3061f138-88ea-4fbc-8868-0478d55ec7bd - samples
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PROVIDER: EGAD00001007821 | EGA |
REPOSITORIES: EGA
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Project description:Data quality control and adaptor-trimmed were performed with the Trimomatic tool. Paired-reads were mapped to the hg19 human reference with methylCtools aligner.
| EGAS00001004346 | EGA
Project description:Purpose: Purpose:Exploring genes regulated by trim11 and kdm5c in breast cancer Methods: TRIM11 knock down and KDM5C knock down MDA-MB-231 cell lines were constructed and Trim11 knock down MMTV mice were generated. The RNA-seq libraries of cell lines and mice mammary tumors were sequenced by Illumina Nova-seq platform with pair-end reads of 150 bp. Results: Quality control of mRNA-seq data was performed using Fatsqc and low-quality bases were trimmed. The adaptor sequence was removed using Cutadapt (version 1.16) to clean RNA-seq raw data. All RNA-seq data were mapped to the human reference genome (hg19) or mouse reference genome (mm10) by HISAT2 (version 2.1.0). The gene expression level was calculated by Cufflinks with default parameters. Differential expressed genes (DEGs) were identified by 1.5-fold change and p-value < 0.05. Gene ontology analysis and KEGG pathways analysis was performed using DAVID (https://david.ncifcrf.gov). Conclusions: Our study represents biological process and KEGG pathway enrichment analyses of TRIM11 and KDM5C down-regulated genes or up-regulated genes
2022-10-27 | GSE185831 | GEO
Project description:Purpose: The purpose of this data is to compare the transcriptome of embryonic stem cell (ESCs), Induced pluripotent stem cell (iPSCs) and fibroblasts using RNA-seq. Methods: Total RNA was harvested by Trizol (Invitrogen) and RNA profiles of samples were generated by sequencing. Illumina Casava 1.8 software used for basecalling. Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence (using fastx_trimmer) then mapped to hg19 (genome build) whole genome using Tophat. This study provides a framework for the application of pluripotent stem cells RNA expression dynamics compare to fibroblasts profiling toward characterization.
2020-04-23 | GSE130241 | GEO
Project description:This experiment is to explore the mechanism of anti-inflammatory activity of celastrol derivatives on Rheumatoid arthritis fibroblast-like synoviocytes (RAFLS), compared with celastrol. Immortalized RAFLS cells were simulated with 1 ng/mL TNFα for 24h, and exposed to different treatments during the last 4 hours. Total RNA was extracted with Trizol. Transcriptomic profiling was performed with an in-house, proprietary method that captures the 3’ primed end of mRNA molecules for sequencing. The data was processed with a custom script. Briefly, sequencing reads were demultiplexed based on sample barcode with idemux, trimmed with cutadapt to remove polyA, adaptor and low-quality sequences, mapped to human GRCh38 reference assembly with STAR aligner. PCR duplicates were removed based on UMI with UMI-tools. Htseq-count was used to generate read counts. The count matrix was analyzed with DESeq2 package to determine differential genes. Enrichment and GSEA was performed with clusterprofiler.
2025-09-01 | GSE300831 | GEO
Project description:Purpose: RNA-seq analysis to evaluate the impact of MED23 knockdown on the transcriptome of HUVEC cells.Methods: Total RNA was isolated with TRIzol from Med23 knockdown HUVECs (n = 3) or control cells (n = 3). cDNA sequencing libraries were prepared with an NEBNext® Ultra™ RNA Library Prep Kit for Illumina. The RNA-Seq FASTQ raw data were trimmed to remove low-quality reads and adapters using Trimmomatic. The trimmed reads were aligned to the mouse reference genome UCSC GRCh37/hg19 with HISAT2. Gene and transcript quantification was performed using Cutdiff. The results of the mapping of the RNA-seq reads, transcript assembly and abundance estimation were reported as fragments per kilobase of exon per million fragments mapped (FPKM).
2021-10-21 | GSE186112 | GEO
Project description:LSEC fom WT and Bmp9-KO 25-weeks female mice were isolated using collagenase and treated for bulk RNAsequencing. The objective was to determine the biological processes that are altered in Bmp9-KO compared to WT, as BMP9 is know to be a vascular quiescence factor produced by hepatic stellate cells. RNAseq reads were trimmed to remove possible adapter sequences and nucleotides with poor quality using Trimmomatic v.0.36 16. The trimmed reads were mapped to the Mus Musculus MM10 reference genome available on ENSEMBL using the STAR aligner v.2.5.2b 17. Unique gene hit counts were calculated by using ‘featureCounts’ from the Subread package v.1.5.2 WT samples are F126, F121, F120, F119, F135 KO samples are F131, F132, F124 and F133
2024-04-30 | E-MTAB-14012 | biostudies-arrayexpress
Project description:Small RNAs (<100 bases in length) were purified from total RNA samples using the miRNeasy kit (Qiagen), and multiplexed miRNA libraries were prepared using a previously described protocol and sequenced on a HiSeq 2000 (Illumina). Image analysis, base calling, demultiplexing and conversion of BCL to FASTQ format were carried out using CASAVA 1.8.2 software (Illumina). Adaptor sequences were removed using mirExpress software. Fastq were 3p-adaptor trimmed. The sequences were then aligned on hg19 (GRCh37) human reference genome with STAR (v.2.5.2a), allowing no mismatch with reference. Reads were counted using HTSeq-count (HTSeq v 0.6.1p1 Python package) using “intersection-strict” mode, to count mature miRNA abundance according to miRbase v.20.
2020-08-12 | E-MTAB-6553 | biostudies-arrayexpress
Project description:Purpose: Development of resistance to tamoxifen is an important clinical issue in the treatment of patients with breast cancer. Tamoxifen resistance may be the result of the acquisition of epigenetic regulation such as DNA methylation within breast cancer cells resulting in changed mRNA expression of genes being pivotal for estrogen dependent growth. Alternatively, tamoxifen resistance may be due to selection of preexisting resistant cells, which may exhibit cancer stem-like characteristics or a combination of the two mechanisms. Methods: To evaluate the contribution of these possible mechanisms to tamoxifen resistance, we applied modified DNA methylation-specific digital karyotyping (MMSDK) and digital gene expression (DGE) in combination with massively parallel sequencing to analyze a well-established tamoxifen resistant cell line model: MCF-7/S0.5 (tamoxifen sensitive parental cell line) and 4 high-dosage tamoxifen selected resistant offspring sublines (MCF-7/TAMR-1, MCF-7/TAMR-4, MCF-7/TAMR-7 and MCF-7/TAMR-8). MMSDK uses BssHII as mapping enzyme (DNA methylation sensitive enzyme). Both MMSDK and DGE use NlaIII and MmeI to produce 20-21 bp tag. The indexed single-end sequencing was performed by Illumina HiSeq 2000 in BGI-Shenzhen. A dynamic programming algorithm-FASTX-Toolkit implemented in Perl was used to trim the adaptor sequence. The trimmed tags were subjected to quality filtering, so that only tags with sequencing quality higher than 30 for more than 80% of the nucleotides were used for subsequent analysis. For MMSDK tag mapping, we generated a simulated reference library, i.e., BssHII reference library, by in silico enzyme digestion of the human genome (hg19, UCSC) regardless of the methylation state. This library was used as reference for subsequent mapping of the tags in the MMSDK analysis. In the DGE analysis, refMrna (hg19, UCSC) was used as reference for mapping cDNA tags. Subsequently, the Burrows–Wheeler Aligner (BWA) procedure for aligning the MMSDK and DGE tags to the simulated BssHII reference library and refMrna reference library, respectively, was applied. Results: MMSDK libraries using BssHII/NlaIII were generated from the parental tamoxifen sensitive subline MCF-7/S0.5 and the 4 TAMR cell lines: TAMR-1, TAMR-4, TAMR-7 and TAMR-8. The 5 indexed MMSDK libraries were sequenced in one lane and 1.38 Gb clean tag data for all 5 cell lines were obtained, with an average sequencing amount of ~270 Mb per library. On average, 59.5 % of the tags with mapping quality ≥ 20 were mapped back to the simulated BssHII/NlaIII reference library. DGE libraries were also generated from MCF-7/S0.5 and the 4 TAMR cell lines. The 5 indexed DGE libraries were sequenced in one lane and obtained 1.71 Gb clean tag data for all 5 cell lines with an average sequencing amount of ~340 Mb per library. On average, 40.8 % with mapping quality ≥ 20 were mapped back to the simulated NlaIII human transcriptome (refMrna reference library). Our present study demonstrates large differences in global gene expression and DNA methylation profiles between parental tamoxifen-sensitive cell line and 4 high-dosage tamoxifen treatment selected resistant sublines. The tamoxifen resistant cell lines exhibited globally higher methylation level than the parental cell line and an inverse relationship between gene expression and DNA methylation in the promoter regions were noticed. High expression of SOX2 and alterations of other SOX gene family members, E2F gene family members and RB-related pocket protein genes as well as highlighted stem cell pathways imply that cancer initiating cells/stem cells are involved in the resistance to tamoxifen.
2014-02-03 | GSE40665 | GEO
Project description:Deep high-throughput transcriptome sequencing (RNA-seq) performed on 3 pairs of matched tumor and adjacent non-tumorours (NT) tissues from HCC patients of Chinese origin generated 183.6-million reads that could be aligned. We discovered a number of differentially expressed genes and multiple types of somatic single nucleotide variations (SNVs) in expressed genes. After the removal of the error alignments, high-quality reads were mapped to the human reference sequence (GRCh37/hg19) using three different softwares TopHat, Burrows-Wheeler Aligner (BWA) and CLC Genomics Workbench (CLC). The high-quality variants were identified using VarScan with the following parameters: minimum coverage depth of 10, variation frequency of more than 30% and base quality of more than 15. A total of 568, 545 and 494 potential somatic single nucleotide variants (SNVs), including 94, 89 and 101 coding somatic SNVs (cSNVs), were identified in 3 tumor samples HCC448T, HCC473T and HCC510T, respectively. Validation analysis was carried out for 10 of the intersected cSNVs (all are non-synonymous substitutions) within selected genes of interests with the majority confirmed.
2013-04-02 | GSE33294 | GEO
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Jonathan Preall jpreall@cshl.edu (Generation 0 Data from Hannon Lab), Carrie Davis davisc@cshl.edu (experimental), Alex Dobin dobin@cshl.edu (computational), Wei Lin wlin@cshl.edu (computational), Tom Gingeras gingeras@cshl.edu (primary investigator)). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). hg18: This data was produced by Hannon lab part of Cold Spring Harbor as part of the ENCODE Project. The series depicts NextGen sequencing information for RNAs between the sizes of 20-200 nt isolated from RNA samples from tissues or sub cellular compartments of cell lines. hg19: This track depicts NextGen sequencing information for RNAs between the sizes of 20-200 nt isolated from RNA samples from tissues or sub cellular compartments from ENCODE cell lines. The overall goal of the ENCODE project is to identify and characterize all functional elements in the sequence of the human genome. hg19: This cloning protocol generates directional libraries that are read from the 5' ends of the inserts, which should largely correspond to the 5' ends of the mature RNAs. The libraries were sequenced on a Solexa platform for a total of 36, 50 or 76 cycles however the reads undergo post-processing resulting in trimming of their 3' ends. Consequently, the mapped read lengths are variable. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf hg18: Small RNAs between 20-200 nt were ribominus treated according to the manufacturer's protocol (Invitrogen) using custom LNA probes targeting ribosomal RNAs (some datasets are also depleted of U snRNAs and high abundant microRNAs). The RNA was treated with Tobacco Alkaline Pyrophosphatase to eliminate any 5' cap structure. Poly-A Polymerase was used to catalyze the addition of C's to the 3' end. The 5' ends were phosphorylated using T4 PNK and an RNA linker was ligated onto the 5' end. Reverse transcription was carried out using a poly-G oligo with a defined 5' extension. The inserts were then amplified using oligos targeting the 5' linker and poly-G extension and containing sequencing adapters. The library was sequenced on an Illumina GA machine for a total of 36, 50 or 76 cycles. Initially 1 lane is run. If an appreciable number of mappable reads are obtained, additional lanes are run. Sequence reads underwent quality filtration using Illumina standard pipeline (Gerlad). The read lengths may exceed the insert sizes and consequently introduce 3' adaptor sequence into the 3' end of the reads. The 3' sequencing adaptor was removed from the reads using a custom clipper program, which aligned the adaptor sequence to the short-reads, allowing up to 2 mismatches and no indels. Regions that aligned were "clipped" off from the read. The trimmed portions were collapsed into identical reads, their count noted and aligned to the human genome (NCBI build 36, hg18 unmasked) using Nexalign (Lassmann et al., not published). The alignment parameters are tuned to tolerate up to 2 mismatches with no indels and will allow for trimmed portions as small as 5 nucleotides to be mapped. We report reads that mapped 10 or fewer times. Data obtained from each lane is processed and mapped independently. The processed/mapped data from each lane is then complied as a single track without additional processing and submitted to UCSC. Consequently, identical reads within a lane were collapsed and their value is reported as the "transfrag" signal value. However, the redundancy between lanes has not been eliminated so the same transfrag may appear multiple times within a signal. hg19: Small RNAs between 20-200 nt were ribominus treated according to the manufacturer's protocol (Invitrogen) using custom LNA probes targeting ribosomal RNAs (some datasets are also depleted of U snRNAs and high abundant microRNAs). The RNA was treated with Tobacco Alkaline Pyrophosphatase to eliminate any 5' cap structures. Poly-A Polymerase was used to catalyze the addition of C's to the 3' end. The 5' ends were phosphorylated using T4 PNK and an RNA linker was ligated onto the 5' end. Reverse transcription was carried out using a poly-G oligo with a defined 5' extension. The inserts were then amplified using oligos targeting the 5' linker and poly-G extension and containing sequencing adapters. The library was sequenced on an Illumina GA machine for a total of 36, 50 or 76 cycles. Initially, one lane was run. If an appreciable number of mappable reads were obtained, additional lanes were run. Sequence reads underwent quality filtration using Illumina standard pipeline (GERALD). The Illumina reads were initially trimmed to discard any bases following a quality score less than or equal to 20 and converted into FASTA format, thereby discarding quality information for the rest of the pipeline. As a result, the sequence quality scores in the BAM output are all displayed as "40" to indicate no quality information. The read lengths may exceed the insert sizes and consequently introduce 3' adapter sequence into the 3' end of the reads. The 3' sequencing adapter was removed from the reads using a custom clipper program (available at http://hannonlab.cshl.edu/fastx_toolkit/), which aligned the adapter sequence to the short-reads using up to 2 mismatches and no indels. Regions that aligned were "clipped" off from the read. Terminal C nucleotides introduced at the 3' end of the RNA via the cloning procedure are also trimmed. The trimmed portions were collapsed into identical reads, their count noted and aligned to the human genome (version hg19, using the gender build appropriate to the sample in question - female/male) using Bowtie (Langmead B. et al). The alignment parameter allowed 0, 1, or 2 mismatches iteratively. We report reads that mapped 20 or fewer times. Discrepancies between hg18 and hg19 versions of CSHL small RNA data: The alignment pipeline for the CSHL small RNA data was updated upon the release of the human genome version hg19, resulting in a few noteworthy discrepancies with the hg18 dataset. First, mapping was conducted with the open-source Bowtie algorithm (http://bowtie-bio.sourceforge.net/index.shtml) rather than the custom NexAlign software. As each algorithm uses different strategies to perform alignments, the mapping results may vary even in genomic regions that do not differ between builds. The read processing pipeline also varies slightly, in that we no longer retain information regarding whether a read was 'clipped' off adapter sequence.
2010-10-08 | E-GEOD-24565 | biostudies-arrayexpress