DAP-Seq Identification of Transcription Factor-Binding Sites in Potato

Plant growth and adaptation to environmental fluctuations involve a tight control of cellular processes which, to a great extent, are mediated by changes at the transcriptional level. This regulation is exerted by transcription factors (TFs), a group of regulatory proteins that control gene expression by directly binding to the gene promoter regions via their cognate TF-binding sites (TFBS). The nature of TFBS defines the pattern of expression of the various plant loci, the precise combinatorial assembly of these elements being key in conferring plant's adaptation ability and in domestication. As such, TFs are main potential targets for biotechnological interventions, prompting in the last decade notable protein-DNA interaction efforts toward definition of their TFBS. Distinct methods based on in vivo or in vitro approaches defined the TFBS for many TFs, mainly in Arabidopsis, but comprehensive information on the transcriptional networks for many regulators is still lacking, especially in crops. In this chapter, detailed protocols for DAP-seq studies to unbiased identification of TFBS in potato are provided. This methodology relies on the affinity purification of genomic DNA-protein complexes in vitro, and high-throughput sequencing of the eluted DNA fragments. DAP-seq outperforms other in vitro DNA-motif definition strategies, such as protein-binding microarrays and SELEX-seq, since the protein of interest is directly bound to the genomic DNA extracted from plants yielding all the potential sites bound by the TF in the genome. Actually, data generated from DAP-seq experiments are highly similar to those out of ChIP-seq methods, but are generated much faster. We also provide a standard procedure to the analysis of the DAP-seq data, addressed to non-experienced users, that involves two consecutive steps: (1) processing of raw data (trimming, filtering, and read alignment) and (2) peak calling and identification of enriched motifs. This method allows identification of the binding profiles of dozens of TFs in crops, in a timely manner.