A systematic survey in Arabidopsis thaliana of transcription factors that modulate circadian parameters
© Hanano et al; licensee BioMed Central Ltd. 2008
Received: 17 June 2007
Accepted: 21 April 2008
Published: 21 April 2008
Plant circadian systems regulate various biological processes in harmony with daily environmental changes. In Arabidopsis thaliana, the underlying clock mechanism is comprised of multiple integrated transcriptional feedbacks, which collectively lead to global patterns of rhythmic gene expression. The transcriptional networks are essential within the clock itself and in its output pathway.
Here, to expand understanding of transcriptional networks within and associated to the clock, we performed both an in silico analysis of transcript rhythmicity of transcription factor genes, and a pilot assessment of functional phenomics on the MYB, bHLH, and bZIP families. In our in silico analysis, we defined which members of these families express a circadian waveform of transcript abundance. Up to 20% of these families were over-represented as clock-controlled genes. To detect members that contribute to proper oscillator function, we systematically measured rhythmic growth via an imaging system in hundreds of misexpression lines targeting members of the transcription-factor families. Three transcription factors were found that conferred aberrant circadian rhythms when misexpressed: MYB3R2, bHLH69, and bHLH92.
Transcript abundance of many transcription factors in Arabidopsis oscillates in a circadian manner. Further, a developed pipeline assessed phenotypic contribution of a panel of transcriptional regulators in the circadian system.
The Arabidopsis thaliana (Arabidopsis) circadian clock drives growth and development in response to daily and seasonal change . This is of ecological relevance as the clock has been shown to be critical for plant fitness and appears to be evolving in correlation with latitude [2, 3]. In Arabidopsis, the clock system is proposed to be composed of integrated transcriptional feedbacks [4–6]. These loops drive global gene expression rhythms . In fact, estimates of the total global consortium of cycling genes has ranged from 2% to 36% of all Arabidopsis transcripts [8–10]. These global regulatory patterns of transcript abundance demonstrate that whole regulatory and metabolic pathways are under clock control [8, 10, 11]. This exquisitely coordinated regulation is thought to be the purpose of the clock. Overall one can see an emerging, systems-level understanding of the complicated biological mechanisms composed of transcriptional networks driven by the clock. Functional tests of these hypotheses are required to fully expand the integrated network.
Understanding the molecular nature of the circadian oscillator is an ongoing task. Within the currently understood core of the oscillator are the sequence related MYB-like factors CIRCADIAN CLOCK ASSOCIATED 1 (CCA1) and LATE ELONGATED HYPOCOTYL (LHY). These genes were first discovered through misexpression studies, as overexpression of either was found to generate an arrhythmic clock [12, 13]. Further work on these factors , and the identification and characterization of other clock genes , resulted in an elegant description of the rhythm-driving oscillator [16–18]. Here a four-loop model has been proposed where in the core of this oscillator lies CCA1/LHY and the pseudo-response regulator TIMING OF CHLOROPHYLL A/B-BINDING PROTEIN (CAB2, also termed LHCB1*1) GENE EXPRESSION 1 (TOC1) [16–18]. This core was confirmed as the cca1 lhy toc1 triple mutant has seriously attenuated rhythmic behavior . CCA1/LHY are genetically transcriptional repressors of TOC1, and TOC1 is a positive genetic factor, with an as of yet unproven biochemical function , that functions in transcriptional induction of CCA1 and LHY. The CCA1/LHY loop is further regulated by a morning loop that contains the TOC1 sequence-related genes PSEUDORESPONSE REGURATOR 9 (PRR9) and PRR7. In turn, the TOC1 arm of the clock is also regulated by a loop that includes the GIGANTEA (GI) flowering-time gene [15, 17]. Current models infer as of yet unidentified transcription factors in this looped network .
Circadian-regulated transcription factors should confer the complete array of phased rhythms of transcript accumulation that is observed [8, 10]. As for example, the MYB-like transcription factors CCA1 and LHY, thought core for normal clock function, are predicted to drive output regulation [10, 8]. Additionally, the MYB-transcription factor EARLY PHYTOCHROME RESPONSIVE 1 (EPR1), the MADS-domain factor FLOWERING LOCUS C (FLC), and a GARP transcription factor, LUX ARRYTHMO (LUX), were also reported to be involved in circadian system [21–23]. These three genes could additionally control a suite of transcript outputs from the clock. Another example of the regulation of circadian outputs by clock-controlled transcription factors is the regulation of the anthocyanin biosynthesis pathway, where structural enzymes for this secondary metabolite are encoded by genes coordinately regulated by a cycling output transcription factor called as PRODUCTION OF ANTHOCYANIN PIGMENT 1, PAP1 . Thus, not all rhythmic transcription factors feedback to the oscillator. We believe it is likely that a small set of transcription factors await to be discovered that can modulate clock function, and just as importantly, we expect that a large set of transcription factors are themselves regulated at the transcript accumulation level to drive the physiological suite of rhythmic outputs.
For the circadian clock to drive rhythmic expression of such a large part of the genome, and for these genes to be phased at all times of the subjective day (no phase bias exists, as shown by ), a suite of transcription factors must be implicated in the clock-output system. The Arabidopsis genome encodes more than 1500 transcription factors that belong to more than 30 different families . Each family of transcription factors was characterized based on the definition of containing a highly conserved DNA-binding domain(s). For example, the Arabidopsis genome contains 133 members of MYB transcription factor superfamily, 162 genes encoding basic helix-loop-helix (bHLH) transcription factors, 75 distinct members of basic region/leucine zipper motif (bZIP) transcription factors [25–27]. Some transcription factors were reported as activators and repressors to compose complexly integrated regulatory loops in the plant circadian system . However, functional characterization of the vast majority of Arabidopsis transcription factors still remains.
Here, we took two overlapping genomic approaches to further catalog the repertoire of transcription factor use within the oscillator and in expression of output traits. These companion approaches identify previously uncharacterized plant genes involved in the circadian system, and further dissects this complex signaling network. For this, we surveyed existing microarray results of the MYB, bHLH, and bZIP transcription factor families and determined those that are clock regulated, and separately, systematically analyzed circadian rhythms in misexpression mutants targeting transcription factors, via time-lapse imaging. We report the discovery of three misexpression lines that have altered circadian parameters. Our suite of analyses lead us to conclude that although many transcription factors do not contribute to normal clock function, transcription factors previously non-described within the clock can be discovered through systematic tests, including computational surveys.
Defining circadian expression within transcription-factor families
As suites of transcripts are clock regulated in Arabidopsis , we hypothesized that this was due to rhythmic accumulation of transcription factors. MYB, bHLH, and bZIP are the predominant factor families previously implicated in light- and clock-regulated accumulation of targets [25–27], so we decided to test how prevalent individual rhythms are within these families. Previously, we have collectively reported no less than 368 genes predicted to encode transcription factors in the MYB (131), bHLH (162), and bZIP (75) transcription factor families in Arabidopsis [25–27]; these were the target pools queried. We accessed expression profiles of circadian experiments, NASCArrays Experiment Reference Number: NASCARRAYS-108 , using Affymetrix ATH1 arrays containing 22,746 probe sets in the public microarray database, GENEVESTIGATOR [28, 29]. This probe set represents 122 MYB, 111 bHLH, and 67 bZIP genes. In these circadian datasets, a total of 185 of these genes (51 MYB, 81 bHLH, and 53 bZIP) were found to be expressed at least one time point (at p < 0.06). We noticed that the expression of more than half of MYB genes was below detection level on these hybridization samples. Perhaps this implies that many MYB transcripts in this experimental protocol were tissue or growth-stage specific. In contrast, most bHLH and bZIP genes were detected in this array experiment. The expression data we processed from these 185 genes was sufficient for further in silico analyses.
MYB, bHLH and bZIP genes scored as rhythmic by COSOPT. Total number of MYB, bHLH and bZIP on the genome, array and expressed in the circadian experiment (p < 0.1) is shown. Number of rhythmic genes is represented as total and percentage of the transcription factors on the array. The rhythmic scoring was performed at three different pMMC-beta thresholds.
Rhythmic (%) on the array
(p < 0.1)
(all genes in Edwards K. D. et.al.)
Circadian function of transcription factors
In the in silico analysis (Figure 1), we found several night-expressed transcription factors. We wondered if such transcription factors could be the as of yet unidentified clock components proposed by current models [16, 17]. To generically test this hypothesis, we surveyed T-DNA tagged lines targeting these transcription factors, obtained from the public stock center, and measured circadian rhythms of these mutants in our system. However, no strong alternations of the circadian rhythm were observed in any of these lines under our assay condition (data not shown). Our observation suggested that none of these factors are the predicted clock element, and thus alternative approaches must be used to define such circadian mutants.
Plants targeting transcription factors analyzed in this study. A total of 198 mutants, including 198 misexpression were analyzed in this study. The misexpression lines targeted 39 MYB, 29 bHLH and 4 bZIP genes. The period phenotypes of 19 out of 22 over-expression lines were not consistent in multiple transgenics. Aberrant clock precision was only observed in 1 out of 3 bZIP48-ox lines. Numbers in ( ) indicated lines over-expressing same genes, which support that the phenotypes were caused by misexpression of the genes.
Misexpression lines exhibit aberrant clock phenotype. Mean circadian periods of leaf movement in Arabidopsis plants misexpressing transcription factors and control seedlings, estimated with BRASS. S.E.M.: standard error of the mean, n: number of contributing leaf traces.
Period (±) S.E.M
24.44 ± 0.46
24.53 ± 0.29
24.00 ± 0.19
26.69 ± 0.28
25.06 ± 0.33
24.65 ± 0.27
25.20 ± 0.44
25.39 ± 0.33
24.92 ± 0.21
24.70 ± 0.37
24.19 ± 0.25
24.94 ± 0.27
26.32 ± 0.77
25.09 ± 0.32
25.16 ± 0.36
24.76 ± 0.41
23.76 ± 0.34
During imaging experiments, we identified additional phenotypically altered lines in the pools of misexpression transgenics (Table 2, Additional files 2, 3 &4). A total of 19 over-expression lines exhibited aberrant periodicity, and one of the bZIP ox plants (bZIP48-ox) lacked clock precision. However, phenotypes from these lines were not confirmed by other lines targeting the over-expression of the same gene. One plausible explanation is that these detected phenotypes are not correlated to the targeted gene, and perhaps was caused by coincident mutations occurring during TDNA transformation.
MYB3R2, bHLH69, and bHLH92 could influence circadian rhythms
MYB3R2 and bHLH69 could alter clock-gene expression
Identification of previously functionally uncharacterized transcription factors in the clock
Here we describe that MYB3R2, bHLH69, and bHLH92 can contribute to the plant-circadian system. Alongside the characterized transcription factors CCA1, LHY, EPR1, FLC, and LUX, this now adds to the list of transcriptional clock-modulators. We provide evidence that MYB3R2 and bHLH69 influences circadian phase, whereas bHLH92 influences phase and periodicity, dependent on environmental conditions. These effects were not as strong as misexpression of CCA1, LHY, or LUX. It is still unclear how MYB3R2, bHLH69, and bHLH92 function in the clock system. Their specific effects depended on the light environment and on the output measured. Expression analysis showed that misexpression of MYB3R2 and bHLH69 resulted in altered transcript levels of clock genes; however, the circadian rhythms still kept 24-h periodicity albeit with aberrant phase. Thus, transcription factors identified here may play a role in environmental input to the clock or the mediation of its effects, rather than functioning as central-clock components. Such processes are described . A future effort to explore a detailed analysis of these transcription factors and the identification of target DNA elements remains to be carried out.
Plant circadian systems possess interlocked feedback loops [17–19]. In addition, there are various junctures for signal convergence and divergence in the input and output pathways [35, 36]. Though a set of clock regulating transcription factors has already been identified sufficient to describe much of the oscillator framework , many other components are believed to still be lacking .
We described an additional 20 misexpression lines that exhibit altered clock phenotypes. Whether these genes are components of input core, or output pathways, is as of yet unknown. This was as the phenotypes detected in these lines were not substantiated with alternative transgenic inserts. Forward-genetic analysis of loss-of-function phenotypes of these lines is worth further attention to determine their function in the clock.
A current mathematical model proposes the existence of an unknown transcription factor "X", which activates CCA1 and LHY [16, 17]. We tested hundreds of transcription factors as a pilot study of functional phenomics within the circadian clock, but it appears that in this test, we did not find "factor X." Still, functional analysis of more than a thousand transcription factors still remains. Thus, our pilot efforts substantiate that it is worthwhile to interrogate, via further functional genomic efforts, all known Arabidopsis transcription factors and to analyze their circadian responses.
Transcriptional networks in clock output pathways
To dissect the transcriptional regulation in circadian clock, we employed a systematic analysis of global-gene expression. In our in silico analysis, up to 20% of the transcription factors assayed were clock controlled (Table 1). This percentage is slightly higher than that of "all" circadian rhythmic genes in the Arabidopsis genome . This implies that the circadian oscillations in the output pathways are not just regulated by a select group of transcriptional feedbacks, and actually require a large number of rhythmic transcription factors. In contrast, the mammalian system is reported to only use around 16 cycling transcription factors, which oscillate in a circadian manner, to regulate the clock . The evolution of transcription-factor function and recruitment of molecular targets leads to the linking of many processes of plant physiology to the circadian system. Some components of these systems direct the clock itself, whereas others are only components of rhythmic physiological outputs.
Here we employed two genomic approaches as a pilot study to explore clock function. We found three genes that could modulate circadian parameters. Many other transcription factors oscillated in a circadian manner. This implicates these factors in physiological circadian outputs. Further exploration, with our described approaches, should bring novel insights in circadian input and output pathways, and identify genes previously non-described as functional within the central-clock oscillator.
Expression analyses through the public database
Gene codes of all transcription factors studied, referred to as AGI numbers, were collected within the Arabidopsis Information Resource. The gene-expression profiles in circadian experiment were available from the public microarray database Genevestigator [29, 28]. Expression values from the data were subject to score circadian rhythms with COSOPT . Data was collated without non-linear regression (Additional file 1).
Generation of transcription factor OX-lines
Full-length coding sequences (ATG-to-Stop) from MYB-, bHLH- and bZIP transcription factors were amplified from respective cDNAs by PCR using attB-sites containing gene-specific primers. Gateway Entry clones were generated via BP-reaction using the vector pDONR201 (Gateway system, Invitrogen, USA). Via LR-reaction the transcription factor cDNAs were transferred behind the double enhancer cauliflower mosaic virus 35S promoter in the plant expression vector pLEELA . Transgenic lines were generated by Agrobacterium tumefaciens-mediated transformation of Arabidopsis plants (Col-0) according to the floral-dip protocol . All transgenic lines were selected and self-fertilized. T2 plants were analyzed in this study.
Plant growth conditions
Seeds were surface sterilized with a 70% ethanol rinse, immediately followed by a rinse with 33% bleach, and then a twice washed with sterile water. The seeds were then aseptically sown on Murashige-Skoog (MS) 1.5% agar medium containing 3% sucrose (pH 5.7) with suitable antibiotic (25 mg/L Kanamycin or 12 mg/L Phosphinotrycin; dependent on the transgene) followed by stratification at 4°C for 4–5 days. Seedlings were grown for 9 days at 22°C under 12 hr light/12 hr dark cycles of 75 μmol m-2 sec-1 cool white fluorescent light. For flowering-time measurements, experiments were as described .
Leaf movement measurement
After 9 days of entraining growth, seedlings were transferred to fresh MS 1.5% agar medium (pH 5.7) containing 3% sucrose without antibiotic, and then agar blocks harboring single seedlings were placed to 25-well square tissue culture dishes (Bibby Sterilin). A set of twenty seedlings in a set within each dish were viewed from the side from plates in a vertically placement. The seedlings were entrained as described above for another day, and then were placed into a growth chamber for imaging over 1 week under constant white light (25–40 μmol m-2 sec-1) at a constant 22°C. A total of 14 dishes, containing 280 seedlings, were prepared and imaged with 14 monochromatic charge coupled device video cameras per an experiment. Images of seedlings from every camera were transferred to a computer via a Flashbus card and through a custom-built parallel-port controller unit (Universal Imaging, Germany) (system development by Visitron Systems), and were captured and saved every 30-min with a computer program Metaview 4.5 (Universal Imaging) over a week. The vertical positions of primary leaves from the images were measured and analyzed using Metamorph and BRASS, the latter provided by Prof. Andrew Millar (University Edinburgh) as described [28, 32]. Period lengths were estimated from the leaf movement data by the fast Fourier transform nonlinear least-squares method . Mean period estimates for each line were based on 10–20 leaf traces from two to four independent experiments analyzed.
Imaging was performed as described via established protocols, where the light was provided from red and blue light-emitting diodes at ~2 μmol m-2 s-1 [5, 42, 43]. Period length and Relative Amplitude of error (RAE) were estimated using FFT-NLLS program .
RNA isolation and reverse transcriptase-PCR
Seedlings grown for 1 week under LD cycles and replicate samples were harvested every 4 hours under LL conditions. Total RNA was isolated from the seedlings using the RNeasy Plant Mini Kit (Qiagen, USA), and then was treated with DNase I before reverse transcription. Reverse transcription was performed on 1.0 μg of total RNA with SuperscriptII (Invitrogen). Quantitative PCR were performed with iQ5 real-time PCR system (BIO-RAD). Gene-specific primers were described previously: CCA1, LHY and TOC1 , GI and TUB . Primers for MYB3R2, bHLH69 and bHLH92 were designed as follow:
We are most grateful for editorial comments from Dr. Chiarina Darrah. Additional gratitude is extended to Mr. Wolfgang Feneberg (Visitron Systems GmbH, Germany) for helping to develop the leaf-imaging system, and to Dr. Kieron Edwards, Dr. Paul Brown, and Prof. Andrew Millar (University of Edinburgh, UK) for advising our data analysis. We thank Nottingham Arabidopsis Stock Centre for providing seeds. This work was supported in the SJD group by a grant from the Deutsche Forschungsgemeinschaft (DA1061/2-1), which financially supported MAD, from the German-Israeli Project Cooperation (DIP project H 3.1), and from the Max Planck Society. Work in the BW group acknowledges funding from the German Federal Ministry of Education and Research (BMBF) in the context of the German plant genomics program GABI (Förderkennzeichen 0312273).
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