6cbced01-d74b-408b-84c1-99812ae60b3f - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001009683 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Paired scRNA sequencing using 10xgenomics library preparation and Illumina HiSeq4000 for sequencing of 2 samples RRMM (relapsed refractory multiple myeloma)
| EGAD00001009681 | EGA
Project description:Here is mostly paired WGS data of RRMM, 45 samples (tumors and controls) in 86 runs. This data was produced by using Illumina TruSeq Nano DNA and NovaSeq6000 or HiSeq X Ten for sequencing. One tumor/control pair is WES data using Agilent SureSelect V5+UTRs and NovaSeq6000 for sequencing.
| EGAD00001009682 | EGA
Project description:To examine the effect of the effects of PKCbeta and Wnt inhibitors on global gene expression of iPSCs in suspension conditions, RNA-seq experiments were performed. Total RNA was extracted with a FastGene RNA premium kit (Nippon Genetics, Co., Ltd, Tokyo, Japan) and strand-specific library preparation was performed. The prepared library was sequenced by a NovaSeq6000 (Illumina, Inc, CA, USA). Sequencing was performed in a 150 bp x2 paired-end configuration with a data output of about 6 Gb per sample (equivalent to about 20 million paired reads). Library preparation and its sequencing were performed in GENEWIZ (Azenta, MA, USA). The sequencing data were analyzed with a CLC Genomics Workbench (QIAGEN, Hulsterweg, the Neterlands) and the R package edgeR (v3.30.3) to identify differentially regulated genes.
2023-01-17 | GSE222833 | GEO
Project description:Virtually all patients with multiple myeloma become unresponsive to treatment over time. Relapsed/refractory multiple myeloma (RRMM) is accompanied by the clonal evolution of myeloma with heterogeneous genomic aberrations and profound changes of the bone marrow microenvironment (BME). However, the molecular mechanisms that drive drug resistance remain elusive. Here, we have analyzed the heterogeneous tumor cell population of 20 RRMM patients and its complex interaction network with the BME by single cell RNA-sequencing before/after treatment. Subclones with chromosome 1q-gain expressed a specific transcriptomic signature and frequently expanded during treatment. Furthermore, RRMM cells shaped an immune suppressive BME by upregulation of inflammatory cytokines and close interaction with the myeloid compartment. It was characterized by the accumulation of PD1+ γδ T-cells and tumor-associated macrophages as well as the depletion of hematopoietic progenitors. Thus, our study resolves transcriptional features of subclones in RRMM and mechanisms of microenvironmental reprogramming with implications for clinical decision-making.
2021-08-18 | GSE161801 | GEO
Project description:ChIP-seq was performed to assess changes in the activity of the MYC SE upon deletion of its modules or CTCF binding sites. Immunoprecipitation of crosslinked chromatin was performed with antibodies directed against H3K27Ac (Diagenode C15410196), H3K9Ac (Diagenode C15410004), H3K4me3 (Diagenode C15410003), RUNX1 (Abcam ab23980) or CTCF (Cell Signalling, 2899S). Crosslinks were reversed overnight at 65°C in the presence of proteinase K (New England Biolabs). De-crosslinked material was purified using a QIAGEN PCR Purification Kit. The purified DNA was processed according to the Nextflex ChIP Sample Preparation Protocol (Perkin Elmer) or the Microplex library preparation kit V2 (Diagnode C05010013) and sequenced on the Illumina NovaSeq6000 platform.
2021-07-26 | E-MTAB-9965 | biostudies-arrayexpress
Project description:Pneumonia remains the leading cause of death in children under five, but existing diagnostic methods frequently lead to innecessary or mistaken treatment. M. pneumoniae lacks cellular wall so it does not respond to common firs-line antibiotic. Our study aims to guide the diagnosis and treatment by identifying host transcriptomic biomarkers in the blood of children with Mycoplasma pneumoiae pneumonia. Using RNA sequencing, we identified and validated 8 different n-transcript signature that accurately differentiates M. pneumoniae pneumonia from the rest of pneumonias. A strand specific library preparation was completed using NEBNext® Ultra™ II mRNA kit (NEB) and NEB rRNA/globin depletion probes following manufacturer’s recommendations. Individual libraries were normalized using Qubit, pooled together and diluted. The sequencing was performed using a 150 or 75 paired-end configuration in a Novaseq6000 or HiSeq 4000 platforms. Quality control of raw data was carried out using FastQC, alignment and read counting were performed using STAR, alignment filtering was done with SAMtools and read counting was carried out using FeatureCounts. RNAseq data was processed for batch correction using control samples and COMBAT-Seq package.
2024-12-08 | E-MTAB-14588 | biostudies-arrayexpress
Project description:RNA sequencing was performed to quantify differential gene expression between pig placentae exposed to thermoneutral control or cyclic heat stress conditions between d40 and d60 of gestation (early-mid gestation). Placental samples from female fetuses were collected at d60 of gestation and were subjected to sequencing library preparation and NovaSeq6000 sequencing. 150 bp paired-end reads were generated from each sample. A total of 169 genes were differentially expressed between control and heat stress placentae, of which 35 genes were upregulated and 134 genes were downregulated by maternal heat stress. Gene ontology and pathway enrichment analysis revealed the differentially expressed genes are associated with placental nutrient transporter and metabolism.
2021-04-15 | GSE168571 | GEO
Project description:Multiple myeloma (MM) is a common hematological malignancy with poorly understood recurrence and relapse mechanisms. Notably, bortezomib resistance leading to relapse makes MM treatment significantly challenging. To clarify the drug resistance mechanism, we employed a quantitative proteomics approach to identify differentially expressed protein candidates implicated in bortezomib-resistant recurrent and relapsed MM (RRMM). Bone marrow biopsy specimens from five patients newly diagnosed with MM (NDMM) were compared with those from five patients diagnosed with bortezomib-resistant RRMM using tandem mass tag-mass spectrometry (TMT-MS). Subcellular localization and functional classification of the differentially expressed proteins were determined by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and hierarchical clustering. Top candidates identified were validated with parallel reaction monitoring (PRM) analysis using tissue samples from 11 NDMM and 8 RRMM patients, followed by comparison with the NCBI Gene Expression Omnibus (GEO) dataset of 10 MM patients and 10 healthy controls (Accession No.: GSE80608). Thirty-four differentially expressed proteins in RRMM, including proteinase inhibitor 9 (SERPINB9) were identified by TMT-MS. Subsequent functional enrichment analyses of the identified protein candidates indicated their involvement in regulating cellular metabolism, apoptosis, programmed cell death, lymphocyte-mediated immunity, and defense response pathways in RRMM. The top protein candidate SERPINB9 was confirmed by PRM analysis as well as by comparison with an NCBI GEO dataset. We elucidated the proteome landscape of bortezomib-resistant RRMM and identified SERPINB9 as a promising novel therapeutic target. Our results provide a resource for future studies on the mechanism of RRMM.
2021-03-03 | PXD022182 | Pride
Project description:Pneumonia remains the leading cause of death in children under five, but existing diagnostic methods frequently lead to either insufficient or excessive treatments. Our study aims to bridge this gap by identifying host transcriptomic biomarkers in the blood of children with confirmed viral or bacterial pneumonia. Using RNA sequencing, we identified and validated in an independent cohort a 5-transcript signature that accurately differentiates bacterial from viral pneumonia. This signature has considerable potential to improve diagnostic accuracy for pediatric pneumonia, minimizing delays in diagnosis and avoiding unnecessary treatments, with the possibility of significantly impacting clinical practice. a strand specific library preparation was completed using NEBNext® Ultra™ II mRNA kit (NEB) and NEB rRNA/globin depletion probes following manufacturer’s recommendations. Individual libraries were normalized using Qubit, pooled together and diluted. The sequencing was performed using a 150 paired-end configuration in a Novaseq6000 platform. Quality control of raw data was carried out using FastQC, alignment and read counting were performed using STAR, alignment filtering was done with SAMtools and read counting was carried out using FeatureCounts. RNAseq data was processed for batch correction using control samples and COMBAT-Seq package.
2024-12-08 | E-MTAB-14564 | biostudies-arrayexpress