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      PlantPAN3.0: a new and updated resource for reconstructing transcriptional regulatory networks from ChIP-seq experiments in plants

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          Abstract

          The Plant Promoter Analysis Navigator (PlantPAN; http://PlantPAN.itps.ncku.edu.tw/) is an effective resource for predicting regulatory elements and reconstructing transcriptional regulatory networks for plant genes. In this release (PlantPAN 3.0), 17 230 TFs were collected from 78 plant species. To explore regulatory landscapes, genomic locations of TFBSs have been captured from 662 public ChIP-seq samples using standard data processing. A total of 1 233 999 regulatory linkages were identified from 99 regulatory factors (TFs, histones and other DNA-binding proteins) and their target genes across seven species. Additionally, this new version added 2449 matrices extracted from ChIP-seq peaks for cis-regulatory element prediction. In addition to integrated ChIP-seq data, four major improvements were provided for more comprehensive information of TF binding events, including (i) 1107 experimentally verified TF matrices from the literature, (ii) gene regulation network comparison between two species, (iii) 3D structures of TFs and TF-DNA complexes and (iv) condition-specific co-expression networks of TFs and their target genes extended to four species. The PlantPAN 3.0 can not only be efficiently used to investigate critical cis- and trans-regulatory elements in plant promoters, but also to reconstruct high-confidence relationships among TF–targets under specific conditions.

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          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.
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            The RCSB protein data bank: integrative view of protein, gene and 3D structural information

            The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, http://rcsb.org), the US data center for the global PDB archive, makes PDB data freely available to all users, from structural biologists to computational biologists and beyond. New tools and resources have been added to the RCSB PDB web portal in support of a ‘Structural View of Biology.’ Recent developments have improved the User experience, including the high-speed NGL Viewer that provides 3D molecular visualization in any web browser, improved support for data file download and enhanced organization of website pages for query, reporting and individual structure exploration. Structure validation information is now visible for all archival entries. PDB data have been integrated with external biological resources, including chromosomal position within the human genome; protein modifications; and metabolic pathways. PDB-101 educational materials have been reorganized into a searchable website and expanded to include new features such as the Geis Digital Archive.
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              The Sol Genomics Network (SGN)—from genotype to phenotype to breeding

              The Sol Genomics Network (SGN, http://solgenomics.net) is a web portal with genomic and phenotypic data, and analysis tools for the Solanaceae family and close relatives. SGN hosts whole genome data for an increasing number of Solanaceae family members including tomato, potato, pepper, eggplant, tobacco and Nicotiana benthamiana. The database also stores loci and phenotype data, which researchers can upload and edit with user-friendly web interfaces. Tools such as BLAST, GBrowse and JBrowse for browsing genomes, expression and map data viewers, a locus community annotation system and a QTL analysis tools are available. A new tool was recently implemented to improve Virus-Induced Gene Silencing (VIGS) constructs called the SGN VIGS tool. With the growing genomic and phenotypic data in the database, SGN is now advancing to develop new web-based breeding tools and implement the code and database structure for other species or clade-specific databases.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2019
                05 November 2018
                05 November 2018
                : 47
                : Database issue , Database issue
                : D1155-D1163
                Affiliations
                [1 ]Graduate Program in Translational Agricultural Sciences, National Cheng Kung University and Academia Sinica, Taiwan
                [2 ]School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China
                [3 ]Institute of Tropical Plant Sciences, College of Biosciences and Biotechnology, National Cheng Kung University, Tainan 70101, Taiwan
                [4 ]Department of Life Sciences, College of Biosciences and Biotechnology, National Cheng Kung University, Tainan 70101, Taiwan
                Author notes
                To whom correspondence should be addressed. Tel: +886 6 2757575 (Ext. 57322); Fax: +886 6 2083663; Email: sarah321@ 123456mail.ncku.edu.tw

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.

                Article
                gky1081
                10.1093/nar/gky1081
                6323957
                30395277
                a5562d06-cc94-4315-b200-aebf4c97f082
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 22 October 2018
                : 16 October 2018
                : 14 September 2018
                Page count
                Pages: 9
                Funding
                Funded by: Ministry of Science and Technology 10.13039/100007225
                Award ID: MOST 105-2311-B-006-004-MY3
                Categories
                Database Issue

                Genetics
                Genetics

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