25
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      metaseq: a Python package for integrative genome-wide analysis reveals relationships between chromatin insulators and associated nuclear mRNA

      research-article
      * , , *
      Nucleic Acids Research
      Oxford University Press

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Here we introduce metaseq, a software library written in Python, which enables loading multiple genomic data formats into standard Python data structures and allows flexible, customized manipulation and visualization of data from high-throughput sequencing studies. We demonstrate its practical use by analyzing multiple datasets related to chromatin insulators, which are DNA–protein complexes proposed to organize the genome into distinct transcriptional domains. Recent studies in Drosophila and mammals have implicated RNA in the regulation of chromatin insulator activities. Moreover, the Drosophila RNA-binding protein Shep has been shown to antagonize gypsy insulator activity in a tissue-specific manner, but the precise role of RNA in this process remains unclear. Better understanding of chromatin insulator regulation requires integration of multiple datasets, including those from chromatin-binding, RNA-binding, and gene expression experiments. We use metaseq to integrate RIP- and ChIP-seq data for Shep and the core gypsy insulator protein Su(Hw) in two different cell types, along with publicly available ChIP-chip and RNA-seq data. Based on the metaseq-enabled analysis presented here, we propose a model where Shep associates with chromatin cotranscriptionally, then is recruited to insulator complexes in trans where it plays a negative role in insulator activity.

          Related collections

          Most cited references24

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          BigWig and BigBed: enabling browsing of large distributed datasets

          Summary: BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Availability and implementation: Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu Contact: ann@soe.ucsc.edu Supplementary information: Supplementary byte-level details of the BigWig and BigBed file formats are available at Bioinformatics online. For an in-depth description of UCSC data file formats and custom tracks, see http://genome.ucsc.edu/FAQ/FAQformat.html and http://genome.ucsc.edu/goldenPath/help/hgTracksHelp.html
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Identification of functional elements and regulatory circuits by Drosophila modENCODE.

            To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Design and analysis of ChIP-seq experiments for DNA-binding proteins

              Recent progress in massively parallel sequencing platforms has allowed for genome-wide measurements of DNA-associated proteins using a combination of chromatin immunoprecipitation and sequencing (ChIP-seq). While a variety of methods exist for analysis of the established microarray alternative (ChIP-chip), few approaches have been described for processing ChIP-seq data. To fill this gap, we propose an analysis pipeline specifically designed to detect protein binding positions with high accuracy. Using three separate datasets, we illustrate new methods for improving tag alignment and correcting for background signals. We also compare sensitivity and spatial precision of several novel and previously described binding detection algorithms. Finally, we analyze the relationship between the depth of sequencing and characteristics of the detected binding positions, and provide a method for estimating the sequencing depth necessary for a desired coverage of protein binding sites.
                Bookmark

                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                18 August 2014
                24 July 2014
                24 July 2014
                : 42
                : 14
                : 9158-9170
                Affiliations
                Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, 20892, USA
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +1 301 451 8206; Fax: +1 301 496 5239; Email: dalerr@ 123456niddk.nih.gov
                Correspondence may also be addressed to Elissa P. Lei. Tel: +1 301 435 8989; Fax: +1 301 496 5239; Email: leielissa@ 123456niddk.nih.gov
                Article
                10.1093/nar/gku644
                4132753
                25063299
                7ffcf04b-42cb-49bb-a2bb-cd926a7a9072
                Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.
                History
                : 02 July 2014
                : 11 June 2014
                : 23 April 2014
                Page count
                Pages: 13
                Categories
                Genomics
                Custom metadata
                18 August 2014

                Genetics
                Genetics

                Comments

                Comment on this article