The frequency gene is required for temperature-dependent regulation of many clock-controlled genes in Neurospora crassa.

Abstract

The circadian clock of Neurospora broadly regulates gene expression and is synchronized with the environment through molecular responses to changes in ambient light and temperature. It is generally understood that light entrainment of the clock depends on a functional circadian oscillator comprising the products of the wc-1 and wc-2 genes as well as those of the frq gene (the FRQ/WCC oscillator). However, various models have been advanced to explain temperature regulation. In nature, light and temperature cues reinforce one another such that transitions from dark to light and/or cold to warm set the clock to subjective morning. In some models, the FRQ/WCC circadian oscillator is seen as essential for temperature-entrained clock-controlled output; alternatively, this oscillator is seen exclusively as part of the light pathway mediating entrainment of a cryptic "driving oscillator" that mediates all temperature-entrained rhythmicity, in addition to providing the impetus for circadian oscillations in general. To identify novel clock-controlled genes and to examine these models, we have analyzed gene expression on a broad scale using cDNA microarrays. Between 2.7 and 5.9% of genes were rhythmically expressed with peak expression in the subjective morning. A total of 1.4-1.8% of genes responded consistently to temperature entrainment; all are clock controlled and all required the frq gene for this clock-regulated expression even under temperature-entrainment conditions. These data are consistent with a role for frq in the control of temperature-regulated gene expression in N. crassa and suggest that the circadian feedback loop may also serve as a sensor for small changes in ambient temperature.

Full text

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Copyright  2003 by the Genetics Society of America
Thefrequency GeneIsRequired forTemperature-DependentRegulation ofMany
Clock-Controlled Genes in Neurospora crassa
Minou Nowrousian,1Giles E. Duffield, Jennifer J. Loros and Jay C. Dunlap2
Departments of Genetics and Biochemistry, Dartmouth Medical School, Hanover, New Hampshire 03755
Manuscript received November 11, 2002
Accepted for publication February 21, 2003
ABSTRACT
The circadian clock of Neurospora broadly regulates gene expression and is synchronized with the
environment through molecular responses to changes in ambient light and temperature. It is generally
understood that light entrainment of the clock depends on a functional circadian oscillator comprising
the products of the wc-1 and wc-2 genes as well as those of the frq gene (the FRQ/WCC oscillator). However,
various models have been advanced to explain temperature regulation. In nature, light and temperature
cues reinforce one another such that transitions from dark to light and/or cold to warm set the clock to
subjectivemorning.Insomemodels,theFRQ/WCCcircadianoscillatorisseenasessentialfortemperature-
entrainedclock-controlledoutput;alternatively,thisoscillatorisseenexclusivelyaspartofthelightpathway
mediatingentrainmentofacryptic“drivingoscillator”thatmediatesalltemperature-entrainedrhythmicity,
in addition to providing the impetus for circadian oscillations in general. To identify novel clock-controlled
genes and to examine these models, we have analyzed gene expression on a broad scale using cDNA
microarrays. Between 2.7 and 5.9% of genes were rhythmically expressed with peak expression in the
subjectivemorning.Atotalof1.4–1.8%ofgenesrespondedconsistentlytotemperatureentrainment;allare
clock controlled and all required the frq gene for this clock-regulated expression even under temperature-
entrainment conditions. These data are consistent with a role for frq in the control of temperature-
regulated gene expression in N. crassa and suggest that the circadian feedback loop may also serve as a
sensor for small changes in ambient temperature.
T
dian rhythms (Dunlap 1999). The circadian system of
N.crassaiscomposedofseveralinterdependentmolecu-
larfeedbackloops(Aronsonetal.1994a;Crosthwaite
et al. 1997; Lee et al. 2000; Cheng et al. 2001; Denault
et al. 2001; Goerl et al. 2001; Heintzen et al. 2001) that
regulatethetime-of-day-specificexpressionofanumber
of output genes, thereby generating distinct pheno-
types, e.g., the clock-dependent rhythm of macroconid-
iation.Theclockintegratesinputsignals,includinglight
and temperature changes, to keep the organism in tune
with the environment. Both light and temperature have
similar entrainment effects on the circadian clock in
that 12 hr/12 hr cycles of light/dark or warm/cold
result in a 24-hr rhythm of conidiation with the peak
ofconidiationoccurringjustpriortothetransitionfrom
dark to light or from cold to warm, the time point
defined as subjective dawn. Known players involved in
circadianandlightregulationoftheseprocessesinclude
the products of the frq, wc-1, wc-2, and vvd genes (Loros
and Dunlap 2001). However, there is evidence that
HE ascomyceteNeurosporacrassahasalongstanding
as a model organism for the investigation of circa-
other genes also contribute to the circadian system in
Neurospora and might comprise independent, if not
circadian, feedback loops (e.g., Loros and Feldman
1986; Merrow et al. 1999; Lakin-Thomas and Brody
2000; Ramsdale and Lakin-Thomas 2000).
Part of clock-controlled gene expression in Neuro-
spora is exercised at the level of transcription (Loros
and Dunlap 1991). Over the last decade, clock-con-
trolled genes (ccgs), which exhibit cycling mRNA levels,
have been identifiedby subtractive hybridization, differ-
ential screening of cDNA libraries, and expressed se-
quence tag (EST) sequencing (Loros et al. 1989; Bell-
Pedersenetal.1996b;Zhuetal.2001).Anothermethod
for the identification of genes that are differentially
regulated is microarray technology. In recent years, mi-
croarrays have been widely used to analyze gene expres-
sion in a growing number of organisms, including
plants, mammals, bacteria, and yeast (Schena et al.
1995;DeRisietal.1997;Wilsonetal.1999;Harmeretal.
2000; Perou et al. 2000). For filamentous fungi, cDNA
microarrays have been established for Trichoderma reesei
(Chambergo et al. 2002) and for N. crassa (Lewis et al.
2002).
Here we report the use of microarrays for the identi-
fication of novel clock-controlled genes in N. crassa and
foracomparisonoftemperaturecontrolofgeneexpres-
sion in the wild-type and a frq null mutant strain. This
analysis allowed us to evaluate existing models for tem-
1Present address: Lehrstuhl fu ¨r Allgemeine und Molekulare Botanik,
Ruhr-Universita ¨t Bochum, 44780 Bochum, Germany.
2Corresponding author: Department of Genetics, HB7400, Dartmouth
Medical School, Hanover, NH 03755.
E-mail: jay.c.dunlap@dartmouth.edu
Genetics 164: 923–933 (July 2003)

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924 M. Nowrousian et al.
libraries and the sequencing and analysis of 13,000 clones
from these libraries have been described (Zhu et al. 2001). A
unigene library was established by choosing a single clone
representing each gene in the libraries. The unigene library
consists of ?1100 clones in 12 microtiter plates (plates UA–
UL). As it was found that there were errors in the original
annotation of the morning and evening libraries (a common
problem in EST libraries, Knight 2001), most of the clones
oftheunigenelibraryhavebeenresequencedattheAdvanced
Center for Genome Technology (University of Oklahoma,
Norman, OK) as described previously (Zhu et al. 2001). A
copy of the unigene library was deposited with the Fungal
Genetics Stock Center (University of Kansas Medical Center,
Kansas City). Sequence information can be found in the on-
line supplementary material at http:/ /www.genetics.org/sup
plemental/.AmplificationofthecDNAinsertsfromthelibrary
was done according to Hedge et al. (2000) using the universal
forward primer (5? GACGTTGTAAAACGACGGCC) and the
universal reverse primer (5? CACAGGAAACAGCTATGACC).
PCR results were verified by agarose gel electrophoresis and
the PCR products were purified using a QIAquick multiwell
PCR purification kit according to the manufacturer’s protocol
(QIAGEN, Hilden, Germany). PCR products were then dis-
solved in 3? SSC buffer and spotted onto CLONTECH (Palo
Alto, CA) DNA-ready type II slides or dissolved in 50% DMSO
and spotted onto GAPSII slides (Corning, Acton, MA) with a
GMS 417 arrayer (Affymetrix, Santa Clara, CA). Each PCR
product was spotted twice on each slide. Postprinting slide
procedures were performed according to the manufacturer’s
recommendations.
Microarray target preparation, hybridization, and scanning:
For time course experiments in DD, microarray targets were
made using a CLONTECH Atlas glass fluorescent labeling kit
and FluoroLink Cy3 or Cy5 monofunctional dyes (Amersham
Pharmacia,Piscataway,NJ)according totheCLONTECHpro-
tocol. A total of 3–5 ?g of DNaseI-treated poly(A) RNA was
used as starting material for each target, and a mixture of 2
?g oligo(dT) and 2 ?g random hexamer oligonucleotides
(both from GIBCO Invitrogen, Carlsbad, CA) was used as a
primer for reverse transcription. For time course experiments
in DD, each slide was hybridized with two targets, one “experi-
mental target,” which was made from the RNA of interest
and varied for each slide, and one “reference RNA,” which
consisted of a combination of RNAs from different growth
conditions and was the same for each slide used in a given
experiment. (RNAs used as references were extracted from
mycelia grown as described above and harvested at different
DDtimes,withsomeofthembeinggivena5-minlightpulse15
min to 1 hr prior to harvest.) “Experimental” and “reference”
RNAs were labeled with Cy3 and Cy5 dyes, respectively, and
the dyes were switched in one of the biologically independent
replicas of each experiment. Hybridization was done for 16 hr
at 50? in CLONTECH GlassHyb hybridization solution using a
CLONTECH hybridization chamber, and slides were washed
in wash solution according to the manufacturer’s recommen-
dations (CLONTECH).
For temperature-entrainment experiments, microarray tar-
getsweremadefromDNase-treatedtotalRNAorpoly(A)RNA
(7 or 1 ?g, respectively). Reverse transcription was done in
the presence of aminoallyl-dUTP (Sigma, St. Louis), 2 ?g
oligo(dT), 5 ?g random hexamer oligonucleotides, and 600
units Superscript II reverse transcriptase (GIBCO, Gaithers-
burg, MD) in a 30-?l reaction at 42?. Cy3 or Cy5 dyes were
coupled in a second step in 0.5 m sodium bicarbonate buffer
(pH 9.0). Targets were cleaned with QIAquick PCR purifica-
tionkit(QIAGEN)andvacuumdried.Forhybridization,slides
were prehybridized in 5? SSC, 0.1% SDS, 1% BSA for 45
min at 42?. Targets were resuspended in 14-?l hybridization
perature-influenced clock-regulated gene expression.
One recent model (Merrow et al. 1999) states that
FRQ/WCC are required only for light input, with tem-
perature input and output not requiring FRQ. To be
consistent with this model, temperature regulation of
clock-controlled genes should be largely independent
of frq and therefore similar in the knockout strain frq10
and in the wild type. However, we found that clock-
controlled genes that are also temperature-regulated
lose both temperature and clock regulation in the frq10
strain. This demonstrates that at least part of tempera-
ture-regulated gene expression in Neurospora depends
on frq and on a fully functional circadian clock.
MATERIALS AND METHODS
Strains and growth conditions: The following N. crassa
strains were used: frq?(wild type) strain 87-3 (bd; a), long
period mutant 585-7 (bd; frq7a), and frq knockout strain 86-1
(bd; frq10A; Aronson et al. 1994b). Neurospora media (Vo-
gel’s) were as described (Davis and deSerres 1970). Culture
conditions for rhythmic RNA analysis and light-induction ex-
periments were similar to published methods (Heintzen et
al. 2001) with the following modifications: For analysis under
free-running conditions in constant darkness (DD), strains
were grown in 100-ml Erlenmeyer flasks in 50 ml of liquid
culture medium with 1? Vogel’s salts, 2% glucose, 0.5% argi-
nine, and 50 ?g/liter biotin at 25?. For time courses, the
followingtimesinconstantdarknesswereusedforarrayexper-
iments: DD12, DD16, DD20, DD24, and DD28 for strain 87-3
and DD17, DD22, DD27, DD32, and DD37 for strain 585-7.
Samples were kept in constant light prior to transfer to con-
stant darkness, and transfer to DD was staggered to ensure
that samples were of similar developmental age at the time
of harvest (Loros and Dunlap 1991). Neurospora does not
respond to light with wavelengths ?550 nm (red light), so
for temperature-entrainment experiments mycelial mats were
grown in constant darkness or red light (DD) for 48 hr at 22?.
Mycelial disks (1 cm in diameter) were cut from mats in DD
and transferred to liquid medium. These samples were then
transferred to entrainment conditions (cycles of 12 hr at 22?/
12 hr at 27?) and harvested after at least 44 hr under entrain-
ment (for a representation of the temperature entrainment,
see Figure S1 in supplementary material at http:/ /www.gene
tics.org/supplemental/).Forarrayexperiments,thefollowing
five time points were used (time in hours given after the
last change of temperature from high to low or low to high,
respectively; for exact times, see individual experiments): 10–
11.5 hr at 27?, 2–6 hr at 22?, 10–11.5 hr at 22?, 2 hr at 27?,
and 4–6 hr at 27?.
Preparation and analysis of RNA and proteins: RNA was
prepared as described previously (Yarden et al. 1992; Heint-
zen et al. 2001) and poly(A) RNA was extracted from total
RNA with a poly(A) tract kit according to the manufacturer’s
protocol (Promega, Madison, WI). Integrity of all RNAs were
verified by agarose gel and Northern blot analysis using genes
with known expression patterns as probes prior to poly(A)
RNAextraction.Northernblotswerepreparedandhybridized
according tostandard techniques (Maniatis et al.1982) using
DNA probes or riboprobes synthesized with DECAprime II kit
orStrip-EZRNAT3/T7kit(Ambion,Austin,TX).Preparation
of protein extracts, SDS-PAGE, and Western blot analysis were
performed as described before (Denault et al. 2001).
Generationofaunigenelibraryandmicroarraypreparation:
The generation of two time-of-day-specific N. crassa cDNA

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925Temperature Regulation of Clock-Controlled Genes
solution(50%formamide,5? SSC,0.1%SDS)andhybridized
inthepresenceof0.1?g/?lssDNAand0.2 ?g/?ltRNA(both
Sigma)for16hrat42?.Foreachtemperatureexperiment,five
or six samples corresponding to five or six different time
points for frq wild type and frq10, respectively, were labeled
with Cy3 and Cy5, respectively,and hybridized to five different
slides so that the corresponding time points of the two differ-
ent strains were hybridized to the same slide. In repeat experi-
ments, dyes were exchanged between the strains. Slides were
washed twice (1 min and 5 min) in 2? SSC, 0.1% SDS, 10
min in 0.1? SSC, 0.1% SDS, and 1 min in 0.1? SSC. They
were briefly rinsed first in distilled water and then in 95%
ethanol and dried by a brief centrifugation step. All washes
were done at room temperature except the first one (42?).
Slides were scanned using a GMS 418 Scanner (Affymetrix)
and stored as tiff files.
Primary microarray data analysis: Analysis of tiff files from
arrays was done with ScanAlyze (written by Michael Eisen,
Stanford University, http:/ /rana.lbl.gov/EisenSoftware.htm).
Grids were predefined and manually adjusted to ensure opti-
mal spot recognition. Spots with dust or locally high back-
ground were discarded. The resulting data files were further
analyzed in Excel (Microsoft, Redmond, WA) or by using
Cluster and Treeview (Eisen et al. 1998). Thresholds for
CH1GTB1 andCH2GTB1 valuescalculated byScanAlyze were
set to ?0.55 or ?0.65 to eliminate spots that had signals
not significantly above background levels. For the final data
analysis, data points were averaged from two replicates for
each PCR product on each slide. To correct for differences
between slides or for uneven loss of samples during target
preparation, one of the following normalization methods was
employed: For time courses in DD, the “experimental RNA”
value(foreachspotontheslide)wasdividedbythe“reference
RNA” value for each spot. Alternatively, for normalization
within time courses, the average fluorescence value for the
whole slide was determined for each slide within an experi-
mental series and a normalization factor was determined. The
resulting expression patterns after normalization for pre-
viously characterized control genes were similar to the ex-
pected behavior, thereby verifying that our microarray hybrid-
izations couldreproducibly detect changes ingene expression
patterns.
For the time course experiments, the corrected value for
each cDNA clone was divided by the value of DD24 [24 hr in
darkness, equal to circadian time (CT) 15 for strain 87-3] or
the value of DD32 (equal to CT15 for strain 585-7), thereby
setting the CT15 value for each clone at 1. The CT15 value
is typically the trough of the rhythm. The resulting values give
the amplitude of change for each cDNA clone within a time
courserelativetoCT15.CTisaformalismwherebytheendoge-
nous circadian biological day (22 hr in the wild type, 29 hr
in frq7) is divided into 24 equal parts so that equivalent phases
inthecyclecanbecomparedinstrainshavingdifferentperiod
length.Byconvention,CT0correspondstosubjectivedawnon
a12hr/12hrlight/darkcycle,soCT15correspondsroughlyto
3 hr after subjective dusk. Normalization of the temperature-
entrainment experiments was done similarly to the experi-
ments under free-running conditions (DD) in that the expres-
sion value for each gene at one of the five or six time points
(usually 10 hr or 11.5 hr at 27?) was set to 1. Expression values
at the other four time points are then given in relation to this
time point. Alternatively, expression levels were compared
between the wild type and the frq10mutant strain by dividing
the wild-type value for each cDNA clone by the frq10value.
Using this method of normalization allowed us to focus on
changes within the expression of a given gene by eliminating
information about absolute expression levels. Normalized ex-
pression values for all microarray experiments can be found
in the supplemental Table S1 at http:/ /www.genetics.org/sup
plemental/.
Microarray data analysis to identify clock-controlled and
temperature-regulated genes: After normalization as de-
scribedabove,microarraydatafromfree-runningandtemper-
ature-entrainment time courses were subjected to the follow-
ing analysis to identify cycling genes: The resulting data files
were further analyzed in Excel (Microsoft) and using Cluster
and Treeview (Eisen et al. 1998) to find clones that fulfilled
the following criteria: (1) Expression patterns are consistent
with clock control (one peak and one trough ?12 hr apart
in wild type connected by increasing or decreasing values,
respectively, within the observed time span) in at least three
out of the four experiments; (2) amplitudes are at least 2-fold
in one and at least 1.8-fold and 1.5-fold in the other two
experiments; and (3) peaks and troughs of expression for the
individualexperimentsareinphase(nomorethan4hrapart).
Data files from free-running experiments were additionally
analyzedusingtheCORRCOSalgorithm(M.Straume,Univer-
sityof VirginiaCenter forBiomathematical Technology,Char-
lottesville, VA) as initially described in Harmer et al. (2000)
and also as used by Duffield et al. (2002) to identify clock-
controlled genes. CORRCOS empirically tests for statistically
significant(P?0.05)cross-correlationbetweenthetimeseries
arising from hybridization to each microarray probe and co-
sine waves of specific period and phase. A significant correla-
tion with a cosine wave of an optimal period between 18 and
28hrisreportedbythealgorithm.Theanalysisisindependent
of signal strength and amplitude of change. The CORRCOS
algorithm was used to identify rhythmic expression patterns
in the four free-running time course experiments. Genes that
were identified in at least two out of the four experiments
were carefully reexamined to determine whether they were
consistent with the criteria described under 1–3. For the free-
running experiments, both the CORRCOS analysis, which is
amplitude independent, and the analysis using Excel, Cluster,
and Treeview, identified several genes that generally had cy-
cling expression patterns but did not meet the amplitude
criteria or were rhythmic in only two out of four experiments.
These genes, which might comprise a set of weak clock-con-
trolledgenes,canbefoundinsupplementalTableS2athttp:/ /
www.genetics.org/supplemental/.
Supplementary data and tables: Primary data and analyses
too extensive to be printed in the journal have been deposited
in a publicly accessible form at http:/ /www.genetics.org/sup
plemental/.
RESULTS
We have assembled an N. crassa unigene library from
two existing cDNA libraries (Zhu et al. 2001). The uni-
gene library represents ?1000 different genes and was
used to generate cDNA microarrays. With these arrays, we
examined the changes that occur in the abundance of
transcripts during the course of the circadian day and
during temperature-entrainment conditions. A table with
hybridization results can be found in the supplementary
material (supplemental Table S1 at http:/ /www.genetics.
org/supplemental/). In general, we found that microar-
rays accurately reported qualitative changes in gene ex-
pression known to occur from previous work, but quan-
titatively revealed smaller responses than prior Northern
blot or real time-PCR approaches did, as had also been

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926 M. Nowrousian et al.
foundbyotherstudiesinourownandotherlaboratories
(Duffield et al. 2002).
Identification of clock-controlled genes: For time
courses in DD, five different time points spanning a
circadian cycle were investigated in each experiment.
Three independent experiments were carried out with
tissues from a clock wild-type strain (strain 87-3, frq?,
period length 21.6 hr) and one experiment was per-
formed using a frq7mutant (strain 585-7). This mutant
has a period length (29 hr) longer than that of the wild
type and is used to verify that gene expression patterns
thatappeartoberhythmicaretrulyundercontrolofthe
circadianclockratherthanofdevelopmentalregulation
(Loros et al. 1989; Bell-Pedersen et al. 1996b). For
the experiments with the wild-type and the frq7strains,
DD times were chosen to correspond to similar CTs,
thereby allowing a direct comparison between the wild-
type and the frq7samples. The time courses used for
array hybridization experiments were chosen to cover
almost an entire circadian day (CT1–CT19) to allow
observation of at least onepeak and trough of transcript
abundance for each clock-regulated gene. Genes with
expression patterns consistent with clock control were
identified using two different data analysis methods: In
one approach, genes were analyzed according to their
expression patterns and amplitudes using Excel, Clus-
ter, and Treeview (see materials and methods for
details); in the second approach, we used the COR-
RCOS algorithm to identify cycling genes. With both
methods, several previously known clock-controlled
genes, e.g., ccg-1, eas (ccg-2), ccg-13, and lyz (Loros et al.
1989; Zhu et al. 2001) were among the genes identified.
In general, CORRCOS identified fewer rhythmic genes
than the other approach, probably reflecting the rela-
tively short time courses that were used for the four
experiments.
Using a combination of these two approaches, 27
genes were identified as robustly clock controlled (Fig-
ure 1, Table 1). [Table 1 associates unigene/EST clone
names with corresponding unique locus identifier
(NCU) numbers found in the annotated Neurospora
genomic sequence at http:/ /www-genome.wi.mit.edu/
annotation/fungi/neurospora/.] Six of these were
found to be strongly rhythmically expressed in all four
experiments;amongthesearetheknownrobustlyclock-
controlled genes ccg-1, eas (ccg-2), ccg-13, and ccg-14
(Loros et al. 1989; Zhu et al. 2001). The other two
strongly rhythmic genes (unigene clones UBh05 and
ULd10, neither of which has significant homology to
genes previously associated with a phenotype) had not
previously been identified. Some other genes that have
been identified previously as clock controlled did not
meet the threshold criteria, but we found in a previous
study that ccgs vary greatly with respect to the level of
clock control (Zhu et al. 2001), and our use of stringent
thresholdsmightleadtoexclusionofmoreweaklyclock-
controlled genes. Also, tissues used in this investigation
were grown in medium with 2% glucose, a condition
that increases the amplitudes of several known clock-
controlled genes but decreases amplitudes of others
(Bell-Pedersen et al. 1996b). All the putative clock-
controlled genes that were identified show peaks in ex-
pression late in the subjective night or early in the sub-
jective morning (CT19–CT6). These data establish a
broad baseline characterization by identifying ?2.7%
of the genes as being regulated by circadian rhythms at
the level of RNA abundance. An additional 32 genes
that showed rhythmic expression patterns but did not
meet the threshold criteria with respect to amplitude,
or showed cycling expression in only two of four experi-
ments, might comprise a set of weakly clock-controlled
genes (see the supplemental Table S2 at http:/ /www.
genetics.org/supplemental/).
To verify our array results, we tested six genes by
Northern blot analysis (Figure 1C; due to space con-
straints, only two time courses are shown). For all genes,
atleasttwoNorthernblotswithRNAsfromindependent
time courses were investigated; one time course origi-
nated from the wild type and one from a frq7mutant
(strain 585-7). The Northern analyses confirmed our
array data and demonstrated that amplitudes of 1.5- to
2-fold on arrays, which could reproducibly be followed
?
Figure 1.—Clock-controlled and temperature-regulated gene expression. Clusterand Northern blot analysis of clock-controlled
and temperature-dependent gene expression of a subset of genes from the microarrays. (A) Cluster analysis and visualization
were done with Cluster and Treeview (Eisen et al. 1998). The graph shows three out of four array experiments carried out under
free-running conditions, or temperature-entrainment conditions, and the ratios for frq?/frq10at the end of the warm temperature
period (first time point in each temperature-entrainment experiment) for all four experiments. Growth conditions are indicated
above each experiment. The cluster is divided into three sections, the top section containing genes that are both clock controlled
and temperature regulated in the wild type, the middle section containing genes that are clock controlled but not robustly
temperature regulated, and the bottom section contains a selection of genes that are not regulated under either condition.
Unigene clone numbers are given on the right, and their identities, when known, are given in Table 1 along with their unique
genome annotation locus identifiers. (B) Representation of one of the genes from each subset from A; labeling of the x-axis
indicateshoursintherespectivetemperaturefortemperature-entrainmentexperimentsorCTtimesforfree-runningexperiments.
(C) Northern blot verification of two newly identified clock-controlled genes. Total RNA (30 ?g/lane) was extracted from the
frq7strain after growth in darkness for the indicated times in DD. The corresponding CT is given below the DD values. Below
each blot, values (normalized to ethidium-bromide-stained rRNAs on the gels) are plotted. The lowest value was set to 1.
Riboprobes used are indicated in the graph. For each gene, two independent RNA sets were hybridized; only one is shown in
this figure.

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927 Temperature Regulation of Clock-Controlled Genes