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A DNA-binding-site landscape and regulatory network analysis for NAC transcription factors inArabidopsis thaliana
Author(s) -
Søren Lindemose,
Michael K. Jensen,
Jan Van de Velde,
Charlotte O’Shea,
Ken S. Heyndrickx,
Christopher T. Workman,
Klaas Vandepoele,
Karen Skriver,
Federico De Masi
Publication year - 2014
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gku502
Subject(s) - biology , dna binding site , transcription factor , computational biology , genetics , gene , functional genomics , microarray analysis techniques , arabidopsis , genomics , promoter , gene expression , genome , mutant
Target gene identification for transcription factors is a prerequisite for the systems wide understanding of organismal behaviour. NAM-ATAF1/2-CUC2 (NAC) transcription factors are amongst the largest transcription factor families in plants, yet limited data exist from unbiased approaches to resolve the DNA-binding preferences of individual members. Here, we present a TF-target gene identification workflow based on the integration of novel protein binding microarray data with gene expression and multi-species promoter sequence conservation to identify the DNA-binding specificities and the gene regulatory networks of 12 NAC transcription factors. Our data offer specific single-base resolution fingerprints for most TFs studied and indicate that NAC DNA-binding specificities might be predicted from their DNA-binding domain's sequence. The developed methodology, including the application of complementary functional genomics filters, makes it possible to translate, for each TF, protein binding microarray data into a set of high-quality target genes. With this approach, we confirm NAC target genes reported from independent in vivo analyses. We emphasize that candidate target gene sets together with the workflow associated with functional modules offer a strong resource to unravel the regulatory potential of NAC genes and that this workflow could be used to study other families of transcription factors.

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