Lindemose, Søren5; Jensen, Michael Krogh1; de Velde, Jan Van9; O'Shea, Charlotte5; Heyndrickx, Ken S.9; Workman, Christopher7; Vandepoele, Klaas9; Skriver, Karen5; De Masi, Federico8
1 Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark2 Synthetic Biology Tools for Yeast, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark3 Department of Systems Biology, Technical University of Denmark4 Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark5 University of Copenhagen6 Ghent University7 Regulatory Genomics, Department of Biotechnology and Biomedicine, Technical University of Denmark8 Department of Bio and Health Informatics, Technical University of Denmark9 Ghent University
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.
Nucleic Acids Research, 2014, Vol 42, Issue 12, p. 7681-7693