Microarray expression profiling in the denervated hippocampus identifies long noncoding RNAs functionally involved in neurogenesis
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ABSTRACT:
ORGANISM(S): Rattus norvegicus
PROVIDER: GSE96992 | GEO | 2017/03/28
SECONDARY ACCESSION(S): PRJNA380550
REPOSITORIES: GEO
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Project description:Purpose: Pulmonary tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), has long been associated with the development of lung adenocarcinoma (LUAD) and sarcoidosis. These chronic lung diseases share histopathological similarities that challenge differential diagnosis. Methods: Human lung tissues were used for total RNA extraction with RNeasy Plus Mini Kit (Qiagen) according to the manufacturer’s protocol. RNA purity was assessed using a Nanodrop ND-2000 (Thermo Scientific), and each RNA sample had an A260:A280 ratio above 1.8 and an A260:A230 ratio above 2.0. RNA integrity was evaluated using the Agilent 2200 TapeStation (Agilent Technologies), and each sample had the RNA Integrity Number (RIN) above 7.0. The ribosomal RNAs (rRNAs) were removed using Ribo-Zero rRNA Removal Kits (Illumina). RNA libraries were then constructed by NEBNext Ultra RNA Library Prep Kit for Illumina (New England Biolabs) and evaluated using the Agilent 2200 TapeStation and Qubit® 2.0 (Life Technologies). Sequencing was performed by RiboBio Co., Ltd. on an Illumina HiSeq 3000 machine with paired-end 150-bp reads. The adaptors and low quality bases assessed using FASTQC 0.11.3 were trimmed by Trimmomatic 0.39 using the following options: TRAILING:20, MINLEN:235 and CROP:235. Trimmed reads were then aligned to the ensembl 79 (GRCh38.p2) reference genome using STAR 2.4.2a. FeatureCounts 1.6.2 was subsequently employed to convert aligned short reads into read counts for each sample. Genes with less than ten counts in two or more samples were removed. The data were then analyzed using R 3.4.4 and DEseq2 1.18.1. Differentially expressed genes of each disease group were identified using Wald statistics test, with fold-change > 2 and Benjamini–Hochberg (BH)-adjusted P < 0.1 as compared to NC group. Results: These findings provide novel pathogenic links and molecular markers for better understanding and differential diagnosis of pulmonary TB, LUAD and sarcoidosis.
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Project description:A large number of oral squamous cell carcinomas (OSCCs) are believed to be preceded by oral potentially malignant disorders (OPMD) that have an increased likelihood of malignant transformation compared to clinically normal mucosa. This study was performed to identify differentially expressed genes between OPMDs that underwent malignant transformation (MT) and those that did not, termed ‘non-transforming’ (NT) cases. Total RNA was extracted from formalin-fixed paraffin-embedded tissue biopsies of 20 OPMD cases with known clinical outcomes (10 MT vs. 10 NT). Samples were assessed for quantity, quality and integrity of RNA prior to sequencing. Analysis for differential gene expression between MT and NT was performed using statistical packages in R. Genes were considered to be significantly differentially expressed if the False Discovery Rate corrected p-value was < 0.05. RNA yield was variable but RNA purity was good (A260/A280 >1.90). Analysis of RNA-Sequencing outputs revealed 41 genes (34 protein-coding; 7 non-coding) that were significantly differentially expressed between MT and NT cases. The log2 fold change for the statistically significant differentially expressed genes ranged from -2.63 to 2.48, with 23 protein-coding genes being downregulated and 11 protein-coding genes being upregulated in MT cases compared to NT cases. Several candidate genes that may play a role in malignant transformation of OPMD have been identified. Experiments to validate these candidates are underway. It is anticipated that this work will contribute to better understanding of the aetiopathogenesis of OPMD and development of novel biomarkers.
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Project description:Juvenile pilocytic astrocytoma (JPA) is one of the most common brain tumors in children. The expression profiles of 21 JPAs, determined using Affymetrix GeneChip U133A, were compared with subjects with normal cerebella. The genes involved in neurogenesis, cell adhesion, synaptic transmission, central nervous system development, potassium ion transport, protein dephosphorylation, and cell differentiation were found to be significantly deregulated in JPA. These 21 JPAs were further clustered into two major groups by unsupervised hierarchical clustering using a set of 848 genes with high covariance (0.5-10). Supervised analysis with Significance Analysis of Microarrays software between these two potential subgroups identified a list of significant differentially expressed genes involved in cell adhesion, regulation of cell growth, cell motility, nerve ensheathment, and angiogenesis. Immunostaining of myelin basic protein on paraffin sections derived from 18 incompletely resected JPAs suggests that JPA without myelin basic proteinâpositively stained tumor cells may have a higher tendency to progress. Experiment Overall Design: Under an Institutional Review Boardâapproved protocol, brain tumor tissues were obtained, after informed consent, from patients undergoing tumor resection or other tumor-related neurosurgical procedures at the Texas Children's Hospital, Baylor College of Medicine. Samples of normal cerebellar tissue (n = 2) were isolated from surgically removed tissue adjacent to resected tumor tissue. Portions of the tumors were fixed in 10% formaldehyde and embedded in paraffin for sectioning and pathologic reviews, and the residual tissue samples were snap-frozen in liquid nitrogen and stored at â80°C for RNA extraction. All samples were obtained at initial diagnosis with no prior exposure to chemotherapy or radiation therapy. Normal fetal brain RNA was obtained from Stratagene (La Jolla, CA) and a normal cerebellum RNA was from Ambion, Inc. (Austin, TX). Total RNA was isolated using Trizol reagent (Invitrogen, Carlsbad, CA) followed by DNase I treatment and clean-up on aRNeasy spin column (Qiagen, Valencia, CA). RNA quality and purity were assessed by agarose gel electrophoresis and absorbance measurement at A260/A280.
2008-10-26 | E-GEOD-12907 | biostudies-arrayexpress
Project description:Purpose: Epigenetic regulation contributes to pathogenesis of neurondegenerative disease. We found that dis-regulation of a 242-gene subnetwork related to DNA methylation regulated neuronal differentiation are common in AD and HD. There are two DNA methyltransferases, DNMT1 and DNMT3A, in the subnetwork. DNMT1 is one of top hub genes in the network and likely to play a key regulatory role in the subnetwork. To validate that DNMT1 is a key regulator for the subnetwork, and DNMT3A not as one, we constructed two brain-specific conditional knockout mice. Methods: Cortices were dissected from Dnmt1 conditional knockout (CKO), Dnmt3a CKO, and respective littermate control mice at 18 weeks. RNA was isolated from three biological replicates for each genotype using TRIzol (Invitrogen) extraction and isopropanol precipitation. RNA samples were resuspended in water and further purified with RNeasy columns with on-column DNase treatment (Qiagen). RNA purity was assessed by measuring the A260/A280 ratio using a NanoDrop and RNA quality checked using an Agilent 2100 Bioanalyzer (Agilent Technologies). Approximately 250 ng of total RNA per sample were used for library construction by the TruSeq RNA Sample Prep Kit (Illumina) and sequenced using the Illumina HiSeq 2500 instrument according to the manufacturer's instructions. Sequence reads were aligned to mouse genome assembly mm10 and quantified using Cufflinks. Results: Genes differentially expressed in CKO mice compared to littermate control mice, or the Dnmt1 CKO signature, including GSN (the genes with the largest number of connection in the subnetwork) and SOX10 (a key transcription factor of myelination), significantly overlaps with the subnetwork. Broadly, the Dnmt1 CKO signature is enriched for genes involved in GO biological processes immune response, lipid metabolism, endocytosis, glial cell differentiation, and nerve ensheatment, consistent with biological function of the subnetwork. Moreover, the Dnmt1 CKO mice show increased predilection to seizures, an incidence also increased in patients with AD (Amatniek et al, 2006) as well as juvenile form of HD (Cloud et al, 2012). In contrast, the Dnmt3a CKO signature does not overlap with the subnetwork (p=0.07) and is not enriched for any GO biological process. Conclusions: These results suggest the Dnmt1 regulates common genes related with AD and HD while Dnmt3a has little effect.
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