Meeting our Makers:Uncovering the cis-regulatory activity of transposable elements using statistical learning

The adaptation of organisms to their environment depends on the innovative potential inherent to genetic variation. In complex organisms such as mammals, processes like development and immunity require tight gene regulation. Complex forms emerge more often as a result of changes in gene regulation rather than gene products. Recent evidence accumulates to suggest that after spreading, transposable elements may become co-opted as cis-regulatory elements, thereby integrating neighboring genes into gene regulatory networks. Current methods for detecting cis-regulatory transposable elements rely on the joint exploration of multi-omics datasets, whose generation is both costly and time-consuming. We propose that modeling protein-coding gene expression (RNA-seq) as a function of the distribution of transposable elements into subfamilies as well as their respective genomic distances to promoters is sufficient to detect changes in transposable element-mediated cis-regulation. We leverage this model to show that far from solely affecting transcription during pre-implantation embryogenesis, evolutionarily recent transposable elements fine tune gene expression in cis throughout and beyond gastrulation while controlled by conserved master transcription factors. Moreover, we find that transposable elements optimally explain transcription at protein-coding gene promoters located within a 500kb range. Altogether, this work quantitatively shows that transposable elements disperse ready-for-use cis-acting platforms poised for integrating genes into regulatory networks controlled by conserved transcriptional and epigenetic regulators. Thus, metazoan adaptation appears to emerge from a rich genomic ecosystem whereby transposable elements propagate in the gene pool in symbiosis with their cognate activators and controllers. Methods-wise, our work opens up new avenues for studying the regulatory role of transposable elements in the next-generation sequencing era.