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      Identification and Validation of Novel Hedgehog-Responsive Enhancers Predicted by Computational Analysis of Ci/Gli Binding Site Density

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          Abstract

          The Hedgehog (Hh) signaling pathway directs a multitude of cellular responses during embryogenesis and adult tissue homeostasis. Stimulation of the pathway results in activation of Hh target genes by the transcription factor Ci/Gli, which binds to specific motifs in genomic enhancers. In Drosophila, only a few enhancers ( patched, decapentaplegic, wingless, stripe, knot, hairy, orthodenticle) have been shown by in vivo functional assays to depend on direct Ci/Gli regulation. All but one ( orthodenticle) contain more than one Ci/Gli site, prompting us to directly test whether homotypic clustering of Ci/Gli binding sites is sufficient to define a Hh-regulated enhancer. We therefore developed a computational algorithm to identify Ci/Gli clusters that are enriched over random expectation, within a given region of the genome. Candidate genomic regions containing Ci/Gli clusters were functionally tested in chicken neural tube electroporation assays and in transgenic flies. Of the 22 Ci/Gli clusters tested, seven novel enhancers (and the previously known patched enhancer) were identified as Hh-responsive and Ci/Gli-dependent in one or both of these assays, including: Cuticular protein 100A ( Cpr100A); invected ( inv), which encodes an engrailed-related transcription factor expressed at the anterior/posterior wing disc boundary; roadkill (rdx), the fly homolog of vertebrate Spop; the segment polarity gene gooseberry (gsb); and two previously untested regions of the Hh receptor-encoding patched (ptc) gene. We conclude that homotypic Ci/Gli clustering is not sufficient information to ensure Hh-responsiveness; however, it can provide a clue for enhancer recognition within putative Hedgehog target gene loci.

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          An optimized transgenesis system for Drosophila using germ-line-specific phiC31 integrases.

          Germ-line transformation via transposable elements is a powerful tool to study gene function in Drosophila melanogaster. However, some inherent characteristics of transposon-mediated transgenesis limit its use for transgene analysis. Here, we circumvent these limitations by optimizing a phiC31-based integration system. We generated a collection of lines with precisely mapped attP sites that allow the insertion of transgenes into many different predetermined intergenic locations throughout the fly genome. By using regulatory elements of the nanos and vasa genes, we established endogenous sources of the phiC31 integrase, eliminating the difficulties of coinjecting integrase mRNA and raising the transformation efficiency. Moreover, to discriminate between specific and rare nonspecific integration events, a white gene-based reconstitution system was generated that enables visual selection for precise attP targeting. Finally, we demonstrate that our chromosomal attP sites can be modified in situ, extending their scope while retaining their properties as landing sites. The efficiency, ease-of-use, and versatility obtained here with the phiC31-based integration system represents an important advance in transgenesis and opens up the possibility of systematic, high-throughput screening of large cDNA sets and regulatory elements.
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            The UCSC Genome Browser database: update 2011

            The University of California, Santa Cruz Genome Browser (http://genome.ucsc.edu) offers online access to a database of genomic sequence and annotation data for a wide variety of organisms. The Browser also has many tools for visualizing, comparing and analyzing both publicly available and user-generated genomic data sets, aligning sequences and uploading user data. Among the features released this year are a gene search tool and annotation track drag-reorder functionality as well as support for BAM and BigWig/BigBed file formats. New display enhancements include overlay of multiple wiggle tracks through use of transparent coloring, options for displaying transformed wiggle data, a ‘mean+whiskers’ windowing function for display of wiggle data at high zoom levels, and more color schemes for microarray data. New data highlights include seven new genome assemblies, a Neandertal genome data portal, phenotype and disease association data, a human RNA editing track, and a zebrafish Conservation track. We also describe updates to existing tracks.
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              MatInd and MatInspector: new fast and versatile tools for detection of consensus matches in nucleotide sequence data.

              The identification of potential regulatory motifs in new sequence data is increasingly important for experimental design. Those motifs are commonly located by matches to IUPAC strings derived from consensus sequences. Although this method is simple and widely used, a major drawback of IUPAC strings is that they necessarily remove much of the information originally present in the set of sequences. Nucleotide distribution matrices retain most of the information and are thus better suited to evaluate new potential sites. However, sufficiently large libraries of pre-compiled matrices are a prerequisite for practical application of any matrix-based approach and are just beginning to emerge. Here we present a set of tools for molecular biologists that allows generation of new matrices and detection of potential sequence matches by automatic searches with a library of pre-compiled matrices. We also supply a large library (> 200) of transcription factor binding site matrices that has been compiled on the basis of published matrices as well as entries from the TRANSFAC database, with emphasis on sequences with experimentally verified binding capacity. Our search method includes position weighting of the matrices based on the information content of individual positions and calculates a relative matrix similarity. We show several examples suggesting that this matrix similarity is useful in estimating the functional potential of matrix matches and thus provides a valuable basis for designing appropriate experiments.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                28 December 2015
                2015
                : 10
                : 12
                : e0145225
                Affiliations
                [1 ]Department of Cell and Developmental Biology, The University of Michigan, Ann Arbor, MI 48109, United States of America
                [2 ]Department of Computational Medicine and Bioinformatics, The University of Michigan, Ann Arbor, MI 48109, United States of America
                [3 ]Cellular and Molecular Biology Program, The University of Michigan, Ann Arbor, MI 48109, United States of America
                University of Iceland, ICELAND
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: DLG SB BLA KG DSL JYS AMU. Performed the experiments: KG DSL JYS NR DSP LAJ AMU. Analyzed the data: KG DSL JYS NR DSP LAJ AMU. Wrote the paper: DLG SB BLA KG DSL JYS AMU.

                [¤]

                Current address: Department of Biology, Elon University, Elon, NC 27244, United States of America

                ‡ These authors are co-first authors on this work.

                Article
                PONE-D-15-18913
                10.1371/journal.pone.0145225
                4692483
                26710299
                51eaa6e9-3b6b-4b85-a763-b6952f346a5c
                © 2015 Gurdziel et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 1 May 2015
                : 1 December 2015
                Page count
                Figures: 6, Tables: 1, Pages: 24
                Funding
                DLG, SB and BLA were funded by a Research Team Grant from The University of Michigan Center for Organogenesis. DLG is grateful for support from NIH R01-DK65850 and NIH P01-DK062041. KG was supported by NIH T32 DK094775 and the Training Program in Bioinformatics (NIH T32 GM070499). AMU was supported by NIH F30DK082144 and the Medical Scientist Training Program (NIH T32GM007863). DSL was supported by the Cellular and Molecular Biology Training Grant (NIH T32-GM007315) and a Center for Organogenesis predoctoral fellowship (NIH T32-HD007505); the Barolo lab was supported by NIH grant GM076509 and NSF grant MCB-1157800. Work in the Allen lab is supported by an AHA scientist development grant (11SDG6380000) and by NIH R21 CA167122 and NIH R01 DC014428.
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