Defining kinetic roles of transcriptional activators in the early Drosophila embryo

SUMMARYMost animal transcription factors are categorized as activators or repressors without specifying their mechanisms of action. Defining their specific roles is critical for deciphering the logic of transcriptional regulation and predicting the function of regulatory sequences. Here, we define the kinetic roles of three activating transcription factors in the Drosophila embryo—Zelda, Bicoid and Stat92E—by introducing their binding sites into theeven skippedstripe 2 enhancer and measuring transcriptional output with live imaging. We find that these transcription factors act on different subsets of kinetic parameters, and these subsets can change over the course of nuclear cycle (NC) 14. These transcription factors all increase the fraction of active nuclei. Zelda dramatically shortens the time interval between the start of NC 14 and initial activation, and Stat92E increases the duration of active transcription intervals throughout NC 14. Zelda also decreases the time intervals between instances of active transcription early in NC 14, while Stat92E does so later. Different transcription factors therefore play distinct kinetic roles in activating transcription; this has consequences for understanding both regulatory DNA sequences as well as the biochemical function of transcription factors.

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Comparison of Promoter Sequences Based on Inter Motif Distance

International Journal of Software Science and Computational Intelligence ◽

10.4018/ijssci.2011070105 ◽

2011 ◽

Vol 3 (3) ◽

pp. 57-68

Author(s):

A. Meera ◽

Lalitha Rangarajan

Keyword(s):

Dna Sequences ◽

Gene Networks ◽

Distance Measure ◽

Citrate Synthase ◽

Substantial Part ◽

Regulatory Sequences ◽

Promoter Sequences ◽

Regulatory Dna Sequences ◽

Important Challenge ◽

Regulatory Dna

Understanding how the regulation of gene networks is orchestrated is an important challenge for characterizing complex biological processes. The DNA sequences that comprise promoters do not provide much direct information about regulation. A substantial part of the regulation results from the interaction of transcription factors (TFs) with specific cis regulatory DNA sequences. These regulatory sequences are organized in a modular fashion, with each module (enhancer) containing one or more binding sites for a specific combination of TFs. In the present work, the authors have proposed to investigate the inter motif distance between the important motifs in the promoter sequences of citrate synthase of different mammals. The authors have used a new distance measure to compare the promoter sequences. Results reveal that there exists more similarity between organisms in the same chromosome.

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Comparison of Promoter Sequences Based on Inter Motif Distance

Advances in Abstract Intelligence and Soft Computing ◽

10.4018/978-1-4666-2651-5.ch025 ◽

2013 ◽

pp. 374-385

Author(s):

A. Meera ◽

Lalitha Rangarajan

Keyword(s):

Dna Sequences ◽

Gene Networks ◽

Distance Measure ◽

Citrate Synthase ◽

Substantial Part ◽

Regulatory Sequences ◽

Promoter Sequences ◽

Regulatory Dna Sequences ◽

Important Challenge ◽

Regulatory Dna

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Eukaryotic transient expression system dependent on transcription factors and regulatory DNA sequences of vaccinia virus.

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.82.1.19 ◽

1985 ◽

Vol 82 (1) ◽

pp. 19-23 ◽

Cited By ~ 31

Author(s):

M. A. Cochran ◽

M. Mackett ◽

B. Moss

Keyword(s):

Transcription Factors ◽

Vaccinia Virus ◽

Transient Expression ◽

Dna Sequences ◽

Expression System ◽

Transient Expression System ◽

Regulatory Dna Sequences ◽

Regulatory Dna

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A comprehensive fitness landscape model reveals the evolutionary history and future evolvability of eukaryotic cis-regulatory DNA sequences

10.1101/2021.02.17.430503 ◽

2021 ◽

Author(s):

Eeshit Dhaval Vaishnav ◽

Carl G. de Boer ◽

Moran Yassour ◽

Jennifer Molinet ◽

Lin Fan ◽

...

Keyword(s):

Gene Expression ◽

Dna Sequences ◽

Two Dimensions ◽

Fitness Landscapes ◽

Regulatory Sequence ◽

Stabilizing Selection ◽

Regulatory Sequences ◽

Mutational Robustness ◽

Regulatory Dna Sequences ◽

Regulatory Dna

Mutations in non-coding cis-regulatory DNA sequences can alter gene expression, organismal phenotype, and fitness. Fitness landscapes, which map DNA sequence to organismal fitness, are a long-standing goal in biology, but have remained elusive because it is challenging to generalize accurately to the vast space of possible sequences using models built on measurements from a limited number of endogenous regulatory sequences. Here, we construct a sequence-to-expression model for such a landscape and use it to decipher principles of cis-regulatory evolution. Using tens of millions of randomly sampled promoter DNA sequences and their measured expression levels in the yeast Sacccharomyces cerevisiae, we construct a deep transformer neural network model that generalizes with exceptional accuracy, and enables sequence design for gene expression engineering. Using our model, we predict and experimentally validate expression divergence under random genetic drift and strong selection weak mutation regimes, show that conflicting expression objectives in different environments constrain expression adaptation, and find that stabilizing selection on gene expression leads to the moderation of regulatory complexity. We present an approach for detecting selective constraint on gene expression using our model and natural sequence variation, and validate it using observed cis-regulatory diversity across 1,011 yeast strains, cross-species RNA-seq from three different clades, and measured expression-to-fitness curves. Finally, we develop a characterization of regulatory evolvability, use it to visualize fitness landscapes in two dimensions, discover evolvability archetypes, quantify the mutational robustness of individual sequences and highlight the mutational robustness of extant natural regulatory sequence populations. Our work provides a general framework that addresses key questions in the evolution of cis-regulatory sequences.

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Quantifying the regulatory role of individual transcription factors in Escherichia coli

10.1101/2021.01.04.425191 ◽

2021 ◽

Author(s):

Sunil Guharajan ◽

Shivani Chhabra ◽

Vinuselvi Parisutham ◽

Robert C Brewster

Keyword(s):

Transcription Factors ◽

Dna Sequences ◽

Transcription Initiation ◽

Target Genes ◽

Regulatory Role ◽

E Coli ◽

Regulatory Dna Sequences ◽

The Individual ◽

Regulatory Dna

Transcription factors (TFs) modulate gene expression by binding to regulatory DNA sequences surrounding target genes. To isolate the fundamental regulatory interactions of E. coli TFs, we measure regulation of TFs acting on synthetic target genes that are designed to isolate the individual TF regulatory effect. This data is interpreted through a thermodynamic model that decouples the role of TF copy number and TF binding affinity from the interactions of the TF on RNA polymerase through two distinct mechanisms: (de)stabilization of the polymerase and (de)acceleration of transcription initiation. We find the contribution of each mechanism towards the observed regulation depends on TF identity and binding location; for the set of TFs studied here, regulation immediately downstream of the promoter is not sensitive to TF identity, however these same TFs regulate through distinct mechanisms at an upstream binding site. Furthermore, depending on binding location, these two mechanisms of regulation can act coherently, to reinforce the observed regulatory role (activation or repression), or incoherently, where the TF regulates two distinct steps with opposing effect.

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