Developmental Cell Article - COnnecting REpositories › download › pdf › 81121267.pdf · Developmental Cell Article Balanced Nucleocytosolic Partitioning Deﬁnes a Spatial Network

Developmental Cell

Article

Balanced Nucleocytosolic PartitioningDefines a Spatial Network to CoordinateCircadian Physiology in PlantsYumi Kim,1,10 Seungmin Han,2,10 Miji Yeom,3 Hyunmin Kim,3 Junhyun Lim,4 Joon-Yung Cha,6 Woe-Yeon Kim,6

David E. Somers,4,7 Joanna Putterill,8 Hong Gil Nam,1,9,* and Daehee Hwang2,4,5,*1Department of New Biology, DGIST, Daegu 711-873, Republic of Korea2School of Interdisciplinary Bioscience and Bioengineering3Division of Molecular and Life Sciences4Division of Integrative Biosciences and Biotechnology5Department of Chemical Engineering

Pohang University of Science and Technology, Pohang, Kyungbuk 790-784, Republic of Korea6Division of Applied Life Science (BK21 Program), Gyeongsang National University, Jinju, Kyungnam 660-701, Republic of Korea7Department of Molecular Genetics, The Ohio State University, Columbus, OH 43210, USA8Plant Molecular Sciences, School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand9Center for Systems Biology of Plant Senescence and Life History, Institute for Basic Science, Daegu 711-873, Republic of Korea10These authors contributed equally to this work

*Correspondence: [email protected] (H.G.N.), [email protected] (D.H.)

http://dx.doi.org/10.1016/j.devcel.2013.06.006

SUMMARY

Biological networks consist of a defined set of regu-latory motifs. Subcellular compartmentalization ofregulatory molecules can provide a further dimen-sion in implementing regulatory motifs. However,spatial regulatory motifs and their roles in biologicalnetworks have rarely been explored. Here we show,using experimentation and mathematical modeling,that spatial segregation of GIGANTEA (GI), a criticalcomponent of plant circadian systems, into nuclearand cytosolic compartments leads to differentialfunctions as positive and negative regulators of thecircadian core gene, LHY, forming an incoherentfeedforward loop to regulate LHY. This regulatorymotif formed by nucleocytoplasmic partitioningof GI confers, through the balanced operation ofthe nuclear and cytosolic GI, strong rhythmicity androbustness to external and internal noises to thecircadian system. Our results show that spatial andfunctional segregation of a single molecule speciesinto different cellular compartments provides ameans for extending the regulatory capabilities ofbiological networks.

INTRODUCTION

Living organisms execute cellular functions through the opera-

tion of biological networks. These networks are composed

of recurring regulatory building blocks, referred to as network

motifs (Milo et al., 2002). A network motif is defined by a set of

molecules and their interactions. Network motifs, such as feed-

back and feedforward loops, serve as basic building blocks that

D

collectively confer regulatory capability of biological networks.

The functional roles of the network motifs in controlling induction

and repression kinetics of target genes have been studied in

transcriptional regulatory and signaling networks (Mangan and

Alon, 2003).

Cells employ compartmentalization of the internal space,

which confines particular proteins in each cellular compartment.

Proteins localized at the same subcellular compartment are

often functionally associated through their interactions. On the

other hand, a large number of proteins, up to more than 35%

(King and Guda, 2007; Zhang et al., 2008), are localized at

multiple compartments. The spatially segregated proteins often

have different regulatory functions (Chung and Eng, 2005; Garcıa

et al., 2010; Wu and Spalding, 2007). These molecules can form

spatial regulatory motifs. Thus, spatial segregation of a molecule

into subcellular compartments can provide a further dimension

to form regulatory motifs in biological networks (Scott and Paw-

son, 2009). Unfolding the regulatory modes of network motifs in

space increases the degree of freedom for construction of the

network motifs, which may enhance regulatory capability of

biological networks. However, spatial regulatory motifs and their

roles to regulate complex physiological processes have not been

investigated.

The plant circadian network has been amodel system to study

regulatorymotifs and their roles (Alabadı et al., 2001; Locke et al.,

2005). The circadian system in Arabidopsis controls the rhythmic

expression of genes involved in diverse physiological processes,

such as starchmetabolism, photosynthesis, defense, and photo-

periodic flowering (Covington et al., 2008; Dodd et al., 2005;

Harmer et al., 2000; Michael et al., 2008a, 2008b; Putterill et al.,

2004). The rhythmic expression of these genes is highly coordi-

nated with adaptive relevance to the daily cycle by various inter-

locking regulatorymotifs (deMontaigu et al., 2010;Harmer, 2009;

McClung, 2008; Pokhilko et al., 2010, 2012). However, the regu-

latory motifs in the plant circadian network have been studied

with little consideration of the spatial dimension. Components

evelopmental Cell 26, 73–85, July 15, 2013 ª2013 Elsevier Inc. 73

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Developmental Cell

Spatial Circadain Network

of the circadian system are present in the cytosol, the nucleus,

or both (Table S1 available online). GIGANTEA (GI) is a critical

component in the circadian system, which controls the circadian

period and amplitude in plants (Park et al., 1999). GI expression is

negatively regulated by the circadian core clock gene, LATE

ELONGATED HYPOCOTYL (LHY) (Knowles et al., 2008; Mizogu-

chi et al., 2002). GI also regulates transcription of LHY (Fowler

et al., 1999; Park et al., 1999). GI localizes to both the nucleus

and the cytoplasm (Kim et al., 2007). Day-length-dependent

flowering, a circadian output, is mostly regulated by nuclear GI

(Fornara et al., 2009; Gunl et al., 2009; Sawa and Kay, 2011;

Sawa et al., 2007; Suarez-Lopez et al., 2001). At the same time,

the stability of a cytosol-localized circadian input, ZEITLUPE

(ZTL), is regulated by GI (Kim et al., 2007). This suggests that

partitioning of GI into the nucleus and cytosol may provide

spatially differentiated functions.

We reasoned that the plant circadian system might have

adopted nucleocytoplasmic partitioning as a regulatory mech-

anism to coordinate diverse physiological outputs. Through

integration of computational modeling and experimentations

using transgenic plants with nuclear and cytosol-enriched GI,

we demonstrate that the spatial segregation of a molecule GI

is encoded into a network motif, which can lead to enhanced

regulatory capability of the circadian network involving GI in con-

trolling the circadian rhythmicity (i.e., phase, shape, and ampli-

tude) of the core oscillator LHY and also coordinating circadian

physiology, such as flowering and photosynthesis.

RESULTS

Spatially Differentiated Roles of GIFirst, we used gi-2 mutant plants to generate transgenic

Arabidopsis plants. gi-2 is a null mutation of the GI gene that is

caused by 8 bp deletions in the fourth exon and leads to a

premature stop codon at 144 amino acid. The transgenic

Arabidopsis plants expressed GI fused to green fluorescent pro-

tein gene (GIpro::GI-GFP), GI-GFP with a nuclear localization

signal (Kalderon et al., 1984) (GIpro::GI-GFP-NLS), or GI-GFP

with a nuclear export signal (Henderson and Eleftheriou, 2000)

(GIpro::GI-GFP-NES) under the control of the native promoter

(Figures S1A–S1D). The transgenic gi-2 plants expressing

GIpro::GI-GFP-NLS (called GI-NLS plants) and the gi-2 plants

expressing GIpro::GI-GFP-NES (calledGI-NES plants) preferen-

tially produced GI-GFP in the nucleus and cytosol, respectively,

although residual amounts of nuclear and cytosolic GI were still

present in GI-NES and GI-NLS plants, respectively (Figure S1D).

We then examined alterations of circadian physiology, such as

flowering time and seedling growth, in our transgenic plants.

GIpro::GI-GFP complemented the two circadian physiological

lesions altered by the gi-2 mutation (Figures 1A and 1B). In

contrast, GI-NLS and GI-NES differentially complemented the

circadian lesions:GI-NLS complemented flowering and seedling

growth, whereas GI-NES complemented seedling growth (Fig-

ures 1A and 1B). This differential complementation is recapitu-

lated in other transgenic plants that were generated in gi-ko,

a T-DNA insertional mutant showing null expression of GI

(Figures S1E and S1F). GI controls stability of a clock regulatory

protein, ZTL (Kim et al., 2007). GI-NES was more effective in

controlling the stability of ZTL (Figure 1C). To systematically

74 Developmental Cell 26, 73–85, July 15, 2013 ª2013 Elsevier Inc.

investigate this differential complementation, we performed a

genome-wide gene expression analysis of wild-type (WT; Col),

gi-2, GI-NLS, and GI-NES plants grown under conditions of

16 hr light and 8 hr dark (LD) at 1 hr (Zeitgeber time 1, ZT1) and

16 hr (ZT16) after the light is turned on, representingmorning and

evening, respectively (Figure 1D). In the gi-2mutant, the expres-

sion levels of 924 and 1,014 genes were significantly altered at

ZT1 and ZT16, respectively (see Figure 1D and Tables S2A–

S2C for the lists of the significantly altered genes at ZT1 and

ZT16 and Figure S1G for validation of a subset of these altered

genes by quantitative real-time PCR). The complementation of

the gi-2 mutation by GI-NLS and GI-NES can be categorized

into the four patterns (patterns 1–4). Pattern 1 includes genes

predominantly regulated by nuclear GI (GIN), whereas pattern 2

includes genes predominantly regulated by cytosolic GI (GIC).

Thus, patterns 1 and 2 indicate that nuclear and cytosolic GI con-

trol independent functions depending on spatial location.

Pattern 3 includes genes regulated by either GIN or GIC, implying

that transcriptional regulation of these genes requires the action

of only one of GIN and GIC. In contrast, pattern 4 includes genes

whose transcriptional regulation requires the action of both GINand GIC. Patterns 3 and 4 suggest that functions of nuclear

and cytosolic GI, albeit physically separated, are interlinked,

leading to coordinately regulated physiological outputs. The

number and function of genes in each complementation pattern

at ZT16 are different from those at ZT1, indicating that the tran-

scriptional regulatory networks governed by GI may differ

depending on the phase of the circadian cycle. GIpro::GI-GFP

conferred restoration of expression of 25%–75% of the genes

in each pattern (Figures S1H and S1I; see Discussion for details).

Identification of the Nuclear and Cytosolic GI-LHYNetwork by Mathematical ModelingThese results indicate that the spatial segregation of GI has a

fundamental role in regulating and coordinating diverse circa-

dian physiological processes through daily changes of the

expression of hundreds of genes. How is spatially segregated

GI in the nucleus and cytosol then incorporated into the circadian

system to regulate daily changes of the gene expression?

In Arabidopsis, LHY / CIRCADIAN CLOCK ASSOCIATED 1

(CCA1) and TIMING OF CAB EXPRESSION 1 (TOC1) form a

core oscillator, in which LHY represents the morning component

and TOC1 the evening component (Alabadı et al., 2001). The

absence of GI in the gi-2 mutant led to markedly reduced LHY

expression under diurnal conditions, as reported previously

(Fowler et al., 1999; Park et al., 1999). LHY expression was

completely restored byGI-NLS but only partially byGI-NES (Fig-

ure 2A). In contrast, TOC1was not affected by the gi-2mutation,

consistent with previous reports (Figure S2A) (Gunl et al., 2009;

Kim et al., 2007; Martin-Tryon et al., 2007). GI also controls the

free-running circadian rhythms of LHY expression (Park et al.,

1999). The gi-2 mutation substantially reduced the peak ampli-

tude of LHY rhythm with a delayed phase under the free-running

conditions (Figure 2B). This reduced LHY amplitude was largely

restored by GI-NLS. GI-NES increased rhythmic LHY expres-

sion, but with a reduced amplitude. Both GI-NLS and GI-NES

did not restore the delayed phase of the LHY peak. Our data

showed that nuclear and cytosolic GI had differential effects

on circadian LHY expression. To understand the nuclear and

Figure 1. Nucleus- and Cytosol-Localized GIs Differentially Control Gene Expression

(A) Flowering time ofWT (Col), gi-2,GIpro::GI-GFP,GI-NLS, andGI-NES plants, indicated by the total number of leaves at the time of first flower opening under LD

conditions. Data are shown as themean ± SEM. The asterisks indicate significant difference fromWT (p < 0.001; Tukey’s honestly significant difference [HSD] test

after one-way ANOVA).

(B) Seedling growth as indicated by hypocotyl length under LD. Data are shown as the mean ± SEM. The asterisks indicate significant difference from WT

(p < 0.001; Tukey’s HSD test after one way ANOVA).

(C) Stabilization of ZTL byGI-NES but not byGI-NLS. The ZTL protein level was measured at ZT13 inWT (Col), gi-2,GI-NLS, andGI-NES plants using an anti-ZTL

antibody (Kim et al., 2003). HSP90, loading control.

(D) Patterns of complementation of the gi-2 mutation by GI-NLS and GI-NES at 1 hr (Morning, ZT1) and 16 hr (Evening, ZT16). Red and green, up- and down-

regulation of the genes in gi-2,GI-NLS, andGI-NES plants, compared toWT plants, respectively. Color bar, gradient of log2-fold changes of individual transgenic

plants, compared to WT. Patterns 1 and 2, complementation by only GI-NLS (GIN) or GI-NES (GIC), respectively; pattern 3, complementation by eitherGI-NLS or

GI-NES (GIN or GIC); pattern 4, complementation that requires both GI-NLS and GI-NES (GIN and GIC).

See also Figure S1 and Tables S1 and S2.

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cytosolic GI-dependent circadian network, we mathematically

modeled the regulatory relationships between a core oscillator

LHY and nuclear (GIN) and cytosolic GI (GIC).

To build a model structure, we first obtained previously

described relationships among GIN, GIC, and LHY (Figure S2B):

(1) GI positively regulates LHY expression (Fowler et al., 1999;

Mizoguchi et al., 2002; Park et al., 1999); (2) GI localizes to

both the nucleus and cytosol (GIC4GIN) (Figure S1D); and (3)

LHY negatively regulates GI mRNA expression (LHY�jGImRNA;

Mizoguchi et al., 2005). Two inputs were used for GI and LHY

(input 1/GImRNA and input 2/LHYmRNA). Input 1 includes

exogenous (e.g., light and temperature) and endogenous (e.g.,

regulation from other loops in circadian clock) signals to regulate

D

GI expression (Figure S1B). In the absence of GI, residual LHY

rhythms are still generated (Figures 2A and 2B) by GI-indepen-

dent signaling, which wasmodeled as input 2. However, whether

GIN and GIC positively or negatively regulate LHY expression

(GIC-LHYmRNA and GIN-LHYmRNA; red lines in Figure S2B) is

unknown. With the known and unknown relationships, we con-

structed a model structure and then simplified it (Figure S2B)

by combining translation reactions of GI and LHY and transport

of LHY from the cytosol to the nucleus (Karlebach and Shamir,

2008).

To examine the unknown relationships (GIC-LHY andGIN-LHY)

in the simplified structure, we generated five possible structures

with different positive and negative regulation of LHY expression


Figure 2. Computational Modeling of the Regulatory Network between LHY and Nuclear and Cytosolic GI

(A) Daily rhythmic expression of LHY mRNA in WT, gi-2, GI-NLS, and GI-NES plants under LD conditions. LHY expression normalized to ACTIN2 (ACT). Data,

mean ± SEM.

(B) Cycling LHY expression in free-running conditions.

(C) Structures 1 and 2, positing positive regulation of GI on LHY expression. Black line, known relationship of nuclear (GIN) and/or cytosolic GI (GIC) with LHY. Red

line, hypothesized relationship.

(D) Structures 3–5, positing positive and negative regulation of GI on LHY expression.

(E) Shape and phase errors of LHY peaks computed as differences in the shape and phase of simulated LHY peaks relative to those of experimental LHY peak in

wild-type. Wild-type situation corresponds to zero shape and phase errors (i.e., origin). After binning the shape and phase errors separately at 5% intervals, we

counted the number of simulations in each bin. Color bar (in G), log10 frequency of simulations in each bin.

(F) LHY expression profile in WT plants. A Gaussian function was fitted to the LHYmRNA levels measured under LD conditions. The red closed circle represents

experimental data, and the blue solid line represents simulated LHY. The phase was determined as the timewhen the LHY expression level reached its maximum.

The shape of the peak was defined as the width at half of the LHY peak amplitude. The reference amplitude in this study was set to one.

(G) Shape and phase errors of LHY peaks in structures 3–5 (left to right).

See also Figure S2.

Developmental Cell


by GIC and GIN (Figures 2C and 2D) and then selected a most

feasible structure that produces experimentally measured WT

LHY oscillation (Figure 2A). GI positively regulates the expression

of LHY, and GI-NLS largely restores LHY expression in the gi-2

mutant (Figures 2A and 2B). Thus, we first constructed two struc-

tures (Figure 2C) with LHY positively regulated either only by

nuclear GI (structure 1) or by both nuclear and cytosolic GI (struc-

ture 2) and then developed mathematical models for these two

structures as described in Mangan and Alon (2003) (Supple-

mental Experimental Procedures). We then simulated the

models to compute profiles of GIN, GIC, and LHY expression

using wide ranges of strengths of all the regulations in the two

structures (Experimental Procedures; Supplemental Experi-

mental Procedures). Using the simulated LHY profiles, we calcu-

lated phases, shapes, and amplitudes of LHY oscillation and

then computed relative differences (errors) of the phases and

shapes (Figure 2E), compared to those of the WT LHY profile


(Figure 2F). Structures 1 and 2 resulted in large phase and shape

errors (away from the origin in Figure 2E), indicating that they

failed to generate the WT LHY oscillation.

Thus, we generated three other structures involving negative

regulation of LHY by nuclear and/or cytosolic GI (Figure 2D).

Structure 3 was most likely to produce small phase and shape

errors (less than 10% of errors), whereas structure 4 was less

likely to produce the small errors (Figure 2G), indicating their

capability of generating the WT LHY oscillation. In contrast,

structure 5 was unlikely to generate the WT LHY oscillation. To

further discriminate structures 3 and 4, we simulated the two

structures under free-running circadian conditions with a daily

decrease of GI input (Figure S2C) and then evaluated whether

either structure resulted in daily decrease in amplitude of LHY

oscillation. Structure 3 led to a daily decrease in amplitude of

LHY oscillation (Figure S2C), consistent with previous experi-

mental data (Edwards et al., 2010; Martin-Tryon et al., 2007;

Figure 3. The Negative Effect of Cytosolic GI on the Kinetics of LHY

(A) Predicted delayed induction kinetics of LHY with increasing strengths of

GICCLHY in structure 3. KGIC,LHYmis the parameter controlling the strength of

the inhibition of LHY expression by GIC in the mathematical model for struc-

ture 3. As the KGIC,LHYmvalue decreases, the inhibition strength increases

(Supplemental Experimental Procedures). Gray dashed lines indicate 50%and

70% of the LHY peak amplitude in WT.

(B) Predicted time (rising time) to reach 50% and 70% (denoted by gray

dashed lines in A) of the LHY peak amplitude in wild-type with increasing

inhibition strengths of LHY by GIC.

(C) Experimental validation of LHY inhibition by GIC. LHY expression was

measured by the luminescence intensity produced from LHYpro::LUC

cotransfected with GI-NLS alone or with GI-NLS and increasing amounts of

GI-NES into gi-2 protoplasts. LHYpro::LUC intensities from each combination

were normalized with intensities from 35S::RLuc. Gray dashed lines indi-

cate 50% and 70% of the LHY peak amplitude in GI-NLS alone. Control,

Figure S3C.

(D) Incubation time needed to reach 50% and 70% (denoted by gray dashed

lines in C) of the LHY peak in (C).

See also Figure S3.

Developmental Cell


Mizoguchi et al., 2002). In contrast, structure 4 resulted in rather

daily increase (see Figure S2C for simulation results for other

structures under free-running conditions and Figure S2D for

the use of oscillation of GIC and GIN expression for comparison

of the five structures). These simulation results under both

diurnal and free-running conditions together indicate that struc-

ture 3 is most feasible to generate the WT circadian phases,

shapes, and amplitudes of LHY expression (Supplemental

Experimental Procedures).

Cytosolic GI Negatively Regulates LHYThe predicted negative regulation of LHY expression by GIC(structure 3, Figure 2D) was unexpected, as GI promotes LHY

expression overall (Fowler et al., 1999; Park et al., 1999). How-

ever, the negative regulation of LHY by GIC could be a hidden

regulatory layer embedded in the interlocked circadian network

that overall promotes LHY expression. To test the feasibility

of negative regulation of LHY by GIC, we simulated the effect

D

of increasing amounts of GIC on the GIN-induced expression of

LHY. The most notable result was the delayed induction of

LHY expression with increasing amounts of GIC, showing that

the negative regulation by GIC is implemented as a kinetic delay

(Figures 3A and 3B; Supplemental Experimental Procedures). A

negative effect of GIC on the induction kinetics of LHY expression

was then experimentally confirmed by transient expression

assays in plant cells (see Figures 3C, 3D, and S3A–S3G for con-

trol experiments and other trials). When an increasing amount

of GI-NES DNA was introduced along with a fixed amount of

GI-NLS DNA into Arabidopsis protoplasts, the induction kinetics

of LHY expression was delayed, consistent with the simulation

results. In contrast, when an increasing amount of GI-NLS

DNAwas introduced, we were able to notice mostly the increase

of LHY expression rather than modulating the kinetics of LHY

induction (Figure S3H). Thus, these data support the notion

that nuclear GI positively regulates LHY expression level,

whereas cytosolic GI negatively regulates induction kinetics of

LHY expression.

Given that GIC imposes a kinetic delay on the induction of LHY

expression, what is the role of GIC in generating the circadian

rhythmicity of LHY? To answer this question, we simulated the

effect of negative regulation by GIC on generation of the rhythmic

pattern of LHY expression using different strengths of the nega-

tive regulation (Figure S3I). To understand the systematic effect

of negative regulation, for each strength of the negative regu-

lation, we used awide range of strengths of positive regulation by

GIN (Supplemental Experimental Procedures). For all strengths

of negative regulation, we then evaluated and compared the like-

lihoods of generating LHY phases and shapes experimentally

measured in WT plants (Figure S3I). We found that with

increasing strengths of negative regulation by GIC, the probabil-

ity of generating LHY phases and shapes in wild-type plants

(close to the origin in Figure S3I) was increased. These data indi-

cate that the negative regulation by GIC contributes to the capa-

bility to generate the circadian rhythmicity of the core oscillator

LHY by acting as a kinetic tuner (see Supplemental Experimental

Procedures for further discussion).

GI Forms an Incoherent Feedforward LoopStructure 3 defines a type 3 incoherent feedforward loop (I3-FFL)

(Figure 4A). The feedforward loops (FFLs), important regulatory

motifs in biological system, involve two separate regulations of

the final component (Z) by the initial component (X): (1) direct

regulation on Z by X and (2) indirect regulation on Z via the sec-

ond component (Y) regulated by X. The FFLs are categorized into

coherent and incoherent loops (Alon, 2007). In the coherent

FFLs, both direct and indirect regulations are positive or nega-

tive, whereas in the incoherent FFLs, one of direct and indirect

regulation is positive, but the other is negative. The incoherent

FFLs are further categorized into four types depending on how

incoherent relationships in the direct and indirect regulations

are formed among X, Y, and Z (Figure S4A). In the type 3

incoherent FFL (I3-FFL), X (cytosolic GI in our case) negatively

regulates Z (LHY), and Y (nuclear GI) positively regulated by X

positively regulates Z (Figure 4A). In biological systems, I3-FFL

is employed to generate a strong pulse and to accelerate tempo-

ral responses (Mangan and Alon, 2003). We therefore examined

the roles of the I3-FFL formed by GIC and GIN in defining the


Figure 4. Nuclear and Cytosolic GI Define an

I3-FFL

(A) The I3-FFL defined by the nucleocytosolic parti-

tioning of GI (structure 3, right) in comparison with a

typical I3-FFL (Left).

(B andC) Residual LHY pulse in gi-2 plants, compared

to that in WT plants (B), consistent with simulation

results of the I3-FFL structure in situations corre-

sponding to both plants (C). LHY expression in WT

and gi-2 plants was replotted from Figure 2A.

(D) Probability of generating an LHY pulse through

coordinated action of negative and positive regulation

by GIC and GIN, respectively, in the I3-FFL. The I3-FFL

was simulated with varying strength values for

positive (1/KGIN,LHYm) and negative regulation

(1/KGIC,LHYm). The number of simulations generating a

feasible LHY pulse was counted at intervals of 0.25

for each strength value. Color bar, log10 frequency.

Dotted box, range with a high probability of gener-

ating a strong LHY pulse.

(E) Generation of a strong LHY pulse requires coor-

dination of GIC and GIN. LHY pulse generation in gi-2

plants (origin in D) andwith decreasing ratios (x, y, and

z in D) of LHY activation by GIN to LHY inhibition by

GIC (GIN/LHY/GICCLHY).

(F) Nuclear and cytosolic GI cycling in GIpro::GI-GFP

(upper) and CsV::GI-GFP (lower) under LD condition.

GI proteins were fractionated from 10-day-old seed-

lings grown under LD. Nuclear and cytosolic GI-GFP

proteins in each plant were measured and normalized

with HSP90 and Histone-3, respectively. Data,

mean ± SEM from three biological trials.

(G and H) Generation of a strong LHY pulse in plants

and simulations, respectively, in GIpro::GI-GFP

(upper), but not in CsV::GI-GFP (lower). LHY expres-

sion levels were measured from 10-day-old seedlings

under LD and then normalized with that of ACT. Data,

mean ± SEM from three biological trials.

See also Figure S4.

Developmental Cell


properties of LHY rhythms. We first tested whether the I3-FFL

can generate a strong pulse of LHY expression. In the absence

of GI in the gi-2 mutant, LHY shows a residual peak, whereas

in WT the LHY pulse is stronger (Figure 4B). Our mathematical

modeling showed that this situation can be implemented by

the I3-FFL (Figure 4C; Supplemental Experimental Procedures).

This supports the notion that the I3-FFL employs GIC as a nega-

tive and GIN as a positive component to function as a strong

pulse generator.

For an I3-FFL to generate a strong pulse, the coordinated

action of negative and positive regulation is critical (Mangan

and Alon, 2003). We therefore tested the effect of the balance

between GIC and GIN on the generation of a strong pulse of

LHY expression by varying the relative amounts of GIC, and

GIN (Figure 4D; Supplemental Experimental Procedures). The

results show that a strong LHY pulse was generated at a greater

frequency when the amounts of both GIC and GIN are above


certain levels (the dotted box in Figure 4D).

This indicates that strong LHY pulse gener-

ation requires the balanced action of both

the positive GIN and negative GIC. The gi-2

mutation (origin in Figure 4D) shows a resid-

ual pulse of LHY expression (Figure 4B, and upper and left panel

in Figure 4E). When only GIN was increased from the gi-2 situa-

tion (‘‘x’’ in Figure 4D), a strong peak was not formed (upper

and right panel in Figure 4E). However, when GIC was increased

together with GIN from the gi-2 situation (‘‘y’’ in Figure 4D), a

strong peak resulted (lower and left panel in Figure 4E). However,

when GIC was further increased (‘‘z’’ in Figure 4D), the peak

amplitude was much lower (lower and right panel in Figure 4E).

These results indicate that the coordinated action of negative

cytosolic and positive nuclear GI in our I3-FFL is critical in gener-

ating strongly pulsed expression of LHY.

For the I3-FFL to generate a strong pulse, the kinetics of the

negative and positive components are important (Alon, 2007)

(Figure S4B). We experimentally tested the effect of varying the

kinetics of GIC and GIN on the generation of a strong pulse of

LHY expression by examining gi-2 plants, GIpro::GI-GFP plants,

in which GI expression is controlled by a native promoter (upper

Developmental Cell


panels in Figures 4F–4G, S4C, and S4E), and CsV::GI-GFP

plants, in whichGI expression is controlled by a constitutive pro-

moter (lower panels in Figures 4F and 4G and Figures S4D and

S4F). The GIpro::GI-GFP transgenic plants produced GI-GFP

with a daily oscillation (Figure 4F upper panel and Figures S4C

and S4E). In contrast, the CsV::GI-GFP transgenic plants pro-

duced GI-GFP arrhythmically (Figure 4F lower panel and Fig-

ure S4D), resulting in disruption of the kinetics of GIC and GIN.

A strong pulse of LHY expression was generated in GIpro::

GI-GFP plants but not in CsV::GI-GFP plants (Figures 4G and

S4E), consistent with our simulation using rhythmic expression

of GIN and GIC in the GIpro::GI-GFP plants and constitutive

expression of GIN and GIC in CsV::GI-GFP plants (Figure 4H;

Supplemental Experimental Procedures). Interestingly, an addi-

tional CsV::GI-GFP line we examined showed GI expression at a

high level but with a daily cycling pattern (Figure S4F), thus

resulting in LHY pulse similar to those in WT plants, as in the

previously reported 35S::GI overexpression plants (Mizoguchi

et al., 2005).

In I3-FFL, the final component (LHY) generates a pulse when

the initial component (GIC) is decreased (Ma et al., 2009; Mangan

and Alon, 2003). To test this characteristic of I3-FFL, we further

examined LHY expression pattern in a transgenic plant, in which

GI expression can be ectopically induced using chemical treat-

ment besides the endogenous GI expression (Figure S4G). We

treated the chemical just before GI expression decreases,

thereby disrupting the decrease of GI expression. In this situa-

tion, the amplitude of LHY pulse was reduced. All the above

data showed that the kinetics of GIC andGIN expression is critical

in generating a strong pulse of LHY expression, as expected

from the characteristic of I3-FFL (Ma et al., 2009; Mangan and

Alon, 2003).

The Cytosolic GI in the I3-FFL Ensures Robustnessin Both Circadian Amplitude and PhaseCircadian system, as many other biological systems, has

intrinsic molecular noises. Internal stochastic nature of circadian

rhythm provides variable rhythmic patterns of circadian outputs,

such as leaf movement and gene expression, in individual plants.

Relative amplitude error (RAE) has been used as a quantitative

measure to evaluate the presence of circadian rhythmicity in

the time-course data. The variable rhythmic patterns of circadian

outputs can be studied by examining the distributions of RAE

and circadian peak phases in individual plants. Yet, there has

been little mechanistic study on control of RAE and phase distri-

bution in the circadian system. Here, we experimentally tested

the contribution of nuclear and cytosolic GI to the distributions

of RAE and peak phases of leaf movement under free-running

conditions. GI-NES plants showed smaller standard deviations

(or variability) of RAE and peak phases than GI-NLS plants (Fig-

ure 5A). Furthermore, GIpro::GI-GFP plants expressing GI-GFP

in both nucleus and cytosol showed much smaller standard

deviations of RAE (Figure S5A) and peak phases (Figure S5B)

than GI-NLS plants. These data supported that cytosolic GI

functions to control robustness of circadian rhythm as indicated

by reduced standard deviations of RAE and peak phases. This

observation is further supported by the rhythmic behavior of

circadian regulation promoter activities (Figure 5B). The internal

stochastic noises in the circadian rhythm can be additionally

D

manifested into physiological outputs such as circadian-

regulated seedling growth (Dowson-Day andMillar, 1999; Nozue

et al., 2007). We tested the variability of seedling growth of

GI-NLS and GI-NES lines under free-running conditions after

circadian entraining (Figure 5C). We found that the variability

was much lower in GI-NES seedlings than in GI-NLS seedlings,

as indicated by 95%confidence interval of hypocotyl length (Fig-

ure 5C). These results indicate that the cytosolic GI ensures

robustness in circadian outputs at both molecular and physio-

logical levels under stochastic noises.

Features of the Spatial GI LoopTypical I3-FFLs employ three different substances (Figure 4A).

Notably, our I3-FFL involves only two substances, but one of

these, GI, was spatially segregated into the nucleus and cytosol,

acting as positive and negative components, respectively (Fig-

ure 4A). Why then does the spatially segregated loop employ a

single substance for negative and positive roles rather than

two different substances? To investigate the functional signi-

ficance of this spatial GI loop, we postulated alternative struc-

tures (Supplemental Experimental Procedures) involving three

different substances but otherwise mimicking the observed

I3-FFL network, in that the positive component, Y, is located in

the nucleus, and the negative component, X, is located in the

cytosol (Figure 5D). In alternative 1 the link between positive

and negative components occurs in the nucleus (XN/YN), and

in alternative 2 it occurs in the cytosol (XC/YC) (Figure 5D).

The above experimental data implied that the spatially segre-

gated GI in the I3-FFL provides the plant circadian system with

robustness against stochastic noises. We thus simulated the

alternatives to examine the robustness of LHY amplitude against

stochastic external (e.g., transient variation of light intensity; Fig-

ures 5E, 5F, and S5C–S5F) and internal (Figures S5G–S5J)

noises to GI. Structure 3 showed lower variation of LHY ampli-

tudes around the noise-free amplitude, indicating greater

robustness of LHY amplitude than both of the alternatives, in

the case of noise-to-input ratio = 1 (Figures 5E; Supplemental

Experimental Procedures). When the input noise level was varied

from noise-to-input ratio = 0 to 1, in alternatives 1 and 2, the

mean (upper, Figure 5F) and the standard deviation (lower, Fig-

ure 5F) of LHY amplitude significantly deviated from those under

noise-free conditions (noise-to-input ratio = 0). In contrast, struc-

ture 3 showed much lower deviation throughout all the range of

noise-to-input ratios (Figure 5F). Furthermore, we varied all the

kinetic parameters in the models. Structure 3 still resulted in

greater robustness under both external (Figures S5C–S5F) and

internal stochastic noises (Figures S5G–S5J). The results imply

that the spatial I3-FFL by the single substance provides

enhanced robustness of LHY amplitude in the plant circadian

system.

DISCUSSION

Spatial Partitioning of GI Enhances ComputationalPerformance of the Plant Circadian NetworkRegulatory capability of biological networks provides a funda-

mental basis for various characteristics of physiological pro-

cesses, such as response kinetics and robustness against

external and internal noise. This regulatory capability is defined


Figure 5. Cytosolic GI in the I3-FFL Ensures

Robustness in Both Amplitude and Phase

(A) Relative amplitude errors (RAE; left) and normalized

phase distribution (right) of leaf movement in individual

GI-NLS and GI-NES plants under free-running condi-

tions. RAE from each plant was computed using the FFT-

NLLS suite (Plautz et al., 1997). The mean values of the

phases of the first and second peaks were set to 1 for

normalization.

(B) RAE of CCR2pro::LUC in individual GI-NLS and

CAB2pro::LUC in individual GI-NES plants under free-

running conditions.

(C) Variability of seedling growth in individualGI-NLS and

GI-NES plants under free-running conditions. Seedlings

were entrained under LD for 3 days and transferred to

continuous darkness for 4 days. Means ± 95% confi-

dence interval; 4.28 ± 0.25 (WT), 4.77 ± 0.45 (gi-2), 4.58 ±

0.48 (GI-NLS), and 4.53 ± 0.31 (GI-NES). Red line, mean

hypocotyl lengths.

(D) Alternatives to structure 3. In the alternatives, two

separate components, X and Y, replace spatially segre-

gated GI in structure 3. The negative component (XC) in

the cytosol and positive component (YN) in the nucleus

reflect their spatially segregated actions. Green and red,

cytosolic and nuclear localization, respectively.

(E and F) LHY expression profiles (E) under transient

external noise added to the input to GI (input 1). The

standard deviation of the noise (blue profiles in E) was

equal to the amplitude of input 1 (noise to input ratio = 1)

(Supplemental Experimental Procedures). Green and red

lines in (E), LHY amplitudes under noise-free conditions

and under noise, respectively. The mean and standard

deviation of the LHY amplitudes are given in parenthe-

ses. (F) The mean (upper) and standard deviation (lower)

of the LHY amplitudes relative to those in noise-free

conditions with varying noise to input ratios.

See also Figure S5.

Developmental Cell


by collective actions of regulatory motifs. However, current

understanding of how the biological networks implement regula-

tory motifs to perform complex regulatory tasks remains still

largely elusive. In this study, we unfolded, by spatial dimension,

the network motif involving GI and LHY, critical components in

the plant circadian system. The previous experimental data sug-

gested a positive action of GI on LHY expression (Park et al.,

1999). In contrast, the previous modeling data suggested a

negative action of GI on LHY (Pokhilko et al., 2010). In both

cases, the spatial dimension was not considered. By considering

the spatial dimension, we have shown that nucleocytosolic par-

titioning of GI leads to segregation of the regulatory mode of GI;


the nuclear GI and cytosolic GI act as positive

and negative regulators of the core oscillator

LHY. Newly discovered regulatory modes of

nuclear and cytosolic GI by spatial segregation

form a spatial I3-FFL regulatory motif previ-

ously unrecognized in the plant circadian

network.

I3-FFL Defined by GI CoordinatesCircadian PhysiologyWhat, then, is the role of the I3-FFL formed by

spatially segregated GI in coordinating physio-

logical processes during a daily cycle? Photosynthesis is a phys-

iological process critically affected by the circadian network

(Dodd et al., 2005; Harmer et al., 2000). Thus, we analyzed the

role of the spatial I3-FFL in regulation of genes encoding photo-

synthetic components (Figure 6) during a daily cycle using the

gene expression data (Figure 1D). In the morning, a set of photo-

synthetic genes is upregulated by GI (‘‘upregulated’’ at ZT1 in

Figure 6), whereas another set of photosynthetic genes is down-

regulated by GI (‘‘downregulated’’at ZT16 in Figure 6) in the eve-

ning. In the morning, the I3-FFL establishes the LHY peak via the

concerted action of nuclear and cytosolic GI (Figure 4). Among

the photosynthetic genes upregulated by GI in the morning, a

Figure 6. Temporal Transition of the Spatial I3-FFL and Its Role in Regulation of Photosynthetic and Flowering Genes at ZT1 and ZT16

The genes in photosynthesis and flowering pathways regulated by nuclear and cytosolic GI at ZT1 (morning) and ZT16 (evening) were classified into the four

patterns in Figure 1D. GIC, GIN, and LHY were linked with I3-FFL. Four regulatory modes corresponding to the patterns are depending on the requirement of

nuclear (GIN) and cytosolic GI (GIC) in regulation of the genes in individual patterns (see text for Figure 1D). Pattern 4 represents the regulation by the I3-FFL

involving both GIN and GIC (‘‘AND’’) and also LHY. Regulatory modes from cytosolic and nuclear GI (GIC and GIN) and LHY were represented by green, blue, and

red lines, respectively. The arrow and flat lines denote positive and negative regulations, respectively. Expression profiles of GIC, GIN, and LHYwere schematically

displayed in the middle of the figure and gray-dashed lines represent morning and evening when the analysis was performed.

See also Figure S6.

Developmental Cell


majority of them (in pattern 4 at ZT1 in Figure 6) are upregulated

possibly through LHY established by the action of the I3-FFL,

involvingboth nuclear andcytosolicGI (‘‘AND’’ at ZT1 in Figure 6),

as previously reported (Michael et al., 2008a) (Figure S6). In

contrast, in the evening, nuclear and cytosolic GI are induced,

and the LHY peak established by the action of the I3-FFL disap-

pears (see expression profiles of nuclear and cytosolic GI and

D

LHY in Figure 6). Among the photosynthetic genes downregu-

lated by GI in the evening, a major set of them (in pattern 3 at

ZT16 in Figure 6) is downregulated by either the induced nuclear

or cytosolicGI (‘‘OR’’ at ZT16 in Figure 6). Furthermore, thedisap-

pearance of the LHY peak activates the evening components

of the circadian system, possibly leading to downregulation of

another major set of the genes (in pattern 4 at ZT16 in Figure 6).


Developmental Cell


The I3-FFL defined byGI is a loop embedded in the outer feed-

back loop, where GI is also under cyclic regulation by the core

oscillator, LHY (Figure 2D). Thus, the LHY rhythm controlled by

the I3-FFL, in turn, controls the daily GI rhythm, which peaks at

evening. In addition to photosynthesis, GI also regulates day-

length-dependent flowering time as a circadian output. Our anal-

ysis showed that GI mainly controls flowering-related genes in

the evening (ZT16 in Figure 6). These flowering-related genes

can be regulated mostly by only nuclear GI (genes in pattern 1

at ZT16 in Figure 6) or by either nuclear or cytosolic GI (genes

in pattern 3 at ZT16 in Figure 6). Among them, the genes regu-

lated by only nuclear GI (pattern 1) included the major regulatory

genes of flowering time, CO and FT, which were previously

shown to be under direct transcriptional control by GI (Sawa

and Kay, 2011; Sawa et al., 2007). Furthermore, the disappear-

ance of the LHY peak established by the action of the I3-FFL in

the evening activates the evening components of the circadian

system, possibly leading to upregulation of another set of flower-

ing-related genes (genes in pattern 4 at ZT16 in Figure 6). Thus,

the differential activation of the spatial I3-FFL along the daily

cycle can provide a greater regulatory capability of controlling

and entangling various physiological processes in the circadian

system.

In addition, GIpro::GI-GFP revealed various degrees of the

complementation for patterns 1–4 (Figures S1H and S1I). Espe-

cially, pattern 4 showed a lower degree of complementation in

the morning and evening. The genes in pattern 4 require the

coordinated action of both nuclear and cytosolic GI for comple-

menting the altered expression by the gi-2mutation. This obser-

vation suggests that, although GIpro::GI-GFP plants produced

nuclear and cytosolic GI, they might have not achieved the

wild-type ratio of nuclear and cytosolic GI for their coordinated

action required to complement the genes in pattern 4. This sup-

ports our findings that the coordinated action of nuclear and

cytosolic GI through the I3-FFL is important for functions of plant

circadian system.

Utilization of Spatial Partitioning in Biological NetworksHere, we showed that spatial partitioning of GI can be utilized to

construct an I3-FFL. Can the cytosolic and nuclear GI form

another regulatory loop with genes other than LHY? GI has a

multitude of functions, controlling thousands of genes. GI also

interacts with other cellular components including several

nuclear proteins and at least one cytosolic protein (ZTL). Thus,

the cytosolic and the nuclear GI have high potential to form reg-

ulatory loops with other genes. The other regulatory loops may

not necessarily be I3-FFL but could also be other types.

In addition to GI, many circadian components show nuclear

and cytosolic distribution (Table S1). The studies on the circa-

dian components have so far focused mostly on the temporal

dimension. Our discovery argues the inclusion of the spatial

dimension of these components into the current circadian

model may better recapitulate the plant circadian regulatory

mechanisms.

Although I3-FFL serves as an important regulatory network

motif, I3-FFLs have rarely been identified in a real biological

context (Mangan et al., 2006). In this study, we recognized the

presence of an I3-FFL and its regulatory power only when we

considered spatial partitioning. The spatial partitioning is


recently being recognized as an important functional and regula-

tory dimension in biology. We thus envision that the spatial par-

titioning is utilized far frequently in constructing the biological

regulatory motifs. The spatial regulatory motifs can be further

resolved in time to include temporal changes of the regulatory

structures in the motifs, involving (1) redistribution of molecules

from a compartment to other compartments and (2) construction

of new regulatory relationships among the molecules. In conclu-

sion, we argue that the spatial distribution of a molecule may

serve as a fundamental principle that biological systems have

adopted during evolution to enhance the computational perfor-

mance of biological networks.

EXPERIMENTAL PROCEDURES

Plant Materials

The gi-2 and gi-komutants were reported previously (Martin-Tryon et al., 2007;

Park et al., 1999). A GIpro::GI-GFP gene fragment was introduced into a

pART27 (Gleave, 1992) backbone. The GIpro::GI-GFP-NLS and GIpro::GI-

GFP-NES vectors were constructed using NLS (Kalderon et al., 1984) from

SV4012 and NES (Henderson and Eleftheriou, 2000) from MAPKII in a

pPZP221 (Hajdukiewicz et al., 1994) backbone. The GIpro::GI-GFP-NLS and

GIpro::GI-GFP-NES constructs were introduced into Col, and the gi-2 muta-

tion was then introduced via a genetic cross. Subsequently, these constructs

were additionally transformed into gi-ko. To generate VGE::GI-GFP, GI-

inducible transgenic plants, a chemical-inducible vector having ecdysone

agonist induced promoter (Koo et al., 2004) fused withGI-GFPwas introduced

into WT (Col) plants.

Flowering, Seedling Growth, and Leaf Movement Assays

These experiments were performed as previously described (Kim et al., 2008).

We examined the distributions of the first (black in Figure 5A) and second (blue

in Figure 5A) peak times to investigate the role of nuclear and cytosolic GI in

controlling robustness against the variability in themovements of the individual

leaves. The first or second peaks were first identified by smoothing the tempo-

ral profiles and then identifying the first and secondmaximum points. For each

fitted peak, the peak time was then identified as the location of the fitted

Gaussian function. Finally, the peak times were normalized to the mean time

of the peaks.

For an analysis of seedling growth under free-running conditions (Figure 5C),

seeds were sown on 0.5 3 Murashige and Skoog media without sucrose.

Seedlings were entrained for 3 days and transferred to continuous darkness

for 4 days.

Immunoblot Analysis

Immunoblot analyses for GI, ZTL, HSP90, and H3 protein detection were per-

formed as previously reported (Kim et al., 2003, 2007). Polyclonal anti-HSP90

antibodies were generated in rabbits and were diluted 1:5,000 for detection.

Nuclear or cytosolic fractions were performed with/without the detergent

NP40 in protein extraction buffer or the CelLytic PN-Plant Nuclei Isolation Kit

(Sigma-Aldrich).

Quantitative RT-PCR

These experiments were performed as previously described (Kim et al., 2008).

To measure LHY and TOC1 transcripts, RNA was isolated from 10-day-old

seedlings growing under LD conditions. To measure GI and LHY transcripts

in GI-inducible plants, plants grown for 10 days under 12L/12D conditions

were transferred to continuous light conditions, andGI-GFPwas then induced

with 50 mMMOF at ZT12. Plants were harvested every 6 hr starting 1 hr induc-

tion.We also confirmed differential expression identified from gene expression

profiles by qPCR. The list of primer sequences used was summarized in Sup-

plemental Experimental Procedures.

Microarray Experiments

Seven-day-old seedlings grown under LD conditions were harvested at ZT1

and ZT16. Total RNA was isolated and used for microarray experiments. The

Developmental Cell


integrity of the total RNA was evaluated using a Bioanalyzer 2100 (Agilent

Technologies). The RNA integrity in all samples was sufficient for gene expres-

sion analysis (RNA integrity number > 9.5). The RNA was reverse transcribed,

amplified, and then hybridized onto customized Arabidopsis gene expression

microarrays containing 43,803 probes corresponding to 25,945 annotated

genes, according to standard Agilent protocols. mRNA levels were measured

for three biological replicates from each transgenic plant (WT [Col], gi-2,

GI-NLS, GI-NES, GIpro::GI-GFP) at ZT1 and ZT16. Log2 intensities were

normalized using quantile normalization (Bolstad et al., 2003).

Measurement of LHY Promoter Activity by Transient Expression

To identify negative regulation of LHY expression by cytosolic GI, we intro-

duced a transient expression system using Arabidopsis protoplasts. Proto-

plasts were prepared using the third to sixth leaves from 1-month-old gi-2

plants at ZT1. LHYpro::LUC (10 mg of DNA for all tubes), 35Spro::Renilla

LUC (5 mg of DNA for all tubes), CsV::GI-GFP-NLS (9.6 mg of DNA for each

tube except gi-2), CsV::GFP-NES (5.2, 10.4, and 15.6 mg of DNA), and

CsV::GI-GFP-NES (9.6, 19.2, and 28.8 mg of DNA) were transfected in each

combination. Transfected cells were divided into two groups, one in which

luciferin was provided as a substrate for firefly LUC and the other with coe-

lenterazine as a substrate for Renilla LUC. Luminescence intensities were

measured with a Peltier-cooled charge-coupled device slow scan camera

(Versarray, Roper Scientific) and analyzed using MetaVue software (Universal

Imaging). The luminescence intensity from Renilla LUC was used for

normalization.

Identification of Differentially Expressed Genes

Using the normalized log2 intensities, we applied an integrative statistical

method described previously (Lee et al., 2010) to identify differentially

expressed genes (DEGs) with respect to the following comparisons: (1) WT

versus gi-2; (2) WT versus GI-NLS; (3) WT versus GI-NES; (4) gi-2 versus

GI-NLS; (5) gi-2 versus GI-NES; (6) gi-2 versus GIpro::GI-GFP; (7) GI-NLS

versus GIpro::GI-GFP; and (8) GI-NES versus GIpro::GI-GFP. Briefly, in this

method, we applied both two-sample t test and log2 median difference test

for each comparison to compute T-statistic values and log2 median differ-

ences, respectively, for individual genes. After computing adjusted p values

for the t test and median difference test for each gene, we then combined

these p values using Stouffer’s method (Hwang et al., 2005) (see Supplemental

Experimental Procedures for the method to compute the adjusted p values).

Finally, we identified the DEGs having combined p values of less than 0.05

and absolute log2 median differences greater than a specified cutoff value

(see Supplemental Experimental Procedures for the determination of the cutoff

value). The cutoff values for the absolute log2 median differences used in the

comparisons of (1) WT and GI transgenic plants, (2) gi-2 and other GI trans-

genic plants, (3) GI-NLS and GIpro::GI-GFP, and (4) GI-NES and GIpro::GI-

GFP are 0.2488, 0.2408, 0.2683, and 0.2697, respectively.

Identification of GI-NLS- and GI-NES-Dependent Complementation

Expression Patterns

To investigate the nuclear and cytosolic GI-dependent complementation of the

gi-2mutation, for each time point (ZT1 and ZT16), we first identified all 26 DEG

clusters in the three following comparisons: WT versus gi-2, WT versus

GI-NLS, and WT versus GI-NES (Table S2A). Among these 26 clusters, we

focused on the eight major clusters showing nuclear and cytosolic GI-

dependent complementation expression patterns (Figure 1D). To address

GI-dependent complementation based on the expression pattern, we further

used the differential expression between gi-2 and GI mutant plants (GI-NLS

and GI-NES) as criteria, together with the differential expression between

WT and GI mutant plants. For example, the complementation predominant

in GI-NLS (pattern 1 in Figure 1D) included the DEGs in the comparisons of

WT versus gi-2, WT versusGI-NES, and gi-2 versusGI-NLS (see Supplemental

Experimental Procedures for other GI-dependent complementation). The eight

major clusters were categorized into four groups of complementation expres-

sion patterns separately at ZT1 and ZT16 (Figure 1D).

To validate the requirement of GIN and/or GIC to complement the lesion

due to the gi-2 mutation, we compared GIpro::GI-GFP with WT and other

GI-transgenic plants (Figures S1H and S1I). For patterns 1–4 in Figure 1D,

we investigated genes showing recovery of altered gene expression in at least

D

one of gi-2, GI-NLS, and GI-NES by GIpro::GI-GFP. We defined the genes as

complemented genes for each pattern by GIpro::GI-GFP. See Supplemental

Experimental Procedures for detailed methods and discussion on confidence

of gene expression data.

Simulation of Mathematical Models

For each structure, we sampled 30,000 parameter sets at the logarithmic scale

using the Latin hypercube sampling method (Iman et al., 1980) in the following

ranges: (1) 1 3 10�3–10 for the parameter (Ki,j) for strength of activation or

repression of molecule j by molecule i; (2) 1 3 10�2–10 for transport rate (p1)

from GIC to GIN; (3) 10�1.5–101.5 for transport rate from GIN to GIC relative

to p1; and (4) 13 10�3–10 for input 1 and input 2 (see model equations in Sup-

plemental Experimental Procedures). For each set of parameters, we simu-

lated the model structure by a MATLAB ordinary differential equation (ODE)

solver (‘‘ode15s’’). Using the simulation results, we selected feasible LHY pro-

files with (1) single peaks during a day, (2) peak amplitudes larger than 2.5 3

[LHY peak amplitude activated only by input 2] (i.e., peaks predominantly

generated by input 1), and (3) peaks appearing following activation by input

2, thus focusing on situations where LHY oscillation is collectively controlled

by both GI-dependent (input 1) and GI-independent (input 2) inputs. To eval-

uate the likelihood of generating WT LHY oscillation, we computed shape

and phase errors as shown in Figures 2E and 2G.

ACCESSION NUMBERS

The NCBI GEO accession number for the gene expression data reported in this

paper is GSE47169.

SUPPLEMENTAL INFORMATION

Supplemental Information includes Supplemental Experimental Procedures,

six figures, and two tables and can be found with this article online at http://

dx.doi.org/10.1016/j.devcel.2013.06.006.

ACKNOWLEDGMENTS

We thank K.H. Suh, Y.S. Park, Y.S. Lim, and B.H. Kim for technical assistance.

This research was supported by Korean MEST grants IBS (CA1208), NRSP

(2010-0020417), and WCU (R31-2008-000-10105-0 and R32-10148) and the

RDA Next-Generation BioGreen 21 Program (PJ009072 and PJ009615).

Received: August 2, 2012

Revised: March 14, 2013

Accepted: June 6, 2013

Published: July 3, 2013

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