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Dense and pleiotropic regulatory information in a developmental enhancer

researchsnappy by researchsnappy
October 17, 2020
in Healthcare Research
0
Dense and pleiotropic regulatory information in a developmental enhancer
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  • 1.

    Wittkopp, P. J. & Kalay, G. Cis-regulatory elements: Molecular mechanisms and evolutionary processes underlying divergence. Nat. Rev. Genet. 13, 59–69 (2011).

    Article 

    Google Scholar
     

  • 2.

    Crocker, J. & Ilsley, G. R. Using synthetic biology to study gene regulatory evolution. Curr. Opin. Genet. Dev. 47, 91–101 (2017).

    CAS 
    Article 

    Google Scholar
     

  • 3.

    Mogno, I., Kwasnieski, J. C. & Cohen, B. A. Massively parallel synthetic promoter assays reveal the in vivo effects of binding site variants. Genome Res. 23, 1908–1915 (2013).

    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 4.

    Patwardhan, R. P. et al. Massively parallel functional dissection of mammalian enhancers in vivo. Nat. Biotechnol. 30, 265–270 (2012).

    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 5.

    Weingarten-Gabbay, S. et al. Systematic interrogation of human promoters. Genome Res. 29, 171–183 (2019).

    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 6.

    de Boer, C. G. et al. Deciphering eukaryotic gene-regulatory logic with 100 million random promoters. Nat. Biotechnol. 38, 56–65 (2020).

    Article 

    Google Scholar
     

  • 7.

    Duveau, F., Yuan, D. C., Metzger, B. P. H., Hodgins-Davis, A. & Wittkopp, P. J. Effects of mutation and selection on plasticity of a promoter activity in Saccharomyces cerevisiae. Proc. Natl Acad. Sci. USA 114, E11218–E11227 (2017).

    CAS 
    Article 

    Google Scholar
     

  • 8.

    Crocker, J. et al. Low affinity binding site clusters confer hox specificity and regulatory robustness. Cell 160, 191–203 (2015).

    CAS 
    Article 

    Google Scholar
     

  • 9.

    Payre, F. Genetic control of epidermis differentiation in Drosophila. Int. J. Dev. Biol. 48, 207–215 (2004).

    CAS 
    Article 

    Google Scholar
     

  • 10.

    Belliveau, N. M. et al. Systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria. Proc. Natl Acad. Sci. USA 115, E4796–E4805 (2018).

    CAS 
    Article 

    Google Scholar
     

  • 11.

    Storey, J. D., Tibshirani, R. Statistical significance for genomewide studies. Proc. Natl Acad. Sci. USA 100, 9440–9445 (2003).

    ADS 
    MathSciNet 
    CAS 
    Article 

    Google Scholar
     

  • 12.

    Pollard, K. S., Hubisz, M. J., Rosenbloom, K. R. & Siepel, A. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res. 20, 110–121 (2010).

    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 13.

    Smith, J. M. et al. Developmental constraints and evolution: a perspective from the Mountain Lake Conference on Development and Evolution. Q. Rev. Biol. 60, 265–287 (1985).

    Article 

    Google Scholar
     

  • 14.

    Uller, T., Moczek, A. P., Watson, R. A., Brakefield, P. M. & Laland, K. N. Developmental bias and evolution: a regulatory network perspective. Genetics 209, 949–966 (2018).

    Article 
    PubMed 

    Google Scholar
     

  • 15.

    Rastogi, C. et al. Accurate and sensitive quantification of protein-DNA binding affinity. Proc. Natl Acad. Sci. USA 115, E3692–E3701 (2018).

    CAS 
    Article 

    Google Scholar
     

  • 16.

    Chang, M. V., Chang, J. L., Gangopadhyay, A., Shearer, A. & Cadigan, K. M. Activation of wingless targets requires bipartite recognition of DNA by TCF. Curr. Biol. 18, 1877–1881 (2008).

    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 17.

    Nagy, O. et al. Correlated Evolution of Two Copulatory Organs via a Single cis-Regulatory Nucleotide Change. Curr. Biol. 28, 3450–3457.e13 (2018).

    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 18.

    Sabarís, G., Laiker, I., Preger-Ben Noon, E. & Frankel, N. Actors with multiple roles: pleiotropic enhancers and the paradigm of enhancer modularity. Trends Genet. 35, 423–433 (2019).

    Article 

    Google Scholar
     

  • 19.

    Vincent, B. J., Estrada, J. & DePace, A. H. The appeasement of Doug: a synthetic approach to enhancer biology. Integr. Biol. 8, 475–484 (2016).

    Article 

    Google Scholar
     

  • 20.

    Dey, S. S., Foley, J. E., Limsirichai, P., Schaffer, D. V. & Arkin, A. P. Orthogonal control of expression mean and variance by epigenetic features at different genomic loci. Mol. Syst. Biol. 11, 806 (2015).

    Article 
    PubMed 

    Google Scholar
     

  • 21.

    Stern, D. L. et al. Genetic and transgenic reagents for Drosophila simulans, D. mauritiana, D. yakuba, D. santomea, and D. virilis. G3 7, 1339–1347 (2017).

    CAS 

    Google Scholar
     

  • 22.

    Zabidi, M. A. et al. Enhancer-core-promoter specificity separates developmental and housekeeping gene regulation. Nature 518, 556–559 (2015).

    ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 23.

    Frankel, N. et al. Phenotypic robustness conferred by apparently redundant transcriptional enhancers. Nature 466, 490–493 (2010).

    ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 24.

    Tsai, A., Alves, M. R. & Crocker, J. Multi-enhancer transcriptional hubs confer phenotypic robustness. eLife 8, e45325 (2019).

    Article 
    PubMed 

    Google Scholar
     

  • 25.

    Preger-Ben Noon, E. et al. Comprehensive analysis of a cis-regulatory region reveals pleiotropy in enhancer function. Cell Rep. 22, 3021–3031 (2018).

    CAS 
    Article 

    Google Scholar
     

  • 26.

    Crocker, J., Tsai, A. & Stern, D. L. A fully synthetic transcriptional platform for a multicellular eukaryote. Cell Rep. 18, 287–296 (2017).

    CAS 
    Article 

    Google Scholar
     

  • 27.

    Jacob, F. The Possible and the Actual (Univ. Washington Press, 1994).

  • 28.

    Stern, D. L. & Sucena, E. Preparation of cuticles from unhatched first-instar Drosophila larvae. Cold Spring Harb. Protoc. 2011, 065532 (2011).


    Google Scholar
     

  • 29.

    Tischer, C., Hilsenstein, V., Hanson, K. & Pepperkok, R. Adaptive fluorescence microscopy by online feedback image analysis. Methods Cell Biol. 123, 489–503 (2014).

    Article 

    Google Scholar
     

  • 30.

    Politi, A. Z. et al. Quantitative mapping of fluorescently tagged cellular proteins using FCS-calibrated four-dimensional imaging. Nat. Protoc. 13, 1445–1464 (2018).

    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 31.

    Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 32.

    Arganda-Carreras, I. et al. in Computer Vision Approaches to Medical Image Analysis. CVAMIA 2006. Lecture Notes in Computer Science Vol. 4241 (eds Beichel, R. R. & Sonka, M.) (Springer, 2006).

  • 33.

    Campbell, R. notBoxPlot https://github.com/raacampbell/notBoxPlot (2020).

  • 34.

    Jonas. Violin Plots for Plotting Multiple Distributions (distributionPlot.m) https://uk.mathworks.com/matlabcentral/fileexchange/23661-violin-plots-for-plotting-multiple-distributions-distributionplot-m (2020).

  • 35.

    Cock, P. J. A. et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics 25, 1422–1423 (2009).

    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 36.

    Virtanen, P. et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat. Methods 17, 261–272 (2020).

    CAS 
    Article 
    PubMed 

    Google Scholar
     

  • 37.

    McKinney, W. Data structures for statistical computing in Python. Proc. 9th Python Sci. Conf. (2010).

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