Genome-wide capture of plasticity-induced nascent RNAs in neurons: nRNA-seq

It is well known that the formation of long-term memories requires the synthesis of RNA. However, the identities of these RNAs and the scope of this process remain elusive. Major limitations of existing technologies are (i) very high cost and (ii) laborious computation needed to separate large scale transcriptome datasets (e.g. microarrays and standard RNA-seq) between control and experimental preparations. These conventional approaches make it virtually impossible to achieve a desired time course of the highly dynamic, genome-wide transcriptional events underlying learning and memory. Here we describe a direct and efficient method (nRNA-seq) to perform unbiased capture and sequencing of newly synthesized RNA following long-term plasticity on the scale of the entire genome, using the marine mollusk Aplysia californica as a model. Specifically, we use an analog of uridine, 5-ethynyl uridine, combined with click chemistry and high-throughput sequencing to catalog nascent transcripts induced by two facilitatory transmitters (serotonin and nitric oxide) using a well-developed paradigm of long-term sensitization and behavioral arousal in Aplysia. Importantly, we captured virtually all RNAs previously identified in single gene targeted studies including cAMP-dependent signaling components such as CREB1, PKA, neurexin, selected glutamate receptors and ion channels. In addition, we identified and annotated more than 2,000 RNAs following just a single administration of 5-HT. The majority of these transcripts have never been implicated in long-term plasticity; this includes NMDA type 2 receptors, dozens of components involved in chromatin remodeling, molecular chaperons, transcriptional factors and a large diversity of non-coding RNAs. Many newly discovered non-coding RNAs have also been identified, such as CpG rich promoter-like associated sequence motifs, revealing the diversity of cis-regulatory elements underlying long-term plasticity. Finally, our new cost-efficient protocol is sensitive enough to perform direct sequencing of individual identified neurons as they learn and remember.