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19 Publications visible to you, out of a total of 19

Abstract (Expand)

Predicting a multicellular organism’s phenotype quantitatively from its genotype is challenging, as genetic effects must propagate across scales. Circadian clocks are intracellular regulators that control temporal gene expression patterns and hence metabolism, physiology and behaviour. Here we explain and predict canonical phenotypes of circadian timing in a multicellular, model organism. We used diverse metabolic and physiological data to combine and extend mathematical models of rhythmic gene expression, photoperiod-dependent flowering, elongation growth and starch metabolism within a Framework Model for the vegetative growth of Arabidopsis thaliana, sharing the model and data files in a structured, public resource. The calibrated model predicted the effect of altered circadian timing upon each particular phenotype in clock-mutant plants under standard laboratory conditions. Altered night-time metabolism of stored starch accounted for most of the decrease in whole-plant biomass, as previously proposed. Mobilization of a secondary store of malate and fumarate was also mis-regulated, accounting for any remaining biomass defect. The three candidate mechanisms tested did not explain this organic acid accumulation. Our results link genotype through specific processes to higher-level phenotypes, formalizing our understanding of a subtle, pleiotropic syndrome at the whole-organism level, and validating the systems approach to understand complex traits starting from intracellular circuits.

Authors: Yin Hoon Chew, Daniel D Seaton, Virginie Mengin, Anna Flis, Sam T Mugford, Gavin M George, Michael Moulin, Alastair Hume, Samuel C Zeeman, Teresa B Fitzpatrick, Alison M Smith, Mark Stitt, Andrew J Millar

Date Published: 1st Jul 2022

Publication Type: Journal

Abstract (Expand)

The circadian clock coordinates plant physiology and development. Mathematical clock models have provided a rigorous framework to understand how the observed rhythms emerge from disparate, molecular processes. However, models of the plant clock have largely been built and tested against RNA timeseries data in arbitrary, relative units. This limits model transferability, refinement from biochemical data and applications in synthetic biology. Here, we incorporate absolute mass units into a detailed model of the clock gene network in Arabidopsis thaliana. We re-interpret the established P2011 model, highlighting a transcriptional activator that overlaps the function of REVEILLE 8/LHY-CCA1-LIKE 5. The U2020 model incorporates the repressive regulation of PRR genes, a key feature of the most detailed clock model KF2014, without greatly increasing model complexity. We tested the experimental error distributions of qRT-PCR data calibrated for units of RNA transcripts/cell and of circadian period estimates, in order to link the models to data more appropriately. U2019 and U2020 models were constrained using these data types, recreating previously-described circadian behaviours with RNA metabolic processes in absolute units. To test their inferred rates, we estimated a distribution of observed, transcriptome-wide transcription rates (Plant Empirical Transcription Rates, PETR) in units of transcripts/cell/hour. The PETR distribution and the equivalent degradation rates indicated that the models’ predicted rates are biologically plausible, with individual exceptions. In addition to updated clock models, FAIR data resources and a software environment in Docker, this validation process represents an advance in biochemical realism for models of plant gene regulation.

Authors: Uriel Urquiza Garcia, Andrew J Millar

Date Published: 5th Aug 2021

Publication Type: Journal

Abstract (Expand)

The circadian clock coordinates plant physiology and development. Mathematical clock models have provided a rigorous framework to understand how the observed rhythms emerge from disparate, molecular processes. However, models of the plant clock have largely been built and tested against RNA timeseries data in arbitrary, relative units. This limits model transferability, refinement from biochemical data and applications in synthetic biology. Here, we incorporate absolute mass units into a detailed, gene circuit model of the clock in Arabidopsis thaliana. We re-interpret the established P2011 model, highlighting a transcriptional activator that overlaps the function of REVEILLE 8/LHY-CCA1-LIKE 5, and refactor dynamic equations for the Evening Complex. The U2020 model incorporates the repressive regulation of PRR genes, a key feature of the most detailed clock model F2014, without greatly increasing model complexity. We tested the experimental error distributions of qRT-PCR data calibrated for units of RNA transcripts/cell and of circadian period estimates, in order to link the models to data more appropriately. U2019 and U2020 models were constrained using these data types, recreating previously-described circadian behaviours with RNA metabolic processes in absolute units. To test their inferred rates, we estimated a distribution of observed, transcriptome-wide transcription rates (Plant Empirical Transcription Rates, PETR) in units of transcripts/cell/hour. The PETR distribution and the equivalent degradation rates indicated that the models’ predicted rates are biologically plausible, with individual exceptions. In addition to updated, explanatory models of the plant clock, this validation process represents an advance in biochemical realism for models of plant gene regulation.

Authors: Uriel Urquiza-Garcia, Andrew J Millar

Date Published: 20th Mar 2021

Publication Type: Tech report

Abstract (Expand)

Protein data over circadian time scale is scarce for clock transcription factors. Further work in this direction is required for refining quantitative clock models. However, gathering highly resolved dynamics of low-abundance transcription factors has been a major challenge in the field. In this work we provide a new tool that could help this major issue. Bioluminescence is an important tool for gathering data on circadian gene expression. It allows data collection over extended time periods for low signal levels, thanks to a large signal-to-noise ratio. However, the main reporter so far used, firefly luciferase (FLUC), presents some disadvantages for reporting total protein levels. For example, the rapid, post-translational inactivation of this luciferase will result in underestimation of protein numbers. A more stable reporter protein could in principle tackle this issue. We noticed that NanoLUC might fill this gap, given its reported brightness and the stability of both enzyme and substrate. However, no data in plant systems on the circadian time scale had been reported.

Authors: Uriel Urquiza-García, Andrew J. Millar

Date Published: 1st Dec 2019

Publication Type: Journal

Abstract (Expand)

We assessed mechanistic temperature influence on flowering by incorporating temperature-responsive flowering mechanisms across developmental age into an existing model. Temperature influences the leaf production rate as well as expression of FLOWERING LOCUS T (FT), a photoperiodic flowering regulator that is expressed in leaves. The Arabidopsis Framework Model incorporated temperature influence on leaf growth but ignored the consequences of leaf growth on and direct temperature influence of FT expression. We measured FT production in differently aged leaves and modified the model, adding mechanistic temperature influence on FT transcription, and causing whole-plant FT to accumulate with leaf growth. Our simulations suggest that in long days, the developmental stage (leaf number) at which the reproductive transition occurs is influenced by day length and temperature through FT, while temperature influences the rate of leaf production and the time (in days) the transition occurs. Further, we demonstrate that FT is mainly produced in the first 10 leaves in the Columbia (Col-0) accession, and that FT accumulation alone cannot explain flowering in conditions in which flowering is delayed. Our simulations supported our hypotheses that: (i) temperature regulation of FT, accumulated with leaf growth, is a component of thermal time, and (ii) incorporating mechanistic temperature regulation of FT can improve model predictions when temperatures change over time.

Authors: Hannah A Kinmonth-Schultz, Melissa J S MacEwen, Daniel D Seaton, Andrew J Millar, Takato Imaizumi, Soo-Hyung Kim

Date Published: 2019

Publication Type: Journal

Abstract (Expand)

Plants sense light and temperature changes to regulate flowering time. Here, we show that expression of the Arabidopsis florigen gene, FLOWERING LOCUS T (FT), peaks in the morning during spring, a different pattern than we observe in the laboratory. Providing our laboratory growth conditions with a red/far-red light ratio similar to open-field conditions and daily temperature oscillation is sufficient to mimic the FT expression and flowering time in natural long days. Under the adjusted growth conditions, key light signalling components, such as phytochrome A and EARLY FLOWERING 3, play important roles in morning FT expression. These conditions stabilize CONSTANS protein, a major FT activator, in the morning, which is probably a critical mechanism for photoperiodic flowering in nature. Refining the parameters of our standard growth conditions to more precisely mimic plant responses in nature can provide a powerful method for improving our understanding of seasonal response.

Authors: Y. H. Song, A. Kubota, M. S. Kwon, M. F. Covington, N. Lee, E. R. Taagen, D. Laboy Cintron, D. Y. Hwang, R. Akiyama, S. K. Hodge, H. Huang, N. H. Nguyen, D. A. Nusinow, A. J. Millar, K. K. Shimizu, T. Imaizumi

Date Published: 27th Sep 2018

Publication Type: Not specified

Abstract (Expand)

Summary paragraph Predicting a multicellular organism’s phenotype quantitatively from its genotype is challenging, as genetic effects must propagate up time and length scales. Circadian clocks arelength scales. Circadian clocks are intracellular regulators that control temporal gene expression patterns and hence metabolism, physiology and behaviour, from sleep/wake cycles in mammals to flowering in plants 1–3 . Clock genes are rarely essential but appropriate alleles can confer a competitive advantage 4,5 and have been repeatedly selected during crop domestication 3,6 . Here we quantitatively explain and predict canonical phenotypes of circadian timing in a multicellular, model organism. We used metabolic and physiological data to combine and extend mathematical models of rhythmic gene expression, photoperiod-dependent flowering, elongation growth and starch metabolism within a Framework Model for growth of Arabidopsis thaliana 7–9 . The model predicted the effect of altered circadian timing upon each particular phenotype in clock-mutant plants. Altered night-time metabolism of stored starch accounted for most but not all of the decrease in whole-plant growth rate. Altered mobilisation of a secondary store of organic acids explained the remaining defect. Our results link genotype through specific processes to higher-level phenotypes, formalising our understanding of a subtle, pleiotropic syndrome at the whole-organism level, and validating the systems approach to understand complex traits starting from intracellular circuits.

Authors: Yin Hoon Chew, Daniel D. Seaton, Virginie Mengin, Anna Flis, Sam T. Mugford, Alison M. Smith, Mark Stitt, Andrew J Millar

Date Published: 6th Feb 2017

Publication Type: Tech report

Abstract (Expand)

Predicting a multicellular organism’s phenotype quantitatively from its genotype is challenging, as genetic effects must propagate across scales. Circadian clocks are intracellular regulators that control temporal gene expression patterns and hence metabolism, physiology and behaviour. Here we explain and predict canonical phenotypes of circadian timing in a multicellular, model organism. We used diverse metabolic and physiological data to combine and extend mathematical models of rhythmic gene expression, photoperiod-dependent flowering, elongation growth and starch metabolism within a Framework Model for the vegetative growth of Arabidopsis thaliana, sharing the model and data files in a structured, public resource. The calibrated model predicted the effect of altered circadian timing upon each particular phenotype in clock-mutant plants under standard laboratory conditions. Altered night-time metabolism of stored starch accounted for most of the decrease in whole-plant biomass, as previously proposed. Mobilisation of a secondary store of malate and fumarate was also mis-regulated, accounting for any remaining biomass defect. We test three candidate mechanisms for the accumulation of these organic acids. Our results link genotype through specific processes to higher-level phenotypes, formalising our understanding of a subtle, pleiotropic syndrome at the whole-organism level, and validating the systems approach to understand complex traits starting from intracellular circuits. This work updates the first biorXiv version, February 2017,with an expanded description and additional analysis of the same core data sets and the same FMv2 model, summary tables and supporting, follow-on data from three further studies with further collaborators. This biorXiv revision constitutes the second version of this report.

Authors: Yin Hoon Chew, Daniel D. Seaton, Virginie Mengin, Anna Flis, Sam T. Mugford, Gavin M. George, Michael Moulin, Alastair Hume, Samuel C. Zeeman, Teresa B. Fitzpatrick, Alison M. Smith, Mark Stitt, Andrew J. Millar

Date Published: 6th Feb 2017

Publication Type: Tech report

Abstract (Expand)

Our understanding of the complex, transcriptional feedback loops in the circadian clock mechanism has depended upon quantitative, timeseries data from disparate sources. We measure clock gene RNA profiles in Arabidopsis thaliana seedlings, grown with or without exogenous sucrose, or in soil-grown plants and in wild-type and mutant backgrounds. The RNA profiles were strikingly robust across the experimental conditions, so current mathematical models are likely to be broadly applicable in leaf tissue. In addition to providing reference data, unexpected behaviours included co-expression of PRR9 and ELF4, and regulation of PRR5 by GI. Absolute RNA quantification revealed low levels of PRR9 transcripts (peak approx. 50 copies cell(-1)) compared with other clock genes, and threefold higher levels of LHY RNA (more than 1500 copies cell(-1)) than of its close relative CCA1. The data are disseminated from BioDare, an online repository for focused timeseries data, which is expected to benefit mechanistic modelling. One data subset successfully constrained clock gene expression in a complex model, using publicly available software on parallel computers, without expert tuning or programming. We outline the empirical and mathematical justification for data aggregation in understanding highly interconnected, dynamic networks such as the clock, and the observed design constraints on the resources required to make this approach widely accessible.

Authors: A. Flis, A. P. Fernandez, T. Zielinski, V. Mengin, R. Sulpice, K. Stratford, A. Hume, A. Pokhilko, M. M. Southern, D. D. Seaton, H. G. McWatters, M. Stitt, K. J. Halliday, A. J. Millar

Date Published: 16th Oct 2015

Publication Type: Not specified

Abstract (Expand)

Clock-regulated pathways coordinate the response of many developmental processes to changes in photoperiod and temperature. We model two of the best-understood clock output pathways in Arabidopsis, which control key regulators of flowering and elongation growth. In flowering, the model predicted regulatory links from the clock to cycling DOF factor 1 (CDF1) and flavin-binding, KELCH repeat, F-box 1 (FKF1) transcription. Physical interaction data support these links, which create threefold feed-forward motifs from two clock components to the floral regulator FT. In hypocotyl growth, the model described clock-regulated transcription of phytochrome-interacting factor 4 and 5 (PIF4, PIF5), interacting with post-translational regulation of PIF proteins by phytochrome B (phyB) and other light-activated pathways. The model predicted bimodal and end-of-day PIF activity profiles that are observed across hundreds of PIF-regulated target genes. In the response to temperature, warmth-enhanced PIF4 activity explained the observed hypocotyl growth dynamics but additional, temperature-dependent regulators were implicated in the flowering response. Integrating these two pathways with the clock model highlights the molecular mechanisms that coordinate plant development across changing conditions.

Authors: D. D. Seaton, R. W. Smith, Y. H. Song, D. R. MacGregor, K. Stewart, G. Steel, J. Foreman, S. Penfield, T. Imaizumi, A. J. Millar, K. J. Halliday

Date Published: 21st Jan 2015

Publication Type: Not specified

Abstract (Expand)

Understanding how dynamic molecular networks affect whole-organism physiology, analogous to mapping genotype to phenotype, remains a key challenge in biology. Quantitative models that represent processes at multiple scales and link understanding from several research domains can help to tackle this problem. Such integrated models are more common in crop science and ecophysiology than in the research communities that elucidate molecular networks. Several laboratories have modeled particular aspects of growth in Arabidopsis thaliana, but it was unclear whether these existing models could productively be combined. We test this approach by constructing a multiscale model of Arabidopsis rosette growth. Four existing models were integrated with minimal parameter modification (leaf water content and one flowering parameter used measured data). The resulting framework model links genetic regulation and biochemical dynamics to events at the organ and whole-plant levels, helping to understand the combined effects of endogenous and environmental regulators on Arabidopsis growth. The framework model was validated and tested with metabolic, physiological, and biomass data from two laboratories, for five photoperiods, three accessions, and a transgenic line, highlighting the plasticity of plant growth strategies. The model was extended to include stochastic development. Model simulations gave insight into the developmental control of leaf production and provided a quantitative explanation for the pleiotropic developmental phenotype caused by overexpression of miR156, which was an open question. Modular, multiscale models, assembling knowledge from systems biology to ecophysiology, will help to understand and to engineer plant behavior from the genome to the field.

Authors: Y. H. Chew, B. Wenden, A. Flis, V. Mengin, J. Taylor, C. L. Davey, C. Tindal, H. Thomas, H. J. Ougham, P. de Reffye, M. Stitt, M. Williams, R. Muetzelfeldt, K. J. Halliday, A. J. Millar

Date Published: 10th Sep 2014

Publication Type: Not specified

Abstract

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Authors: Karl Fogelmark, Carl Troein

Date Published: 17th Jul 2014

Publication Type: Not specified

Abstract

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Authors: Karl Fogelmark, Carl Troein

Date Published: 17th Jul 2014

Publication Type: Journal

Abstract (Expand)

In many plants, starch is synthesized during the day and degraded during the night to avoid carbohydrate starvation in darkness. The circadian clock participates in a dynamic adjustment of starch turnover to changing environmental condition through unknown mechanisms. We used mathematical modelling to explore the possible scenarios for the control of starch turnover by the molecular components of the plant circadian clock. Several classes of plausible models were capable of describing the starch dynamics observed in a range of clock mutant plants and light conditions, including discriminating circadian protocols. Three example models of these classes are studied in detail, differing in several important ways. First, the clock components directly responsible for regulating starch degradation are different in each model. Second, the intermediate species in the pathway may play either an activating or inhibiting role on starch degradation. Third, the system may include a light-dependent interaction between the clock and downstream processes. Finally, the clock may be involved in the regulation of starch synthesis. We discuss the differences among the models' predictions for diel starch profiles and the properties of the circadian regulators. These suggest additional experiments to elucidate the pathway structure, avoid confounding results and identify the molecular components involved.

Authors: D. D. Seaton, O. Ebenhoh, A. J. Millar, A. Pokhilko

Date Published: 18th Dec 2013

Publication Type: Not specified

Abstract (Expand)

The circadian clocks that drive daily rhythms in animals are tightly coupled among the cells of some tissues. The coupling profoundly affects cellular rhythmicity and is central to contemporary understanding of circadian physiology and behavior. In contrast, studies of the clock in plant cells have largely ignored intercellular coupling, which is reported to be very weak or absent. We used luciferase reporter gene imaging to monitor circadian rhythms in leaves of Arabidopsis thaliana plants, achieving resolution close to the cellular level. Leaves grown without environmental cycles for up to 3 wk reproducibly showed spatiotemporal waves of gene expression consistent with intercellular coupling, using several reporter genes. Within individual leaves, different regions differed in phase by up to 17 h. A broad range of patterns was observed among leaves, rather than a common spatial distribution of circadian properties. Leaves exposed to light-dark cycles always had fully synchronized rhythms, which could desynchronize rapidly. After 4 d in constant light, some leaves were as desynchronized as leaves grown without any rhythmic input. Applying light-dark cycles to such a leaf resulted in full synchronization within 2-4 d. Thus, the rhythms of all cells were coupled to external light-dark cycles far more strongly than the cellular clocks were coupled to each other. Spontaneous desynchronization under constant conditions was limited, consistent with weak intercellular coupling among heterogeneous clocks. Both the weakness of coupling and the heterogeneity among cells are relevant to interpret molecular studies and to understand the physiological functions of the plant circadian clock.

Authors: B. Wenden, D. L. Toner, S. K. Hodge, R. Grima, A. J. Millar

Date Published: 13th Apr 2012

Publication Type: Not specified

Abstract (Expand)

Circadian clocks synchronise biological processes with the day/night cycle, using molecular mechanisms that include interlocked, transcriptional feedback loops. Recent experiments identified the evening complex (EC) as a repressor that can be essential for gene expression rhythms in plants. Integrating the EC components in this role significantly alters our mechanistic, mathematical model of the clock gene circuit. Negative autoregulation of the EC genes constitutes the clock's evening loop, replacing the hypothetical component Y. The EC explains our earlier conjecture that the morning gene Pseudo-Response Regulator 9 was repressed by an evening gene, previously identified with Timing Of CAB Expression1 (TOC1). Our computational analysis suggests that TOC1 is a repressor of the morning genes Late Elongated Hypocotyl and Circadian Clock Associated1 rather than an activator as first conceived. This removes the necessity for the unknown component X (or TOC1mod) from previous clock models. As well as matching timeseries and phase-response data, the model provides a new conceptual framework for the plant clock that includes a three-component repressilator circuit in its complex structure.

Authors: A. Pokhilko, A. P. Fernandez, K. D. Edwards, M. M. Southern, K. J. Halliday, A. J. Millar

Date Published: 6th Mar 2012

Publication Type: Not specified

Abstract (Expand)

bioRxiv preprint 2017 Plants respond to seasonal cues such as the photoperiod, to adapt to current conditions and to prepare for environmental changes in the season to come. To assess photoperiodic responses at the protein level, we quantified the proteome of the model plant Arabidopsis thaliana by mass spectrometry across four photoperiods. This revealed coordinated changes of abundance in proteins of photosynthesis, primary and secondary metabolism, including pigment biosynthesis, consistent with higher metabolic activity in long photoperiods. Higher translation rates in the day time than the night likely contribute to these changes via rhythmic changes in RNA abundance. Photoperiodic control of protein levels might be greatest only if high translation rates coincide with high transcript levels in some photoperiods. We term this proposed mechanism ‘translational coincidence’, mathematically model its components, and demonstrate its effect on the Arabidopsis proteome. Datasets from a green alga and a cyanobacterium suggest that translational coincidence contributes to seasonal control of the proteome in many phototrophic organisms. This may explain why many transcripts but not their cognate proteins exhibit diurnal rhythms.

Authors: Daniel Seaton, Alexander Graf, Katja Baerenfaller, Mark Stitt, Andrew Millar, Wilhelm Gruissem

Date Published: No date defined

Publication Type: Not specified

Abstract

BioRxiv preprint:

Authors: Hannah A Kinmonth-Schultz, Melissa J MacEwen, Daniel D Seaton, Andrew J Millar, Takato Imaizumi, Soo-Hyung Kim

Date Published: No date defined

Publication Type: Not specified

Abstract (Expand)

BioRxiv preprint, 4 April 2018. Abstract: Daily light-dark cycles (LD) drive dynamic regulation of plant and algal transcriptomes via photoreceptor pathways and 24-hour, circadian rhythms. Diel regulation of protein levels and modifications has been less studied. Ostreococcus tauri, the smallest free-living eukaryote, provides a minimal model proteome for the green lineage. Here, we compare transcriptome data under LD to the algal proteome and phosphoproteome, assayed using shotgun mass-spectrometry. Under 10% of 855 quantified proteins were rhythmic but two-thirds of 860 phosphoproteins showed rhythmic modification(s). Most rhythmic proteins peaked in the daytime. Model simulations showed that light-stimulated protein synthesis largely accounts for this distribution of protein peaks. Prompted by apparently dark-stable proteins, we sampled during prolonged dark adaptation, where stable RNAs and very limited change to the proteome suggested a quiescent, cellular “dark state”. In LD, acid-directed and proline-directed protein phosphorylation sites were regulated in antiphase. Strikingly, 39% of rhythmic phospho-sites reached peak levels just before dawn. This anticipatory phosphorylation is distinct from light-responsive translation but consistent with plant phosphoprotein profiles, suggesting that a clock-regulated phospho-dawn prepares green cells for daytime functions.

Authors: Zeenat B. Noordally, Matthew M. Hindle, Sarah F. Martin, Daniel D. Seaton, Ian Simpson, Thierry Le Bihan, Andrew J. Millar

Date Published: No date defined

Publication Type: Not specified

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