Strand-oriented RNAseq of LNCaP prostate cancer cells in culture for 48 h in the absence of androgen
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE79301 | GEO | 2016/09/08
SECONDARY ACCESSION(S): PRJNA315431
REPOSITORIES: GEO
Similar Datasets
Project description:The goal of this study was to use NGS RNAseq deep-sequencing in order to characterize the complement of polyadenylated mRNAs and lncRNAs expressed in LNCaP, a prostate cancer cell line. RNA-seq data were processed as aggregates of the two biological replicates to increase resulting transcriptome coverage. Trimmed reads were mapped with TopHat v.2.0.12 and Bowtie v.2.2.3, and a custom GTF file to guide transcriptome assembly. This custom GTF file was built by using the human transcriptome annotation GTF file downloaded from Ensembl Project web-site (http://www.ensembl.org/) and modified to include all lncRNAs reported in Cabili et al, Genes & Development 2011. polyA+ RNA profiles of LNCaP prostate cancer cell line grown in culture for 48 h in the absence of androgen were generated by paired-end deep sequencing, in duplicate, using Illumina HiSeq2000.
2016-09-08 | E-GEOD-79301 | biostudies-arrayexpress
Project description:The aim of this study was to use NGS RNAseq deep-sequencing in order to characterize the polyadenylated mRNAs and lncRNAs expressed in LNCaP cells treated with androgen hormone compared with untreated LNCaP cells (GSE79301). Trimmed reads were mapped using the hg19 genome with TopHat v.2.0.12 and Bowtie v.2.2.3. The assembly was guided by a custom GTF file created with transcripts fromhuman lncRNA annotations from GENCODE v19 (Harrow, Frankish et al.2012) and those already annotated as lincRNAs in (Cabili, Trapnell et al. 2011; Prensner, Iyer et al. 2011; Hangauer, Vaughn et al. 2013). The diferencial expression was calculated by the sum of exon read count per gene with HTSeq (Anders, Pyl et al. 2015), followed by a DESeq2 analysis (Love, Huber et al. 2014).
2017-12-31 | GSE102305 | GEO
Project description:Purpose: Study the differentially expressed genes in hippocampal rat CA1 regions 90 minutes after Long-Term Potentiation (LTP) was induced using field recordings Methods: hippocampal rat CA1 region mRNA profiles of control (unstimulated) and 90 minutes after LTPwas induced (LTP 90) were generated by deep sequencing. A pool of approximately 10 CA1 regions collected from at least 3 different animals were used. The seq library was prepared using TruSeq RNA Sample Prep Kit v2 protocol (Illumina, CA, USA). For the RNA-Seq data analysis Tophat 2.0.13, bowtie 2.1.0 , samtool 0.1.7 and cufflinks 1.3.0 were used. The rn5-bowtie2 index was generated with the command 'bowtie2-build rn5.fa rn5'. The 'rn5.fa'-file was downloaded from the UCSC genome browser. The mm10-bowtie2 index was downloaded from http://bowtie-bio.sourceforge.net/bowtie2/manual.shtml. RefSeq geneTracks and GTF-files for the rn5 and mm10 genome assembly were downloaded from UCSC genome browser. Common gene ids in the GTF-files were matched to individual transcript_ids using the corresponding official symbols obtained from the geneTracks files. Conclusions: Our study illustrates the nature of the different transcripts in acute rat hippocampal slices after LTP 90 minutes was induced using field electrophysiology and compares them with control, unstimulated slices. Thius allowed us to identify wich genes are modulated in the hippocampus in order to promote and sustain LTP.
2018-10-02 | GSE120712 | GEO
Project description:We profiled total-mRNA from yeast cells grown in identical conditions to match samples submitted for proteome-wide absolute quantification. Matching mRNA profiles to absolute protein copies numbers enables a more accurate comparison of transcript to final protein levels. Here we were able to show direct comparison results in a correlation of Rsquared of 0.58, show suggesting as much as ~40% of final protein levels in yeast cannot be determined from mRNA levels alone. Reads were mapped to a reference genome of S. cerevisiae, downloaded from the Saccharomyces Genome Database (SGD), using Bowtie version 1 (74). Mapped sequences were then assembled into transcripts and quantified using Cufflinks version 2.0 (75) (using the SGD reference genome GTF file).
2015-10-10 | GSE73898 | GEO
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of gene expression profiles of a chlorosis mutant of Pakchoi. The goals of this study are to transcriptome analysis of a chlorosis. Methods: mRNA profiles of the aboveground parts of WT and a chlorosis mutant were generated by deep sequencing, in triplicate, using Illumina Hiseq platform. The reference genome and gene model annotation files were downloaded from the genome website （http://brassicadb.org/brad/index.php, v1.5）. An index of the reference genome was built using Bowtie v.2.2.3 and paired-end clean reads were aligned to the reference genome using TopHat v.2.0.12. qRT–PCR validation was performed using SYBR Green assays. Results: Based on the threshold values of absolute value of log2 ratio ≥ 1 and FDR ≤ 0.05, a total of 2958 DEGs was identified. Among 2958 DEGs, 9 DEGs related to chlorophyll synthesis and chlorophyll metabolism were identified. The DEGs identified by RNA sequencing were confirmed by qRT-PCR analysis, indicating that the data were reliable. These findings provide information that can be useful for investigating the molecular mechanisms of leaf color mutant. Conclusions: The results presented here reveal changes in the transcriptome profile of a chlorosis mutant. DEGs related to chlorophyll biosynthesis were detected.. These findings provide information that can be useful for investigating the molecular mechanisms underlying the response to chilling stress in cucumber and other plants.
2019-03-23 | GSE112255 | GEO
Project description:Purpose: Study the differentially expressed genes in the hippocampus of mice, comparing Wt1∆ mice with their control wild type littermates in basal conditions (naïve untrained animals). Methods: Forebrain-specific deletion of Wt1 was achieved by crossing animals homozygous for the conditional Wt1 knockout allele (Wt1fl/fl) with a transgenic line, Camk2a-Cre, (B6.Cg-Tg(Camk2a-cre)T29-1Stl/J; Jackson Lab: http://jaxmice.jax.org/strain/005359.html). Expression of Cre recombinase resulted in the in-frame deletion of exons 8 and 9 and generated a truncated allele encoding a shortened non functional WT1 protein lacking zinc fingers 2 and 3 in their forebrain (starting at P21). Brains of Wt1∆ mice (n=2) and their control littermates (wild type; n=2) were removed, dorsal hippocampi were dissected and used for library preparation. The seq library was prepared using TruSeq RNA Sample Prep Kit v2 protocol (Illumina, CA, USA). For the RNA-Seq data analysis Tophat 2.0.13, bowtie 2.1.0 , samtool 0.1.7 and cufflinks 1.3.0 were used. The rn5-bowtie2 index was generated with the command 'bowtie2-build rn5.fa rn5'. The 'rn5.fa'-file was downloaded from the UCSC genome browser. The mm10-bowtie2 index was downloaded from http://bowtie-bio.sourceforge.net/bowtie2/manual.shtml. RefSeq geneTracks and GTF-files for the rn5 and mm10 genome assembly were downloaded from UCSC genome browser. Common gene ids in the GTF-files were matched to individual transcript_ids using the corresponding official symbols obtained from the geneTracks files. Conclusions: Our study illustrates the nature of the different transcripts in Wt1∆ mice compared to their control wild type littermates at basal state (untrained). This experiment allowed us to identify wich genes are modulated in the hippocampus by the transcription fator WT1.
2018-10-02 | GSE120708 | GEO
Project description:Operon prediction for Mycobacterium tuberculosis using RNA-seq data and GTF file
| PRJEB52835 | ENA
Project description:TaGPC1 and TaGPC2 are NAC-domain transcription factors which accelerate the onset of senescence and facilitate nutrient translocation in wheat. We developed knockout mutants of these genes in tetraploid wheat and used RNA-seq to identify the effect of these mutations on the wheat flag leaf transcriptome during monocarpic senescence. Several transporter-related genes were identified which were upregulated during senescence and differentially expressed between genotypes. Illumina cDNA libraries were constructed from four biological replicates of three genotypes (WT, gpc-a1 and gpc-a1/gpc-b2) at three timepoints (Heading date, 12 days after anthesis and 22 days after anthesis). Reads were aligned to a collection of assembled genomic contigs from flow-sorted chromosome arms (A and B genomes only) provided by the International Wheat Genome Sequencing Consortium. A custom GTF file was generated to identify 139828 gene loci corresponding to transcribed regions of this reference sequence. Please note that the contig names provided by URGI (http://wheat-urgi.versailles.inra.fr/Seq-Repository) were used in the analysis. Most, but not all, of these loci are present in Ensembl (With a modified name, but the same basic information, chromosome arm and unique contig ID) at ftp://ftp.ensemblgenomes.org/pub/plants/release-22/fasta/triticum_aestivum/dna/ Therefore, the contig IDs from URGI (which are available for all our sequences) were used in the processed data file (i.e. the count table and GFF file) and an additional file describing the corresponding Ensembl names for these was provided (Additional_file_2.xlsx).
2014-12-23 | E-GEOD-60635 | biostudies-arrayexpress
Project description:***This experiment was updated on 26-02-2016 to correct the accidental mis-labelling of some raw data files. For data downloaded before this date, please note that the file labelled as Caulonema_a.pair contains the raw data for Chloronema A and the file labelled as Chloronema_a.pair contains the data for Caulonema A. ***** We analyzed the transcriptional profile of all phases in the life cycle of P. patens, including all major tissues and 4 different sporophyte developmental stages. For this analysis we took advantage of a custom designed NimbleGene microarray based on genome version 1.6, and developed adequate protocols for the isolation and purification of mRNA directly from mechanically purified cells of chloronema, caulonema, rhizoids, gametophores, sporophytes, spores, archegonia and protoplasts.
2015-12-01 | E-MTAB-3069 | biostudies-arrayexpress
Project description:To obtain a preliminary picture at the transcriptional level of the set of genes linked to the regulatory activity of the small RNA GssA of P. aeruginosa PA14, we analyzed the global transcription profile of PA14deltagssA strain in comparison with PA14 by an RNA-seq approach, extracting total RNA at OD600 of 2, corresponding to early stationary phase, when the two strains were grown in Brain Heart Infusion (BHI) rich medium, a condition in which, at the time of its identification, a relevant expression of GssA was noted. For each strain, three independent biological replicates were performed. The concentration and the purity of the RNA starting material were determined spectrophotometrically while RNA Integrity Number (RIN) was measured on an Agilent TapeStation 4200. An additional DNase step was included to cleave DNA that could interfere with rRNA removal and negatively affect library preparation and sequencing. RNA libraries were generated starting from 3 μg of total RNA. rRNA was depleted with Illumina Ribo-Zero rRNA Removal Kit (Gram-Negative Bacteria) and libraries were generated according to Illumina TruSeq® Stranded mRNA Library Prep protocol. RNA libraries were accurately quantified with a fluorometric method: QUBIT dsDNA HS assay kit and the size and purity were verified on an Agilent TapeStation 4200. RNA libraries were then sequenced on an Illumina HiSeq with paired-end reads 150 bp long. For RNA-Seq data analysis, P. aeruginosa UCBPP-PA14 (NCBI: NC_008463.1) genome and annotation (GTF) were downloaded from the Pseudomonas Genome Database. Alignment of paired Fastq RNA-Seq reads to P. aeruginosa UCBPP-PA14 genome was performed using the STAR aligner (v2.7.0) with the quantMode TranscriptomeSAM GeneCounts option turned on. SAM files were converted to BAM, sorted, and indexed using SAMtools. Differential gene expression analysis was performed using DESeq2 using a design = ~ condition model and dedicated R scripts. The false discovery rate was controlled using the Benjamini-Hochberg procedure, with an adjusted p-value (FDR) ≤ 0.1. P. aeruginosa gene IDs were annotated with a gene description field using a custom tool (IdToGeneNamesScript) using the P. aeruginosa UCBPP-PA14 GTF file as annotation input.
2022-11-30 | E-MTAB-12073 | biostudies-arrayexpress