ORCID Profile
0000-0002-4958-4209
Current Organisation
University of Essex
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Publisher: Cold Spring Harbor Laboratory
Date: 06-02-2017
DOI: 10.1101/105437
Abstract: 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 erse 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, 0.1101/105437 , 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.
Publisher: Oxford University Press (OUP)
Date: 30-05-2022
DOI: 10.1093/INSILICOPLANTS/DIAC010
Abstract: 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 erse 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.
Publisher: The Royal Society
Date: 10-2015
DOI: 10.1098/RSOB.150042
Abstract: 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.
Publisher: Oxford University Press (OUP)
Date: 29-06-2017
DOI: 10.1104/PP.17.00601
Publisher: Proceedings of the National Academy of Sciences
Date: 02-09-2014
Abstract: Plants respond to environmental change by triggering biochemical and developmental networks across multiple scales. Multiscale models that link genetic input to the whole-plant scale and beyond might therefore improve biological understanding and yield prediction. We report a modular approach to build such models, validated by a framework model of Arabidopsis thaliana comprising four existing mathematical models. Our model brings together gene dynamics, carbon partitioning, organ growth, shoot architecture, and development in response to environmental signals. It predicted the biomass of each leaf in independent data, demonstrated flexible control of photosynthesis across photoperiods, and predicted the pleiotropic phenotype of a developmentally misregulated transgenic line. Systems biology, crop science, and ecology might thus be linked productively in a community-based approach to modeling.
Publisher: Wiley
Date: 17-01-2019
DOI: 10.1111/PCE.13440
Abstract: Plants accumulate reserves in the daytime to support growth at night. Circadian regulation of diel reserve turnover was investigated by profiling starch, sugars, glucose 6-phosphate, organic acids, and amino acids during a light-dark cycle and after transfer to continuous light in Arabidopsis wild types and in mutants lacking dawn (lhy cca1), morning (prr7 prr9), dusk (toc1, gi), or evening (elf3) clock components. The metabolite time series were integrated with published time series for circadian clock transcripts to identify circadian outputs that regulate central metabolism. (a) Starch accumulation was slower in elf3 and prr7 prr9. It is proposed that ELF3 positively regulates starch accumulation. (b) Reducing sugars were high early in the T-cycle in elf3, revealing that ELF3 negatively regulates sucrose recycling. (c) The pattern of starch mobilization was modified in all five mutants. A model is proposed in which dawn and dusk/evening components interact to pace degradation to anticipated dawn. (d) An endogenous oscillation of glucose 6-phosphate revealed that the clock buffers metabolism against the large influx of carbon from photosynthesis. (e) Low levels of organic and amino acids in lhy cca1 and high levels in prr7 prr9 provide evidence that the dawn components positively regulate the accumulation of amino acid reserves.
Location: Germany
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Virginie Mengin.