Literature DB >> 16980977

Quantitative and predictive model of transcriptional control of the Drosophila melanogaster even skipped gene.

Hilde Janssens1, Shuling Hou, Johannes Jaeger, Ah-Ram Kim, Ekaterina Myasnikova, David Sharp, John Reinitz.   

Abstract

Here we present a quantitative and predictive model of the transcriptional readout of the proximal 1.7 kb of the control region of the Drosophila melanogaster gene even skipped (eve). The model is based on the positions and sequence of individual binding sites on the DNA and quantitative, time-resolved expression data at cellular resolution. These data demonstrated new expression features, first reported here. The model correctly predicts the expression patterns of mutations in trans, as well as point mutations, insertions and deletions in cis. It also shows that the nonclassical expression of stripe 7 driven by this fragment is activated by the protein Caudal (Cad), and repressed by the proteins Tailless (Tll) and Giant (Gt).

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Year:  2006        PMID: 16980977     DOI: 10.1038/ng1886

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


  103 in total

Review 1.  A vision for a biomedical cloud.

Authors:  R L Grossman; K P White
Journal:  J Intern Med       Date:  2012-02       Impact factor: 8.989

2.  Quantitatively predictable control of Drosophila transcriptional enhancers in vivo with engineered transcription factors.

Authors:  Justin Crocker; Garth R Ilsley; David L Stern
Journal:  Nat Genet       Date:  2016-02-08       Impact factor: 38.330

3.  A sequence level model of an intact locus predicts the location and function of nonadditive enhancers.

Authors:  Kenneth A Barr; John Reinitz
Journal:  PLoS One       Date:  2017-07-17       Impact factor: 3.240

4.  Quantitative analysis reveals genotype- and domain- specific differences between mRNA and protein expression of segmentation genes in Drosophila.

Authors:  Svetlana Surkova; Alena Sokolkova; Konstantin Kozlov; Sergey V Nuzhdin; Maria Samsonova
Journal:  Dev Biol       Date:  2019-01-07       Impact factor: 3.582

Review 5.  Pipeline for acquisition of quantitative data on segmentation gene expression from confocal images.

Authors:  Svetlana Surkova; Ekaterina Myasnikova; Hilde Janssens; Konstantin N Kozlov; Anastasia A Samsonova; John Reinitz; Maria Samsonova
Journal:  Fly (Austin)       Date:  2008-03-08       Impact factor: 2.160

6.  Combinatorial binding predicts spatio-temporal cis-regulatory activity.

Authors:  Robert P Zinzen; Charles Girardot; Julien Gagneur; Martina Braun; Eileen E M Furlong
Journal:  Nature       Date:  2009-11-05       Impact factor: 49.962

7.  Synthetic enhancer design by in silico compensatory evolution reveals flexibility and constraint in cis-regulation.

Authors:  Kenneth A Barr; Carlos Martinez; Jennifer R Moran; Ah-Ram Kim; Alexandre F Ramos; John Reinitz
Journal:  BMC Syst Biol       Date:  2017-11-29

Review 8.  Building quantitative, three-dimensional atlases of gene expression and morphology at cellular resolution.

Authors:  David W Knowles; Mark D Biggin
Journal:  Wiley Interdiscip Rev Dev Biol       Date:  2013-02-04       Impact factor: 5.814

9.  Ancestral resurrection of the Drosophila S2E enhancer reveals accessible evolutionary paths through compensatory change.

Authors:  Carlos Martinez; Joshua S Rest; Ah-Ram Kim; Michael Ludwig; Martin Kreitman; Kevin White; John Reinitz
Journal:  Mol Biol Evol       Date:  2014-01-09       Impact factor: 16.240

10.  Transcription factors, coregulators, and epigenetic marks are linearly correlated and highly redundant.

Authors:  Tobias Ahsendorf; Franz-Josef Müller; Ved Topkar; Jeremy Gunawardena; Roland Eils
Journal:  PLoS One       Date:  2017-12-07       Impact factor: 3.240

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