3659 results for "RNA AND sequencing OR transcriptome"

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• Orthotopic murine Group 3 medulloblastoma in C57Bl/6 mice treated with sham or craniospinal irradiation

  Mice with medulloblastoma (Group 3) were treated with sham (isofluorane and imaging xray) or CSI as described by Abbas et al (2022). Total RNA was isolated with RNeasy Plus Mini Kit (Qiagen), library preparation (SureSelect, Agilent), rRNA depletion (Ribo-Zero Plus, Illumina) and sequencing were carried out by GenomicsWA or Australian Genome Research Facility. Libraries were sequenced on NovaSeq 6000 S1 flow cells as paired-end 150bp reads (Illumina).

  Dataset EGAD00001008510

• ProstOmics - Bulk Transcriptomics

  Bulk transcriptomics data from 176 prostate tissue samples (37 patients, 27 with post-surgery relapse) that were acquired using the SENSE mRNA-Seq Library Prep Kit V2 and Illumina NextSeq 500 instrument. The raw transcriptomics data is single-read RNA-seq. The individual samples have information on patient origin and sample type (cancer, cancer-adjacent field-effect normal or normal sample far from cancer). Patient metadata include information of age at surgery, time (months) until reported relapse, pre-surgery PSA and post-surgery T-stage.

  Dataset EGAD50000000604

• RNA-seq analysis of CCO+/CCO- hepatocytes in normal human liver

  RNAseq data from Passman et al 2023. Clonal CCO-deficient hepatocyte patches and nearby CCO-proficient hepatocytes were identified in morphologically normal human livers and sampled at varying distances along the PT-CV axis. Samples are characterised according to their location within the liver lobule, with "PT" denoting samples abutting the portal triad, "CV" denoting samples abutting the central hepatic vein, and "Mid" sampled acquired midway between these structures. Analysis was performed on an Illumina Nextseq using a high output kit and 100 single-end cycles.

  Dataset EGAD00001010033

• Cambridge COVID-19 Single-cell PBMC

  Single-cell multi-omic profiling of healthy controls, asymptomatic and hosptial-admitted COVID19 patients recruited from Addenbrookes and Royal Papworth hospitals, in collaboration with the NIHR Cambridge Bioresource. Data represent RNA-seq, surface protein measurements (CITE-seq) of 192 antibody targets, along with VDJ-seq profiling of single T cell and B cell receptors. Samples are pooled, with 4 donors per pool. Germ-line genotypes are provided (VCF) to aid demultiplexing of single-cell and assignment to specific patient donor samples.

  Dataset EGAD00001007867

• Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids

  Non-invasive acquisition of mRNA data from the skin can be extremely useful for understanding skin physiology and diseases. Inspired by the holocrine process, in which the sebaceous glands secrete cell contents into the sebum, we focused on the possible presence of mRNAs in skin surface lipids (SSLs). We found that measurable levels of human mRNAs exist in SSLs, where the sebum protects them from degradation by RNases. The AmpliSeq transcriptome analysis was modified to measure SSL-RNA levels, and our results revealed that the SSL-RNAs predominantly comprised mRNAs derived from sebaceous glands, the epidermis, and hair follicles. Analysis of SSL-RNAs non-invasively collected from patients with atopic dermatitis revealed significantly increased expression of inflammation-related genes and decreased expression of terminal-differentiation���related genes, consistent with the results of previous reports. Further, we found that lipid-synthesis���related genes were downregulated in the sebaceous glands of patients with atopic dermatitis. These results indicate that the analysis of SSL-RNAs is a promising strategy to understand the pathophysiology of skin diseases.

  Study JGAS000416

• Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids

  Non-invasive acquisition of mRNA data from the skin can be extremely useful for understanding skin physiology and diseases. Inspired by the holocrine process, in which the sebaceous glands secrete cell contents into the sebum, we focused on the possible presence of mRNAs in skin surface lipids (SSLs). We found that measurable levels of human mRNAs exist in SSLs, where the sebum protects them from degradation by RNases. The AmpliSeq transcriptome analysis was modified to measure SSL-RNA levels, and our results revealed that the SSL-RNAs predominantly comprised mRNAs derived from sebaceous glands, the epidermis, and hair follicles. Analysis of SSL-RNAs non-invasively collected from patients with atopic dermatitis revealed significantly increased expression of inflammation-related genes and decreased expression of terminal-differentiation���related genes, consistent with the results of previous reports. Further, we found that lipid-synthesis���related genes were downregulated in the sebaceous glands of patients with atopic dermatitis. These results indicate that the analysis of SSL-RNAs is a promising strategy to understand the pathophysiology of skin diseases.

  Study JGAS000418

• Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids

  Non-invasive acquisition of mRNA data from the skin can be extremely useful for understanding skin physiology and diseases. Inspired by the holocrine process, in which the sebaceous glands secrete cell contents into the sebum, we focused on the possible presence of mRNAs in skin surface lipids (SSLs). We found that measurable levels of human mRNAs exist in SSLs, where the sebum protects them from degradation by RNases. The AmpliSeq transcriptome analysis was modified to measure SSL-RNA levels, and our results revealed that the SSL-RNAs predominantly comprised mRNAs derived from sebaceous glands, the epidermis, and hair follicles. Analysis of SSL-RNAs non-invasively collected from patients with atopic dermatitis revealed significantly increased expression of inflammation-related genes and decreased expression of terminal-differentiation���related genes, consistent with the results of previous reports. Further, we found that lipid-synthesis���related genes were downregulated in the sebaceous glands of patients with atopic dermatitis. These results indicate that the analysis of SSL-RNAs is a promising strategy to understand the pathophysiology of skin diseases.

  Study JGAS000417

• RaScALL: Rapid (Ra) screening (Sc) of RNA-seq data for prognostically significant genomic alterations in acute lymphoblastic leukaemia (ALL)

  RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, a full RNA-seq Bioinformatics workflow is time-consuming and costly in a clinical setting where rapid detection and accurate reporting of clinically relevant alterations are essential. To accelerate the identification of ALL-specific alterations (including gene fusions, single nucleotide variants and focal gene deletions), we developed the rapid screening tool RaScALL, capable of identifying more than 100 prognostically significant lesions directly from raw sequencing reads. RaScALL uses the k-mer based targeted detection tool km and known ALL variant information to achieve a high degree of accuracy for reporting subtype defining genomic alterations compared to standard alignment-based pipelines. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% (164 samples) of reported cases in a 180-patient Australian study cohort and 95% (n=63) of samples in a North American validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n=12) and IKZF1 p.N159Y (n=4). Accurate detection of intragenic IKZF1 deletions resulting in aberrant transcript isoforms was also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches, ensuring accelerated risk-stratification and therapeutic triage.

  Dataset EGAD00001009087

• Single-cell RNA sequencing of 16 NPM1 mutated AML patients

  NPM1 mutated AML is the largest class in WHO classification, however several subtypes within NPM1 were already reported. Here, we sequence 16 NPM1 mutated AML samples with single-cell RNA-sequencing and multi-color flow cytometry from three major NPM1 subtypes we previously identified, totaling more than half a million cells. We show that the differences among three NPM1 subtypes are mainly driven by cell composition, and these differences are also reflected at cell surface protein level. With the re-analysis of CITE-seq data from another cohort and single cell variant calling on our data, we also report two distinct stem cell phenotypes: one with leukemic (CD34dimCD38-CD45RA+) and another with pre-leukemic (CD34+CD38-CD45RA-) origin. We believe that our data and findings provide novel insights regarding the etiology of NPM1 mutated AML.

  Study EGAS50000000332

• Cell line data (RNAseq, ATACseq, ChIPseq)

  Content: 2 GB RTK I cell lines (LN229, ZH487) in two conditions (NT control and shSOX10). RNAseq: single replicates per condition, polyA+ RNA sequencing, SE. ATACseq: biological replicates per condition, SE. ChIPseq (histone H3 modifications, LN229 only): all marks for each condition were pooled and sequenced on two lanes for each pool. ChIPseq (BRD4 and SOX10): SOX10 libraries were sequenced on single lanes. BRD4 samples were multiplexed and sequenced in two lanes. ChIPseq input samples are also included. Data type and technology: RNAseq: SE 50bp sequenced on HiSeq2000/4000. ATACseq: SE 50bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000.

  Dataset EGAD00001005493