Project description:To address the global impact of PARP-1 on DNA methylation, we treated cells with PJ34 (PARylation inhibitor) and isolated genomic DNA from vehicle and PJ34 treated cells. This DNA was bisulfite treated and hybridized to the Illumina infinium Methylation 450 Beadchip. We next used these RNA-seq data sets (control, PARP-1 KD and PARylation inhibited) to assess whether PARP plays a role in DNA methylation by assessing differential methylation patterns. PARP1 mediates methylation patterns. DNA from vehicle and PJ34 (PARylation inhibited) cells. 750ng of geneomic DNA was bisulfite converted and used for the Illumia infinium HD methylation assay.
Project description:Study the effect of PARP-14 and its activity on Th2 differentiation ChIP seq was performed on Th2 differentiated cells isolated from PARP-14 +/+ and PARP-14 -/- treated with or without PJ34
Project description:To achieve the extreme nuclear condensation necessary for sperm function, most histones are replaced with protamines during spermiogenesis in mammals. Mature sperm retain only a small fraction of nucleosomes, which are, in part, enriched on gene regulatory sequences, and recent findings suggest that these retained histones provide epigenetic information that regulates expression of a subset of genes involved in embryo development after fertilization. We addressed this tantalizing hypothesis by analyzing two mouse models exhibiting abnormal histone positioning in mature sperm due to impaired poly(ADP-ribose) (PAR) metabolism during spermiogenesis and identified altered sperm histone retention in specific gene loci genome-wide using MNase digestion-based enrichment of mononucleosomal DNA. We then set out to determine the extent to which expression of these genes was altered in embryos generated with these sperm. For control sperm, most genes showed some degree of histone association, unexpectedly suggesting that histone retention in sperm genes is not an all-or-none phenomenon and that a small number of histones may remain associated with genes throughout the genome. The amount of retained histones, however, was altered in many loci when PAR metabolism was impaired. To ascertain whether sperm histone association and embryonic gene expression are linked, the transcriptome of individual 2-cell embryos derived from such sperm was determined using microarrays and RNA sequencing. Strikingly, a moderate but statistically significant portion of the genes that were differentially expressed in these embryos also showed different histone retention in the corresponding gene loci in sperm of their fathers. These findings provide new evidence for the existence of a linkage between sperm histone retention and gene expression in the embryo. Seven WT (wild-type) samples of one 2-cell embryo each, all from fathers treated with saline (controls). Each group A, B, D consists of eggs fertilized by the same father (each sample is a single 2 cell embryo, 2CE). Ten samples of 2CE from fathers treated with PJ34 (PARP inhibitor) for 6 weeks, in the same setup (PJ-MTM11-1 to PJ34-MTM14-2, offspring from fathers MTM11, MTM13 or MTM14). All mice are wild-type, strain 129SVE (=129S6/SvEvTac, Taconic).
Project description:Cryptomonas sp. was grown under phototrophic conditions, glucose supplemented phototrophic conditions and 3 different dissolved organic carbon (DOC) concentrations: 1.5, 30 and 90 mg C l−1. The objective was to study the adaptations that make Cryptomonas sp. thrive under high DOC conditions.
Project description:Silencing of DND1 in potato leads to resistance to late blight, powdery mildew and Botrytis cinerea. At the same time, however, it reduces plant growth and causes leaf necrosis. To get knowledge on the molecular events behind the pleiotropic effect of DND1 downregulation in potato transcriptome analysis were performed on three DND1 silenced lines in comparison with the potato cultivar ‘Désirée’ as a wild-type.
Project description:The host response of the primary intestinal epithelium to human astrovirus (HAstV infection has not been elucidated to date. In order to characterize the global effects of AstV infection on human intestinal tissue, we performed transcriptional profiling of VA1-infected human intestinal enteroids (HIE) by RNAseq. We used the D124 line for our studies since AstV infections are typically symptomatic in very young children, and our prior infection studies indicated rapid infection in D124. D124 HIE were mock-infected or infected with VA1 (MOI = 1) and harvested at 0 hpi (i.e., 1h post-adsorption), 12 hpi, and 24 hpi (Fig 4A). To monitor viral replication, VA1 genome copies were detected by RT-qPCR, revealing an approximately 1 and 2 log increase at 12 and 24 hpi, respectively (Fig 4B). Cellular RNA was extracted and analyzed by RNAseq. Genome copies as determined by RT-qPCR were correlated to the proportion of viral transcripts in the pool of sequenced RNA collected from the same HIE cultures, revealing an exceptionally strong correlation between the two measures of viral replication (r2 = 0.98, P = 2.5 x 10^-14. VA1 genome reads contributed 0.05 ± 0.02 x% of total RNAseq reads at 24 hpi, further confirming robust infection. Differential expression analysis was performed to identify genes associated with the HIE host response to VA1 infection. A total of 23,220 genes were detected. Differential expression of genes at each timepoint was graphed in a volcano plot. The log2 fold change in normalized expression (transcripts per million reads [TPM]) of all expressed host genes in VA1-infected HIEs relative to mock-infected HIE is shown on the x-axis. The -log10 transformed P-value is given on the y-axis. Genes that are significantly up-regulated (adjusted P < 0.05) in VA1-infected D124 HIE relative to mock-infected HIE are colored red, while significantly down-regulated genes are colored blue. Overall, after a 1 hour adsorption (0 hpi), 110 genes were significantly upregulated and 136 genes were downregulated , indicating changes due to viral attachment to cells. This number was reduced at 12 hpi, with 8 significantly upregulated and 5 downregulated genes. At 24 hpi, 154 upregulated and 49 downregulated genes compared to the mock-infected control were identified. We next identified the top 15 significantly up- and down-regulated genes at 24 hpi. This group of genes was used to generated a heatmap of the mean scaled fold-change (Z-score) in expression of each of them in virus-infected HIE relative to mock-infected HIE at each timepoint (Fig 4D). Most of the upregulated genes at 24 hpi were involved in type I and type III interferon (IFN) signaling. Of the IFN genes, IFNL1 was highly upregulated, with IFNA1 and IFNB1 upregulation being slightly lower (Fig S4B). No upregulation was observed for the genes encoding IFN-γ, or the type I and III IFN receptors (data not shown). The top 12 IFN-stimulated genes (ISGs) also positively correlated with VA1 infection (Fig S4C). Conversely, the top 12 downregulated genes, including fermitin family member 1 (FERMT1), signal peptide peptidase like 3 (SPPL3), and tetratricopeptide repeat domain 19 (TTC19) negatively correlated with VA1 infection (Fig S4D). Next, we evaluated lists of the top 100 up- and down-regulated genes at 24 hpi using an over-abundance test to identify significantly over-represented REACTOME pathways in these lists. These data revealed that the top four significantly enriched pathways among upregulated genes were all related to innate antiviral signaling (Fig 4E), which will be investigated in more detail below. For downregulated genes, the top two pathways were “neurexins and neuroligins”, which play signaling roles in synapse development, and “protein-protein interactions at synapses”. The biological significance of synapses during astrovirus infection remains to be elucidated. In order to evaluate the potential for coordinated and directional activation of genes in known signaling pathways, we applied gene set enrichment analysis (GSEA) to our RNAseq differential expression data. Based on the strong dominance of IFN signaling pathways, we focused our GSEA analysis on immune signaling (Fig 4F). During the adsorption phase, nucleic acid pattern recognition receptor signaling pathways (TLRs, STING) were upregulated, consistent with their early role in virus recognition and induction of IFN signaling. At 24 hpi, these early signaling events had been largely replaced by the later phase of IFN signaling and expression of ISGs. Taken together, these data indicate that VA1 infection predominantly elicited antiviral IFN signaling in HIE-derived fetal duodenum at the transcript level.
Project description:We applied the transcriptome profiling (RNA-seq) for high-throughput profiling of genes changes in VSMC dedifferentiation. Rat primary VSMCs were divided into 3 groups, control, PDGF-BB, PDGF-BB+PJ34,and mRNA sequence were performed. We found that PDGF-BB could upregualted the genes involved in cell proliferation and migration, and downregulated the VSMC contractile genes, all of which could be reversed by PARP inhibitor PJ34. Then we knockdowned the co-factor Myocardin in VSMCs, and found the above effects of PJ34 were nearly abolished.Our study first provided the transcription changes by RNA-seq in VSMC dedifferentiation, and demonstrated the key roles of PARP1 and the PARylation process in VSMC phenotypic switch.
Project description:The non-tumourigenic breast cell line MCF10A was transduced using pINDUCER21-MYB vector to express MYB upon addition of doxyclyclin (DOX), and compared to an empty vector (EV) control (pINDUCER21 (ORF-EG)) with and without the addition of DOX
Project description:Medulloblastoma is subdivided into different subgroups: WNt, SHH, Group 3 and Group 4. Since these subgroups are associated with different OS and metastasis rates it is crucial to understand them better. Six medulloblastoma cell lines, DAOY, ONS-76, D458, HD-MB03, CHLA-01-MED, CHLA-01R-MED, have been sequenced to compare them with medulloblastoma patient data. Methods: Medulloblastoma cell lines representating the different subgroups have been cultured and cell were harvested and RNA was isolated when 70% confluency was reached. In detail, DAOY and D458 were grown in DMEM (Thermo Fisher) with 10% FBS (HyClone, Thermo Fisher), ONS-76 and HD-MB03 were grown in RPMI 1640 (Sigma-Aldrich) with 10% FBS and CHLA-01-MED and CHLA-01R-MED were grown in DMEMF12 supplemented with B27, 20 ng/ml EGF and 20 ng/ml bFGF (all Thermo Fisher). All cells were maintained at 37 °C in a humidified atmosphere containing 5% CO2. During the course of this study, all cell lines were routinely confirmed to be mycoplasma negative (MycoAlert, Lonza, Basel, Switzerland).Cell pellets of at least 100,000 cells were washed with HBSS and frozen in liquid nitrogen. For homogenization, ceramic spheres (Lysing Matrix D, MP Biomedicals, Santa Ana, California, USA) and the FastPrep-24 homogenizer was used (MP Biomedicals, speed 4 m/s, tube holder MP:24*2 and time 20 s). Total RNA was isolated from 2D pellets using the NucleoSpin RNA Plus Kit (Macherey-Nagel, Düren, Germany) according to the manufacturer’s instructions. In total, 3 biological replicates of each cell line were processed respectively. RNA amount was determined using the Qubit RNA BR kit with the Qubit 4 (both ThermoFisher). Library preparation and RNA sequencing (transcriptome sequencing including lncRNA on Illumina PE150) were performed by Novogene (Cambridge, UK) Company Limited, Cambridge, UK. Samples with less than 100 ng or with non-qualifying RIN values were excluded from the sequencing. All prepared libraries successfully passed Novogene’s internal quality control checks and were sequenced. Following sequencing, quality control of the sequencing data was performed that confirmed all samples had high quality scores, indicating good technical performance of the sequencing. We used FastQC to perform quality checks of raw RNA data followed by adapter and low quality read filtering using the Cutadapt package (version 1.16.6) [reference]. The trimmed paired-end sequences were aligned with the human genome (hg38) and Gencode annotation (v35) using the STAR (version 2.7.5b) alignment tool. Unique reads from genomic alignment were processed and we used the featureCount tool for transcript abundance quantification. STAR read counts were used as input into edgeR. Genes with read counts greater than 10 in three or more samples were kept for subsequent analyses. After normalization analyses, counts per million (cpm) on a log2 scale were used for downstream exploratory analyses.