4.7 Article Proceedings Paper

Capturing Auxin Response Factors Syntax Using DNA Binding Models

Journal

MOLECULAR PLANT
Volume 12, Issue 6, Pages 822-832

Publisher

CELL PRESS
DOI: 10.1016/j.molp.2018.09.010

Keywords

Auxin; Auxin Response Factor; DAP-seq; DNA binding model

Funding

  1. Agence Nationale de la Recherche [ANR-12-BSV6-0005]
  2. University Grenoble Alpes
  3. Grenoble Alliance for Cell and Structural Biology [ANR-10-LABX-49-01]
  4. Russian State Budget [0324-2019-0040]
  5. Russian Foundation for Basic Research [18-04-01130]
  6. Agence Nationale de la Recherche (ANR) [ANR-12-BSV6-0005] Funding Source: Agence Nationale de la Recherche (ANR)

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Auxin is a key hormone performing a wealth of functions throughout the life cycle of plants. It acts largely by regulating genes at the transcriptional level through a family of transcription factors called auxin response factors (ARFs). Even though all ARF monomers analyzed so far bind a similar DNA sequence, there is evidence that ARFs differ in their target genomic regions and regulated genes. Here, we report the use of position weight matrices (PWMs) to model ARF DNA binding specificity based on published DNA affinity purification sequencing (DAP-seq) data. We found that the genome binding of two ARFs (ARF2 and ARF5/Monopteros [MP]) differ largely because these two factors have different preferred ARF binding site (ARFbs) arrangements (orientation and spacing). We illustrated why PWMs are more versatile to reliably identify ARFbs than the widely used consensus sequences and demonstrated their power with biochemical experiments in the identification of the regulatory regions of IAA19, an well-characterized auxin-responsive gene. Finally, we combined gene regulation by auxin with ARF-bound regions and identified specific ARFbs configurations that are over-represented in auxin-upregulated genes, thus deciphering the ARFbs syntax functional for regulation. Our study provides a general method to exploit the potential of genome-wide DNA binding assays and to decode gene regulation.

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