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accession-icon GSE29798
A combined RNAi and localization approach for dissecting long noncoding RNAs reveals a function of Panct1 in ES cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon

Description

Long non-coding RNAs (lncRNAs) regulate diverse biological pathways. Unlike protein coding genes, where methods to comprehensibly study their functional roles in cellular systems are available, techniques to systematically investigate lncRNAs have largely remained unexplored. Here, we report a technology for combined Knockdown and Localization Analysis of Non-coding RNAs (c-KLAN) that merges phenotypic characterization and localization approaches to study lncRNAs. Using a library of endoribonuclease prepared short interfering RNAs (esiRNAs) coupled with a pipeline for synthesizing labeled riboprobes for RNA fluorescence in situ hybridization (FISH), we demonstrate the utility of c-KLAN by identifying a novel transcript Panct1 (Pluripotency associated non-coding transcript 1) that regulates embryonic stem cell identity. We postulate that c-KLAN should be generally useful in the discovery of lncRNAs implicated in various biological processes.

Publication Title

Combined RNAi and localization for functionally dissecting long noncoding RNAs.

Sample Metadata Fields

Specimen part

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accession-icon GSE27888
Comparative transcriptome analysis of APPs-DM and APLP2-KO brains
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon

Description

Despite its key role in Alzheimer pathogenesis, the physiological function(s) of the amyloid precursor protein (APP) and of its proteolytic fragments are still poorly understood. The secreted APPs ectodomain has been shown to be involved in neuroprotection and synaptic plasticity. The -secretase generated APP intracellular domain, AICD, functions as a transcriptional regulator in heterologous reporter assays although its role for endogenous gene regulation has remained controversial. Previously, we have generated APPs knockin (KI) mice expressing solely the secreted ectodomain APPs. Here, we generated double mutants (APPs-DM) by crossing APPs-KI mice onto an APLP2-deficient background and show that APPs rescues the postnatal lethality of the majority of APP/APLP2 double knockout mice. Despite normal CNS morphology and unaltered basal synaptic transmission, young APPs-DM mice already showed pronounced hippocampal dysfunction, impaired spatial learning and a deficit in LTP. To gain further mechanistic insight into which domains/proteolytic fragments are crucial for hippocampal APP/APLP2 mediated functions, we performed a DNA microarray transcriptome profiling of prefrontal cortex and hippocampus of adult APLP2-KO (APLP2-/-) and APPs-DM mice (APP/APLP2-/- mice).Interestingly, this analysis failed to reveal major genotype-related transcriptional differences. Expression differences between cortex and hippocampus were, however, readily detectable.

Publication Title

APP and APLP2 are essential at PNS and CNS synapses for transmission, spatial learning and LTP.

Sample Metadata Fields

Sex, Specimen part

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accession-icon SRP198358
Profiling of the host small non-coding RNAome in Mycobacterium tuberculosis infection
  • organism-icon Homo sapiens
  • sample-icon 48 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We report a study about differentially expressed small non-coding RNAs in the blood of humans harboring a latent (LTBI) or active tuberculosis (TB) infection in comparison with exposed controls (ExC) and treated LTBI (LTBItt). All non-TB subjects enrolled in this study were recent close contacts (rCt) of a newly diagnosed contagious TB cases enrolled in Rio de Janeiro, Brazil. The detailed methodology is described below. According to Brazilian Ministry of Health (BMH) guidelines, the screen to detect LTBI among recent contacts comprises a clinical evaluation by a physician specializing in pulmonary diseases, a chest X-ray (CXR), and a tuberculin skin test (TST, cut-off 5mm). Additionally, as part of this study, blood was collected for short- (st) and long-term (lt) IGRA. St-IGRA was performed by stimulating whole blood with the Mtb antigen ESAT6:CFP10 (expressed as a fusion protein) for 22h (cut-off 10pg/mL). Lt-IGRA involved stimulating peripheral blood mononuclear cells (PBMC) with this same antigen for 5 days (cut-off 100 pg/mL). Cases were defined as follows: ExC were recent close contacts of a TB index case and had a negative response to both TST and in house interferon-gamma release assay (IGRA) by stimulating blood-derived specimens with ESAT6:CFP10 indicating absence of Mycobacterium tuberculosis (Mtb) infection. LTBI was defined as (1) a TST induration >5 mm measured 72 h after intradermal injection of Mtb purified protein derivative (PPD) and (2) a positive IGRA response (to either st-IGRA or lt-IGRA, or both) if indicators of active disease were observed on CXR, (3) the absence of acid-fast bacilli (AFB) and negative Lowenstein-Jensen (LJ) culture of clinical specimens were also required. LTBItt consisted of LTBI cases (TST+/IGRA+ at enrollment) who completed a 6-month course of IPT. Their blood samples were collected >2 months after the end of isoniazid (INH) preventive treatment (IPT). Active TB was defined as (1) respiratory symptoms suggestive of TB, and/or (2) detection of AFB and/or positive LJ culture in sputum, bronchoalveolar lavage or biopsy, followed by (3) remission of symptoms upon anti-TB chemotherapy. Their blood samples were obtained before initiation of treatment. Whole blood was collected in PAXgene RNA tubes (PreAnalytiX, SWZ) and was stored at -80°C for <2 years before RNA extraction. sncRNA libraries. Total RNA (including small RNA) was isolated using the PAXgene Blood miRNA Kit (PreAnalytiX, SWZ), which is indicated for the isolation and purification of total RNA longer than 18 nucleotides. The manufacturer’s instructions were followed at both stages. Total RNA was quantified with a Nanodrop ND-1000 spectrophotometer (Thermo Scientific, EUA) and RNA integrity was assessed via agarose gel electrophoresis. One microgram RNA was used for cDNA library preparation (TruSeq Small RNA Sample Preparation® Kit, Illumina, San Diego, CA) following the manufacturer’s protocols. RNAseq was performed on an Illumina HiSeq® 2500 Sequencing System (Illumina, San Diego, CA), generating 50 bp single reads and ≈16 million reads passing filter for each sample. Pre-processing and differential expression. The FASTQ files were preprocessed (FastQC 0.11.2), adaptors trimmed (Cutadapt 1.7.1), aligned to the human genome (STAR 2.4.1d), counted (featureCounts 1.4.6) on the Oasis 2.0 web platform. Transcripts with <5 reads in at least one sample were excluded. Then, normalized and evaluated for differentially expressed (DE) transcripts using DESeq2 (v. 1.16) on the Oasis 2.0 web platform (https://oasis.dzne.de/). Overall design: We collected blood samples from recent close contacts at recruitment and monitored them for 1 year. All TB cases were treatment-naïve. An active TB sncRNA signature was derived from whole blood RNA sequencing data by comparing TB and non-TB groups. Notably, it classified all TB cases correctly and reclassified 8 presumed LTBI cases as TB, 5 of whom turned out to have features of Mycobacterium tuberculosis infection on chest radiographs.

Publication Title

Reprogramming of Small Noncoding RNA Populations in Peripheral Blood Reveals Host Biomarkers for Latent and Active Mycobacterium tuberculosis Infection.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE37382
Subgroup specific somatic copy number aberrations in the medulloblastoma genome [mRNA]
  • organism-icon Homo sapiens
  • sample-icon 285 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

Affymetrix Human Gene 1.1 ST Array profiling of 285 primary medulloblastoma samples.

Publication Title

Subgroup-specific structural variation across 1,000 medulloblastoma genomes.

Sample Metadata Fields

Sex, Age

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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