Enhanced TF binding site maps improve regulatory networks learned from accessible chromatin data

Abstract

Determining where transcription factors (TF) bind in genomes provides insights into which transcriptional programs are active across organs, tissue types, and environmental conditions. Recent advances in high-throughput profiling of regulatory DNA have yielded large amounts of information about chromatin accessibility. Interpreting the functional significance of these datasets requires knowledge of which regulators are likely to bind these regions. This can be achieved by using information about TF binding preferences, or motifs, to identify TF binding events that are likely to be functional. Although different approaches exist to map motifs to DNA sequences, a systematic evaluation of these tools in plants is missing. Here we compare four motif mapping tools widely used in the Arabidopsis research community and evaluate their performance using chromatin immunoprecipitation datasets for 40 TFs. Downstream gene regulatory network (GRN) reconstruction was found to be sensitive to the motif mapper used. We further show that the low recall of FIMO, one of the most frequently used motif mapping tools, can be overcome by using an Ensemble approach, which combines results from different mapping tools. Several examples are provided demonstrating how the Ensemble approach extends our view on transcriptional control for TFs active in different biological processes. Finally, a new protocol is presented to efficiently derive more complete cell type-specific GRNs through the integrative analysis of open chromatin regions, known binding site information, and expression datasets.