Analysis of the Drosophila and human DPR elements reveals a distinct human variant whose specificity can be enhanced by machine learning

The RNA polymerase II core promoter is the site of convergence of the signals that lead to the initiation of transcription. Here, we performed a comparative analysis of the downstream core promoter region (DPR) in Drosophila and humans by using machine learning. These studies revealed a distinct human-specific version of the DPR and led to the use of machine learning models for the identification of synthetic extreme DPR motifs with specificity for human transcription factors relative to Drosophila factors and vice versa. More generally, machine learning models could similarly be used to design synthetic DNA elements with customized functional properties. In this study, Vo ngoc et al. used machine learning to compare the downstream core promoter (DPR) region, a DNA motif within the core promoter involved in transcription initiation, in humans and Drosophila. They identify synthetic DPR variants with specificity for species-specific transcription factors and discuss implications of their synthetic variant modeling strategy in the functional annotation of DNA sequence elements.

Automated summary

In this study, machine learning was used to compare DPR region, a DNA motif involved in transcription initiation, in humans and Drosophila. A distinct human-specific version of DPR was identified and machine learning models were used to predict synthetic DPR motifs with specificity for human transcription factors. These findings demonstrate the potential of machine learning in designing synthetic DNA elements with specific functional properties.