Identification and characterization of transcribed enhancers during cerebellar development through enhancer RNA analysis

Abstract

Abstract Background The development of the brain requires precise coordination of molecular processes across many cell-types. Underpinning these events are gene expression programs which require intricate regulation by non-coding regulatory sequences known as enhancers. In the context of the developing brain, transcribed enhancers (TEs) regulate temporally-specific expression of genes critical for cell identity and differentiation. Transcription of non-coding RNAs at active enhancer sequences, known as enhancer RNAs (eRNAs), is tightly associated with enhancer activity and has been correlated with target gene expression. TEs have been characterized in a multitude of developing tissues, however their regulatory role has yet to be described in the context of embryonic and early postnatal brain development. In this study, eRNA transcription was analyzed to identify TEs active during cerebellar development, as a proxy for the developing brain. Cap Analysis of Gene Expression followed by sequencing (CAGE-seq) was conducted at 12 stages throughout embryonic and early postnatal cerebellar development. Results Temporal analysis of eRNA transcription identified clusters of TEs that peak in activity during either embryonic or postnatal times, highlighting their importance for temporally specific developmental events. Functional analysis of putative target genes identified molecular mechanisms under TE regulation revealing that TEs regulate genes involved in biological processes specific to neurons. We validate enhancer activity using in situ hybridization of eRNA expression from TEs predicted to regulate Nfib, a gene critical for cerebellar granule cell differentiation. Conclusions The results of this analysis provide a valuable dataset for the identification of cerebellar enhancers and provide insight into the molecular mechanisms critical for brain development under TE regulation. This dataset is shared with the community through an online resource (https://goldowitzlab.shinyapps.io/trans-enh-app/).