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  • Transcriptome Mapping - Monitoring Gene Expression  (6)
  • Oxford University Press  (6)
  • Copernicus
  • 2015-2019  (6)
  • 1955-1959
  • 1
    Publication Date: 2016-06-21
    Description: RNA sequencing (RNAseq) has become the method of choice for transcriptome analysis, yet no consensus exists as to the most appropriate pipeline for its analysis, with current benchmarks suffering important limitations. Here, we address these challenges through a rich benchmarking resource harnessing (i) two RNAseq datasets including ERCC ExFold spike-ins; (ii) Nanostring measurements of a panel of 150 genes on the same samples; (iii) a set of internal, genetically-determined controls; (iv) a reanalysis of the SEQC dataset; and (v) a focus on relative quantification (i.e. across-samples). We use this resource to compare different approaches to each step of RNAseq analysis, from alignment to differential expression testing. We show that methods providing the best absolute quantification do not necessarily provide good relative quantification across samples, that count-based methods are superior for gene-level relative quantification, and that the new generation of pseudo-alignment-based software performs as well as established methods, at a fraction of the computing time. We also assess the impact of library type and size on quantification and differential expression analysis. Finally, we have created a R package and a web platform to enable the simple and streamlined application of this resource to the benchmarking of future methods.
    Keywords: Transcriptome Mapping - Monitoring Gene Expression
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 2
    Publication Date: 2016-04-08
    Description: MicroRNAs (miRNAs), small non-coding RNA molecules, are important biomarkers for research and medical purposes. Here, we describe the development of a fast and simple method using highly fluorescent oligonucleotide-silver nanocluster probes (DNA/AgNCs) to efficiently detect specific miRNAs. Due to the great sequence diversity of miRNAs in humans and other organisms, a uniform strategy for miRNA detection is attractive. The concept presented is an oligonucleotide-based locking-to-unlocking system that can be endowed with miRNA complementarity while maintaining the same secondary structure. The locking-to-unlocking system is based on fold-back anchored DNA templates that consist of a cytosine-rich loop for AgNCs stabilization, an miRNA recognition site and an overlap region for hairpin stabilization. When an miRNA is recognized, fluorescence in the visible region is specifically extinguished in a concentration-dependent manner. Here, the exact composition of the fold-back anchor for the locking-to-unlocking system has been systematically optimized, balancing propensity for loop-structure formation, encapsulation of emissive AgNCs and target sensitivity. It is demonstrated that the applied strategy successfully can detect a number of cancer related miRNAs in RNA extracts from human cancer cell lines.
    Keywords: Transcriptome Mapping - Monitoring Gene Expression
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 3
    Publication Date: 2015-05-03
    Description: Cap analysis of gene expression (CAGE) is a high-throughput method for transcriptome analysis that provides a single base-pair resolution map of transcription start sites (TSS) and their relative usage. Despite their high resolution and functional significance, published CAGE data are still underused in promoter analysis due to the absence of tools that enable its efficient manipulation and integration with other genome data types. Here we present CAGEr , an R implementation of novel methods for the analysis of differential TSS usage and promoter dynamics, integrated with CAGE data processing and promoterome mining into a first comprehensive CAGE toolbox on a common analysis platform. Crucially, we provide collections of TSSs derived from most published CAGE datasets, as well as direct access to FANTOM5 resource of TSSs for numerous human and mouse cell/tissue types from within R, greatly increasing the accessibility of precise context-specific TSS data for integrative analyses. The CAGEr package is freely available from Bioconductor at http://www.bioconductor.org/packages/release/bioc/html/CAGEr.html .
    Keywords: Transcriptome Mapping - Monitoring Gene Expression
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 4
    Publication Date: 2016-04-08
    Description: The variability and complexity of the transcription initiation process was examined by adapting RNA ligase-mediated rapid amplification of 5' cDNA ends (5'-RACE) to Next-Generation Sequencing (NGS). We oligo-labelled 5'-m 7 G-capped mRNA from two genes, the simple mono-exonic Beta-2-Adrenoceptor (ADRB2R) and the complex multi-exonic Glucocorticoid Receptor (GR, NR3C1) , and detected a variability in TSS location that has received little attention up to now. Transcription was not initiated at a fixed TSS, but from loci of 4 to 10 adjacent nucleotides. Individual TSSs had frequencies from 〈0.001% to 38.5% of the total gene-specific 5' m 7 G-capped transcripts. ADRB2R used a single locus consisting of 4 adjacent TSSs. Unstimulated, the GR used a total of 358 TSSs distributed throughout 38 loci, that were principally in the 5' UTRs and were spliced using established donor and acceptor sites. Complete demethylation of the epigenetically sensitive GR promoter with 5-azacytidine induced one new locus and 127 TSSs, 12 of which were unique. We induced GR transcription with dexamethasone and Interferon-, adding one new locus and 185 additional TSSs distributed throughout the promoter region. In-vitro the TSS microvariability regulated mRNA translation efficiency and the relative abundance of the different GR N-terminal protein isoform levels.
    Keywords: Transcriptome Mapping - Monitoring Gene Expression
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 5
    Publication Date: 2015-12-02
    Description: As the use of RNA-seq has popularized, there is an increasing consciousness of the importance of experimental design, bias removal, accurate quantification and control of false positives for proper data analysis. We introduce the NOISeq R-package for quality control and analysis of count data. We show how the available diagnostic tools can be used to monitor quality issues, make pre-processing decisions and improve analysis. We demonstrate that the non-parametric NOISeqBIO efficiently controls false discoveries in experiments with biological replication and outperforms state-of-the-art methods. NOISeq is a comprehensive resource that meets current needs for robust data-aware analysis of RNA-seq differential expression.
    Keywords: Transcriptome Mapping - Monitoring Gene Expression
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 6
    Publication Date: 2015-01-10
    Description: Methods that permit controlled changes in the expression of genes are important tools for biological and medical research, and for biotechnological applications. Conventional methods are directed at individually changing each gene, its regulatory elements or its mRNA's translation rate. We demonstrate that the CRISPR-associated DNA-binding Cascade complex can be used for efficient, long-lasting and programmable gene silencing. When Cascade is targeted to a promoter sequence the transcription of the downstream gene is inhibited, resulting in dramatically reduced expression. The specificity of Cascade binding is provided by the integral crRNA component, which is easily designed to target virtually any stretch of DNA. Cascade targeted to the ORF sequence of the gene can also silence expression, albeit at lower efficiency. The system can be used to silence plasmid and chromosome targets, simultaneously target several genes and is active in different bacterial species and strains. The findings described here are an addition to the expanding range of CRISPR-based technologies and may be adapted to additional organisms and cell systems.
    Keywords: Transcriptome Mapping - Monitoring Gene Expression
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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