The NRON complex controls circadian clock function through regulated PER and CRY nuclear translocation

Post-translational regulation plays a central role in the circadian clock mechanism. However, nucleocytoplasmic translocation of core clock proteins, a key step in circadian timekeeping, is not fully understood. Earlier we found that the NRON scaffolding complex regulates nuclear translocation of NFAT and its signaling. Here, we show that components of the NRON complex also regulate the circadian clock. In peripheral cell clock models, genetic perturbation of the NRON complex affects PER and CRY protein nuclear translocation, dampens amplitude, and alters period length. Further, we show small molecules targeting the NFAT pathway alter nuclear translocation of PER and CRY proteins and impact circadian rhythms in peripheral cells and tissue explants of the master clock in the suprachiasmatic nucleus. Taken together, these studies highlight a key role for the NRON complex in regulating PER/CRY subcellular localization and circadian timekeeping

The Local Edge Machine: inference of dynamic models of gene regulation

We present a novel approach, the Local Edge Machine, for the inference of regulatory interactions directly from time-series gene expression data. We demonstrate its performance, robustness, and scalability on in silico datasets with varying behaviors, sizes, and degrees of complexity. Moreover, we demonstrate its ability to incorporate biological prior information and make informative predictions on a well-characterized in vivo system using data from budding yeast that have been synchronized in the cell cycle. Finally, we use an atlas of transcription data in a mammalian circadian system to illustrate how the method can be used for discovery in the context of large complex networks.Department of Applied Mathematic

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding ‘big data’ that is conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

PSMD11 modulates circadian clock function through PER and CRY nuclear translocation.

The molecular circadian clock is regulated by a transcriptional translational feedback loop. However, the post-translational control mechanisms are less understood. The NRON complex is a large ribonucleoprotein complex, consisting of a lncRNA and several proteins. Components of the complex play a distinct role in regulating protein phosphorylation, synthesis, stability, and translocation in cellular processes. This includes the NFAT and the circadian clock pathway. PSMD11 is a component of the NRON complex and a lid component of the 26S proteasome. Among the PSMD family members, PSMD11 has a more specific role in circadian clock function. Here, we used cell and biochemical approaches and characterized the role of PSMD11 in regulating the stability and nuclear translocation of circadian clock proteins. We used size exclusion chromatography to enrich the NRON complex in the cytosolic and nuclear fractions. More specifically, PSMD11 knockdown affected the abundance of PER2 and CRY2 proteins and the nuclear translocation of CRY1. This changed the relative abundance of CRY1 and CRY2 in the nucleus. Thus, this work defines the role of PSMD11 in the NRON complex regulating the nuclear translocation of circadian repressors, thereby enabling cellular circadian oscillations

Role for LSM genes in the regulation of circadian rhythms

Growing evidence suggests that core spliceosomal components differentially affect RNA processing of specific genes; however, whether changes in the levels or activities of these factors control specific signaling pathways is largely unknown. Here we show that some SM-like (LSM) genes, which encode core components of the spliceosomal U6 small nuclear ribonucleoprotein complex, regulate circadian rhythms in plants and mammals. We found that the circadian clock regulates the expression of LSM5 in Arabidopsis plants and several LSM genes in mouse suprachiasmatic nucleus. Further, mutations in LSM5 or LSM4 in Arabidopsis, or down-regulation of LSM3, LSM5, or LSM7 expression in human cells, lengthens the circadian period. Although we identified changes in the expression and alternative splicing of some core clock genes in Arabidopsis lsm5 mutants, the precise molecular mechanism causing period lengthening remains to be identified. Genome-wide expression analysis of either a weak lsm5 or a strong lsm4 mutant allele in Arabidopsis revealed larger effects on alternative splicing than on constitutive splicing. Remarkably, large splicing defects were not observed in most of the introns evaluated using RNA-seq in the strong lsm4 mutant allele used in this study. These findings support the idea that some LSM genes play both regulatory and constitutive roles in RNA processing, contributing to the fine-tuning of specific signaling pathways.Fil: Perez Santangelo, Maria Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquimicas de Buenos Aires; Argentina. Fundación Instituto Leloir; ArgentinaFil: Mancini, Estefania. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquimicas de Buenos Aires; Argentina. Fundación Instituto Leloir; ArgentinaFil: Francey, Lauren J.. University of Pennsylvania. Department of Systems Pharmacology and Translational Therapeutics; Estados UnidosFil: Schlaen, Rubén Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquimicas de Buenos Aires; Argentina. Fundación Instituto Leloir; ArgentinaFil: Chernomoretz, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquimicas de Buenos Aires; Argentina. Fundación Instituto Leloir; ArgentinaFil: Hogenesch, John B.. University of Pennsylvania. Department of Systems Pharmacology and Translational Therapeutics; Estados UnidosFil: Yanovsky, Marcelo Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquimicas de Buenos Aires; Argentina. Fundación Instituto Leloir; Argentin