ORCID Profile
0000-0003-1756-3654
Current Organisation
The University of Edinburgh
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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: Institution of Engineering and Technology (IET)
Date: 06-2007
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: Wiley
Date: 15-07-2016
DOI: 10.1111/PCE.12754
Abstract: Plants use the circadian clock to sense photoperiod length. Seasonal responses like flowering are triggered at a critical photoperiod when a light-sensitive clock output coincides with light or darkness. However, many metabolic processes, like starch turnover, and growth respond progressively to photoperiod duration. We first tested the photoperiod response of 10 core clock genes and two output genes. qRT-PCR analyses of transcript abundance under 6, 8, 12 and 18 h photoperiods revealed 1-4 h earlier peak times under short photoperiods and detailed changes like rising PRR7 expression before dawn. Clock models recapitulated most of these changes. We explored the consequences for global gene expression by performing transcript profiling in 4, 6, 8, 12 and 18 h photoperiods. There were major changes in transcript abundance at dawn, which were as large as those between dawn and dusk in a given photoperiod. Contributing factors included altered timing of the clock relative to dawn, light signalling and changes in carbon availability at night as a result of clock-dependent regulation of starch degradation. Their interaction facilitates coordinated transcriptional regulation of key processes like starch turnover, anthocyanin, flavonoid and glucosinolate biosynthesis and protein synthesis and underpins the response of metabolism and growth to photoperiod.
Publisher: SAGE Publications
Date: 10-2017
Abstract: Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.
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: Frontiers Media SA
Date: 15-05-2017
Publisher: Springer Science and Business Media LLC
Date: 13-12-2006
DOI: 10.1007/S00122-006-0468-Y
Abstract: Circadian rhythms regulate many aspects of plant growth, fitness and vigour. The components and detailed mechanism of circadian regulation to date have been dissected in the reference species Arabidopsis thaliana. To determine the genetic basis and range of natural allelic variation for intrinsic circadian period in the closest crop relatives, we used an accurate and high throughput data capture system to record rhythmic cotyledon movement in two immortal segregating populations of Brassica oleracea, derived from parent lines representing different crop types. Periods varied between 24.4 and 26.1 h between the parent lines, with transgressive segregation between extreme recombinant lines in both populations of approximately 3.5 h. The additive effect of in idual QTL identified in each population varied from 0.17 to 0.36 h. QTL detected in one doubled haploid population were verified and the mapping intervals further resolved by determining circadian period in genomic substitution lines derived from the parental lines. Comparative genomic analysis based on collinearity between Brassica and Arabidopsis also allowed identification of candidate orthologous genes known to regulate period in Arabidopsis, that may account for the additive circadian effects of specific QTL. The distinct QTL positions detected in the two populations, and the extent of transgressive segregation suggest that there is likely to be considerable scope for modulating the range of available circadian periods in natural populations and crop species of Brassica. This may provide adaptive advantage for optimising growth and development in different latitudes, seasons or climate conditions.
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: Proceedings of the National Academy of Sciences
Date: 22-04-2015
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: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Andrew Millar.