References of "Nucleic acids research"
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See detailSimple ClinVar:an interactive web server to explore and retrieve gene and disease variants 1 aggregated in ClinVar database
Pérez-Palma, Eduardo; Gramm, Marie; Nürnberg, Peter et al

in Nucleic Acids Research (2019)

Clinical genetic testing has exponentially expanded in recent years, leading to an overwhelming amount of patient variants with high variability in pathogenicity and heterogeneous phenotypes. A large part ... [more ▼]

Clinical genetic testing has exponentially expanded in recent years, leading to an overwhelming amount of patient variants with high variability in pathogenicity and heterogeneous phenotypes. A large part of the variant level data are comprehensively aggregated in public databases such as ClinVar. However, the ability to explore this rich resource and answer general questions such as “How many genes inside ClinVar are associated with a specific disease? or “In which part of the protein are patient variants located?” is limited and requires advanced bioinformatics processing. Here, we present Simple ClinVar (http://simple-clinvar.broadinstitute.org/) a web- server application that is able to provide variant, gene, and disease level summary statistics based on the entire ClinVar database in a dynamic and user-friendly web-interface. Overall, our web application is able to interactively answer basic questions regarding genetic variation and its known relationships to disease. By typing a disease term of interest, t he user can identify in seconds the genes and phenotypes most frequently reported to ClinVar. Subsets of variants can then be further explored, filtered, or mapped and visualized in the corresponding protein sequences. Our website will follow ClinVar monthly releases and provide easy access to rich ClinVar resources to a broader audience including basic and clinical scientists. [less ▲]

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See detailAn integrative method to predict signallingperturbations for cellular transitions
Zaffaroni, Gaia UL; Okawa, Satoshi UL; Morales-Ruiz, Manuel et al

in Nucleic Acids Research (2019)

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See detailTemporal enhancer profiling of parallel lineages identifies AHR and GLIS1 as regulators of mesenchymal multipotency
Gerard, Déborah UL; Schmidt, Florian; Ginolhac, Aurélien UL et al

in Nucleic Acids Research (2018)

Temporal data on gene expression and context-specific open chromatin states can improve identification of key transcription factors (TFs) and the gene regulatory networks (GRNs) controlling cellular ... [more ▼]

Temporal data on gene expression and context-specific open chromatin states can improve identification of key transcription factors (TFs) and the gene regulatory networks (GRNs) controlling cellular differentiation. However, their integration remains challenging. Here, we delineate a general approach for data-driven and unbiased identification of key TFs and dynamic GRNs, called EPIC-DREM. We generated time-series transcriptomic and epigenomic profiles during differentiation of mouse multipotent bone marrow stromal cell line (ST2) toward adipocytes and osteoblasts. Using our novel approach we constructed time-resolved GRNs for both lineages and identifed the shared TFs involved in both differentiation processes. To take an alternative approach to prioritize the identified shared regulators, we mapped dynamic super-enhancers in both lineages and associated them to target genes with correlated expression profiles. The combination of the two approaches identified aryl hydrocarbon receptor (AHR) and Glis family zinc finger 1 (GLIS1) as mesenchymal key TFs controlled by dynamic cell type-specific super-enhancers that become repressed in both lineages. AHR and GLIS1 control differentiation-induced genes and their overexpression can inhibit the lineage commitment of the multipotent bone marrow-derived ST2 cells. [less ▲]

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See detailThe Virtual Metabolic Human database: integrating human and gut microbiome metabolism with nutrition and disease
Noronha, Alberto UL; Modamio Chamarro, Jennifer UL; Jarosz, Yohan UL et al

in Nucleic Acids Research (2018)

A multitude of factors contribute to complex diseases and can be measured with ‘omics’ methods. Databases facilitate data interpretation for underlying mechanisms. Here, we describe the Virtual Metabolic ... [more ▼]

A multitude of factors contribute to complex diseases and can be measured with ‘omics’ methods. Databases facilitate data interpretation for underlying mechanisms. Here, we describe the Virtual Metabolic Human (VMH, www.vmh.life) database encapsulating current knowledge of human metabolism within five interlinked resources ‘Human metabolism’, ‘Gut microbiome’, ‘Disease’, ‘Nutrition’, and ‘ReconMaps’. The VMH captures 5180 unique metabolites, 17 730 unique reactions, 3695 human genes, 255 Mendelian diseases, 818 microbes, 632 685 microbial genes and 8790 food items. The VMH’s unique features are (i) the hosting of the metabolic reconstructions of human and gut microbes amenable for metabolic modeling; (ii) seven human metabolic maps for data visualization; (iii) a nutrition designer; (iv) a user-friendly webpage and application-programming interface to access its content; (v) user feedback option for community engagement and (vi) the connection of its entities to 57 other web resources. The VMH represents a novel, interdisciplinary database for data interpretation and hypothesis generation to the biomedical community. [less ▲]

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See detailConfronting the catalytic dark matter encoded by sequenced genomes
Ellens, Kenneth W.; Christian, Nils; Satagopam, Venkata UL et al

in Nucleic Acids Research (2017), 45(20), 11495-11514

The post-genomic era has provided researchers with a deluge of protein sequences. However, a significant fraction of the proteins encoded by sequenced genomes remains without an identified function. Here ... [more ▼]

The post-genomic era has provided researchers with a deluge of protein sequences. However, a significant fraction of the proteins encoded by sequenced genomes remains without an identified function. Here, we aim at determining how many enzymes of uncertain or unknown function are still present in the Saccharomyces cerevisiae and human proteomes. Using information available in the Swiss-Prot, BRENDA and KEGG databases in combination with a Hidden Markov Model-based method, we estimate that >600 yeast and 2000 human proteins (>30% of their proteins of unknown function) are enzymes whose precise function(s) remain(s) to be determined. This illustrates the impressive scale of the ‘unknown enzyme problem’. We extensively review classical biochemical as well as more recent systematic experimental and computational approaches that can be used to support enzyme function discovery research. Finally, we discuss the possible roles of the elusive catalysts in light of recent developments in the fields of enzymology and metabolism as well as the significance of the unknown enzyme problem in the context of metabolic modeling, metabolic engineering and rare disease research. [less ▲]

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See detailAnalysis of primary microRNA loci from nascent transcriptomes reveals regulatory domains governed by chromatin architecture
Bouvy-Liivrand, Maria; Hernandez de Sande, Ana; Pölönen, Petri et al

in Nucleic Acids Research (2017)

Changes in mature microRNA (miRNA) levels that occur downstream of signaling cascades play an important role during human development and disease. However, the regulation of primary microRNA (pri-miRNA ... [more ▼]

Changes in mature microRNA (miRNA) levels that occur downstream of signaling cascades play an important role during human development and disease. However, the regulation of primary microRNA (pri-miRNA) genes remains to be dissected in detail. To address this, we followed a data-driven approach and developed a transcript identification, validation and quantification pipeline for characterizing the regulatory domains of pri-miRNAs. Integration of 92 nascent transcriptomes and multilevel data from cells arising from ecto-, endo- and mesoderm lineages reveals cell type-specific expression patterns, allows fine-resolution mapping of transcription start sites (TSS) and identification of candidate regulatory regions. We show that inter- and intragenic pri-miRNA transcripts span vast genomic regions and active TSS locations differ across cell types, exemplified by the mir-29a∼29b-1, mir-100∼let-7a-2∼125b-1 and miR-221∼222 clusters. Considering the presence of multiple TSS as an important regulatory feature at miRNA loci, we developed a strategy to quantify differential TSS usage. We demonstrate that the TSS activities associate with cell type-specific super-enhancers, differential stimulus responsiveness and higher-order chromatin structure. These results pave the way for building detailed regulatory maps of miRNA loci. [less ▲]

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See detailThe Effects of Sequence Variation on Genome-wide NRF2 Binding––New Target Genes and Regulatory SNPs
Kuosmanen, Suvi; Viitala, Sari; Laitinen, Tuomo et al

in Nucleic Acids Research (2016), 44(4), 1760-1775

Transcription factor binding specificity is crucial for proper target gene regulation. Motif discovery algorithms identify the main features of the binding patterns, but the accuracy on the lower affinity ... [more ▼]

Transcription factor binding specificity is crucial for proper target gene regulation. Motif discovery algorithms identify the main features of the binding patterns, but the accuracy on the lower affinity sites is often poor. Nuclear factor E2-related factor 2 (NRF2) is a ubiquitous redox-activated transcription factor having a key protective role against endogenous and exogenous oxidant and electrophile stress. Herein, we decipher the effects of sequence variation on the DNA binding sequence of NRF2, in order to identify both genome-wide bind- ing sites for NRF2 and disease-associated regulatory SNPs (rSNPs) with drastic effects on NRF2 binding. Interactions between NRF2 and DNA were studied using molecular modelling, and NRF2 chromatin immunoprecipitation-sequence datasets together with protein binding microarray measurements were utilized to study binding sequence variation in detail. The binding model thus generated was used to identify genome-wide binding sites for NRF2, and genomic binding sites with rSNPs that have strong effects on NRF2 binding and reside on active regulatory elements in human cells. As a proof of concept, miR-126–3p and -5p were identified as NRF2 target microRNAs, and a rSNP (rs113067944) residing on NRF2 target gene (Ferritin, light polypeptide, FTL) promoter was experimentally verified to decrease NRF2 binding and result in decreased transcriptional activity. [less ▲]

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See detailThe Human Phenotype Ontology in 2017
Köhler, Sebastian; Vasilevsky, Nicole A.; Engelstad, Mark et al

in Nucleic Acids Research (2016)

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components ... [more ▼]

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology. [less ▲]

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See detailCell type-selective disease-association of genes under high regulatory load
Galhardo, Mafalda Sofia UL; Berninger, Philipp; Nguyen, Thanh Phuong UL et al

in Nucleic Acids Research (2015), 43(18), 8839-8855

We previously showed that disease-linked metabolic genes are often under combinatorial regulation. Using the genome-wide ChIP-Seq binding profiles for 93 transcription factors in nine different cell lines ... [more ▼]

We previously showed that disease-linked metabolic genes are often under combinatorial regulation. Using the genome-wide ChIP-Seq binding profiles for 93 transcription factors in nine different cell lines, we show that genes under high regulatory load are significantly enriched for disease-association across cell types. We find that transcription factor load correlates with the enhancer load of the genes and thereby allows the identification of genes under high regulatory load by epigenomic mapping of active enhancers. Identification of the high enhancer load genes across 139 samples from 96 different cell and tissue types reveals a consistent enrichment for disease-associated genes in a cell type-selective manner. The underlying genes are not limited to super-enhancer genes and show several types of disease-association evidence beyond genetic variation (such as biomarkers). Interestingly, the high regulatory load genes are involved in more KEGG pathways than expected by chance, exhibit increased betweenness centrality in the interaction network of liver disease genes, and carry longer 3'UTRs with more microRNA (miRNA) binding sites than genes on average, suggesting a role as hubs integrating signals within regulatory networks. In summary, epigenetic mapping of active enhancers presents a promising and unbiased approach for identification of novel disease genes in a cell type-selective manner. [less ▲]

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See detailIdentification of large-scale genomic variation in cancer genomes using in silico reference models
Killcoyne, Sarah UL; del Sol Mesa, Antonio UL

in Nucleic Acids Research (2015)

Identifying large-scale structural variation in cancer genomes continues to be a challenge to researchers. Current methods rely on genome alignments based on a reference that can be a poor fit to highly ... [more ▼]

Identifying large-scale structural variation in cancer genomes continues to be a challenge to researchers. Current methods rely on genome alignments based on a reference that can be a poor fit to highly variant and complex tumor genomes. To address this challenge we developed a method that uses available breakpoint information to generate models of structural variations. We use these models as references to align previously unmapped and discordant reads from a genome. By using these models to align unmapped reads, we show that our method can help to identify large-scale variations that have been previously missed. [less ▲]

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See detailDisease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data.
Kibbe, Warren A.; Arze, Cesar; Felix, Victor et al

in Nucleic Acids Research (2015), 43(Database issue), 1071-8

The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype ... [more ▼]

The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens of human disease. DO is a biomedical resource of standardized common and rare disease concepts with stable identifiers organized by disease etiology. The content of DO has had 192 revisions since 2012, including the addition of 760 terms. Thirty-two percent of all terms now include definitions. DO has expanded the number and diversity of research communities and community members by 50+ during the past two years. These community members actively submit term requests, coordinate biomedical resource disease representation and provide expert curation guidance. Since the DO 2012 NAR paper, there have been hundreds of term requests and a steady increase in the number of DO listserv members, twitter followers and DO website usage. DO is moving to a multi-editor model utilizing Protege to curate DO in web ontology language. This will enable closer collaboration with the Human Phenotype Ontology, EBI's Ontology Working Group, Mouse Genome Informatics and the Monarch Initiative among others, and enhance DO's current asserted view and multiple inferred views through reasoning. [less ▲]

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See detailuORFdb--a comprehensive literature database on eukaryotic uORF biology.
Wethmar, Klaus; Barbosa Da Silva, Adriano UL; Andrade-Navarro, Miguel A. et al

in Nucleic acids research (2014), 42(1), 60-7

Approximately half of all human transcripts contain at least one upstream translational initiation site that precedes the main coding sequence (CDS) and gives rise to an upstream open reading frame (uORF ... [more ▼]

Approximately half of all human transcripts contain at least one upstream translational initiation site that precedes the main coding sequence (CDS) and gives rise to an upstream open reading frame (uORF). We generated uORFdb, publicly available at http://cbdm.mdc-berlin.de/tools/uorfdb, to serve as a comprehensive literature database on eukaryotic uORF biology. Upstream ORFs affect downstream translation by interfering with the unrestrained progression of ribosomes across the transcript leader sequence. Although the first uORF-related translational activity was observed >30 years ago, and an increasing number of studies link defective uORF-mediated translational control to the development of human diseases, the features that determine uORF-mediated regulation of downstream translation are not well understood. The uORFdb was manually curated from all uORF-related literature listed at the PubMed database. It categorizes individual publications by a variety of denominators including taxon, gene and type of study. Furthermore, the database can be filtered for multiple structural and functional uORF-related properties to allow convenient and targeted access to the complex field of eukaryotic uORF biology. [less ▲]

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See detailDirect elicitation of template concentration from quantification cycle (Cq) distributions in digital PCR
Mojtahedi, Mitra; Fouquier d'Hérouël, Aymeric UL; Huang, Sui

in Nucleic Acids Research (2014), 42(16), 126

Digital PCR (dPCR) exploits limiting dilution of a template into an array of PCR reactions. From this array the number of reactions that contain at least one (as opposed to zero) initial template is ... [more ▼]

Digital PCR (dPCR) exploits limiting dilution of a template into an array of PCR reactions. From this array the number of reactions that contain at least one (as opposed to zero) initial template is determined, allowing inferring the original template concentration. Here we present a novel protocol to efficiently infer the concentration of a sample and its optimal dilution for dPCR from few targeted qPCR assays. By taking advantage of the real-time amplification feature of qPCR as opposed to relying on endpoint PCR assessment as in standard dPCR prior knowledge of template concentration is not necessary. This eliminates the need for serial dilutions in a separate titration and reduces the number of necessary reactions. We describe the theory underlying our approach and discuss experimental moments that contribute to uncertainty. We present data from a controlled experiment where the initial template concentration is known as proof of principle and apply our method on directly monitoring transcript level change during cell differentiation as well as gauging amplicon numbers in cDNA samples after pre-amplification. [less ▲]

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See detailThe FurA regulon in Anabaena sp. PCC 7120: in silico prediction and experimental validation of novel target genes.
Gonzalez, Andres; Espinosa Angarica, Vladimir UL; Sancho, Javier et al

in Nucleic acids research (2014), 42(8), 4833-46

In the filamentous cyanobacterium Anabaena sp. PCC 7120, the ferric uptake regulator FurA functions as a global transcriptional regulator. Despite several analyses have focused on elucidating the FurA ... [more ▼]

In the filamentous cyanobacterium Anabaena sp. PCC 7120, the ferric uptake regulator FurA functions as a global transcriptional regulator. Despite several analyses have focused on elucidating the FurA-regulatory network, the number of target genes described for this essential transcription factor is limited to a handful of examples. In this article, we combine an in silico genome-wide predictive approach with experimental determinations to better define the FurA regulon. Predicted FurA-binding sites were identified upstream of 215 genes belonging to diverse functional categories including iron homeostasis, photosynthesis and respiration, heterocyst differentiation, oxidative stress defence and light-dependent signal transduction mechanisms, among others. The probabilistic model proved to be effective at discerning FurA boxes from non-cognate sequences, while subsequent electrophoretic mobility shift assay experiments confirmed the in vitro specific binding of FurA to at least 20 selected predicted targets. Gene-expression analyses further supported the dual role of FurA as transcriptional modulator that can act both as repressor and as activator. In either role, the in vitro affinity of the protein to its target sequences is strongly dependent on metal co-regulator and reducing conditions, suggesting that FurA couples in vivo iron homeostasis and the response to oxidative stress to major physiological processes in cyanobacteria. [less ▲]

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See detailNAR Molecular Biology Database Collection entry number 0953
Choi, C.; Münch, R.; Klein, J. et al

in Nucleic Acids Research (2014)

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See detailIntegrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network
Galhardo, Mafalda Sofia UL; Sinkkonen, Lasse UL; Berninger, Philippe et al

in Nucleic Acids Research (2013)

Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied ... [more ▼]

Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied through experimental and computational analysis. Integrating gene regulation data with a human metabolic network prompted the establishment of an open-sourced web portal, IDARE (Integrated Data Nodes of Regulation), for visualizing various gene-related data in context of metabolic pathways. Motivated by increasing availability of deep sequencing studies, we obtained ChIP-seq data from widely studied human umbilical vein endothelial cells. Interestingly, we found that association of metabolic genes with multiple transcription factors (TFs) enriched disease-associated genes. To demonstrate further extensions enabled by examining these networks together, constraintbased modeling was applied to data from human preadipocyte differentiation. In parallel, data on gene expression, genome-wide ChIP-seq profiles for peroxisome proliferator-activated receptor (PPAR) c, CCAAT/enhancer binding protein (CEBP) a, liver X receptor (LXR) and H3K4me3 and microRNA target identification for miR-27a, miR-29a and miR-222 were collected. Disease-relevant key nodes, including mitochondrial glycerol-phosphateacyltransferase (GPAM), were exposed from metabolic pathways predicted to change activity by focusing on association with multiple regulators. In both cell types, our analysis reveals the convergence of microRNAs and TFs within the branched chain amino acid (BCAA) metabolic pathway, possibly providing an explanation for its downregulation in obese and diabetic conditions. [less ▲]

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