Prediction of gene regulatory enhancers across species reveals evolutionarily conserved sequence properties.

ABSTRACT: Genomic regions with gene regulatory enhancer activity turnover rapidly across mammals. In contrast, gene expression patterns and transcription factor binding preferences are largely conserved between mammalian species. Based on this conservation, we hypothesized that enhancers active in different mammals would exhibit conserved sequence patterns in spite of their different genomic locations. To investigate this hypothesis, we evaluated the extent to which sequence patterns that are predictive of enhancers in one species are predictive of enhancers in other mammalian species by training and testing two types of machine learning models. We trained support vector machine (SVM) and convolutional neural network (CNN) classifiers to distinguish enhancers defined by histone marks from the genomi

SUBMITTER: Chen L 

PROVIDER: S-EPMC6191148 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature