letters to nature
Electrophysiology

Acknowledgements

Brain slices were prepared essentially as described29. IPSCs and population spikes were
evoked by square pulse stimuli (0.066 Hz, 5–12 mA, 200 ms) delivered by means of bipolar
tungsten electrodes positioned within the lateral amygdala close to the external capsule.
Population spikes were recorded in the basolateral amygdala close to lateral amygdalausing glass microelectrodes (2–3 MQ) filled with artificial cerebrospinal fluid (ACSF)29.
HFS (five trains at 100 Hz for 1 s, 10-s interstimulus interval) was applied to induce LTP,
and LFS1 (900 pulses at 1 Hz) was applied to induce LTD. Whole-cell GABA-mediatedcurrents were isolated by adding NBQX (0.005 mM) and D-(-)-2-amino-5phosphopentanoic acid (AP5; 0.05 mM) to ACSF (bubbled with 95% O2/5% CO2; pH7.3), and were recorded from visually identified somata of principal neurons of thebasolateral amygdala30 by glass electrodes (4.5–5 MQ)16 containing (in mM): Mg-ATP 2,
CsCH3SO3 100, CsCl 60, EGTA 0.2, HEPES 10, MgCl2 1, QX314 5 and Na3GTP 0.3 (pH7.3). Patch clamp experiments were performed at 24 ^ 1 8C at a holding potential of
270 mV. LTDi was induced by 100 stimuli at 1 Hz (LFS 2). PPF was induced as described30.
Data are expressed as means ^ s.e.m. We tested significance using the Student’s t-test.

S.C.A., T.B. and G.R. contributed equally to this work. We thank S. Bourier, B. Brachvogel
and W. Wurst for feeder cells and technical support; K. Pfeffer for E14 embryonic stem
cells; K. Rajewsky for Cre deleter mouse line; B. Lüscher for FRT-flanked PGK-neo
cassette; M. Wiedemann, H. Dietrich, B. Wölfel, A. Daschner, F. Fezza and A. Rippl fortechnical assistance, mouse breeding and genotyping; A. Mederer for help withbehavioural experiments; F. Holsboer for continuous support; E. Güll for secretarial work;
and C. Behl for critically reading the manuscript.

Competing interests statement
The authors declare that they have no competing financial interests.
Correspondence and requests for materials should be addressed to B.L.
(e-mail: lutz@mpipsykl.mpg.de).

Received 24 December 2001; accepted 16 April 2002; doi:10.1038/nature00839.
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Supplementary Information accompanies the paper on Nature’s website(http://www.nature.com/nature).

534..............................................................

A transcription factor response
element for gene expression
during circadian night
Hiroki R. Ueda*†, Wenbin Chen*, Akihito Adachi‡, Hisanori Wakamatsu*,
Satoko Hayashi*, Tomohiro Takasugi*, Mamoru Nagano‡Ken-ichi Nakahama‡, Yutaka Suzuki§, Sumio Sugano§,
Masamitsu Iino†, Yasufumi Shigeyoshi‡ & Seiichi Hashimoto** Molecular Medicine Laboratories, Institute for Drug Discovery Research,
Yamanouchi Pharmaceutical Company, Ltd, 21 Miyukigaoka, Tsukuba, Ibaraki
305-8585, Japan† Department of Pharmacology, Graduate School of Medicine, The University ofTokyo, 7-3-1 Bunkyo-ku, Tokyo 113-0033, Japan‡ Department of Anatomy and Neurobiology, Kinki University School of Medicine,377-2 Ohno-Higashi, Osakasayama City, Osaka 589-8511, Japan§ Human Genome Center, Institute of Medical Science, The University of Tokyo,
4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan.............................................................................................................................................................................

Mammalian circadian clocks consist of complex integrated feedback loops1–10 that cannot be elucidated without comprehensive
measurement of system dynamics and determination of network
structures11. To dissect such a complicated system, we took asystems-biological approach based on genomic, molecular andcell biological techniques. We profiled suprachiasmatic nuclei
and liver genome-wide expression patterns under light/darkcycles and constant darkness. We determined transcription
start sites of human orthologues for newly identified cycling
genes and then performed bioinformatical searches for relationships between time-of-day specific expression and transcription
factor response elements around transcription start sites. Here
we demonstrate the role of the Rev-ErbA/ROR response elementin gene expression during circadian night, which is in phase with
Bmal1 and in antiphase to Per2 oscillations. This role was verified
using an in vitro validation system, in which cultured fibroblasts
transiently transfected with clock-controlled reporter vectors
exhibited robust circadian bioluminescence12.
To perform comprehensive measurement of mammalian circadian gene expression, we profiled genome-wide expression patternsof central (suprachiasmatic nuclei, SCN) and peripheral (liver)clocks every four hours during light/dark cycles (LD) or constantdarkness (DD) over two days. We extracted total RNA from 50
pooled SCNs and four pooled livers at each time point, preparedbiotinylated complementary RNA and used an Affymetrix mousehigh-density oligonucleotide probe array (GeneChip) to determine
SCN and liver gene expression.
The data obtained were analysed through two statistical cosine
filters, one for LD and the other for DD time courses (see© 2002 Nature Publishing Group

NATURE | VOL 418 | 1 AUGUST 2002 | www.nature.com/natureletters to nature
Supplementary Information), to identify a set of genes rhythmically
expressed under both LD and DD. On the basis of two successive
filtrations, we classified 101 genes in the SCN and 393 genes in theliver as ‘significantly rhythmic under both LD and DD’. In addition,
we found two genes in the liver, Rgs16 and Hsp70-1, with high 24-h
autocorrelation under LD and DD and high cross-correlation
between LD and DD liver expression profiles (see Supplementary
Information), but without high correlation with the cosine curves.
In total, we identified 101 genes in the SCN and 395 genes in the liver(Supplementary Information Tables 1 and 2). We also found 21
genes rhythmically expressed in both tissues (Supplementary Information Table 3). These are likely to be the minimum numbers ofgenes rhythmically expressed under both LD and DD in the SCN
and/or liver; the number may increase if different filtration cut-off
values are applied. Random profiles produced 18 and 13 samples
classified as ‘rhythmic under both LD and DD’ in the SCN and liver,respectively. Using this estimate, we concluded that we had ident-

ified a substantial number (,80 for the SCN and ,380 for the liver)of cycling genes.
Figures 1b and 2b display the cycling genes that we identified
from the SCN and liver expression profiles, ordered by the averaged
peak time between LD and DD (see Supplementary Information).
Peak times of periodic expression profiles are spread over 24 h.
When classified into 4-h interval groups ranging from CT0 (circadian time zero: the beginning of the subjective day) to CT24 (theend of subjective night, equal to CT0), we found the following
distribution of peak times in the SCN (Supplementary Information
Table 1): eight genes in CT0–4, 23 genes in CT4–8, 16 genes in CT8–12, 16 genes in CT12–16, 28 genes in CT16–20 and ten genes inCT20–24. We also found the following distribution in the liver(Supplementary Information Table 2): 91 genes in CT0–4, 71 genes
in CT4–8, 58 genes in CT8–12, 63 genes in CT12–16, 50 genes in
CT16–20 and 54 genes in CT20–24. The locations of these groups
are indicated in Figs 1b and 2b.

Figure 1 Temporal expression profiles in mouse suprachiasmatic nuclei. a, Periodic
expression of known clock-controlled genes in mouse SCN under light/dark cycles (LD)and constant darkness (DD). Data were normalized so that the average signal intensity
over 12-point time courses is 1.0. b, c, Organization of SCN expression profiles by peaktime (b) and hierarchical clustering (c). In both diagrams, columns represent time points,
and rows represent genes. The colours in descending order from red to black to green
represent the normalized data (the average and standard deviation over 12-point timecourses are 0.0 and 1.0, respectively).

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letters to nature
To cluster our cycling genes in accordance with the data, we
performed hierarchical clustering. Figures 1c and 2c display theentire organization of our cycling genes in the SCN and liver,respectively. We found four main clusters in the SCN: the RevErbA/Per2 cluster (35 genes, average phase at CT6.0), Cry1 cluster(15 genes, average phase at CT12.1), Bmal1 cluster (32 genes,
average phase at CT17.0) and Id2 cluster (eight genes, averagephase at CT20.8). We also found five main clusters in the liver: the
Rev-ErbA cluster (87 genes, average phase at CT8.0), Per2 cluster (75genes, average phase at CT13.2), Cry1 cluster (52 genes, averagephase at CT17.8), Bmal1 cluster (58 genes, average phase at CT20.5)
and Id cluster (107 genes, average phase at CT3.1). The locations ofthese clusters are indicated in Figs 1c and 2c (see Supplementary
Information Figs 1 and 2 for detailed results).
As an independent test, we measured the levels of expression
under DD of three to 12 genes for each cluster using the quantitative
polymerase chain reaction (PCR) assay in both SCN and liver. We

used the same samples that were used to prepare probes for
microarray hybridizations. The expression profiles of the genes, asmeasured by these two independent methods, were very similar inboth phase and amplitude (Supplementary Information Figs 3 and
4). These results confirmed our microarray measurements. To verify
further our SCN microarray measurements, we explored the spatiotemporal expression profiles under DD of the genes identified in the
SCN by an in situ hybridization study using 35S-labelled cRNA
probes (Fig. 3). The spatiotemporal expression profiles obtained
from the in situ hybridization study were highly consistent with thetemporal expression pattern obtained from the microarray experiments and further complement the microarray data because theirsignal intensity in the SCN is difficult to infer from microarray data.
Identification of more than 100 cycling genes in the SCN andnearly 400 cycling genes in the liver offered the opportunity to infer
the transcriptional control mechanisms generating circadian
expression. To do so, we analysed the promoter regions of newly

Figure 2 Temporal expression profiles in the mouse liver. a, Periodic expression of known
clock-controlled genes in mouse liver under LD and DD. Data were normalized so that the
average signal intensity over 12-point time courses is 1.0. b, c, Organization of liver
expression profiles by peak time (b) and hierarchical clustering (c). In both diagrams,

columns represent time points, and rows represent genes. The colours in descendingorder from red to black to green represent the normalized data (the average and standard
deviation over 12-point time courses are 0.0 and 1.0, respectively).

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identified cycling genes in the SCN and liver. One of the maindifficulties in analysing the promoter regions in higher eukaryotes,
such as humans, mice and rats, is the lack of precise positional
information of transcription start sites (TSSs). It is difficult to use
translation start codons to estimate promoter regions because inmany cases TSSs appear to be distant from translation initiationsites in higher eukaryotes. In fact, the TSS of the clock gene Bmal1 is
more than 60 kilobases (kb) away from the translation initiation
ATG codon10. The other difficulty in analysing the promoter regionsof mouse genes is the low coverage of publicly available sequence
information over the entire mouse genome.
To address these two difficulties, we systematically determined
the TSS of human orthologues of newly identified cycling genes by
the oligo-capping method13 (see Methods) and then mapping the
TSS onto the human genome, the draft sequence for which is
publicly available. This approach is based on the evidence thatcircadian systems are well conserved between human and mouse14,
and that the promoter region of the clock gene Per1 is highly
homologous in humans and mice15. We identified the TSS of 45 and189 human orthologues for cycling genes in the SCN and liver,respectively (Supplementary Information Tables 4 and 5). Using
positional information for these TSSs on the human genome, we
defined the adjacent sequences as the putative promoter regions. We

Figure 3 Spatiotemporal expression profiles in mouse SCN under DD conditions. Data forthe genes (Hmg4 (a), Ras-like protein 1190017B18Rik (b), Rgs16 (c), Oligoribonucleaselike protein 1810038D15Rik (d), Dexras1 (e), V1a (f), Pkib (g), Hsp105 (h), Id2 (i) andHsp40 (j)) consist of representative in situ hybridization autoradiograms of the SCN andquantitative graphs. Numbers above the radiograms indicate circadian time (h). Meansare indicated by solid lines and individual values by open circles (n ¼ 2).
NATURE | VOL 418 | 1 AUGUST 2002 | www.nature.com/naturethen searched for the relationship between circadian expression andknown circadian transcription factor response elements in the
retrieved promoter regions of these genes (see Supplementary
Information Tables 6 and 7 for detailed results).
We found seven cycling genes in the SCN with putative cyclic
AMP response elements (CRE: TGACGT16) in the promoter regionsof their orthologues, the phases of which consolidate to subjectiveday (circadian time, CT7.0 ^ 1.6, mean ^ s.d.). Phase consolidation of the genes with putative CRE is consistent with the previous
observation that the reporter gene, driven by a CRE-containing
promoter, displays clear circadian expression with a peak timeoccurring during subjective day in the SCN17.
We also found ten cycling genes in the SCN with putative RevErbA/ROR response elements (AGGTCA18), to which Rev-ErbA
and ROR family members bind, in the promoter regions of theirorthologues. The phases of these genes consolidate to subjective
night or dawn (CT19.2 ^ 3.3, mean ^ s.d.). The ten genes identified include Bmal1 and E4bp4, which display similar circadian
expressions antiphase to Per2 oscillations in both SCN and the liver(Figs 1 and 2). These observations suggest that Rev-ErbA/ROR
response elements play an important role in generating circadianoscillation antiphase to Per genes expression.
To explore the roles of Rev-ErbA/ROR response elements, we firstexamined in detail the spatiotemporal expression profiles in the
SCN of all entire Rev-ErbA and ROR family members shown to bindto the same Rev-ErbA/ROR response element19. Rev-ErbA, RevErbAb, RORa and RORb displayed similar circadian expression
profiles in the SCN, with peaks during the day and troughs during
the night (Fig. 4), whereas RORg was not detected in the SCN
throughout the 24-h cycle (data not shown). Rev-ErbAa, Rev-ErbAb
and RORa demonstrated dynamic oscillation and were expressedvery highly at CT4 (Rev-ErbAa and Rev-ErbAb) or CT8 (RORa),
with peak levels three times those of troughs. RORb showed
moderate to strong expression at every time point examined. The
amplitude of RORb oscillation was low compared with those of theother three genes in the family.
We also examined in detail the temporal expression profiles in theliver of the entire Rev-ErbA and ROR family by quantitative PCR.
Rev-ErbAa, Rev-ErbAb and RORg exhibited clear circadian oscillations (Supplementary Information Fig. 5) whereas RORa exhibited little or no circadian rhythmicity, and RORb was not detected in
the liver throughout the 24-h cycle (data not shown). Rev-ErbAaand Rev-ErbAb demonstrated dynamic oscillation, were very highly
expressed at CT4–8 (Rev-ErbAa) and CT8 (Rev-ErbAb), and had
peak levels more than 100 (Rev-ErbAa) and ten (Rev-ErbAb) times

Figure 4 Spatiotemporal profiles of expression of the Rev-ErbA and ROR family in themouse SCN under DD conditions. Representative in situ hybridization autoradiograms andgraphs of relative mRNA abundance are shown. Numbers above the radiograms indicate
circadian time (h). Means are indicated by solid lines and individual values by open circles(n ¼ 2).

© 2002 Nature Publishing Group

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letters to nature
trough levels. RORg also displayed clear oscillations, and was
expressed highly at CT16–20 with a peak level three times thetrough level.
To validate the hypothesized circadian circuit, we have developed
an in vitro clock-controlled element determination system12. We
created dLuc by fusing a rapid degradation domain modified frommouse ornithine decarboxylase to the carboxy-terminal end of
firefly luciferase. The rapid functional half-life of the dLuc proteins,
20–30 min, was suitable for probing circadian transcriptional
dynamics in real time12.
To verify the role of Rev-ErbA/ROR response elements in generating circadian expression antiphase to Per2 oscillation, we fused
the 60-base-pair promoter region of the Bmal1 promoter, containing wild-type and mutant Rev-ErbA/ROR response elements, to the
SV40 basic promoter driving a dLuc reporter gene (Fig. 5a). This 60base-pair region is completely conserved between human andmouse Bmal1 genes and is near the TSS in both cases. Transfection
experiments confirmed that the wild-type construct can be activated by RORa and repressed by Rev-ErbAa, and that the mutant
cannot (data not shown). To examine the circadian expression
driven by the Rev-ErbA/ROR response element, we transfected
these constructs into cultured Rat1-R12 fibroblasts, stimulatedwith dexamethasone, and measured luminescence from thesecells. Bioluminescence levels from the wild-type Rev-ErbA/ROR
response elements displayed circadian rhythmicity (Fig. 5d, n ¼ 3)
and the phase of their oscillations was in phase with the levels of
luminescence from the Bmal1 promoter fused to the destabilized
luciferase (Fig. 5c, n ¼ 3) and antiphase to those from the Per2
promoter (Fig. 5b, n ¼ 3). On the other hand, bioluminescencelevels from the mutant Rev-ErbA/ROR response elements exhibitedno circadian rhythmicity (Fig. 5e, n ¼ 3) and displayed lightemission patterns similar to those from the SV40 promoter alone(Fig. 5f, n ¼ 3). On the basis of these observations, we concluded
that Rev-ErbA/ROR response elements play an important role ingenerating circadian night expression in phase with Bmal1
expression and antiphase to Per2 expression.
We have thus analysed mammalian circadian rhythms on thebasis of genome-wide expression measurements, extensive determination of TSSs, bioinformatical search for transcription factor
response elements, and in vitro validation of clock-controlledelements. The power of this systems-biological approach is demonstrated by the discovery and validation of the function of Rev-ErbA/
ROR response elements in generating gene expression during
circadian night, which is in phase with Bmal1 and antiphase toPer2 expression. This approach can be applied to the analysis ofrecently described mammalian cycling genes20–24. Although efficientin vitro validation systems remain to be developed, the systemsbiological approach may be applicable to circadian rhythms inhigher eukaryotes such as Drosophila25–27 or Arabidopsis28, as well asother biological systems such as mammalian cell cycles29, in which
genome-wide expression profiles have been measured.
A

Methods
Microarray experiments
Slices (0.5 mm thick) of mouse brain were generated using Mouse Brain Matrix(Neuroscience) under LD or DD conditions, and then the SCNs were punched out
bilaterally from the frozen slices under a stereomicroscope with a microdissecting needle(gauge 0.5 mm). Livers were dissected and frozen in liquid nitrogen. Total RNA wasprepared from 50 pooled pairs of SCNs and four pooled livers at each time point using
Trizol reagent (GIBCO BRL). Complementary DNA synthesis and cRNA labelling
reactions were performed as previously described26. We used Affymetrix high-density
oligonucleotide arrays for Mus musculus (Murine Genome Array U74A) version 2 for SCN
expression and version 1 for liver expression profiling. Expression data and other systemsbiological information used in this paper will be available at the Database for Systems
Biology (http://www.dbsb.org/).

Animals
Balb/c mice (male) purchased five weeks postpartum were adapted to standard 12-h light/
12-h dark cycles (LD) for two weeks before samples were obtained under LD or constantdarkness (DD) conditions every 4 h starting at ZT0 (zeitgeber time zero) or CT0 over twodays.

In situ hybridization
The in situ hybridization and method of quantification of messenger RNA have been
described in detail previously30. Serial coronal sections (40 mm thick) of mouse brain wereprepared using a cryostat. Fragments of cDNA were obtained by PCRs, which were thensubcloned into PGEM-T easy vector (Promega). 35S-labelled sense and antisense probes
were transcribed using T7 or SP6 RNA polymerases. Antisense probes produced specifichybridization signals in the SCNs and/or other brain regions, whereas the sections
hybridized with the sense probes exhibited no specific signal. The radioactivity of eachsection on BioMax film (Kodak) was analysed using a microcomputer interfaced to an
image analysing system (MCID, Imaging Research) after conversion to relative opticaldensity using 14C-acrylic standards (Amersham). Data were normalized with respect tothe difference between signal intensities in equal areas of the SCN and the corpus callosum.
The optical densities of the sections from the rostralmost caudalmost portion of the SCNs
(ten sections per mouse) were then summed; the sum was used as the mRNA abundance inthis region. ‘Relative RNA abundance’ means that the peak value was adjusted to 100%.

Quantitative PCR

Figure 5 A Rev-ErbA/ROR response element sufficient for gene expression during
circadian night. a, Diagram of wild-type and mutant 60-base-pair Bmal1 promoter region
fused to the SV40 basic promoter driving a destabilized luciferase (dLuc) reporter gene.
The wild-type 60-base-pair region contains two putative Rev-ErbA/ROR response
elements. Well-conserved base pairs18 (bold) and mutated base pairs (italic) are indicated.
b, c, Representative circadian rhythms of bioluminescence from Per2 (b) and Bmal1 (c)promoter fused to a dLuc reporter gene. d–f, Representative circadian rhythms of
bioluminescence from wild-type (d) and mutant (e) constructs or from SV40 promoter (f)fused to a dLuc reporter gene.
538

To verify the microarray results, quantitative PCR was performed with the ABI Prism 7700
and SYBR Green Reagents (Applied Biosystems). cDNAs were synthesized from 0.5 mg of
total RNA using Superscript II reverse transcriptase (Invitrogen). Samples contained 1 £SYBR Green Master Mix, 0.5 mM primers and 1/40 synthesized cDNA in a 25 ml volume.
The PCR conditions were as follows: 10 min at 95 8C, then 40 cycles of 15 s at 94 8C, 30 s at
60 8C and 1 min at 72 8C. Absolute cDNA abundance was calculated using the standard
curve obtained from mouse genomic DNAs. We used GAPDH as an internal control.

Determination of transcription start sites
In order to determine TSSs, oligo-capping was performed as described previously13 using
10 mg of polyA þ RNA isolated from whole human brain, cerebellum and liver. cDNA wassynthesized using a Thermoscript (Gibco BRL) from the oligo-capped mRNA andamplified by nested PCR with outer and inner 5 0 primers complementary to the capreplacing oligo sequence and outer and inner 3 0 gene-specific primers. The PCR products
were purified and sequenced. TSSs were identified precisely as the oligo-capped sites of thecDNAs.

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NATURE | VOL 418 | 1 AUGUST 2002 | www.nature.com/natureletters to nature
Constructs
The wild-type Rev-ErbA/ROR response element and mutant Rev-ErbA/ROR response
element were constructed as follows: the following oligonucleotides were inserted into the
SmaI site of the SV40-dLuc vector12. WT:5 0 -GATTGGTCGGAAAGTAGGTTAGTGG
TGCGACATTTAGGGAAGGCAGAAAGTAGGTCAGGGACGGAGG-3 0 . Mutant:
5 0 -GATTGGTCGGAAAGTCCTAGCGTGGTGCGACATTTAGGGAAGGCAGAAAGTCCTAGCGGGACGGAGG-3 0 . The constructs were verified by sequencing.

Transfection and real-time monitoring of circadian bioluminescence
Rat1-R12 cells (ATCC) were grown in Dulbecco’s modified Eagle’s medium supplemented
with 10% fetal bovine serum (Sigma). Cells were plated at 1.0 £ 106 cells per dish in 35-mm
dishes 24 h before transfection. Cells were transfected with LipofectAMINE 2000 reagent(GIBCO BRL) according to the manufacturer’s instructions. Cells in each dish weretransfected with 1 mg (total) of expression plasmids. After 16 h, cells in each dish were treatedwith 0.1 mM dexamethasone (Sigma), and after 2 h these media were replaced with 2 ml
culture medium (Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine
serum (Sigma)) supplemented with 10 mM HEPES (pH 7.2), 0.1 mM luciferin (Promega),
and antibiotics (25 U ml21 penicillin, 25 mg ml21 streptomycin). Bioluminescence wasmeasured with photomultiplier tube (PMT) detector assemblies (Hamamatsu). The
modules and cultures were maintained in a light-tight incubator at 36 8C and interfaced to
IBM PC-type computers for continuous data acquisition. The PMT was positioned about
2 cm above the culture, and photon counts were integrated over 1-min intervals.
Received 12 April; accepted 5 June 2002; doi:10.1038/nature00906.
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2. Bunger, M. K. et al. Mop3 is an essential component of the master circadian pacemaker in mammals.
Cell 103, 1009–1017 (2000).
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NATURE | VOL 418 | 1 AUGUST 2002 | www.nature.com/nature

Supplementary Information accompanies the paper on Nature’s website(http://www.nature.com/nature).

Acknowledgements
We thank T. Kojima, T. Katakura and H. Urata for technical assistance. This study was
performed as a part of a research and development project of the Industrial Science andTechnology Program supported by NEDO (New Energy and Industrial Technology
Development Organization).

Competing interests statement
The authors declare that they have no competing financial interests.
Correspondence and requests for materials should be addressed to H.R.U.
(e-mail: hiro@m.u-tokyo.ac.jp) or to Y.S. (e-mail: shigey@med.kindai.ac.jp).

..............................................................

A re-examination of proximodistal
patterning during vertebrate limb
development
Andrew T. Dudley*, Marı́a A. Ros† & Clifford J. Tabin** Department of Genetics, Harvard Medical School, 200 Longwood Avenue,
Boston, Massachusetts 02115, USA† Departamento de Anatomı́a y Biologı́a Celular, Facultad de Medicina,
Universidad de Cantabria, 39011 Santander, Espana.............................................................................................................................................................................

The ‘progress zone’ model provides a framework for understanding progressive development of the vertebrate limb1. This modelholds that undifferentiated cells in a zone of fixed size at the distal
tip of the limb bud (the progress zone) undergo a progressivechange in positional information such that their specification isaltered from more proximal to more distal fates. This positionalchange is thought to be driven by an internal clock that is kept
active as long as the cells remain in the progress zone. However,owing to cell division, the most proximal of these cells arecontinually pushed outside the confines of the zone. As they
exit, clock function ceases and cells become fixed with thepositional value last attained while within the zone. In contrast
to this model, our data suggest that the various limb segments are‘specified’ early in limb development as distinct domains, withsubsequent development involving expansion of these progenitor
populations before differentiation. We also find, however, thatthe distal limb mesenchyme becomes progressively ‘determined’,that is, irreversibly fixed, to a progressively limited range ofpotential proximodistal fates.
Overlying the progress zone is a ridge of pseudostratified epithelium, known as the apical ectodermal ridge (AER), which runs
along the anterior–posterior rim of the distal tip of the limb bud2.
When the AER is removed, the limb fails to form distal structures,
suggesting that patterning of the distal limb is dependent on the
AER3. The observation that less severe truncations result when the
AER is removed at progressively later stages has been taken as strong
evidence in support of the progress zone model. In this context, a‘specification map’ for the formation of the skeletal elements of thechick wing has been proposed on the basis of examination oftruncations resulting from AER removal at various stages4. We
noted, however, that other reports have shown that, after removal of
the AER, some distal mesenchyme cells are eliminated by cell death.
In particular, one study detected a region of cell death extending
200 mm from the distal tip within 4 h after AER removal at stage 22(ref. 5). We reasoned that if this region of cell death remained
constant in size at every stage, then a proportionally larger part of© 2002 Nature Publishing Group

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