Combining phylogenetic footprinting with motif models incorporating intra-motif dependencies

[ Background] Transcriptional gene regulation is a fundamental process in nature, and the experimental and computational investigation of DNA binding motifs and their binding sites is a prerequisite for elucidating this process. Approaches for de-novo motif discovery can be subdivided in phylogenetic footprinting that takes into account phylogenetic dependencies in aligned sequences of more than one species and non-phylogenetic approaches based on sequences from only one species that typically take into account intra-motif dependencies. It has been shown that modeling (i) phylogenetic dependencies as well as (ii) intra-motif dependencies separately improves de-novo motif discovery, but there is no approach capable of modeling both (i) and (ii) simultaneously.[Results] Here, we present an approach for de-novo motif discovery that combines phylogenetic footprinting with motif models capable of taking into account intra-motif dependencies. We study the degree of intra-motif dependencies inferred by this approach from ChIP-seq data of 35 transcription factors. We find that significant intra-motif dependencies of orders 1 and 2 are present in all 35 datasets and that intra-motif dependencies of order 2 are typically stronger than those of order 1. We also find that the presented approach improves the classification performance of phylogenetic footprinting in all 35 datasets and that incorporating intra-motif dependencies of order 2 yields a higher classification performance than incorporating such dependencies of only order 1.[Conclusion] Combining phylogenetic footprinting with motif models incorporating intra-motif dependencies leads to an improved performance in the classification of transcription factor binding sites. This may advance our understanding of transcriptional gene regulation and its evolution.This work was financially supported by DFG (grant no. GR3526/1), Gencat (2014 SGR 118), and Collectiveware (TIN2015-66863-C2-1-R).Peer reviewe

Additional file 1 of Combining phylogenetic footprinting with motif models incorporating intra-motif dependencies

Supplementary Material. This file is structured in three sections, presenting four additional studies, details about the implementation and some statistics regarding the datasets of all 35 TFs. In Section 1, Supplementary Results, we first study differences among species–specific motifs of 35 TFs. We then study the robustness of the proposed PFM to different species compositions on data of 35 TFs. Third, we examine the impact of base dependencies and phylogenetic dependencies on classification performance. In the fourth subsection, we compare the proposed PFM(2) with a state of the art tool by Eggeling et al. 2015 [13] on data of 35 TFs. In the fifth subsection, we show statistics of the distances between ChIP-seq positive regions and the alignment coverage of ten species. Finally, we specify the run–time of our freely available implementation of the proposed PFM. In Section 2, Supplementary Methods, we specify details about the estimation of species–specific motifs and we define a statistical test for the significance of differences among species–specific motifs. In Section 3, Supplementary Tables, we show statistics of the datasets of 35 TFs, summarize results regarding the significance of species–specific motifs and the impact of base dependencies and phylogenetic dependencies, and show the alignment coverage of ten species for 35 TFs. (PDF 1034.24 kb