An in vitro-identified high-affinity nucleosome-positioning signal is capable of transiently positioning a nucleosome in vivo

<p>Abstract</p> <p>Background</p> <p>The physiological function of eukaryotic DNA occurs in the context of nucleosomal arrays that can expose or obscure defined segments of the genome. Certain DNA sequences are capable of strongly positioning a nucleosome <it>in vitro</it>, suggesting the possibility that favorable intrinsic signals might reproducibly structure chromatin segments. As high-throughput sequencing analyses of nucleosome coverage <it>in vitro </it>and <it>in vivo </it>have become possible, a vigorous debate has arisen over the degree to which intrinsic DNA:nucleosome affinities orchestrate the <it>in vivo </it>positions of nucleosomes, thereby controlling physical accessibility of specific sequences in DNA.</p> <p>Results</p> <p>We describe here the <it>in vivo </it>consequences of placing a synthetic high-affinity nucleosome-positioning signal, the 601 sequence, into a DNA plasmid vector in mice. Strikingly, the 601 sequence was sufficient to position nucleosomes during an early phase after introduction of the DNA into the mice (when the plasmid vector transgene was active). This positioning capability was transient, with a loss of strong positioning at a later time point when the transgenes had become silent.</p> <p>Conclusions</p> <p>These results demonstrate an ability of DNA sequences selected solely for nucleosome affinity to organize chromatin <it>in vivo</it>, and the ability of other mechanisms to overcome these interactions in a dynamic nuclear environment.</p

Itt1p, a novel protein inhibiting translation termination in Saccharomyces cerevisiae

BACKGROUND: Termination of translation in eukaryotes is controlled by two interacting polypeptide chain release factors, eRFl and eRF3. eRFl recognizes nonsense codons UAA, UAG and UGA, while eRF3 stimulates polypeptide release from the ribosome in a GTP- and eRFl – dependent manner. Recent studies has shown that proteins interacting with these release factors can modulate the efficiency of nonsense codon readthrough. RESULTS: We have isolated a nonessential yeast gene, which causes suppression of nonsense mutations, being in a multicopy state. This gene encodes a protein designated Itt1p, possessing a zinc finger domain characteristic of the TRIAD proteins of higher eukaryotes. Overexpression of Itt1p decreases the efficiency of translation termination, resulting in the readthrough of all three types of nonsense codons. Itt1p interacts in vitro with both eRFl and eRF3. Overexpression of eRFl, but not of eRF3, abolishes the nonsense suppressor effect of overexpressed Itt1p. CONCLUSIONS: The data obtained demonstrate that Itt1p can modulate the efficiency of translation termination in yeast. This protein possesses a zinc finger domain characteristic of the TRIAD proteins of higher eukaryotes, and this is a first observation of such protein being involved in translation

Compartmentalisation and localisation of the translation initiation factor (eIF) 4F complex in normally growing fibroblasts

Previous observations of association of mRNAs and ribosomes with subcellular structures highlight the importance of localised translation. However, little is known regarding associations between eukaryotic translation initiation factors and cellular structures within the cytoplasm of normally growing cells. We have used detergent-based cellular fractionation coupled with immunofluorescence microscopy to investigate the subcellular localisation in NIH3T3 fibroblasts of the initiation factors involved in recruitment of mRNA for translation, focussing on eIF4E, the mRNA cap-binding protein, the scaffold protein eIF4GI and poly(A) binding protein (PABP). We find that these proteins exist mainly in a soluble cytosolic pool, with only a subfraction tightly associated with cellular structures. However, this "associated" fraction was enriched in active "eIF4F" complexes (eIF4E.eIF4G.eIF4A.PABP). Immunofluorescence analysis reveals both a diffuse and a perinuclear distribution of eIF4G, with the perinuclear staining pattern similar to that of the endoplasmic reticulum. eIF4E also shows both a diffuse staining pattern and a tighter perinuclear stain, partly coincident with vimentin intermediate filaments. All three proteins localise to the lamellipodia of migrating cells in close proximity to ribosomes, microtubules, microfilaments and focal adhesions, with eIF4G and eIF4E at the periphery showing a similar staining pattern to the focal adhesion protein vinculin

A manually curated ChIP-seq benchmark demonstrates room for improvement in current peak-finder programs

Chromatin immunoprecipitation (ChIP) followed by high throughput sequencing (ChIP-seq) is rapidly becoming the method of choice for discovering cell-specific transcription factor binding locations genome wide. By aligning sequenced tags to the genome, binding locations appear as peaks in the tag profile. Several programs have been designed to identify such peaks, but program evaluation has been difficult due to the lack of benchmark data sets. We have created benchmark data sets for three transcription factors by manually evaluating a selection of potential binding regions that cover typical variation in peak size and appearance. Performance of five programs on this benchmark showed, first, that external control or background data was essential to limit the number of false positive peaks from the programs. However, >80% of these peaks could be manually filtered out by visual inspection alone, without using additional background data, showing that peak shape information is not fully exploited in the evaluated programs. Second, none of the programs returned peak-regions that corresponded to the actual resolution in ChIP-seq data. Our results showed that ChIP-seq peaks should be narrowed down to 100–400 bp, which is sufficient to identify unique peaks and binding sites. Based on these results, we propose a meta-approach that gives improved peak definitions

Preferential Nucleosome Occupancy at High Values of DNA Helical Rise

Nucleosomes are the basic structural units of eukaryotic chromatin and play a key role in the regulation of gene expression. Nucleosome formation depends on several factors, including properties of the sequence itself, but also physical constraints and epigenetic factors such as chromatin-remodelling enzymes. In this view, a sequence-dependent approach is able to capture a general tendency of a region to bind a histone octamer. A reference data set of positioned nucleosomes of Saccharomyces cerevisiae was used to study the role of DNA helical rise in histone–DNA interaction. Genomic sequences were transformed into arrays of helical rise values by a tetranucleotide code and then turned into profiles of mean helical rise values. These profiles resemble maps of nucleosome occupancy, suggesting that intrinsic histone–DNA interactions are linked to helical rise. The obtained results show that preferential nucleosome occupancy occurs where the mean helical rise reaches its largest values. Mean helical rise profiles obtained by using maps of positioned nucleosomes of the Drosophila melanogaster and Plasmodium falciparum genomes, as well as Homo sapiens chromosome 20 confirm that nucleosomes are mainly located where the mean helical rise reaches its largest values

Nucleosome occupancy reveals regulatory elements of the CFTR promoter

Access to regulatory elements of the genome can be inhibited by nucleosome core particles arranged along the DNA strand. Hence, sites that are accessible by transcription factors may be located by using nuclease digestion to identify the relative nucleosome occupancy of a genomic region. In order to define novel cis regulatory elements in the ∼2.7-kb promoter region of the cystic fibrosis transmembrane conductance regulator (CFTR) gene, we define its nucleosome occupancy. This profile reveals the precise positions of nucleosome-free regions (NFRs), both cell-type specific and others apparently unrelated to CFTR-expression level and offer the first high-resolution map of the chromatin structure of the entire CFTR promoter in relevant cell types. Several of these NFRs are strongly bound by nuclear factors in a sequence-specific manner, and directly influence CFTR promoter activity. Sequences within the NFR1 and NFR4 elements are highly conserved in many human gene promoters. Moreover, NFR1 contributes to promoter activity of another gene, angiopoietin-like 3 (ANGPTL3), while NFR4 is constitutively nucleosome-free in promoters genome wide. Conserved motifs within NFRs of the CFTR promoter also show a high level of protection from DNase I digestion genome-wide, and likely have important roles in the positioning of nucleosome core particles more generally

Infectious Disease Ontology

Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain

Reassessment of Piwi Binding to the Genome and Piwi Impact on RNA Polymerase II Distribution

Drosophila Piwi was reported by Huang et al. (2013) to be guided by piRNAs to piRNA-complementary sites in the genome, which then recruits Heterochromatin Protein 1a and histone methyltransferase Su(Var)3-9 to the sites. Among additional findings, Huang et al. (2013) also reported Piwi binding sites in the genome and the reduction of RNA polymerase II in euchromatin but its increase in pericentric regions in piwi mutants. Marinov et al. (2015) disputed the validity of the Huang et al. bioinformatic pipeline that led to the last two claims. Here we report our independent reanalysis of the data using current bioinformatic methods. Our reanalysis agrees with Marinov et al. (2015) that Piwi’s genomic targets still remain to be identified, yet confirms the Huang et al. claim that Piwi influences RNA polymerase II distribution in the genome. This Response addresses the Marinov et al. (2015) Matters Arising, published concurrently in Developmental Cell