Congratulations to Ling and Alex on their paper being published in PLOS Computational Biology. They developed a machine learning approach to model the DNA sequence properties of gene regulatory enhancers and then quantify the conservation of enhancers’ sequence properties across diverse mammalian species. They demonstrate deep conservation of enhancer sequence properties despite the rapid turnover of the specific genomic regions that have enhancer activity. This work has broad relevance to our understanding of enhancer sequence architecture and the prediction of the effects of non-coding mutations on function within and between species. Check it out:
Prediction of gene regulatory enhancers across species reveals evolutionarily conserved sequence properties