Automated incorporation of pairwise dependency in transcription factor binding site prediction using dinucleotide weight tensors

Gene regulatory networks are ultimately encoded by the sequence-specific binding of (TFs) to short DNA segments. Although it is customary to represent the binding specificity of a TF by a position-specific weight matrix (PSWM), which assumes each position within a site contributes independently to the overall binding affinity, evidence has been accumulating that there can be significant dependencies between positions. Unfortunately, methodological challenges have so far hindered the development of a practical and generally-accepted extension of the PSWM model. On the one hand, simple models that only consider dependencies between nearest-neighbor positions are easy to use in practice, but fail to account for the distal dependencies that are observed in the data. On the other hand, models that allow for arbitrary dependencies are prone to overfitting, requiring regularization schemes that are difficult to use in practice for non-experts. Here we present a new regulatory motif model, called dinucleotide weight tensor (DWT), that incorporates arbitrary pairwise dependencies between positions in binding sites, rigorously from first principles, and free from tunable parameters. We demonstrate the power of the method on a large set of ChIP-seq data-sets, showing that DWTs outperform both PSWMs and motif models that only incorporate nearest-neighbor dependencies. We also demonstrate that DWTs outperform two previously proposed methods. Finally, we show that DWTs inferred from ChIP-seq data also outperform PSWMs on HT-SELEX data for the same TF, suggesting that DWTs capture inherent biophysical properties of the interactions between the DNA binding domains of TFs and their binding sites. We make a suite of DWT tools available at dwt.unibas.ch, that allow users to automatically perform 'motif finding', i.e. the inference of DWT motifs from a set of sequences, binding site prediction with DWTs, and visualization of DWT 'dilogo' motifs

Implication of Estrogen Response Elements in Expression of Secondary Sex-Traits in the Sex-Role Reversed Gulf Pipefish, Syngnathus scovelli

Intralocus conflict, the differential selection optima for a genomic region, between males and females created by sexual selection can be resolved with the presence of sex-biased hormone response elements (HREs) in the genome which allow for gene regulation through sex-biased hormones. In general, cis-regulatory elements are found more frequently and in closer proximity to hormonally responsive genes. I predict that genes putatively under sexual selection are more likely to have a greater number of proximal sex-biased HREs than randomly selected genes. To investigate this I chose to use estrogen response elements (EREs) and the sex-role reversed Gulf pipefish, Syngnathus scovelli. I demonstrate the secondary sex traits, transverse bands, and body depth described in female S. scovelli do not have any confounding effects of age and confirm those traits do affect male mate choice. To scan the genome of S. scovelli for EREs, I developed and tested an algorithm for identifying putative estrogen binding regions. With confirmation of the secondary sex traits putatively under sexual selection, I used feminized males with female traits to elucidate genes that are involved in production of body depth and ornamentation (i.e., transverse bands). I was able to show that these genes have an excess of EREs compared to typically sex-differentiated genes thereby demonstrating the important role EREs can play in sexual selection