This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.
Although it is generally accepted that cellular differentiation requires changes to transcriptional networks, dynamic regulation of promoters and enhancers at specific sets of genes has not been previously studied en masse. Exploiting the fact that active promoters and enhancers are transcribed, we simultaneously measured their activity in 19 human and 14 mouse time courses covering a wide range of cell types and biological stimuli. Enhancer RNAs, then messenger RNAs encoding transcription factors, dominated the earliest responses. Binding sites for key lineage transcription factors were simultaneously overrepresented in enhancers and promoters active in each cellular system. Our data support a highly generalizable model in which enhancer transcription is the earliest event in successive waves of transcriptional change during cellular differentiation or activation.
Evolutionarily conserved RFX transcription factors (TFs) regulate their target genes through a DNA sequence motif called the X-box. Thereby they regulate cellular specialization and terminal differentiation. Here, we provide a comprehensive analysis of all the eight human RFX genes (RFX1-8), their spatial and temporal expression profiles, potential upstream regulators and target genes.
The mouse and human brain express a large number of noncoding RNAs (ncRNAs). Some of these are known to participate in neural progenitor cell fate determination, cell differentiation, neuronal and synaptic plasticity and transposable elements derived ncRNAs contribute to somatic variation. Dysregulation of specific long ncRNAs (lncRNAs) has been shown in neuro-developmental and neuro-degenerative diseases thus highlighting the importance of lncRNAs in brain function. Even though it is known that lncRNAs are expressed in cells at low levels in a tissue-specific manner, bioinformatics analyses of brain-specific ncRNAs has not been performed. We analyzed previously published custom microarray ncRNA expression data generated from twelve human tissues to identify tissue-specific ncRNAs. We find that among the 12 tissues studied, brain has the largest number of ncRNAs. Our analyses show that genes in the vicinity of brain-specific ncRNAs are significantly up regulated in the brain. Investigations of repeat representation show that brain-specific ncRNAs are significantly more likely to originate in repeat regions especially DNA/TcMar-Tigger compared with non-tissue-specific ncRNAs. We find SINE/Alus depleted from brain-specific dataset when compared with non-tissue-specific ncRNAs. Our data provide a bioinformatics comparison between brain-specific and non tissue-specific ncRNAs. This article is part of a Directed Issue entitled: The Non-coding RNA Revolution.
Theophylline is a nonspecific inhibitor of phosphodiesterases that, despite exerting bronchodilator and anti-inflammatory effects, is a third-line therapy rarely used to treat chronic airflow limitation. We wished to evaluate the efficacy of oral theophylline as measured by improvements in trough (pre-dose) or peak (post-dose) FEV1 and FVC in patients with clinically stable COPD.
Age-related changes in DNA methylation occurring in blood leukocytes during early childhood may reflect epigenetic maturation. We hypothesized that some of these changes involve gene networks of critical relevance in leukocyte biology and conducted a prospective study to elucidate the dynamics of DNA methylation. Serial blood samples were collected at 3, 6, 12, 24, 36, 48 and 60 months after birth in ten healthy girls born in Finland and participating in the Type 1 Diabetes Prediction and Prevention Study. DNA methylation was measured using the HumanMethylation450 BeadChip.
PROM1 is the gene encoding prominin-1 or CD133, an important cell surface marker for the isolation of both normal and cancer stem cells. PROM1 transcripts initiate at a range of transcription start sites (TSS) associated with distinct tissue and cancer expression profiles. Using high resolution Cap Analysis of Gene Expression (CAGE) sequencing we characterize TSS utilization across a broad range of normal and developmental tissues. We identify a novel proximal promoter (P6) within CD133(+) melanoma cell lines and stem cells. Additional exon array sampling finds P6 to be active in populations enriched for mesenchyme, neural stem cells and within CD133(+) enriched Ewing sarcomas. The P6 promoter is enriched with respect to previously characterized PROM1 promoters for a HMGI/Y (HMGA1) family transcription factor binding site motif and exhibits different epigenetic modifications relative to the canonical promoter region of PROM1.
Long-term treatment is recommended in major depressive disorder (MDD) to prevent relapse and to restore functioning. The aim of this study (Orion; NCT01360866) was to assess the long-term safety, tolerability, and efficacy of open-label treatment with adjunctive brexpiprazole in adult patients with MDD.
Objective: Heat shock protein 47 (HSP47) is a collagen-specific molecular chaperone that facilitates collagen maturation. Its role in cancer remains largely unknown. In this study, we investigated the roles of HSP47 in colorectal cancer (CRC) and therapy resistance. Methods: Expression of HSP47 in CRC tissues was examined (1) in paired human CRC/adjacent normal tissues, using real time quantitative reverse transcription polymerase chain reaction (qRT-PCR), The Cancer Genome Atlas (TCGA) database, and 22 independent microarray databases (curated CRC). In vitro studies on several CRC cell lines (HCT116, RKO and CCL228) with modulated HSP47 expression were conducted to assess cell viability and apoptosis (TUNEL assay and caspase-3/-7) during exposure to chemotherapy. AKT signaling and co-immunoprecipitation studies were performed to examine HSP47 and PHLPP1 interaction. In vivo studies using tumor xenografts were conducted to assess the effects of HSP47 modulation on tumor growth and therapy response. Results: HSP47 was upregulated in CRC and was associated with poor prognosis in individuals with CRC. In vitro, HSP47 overexpression supported the survival of CRC cells, whereas its knockdown sensitized cells to 5-fluorouracil (5-FU). HSP47 promoted survival by inhibiting apoptosis, enhancing AKT phosphorylation, and decreasing expression of the AKT-specific phosphatase PHLPP1 when cells were exposed to chemotherapy. These effects were partly results of the interaction between HSP47 and PHLPP1, which decreased PHLPP1 stability and led to more persistent AKT activity. In vivo, HSP47 supported tumor growth despite 5-FU treatment. Conclusions: HSP47 supports the growth of CRC tumors and suppresses the efficacy of chemotherapy via modulation of AKT signaling.
Kruppel-like factor 4 (Klf4) is a transcription factor that regulates many important cellular processes in stem cell biology, cancer, and development. We used histological and molecular methods to study the expression of Klf4 in embryonic development of the normal and Klf4 knockout cerebellum. We find that Klf4 is expressed strongly in early granule cell progenitor development but tails-off considerably by the end of embryonic development. Klf4 is also co-expressed with Pax6 in these cells. In the Klf4-null mouse, which is perinatal lethal, Klf4 positively regulates Pax6 expression and regulates the proliferation of neuronal progenitors in the rhombic lip, external granular layer and the neuroepithelium. This paper is the first to describe a role for Klf4 in the cerebellum and provides insight into this gene's function in neuronal development.
Inflammatory bowel disease (IBD) is a chronic intestinal disorder, with two main types: Crohn's disease (CD) and ulcerative colitis (UC), whose molecular pathology is not well understood. The majority of IBD-associated SNPs are located in non-coding regions and are hard to characterize since regulatory regions in IBD are not known. Here we profile transcription start sites (TSSs) and enhancers in the descending colon of 94 IBD patients and controls. IBD-upregulated promoters and enhancers are highly enriched for IBD-associated SNPs and are bound by the same transcription factors. IBD-specific TSSs are associated to genes with roles in both inflammatory cascades and gut epithelia while TSSs distinguishing UC and CD are associated to gut epithelia functions. We find that as few as 35 TSSs can distinguish active CD, UC, and controls with 85% accuracy in an independent cohort. Our data constitute a foundation for understanding the molecular pathology, gene regulation, and genetics of IBD.
There has recently been marked progress in identifying genetic risk factors for major depression (MD) and bipolar disorder (BD); however, few systematic efforts have been made to elucidate heterogeneity that exists within and across these diagnostic taxa. The Affective disorders, Environment, and Cognitive Trait (AFFECT) study presents an opportunity to identify and associate the structure of cognition and symptom-level domains across the mood disorder spectrum in a prospective study from a diverse US population.Participants were recruited from the 23andMe, Inc research participant database and through social media; self-reported diagnosis of MD or BD by a medical professional and medication status data were used to enrich for mood-disorder cases. Remote assessments were used to acquire an extensive range of phenotypes, including mood state, transdiagnostic symptom severity, task-based measures of cognition, environmental exposures, personality traits. In this paper we describe the study design, and the demographic and clinical characteristics of the cohort. In addition we report genetic ancestry, SNP heritability, and genetic correlations with other large cohorts of mood disorders.A total of 48,467 participants were enrolled: 14,768 with MD, 9864 with BD, and 23,835 controls. Upon enrollment, 47% of participants with MD and 27% with BD indicated being in an active mood episode. Cases reported early ages of onset (mean = 13.2 and 14.3 years for MD and BD, respectively), and high levels of recurrence (78.6% and 84.9% with >5 episodes), psychotherapy, and psychotropic medication use. SNP heritability on the liability scale for the ascertained MD participants (0.19-0.21) was consistent with the high level of disease severity in this cohort, while BD heritability estimates (0.16-0.22) were comparable to reports in other large scale genomic studies of mood disorders. Genetic correlations between the AFFECT cohort and other large-scale cohorts were high for MD but not for BD. By incorporating transdiagnostic symptom assessments, repeated measures, and genomic data, the AFFECT study represents a unique resource for dissecting the structure of mood disorders across multiple levels of analysis. In addition, the fully remote nature of the study provides valuable insights for future virtual and decentralized clinical trials within mood disorders.
Severely-afflicted COVID-19 patients can exhibit disease manifestations representative of sepsis, including acute respiratory distress syndrome and multiple organ failure. We hypothesized that diagnostic tools used in managing all-cause sepsis, such as clinical criteria, biomarkers, and gene expression signatures, should extend to COVID-19 patients. Here we analyzed the whole blood transcriptome of 124 early (1-5 days post-hospital admission) and late (6-20 days post-admission) sampled patients with confirmed COVID-19 infections from hospitals in Quebec, Canada. Mechanisms associated with COVID-19 severity were identified between severity groups (ranging from mild disease to the requirement for mechanical ventilation and mortality), and established sepsis signatures were assessed for dysregulation. Specifically, gene expression signatures representing pathophysiological events, namely cellular reprogramming, organ dysfunction, and mortality, were significantly enriched and predictive of severity and lethality in COVID-19 patients. Mechanistic endotypes reflective of distinct sepsis aetiologies and therapeutic opportunities were also identified in subsets of patients, enabling prediction of potentially-effective repurposed drugs. The expression of sepsis gene expression signatures in severely-afflicted COVID-19 patients indicates that these patients should be classified as having severe sepsis. Accordingly, in severe COVID-19 patients, these signatures should be strongly considered for the mechanistic characterization, diagnosis, and guidance of treatment using repurposed drugs.
Perturbation and time-course data sets, in combination with computational approaches, can be used to infer transcriptional regulatory networks which ultimately govern the developmental pathways and responses of cells. Here, we individually knocked down the four transcription factors PU.1, IRF8, MYB and SP1 in the human monocyte leukemia THP-1 cell line and profiled the genome-wide transcriptional response of individual transcription starting sites using deep sequencing based Cap Analysis of Gene Expression. From the proximal promoter regions of the responding transcription starting sites, we derived de novo binding-site motifs, characterized their biological function and constructed a network. We found a previously described composite motif for PU.1 and IRF8 that explains the overlapping set of transcriptional responses upon knockdown of either factor.
Mutations in three functionally diverse genes cause Rett Syndrome. Although the functions of Forkhead box G1 (FOXG1), Methyl CpG binding protein 2 (MECP2) and Cyclin-dependent kinase-like 5 (CDKL5) have been studied individually, not much is known about their relation to each other with respect to expression levels and regulatory regions. Here we analyzed data from hundreds of mouse and human samples included in the FANTOM5 project, to identify transcript initiation sites, expression levels, expression correlations and regulatory regions of the three genes.
A better understanding of the biological factors underlying antidepressant treatment in patients with major depressive disorder (MDD) is needed. We perform gene expression analyses and explore sources of variability in peripheral blood related to antidepressant treatment and treatment response in patients suffering from recurrent MDD at baseline and after 8 weeks of treatment. The study includes 281 patients, which were randomized to 8 weeks of treatment with vortioxetine (N = 184) or placebo (N = 97). To our knowledge, this is the largest dataset including both gene expression in blood and placebo-controlled treatment response measured by a clinical scale in a randomized clinical trial. We identified three novel genes whose RNA expression levels at baseline and week 8 are significantly (FDR < 0.05) associated with treatment response after 8 weeks of treatment. Among these genes were SOCS3 (FDR = 0.0039) and PROK2 (FDR = 0.0028), which have previously both been linked to depression. Downregulation of these genes was associated with poorer treatment response. We did not identify any genes that were differentially expressed between placebo and vortioxetine groups at week 8 or between baseline and week 8 of treatment. Nor did we replicate any genes identified in previous peripheral blood gene expression studies examining treatment response. Analysis of genome-wide expression variability showed that type of treatment and treatment response explains very little of the variance, a median of <0.0001% and 0.05% in gene expression across all genes, respectively. Given the relatively large size of the study, the limited findings suggest that peripheral blood gene expression might not be the best approach to explore the biological factors underlying antidepressant treatment.
The genetic architecture of antidepressant response is poorly understood. Polygenic risk scores (PRS), exploration of placebo response and the use of sub-scales might provide insights. Here, we investigate the association between PRSs for relevant complex traits and response to vortioxetine treatment and placebo using clinical scales, including sub-scales and self-reported assessments. We collected a clinical test sample of Major Depressive Disorder (MDD) patients treated with vortioxetine (N = 907) or placebo (N = 455) from seven randomized, double-blind, clinical trials. In parallel, we obtained data from an observational web-based study of vortioxetine-treated patients (N = 642) with self-reported response. PRSs for antidepressant response, psychiatric disorders, and symptom traits were derived using summary statistics from well-powered genome-wide association studies (GWAS). Association tests were performed between the PRSs and treatment response in each of the two test samples and empirical p-values were evaluated. In the clinical test sample, no PRSs were significantly associated with response to vortioxetine treatment or placebo following Bonferroni correction. However, clinically assessed treatment response PRS was nominally associated with vortioxetine treatment and placebo response given by several secondary outcome scales (improvement on HAM-A, HAM-A Psychic Anxiety sub-scale, CPFQ & PDQ), (P ≤ 0.026). Further, higher subjective well-being PRS (P ≤ 0.033) and lower depression PRS (P = 0.01) were nominally associated with higher placebo response. In the self-reported test sample, higher schizophrenia PRS was significantly associated with poorer self-reported response (P = 0.0001). The identified PRSs explain a low proportion of the variance (1.2-5.3%) in placebo and treatment response. Although the results were limited, we believe that PRS associations bear unredeemed potential as a predictor for treatment response, as more well-powered and phenotypically similar GWAS bases become available.
The Caco-2 cell line is one of the most important in vitro models for enterocytes, and is used to study drug absorption and disease, including inflammatory bowel disease and cancer. In order to use the model optimally, it is necessary to map its functional entities. In this study, we have generated genome-wide maps of active transcription start sites (TSSs), and active enhancers in Caco-2 cells with or without tumour necrosis factor (TNF)-α stimulation to mimic an inflammatory state. We found 520 promoters that significantly changed their usage level upon TNF-α stimulation; of these, 52% are not annotated. A subset of these has the potential to confer change in protein function due to protein domain exclusion. Moreover, we locate 890 transcribed enhancer candidates, where ∼50% are changing in usage after TNF-α stimulation. These enhancers share motif enrichments with similarly responding gene promoters. As a case example, we characterize an enhancer regulating the laminin-5 γ2-chain (LAMC2) gene by nuclear factor (NF)-κB binding. This report is the first to present comprehensive TSS and enhancer maps over Caco-2 cells, and highlights many novel inflammation-specific promoters and enhancers.
The mammalian CNS is one of the most complex biological systems to understand at the molecular level. The temporal information from time series transcriptome analysis can serve as a potent source of associative information between developmental processes and regulatory genes. Here, we introduce a new transcriptome database called, Cerebellar Gene Regulation in Time and Space (CbGRiTS). This dataset is populated with transcriptome data across embryonic and postnatal development from two standard mouse strains, C57BL/6J and DBA/2J, several recombinant inbred lines and cerebellar mutant strains. Users can evaluate expression profiles across cerebellar development in a deep time series with graphical interfaces for data exploration and link-out to anatomical expression databases. We present three analytical approaches that take advantage of specific aspects of the time series for transcriptome analysis. We demonstrate the use of CbGRiTS dataset as a community resource to explore patterns of gene expression and develop hypotheses concerning gene regulatory networks in brain development.
Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the facets that you can filter your papers by.
From here we'll present any options for the literature, such as exporting your current results.
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.
Year:
Count: