obtained through trimming the raw reads. We find that SOD1 occupies DNA sites with distinct sequence preference in the nucleus. The treatment with either H2O2 or LD100 was found to decrease the strength of SOD1 binding to DNA, indicating that the H2O2 exposure- or SOD1 inhibition-mediated redox dyshomeostasis may result in decreased genes that are reasonably regulated through alteration of SOD1 structures compared to control.
2018-12-20 | GSE124082 | GEO
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: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:Spiders are renowned for their efficient capture of flying insects using intricate aerial webs. How the spider nervous systems evolved to cope with this specialized hunting strategy and various environmental clues in an aerial space remains unknown. Here, we report a brain cell atlas of >30,000 single-cell transcriptomes from a web-building spider (Hylyphantes graminicola). Our analysis revealed the preservation of ancestral neuron types in spiders, including the potential coexistence of noradrenergic and octopaminergic neurons, and many peptidergic neuronal types that are lost in insects. By comparing the genome of two newly sequenced plesiomorphic burrowing spiders with three aerial web-building spiders, we found that the positively selected genes in the ancestral branch of web-building spiders were preferentially expressed (42%) in the brain, especially in the three mushroom body-like neuronal types. By gene enrichment analysis and RNAi experiments, these genes were suggested to be involved in the learning and memory pathway and may influence the spiders’ web-building and hunting behavior. Our results provide key sources for understanding the evolution of behavior in spiders and reveal how molecular evolution drives neuron innovation and the diversification of associated complex behaviors.
2023-10-24 | GSE241696 | GEO
Project description:The goals of this study are to use Next-generation sequencing (NGS) to detect bacterial mRNA profiles of wild-type A.baylyi ADP1, and its mRNA response under the exposure of two disinfectants, chloramine and free chlorine. The concentrations 10 mg/L. The group without dosing disinfectants was the control group. Each concentration was conducted in triplicate. By comparing the mRNA profiles of experimental groups and control group, the effects of these two disinfectants on transcriptional levels can be revealed. Illumina HiSeq 2500 was applied. The NGS QC toolkit (version 2.3.3) was used to treat the raw sequence reads to trim the 3’-end residual adaptors and primers, and the ambiguous characters in the reads were removed. Then, the sequence reads consisting of at least 85% bases were progressively trimmed at the 3’-ends until a quality value ≥ 20 were kept. Downstream analyses were performed using the generated clean reads of no shorter than 75 bp. The clean reads of each sample were aligned to the A.baylyi ADP1 reference genome (NC_005966.1), using SeqAlto (version 0.5). Cufflinks (version 2.2.1) to calculate the strand-specific coverage for each gene, and to analyze the differential expression in triplicate bacterial cell cultures. The statistical analyses and visualization were conducted using CummeRbund package in R. (http://compbio.mit.edu/cummeRbund/). Gene expression was calculated as fragments per kilobase of a gene per million mapped reads (FPKM, a normalized value generated from the frequency of detection and the length of a given gene.
2021-05-12 | GSE142062 | GEO
Project description:Whole exome sequencing of 5 HCLc tumor-germline pairs. Genomic DNA from HCLc tumor cells and T-cells for germline was used. Whole exome enrichment was performed with either Agilent SureSelect (50Mb, samples S3G/T, S5G/T, S9G/T) or Roche Nimblegen (44.1Mb, samples S4G/T and S6G/T). The resulting exome libraries were sequenced on the Illumina HiSeq platform with paired-end 100bp reads to an average depth of 120-134x. Bam files were generated using NovoalignMPI (v3.0) to align the raw fastq files to the reference genome sequence (hg19) and picard tools (v1.34) to flag duplicate reads (optical or pcr), unmapped reads, reads mapping to more than one location, and reads failing vendor QC.
2016-02-01 | E-MTAB-4313 | biostudies-arrayexpress
Project description:Purpose: The goal of this study are to investigate the TRPM1-regulated genes using RNAseq to compare the transcriptome profiling between 661W cells expressing TRPM1 and control vectors Methods: RNAs were isolatedusing the RNeasy Mini kit (Qiagen). RNA-seq libraries were prepared using the KAPA mRNA HyperPrep Kit (KAPA Biosystems, Roche, Basel, Switzerland) and validated using the Qsep 100 DNA/RNA Analyzer (BiOptic Inc., Taiwan). Libraries were sequenced on a NovaSeq 6000 sequencer (Illumina, CA, USA). Clean reads were aligned to the mouse genome (GRCm38) using HISAT2 (version 2.1.0) after removing low-quality reads. The differential expression of genes between TRPM1-overexpression and control cells was computed using the fragments per kilobase of transcript per million mapped reads calculated by featureCounts (version 2.0.0). Raw read counts were imported into edgeR (version 3.28.1) and analyzed by using R package of DESeq (version 1.40.0). Genes with false discovery rate (FDR) p-value < 0.05 adjusted by using Benjamini–Hochberg (BH) method were considered as differentially expressed genes (DEGs). Gene set enrichment analysis of the genes differentially expressed upon TRPM1 expression was done using the Gene Set Knowledgebase（GSKB）hallmark gene sets. Results: We had 40,922,040 clean reads in the control group and 44,244,608 clean reads in the TRPM1-overexpressing group. We mapped 43,253, 668 (97.76%) sequence reads in the control group and 39,942,649 (97.6%) sequence reads in the TRPM1-overexpressing group. We identified 16,014 transcripts. 76 transcripts showed differential expression between the vector control group and TRPM1-expressing group, with a fold change ≥1.5 and p value <0.01. Gene set enrichment analysis of the genes differentially expressed upon TRPM1 expression uncovered several TRPM1-regulated genes that may contribute to photoreceptor function, such as retina morphogenesis and JAK-STAT cascade. Conclusions: Our study represents the genes associated with TRPM1 overexpression in 661W photoreceptor cells using RNA-seq approach. The overexpression of TRPM1 may contribute to regulate the photoreceptor morphogenesis and function
2021-01-29 | GSE165691 | GEO
Project description:Macrobrachium nipponense different living states Raw sequence reads
| PRJNA656359 | ENA
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