Anna Flis

Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize

The diversity of metabolites found in plants is by far greater than in most other organisms. Metabolic profiling techniques, which measure many of these compounds simultaneously, enabled investigating the regulation of metabolic networks and proved to be useful for predicting important agronomic traits. However, little is known about the genetic basis of metabolites in crops such as maize. Here, a set of 289 diverse maize inbred lines was genotyped with 56,110 SNPs and assayed for 118 biochemical compounds in the leaves of young plants, as well as for agronomic traits of mature plants in field trials. Metabolite concentrations had on average a repeatability of 0.73 and showed a correlation pattern that largely reflected their functional grouping. Genome-wide association mapping with correction for population structure and cryptic relatedness identified for 26 distinct metabolites strong associations with SNPs, explaining up to 32.0% of the observed genetic variance. On nine chromosomes, we detected 15 distinct SNP–metabolite associations, each of which explained more then 15% of the genetic variance. For lignin precursors, including p-coumaric acid and caffeic acid, we found strong associations (P values to ) with a region on chromosome 9 harboring cinnamoyl-CoA reductase, a key enzyme in monolignol synthesis and a target for improving the quality of lignocellulosic biomass by genetic engineering approaches. Moreover, lignin precursors correlated significantly with lignin content, plant height, and dry matter yield, suggesting that metabolites represent promising connecting links for narrowing the genotype–phenotype gap of complex agronomic traits.

Arabidopsis coordinates the diurnal regulation of carbon allocation and growth across a wide range of photoperiods

In short photoperiods, plants accumulate starch more rapidly in the light and degrade it more slowly at night, ensuring that their starch reserves last until dawn. To investigate the accompanying changes in the timing of growth, Arabidopsis was grown in a range of photoperiods and analyzed for rosette biomass, photosynthesis, respiration, ribosome abundance, polysome loading, starch, and over 40 metabolites at dawn and dusk. The data set was used to model growth rates in the daytime and night, and to identify metabolites that correlate with growth. Modeled growth rates and polysome loading were high in the daytime and at night in long photoperiods, but decreased at night in short photoperiods. Ribosome abundance was similar in all photoperiods. It is discussed how the amount of starch accumulated in the light period, the length of the night, and maintenance costs interact to constrain growth at night in short photoperiods, and alter the strategy for optimizing ribosome use. Significant correlations were found in the daytime and the night between growth rates and the levels of the sugar-signal trehalose 6-phosphate and the amino acid biosynthesis intermediate shikimate, identifying these metabolites as hubs in a network that coordinates growth with diurnal changes in the carbon supply.

Multiscale digital Arabidopsis predicts individual organ and whole-organism growth

Significance 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. 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.

Regulatory Properties of ADP Glucose Pyrophosphorylase Are Required for Adjustment of Leaf Starch Synthesis in Different Photoperiods

The properties of a key enzyme of starch synthesis permit adjustment of this process under different day lengths. Arabidopsis (Arabidopsis thaliana) leaves synthesize starch faster in short days than in long days, but the mechanism that adjusts the rate of starch synthesis to daylength is unknown. To understand this mechanism, we first investigated whether adjustment occurs in mutants lacking components of the circadian clock or clock output pathways. Most mutants adjusted starch synthesis to daylength, but adjustment was compromised in plants lacking the GIGANTEA or FLAVIN-BINDING, KELCH REPEAT, F BOX1 components of the photoperiod-signaling pathway involved in flowering. We then examined whether the properties of the starch synthesis enzyme adenosine 5′-diphosphate-glucose pyrophosphorylase (AGPase) are important for adjustment of starch synthesis to daylength. Modulation of AGPase activity is known to bring about short-term adjustments of photosynthate partitioning between starch and sucrose (Suc) synthesis. We found that adjustment of starch synthesis to daylength was compromised in plants expressing a deregulated bacterial AGPase in place of the endogenous AGPase and in plants containing mutant forms of the endogenous AGPase with altered allosteric regulatory properties. We suggest that the rate of starch synthesis is in part determined by growth rate at the end of the preceding night. If growth at night is low, as in short days, there is a delay before growth recovers during the next day, leading to accumulation of Suc and stimulation of starch synthesis via activation of AGPase. If growth at night is fast, photosynthate is used for growth at the start of the day, Suc does not accumulate, and starch synthesis is not up-regulated.

Cellulose synthesis and cell expansion are regulated by different mechanisms in growing Arabidopsis hypocotyls

The production of cellulose in the plant cell wall is controlled by metabolic signals, while the expansion of cells is regulated by changes in cell wall properties controlled by the biological clock. Plant growth is sustained by two complementary processes: biomass biosynthesis and cell expansion. The cell wall is crucial to both as it forms the majority of biomass, while its extensibility limits cell expansion. Cellulose is a major component of the cell wall and cellulose synthesis is pivotal to plant cell growth, and its regulation is poorly understood. Using periodic diurnal variation in Arabidopsis thaliana hypocotyl growth, we found that cellulose synthesis and cell expansion can be uncoupled and are regulated by different mechanisms. We grew Arabidopsis plants in very short photoperiods and used a combination of extended nights, continuous light, sucrose feeding experiments, and photosynthesis inhibition to tease apart the influences of light, metabolic, and circadian clock signaling on rates of cellulose biosynthesis and cell wall biomechanics. We demonstrate that cell expansion is regulated by protein-mediated changes in cell wall extensibility driven by the circadian clock. By contrast, the biosynthesis of cellulose is controlled through intracellular trafficking of cellulose synthase enzyme complexes regulated exclusively by metabolic signaling related to the carbon status of the plant and independently of the circadian clock or light signaling.

Leaf Starch Turnover Occurs in Long Days and in Falling Light at the End of the Day

Starch in Arabidopsis leaves is increasingly liable to degradation with time after dawn, so that accumulation slows and turnover in response to falling light accelerates as the day proceeds. We investigated whether starch degradation occurs at the same time as starch synthesis in Arabidopsis (Arabidopsis thaliana) leaves in the light. Starch accumulated in a linear fashion for about 12 h after dawn, then accumulation slowed and content plateaued. Following decreases in light intensity, the rate of accumulation of starch declined in proportion to the decline in photosynthesis if the decrease occurred <10 h after dawn, but accumulation ceased or loss of starch occurred if the same decrease in light intensity was imposed more than 10 h after dawn. These changes in starch accumulation patterns after prolonged periods in the light occurred at both high and low starch contents and were not related to time-dependent changes in either the rate of photosynthesis or the partitioning of assimilate between starch and Suc, as assessed from metabolite measurements and 14CO2 pulse experiments. Instead, measurements of incorporation of 13C from 13CO2 into starch and of levels of the starch degradation product maltose showed that substantial starch degradation occurred simultaneously with synthesis at time points >14 h after dawn and in response to decreases in light intensity that occurred >10 h after dawn. Starch measurements in circadian clock mutants suggested that the clock influences the timing of onset of degradation. We conclude that the propensity for leaf starch to be degraded increases with time after dawn. The importance of this phenomenon for efficient use of carbon for growth in long days and for prevention of starvation during twilight is discussed.

Defining the robust behaviour of the plant clock gene circuit with absolute RNA timeseries and open infrastructure

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.

Photoperiod‐dependent changes in the phase of core clock transcripts and global transcriptional outputs at dawn and dusk in Arabidopsis

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.

Circadian, Carbon, and Light Control of Expansion Growth and Leaf Movement

A 3D imaging platform was used to analyze the contribution of clock and light signaling to the regulation of diurnal changes in rosette expansion rate and leaf angles in Arabidopsis. We used Phytotyping4D to investigate the contribution of clock and light signaling to the diurnal regulation of rosette expansion growth and leaf movement in Arabidopsis (Arabidopsis thaliana). Wild-type plants and clock mutants with a short (lhycca1) and long (prr7prr9) period were analyzed in a T24 cycle and in T-cycles that were closer to the mutants’ period. Wild types also were analyzed in various photoperiods and after transfer to free-running light or darkness. Rosette expansion and leaf movement exhibited a circadian oscillation, with superimposed transients after dawn and dusk. Diurnal responses were modified in clock mutants. lhycca1 exhibited an inhibition of growth at the end of night and growth rose earlier after dawn, whereas prr7prr9 showed decreased growth for the first part of the light period. Some features were partly rescued by a matching T-cycle, like the inhibition in lhycca1 at the end of the night, indicating that it is due to premature exhaustion of starch. Other features were not rescued, revealing that the clock also regulates expansion growth more directly. Expansion growth was faster at night than in the daytime, whereas published work has shown that the synthesis of cellular components is faster in the day than at nighttime. This temporal uncoupling became larger in short photoperiods and may reflect the differing dependence of expansion and biosynthesis on energy, carbon, and water. While it has been proposed that leaf expansion and movement are causally linked, we did not observe a consistent temporal relationship between expansion and leaf movement.

Parallel analysis of arabidopsis circadian clock mutants reveals different scales of transcriptome and proteome regulation

The circadian clock regulates physiological processes central to growth and survival. To date, most plant circadian clock studies have relied on diurnal transcriptome changes to elucidate molecular connections between the circadian clock and observable phenotypes in wild-type plants. Here, we have integrated RNA-sequencing and protein mass spectrometry data to comparatively analyse the lhycca1, prr7prr9, gi and toc1 circadian clock mutant rosette at the end of day and end of night. Each mutant affects specific sets of genes and proteins, suggesting that the circadian clock regulation is modular. Furthermore, each circadian clock mutant maintains its own dynamically fluctuating transcriptome and proteome profile specific to subcellular compartments. Most of the measured protein levels do not correlate with changes in their corresponding transcripts. Transcripts and proteins that have coordinated changes in abundance are enriched for carbohydrate- and cold-responsive genes. Transcriptome changes in all four circadian clock mutants also affect genes encoding starch degradation enzymes, transcription factors and protein kinases. The comprehensive transcriptome and proteome datasets demonstrate that future system-driven research of the circadian clock requires multi-level experimental approaches. Our work also shows that further work is needed to elucidate the roles of post-translational modifications and protein degradation in the regulation of clock-related processes.