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Scoring the impact of noncoding variation on the function of cis-regulatory regions, on their chromatin state, and on the qualitative and quantitative expression levels of target genes is a fundamental problem in evolutionary genomics. A particular challenge is how to model the divergence of quantitative traits and to identify relationships between the changes across the different levels of the genome, the chromatin activity landscape, and the transcriptome. Here, we examine the use of the Ornstein-Uhlenbeck (OU) model to infer selection at the level of predicted cis-regulatory modules (CRMs), and link these with changes in transcription factor binding and chromatin activity. Using publicly available cross-species ChIP-Seq and STARR-Seq data we show how OU can be applied genome-wide to identify candidate transcription factors for which binding site and CRM turnover is correlated with changes in regulatory activity. Next, we profile open chromatin in the developing eye across three Drosophila species. We identify the recognition motifs of the chromatin remodelers, Trithorax-like and Grainyhead as mostly correlating with species-specific changes in open chromatin. In conclusion, we show in this study that CRM scores can be used as quantitative traits and that motif discovery approaches can be extended towards more complex models of divergence.
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