Systems Biology of Mammalian Circadian Clocks
H.R. UEDA
Laboratory for Systems Biology and Functional Genomics Unit,
Center for Developmental Biology, Riken, Kobe, Hyogo 650-0047, Japan

Systems Biology is a natural extension of molecular biology and can be defined as biology after identification of key gene(s).
Systems-biological research is hence seen as a multistage process, beginning with the comprehensive identification and quantitative analysis of individual system components and their networked interactions and leading to the ability to control existing systems toward the desired state and design new ones based on an understanding of structure and underlying dynamical
principles. In this chapter, we take mammalian circadian clocks as a model system and describe systems-biologicalapproaches, including the identification of clock-controlled genes, clock-controlled cis elements, and clock transcriptional circuits driven by functional genomics; the parameter change of clock components followed by quantitative measurement; andthe dynamic and quantitative perturbation of the clock and its application to one of the fundamental but yet-unsolved questions: singularity behavior of clocks. As perspective for systems-biological investigations, we also introduce the system-level
dynamical questions related to the core of clocks, including delay, nonlinearity, temperature-compensation and synchronization of mammalian circadian oscillator(s), and the system-level information problems related to clocks in the environment,
including the internal representation of light change through perfect adaptation and internal representation of day length
through photoperiodism in mammals.

INTRODUCTION
Systems Biology as “Biology after Identification”
Recent large-scale efforts in genome sequencing,expression profiling, and functional screening have produced an embarrassment of riches for life science
researchers, and biological data can now be accessed inquantities that are orders of magnitude greater than wereavailable even a few years ago. The growing need forinterpretation of data sets, as well as the accelerating
demand for their integration to a higher-level understanding of life, has set the stage for the advent of systems biology (Kitano 2002a,b), in which biological processes andphenomena are approached as complex and dynamic systems. Systems biology is a natural extension of molecularbiology and can be defined as “biology after identificationof key gene(s).” We see systems-biological research as amultistage process, beginning with the comprehensive
identification and quantitative analysis of individual system components and their networked interactions andleading to the ability to control existing systems toward
the desired state and design new ones based on an understanding of structure and underlying dynamical principles(Fig. 1).
Mammalian Circadian Clock as a Model System
We have taken the mammalian circadian clock as an
initial model system that exhibits system-level dynamicaland structural properties in order to develop researchstrategies and technologies for studies of complex anddynamic biological systems. The mammalian circadianclock consists of complexly integrated feedback and feedforward loops (Reppert and Weaver 2002) and also
exhibits well-defined dynamical properties (Dunlap et al.
2004), including (1) endogenous oscillations of an

approximately 24-hour period, (2) entrainment to external
environmental changes (temperature and light cycle), (3)temperature-compensation over a wide range of temperature, and (4) synchronization of multiple cellular clocks
despite the inevitable molecular noise. All of these
dynamical properties would be difficult to elucidate without utilizing such system-level approaches. In addition to
its advantage as a basic model system for systems-biological research, the function of the circadian clock is intimately involved in the control of metabolic andphysiological processes (Panda et al. 2002; Reppert andWeaver 2002), and its dysregulation is associated with theonset and development of numerous human diseases,
including sleep disorders, depression, and dementia. An
improved understanding at the systems level promises toprovide biomedical and clinical investigators with a powerful new arsenal for attacking these conditions.
Development of Systems-BiologicalApproaches and Their Application to Clocks
Attempts to elucidate the design principles of complex
and dynamic biological systems such as the mammalian
circadian clock may require (1) identification of wholenetwork structure through comprehensive (genome-wide)
screening (system identification), (2) prediction and validation to derive the design principle through the accurate
measurement of network behaviors (system analysis), (3)repair and control of network state toward the desired
state through the precise perturbation of its components(system control) and ultimately, (4) reconstruction anddesign of new systems based on the design principles
derived from the identified structure and observed
dynamics of the original network (system design). To
develop these systems-biological approaches, we havefocused mainly on the development and evaluation ofCold Spring Harbor Symposia on Quantitative Biology, Volume LXXII. © 2007 Cold Spring Harbor Laboratory Press 978-087969823-2

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Figure 1. Systems biology. Systems-biological research starts with comprehensive identification (upper left panel). In this step, individual system components and their networked interactions are comprehensively identified. In the second step, to derive the design principle of a target system, the behavior of the system is predicted and validated through an accurate measurement with perturbations (upper
right panel). An understanding of the design principle of the system is essential to derive the method of controlling the system toward
the desired state (lower left panel). Finally, the level of understanding is confirmed by reconstruction of the system (lower right panel).

Identification of Clocks

Development of high-throughput technologies has also
assisted in the efficient use of these resources. These
genome-wide resources and technologies and genomeassociated information currently allow us to comprehensively identify system components of interest (system
identification).
Circadian clocks of multicellular organisms consist ofcomplex integrated regulatory loops with positive or negative regulators known as clock genes (Wuarin and
Schibler 1990; King et al. 1997; Zylka et al. 1998; van der
Horst et al. 1999; Vitaterna et al. 1999; Bunger et al.
2000; Lowrey et al. 2000; Bae et al. 2001; Mitsui et al.
2001; Reick et al. 2001; Zheng et al. 2001; Honma et al.
2002; Preitner et al. 2002; Sato et al. 2004). The transcriptional regulation network of these genes forms a circadian clock oscillator, which is known to control output
genes and to affect physiological and metabolic processes(Panda et al. 2002; Reppert and Weaver 2002). Althoughsome transcriptional regulations of identified clock genes
have been the subject of previous studies, a system-level
understanding of circadian clocks remains to be elucidated. In this section, we provide results of our system
identification of mammalian circadian clocks (Ueda et al.
2002c, 2005).

Following the completion of genome projects for
species such as mouse and human, genome-wide
resources such as small interfering RNA (siRNA) or
cDNA libraries have undergone considerable expansion.

Identification of the mammalian clock circuit. The
mammalian circadian master clock is primarily locatedin the suprachiasmatic nucleus (SCN) (Reppert andWeaver 2002). Transcript analyses have indicated thattechnologies and strategies. For each of these processes,
we have been able to report several strategies and technologies as well as their application to specific questions
in mammalian circadian clocks. This has included theidentification of clock-controlled genes, clock-controlled
cis elements, and clock transcriptional circuits driven byfunctional genomics (Ueda et al. 2002c, 2005) in system
identification, parameter change of clock components byquantitative measurement (Sato et al. 2006) in systemanalysis, dynamic and quantitative perturbation of clock
and its application to one of the fundamental but yetunsolved questions, and singularity behavior of clocks(Ukai et al. 2007) in system control. As for the effort ofsystem design, we recently initiated our current project onin cellulo and in vitro reconstruction of mammalian circadian circuits. In the following sections, we describe indetail these strategies and/or technologies developed foreach stage of systems-biological research, in addition totheir application to the specific question of mammalian
circadian clocks.
SYSTEMS-BIOLOGICAL APPROACHES

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circadian clocks are not restricted to the SCN but arefound in several tissues (Yamazaki et al. 2000) including liver and cultured fibroblast cells such as Rat-1(Balsalobre et al. 1998; Yagita et al. 2001) or NIH-3T3(Akashi and Nishida 2000) cells. The mechanisms
underlying circadian rhythms are also known to be conserved across species (Dunlap et al. 2004). At the basic
core of the clock lies a transcriptional/translational feedback loop (Gekakis et al. 1998; Kume et al. 1999;
Shearman et al. 2000), whose primary components are
known as “clock genes” (Wuarin and Schibler 1990;
King et al. 1997; Zylka et al. 1998; van der Horst et al.
1999; Vitaterna et al. 1999; Bunger et al. 2000; Lowrey
et al. 2000; Bae et al. 2001; Mitsui et al. 2001; Reick et
al. 2001; Zheng et al. 2001; Honma et al. 2002; Preitneret al. 2002; Sato et al. 2004). For example, in the mousesystem, the transcription factors CLOCK and BMAL1
proteins dimerize and directly and indirectly activatetranscription of the Per and Cry genes through E-box
elements (5′-CACGTG-3′) (Gekakis et al. 1998; Kumeet al. 1999). The PER and CRY proteins accumulate in
the cytosol and are then translocated following phosphorylation into the nucleus where they inhibit the activity of CLOCK and BMAL1 (Reppert and Weaver 2002).
The turnover of the inhibitory PER and CRY proteinsleads to a new cycle of activation by CLOCK and
BMAL1 via E-box elements. Despite the reporting ofmany transcriptional regulations of each gene, however,an overview of the circadian clock core network remains
to be put forward.
Complicated networks cannot be elucidated without
access to both (1) comprehensive identification of network circuits and (2) accurate measurement of system
dynamics. In a previous attempt to comprehensively
identify the circadian clock core network, we first quantitatively and comprehensively measured genome-wide
gene expression using a high-density oligonucleotide
probe array (Lipshutz et al. 1999) and identified genes
showing circadian oscillation with characteristic
expression patterns through biostatistics (Fig. 2). The
second step involved comprehensively determining thetranscription start sites (TSSs) (Suzuki et al. 2001) andconserved noncoding regions to construct a genomewide promoter/ enhancer database. Using these data, wepredicted that there was a relationship between expression patterns of identified genes and DNA regulatory
elements on their promoter/enhancer regions. We foundthat clock-controlled elements (CCEs), E boxes (5′CACGTG-3′; Hogenesch et al. 1998), E′ boxes (5′CACGTT-3′; Ueda et al. 2005; Yoo et al. 2005), D
boxes (5′ -TTATG[C/T]AA-3′; Falvey et al. 1996), or
Rev-response elements (RREs) (5′-[A/T]A[A/T]NT[A/G]GGTCA-3′; Harding and Lazar 1993) are distributed throughout the oscillatory genes.
To determine the role of these elements in the circadianclock, we utilized a cell culture system with which we canmonitor circadian rhythms in transcriptional dynamics
using a destabilized luciferase (dLuc) reporter driven byclock-controlled promoters (Fig. 3A). In this cell culture
system—named “in cellulo cycling assay”—we transiently transfected reporter constructs into cultured Rat-1

cells and stimulated them with dexamethasone and measured their bioluminescences. Dexamethasone was administrated to induce macroscopic circadian oscillations in thecultured cells. Through the genome-wide searchingdescribed above, we found CCEs on 16 clock/clock-controlled gene promoter/enhancers. Then, using the in cellulo cycling assay system, we were able to reveal thatfunctionally and evolutionary conserved E/E′ boxes arelocated on noncoding regions of nine genes (Per1, Per2,
Cry1, Dbp, Rorγ, RevErbAα/Nr1d1, RevErbAβ/Nr1d2,
Dec1/Bhlhb2, and Dec2/Bhlhb3), D boxes on those of
seven genes (Per1, Per2, Per3, RevErbAα, RevErbAβ,Rorα, and Rorβ), and RREs on those of six genes(Bmal1/Arntl, Clock, Npas2, Cry1, E4bp4/Nfil3, andRorγ). On the basis of this functional and conserved transcriptional regulatory mechanism, we succeeded in drawing transcriptional circuits underlying mammalian
circadian rhythms (Fig. 3B) (Ueda et al. 2005).
Our analysis further suggested that regulation of E/E′
boxes is the topological vulnerability point in mammalian
circadian clocks. We functionally verified this concept
using in cellulo cycling assay system (Fig. 3C). Overexpression of repressors of E/E′ box regulation (CRY1;
Kume et al. 1999), RRE regulation (REVERBAα; Preitneret al. 2002; Ueda et al. 2002c), or D-box regulation(E4BP4; Mitsui et al. 2001) affected circadian rhythmicity
in Per2 or Bmal1 promoter activity. The effects were different, however, between each repressor, and the severest
effect was observed when the E/E′ box was attacked. Such
different modes of effects cannot be explained by mere
quantitative differences in the strength of these three
repressors, indicating that there is some qualitative difference between E/E′ box, D-box, and RRE regulation in circadian rhythmicity (Ueda et al. 2005).
Analysis of Clocks
To derive the design principles of a system of interest,
it is important to validate the behavior of a predicted system through an accurate measurement with several typesof perturbations (system analysis). In our efforts to identify the circadian clock system, we have succeeded in
drawing the circadian transcriptional circuits and revealed
the topological importance of the morning element, Ebox. In this section, we describe our effort to validate thehypothesis that transcriptional feedback repression
through the E box is required for mammalian clock function. In this study, we collaborated with Dr. John B.
Hogenesch’s and Dr. Steve A. Kay’s groups to change themolecular parameter for feedback repression by functional genomics and then tested the cellular phenotype
caused by this parameter change by our in cellulo cycling
assay system. Through this study, we have demonstrated
the necessity of transcriptional repression for circadianclock function (Sato et al. 2006).
Negative feedback as the heart of the transcriptional
circuit in mammalian clocks. Circadian clocks have been
proposed as consisting of autoregulatory loops in whichtranscriptional feedback and regulated protein turnover
are used to maintain a 24-hour periodicity (Dunlap 1999;

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Figure 2. (A) Strategy for identification of clock-controlled elements (CCEs). Gene expression information was obtained by performing comprehensive expression profiling (left panel). Through statistical analysis, genes with a special characteristic pattern ofexpression (circadian oscillation) were selected (right panel, oscillatory genes are indicated by their color). DNA regulatory elements for specific issue (i.e., expression timing) were predicted by combining expression pattern information and transcriptional
regulatory element information from promoter regions. (B) Genome-wide expression profiles in mouse central (SCN, left panel)and peripheral (liver, right panel) clocks. Total RNA were extracted every 4 hours during light/dark cycles (LD) or constant darkness (DD) over 2 days and used to determine genome-wide gene expression profiles with an Affymetrix mouse high-density
oligonucleotide probe array. Data were normalized so that the average signal intensity and standard deviation over 12-point timecourses were 0.0 and 1.0, respectively. Columns represent time points, and rows represent genes that were organized by peak time.
Colors in descending order from red to black to green represent the normalized data. From the obtained data, we identified a set ofgenes rhythmically expressed under both LD and DD. We classified 101 genes in the SCN and 393 genes in the liver as “significantly rhythmic under both LD and DD.” (C) Temporal expression profiles of transcription factors in the SCN (upper panel) andliver (lower panel) under DD conditions. Relative mRNA levels under DD conditions of the indicated genes were measured withquantitative polymerase chain reaction (Q-PCR) assay, in which GAPDH expression was used as an internal control. Data were normalized so that the average copy number (Q-PCR) over a 12-point time course was 1.0. Circadian expression of transcription factors having functional and evolutionary conserved E boxes (Dbp, Dec1, and Dec2), both E boxes/E′ boxes and D boxes (Per1, Per2,
RevErbAα, and RevErbAβ), D boxes (Per3, Rorα, and Rorβ), RREs (Bmal1, Clock, Npas2, and E4bp4), both E boxes/E′ boxes andRREs (Cry1 and Rorγ) on their noncoding regions. Clock and Rorγ were constitutively expressed in the SCN. (Modified from Ueda
et al. 2002c, 2005.)

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Figure 3. (A) Schematic overview of the experiment. Cultured mammalian cells (Rat-1) were transfected with dLuc under the regulation of CCE and SV40 basic promoter. The circadian change of bioluminescence was monitored by a PMT detector over several
days (upper panel). Representative circadian rhythms of bioluminescence from wild-type CCE fused to the SV40 basic promoter
driving a dLuc reporter. The circadian bioluminescence phase from the Per2 promoter and that of the Bmal1 promoter are marked byyellow and purple lines, respectively (bottom panels). (B) Schematic representation of the transcriptional network of the mammalian
circadian clock. (Ellipsoids) Genes; (rectangles) CCEs. Transcriptional-translational activation and repression are depicted as gray,green, and red lines, respectively. (C) Effect of repression on each CCEs. The E/E′ boxes, D box, and RRE are repressed by overproduction of CRY1, E4BP4, and REVERBAα, respectively. The consequences of those repressions were monitored by Per2-dLuc(upper panel) and Bmal1-dLuc (lower panel). (dLuc) Destabilized luciferase; (CCE) clock-controlled elements; (PMT) photomultiplier tube. (Modified from Ueda et al. 2005.)

Young and Kay 2001; Reppert and Weaver 2002). The
universal necessity for transcriptional feedback repression, however, arose as a question mainly from recent
studies about the cyanobacterial circadian rhythms inwhich repression was shown not to be necessary(Nakajima et al. 2005; Tomita et al. 2005). Circadianfeedback repression in mammals is believed to be mediated by CRYPTOCHROME (CRY1, CRY2) (Kume et al.
1999; van der Horst et al. 1999; Vitaterna et al. 1999) andPERIOD (PER1 and PER2) (Tei et al. 1997; Zheng et al.
1999, 2001) proteins. CRY and PER proteins are hypothesized to autoregulate their own expression by repressing

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the heterodimeric complex of the basic helix-loop-helix(bHLH) PERARNT-SIM (PAS) domain transcriptional
activators CLOCK and BMAL1, which bind to E-box elements in the CRY (Etchegaray et al. 2003) and PER(Gekakis et al. 1998; Ueda et al. 2005; Yoo et al. 2005)
promoters. However, direct evidence for the requirementof CRY-mediated repression of CLOCK/BMAL1 transcriptional activity in the maintenance of circadian clockfunction has yet to be presented. Here, in a fruitful collaboration with the J.B. Hogenesch and the S.A. Kay
groups, we have successfully shown that feedback repression is actually required for mammalian circadian clockfunction (Sato et al. 2006).
To determine the requirement of feedback repression incircadian clock function, we sought to identify the
CLOCK alleles that were insensitive to CRY1 repression
but maintained normal transcriptional activity. Our collaborative partners first generated a library of approximately 6000 random point mutations of human alleles forboth CLOCK and BMAL1 and then screened clones individually in cell-based reporter assays with wild-type
Bmal1 cDNA and a Per1 promoter-luciferase (Per1-Luc)
construct (Gekakis et al. 1998) in the presence of cotransfected Cry1. Of the CLOCK and BMAL1 clones
screened, several reproducibly maintained threefold or
greater reporter activity in the presence of CRY1 compared with wild-type alleles. Notably, these clones
demonstrated transcriptional activities similar to those ofwild type in the absence of cotransfected Cry1, suggesting that these mutations do not cause overt alterations in
the heterodimerization, nuclear localization, DNA-binding, and trans-activation properties of the mutant
CLOCK/BMAL1 complex.
The prevailing transcriptional feedback model (Fig.
4A) predicts that impairment of CRY-mediated repression should have marked effects on circadian expressionof the Per genes. This notion is supported by in vivo
observations that expression of Per1 and Per2 is constitutively elevated in Cry1/Cry2 double-knockout mice
(Okamura et al. 1999; Vitaterna et al. 1999). To determine
whether these mutations in CLOCK and BMAL1 cause
phenotypic changes in circadian gene expression, we performed an in cellulo cycling assay (Ueda et al. 2002b,
2005) (see also above, Identification of Clocks). Mouse
NIH-3T3 cells were transfected with plasmids harboring
destabilized luciferase (dLuc) driven by Per2 or SV40
basic promoters along with the BMAL1 and CLOCK
mutant allele and then monitored using the in cellulo
cycling assay (Fig. 4B, left). Cotransfection of wild-type
CLOCK and BMAL1 did not substantially alter rhythmicity compared with empty vector transfection, as theirperiod lengths were 21.4 hours ±0.4. In contrast, whencompared with wild-type CLOCK/BMAL1, transfectionof either of CLOCK or BMAL1 mutant alleles resulted in
substantial impairment of circadian rhythmicity after one
or two cycles of oscillations. Notably, cotransfection of
the CRY-insensitive mutant CLOCK and BMAL1
together resulted in the loss of circadian Per2 promoter
activity. We were therefore able to demonstrate that thetranscriptional repression of CLOCK/BMAL1 by CRY
was required for circadian E-box activity.

In addition to Per and Cry, the rhythmic expression of
Bmal1 mRNA is also under circadian clock regulation(Shearman et al. 2000). The Bmal1 promoter used in thisstudy, however, does not have E-box sites but instead
contains RRE (Preitner et al. 2002; Ueda et al. 2002c),
whose activities are reciprocally controlled by the rhythmically expressed transcriptional repressor REVERBAα(Preitner et al. 2002) and activator RORα (Sato et al.
2004). As an additional test for circadian clock function,
we examined the effects of mutant CLOCK and BMAL1
on rhythmic RRE activity by in cellulo cycling assays
with a Bmal1-dLuc reporter. Similar to the results with
the Per2-dLuc reporter, transfection of single CLOCK or
BMAL1 mutants resulted in the decreased amplitude ofcycling of Bmal1-dLuc activity compared with wild-type
CLOCK/ BMAL1 transfection. Moreover, this decreasein cycling amplitude was further exacerbated upon
cotransfection of the double-mutant heterodimer (Fig.
4B, right). These results indicate that transcriptional
repression of CLOCK/BMAL1 by CRY is also requiredfor circadian BMAL1 expression through RRE, which isdependent on the transcriptional, translational, and posttranslational actions of endogenous cellular factors.
Arrhythmic Per2 expression seen from a population ofcells expressing the double-mutant CLOCK/BMAL1
complex may be due to the disruption of oscillator function or a lack of synchrony between individual rhythmic
cells. To address these possibilities, we measured quantitative imaging of Per2-dLuc reporter activity from individual NIH-3T3 cells by using an approach similar to thatused in analyzing Bmal1 reporter rhythms from single
cells (Welsh et al. 2004). As with the whole-well assays,
the median reporter activity for the population of imaged
individual cells coexpressing wild-type CLOCK/BMAL1
oscillated rhythmically (Fig. 4C, left). In contrast, thepopulation of individual Clock/Bmal1 mutant cells (Fig.
4C, right) was visibly arrhythmic. Individual reporter
activities from single wild-type cells were rhythmic, as
expected, whereas individual Clock/Bmal1 doublemutant cells showed arrhythmic reporter activities. These
differences in activity patterns were evaluated by two
independent statistical methods that score the circadianrhythmicity of experimental time-course data.
This is the first study that shows functional necessity
for feedback repression in the mammalian circadianclock. Proof of this necessity is important, as recent studies of the cyanobacterial clock found that circadian oscillations in protein phosphorylation can be maintained in
the absence of transcriptional feedback repression in vivo
(Tomita et al. 2005) and with purified proteins in vitro(Nakajima et al. 2005). We therefore sought to formallytest the requirement of CRY-mediated transcriptional
feedback repression in mammalian circadian clock function by developing and implementing a new unbiased cellular genetics approach that uses robust mutagenesis
techniques and mammalian cell-based screening. Ourdata presented here provide direct evidence that CRYmediated feedback repression of the CLOCK/BMAL1
complex is required for mammalian clock function.
Although it is likely that the mammalian clock is governed by a combination of both transcriptional and non-

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Figure 4. (A) Schematic representation of the transcriptional network of the mammalian circadian clock. (Ellipsoids) Genes; (rectangles) CCE. Transcriptional-translational expression, activation and repression are depicted as gray, green, and red lines, respectively.
(B) Coexpression of CLOCK/BMAL1 mutant heterodimers that are insensitive to CRY repression ablates circadian E-box and RRE
activities in NIH-3T3 cells. Plasmids expressing Flag-tagged Clock and Bmal1 alleles were transiently cotransfected with the Per2dLuc reporter plasmid into NIH-3T3 cells. (Left panel) Per2 promoter activities in NIH-3T3 cells transfected with single or double
CRY1-insensitive Clock and Bmal1 mutants were monitored over 5 days. (Right panel) Bmal1 promoter activities in NIH-3T3 cells
transfected with single or double CRY-insensitive mutants of Clock and Bmal1 were monitored over 6 days. All reporter activities werenormalized such that the median wild-type luciferase activity over the time course was 100%. (C) Coexpression of CLOCK/BMAL1
mutant heterodimers impairs circadian rhythmicity in individual cells. Per2-Luc reporter activities from individual NIH-3T3 cells (n= 133) transfected with Flag-tagged wild-type CLOCK/BMAL1 or double-mutant Clock-MT/Bmal1-MT were monitored over 3 days.
Reporter activities from each wild-type or double-mutant cells were normalized such that the maximum bioluminescence value was
set to 100% for each panel. The mean reporter activity for all analyzed single cells at each time point is indicated by a black line.
(Modified from Sato et al. 2006.)

transcriptional feedback mechanisms, any residual circadian properties that remain upon uncoupling of transcriptional feedback are insufficient to maintain circadiantranscriptional output and molecular clock function.
Finally, we predict that the application of cellular genetics technology will have a significant impact on mammalian biology as similar approaches have had on
prokaryotic and yeast biology.

Control of Clocks
System control aims to regulate the target system
toward the desired state through the precise perturbationof its components. To achieve this, it is necessary todevelop an assay system that can be controlled withdynamic and quantitative perturbation.
The circadian clock is known to be entrainable by

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external cues such as light. The light information is transmitted to the circadian clock through sensing mechanisms
containing photoreceptors, and as a result of light pulse,
the clock system shows a drastic change of its dynamics.
In this section, we show the success of control of theoscillating clock system in individual cultured cells via
artificial light-sensing mechanisms. We also applied thisphotoperturbation system to one of the long-standing andunsolved biological phenomena known as the singularity
behavior of circadian clocks (Ukai et al. 2007).
Singularity behaviors of circadian clocks. Circadianclocks exhibit various dynamic properties, making themdifficult to elucidate without quantitative perturbation andprecise measurement of their dynamics. One of the mostfundamental but yet-unsolved dynamic properties of circadian clocks is singularity behavior, in which robust circadian rhythmicity can be abolished after a certain criticalstimulus, such as light and temperature pulses applied at
the appropriate timing and strength. Since the first reportof singularity behavior in Drosophila pseudoobscura by
Arthur T. Winfree (1970), circadian clock singularities
have been experimentally observed in various organisms
including unicells such as Gonyaulax (Taylor et al. 1982),
Euglena (Malinowski et al. 1985), Chlamydomonas(Johnson and Kondo 1992), fungi (Huang et al. 2006),
insects (Winfree 1980), plants (Engelmann et al. 1978;
Covington et al. 2001), and mammals (Jewett et al. 1991;
Honma and Honma 1999), suggesting that this behavior isa shared property of an extremely broad range of circadian clocks (Dunlap et al. 2004).
Although singularity behavior has been widely
observed, little is known about the underlying mechanisms. Since such behaviors were experimentallyobserved at the multicell level (i.e., the collective behavior of unicells or the physiological or locomoter activityof a multicellular organisms), two alternative single-celllevel mechanisms have been proposed to explain theircollapse to singularity: (1) arrhythmicity of individual
clocks (Fig. 5A) or (2) desynchronization of individual
rhythmically oscillating clocks (Fig. 5B) (Winfree 1975,1980). In the former mechanism, individual clocks
become arrhythmic, i.e., the amplitude of the individual
cells is substantially attenuated by the application of thecritical light pulse. In contrast, in the latter mechanism ofdesynchronization, the phases of individual clocks arediversified by the critical light pulse. Although bothmechanisms can explain substantial suppression of themulti-cell-level amplitude of circadian rhythm, there is afundamental difference in dynamical properties between
the two in that the oscillations of individual cells are
impaired in the former, whereas individual cells maintaintheir oscillations in the latter. Importantly, although many
researchers have observed multi-cell-level singularity
behavior in various organisms, it remains elusive whether
arrhythmicity or desynchronization of individual clocks
underlies the singularity behavior of circadian clocks.
Determination of the underlying mechanism for singularity behaviors of circadian clocks may require adjustable
perturbation, because the ability of a critical stimulus todrive circadian clocks into singularity depends on its tim-

Figure 5. (A–B) Schematic diagrams of two alternative singlecell-level mechanisms for multi-cell-level singularity behavior.
Arrhythmicity (A) and desynchronization (B) of individual cellular clocks are indicated. (C) Synthetic implementation of photoresponsiveness within mammalian clock cells. Schematic
representation of melanopsin-dependent photoresponsive NIH3T3 cells and the known Gq signaling pathway. (Modified from
Ukai et al. 2007.)

ing and strength. Various stimuli, such as reagents andtemperature, have been reported to directly reset mammalian cellular clocks (Balsalobre et al. 1998, 2000a,b;
Akashi and Nishida 2000; Yagita and Okamura 2000;
Yagita et al. 2001; Brown et al. 2002; Hirota et al. 2002;
Tsuchiya et al. 2003, 2005). Unfortunately, it is difficult,but not impossible, for these factors to achieve the requisite flexibility in timing and strength. In contrast to perturbations achieved by the use of reagents or temperaturechange, photoperturbation provides an ideal range ofadjustability in timing and strength. Although most mammalian cells cannot sense light, recent studies have shownthat mammalian cells (Neuro-2a; HEK293) become photoresponsive following the introduction of an exogenous
G-protein-coupled photoreceptor, melanopsin (Melyan etal. 2005; Qiu et al. 2005). It was reported that photostimulation of melanopsin triggers a release of intracellular calcium mediated through the Gq-protein signaling pathway,
and, importantly, there are several reports that mammaliancellular clocks can be reset by the Gq-protein signaling
pathway involving a release of intracellular calcium(Balsalobre et al. 2000a; Tsuchiya et al. 2005). TheseSYSTEMS BIOLOGY OF CLOCKS
results suggest that melanopsin-dependent photoperturbation may enable the adjustable and quantitative perturbation of mammalian cellular clocks by changing intracellular calcium level.
To experimentally reveal the underlying mechanism of
singularity behavior of mammalian cells, we synthetically
implemented photoresponsive mammalian cells byexogenously introducing a Gq-protein-coupled photoreceptor—melanopsin in our recent study (Fig. 5C), seealso our recent study (Ukai et al. 2007). We then devised
a high-throughput monitoring system with a light-exposure unit to continuously and quantitatively monitor theeffect of photoperturbation on the state of cellular clocks.
Using this system, we revealed that a critical light pulse
drives cellular clocks into a singularity behavior in whichrobust circadian rhythmicity can be abolished after a certain stimulus. Theoretical analysis and subsequent singlecell-level observation consistently predicted and directly
proved that the desynchronization of individual cellular
clocks underlies this singularity behavior. We also constructed a theoretical framework to explain why singularity behaviors have been experimentally observed invarious organisms and proposed desynchronization as aplausible mechanism for the observable singularity of circadian clocks. Importantly, these in cellulo and in silico
findings are further supported by our in vivo observations
that desynchronization actually underlies the multi-celllevel amplitude decrease in the rat SCN induced by thecritical light pulses that can predispose organisms to transient amplitude decrease in their locomotor activity.
Historically speaking, to elucidate the underlying
mechanism of singularity behaviors, Arthur T. Winfree
and other investigaters conducted a two-pulse experimentand revealed the “unclocklike” behavior of circadianclock, in which the critical light pulse inducing the singularity behavior seemed to decrease the amplitude of circadian clock without affecting its frequency, apparently
arguing against both the simple limit-cycle model and its
resulting prediction that the arrhythmicity would underlie
the singularity behavior. To explain this “unclocklike”
behavior of circadian clock, he proposed the “clockshop”
hypothesis, in which an organism-level circadian clock
consists of multiple circadian oscillators with substantial
fluctuations, and predicted that the desynchronization ofindividual circadian oscillators would underlie the singularity behavior (multi-cell-level amplitude decrease). He
was unable to directly test this prediction, however, as
there was no way to observe single-cell-level circadianrhythmicity at that time. In our recent study (Ukai et al.
2007), his prediction on the desynchronization was
directly proved at least in the mammalian circadian system more than 30 years after he originally proposed it in
his review (Winfree 1975).
Design of Clocks
The next step is system design—reconstruction anddesign of new systems based on the design principles thathave been revealed through the efforts of a combination
strategy of system identification, system analysis, and system control. In this stage, we can validate the sufficiency

9of the hypothesis derived from the identified structure orobserved dynamics. To test the sufficiency of the designprinciples derived from the identified transcriptional circuits underlying mammalian circadian clocks (Fig. 3B),
we are trying to extend our in cellulo cycling assay system(Fig. 3A) to the “physical simulator,” with which we will
be able to implement artificial transcriptional circuits ofinterest. We are planning to use this in cellulo system toprove the sufficiency of the components we predict in thenatural circadian phase-controlling mechanism.
Alternatively, we can also take a radical and fundamental approach for system design of mammalian circadian clocks. In the next section, we introduce, as a radical
approach, our current project on the in vitro reconstruction of the mammalian circadian clock from scratch.
Reconstitution of clocks. The molecular mechanisms
underlying circadian clocks in many organisms have beenstudied for many years (Dunlap 1999; Young and Kay
2001; Reppert and Weaver 2002). Most of the molecularlevel observations in previous studies suggest that every
clock system has the translational-transcriptional negative feedback loop as a central oscillator, in which positive regulators such as BMAL1/CLOCK in mammals
directly or indirectly activate the transcription of its negative regulators such as Pers/Crys, via a cis-acting DNAelement-like E box (Gekakis et al. 1998; Kume et al.
1999; Shearman et al. 2000).
Although comprehensive studies about the molecularmechanism of clocks have been reported, the basic mechanism for the fundamental nature of circadian clocks isstill unclear. Specifically, the mechanism for autonomous
oscillation, the most fundamental mechanism of clocks,
remains to be fully understood.
Recently, these fundamental questions in eukaryotic
clocks have become evident from studies concerning thecircadian clock of cyanobacteria, known as the simplest
organism possessing a circadian clock. Although ubiquitous molecular behaviors concerning the circadian clock,such as negative feedback regulation of clock genes, circadian oscillation of accumulation of mRNA and clock
proteins, and phosphorylation of clock proteins, are also
observed in cyanobacteria, the robust circadian oscillation of the phosphorylation state of KaiC, a circadianclock protein, was reconstituted by mixing only three
cyanobacterial clock proteins and ATP in a test tube (Fig.
6) (Nakajima et al. 2005). The circadian oscillation of
KaiC phosphorylation was therefore proved to be the central oscillator of the cyanobacterial circadian clock. A
number of elegant studies about the cyanobacterial circadian clock evoked the importance of using a biochemical
approach of the circadian clock for fundamental questions, such as autonomous oscillation and temperaturecompensation.
Clock-related genes and proteins have been almost
completely identified in some model organisms such as
mammals, Drosophila, and Neurospora, as well as incyanobacteria (Dunlap 1999; Young and Kay 2001;
Reppert and Weaver 2002; Dunlap et al. 2004). In addition to the identification of clock-related components, wehave clarified the dynamic nature of circadian clocks.

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Figure 6. Biochemical approach to the fundamental questions of the circadian clock. KaiC, one of the three cyanobacterial clock proteins (KaiA, KaiB, and KaiC), has both autokinase and autophosphatase activity, and its phosphorylation state shows circadian rhythmin vivo. When three Kai proteins and ATP are mixed in a test tube, temperature-compensated KaiC phosphorylation rhythm is reconstituted (left). Because the biochemical properties of the mammalian clock proteins are limited, it is thought that the fundamental natureof the mammalian circadian clock is also dependent on these clock proteins (right). (Modified from Nakajima et al. 2005; panel on the
periodic KaiC phosphorylation is courtesy of Dr. M. Nakajima.)

These circumstances in circadian clock studies led us toreevaluate the negative feedback model of the circadianclock by biochemical methods. We have succeeded in the
purification of some clock proteins through the expression system of Escherichia coli. Furthermore, we are now
trying to characterize some basic reactions in the mammalian circadian clock, such as the enzymatic propertiesof casein kinase Iε (CKIε) (Lowrey et al. 2000) and some
protein-protein interactions. Although the mammalian
circadian clock system is more complicated than that of
cyanobacteria, we are now trying to reconstitute the mammalian circadian clock to demonstrate the essential mechanism of autonomous circadian oscillation and the otherfundamental questions.
PERSPECTIVES: SYSTEM-LEVEL QUESTIONSIn the previous sections, we introduced a series of systems-biological approaches as well as their application to
the specific questions such as singularity behaviors ofmammalian circadian clocks. This has provided us withthe groundwork to take a further step forward. It is hightime to fully integrate these approaches to realize a system-level understanding of the mammalian circadianclock. The success of these approaches will therefore bemeasured by the importance and number of system-level
questions that are solved. In the following sections, welist several system-level questions in mammalian circadian clocks (Fig. 7). We first describe the dynamical
problems related to the core of clocks, including thedelay in feedback repression; high-amplitude oscillations
generated by transcriptional response of nonlinearity;
temperature-compensation in elementary processes of
the circadian oscillation; and synchronization of clocks
against inevitable fluctuations of phase and period in
multiple circadian oscillators. We then introduce information problems related to clocks in the environment,
including the internal representation of light change,
especially through a mechanism known as perfect adaptation and the internal representation of day length byphotoperiodism.
Core of Clocks
In the mammalian circadian clocks, it is assumed that thedelay in transcriptional feedback repression has a pivotal
role in generating circadian oscillations based on the basic
control theory. However, the underlying molecular mechanism to generate the delay still remains elusive. We firstdescribe this dynamical question on delay. Nonlinearity intranscriptional feedback repression also has an importantrole in generating high-amplitude circadian oscillation
itself as well as the high-amplitude output oscillations.
Thus, as the second dynamical question, we pick up thisnonlinearity problem. In addition to these dynamical properties, the core of mammalian circadian clocks also exhibit
well-defined dynamical properties, including temperaturecompensation and synchronization of multiple cellular
clocks. We describe these two dynamical questions in thesubsequent sections.

SYSTEMS BIOLOGY OF CLOCKS

11

Figure 7. System-level questions in mammalian circadian clocks. Questions related to core of clocks: Delay in feedback repression
seems to have an important role in the generation of oscillations. Although the nonlinearity involved in generating a high amplitude oftranscription has been implicitly supposed in mammalian circadian clock, its mechanism so far remains unsolved. Although temperature-compensation is one of the most mysterious dynamical properties of clocks, its mechanism so far remains unsolved. The synchronization mechanism to generate synchrony of the multiple cellular clocks has been proposed theoretically but is not yet proven.
Questions related to clocks in environment: Central clock tissue can internally represent a change of environmental light signal probably through perfect adaptation. Several mechanisms for perfect adaptation have been proposed theoretically but are not yet proven in
mammalian circadian clocks. Organisms can also internally represent day length through photoperiodism. Although a gating mechanism is expected, its mechanism so far remains unsolved.

Delay. System identification and system analysis of
mammalian circadian clocks revealed that transcriptional
feedback repression mediated through the E box has animportant role in generating transcriptional circadianoscillation. Interestingly, this transcriptional feedback
repression accompanies delay in elementary processes,
which is consistent with the basic control theory predicting that the negative feedback loop with a certain delay
can generate the oscillation with twofold period of delay.
In mammalian circadian clocks, delay has been observed
at least in two processes (Fig. 7, top right panel). One isthe delay between mRNA amounts and protein amounts.
For example, expression levels of Per1 and Per2 mRNA
are several hours earlier than those of PER1 and PER2

proteins (Lee et al. 2001), respectively. According to thebasic control theory, this delay between mRNA and protein may be one of the determinants of duration of circadian oscillation, although there has so far been no
definitive proof. The other process is the delay between
promoter activity and mRNA amount. For example, promoter activity of Cry1 is several hours earlier than theexpression level of Cry1 mRNA (Etchegaray et al. 2003;
Ueda et al. 2005). Because the Cry1 gene is one of thestrongest repressors for E-box-mediated transcription,
this delay also seems to be one of the determinants ofduration of circadian oscillation.
A delayed process, where an input signal is just shiftedto an output signal by a certain period without change of

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its shape, is completely different from a merely slow process, where an input signal is usually transformed to adulled output signal. Thus, the generation of delay
requires certain molecular mechanisms. However, molecular mechanisms to generate delays and hence oscillations
still remain elusive in mammalian circadian clocks.
Nonlinearity. Nonlinearity is another dynamical property closely associated with delay because a slow processwith certain nonlinearity can restore the original sharp
signal from a dulled signal through amplification (Fig. 7,
top right panel). Sigmoidal response (Fig. 7, top rightpanel), one of the nonlinear responses, is important forthis amplification. Sigmoidal response is also importantto generate high-amplitude circadian oscillations in clock
output where a sharp input signal is usually dulled
through a transfer process. Such sigmoidal responses canamplify the dulled signal to restore the original sharp signal and hence generate high-amplitude outputs.
Several molecular mechanisms can be expected toachieve a sigmoidal response. One class of molecularmechanisms is called as cooperativity (Monod et al.
1963), where multiple subunits work together to accomplish the entire process. In this cooperativity process, a
Hill coefficient, which describes the strength of nonlinearity in a sigmoidal response, is usually smaller than thenumber of subunits, and hence usually approximately 2(Hill coefficient 1 indicates a linear response). On theother hand, the other class of molecular mechanisms
called ultrasensitivity (Goldbeter and Koshland 1981) has
a potential to generate strong nonlinearity, with a Hillcoefficient of more than 2. This switch-like behavior,
where the output signal increases abruptly when an input
signal exceeds a certain threshold, was originally proposed theoretically in antagonistic enzymatic reactions,where an enzyme competes with another enzyme acting
on the same molecule (Goldbeter and Koshland 1981).
However, molecular mechanisms to generate such a sigmoidal response and hence high-amplitude oscillations
still remain elusive in mammalian circadian clocks.
Temperature-compensation. A robust 24-hour period
against environmental changes, such as temperature andnutrition, is an important element for the circadian clock.
The robustness of the period against temperature change
is known as temperature-compensation, which is one of
the intriguing aspects of the circadian clock. Typical biochemical reactions, such as enzymatic reactions, showtemperature dependence, which is represented by a Q10
value of about 2. In contrast, the period of circadianrhythm is independent of or compensated against temperature change (Q10 value of the period is about 1.). The
importance of temperature-compensation in poikilotherm
can be easily understood. Although this aspect of naturein the mammalian circadian clock has been controversial,
it has been confirmed in cultured mammalian cells(Izumo et al. 2003; Tsuchiya et al. 2003). Temperaturecompensation has proved to be one of the general elements of circadian clocks from cyanobacteria to humans.
Despite our increasing knowledge of the molecular mechanism of circadian clocks, however, it is difficult to

explain how circadian clocks sustain such a constantperiod against temperature change.
Theoretical studies (Ruoff et al. 1997; Kurosawa andIwasa 2005) have proposed a balanced reaction model(Fig. 7, middle left panel) for explaining this nature, inwhich increasing kinetic parameters of some reactions in
the negative feedback loop lead to a shortening of theperiod and others lead to prolonging the period. As aresult, the period of the circadian rhythm is unchanged
against temperature change by a balance between positive
and negative effects of reactions on the period. These theoretical explanations seem to be plausible, but the balanceof effects on the period length between basic reactions canbe easily broken by perturbations, such as inhibitors andpoint mutations on clock proteins. Furthermore, these theoretical models seem inconsistent with the fact that many
circadian clock mutants show a diverse period but sustain
temperature-compensation. How do circadian clocks
acquire the robustness against temperature change?
There are some implications for understanding themechanism in studies of the cyanobacterial circadianclock. The circadian rhythm of KaiC phosphorylation canbe reconstituted in a test tube, demonstrating that the
KaiC phosphorylation rhythm is the central oscillator of
the cyanobacterial circadian clock (Nakajima et al. 2005).
The reaction rate of KaiC phosphorylation in a test tube isunaffected by temperature change despite the fact that it
is a biochemical reaction. These observations indicatethat the robustness of circadian oscillation in cyanobacterial cells depends on the biochemical properties of threeclock proteins. Although the mechanism of the KaiC
phosphorylation cycle remains unclear, these findings
suggest a robust reaction model (Fig. 7, middle left panel)for temperature-compensation of circadian clocks, at leastin cyanobacteria.
In summary, there exist two possible models of temperature-compensations of the circadian clock. In the balanced reaction model, increasing kinetic parameters ofsome basic reactions lead to shortening the period, andthose of other basic reactions lead to prolonging theperiod. These effects are cancelled out so that the period
is sustained constantly. In the balanced reaction model,
temperature-compensation is expected as a emergent network property of multiple clock components. In therobust reaction model, such as the cyanobacterial circadian clock, temperature-compensation of the circadianclock is caused by reactions, of which kinetic parameters
are independent of temperature change. In the robust reaction model, temperature-compensation is expected as amolecular property of clock components. According tothis model, the system-level understanding of temperature-compensation extensively depends on the investigation of biochemical property of clock components.
Synchronization of clocks. The core of mammalian
circadian clocks located in the SCN consists of multiple
autonomous single-cell oscillators. The individual cellular oscillators in the SCN produce coherent circadianrhythm despite the inevitable internal noise. However, thesynchronization mechanism to couple individual cellularoscillators is largely unknown. As a possible model of the

SYSTEMS BIOLOGY OF CLOCKS
intercellular synchronization of circadian cellular clocks,
we previously presented a multicellular stochastic modelwith an intercellular synchronization factor that emulates
the synchronization of individual cellular oscillators(Ueda et al. 2002a). In this model, owing to a synchronizing factor, the neighboring cells correct each other’s differences to stay in the proper rhythm, and thus, coherent
oscillation of individual cellular clock is retained even in
the presence of internal noise (Fig. 7, middle right panel).
On the other hand, in the model without such a synchronizing factor, coherent oscillation of individual cellular
clocks is abolished despite the identical initial conditions.
The averaged amplitude is reduced due to the internal
noise and the absence of external time cues such as lightand temperature (Fig. 7, middle right panel).
In our model, a synchronization factor is supposed to be
secreted from the individual cellular oscillators and thenaffect the circadian state of neighboring cells. The model
predicts that if the synchronization factor is secreted during the subjective day, then the synchronization factor
will induce the light-type phase-response in the neighboring cells (Ueda et al. 2002a). On the other hand, it is predicted that if the synchronization factor is secreted during
the subjective night, then it will induce the dark-typephase-response in the neighboring cells.
Interestingly, recent studies reported a candidate synchronization factor, vasoactive intestinal polypeptide(VIP), which seems to possess the predicted dynamical
properties described above. VIP is a peptide-type neurotransmitter that is secreted during the subjective day in the
SCN and is known to induce a light-type phase-responsein the circadian clock in a cultured SCN slice (Reed et al.
2001). Moreover, the VIP receptor VPAC2 is also
expressed in the SCN. Actually, it has been reported thatloss of VIP or VPAC2 disrupted synchrony between each
oscillator neuron in the SCN (Aton et al. 2005; Maywood
et al. 2006). Seen in this light, VIP has an important role inprovoking the synchronous oscillation of cells at the SCN
via VPAC2 receptor signaling. If our theory is correct, wemay be able to reconstruct the synchronization of individual cellular oscillators in cultured cells such as Rat-1 andNIH-3T3, which exhibits no detectable synchronization
among cells, by exogenously expressing VIP and the
VPAC2 receptor under the control of a clock-controlled
promoter at the appropriate timing in cultured cells. The
theory predicts that VIP expressed during the subjective
day will induce the efficient coupling among individual
cellular oscillators, but VIP expressed at other times suchas subjective night will not. The experimental verificationof these predictions may lead to design principles in thesynchronization of mammalian circadian clocks.

Clocks in Environment
Mammalian circadian clocks are surrounded by an environment and thereby receive external stimuli such as lightand temperature to extract environmental information on
the state of the earth. In the following sections, we discuss
how the living organism accurately extracts and internally
represents change of light signals and the day length.

13Internal representation of light change: Perfect adaptation. Living organisms sense changes of external environment and entrain their internal circadian clocks byutilizing environmental change as a time cue. The mostwell-known time cue is light, and dawn and dusk lightmark the advance and delay of the circadian clock,respectively. These rapid illumination changes that occur
at dawn and dusk act on the resetting of circadian rhythmin the SCN, which is known as nonparametric entrainment (Johnson et al. 2003). How does the central clock
tissue internally represent the change of the light signals
in order to achieve nonparametric entrainment?
One of the biologically plausible mechanisms to sense
environmental change is known as perfect adaptation (Haoet al. 2007), where the system can sense not the absolutevalue but the relative change of external signals. Three possible mathematical models have been proposed for (near)
perfect adaptation: (1) feed-forward loop, (2) feedback
loop, and (3) activation-dependent inactivation. The feedforward loop model has activation and inactivation pathways to receptor A from signal S. Signal S both activatesand inactivates receptor A. Suppose that there are fast activation and slow inactivation of receptor A, then the active
form of receptor A* would be perfectly adapted, i.e., A*
would rapidly respond to the step-up of signal S but quickly
go back to its original level. It is also noteworthy that bothactivation and inactivation of receptor A by signal S musthave a similar dependency on signal S in order to achieve
the perfect adaptation in the feed-forward loop model. The
second model is the feedback loop model where signal S
activates receptors, and then the active form receptor A*
inhibits the receptor activation or synthesis. We note thatthe feedback loop model only achieves near perfect adaptation, where A* rapidly responds to the step-up of signal S
and goes back near to its original level (but this is not perfect). The third and most robust model is the active-dependent inactivation model, where signal S activates thereceptor. Then, only activated receptor A* is degraded orinactivated (Fig. 7, bottom left panel).
To solve this information problem on the internal representation of light change, it will be a limiting process to
identify the “perfect adaptation” gene, which only
responds to the change of the light. When the step functionof light is applied, this type of genes will be rapidly
induced once but quickly go back to its original expression
level (Fig. 7, bottom left panel). Following the identification of such genes, precise measurement and quantitative
perturbation of its expression dynamics will be critical forthe system-level understanding of its design principle.
Internal representation of day length: Photoperiodism. Living organisms also measure the day length(i.e., the duration of daily light time) and hence sense theseason of external environment because day length islonger in summer and shorter in winter. This alternationof day length induces a seasonal physiological andmetabolic change called photoperiodism (Dunlap et al.
2004). Living organisms are believed to demonstrate photoperiodism through circadian clock function because
only certain periods in a day (photoinducible phase) are
sensitive to light signals and have a critical role in mea-

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surement of day length. However, it is still largely
unknown how the specific brain region can internally represent the day length through interplay between the circadian clock and light (or dark) signals, especially inmammals (Fig. 7, bottom right panel).
In photoperiodism research on animals, birds such as theJapanese quail are often used because of their dynamic andrapid response to day length change. In birds, it is known
that light exposure in a certain phase (photoinducible
phase) can induce a photoperiodic response. Japanesequail have an approximately 4-hour photoinducible phasethat starts about 12–16 hours after the beginning of thelight period. When the day length becomes longer (seasonchanges to breeding period), female Japanese quail begin
to lay eggs and males’ testicles start to mature. During thebreeding period, their testis enlarge to more than 100 times
that of the nonbreeding period. At the hormonal regulationlevel, triiodothyronine (T3), an active form of enzyme
converted from deiodination of thyroxine (T4) prohormone via Dio2 activity, promotes secretion of gonadotropin-releasing hormone (GnRH) and hence testicularmaturation.
Scientific efforts to reveal the induction mechanism ofphotoperiodic reaction in Japanese quail have achieved
great success in recent years. To summarize, the medianeminence (ME) in the hypothalamus was found to be theresponsible area for photoperiodism formation. In the ME,
light stimulation induces Dio2 at the photoinducible phase.
On the other hand, Dio2 is not induced in the nonphotoinducible phase. As clock gene oscillation has been reported
in these areas, the circadian clock is also thought to exist inthese regions. As there is also a time-dependent gating system (i.e., photoinducible phase), the relationship between
Dio2 gene regulation and the circadian clock system has
already been the subject of discussion (Yoshimura et al.
2003). In mammals, the pineal body, which is known as amelatonin-synthesizing organ, is important in photoperiodic reaction. Because melatonin synthesis occurs during
the night and is repressed by light, melatonin level represents the dark length information. Interestingly, expressionof Dio2 in ME, which highly expresses a melatonin receptor, is also under the influence of melatonin in mammals.
Thus, the mammals and birds share a photoperiodic mechanism.
To solve this information problem on the internal representation of day length and season, it will be a limiting
process to identify the “photoperiodic” gene, which is
rapidly induced (or repressed) in response to the longer
day length, and to regulate Dio2 and other downstream
genes. After the identification of such a gene, precise
measurement and quantitative perturbation of its gating
expression dynamics will be critical for the system-level
understanding of its design principle.
CONCLUSION
Following the identification of the key clock genes, there
was increasing demand for higher-order understanding ofdesign principles in mammalian circadian clocks. In thischapter, we described several approaches, beginning withcomprehensive identification (system identification) andquantitative analysis (system analysis) of individual clock
components and their networked interactions, leading to
the ability to control existing systems toward the desired
state (system control) and the design of new ones based onan understanding of structure and underlying dynamical
principles (system design). We also listed several dynamical and information problems including delay, nonlinearity, temperature-compensation, and synchronization of
mammalian circadian oscillator(s), as well as the internal
representation of light change through perfect adaptationand internal representation of day length through photoperiodism in mammals. We strongly believe that it is now
high time to fully integrate the systems-biological approaches for the solution of the system-level questions.
ACKNOWLEDGMENTS
We thank our collaborators. System identification ofclocks: collaboration with Drs. W. Chen, A. Adachi, H.
Wakamatsu, S. Hayashi, T. Takasugi, M. Nagano, K.
Nakahama, Y. Suzuki, S. Sugano, M. Iino, Y. Shigeyoshi,
S. Hashimoto, M. Sano, and M. Machida. System analysisof clocks: collaboration with Drs. T.K. Sato, R.G. Yamada,
H. Ukai, J.E. Baggs, L.J. Miraglia, T.J. Kobayashi, D.K.
Welsh, S.A. Kay, and J.B. Hogenesch. System control ofclocks: collaboration with Drs. H. Ukai, T.J. Kobayashi, M.
Nagano, K. Masumoto, M. Sujino, T. Kondo, K. Yagita,
and Y. Shigeyoshi. System design of clocks: collaboration
with Drs. M. Nakajima, M. Ishida, M. Ukai-Tadenuma,
and T. Kasukawa. Molecular-timetable method: collaborative work with Drs. W. Chen, Y. Minami, S. Honma, K.
Honma, M. Iino, and S. Hashimoto. Theoretical study on
synchronization of clocks: collaboration with K. Hirose and
M. Iino. We also thank Drs. I. Nikaido, H. Ukai, R.G.
Yamada, T.J. Kobayashi, M. Nakajima, and Y. Minami as
well as A. Wada for creation of the figures and critical reading of manuscript. This research was supported by intramural grant-in-aid from the Center for Developmental
Biology (CDB), Director’s Fund from CDB, President’s
Fund from Riken, grant-in-aid for Genome-network
Project and Scientific Research on Priority Areas “Systems
Genomics” from MEXT, Japan, and grant-in-aid for
NEDO project from METI, Japan.
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