Supplemental Material can be found at:
http://www.jbc.org/cgi/content/full/277/16/14048/DC1
THE JOURNAL OF BIOLOGICAL CHEMISTRY© 2002 by The American Society for Biochemistry and Molecular Biology, Inc.

Vol. 277, No. 16, Issue of April 19, pp. 14048 –14052, 2002
Printed in U.S.A.

Genome-wide Transcriptional Orchestration of Circadian Rhythms
S
in Drosophila*□
Received for publication, December 27, 2001, and in revised form, February 15, 2002
Published, JBC Papers in Press, February 19, 2002, DOI 10.1074/jbc.C100765200

Hiroki R. Ueda‡§¶储, Akira Matsumoto¶**, Miho Kawamura§, Masamitsu Iino‡,
Teiichi Tanimura**‡‡, and Seiichi Hashimoto§
From the ‡Department of Pharmacology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo
113-0033, §Molecular Medicine Research Laboratories, Institute for Drug Discovery Research, Yamanouchi
Pharmaceutical Co., Ltd., 21 Miyukigaoka, Tsukuba, Ibaraki 305-8585, and the **Department of Biology, Faculty of
Science, Kyushu University, Ropponmatsu, Fukuoka 810-8560, JapanThe use of Drosophila has been at the forefront of studies ofthe molecular and genetic basis of circadian rhythms (1). A
number of clock genes have been identified in Drosophila, andinterlocked per-tim and Clk feedback loops are now thought tounderlie the central molecular machinery of circadian rhythms(2, 3). However, we still do not know how expression of thewhole genome is orchestrated by the circadian mechanism nor
have we identified all the genes involved. One comprehensive
way to find out all the rhythmically expressed genes is to utilize
microarray. A number of genes regulated in a circadian manner
have been identified in Arabidopsis and mammalian cultured* This work was performed as a part of a research and development
project of the Industrial Science and Technology Program supported by
NEDO (New Energy and Industrial Technology Development Organization) and was also supported by grants from the Ministry of Education, Science, Sports and Culture of Japan (to T. T. and A. M.). The costsof publication of this article were defrayed in part by the payment ofpage charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate thisfact.
□
S The on-line version of this article (available at http://www.jbc.org)
contains Tables I–VIII.
¶ Both authors contributed equally to this work.
储 To whom correspondence may be addressed. Tel.: 81-298-54-1524;
Fax: 81-298-54-1669; E-mail: hiro@m.u- tokyo.ac.jp.
‡‡ To whom correspondence may be addressed. Tel.: 81-92-726-4759;
Fax: 81-92-726-4625; E-mail: tanimura@rc.kyushu-u.ac.jp.

cells (4, 5). Since information about all the possible transcription units is available in Drosophila (6, 7), we can extensively
analyze the data for all the genes relating to their function.
Functions of identified genes can be analyzed using various
genetic tool and databases (9 –11) available in Drosophila.
EXPERIMENTAL PROCEDURES

Strain and Sample Preparations—white1118 was used as a wild-typestrain, and ClkJrk was also used (11). Flies were reared in a regime of
12 h of light followed by 12 h of darkness (LD),1 and collected every 4 hover 2 days. Total RNA was prepared from 100 heads of 1-week-old
adult males and females using the Fast RNA kit (BIO 101, Inc.) followed by DNase treatment. Double-stranded cDNA was synthesizedfrom 10 ␮g of total RNA using Superscript II reverse transcriptase(Invitrogen) and was used as a template to synthesize biotin-labeledcRNA by in vitro transcription using an ENZO BioArray High Yield
RNA transcript labeling kit. Amplified cRNA was fragmented and hybridized to GeneChip Drosophila arrays (Affymetrix, Santa Clara, CA)
for 16 h at 45 °C. Hybridized arrays were washed, stained, and scanned
using a Hewlett-Packard GeneArray Scanner. Affymetrix GeneChip
software was used to determine the average difference between perfectly matched oligonucleotide probes and single base pair mismatches
for each probe set. Data were then scaled globally such that the total
intensity of each microarray is equal. The resulting hybridization intensity values reflect the abundance of a given mRNA relative to thetotal RNA population and were used in all subsequent analyses. Quantitative PCR was performed using the ABI Prism 7700 and SYBR Green
reagents (Applied Biosystems).
Analysis of Cycling Genes—We examined gene expression profiles
under LD using two successive filters: a periodic filter to extract genes
with periodic expression patterns and a deviation filter to identify genes
where the changes were above background level.
First, to extract genes with periodic expression pattern, we empirically tested for statistically significant cross-correlation between thetemporal expression profiles of each probe set and cosine waves ofdefined period and phases. We prepared cosine waves of nine test
periodicities (␶) from 20 to 28 h in increments of 1 h. Cosine waves ofeach test period were considered over 60 phases (i.e. peaks at 60 equally
spaced times in the defined period), yielding a total of 540 test cosine
waves. Statistical significance was assessed by an empirical procedure.
We generated ⬃14,000 (the same number of probe sets) normally distributed random expression profiles. Then we calculated correlation
between the random profiles and each of the 540 test cosine waves.
Standard deviations and averages of cross-correlation were virtuallyequal for 540 cosine filters despite their different periods and phases.
Thus, we searched for the common cut-off correlation of these cosine
filters so that 95% of random expression profiles were filtered out after
passing 540 parallel cosine filters. We determined this value as 99.8%
probable correlation. This analysis is independent of signal strengthand imposes no minimal change in amplitude.
Next, to further extract genes whose variation was above background, we determined the noise level associated with a series of ex1
The abbreviations used are: LD, 12 h of light followed by 12 h ofdarkness; DD, constant dark; RT, reverse transcription; GABA, ␥-aminobutyric acid.

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Circadian rhythms govern the behavior, physiology,
and metabolism of living organisms. Recent studies
have revealed the role of several genes in the clock
mechanism both in Drosophila and in mammals. To
study how gene expression is globally regulated by theclock mechanism, we used a high density oligonucleotide probe array (GeneChip) to profile gene expression
patterns in Drosophila under light-dark and constantdark conditions. We found 712 genes showing a daily
fluctuation in mRNA levels under light-dark conditions,and among these the expression of 115 genes was still
cycling in constant darkness, i.e. under free-running
conditions. Unexpectedly the expression of a large number of genes cycled exclusively under constant darkness. We found that cycling in most of these genes waslost in the arrhythmic Clock (Clk) mutant under lightdark conditions. Expression of periodically regulated
genes is coordinated locally on chromosomes where
small clusters of genes are regulated jointly. Our findings reveal that many genes involved in diverse functions are under circadian control and reveal the complexity of circadian gene expression in Drosophila.

Genome-wide Orchestration of Circadian Rhythms

14049

perimental procedures for each probe set. Two replicate samples (i.e.
two sets of 100 fly heads collected independently at the same time of theday) were hybridized to two GeneChips. The standard deviation of thetwo signal intensities for each probe set was calculated and used asnoise deviation (␴) in subsequent analysis. Expression profiles which,over the 12 time points, show a standard deviation (s) greater thannoise deviation (␴) with 95% significance are classified as “changing.”
95% probability cut-off values are determined from ␹2 (chi-square)
distribution with 11 degrees of freedom ((12 ⫺ 1) s2/␴2 ⬎ 19.6751).
To estimate the false positive rate, we generated ⬃14,000 (the same
number of probe sets) random expression profiles that were normally
distributed using the noise deviations as determined above. Then we
filtered these random expression profiles using two successive filters.
Random profiles produced 27 genes classified as “periodically changing.” We assume that this estimates the false positive rate (i.e. 3.8% of
all genes identified would be false positives).
To analyze periodicity of gene expression profiles under constantdark (DD), we used damping cosine curves as test waves. We prepareddamping cosine waves of four decay rates (k) from 0.0/h (no damping) to
0.03/h (half-life is 23.0 h) in increments of 0.01/h. Each was consideredat nine test periodicities and over 60 phases as described above. We
used the same cut-off cross-correlation values and the same deviation
filters as in LD analysis.
Phase Analysis—To determine the phase of cycling genes, we tested
for correlation between the temporal expression profiles of each geneand 24-h period cosine waves at 60 different phases. We estimated thephase of each cycling gene from the phase of the cosine wave with which
it was correlated most closely.
Determination of Statistical Significance for Rhythmic Biological
Processes and Periodically Regulated Molecules—We classified the cycling genes by biological process category in the Gene Ontology database (9). For each category, we calculated the probability of finding atleast r periodically regulated genes from the category size (n) using the
cumulative hypergeometric probability distribution. Probability isgiven by:

冘 共 兲共共 兲 兲r⫺1

Probability ⫽ 1 ⫺

l⫽1

n
l

N⫺n
R⫺l

N
n

We also performed similar analyses using the LIGAND metabolic
database (9). We mapped cycling genes into the metabolic network in
Drosophila and calculated the probability for observing at least r cycling genes within n enzymes metabolizing the same molecule using the
cumulative hypergeometric probability distribution as above.
Analysis of ClkJrk—For each gene, expression levels in ClkJrk mutants were averaged with those in wild-type flies. Both were kept in LD
conditions, and equivalent points in the light-dark cycle were compared.
Genes were classified as “up-regulated” if expression was at least 2
times higher in the mutant and “down-regulated” if expression was
least 2 times lower in the mutant. Otherwise genes were classified as“unchanged.”
Mapping of Periodically Regulated Genes and Calculation of Chromosome Correlation Maps—Among 14,010 probes on the GeneChip, 44
probes are for control, and 299 probes map to multiple genes. The other
13,667 probes map to single genes. Among these, there are several
redundant probe sets that map to the same gene, leaving 13,282 nonredundant probes. 12,795 of these match in FlyBase ID (10) to identified
genes from Release 2 Drosophila genomic sequences (6, 7). We identified the chromosomal positions of all 12,795 genes using the BLASTN
algorithm. Using the chromosomal positions obtained above, we
mapped the genes belonging to each Class I, II, and III on chromosomes.
To detect co-regulated regions, we calculated the correlation between
expression patterns under LD conditions of genes on the same chromosome as described elsewhere (12). To identify significantly co-regulated
regions, we calculated the average correlation of six adjacent genes andcompared it with the average correlation of six nonadjacent genes asbackground. There were 140 chromosomal regions where the averagecorrelation of the six adjacent genes was more than 3.5 standard deviations from background, i.e. the mean average correlation of six nonadjacent genes. This analysis showed that a substantial number ofadjacent sets have correlated expression patterns in comparison with
25 expected co-regulated regions derived from a control set of nonadjacent genes. Similar results were obtained from analysis of 2–10 adjacent genes. Among 140 chromosomal regions, 38 clusters of genes included periodically regulated genes. We also analyzed co-expressedregion under the DD condition and obtained similar results to the LD
condition.
RESULTS AND DISCUSSION

where N is the total number of genes within the genome, and R is thetotal number of periodically regulated genes. p values (⫺log10 (probability)) where the sum of probabilities is below 0.05 were consideredsignificant.

We have examined temporal patterns of gene expression
under LD and under DD using a GeneChip (Affymetrix) representing the entire genome (more than 13,500 genes) of Dro-

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FIG. 1. Cycling of gene expression inwild-type flies kept under LD and DD
and in ClkJrk mutant flies under LD. a,a cluster image of 712 cycling genes under
LD. Data were normalized so that the average and the standard deviation of signal
intensities of 12 time points are 0.0 and 1.0,
respectively. For each gene, the 12 horizontal bars along the time axis represent a
48-h series of data. The genes were orderedby their peak time to help to visualize theextensive pattern of cycling. Bars are colored red for positive values and green for
negative values as shown in the upper color
code. b, a cluster image of 456 genes whose
expression is free-running under DD. The
details of representation are similar to a. cand d, phase distributions of the peak expression times of periodically regulated
genes under LD (c) and DD (d) derived
from data on 712 and 456 periodically regulated genes under LD and DD, respectively. Two major populations have peaks
at around ZT10 and ZT20 under LD. Thesepeaks are not found in DD. e, periodic expression of per, tim, vri, Clk, cry, and tounder LD and DD in wild-type and in
ClkJrk mutant background flies under LD.
Data of LD and DD were normalized sothat the average signal intensity of 12 time
points was 1.0. For data in ClkJrk background, signal intensities of these genes
were divided by the average signal intensities under LD conditions. WT, wild type.

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Genome-wide Orchestration of Circadian Rhythms

sophila melanogaster. Flies were collected every 4 h over 2 days
both in LD and DD, and biotin-labeled probes made from cDNAfrom 100 heads were used for hybridization. We estimate thatthe expression of 6,061 genes (43.4% of all genes) was detectedon GeneChip. The number of genes detected here is thought tobe delimited by the detection method using GeneChip, andthere should be additional cycling genes expressed at a lower
level or in a small number of cells. Data were analyzed throughtwo sequential statistical filters, and 712 genes (5.3% of thewhole genome) were classified as periodically regulated genes
in LD (Fig. 1a). This is likely to be a minimum number for thegenes that are periodically regulated; the number may increase
if a different filtration analysis was applied. Our analyses
might not detect genes that cycle in some cells but not inothers, and moreover, it is technically difficult to monitor genes
with very low levels of transcription. The number of periodically regulated genes in Drosophila is similar to that reported
from Arabidopsis under constant light (4), in which 6% of genes
investigated are rhythmic, but is in contrast to cyanobacteria,
in which nearly all genes are expressed periodically (13). We
found that genes implicated in circadian rhythms, including
period (per) (14), timeless (tim) (15), Clock (Clk) (11), vrille (vri)(16), cryptochrome (cry) (17), and takeout (to) (18), cycled withhigh amplitude and in similar phase, as previously reported,
validating our experimental and statistic procedures (Fig. 1e).
We analyzed the phase of periodically regulated genes at aresolution of 0.4 h and found two peaks around ZT10 and ZT20
(Fig. 1c). The peaks may reflect the after-effect of the change
from dark to light and light to dark since significant peaks wereabsent under the constant dark condition (Fig. 1d). The peakphases of the clock genes, Clk, cry, per, vri, tim, and to, were notat these times. We then analyzed the gene expression underDD (Fig. 1b) and found that 115 genes of 712 were still periodically regulated in the free-running condition (Class I, periodically regulated both in LD and DD). The remaining 597
genes were judged to be periodically regulated only in LD(Class II). Surprisingly 341 genes that were not judged asperiodically regulated under LD were, however, periodicallyregulated under DD (Class III). Their cyclings might have been
suppressed or masked under LD as suggested from behavioral
experiments (19). In our classification of genes we should notethat because we used a strict filter to identify periodicallyregulated genes, genes judged to be not cycling might in fact
cycle with low amplitude. Lists of all genes in each class may befound in Supplemental Tables I–III. After completion of ourwork two similar works using GeneChip were published (20,21). Their findings are similar to ours, but there are several
differences, specifically the Class II and III genes were notmentioned in other studies. We think that the major differences are the numbers of sampling and statistical analyses. We
analyzed data for 2 days both under LD and DD, while theprevious studies analyzed data only for 1 day in each light
condition. Several interesting periodically regulated genes
were identified from the three classes, I, II, and III (Fig. 2). The
reliability of GeneChip data was assessed by quantitative RTPCR analyses, which confirmed that both methods yielded
similar data. A novel candidate of clock genes, Pdp1, showing arobust cycling (Fig. 2a), encodes a transcription factor with

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FIG. 2. Three classes of periodicallyregulated genes and validation of GeneChip data by quantitative RT-PCR
using wild-type flies (WT) under LD
and DD and ClkJrk (Clk) mutant flies
under LD. a, Class I genes cycling bothin LD and DD; b, Class II genes cycling
only in LD; c, genes cycling in DD but notin LD. In each class, data are shown for
two to three genes, the rhythmic expression of which was found in this study.
Upper curves in a, b, and c are based on
the GeneChip analyses; lower curves are
based on the quantitative PCR analyses.
Pdp1, PAR domain protein encoding atranscription factor; Pdh, photoreceptor
dehydrogenase; trpl, transient receptor
potential-like encoding a Ca2⫹ channel;
inaC, inactivation no after-potential C encoding a protein kinase C; inaD, inactivation no after-potential D encoding a structural protein containing a PDZ domain;
Cyp4e2, cytochrome P450-4e2.

Genome-wide Orchestration of Circadian Rhythms

14051

homology to vri (16). Most of the genes we found to cycle could
be classified according to the category of their “biological process” as defined in the Gene Ontology database (8) (Supplemental Tables IV and V). Phototransduction is one such category,
which includes a significant number of periodically regulated
genes. Two of these were Class I genes. Photoreceptor dehydrogenase, Pdh, also showed a clear cyclical expression (Fig. 2).
One retinoid-binding protein (CG5958) was periodically expressed with peak at dusk, while the other retinoid-binding
protein (CG10657) belonging to Class II was cycling with almost opposite phases. A number of genes belonged to Class II.
Three opsins, Rh3, Rh4, and Rh6, which express in the central
rhabdomeres of the compound eye’s ommatidia, showed rhythmic expression. Another opsin, Rh5, belonged to Class III. The
ninaA gene encoding cyclophilin, which transports opsins fromendoplasmic reticulum to microvilli membrane, also showedrhythmic expression. Molecules associating with Ca2⫹ signaltransduction in the photoreceptors, inaC, inaD, and trpl, also
cycled (Fig. 2b). The expression of most genes listed above
peaked in the morning, whereas Rh6 and trpl peaked in theevening. Visual sensitivity is controlled by a circadian rhythm
in insects (22), and it would therefore be interesting to know
how cyclical changes in these genes influence photoreceptor
structure and function.
We also used the LIGAND metabolic database (9) to examine
the functional significance of periodically regulated genes (Supplemental Tables VI and VII). Enzymes and transporters involved in metabolism or function of glutamate and GABA wereperiodically regulated. Eaat1, CG5618, and CG7470 are ClassI genes, and Gdh, black, CG4233, and CG7433 are Class II
genes. Gs1 belongs to Class III. All genes except CG4233
showed robust rhythmicity with peaks in the dark phase. In
mammals, glutamate (23) and GABA (24) are neurotransmitters associated with clock function. These molecules mimic

the dark pulse to a circadian rhythm in the optic lobe ofMusca (25). In Drosophila, one type of glutamate receptor ishighly enriched in pacemaker neurons (26), and our datasuggest glutamate and GABA might have a role in the circadian mechanism. In the light of a recent finding that theredox state of NAD cofactors is involved in circadian rhythms(27), it is interesting that many enzymes related to NAD⫹,
NADH, NADP⫹, and NADPH metabolism were periodicallyregulated. There are 16 periodically regulated genes directly
associated to the synthesis of these nicotinamide nucleotides.
Three are in Class I, and the remaining 13 are in Class II.
Their peaks expression occurred in three phases under LD:
noon, dusk, and night.
We next examined the cycling of gene expression in thearrhythmic mutant of the Clock (Clk) gene (11) under LD. Our
study showed that many genes are cycling only in LD, and wethen asked whether the cyclings of the Class II genes are
merely a reflection of light responses. Homozygous ClkJrk mutants show completely arrhythmic locomotor behavior underDD (11). CLK is a transcription factor and activates clockregulated genes (1, 2, 11). In the Clk mutant, periodically
expression of all the clock genes disappeared (Fig. 1e), and only
a few genes were judged to cycle under LD (7, 16, and 23 genes
in Class I, II, and III, respectively; Supplemental Table VIII). It
is possible that the cycling genes in the ClkJrk mutant may
represent genes controlled by a possible CLK-independent
mechanism. We did not analyze the cycling pattern with two
peaks in a day. If cycling is simply controlled by light-on and-off, it shows a pattern with dual peaks in a day. We did notinvestigate this possibility, but genes belonging to the Class III
may have such a property. Further studies are necessary toinvestigate this possibility.
Our results suggest that the cycling of the Class II genes is
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FIG. 3. Global chromosomal profiles of periodic gene expression. a, correlation map for gene clusters that included the Class I genes on
the right arm of the second chromosome. The green block at the center indicates the group of six adjacent co-expressing genes, including cytochrome
P450, Cyp6a17 (Class I), Cyp6a23, Cyp6a19, Cyp6a9, Cyp6a20, and Cyp6a21. The numbers along the matrix represent the gene number along thechromosome. Green squares indicates a positive correlation; red squares indicate a negative correlation. b, the six cytochrome P450 genes that areperiodically co-regulated under LD and DD. Cyp6a17 is represented by the green line with the highest peak at a time point of 25 h. c, correlation
map for gene clusters that included the Class I genes but that have no functional relatedness to each other. d, three genes on the third chromosome(CG11891, which belongs to Class I, CG11889, and CG10513) showed similar rhythmic expressions in LD, and periodic expression of these genes
also persists under DD. Data for CG11889 under DD is not shown here as they included a few negative values. e, correlation map for gene clusters
that included the three Class II genes on the left arm of the third chromosome. f, CG7646, CG7654, and CG7433 are Class II genes, and theirneighboring gene, neurocalcin, showed a similar expression pattern in LD. WT, wild type.

14052

Genome-wide Orchestration of Circadian Rhythms
Although cycling gene expression is not always essential for
circadian function, in clock genes such as cyc (29) and doubletime (30) our study has established the candidacy of many
candidate genes that might be implicated in circadian mechanisms. Further work using genetic tools available in Drosophila should help to explore the function of these genes with theprospect of leading to a greater understanding of the molecularbasis of circadian rhythms in all organisms.
Acknowledgments—We are grateful to Michael Rosbash and Jeffrey
C. Hall for the ClkJrk strain. We thank Shigeru Iwase for computational
analysis; Satoko Hayashi, Tomoko Kojima, Toshie Katakura, Yuko
Mitsuiki, and Makiko Haruta for technical assistance; and MasamiHorikoshi and Takashi Umehara for hospitality in the use of theirlaboratory. We also thank Hideo Iwasaki and Kenji Tomioka for discussion and Jennifer Hallinan and Ian Meinerzhagen for comments on
the manuscript.
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circadian control. Under LD, the expression levels of per, tim,
vri, and to were decreased relative to Clk (Fig. 1e), whereas Clk
and cry continue to express at a high level as previously shown(11, 17). Fig. 2 shows the expression patterns of seven genes in
ClkJrk. If the transcription level of a gene is lowered in ClkJrk,
the gene might be up-regulated by Clk, whereas if the level is
not affected, the gene might be regulated by a CLK-independent mechanism. The expression of about 6% of genes was decreased, while in about 3% of genes it was increased. In thelatter case, their transcription might normally be down-regulated by genes controlled by CLK. These results indicate that
CLK regulates transcription in many genes, but there are othergenes in which transcription is not directly controlled by CLK.
In addition some genes might be negatively regulated by CLK.
We do not think that these changes are caused by the genetic
background differences as we dealt with genes whose expression level changed over 2-fold or one-half. Our study thus
shows that a single mutation in such a central gene regulator
results in global but differential changes of gene expression.
We mapped the chromosomal locations of genes belonging toeach class (I, II, and III) and found that they were not randomly
distributed but clustered on chromosomes. There were 15 clusters where periodically regulated genes occupied a highly condensed chromosome interval. This suggests that temporal gene
expression might be locally regulated on chromosomes. To confirm this possibility, we calculated the correlation of temporal
expression pattern along the neighboring genes on all chromosomes and found 140 chromosomal regions where neighboring
genes are expressed with a similar pattern to each other.
Among them, 38 regions contained at least one periodicallyregulated gene. There were six genes in Class I, 24 in Class II,
and eight in Class III. For example, the expression patterns of
six neighboring genes belonging to the cytochrome P450 family,
located on the right arm of the second chromosome, are similar(Fig. 3, a and b). There is a region where genes are co-regulated, but their functions are unknown (Fig. 3, c and d). Moreover, we found that functionally unrelated genes are co-regulated (Fig. 3, e and f). These results suggest that the temporal
expression of neighboring genes is influenced by a periodicallyregulated gene. Searches of each class of periodically regulated
genes so far failed to reveal any common motifs in the nucleic
acid sequence along the putative regulatory region of each classof cycling genes. We found that the co-regulation of temporal
expression occurs even more globally. The co-regulated regions
were observed along the fourth chromosome at intervals of
about 5–10 genes (data not shown). The regular spacing suggests control at the level of higher order chromatin structure aspreviously reported in suprachiasmatic nuclei neurons (28).
These results suggest that gene expression on chromosomes is
globally regulated by circadian mechanisms, although we still
do not know their molecular bases. Coordinated gene regulation at the chromatin level might be an economical way inremodeling chromosome structures.
Our study thus reveals the complex transcriptional orchestration of genes under LD and DD conditions in Drosophila.