Investigating the Behavioural and Molecular Functions of <i>Cry1</i> and <i>Cry2</i> Using Mouse Mutants

Endogenous circadian clocks generate rhythms of physiology and behaviour that are synchronised to the environment, principally through the light-dark cycle. In mammals, the circadian clock is dependent on interlocked feedback loops that involve several clock elements such as cryptochromes (Cry1 and Cry2). Post-translational modifications control intracellular trafficking, functionality and degradation of CRY proteins which are keys to the functioning of the clock. CRY protein levels are dependent upon their timely degradation by F-box proteins. This has recently been shown in the afterhours (Afh) mutant carrying a mutation in the F-box gene, Fbxl3. Afh has been shown to lengthen circadian period by stabilising levels of CRY proteins across the circadian cycle. To understand the specific roles of each of the two CRY proteins in circadian regulation, we generated compound mouse mutants to investigate the behavioural and molecular consequences of stabilising either CRY1 or CRY2 protein levels in mice lacking the alternative form of Cry. The circadian wheel-running activity assessed in light:dark and constant environmental conditions for both Cry1-/-;Fbx13Afh/Afh and Cry2-/-;Fbx13Afh/Afh (stabilising CRY2 and CRY1 protein levels respectively); clearly show a gradual increase in period length in constant darkness as the dosage of Fbxl3Afh is increased. This would suggest that stabilisation of either CRY protein can lengthen the clock, presumably as a result of a prolonged phase of transcriptional repression by either protein. This effect seen in the compound mutants was confirmed at the gene and protein levels and it was concluded that Cry1 and Cry2 can both act as transcriptional repressors, but that Cry1 plays the predominant inhibitory role in the cerebellum and peripheral organs. Subsequently it has been shown that FBXL21, the closest homologue of FBXL3, also binds to CRY1 and impairs its repressive action towards the transcriptional activators, CLOCK-BMAL1 presumably by degrading CRY1. Due to differences in their expression Fbxl3 and Fbxl21 may have overlapping roles. In-vitro and in vivo analysis in mutants generated in Fbxl21; revealed CRY2 as a preferable target of FBXL21 and that this may contribute to the lower repressive function of Cry2. Further investigation into the genetic interactions between the two F-box genes showed that Fbxl3 is epistatic to Fbxl21. Finally, Fbxl21 has been shown to be associated with schizophrenia in humans. In our hands mutant mouse Fbxl21 showed no such associations, instead indicating an association with anxiety and/or defects in sensorimotor gating

Investigating the behavioural and molecular functions of Cry1 and Cry2 using mouse mutants

Endogenous circadian clocks generate rhythms of physiology and behaviour that are synchronised to the environment, principally through the light-dark cycle. In mammals, the circadian clock is dependent on interlocked feedback loops that involve several clock elements such as cryptochromes (Cryl and Cry2). Post-translational modifications control intracellular trafficking, functionality and degradation of CRY proteins which are keys to the functioning of the clock. CRY protein levels are dependent upon their timely degradation by F-box proteins. This has recently been shown in the afterhours (Afh) mutant carrying a mutation in the F -box gene, Fbxl3. Afh has been shown to lengthen circadian period by stabilising levels of CRY proteins across the circadian cycle. To understand the specific roles of each of the two CRY proteins in circadian regulation, we generated compound mouse mutants to investigate the behavioural and molecular consequences of stabilising either CRY1 or CRY2 protein levels in mice lacking the alternative form of Cry. The circadian wheel-running activity assessed in light:dark and constant environmental conditions for both Cryrl-;FbxI3Afh/Afh and Cry[I-;FbxI3Afh/Afh (stabilising CRY2 and CRY1 protein levels respectively); clearly show a gradual increase in period length in constant darkness as the dosage of Fbxl3Afh is increased. This would suggest that stabilisation of either CRY protein can lengthen the clock, presumably as a result of a prolonged phase of transcriptional repression by either protein. This effect seen in the compound mutants was confirmed at the gene and protein levels.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Beyond the imitation game: Quantifying and extrapolating the capabilities of language models

Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabilities are as yet poorly characterized. In order to inform future research, prepare for disruptive new model capabilities, and ameliorate socially harmful effects, it is vital that we understand the present and near-future capabilities and limitations of language models. To address this challenge, we introduce the Beyond the Imitation Game benchmark (BIG-bench). BIG-bench currently consists of 204 tasks, contributed by 442 authors across 132 institutions. Task topics are diverse, drawing problems from linguistics, childhood development, math, common-sense reasoning, biology, physics, social bias, software development, and beyond. BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models. We evaluate the behavior of OpenAI's GPT models, Google-internal dense transformer architectures, and Switch-style sparse transformers on BIG-bench, across model sizes spanning millions to hundreds of billions of parameters. In addition, a team of human expert raters performed all tasks in order to provide a strong baseline. Findings include: model performance and calibration both improve with scale, but are poor in absolute terms (and when compared with rater performance); performance is remarkably similar across model classes, though with benefits from sparsity; tasks that improve gradually and predictably commonly involve a large knowledge or memorization component, whereas tasks that exhibit "breakthrough" behavior at a critical scale often involve multiple steps or components, or brittle metrics; social bias typically increases with scale in settings with ambiguous context, but this can be improved with prompting

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabilities are as yet poorly characterized. In order to inform future research, prepare for disruptive new model capabilities, and ameliorate socially harmful effects, it is vital that we understand the present and near-future capabilities and limitations of language models. To address this challenge, we introduce the Beyond the Imitation Game benchmark (BIG-bench). BIG-bench currently consists of 204 tasks, contributed by 442 authors across 132 institutions. Task topics are diverse, drawing problems from linguistics, childhood development, math, common-sense reasoning, biology, physics, social bias, software development, and beyond. BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models. We evaluate the behavior of OpenAI's GPT models, Google-internal dense transformer architectures, and Switch-style sparse transformers on BIG-bench, across model sizes spanning millions to hundreds of billions of parameters. In addition, a team of human expert raters performed all tasks in order to provide a strong baseline. Findings include: model performance and calibration both improve with scale, but are poor in absolute terms (and when compared with rater performance); performance is remarkably similar across model classes, though with benefits from sparsity; tasks that improve gradually and predictably commonly involve a large knowledge or memorization component, whereas tasks that exhibit "breakthrough" behavior at a critical scale often involve multiple steps or components, or brittle metrics; social bias typically increases with scale in settings with ambiguous context, but this can be improved with prompting.Comment: 27 pages, 17 figures + references and appendices, repo: https://github.com/google/BIG-benc