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RNA sequencing in human iPSCs derived from bipolar patients to identify important therapeutic molecular targets of Valproate(VPA)

ABSTRACT: Valproate(VPA) has been used in the treatment of bipolar disorder since the 1990s. However, the therapeutic targetsof VPA have remained elusive. Here we used RNA sequencing in human iPSCs derived from bipolar patients to further identify important molecular targets. Human iPSCs were homogenized and total RNA was isolated using the RNeasy Plus Micro Kit (Qiagen, Hilden, Germany). RNA quantity and quality were assessed using fluorometry (Qubit RNA Broad Range Assay Kit and Fluorometer; Invitrogen, Carlsbad, CA) and chromatography (Bioanalyzer and RNA 6000 Nano Kit; Agilent, Santa Clara, CA), respectively. Libraries were prepared using TruSeq Stranded mRNA (PolyA+) kit (Illumina, San Diego, CA) and sequenced by Illumina NextSeq 500. The read length was 75bp with 30-40M reads per sample. FastQC (v0.11.3) was performed to assess data quality. TopHat2 (v2.0.9) aligned the reads to the mouse reference genome (Mus musculus UCSC mm10) and to the Ensembl human reference genome (GRCh38.p13) using default parameters. Alignments were then converted to expression count data using HTseq (v0.6.1) with default union mode.

ORGANISM(S): Homo sapiens

PROVIDER: GSE160761 | GEO | 2020/12/31

REPOSITORIES: GEO

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Project description:Background: Histone deacetylase (HDAC) is strongly associated with epigenetic regulation and carcinogenesis, and its inhibitors induce the differentiation or apoptosis of cancer cells. Valproic acid (VPA) is one of the clinically available HDAC inhibitors. We investigated the anticancer effects of VPA in combination with gemcitabine (GEM) in cholangiocarcinoma cell line, and explored the mechanisms of the anticancer effects using microarray analysis. Methods: A human cholangiocarcinoma cell line (HuCCT1) was used. The anticancer effects of VPA, or gemcitabine (GEM), and the effects of VPA combined with GEM, were studied by cell proliferation assay. The microarray analysis was performed, the genes were picked up using Gene Spring GX11.5, Ingenuity Pathways Analysis (IPA) was performed, and then the gene-expression was determined by RT-PCR. Results: GEM (5nM) and VPA (0.5mM) reduced by 23%, which significantly augmented the anticancer effect of GEM alone or VPA alone (P<0.01). Using the microarray analysis, forty-three genes were identified with the comparison between GEM group and GEM plus VPA combination group. The interactions were shown between genes of the “Cellular Development” relevant to the differentiation of cancer cell using IPA. Total RNA was isolated from both the stimulated and unstimulated cells (HuCCT-1) using RNeasy Mini kit (Qiagen, Valencia, CA). Relative purity was examined using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA expression was analyzed using GeneChip○R Human Gene 1.0 ST Array (Affymetrix, Santa Clara, CA, USA), containing 28,869 oligonucleotide probes for known and unknown genes. First standard cDNA was synthesized from 300 ng of total RNA by using GeneChip○R Whole Transcript (WT) cDNA Synthesis and Amplification Kit (Affymetrix) according to the manufacturer’s instructions. 10 μg of cRNA were input into the second-cycle cDNA reaction. cDNA was fragmented and end-labeled with the GeneChip○R WT Terminal Labeling Kit (Affymetrix). Approximately 5.5μg of fragmented and labeled DNA target was hybridized to the Affymetrix GeneChip○R Human Gene 1.0 ST Array at 45°C for 17h on a GeneChip○R Hybridization Oven 640 (Affymetrix) according to the manufacturer’s recommendation. Hybridized arrays were washed and stained on a GeneChip○R Fluidics Station 450 and scanned on a GeneChip○R Scanner 3000 7G (Affymetrix), and then generated CEL files for each array. The microarray data was normalized by GeneSpring GX 11.5 software (Agilent). The cut-off value was set at 0.5 to 2.0 for the ratio (more than 2.0: up-regulation, 0.5-2.0: no change, less than 0.5: down-regulation). Gene Ontology (GO) was analyzed using GeneSpring GX 11.5 software (Agilent), and p-value < 0.05 was used for significance. Then we used Ingenuity Pathway Analysis (IPA) 8.7 (http://www.ingenuity.com) to determine the functional pathways associated with the set of differentially expressed genes between genotypes. IPA utilizes the knowledge in the literature about biological interactions among genes and proteins.

Project description:Background: Nicotine and alcohol are often co-abused. Adolescence is a vulnerable period for the initiation of both nicotine and alcohol use, which can lead to subsequent neurodevelopmental and behavioral alterations. Aim: The aim was to to determine the effect of nicotine exposure during adolescence on ethanol intake, and the effect of both substances on brain gene expression. Methods: RNA was extracted from a randomly selected subset of mice (16 total; 4 samples from each experimental group). Whole brains (including cerebellum) were dissected. Total RNA was extracted with an RNeasy® Midi Kit (QIAGEN, Valencia, CA). RNA quality was assessed using an Agilent 2100 BioAnalyzer™. An Illumina TruSeq® Stranded mRNA Library Prep Kit (Illumina, San Diego, CA) was used for cDNA library preparation following the manufacturers’ protocol. Libraries were sequenced using an Illumina HiSeq 2500 (Illumina, San Diego, CA). Trimmomatic was used to remove sequencing adapters and low-quality ends. The cleaned dataset was analyzed with the Tuxedo pipeline. Subsequently, readings were mapped to the mouse reference genome (Ensembl GRCm38, mm10) using TopHat2 software (http://tophat.cbcb.umd.edu/). The ‘--library_type’ parameter was set to ‘fr-firststrand’. Default settings were preserved for all other TopHat2 parameters. The resulting alignments files from TopHat2 were used to generate a transcriptome assembly. Gene expression was calculated for each condition using the Cufflinks and Cuffmerge utilities. Cuffdiff2 with default settings was used to identify transcripts that were differentially expressed between each treatment group compared to the water only control group.The significance threshold was set at q < 0.05 (FDR corrected). Finally, a Fisher’s exact test was performed using the GeneOverlap R package to test the significance of DEG overlaps. Gene co-expression networks were identified using the Weighted Gene Co-expression Network Analysis (WGCNA) package. Results: RNA Integrity Number (RIN) was on average 8.23 ± 0.26 for all samples, suggesting high RNA integrity and quality. On average, 43 million, 150 base pair single end reads were generated for each sample and used in the analysis. The resulting alignments files from TopHat2 had an average mapping rate of 87.4%.

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RNA sequencing in human iPSCs derived from bipolar patients to identify important therapeutic molecular targets of Valproate(VPA)

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