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

Phosphorylation regulating the ratio of intracellular CRY1 protein determines the circadian period

The core circadian oscillator in mammals is composed of transcription/translation feedback loop in which cryptochrome (CRY) proteins play critical roles as repressors of their own gene expression. Although post-translational modifications such as phosphorylation of CRY1, are crucial for circadian rhythm, little is known about how phosphorylated CRY1 contributes to the molecular clockwork. To address this, we created a series of CRY1 mutants with single amino acid substitutions at potential phosphorylation sites and performed a cell-based, phenotype-rescuing screen to identify mutants with aberrant rhythmicity in CRY deficient cells. We report 10 mutants with an abnormal circadian period length, including long period (S280D and S588D), short period (S158D, S247D, T249D, Y266D, Y273D, and Y432D), and arrhythmicity (S71D and S404D). When expressing mutated CRY1 in HEK293 cells, we show that most of mutants (S71D, S247D, T249D, Y266D, Y273D, and Y432D) exhibited reduction in repression activity compared with wild-type CRY1 (WT), whereas other mutants had no obvious change. Correspondingly, these mutants also showed differences in protein stability and cellular localization. We show that most of mutants are more stable than WT, except S158D, T249D, and S280D. Although the characteristics of the 10 mutants are various, they all impair the ratio balance of intracellular CRY1 protein. Thus, we conclude that the mutations caused distinct phenotypes most likely through the ratio of functional CRY1 protein in cells

Long-term in vivo recording of circadian rhythms in brains of freely moving mice.

Endogenous circadian clocks control 24-h physiological and behavioral rhythms in mammals. Here, we report a real-time in vivo fluorescence recording system that enables long-term monitoring of circadian rhythms in the brains of freely moving mice. With a designed reporter of circadian clock gene expression, we tracked robust Cry1 transcription reporter rhythms in the suprachiasmatic nucleus (SCN) of WT, Cry1-/- , and Cry2-/- mice in LD (12 h light, 12 h dark) and DD (constant darkness) conditions and verified that signals remained stable for over 6 mo. Further, we recorded Cry1 transcriptional rhythms in the subparaventricular zone (SPZ) and hippocampal CA1/2 regions of WT mice housed under LD and DD conditions. By using a Cre-loxP system, we recorded Per2 and Cry1 transcription rhythms specifically in vasoactive intestinal peptide (VIP) neurons of the SCN. Finally, we demonstrated the dynamics of Per2 and Cry1 transcriptional rhythms in SCN VIP neurons following an 8-h phase advance in the light/dark cycle

Long-term in vivo recording of circadian rhythms in brains of freely moving mice.

Endogenous circadian clocks control 24-h physiological and behavioral rhythms in mammals. Here, we report a real-time in vivo fluorescence recording system that enables long-term monitoring of circadian rhythms in the brains of freely moving mice. With a designed reporter of circadian clock gene expression, we tracked robust Cry1 transcription reporter rhythms in the suprachiasmatic nucleus (SCN) of WT, Cry1-/- , and Cry2-/- mice in LD (12 h light, 12 h dark) and DD (constant darkness) conditions and verified that signals remained stable for over 6 mo. Further, we recorded Cry1 transcriptional rhythms in the subparaventricular zone (SPZ) and hippocampal CA1/2 regions of WT mice housed under LD and DD conditions. By using a Cre-loxP system, we recorded Per2 and Cry1 transcription rhythms specifically in vasoactive intestinal peptide (VIP) neurons of the SCN. Finally, we demonstrated the dynamics of Per2 and Cry1 transcriptional rhythms in SCN VIP neurons following an 8-h phase advance in the light/dark cycle

Structural Study of mCRY2: A Circadian Rhythm Regulator

A circadian clock is a 24 hour biological rhythm that regulates physiological, psychological and behavioral processes in living organisms. Understanding the regulation mechanism of such circadian rhythms can have great impact in certain diseases such as sleeping disorders and cancers. There are many genes regulating circadian rhythms in different species. Cryptochromes (CRY) are photosensory receptors mediating light regulation of growth and development in certain species. Mouse cryptochrome protein mCRY2 has been found to encode a blue light photoreceptor and is important for mice circadian rhythm. The main goal of the project is to determine the atomic structure of mCRY2, via X-ray crystallography. The mCRY2 gene will be cloned into a vector (pET-DEST42) and expressed in bacterial E.Coli strain BL21 (DE3). Expressed protein will be purified using chromatography and other biochemistry methods. Purified protein will be used to screen to obtain crystals for X-ray diffraction. The mCRY2 gene has been isolated by polymerase chain reactions and is ready to be ligated into the vector. The atomic structure of mCRY2 obtained from this project will facilitate our understanding of its function and also allow prediction of its role in mammalian circadian clocks. Furthermore, the results will guide future mutagenesis and biochemistry studies

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