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  • Comparison of 3 oscillating elevations in cytosolic Ca2+ (created using electrical stimulation and measured using aequorin luminescence) in Arabidopsis seedlings. Treatment 1; high frequency high amplitude osc., Treatment 2; high frequency low amplitude osc., Treatment 3; low frequency low amplitude osc. One biological sample per experiment processed as technical dye swaps against intreated control.
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  • N-Methyl-D-aspartate receptors (NMDAr), widely located around the central nervous system, are known to be involved in behavioral disorders. Dizocilpine (commonly referred to as MK-801) is a well known non-competitive NMDAr antagonist. We treated rats with intraperitoneal injection [0.08 (low-dose) and 0.16 (high-dose) mg/kg] of MK-801. In one experiment, 40 min after NaCl (vehicle control) and MK-801 (0.08 mg/kg) injection, electrocorticogram (ECoG) signals were analyzed. In the second experiment, 40 min post-injection, the whole brain of each animal was rapidly removed and separated into amyglada, cerebral cortex, hippocampus, hypothalamus, midbrain and ventral striatum) on ice, followed by analysis using a 4x44K DNA microarray chip. Spectral analysis revealed that a single systemic injection of MK-801 significantly and selectively augmented the power of baseline (30-80 Hz) frequency oscillations. DNA microarray analysis showed the largest number (up- and down- regulations) of gene expressions in the cerebral cortex (378), midbrain (376), hippocampus (375), ventral striatum (353), amygdala (301), and hypothalamus (201) under low-dose of MK-801. Under high-dose, ventral striatum (811) showed the largest number of gene expression changes. Gene expression changes were functionally categorized to reveal expression of genes and function varies with each brain region. MK-801 increases the synchrony of baseline oscillations, causing very early changes in gene expressions in rat brain after acute MK-801 treatment, a first report. The overall goal of the present study was to identify gene expression patterns along rat chromosomes in different brain regions after a single injection of MK-801, which exerts a longer acute effect than ketamine on ongoing brain activities. Two approaches were taken, first electrophysiological and send molecular analysis, where the brain of MK-801-treated rats was subjected to a genome-wide transcriptome mapping analysis (~4400 genes) in the cerebral cortex, midbrain, hippocampus, ventral striatum, amygdala, and hypothalamus regions.
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  • Biological oscillations are observed at many levels of cellular organization. In the social amoebae Dictyostelium discoideum, starvation-triggered multicellular development is organized by periodic cAMP waves, which provide both chemoattractant gradients and developmental signals. We report that GtaC, a GATA transcription factor, exhibits rapid nucleocytoplasmic shuttling in response to cAMP waves. This behavior requires coordinated action of a nuclear localization signal and reversible G protein-coupled receptor (GPCR)-mediated phosphorylation. While both are required for developmental gene expression, receptor occupancy promotes nuclear exit of GtaC, which leads to a transient burst of transcription at each cAMP cycle. We demonstrate that this biological circuit, like an “edge trigger”, filters out high frequency signals and counts those admitted, thereby enabling cells to modulate gene expression according to the dynamic pattern of the external stimuli. Transcriptional profiling during early development of wild-type, gtaC, GFP-GtaC/gtaC, and NLSex-GFP-GtaC/gtaC strains
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  • This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Florencia Pauli mailto:fpauli@hudsonalpha.org). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track is produced as part of the ENCODE project. The track displays copy number variation (CNV) as determined by the Illumina Human 1M-Duo Infinium HD BeadChip assay and circular binary segmentation (CBS). The Human 1M-Duo contains more than 1,100,000 tagSNP markers and a set of ~60,000 additional CNV-targeted markers. The median spacing between markers is 1.5 kb and the mean spacing is 2.4 kb. The B-allele frequency and genotyping single nucleotide polymorphism (SNP) data generated by the experiment are not displayed, but are available for download from the Downloads page. Where applicable, biological replicates of each cell line are reported separately. Possible uses of the data include correction of copy number in peak-calling for ChIP-seq, transcriptome, DNase hypersensitivity, and methylation determinations. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Isolation of genomic DNA and hybridization: Cells were grown according to the approved ENCODE cell culture protocols by the Myers lab and by other ENCODE production groups. The production group is reported in the metadata. Genomic DNA was isolated using the DNeasy Blood and Tissue Kit (Qiagen). DNA concentration and quality were determined by fluorescence (Invitrogen Quant-iT dsDNA High Sensitivity Kit and Qubit Fluorometer), and 400 nanograms of each sample were hybridized to Illumina 1M-Duo DNA Analysis BeadChips. Processing and Analysis: The genotypes from the 1M-Duo Arrays were ascertained with BeadStudio by using default settings and formatting with the A/B genotype designation for each SNP. Primary QC for each sample was a cut-off at a call rate of 0.95. Copy Number Variation (CNV) analysis was performed with circular binary segmentation (DNAcopy) of the log R ratio values at each probe (Olshen et al., 2004). The parameters used were alpha=0.001, nperm=5000, sd.undo=1. The copy number segments are reported with the mean log R ratio for each chromosomal segment called by CBS. Log ratios of ~-0.2 to -1.5 can be considered heterozygous deletions, 0.2 amplifications. Primary QC for each sample was SD of < 0.6.
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  • Background: N-Methyl-D-aspartate receptors (NMDAr), widely located around the central nervous system, are known to be involved in behavioral disorders. Dizocilpine (commonly referred to as MK-801) is a well known non-competitive NMDAr antagonist. Methods: We treated rats with intraperitoneal injection [0.08 (low-dose) and 0.16 (high-dose) mg/kg] of MK-801. In one experiment, 40 min after NaCl (vehicle control) and MK-801 (0.08 mg/kg) injection, electrocorticogram (ECoG) signals were analyzed. In the second experiment, 40 min post-injection, the whole brain of each animal was rapidly removed and separated into amyglada, cerebral cortex, hippocampus, hypothalamus, midbrain and ventral striatum) on ice, followed by analysis using a 4x44K DNA microarray chip. Results: Spectral analysis revealed that a single subcutaneous injection of MK-801 significantly and selectively augmented the power of spontaneous gamma and higher-frequency oscillations. The results from DNA microarray analysis of 4400 genes showed the largest number (up- and down- regulations) of gene expressions in the cerebral cortex (378), midbrain (376), hippocampus (375), ventral striatum (353), amygdala (301), and hypothalamus (201) under low-dose of MK-801. Under high-dose, ventral striatum (811) showed the largest number of gene expression changes. These genes represented... Conclusions: Our results reveal that MK-801 triggered i) an increase in the power of gamma oscillations, and ii) simultaneously caused very early changes in gene expressions in the rat brain, representing a first such inventory of gene expression profiles in brain after acute MK-801 treatment. Nine male 10-weeks-old Wistar rats (300-350 g BW) were housed in acrylic cages (3/cage) at 24ºC and given access to tap water and laboratory chow ad libitum. The rats were divided into two groups, and each group rats received i.p. injection of 0.08 (low-dose) and 0.16 (high-dose) mg/kg of MK-801, respectively. Three rats were treated with saline as sham (vehicle control group) using the same method. After 40 min post-injection, the whole brain of each animal was rapidly removed and put on ice, and brain regions were separated according to the method of Glowinski and Iversen (1996), with minor modifications (Hirano et al., 2007). Each brain region was placed in a 2 mL Eppendorf tube, quickly immersed in liquid nitrogen before being stored in -80ºC prior to further analysis. Each sample was immediately weighed, flash-frozen in liquid nitrogen and stored at -80ºC prior to further analysis. A rat 4 x 44K whole genome oligo DNA microarray chip (G4131F, Agilent Technologies, Palo Alto, CA, USA) was used for global gene expression analysis. The effects of MK-801 were examined in the 6 brain reagion, Ventral striatum, Cerebral cortex, Midbrain, Amygdala, Hippocampus, and Hypothalamus.
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  • The thermophilic fungus Malbranchea cinnamomea belongs to the order of Onygenales and is a promising source of thermostable, industrially relevant biocatalysts, as it can grow at temperatures of more than 50°C and is able to utilise many different types of plant biomass. Enzymes from M. cinnamomea that have been characterised so far include an α-amylase, an α-glucosidase, xylanases and an alkaline β-1,3-1,4-glucanase (lichenase), all of which have been reported to have temperature optima between 50°C and 80°C. With this study, we complement the knowledge of the enzymatic repertoire of M. cinnamomea with a transcriptomic analysis of strain FCH 10.5 to provide a more comprehensive view of its lignocellulolytic enzyme system. Genes differentially expressed during growth on two different polymeric substrates, beechwood xylan and wheat bran, point to differences in the fungal response to the deconstruction of a hardwood hemicellulose (beechwood xylan) and a cereal hemicellulose (wheat bran). The data presented here will form the basis for a systematic exploration of the full potential of this fungus as a source of thermostable enzymes. We sequenced the genome of M. cinnamomea FCH 10.5, which was isolated from the compost of a waste treatment plant in Hanoi, Vietnam (PMC5604768, https://www.ncbi.nlm.nih.gov/nuccore/FQSS02000000). For RNAseq, the fungus was grown on three different carbon sources (glucose, wheat bran, beechwood xylan) at 50°C. Mycelium was harvested after 4h and 48h and RNA was extracted. For RNAseq analysis, the RNA of 4h and 48h samples was mixed 1:1, to get information about both early- and late-response genes during growth on the different carbon sources. Two independent duplicate experiments were done for each substrate. Total RNA was extracted using TRIzol (Invitrogen) and chloroform, and further purified with the RNeasy Plant RNA Kit with on-column DNAse digestion (QIAGEN). The quality of the purified RNA was verified by agarose gel electrophoresis, Nanodrop (Thermo Scientific) and Qubit (Life Technologies). The NEBNext Ultra Directional RNA Library Prep Kit for Illumina (New England Biolabs) was used to process the samples according to the manufacturer’s instructions. Briefly, mRNA was isolated from total RNA using oligo-dT magnetic beads and used to synthesise cDNA. The cDNA was ligated with sequencing adapters and PCR amplified. The quality and yield after sample preparation were determined with the Fragment Analyzer (Advanced Analytical). The size of the resulting products was consistent with the expected size distribution (a broad peak between 300-500 bp). Standard Illumina primers for Illumina cBot and HiSeq 2500, and the HiSeq control software HCS v2.2.58 were used according to manufacturer’s protocols for clustering and DNA sequencing with a concentration of 16.0 pM. The Illumina data analysis pipelines RTA v1.18.64 and Bcl2fastq v2.17 were used for image analysis, base calling, and quality check. Sequencing was performed on an Illumina HiSeq 2500 sequencer. The assembled genome from the DNA sequencing was used as a reference to map the reads using the packages Tophat (v2.0.14. Linux_x86_64) and Bowtie (v2-2.1.0) with a default mismatch rate of 2%. The frequency with which a read was mapped on a transcript was determined based on the mapped locations from the alignment. To normalise for transcript length, fpkm (fragments per kilobase of transcript per million mapped reads) were calculated. For differential expression analysis, the read counts were loaded into the DESeq package v 1.10.1. Genes were considered differentially expressed if they showed a log2 fold change ≥ 1 and the adjusted p-value was < 0.05.
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  • Gray matter volume in the cerebral cortex has been consistently found to be decreased in patients with schizophrenia. The superior temporal gyrus (STG) is one of the cortical regions that exhibit the most pronounced volumetric reduction. This reduction is generally thought to reflect, at least in part, decreased number of synapses; the majority of these synapses are believed to be furnished by glutamatergic axon terminals onto the dendritic spines on pyramidal neurons. Pyramidal neurons in the cerebral cortex exhibit layer-specific connectional properties, providing neural circuit structures that support distinct aspects of higher cortical functions. For instance, dendritic spines on pyramidal neurons in layer 3 of the cerebral cortex are targeted by both local and long-range glutamatergic projections in a highly reciprocal fashion. Synchronized activities of pyramidal neuronal networks, especially in the gamma frequency band (i.e. 30-100 Hz), are critical for the integrity of higher cortical functions. Disturbances of these networks may contribute to the pathophysiology of schizophrenia by compromising gamma oscillation. This concept is supported by the following postmortem and clinical observations. First, the density of dendritic spines on pyramidal neurons in layer 3 of the cerebral cortex, including the STG, have been shown to be significantly decreased by 23-66% in subjects with schizophrenia. Second, consistent with these findings, the average somal area of these pyramidal cells is significantly smaller. Third, we have recently found that, in the prefrontal cortex, the density of glutamatergic axonal boutons, of which dendritic spines are their major targets, was significantly decreased by as much as 79% in layer 3 (but not layer 5) in subjects with schizophrenia. Finally, an increasing number of clinical studies have consistently demonstrated that gamma oscillatory synchrony is profoundly impaired in patients with schizophrenia. Furthermore, gamma impairment has been linked to the symptoms and cognitive deficits of the illness and the severity of these symptoms and deficits have in turn been associated with the magnitude of cortical gray matter reduction. Taken together, understanding the molecular underpinnings of pyramidal cell dysfunction will shed important light onto the pathophysiology of cortical dysfunction of schizophrenia. In order to gain insight into the molecular determinants of pyramidal cell dysfunction in schizophrenia, we combined LCM with Affymetrix microarray and high-throughput TaqMan®-based MegaPlex qRT-PCR approaches, respectively, to elucidate the alterations in messenger ribonucleic acid (mRNA) and microRNA (miRNA) expression profiles of these neurons in layer 3 of the STG. We found that transforming growth factor beta (TGFβ) and BMP (bone morphogenetic proteins) signaling pathways and many genes that regulate extracellular matrix (ECM), apoptosis and cytoskeleton were dysregulated in schizophrenia. In addition, we identified 10 miRNAs that were differentially expressed in this illness; interestingly, the predicted targets of these miRNAs included the dysregulated pathways and gene networks identified by microarray analysis. Together these findings provide a neurobiological framework within which we can begin to formulate and test specific hypotheses about the molecular mechanisms that underlie pyramidal cell dysfunction in schizophrenia. Gene epxression microarray from RNA isolated from pyramidal cells in layer III of the STG from 9 normal controls and 9 subjects with schizophrenia. There was no significant difference between diagnosis groups for age, sex, and post mortem interval (PMI).
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  • Eukaryotic circadian clocks include transcriptional/translational feedback loops that drive 24-hour rhythms of transcription.These transcriptional rhythms underlie oscillations of protein abundance, thereby mediating circadian rhythms of behavior, physiology, and metabolism. Numerous studies over the last decade have employed microarrays to profile circadian transcriptional rhythms in various organisms and tissues. Here we use RNA sequencing (RNA-Seq) to profile the circadian transcriptome of *Drosophila melanogaster* brain from wild-type and *period*-null clock-defective animals. We identify several hundred transcripts whose abundance oscillates with 24-hour periods, including a number of non-coding RNAs (ncRNAs) that were not identified in previous microarray studies. Of particular interest are *U snoRNA host genes* (*Uhgs*), a family of cycling ncRNAs that encode the precursors of over 50 box C/D snoRNAs, key regulators of ribosomal biogenesis. Transcriptional profiling at the level of individual exons reveals alternative splice isoforms for many genes whose relative abundances are regulated by either *period* or circadian time, although the effect of circadian time is muted in comparison to that of *period*. Interestingly, *period* loss-of-function significantly alters the frequency of RNA editing at a number of editing sites, suggesting an unexpected link between a key circadian gene and RNA editing. We also identify tens of thousands of novel splicing events beyond those previously annotated by the modENCODE consortium, including several that affect key circadian genes. These studies demonstrate extensive circadian control of ncRNA expression, reveal the extent of clock control of alternative splicing and RNA editing, and provide a novel, genome-wide map of splicing in *Drosophila* brain. RNA-Seq transcriptional profiling of Drosophila brains from wildtype and period loss-of-function (per0) flies with time points taken over two days in constant darkness. Time points at CT24, 28, 32, 36, 40, 44, 48, 52, 56, 60, 64, and 68. 10-12 brains per time point.
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