RESUMO
Circular RNAs (circRNAs) are a large class of noncoding RNAs. Despite the identification of thousands of circular transcripts, the biological significance of most of them remains unexplored, partly because of the lack of effective methods for generating loss-of-function animal models. In this study, we focused on circTulp4, an abundant circRNA derived from the Tulp4 gene that is enriched in the brain and synaptic compartments. By creating a circTulp4-deficient mouse model, in which we mutated the splice acceptor site responsible for generating circTulp4 without affecting the linear mRNA or protein levels, we were able to conduct a comprehensive phenotypic analysis. Our results demonstrate that circTulp4 is critical in regulating neuronal and brain physiology, modulating the strength of excitatory neurotransmission and sensitivity to aversive stimuli. This study provides evidence that circRNAs can regulate biologically relevant functions in neurons, with modulatory effects at multiple levels of the phenotype, establishing a proof of principle for the regulatory role of circRNAs in neural processes.
Assuntos
Encéfalo , RNA Circular , Transmissão Sináptica , RNA Circular/genética , Animais , Camundongos , Encéfalo/metabolismo , Encéfalo/fisiologia , Camundongos Knockout , Neurônios/metabolismo , Neurônios/fisiologiaRESUMO
Circadian systems provide a fitness advantage to organisms by allowing them to adapt to daily changes of environmental cues, such as light/dark cycles. The molecular mechanism underlying the circadian clock has been well characterized. However, how internal circadian clocks are entrained with regular daily light/dark cycles remains unclear. By collecting and analyzing indirect calorimetry (IC) data from more than 2000 wild-type mice available from the International Mouse Phenotyping Consortium (IMPC), we show that the onset time and peak phase of activity and food intake rhythms are reliable parameters for screening defects of circadian misalignment. We developed a machine learning algorithm to quantify these two parameters in our misalignment screen (SyncScreener) with existing datasets and used it to screen 750 mutant mouse lines from five IMPC phenotyping centres. Mutants of five genes (Slc7a11, Rhbdl1, Spop, Ctc1 and Oxtr) were found to be associated with altered patterns of activity or food intake. By further studying the Slc7a11tm1a/tm1a mice, we confirmed its advanced activity phase phenotype in response to a simulated jetlag and skeleton photoperiod stimuli. Disruption of Slc7a11 affected the intercellular communication in the suprachiasmatic nucleus, suggesting a defect in synchronization of clock neurons. Our study has established a systematic phenotype analysis approach that can be used to uncover the mechanism of circadian entrainment in mice.