Bénédicte Wenden

A conserved molecular basis for photoperiod adaptation in two temperate legumes

Legumes were among the first plant species to be domesticated, and accompanied cereals in expansion of agriculture from the Fertile Crescent into diverse environments across the Mediterranean basin, Europe, Central Asia, and the Indian subcontinent. Although several recent studies have outlined the molecular basis for domestication and eco-geographic adaptation in the two main cereals from this region, wheat and barley, similar questions remain largely unexplored in their legume counterparts. Here we identify two major loci controlling differences in photoperiod response between wild and domesticated pea, and show that one of these, HIGH RESPONSE TO PHOTOPERIOD (HR), is an ortholog of EARLY FLOWERING 3 (ELF3), a gene involved in circadian clock function. We found that a significant proportion of flowering time variation in global pea germplasm is controlled by HR, with a single, widespread functional variant conferring altered circadian rhythms and the reduced photoperiod response associated with the spring habit. We also present evidence that ELF3 has a similar role in lentil, another major legume crop, with a distinct functional variant contributing to reduced photoperiod response in cultivars widely deployed in short-season environments. Our results identify the factor likely to have permitted the successful prehistoric expansion of legume cultivation to Northern Europe, and define a conserved genetic basis for major adaptive changes in flowering phenology and growth habit in an important crop group.

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.

Update on the genetic control of flowering in garden pea

The garden pea has been a model for the genetics of flowering for several decades and numerous flowering loci have been identified, but until recently little was known about the molecular nature of these loci. This paper presents an update on recent work on the molecular genetics of flowering in pea, outlining progress in gene and mutant isolation, expression analyses, grafting and other physiological studies, and candidate gene assessment. Work so far has led to the identification of the LATE1 and DNE loci as orthologues of Arabidopsis GIGANTEA and ELF4, respectively, and candidate genes for several other loci are being evaluated. Expression analysis of an expanded FT-like gene family suggests a more complex role for this group of genes. These results provide the first insight into the circadian clock, photoperiod response mechanism, and mobile signals in pea, and identify both conserved and divergent features in comparison with Arabidopsis.

Light inputs shape the Arabidopsis circadian system

The circadian clock is a fundamental feature of eukaryotic gene regulation that is emerging as an exemplar genetic sub-network for systems biology. The circadian system in Arabidopsis plants is complex, in part due to its phototransduction pathways, which are themselves under circadian control. We therefore analysed two simpler experimental systems. Etiolated seedlings entrained by temperature cycles showed circadian rhythms in the expression of genes that are important for the clock mechanism, but only a restricted set of downstream target genes were rhythmic in microarray assays. Clock control of phototransduction pathways remained robust across a range of light inputs, despite the arrhythmic transcription of light-signalling genes. Circadian interactions with light signalling were then analysed using a single active photoreceptor. Phytochrome A (phyA) is expected to be the only active photoreceptor that can mediate far-red (FR) light input to the circadian clock. Surprisingly, rhythmic gene expression was profoundly altered under constant FR light, in a phyA-dependent manner, resulting in high expression of evening genes and low expression of morning genes. Dark intervals were required to allow high-amplitude rhythms across the transcriptome. Clock genes involved in this response were identified by mutant analysis, showing that the EARLY FLOWERING 4 gene is a likely target and mediator of the FR effects. Both experimental systems illustrate how profoundly the light input pathways affect the plant circadian clock, and provide strong experimental manipulations to understand critical steps in the plant clock mechanism.

Spontaneous spatiotemporal waves of gene expression from biological clocks in the leaf

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.

Mapping of Candidate Genes Involved in Bud Dormancy and Flowering Time in Sweet Cherry (Prunus avium).

The timing of flowering in perennial plants is crucial for their survival in temperate climates and is regulated by the duration of bud dormancy. Bud dormancy release and bud break depend on the perception of cumulative chilling during endodormancy and heat during the bud development. The objectives of this work were to identify candidate genes involved in dormancy and flowering processes in sweet cherry, their mapping in two mapping progenies ‘Regina’ × ‘Garnet’ and ‘Regina’ × ‘Lapins’, and to select those candidate genes which co-localized with quantitative trait loci (QTLs) associated with temperature requirements for bud dormancy release and flowering. Based on available data on flowering processes in various species, a list of 79 candidate genes was established. The peach and sweet cherry orthologs were identified and primers were designed to amplify sweet cherry candidate gene fragments. Based on the amplified sequences of the three parents of the mapping progenies, SNPs segregations in the progenies were identified. Thirty five candidate genes were genetically mapped in at least one of the two progenies and all were in silico mapped. Co-localization between candidate genes and QTLs associated with temperature requirements and flowering date were identified for the first time in sweet cherry. The allelic composition of the candidate genes located in the major QTL for heat requirements and flowering date located on linkage group 4 have a significant effect on these two traits indicating their potential use for breeding programs in sweet cherry to select new varieties adapted to putative future climatic conditions.

Systems biology for plant breeding: the example of flowering time in pea.

As part of a breeding strategy applied to pea (Pisum sativum L.), we propose the use of modelling as a tool for studying flowering time. The pea, both a crop and a model species for developmental processes, represents a valuable tool for systems biology approaches. A preliminary computational model for flowering control was previously developed based on genetic and physiological approaches. This paper discusses possible improvements of the model based on recent molecular advances on the regulation of flowering in peas and the model species Arabidopsis thaliana. A combination of a genetic approach together with agroecophysiological models that are not based on genotype, built into a complete model for flowering time prediction is also proposed. This complete model should allow an accurate prediction of flower initiation and also provide an integrative tool that will be useful for various purposes, from genetic networks to crop models.

Bud Dormancy in Perennial Fruit Tree Species: A Pivotal Role for Oxidative Cues

For perennial plants, bud dormancy is a crucial step as its progression over winter determines the quality of bud break, flowering, and fruiting. In the past decades, many studies, based on metabolic, physiological, subcellular, genetic, and genomic analyses, have unraveled mechanisms underlying bud dormancy progression. Overall, all the pathways identified are interconnected in a very complex manner. Here, we review early and recent findings on the dormancy processes in buds of temperate fruit trees species including hormonal signaling, the role of plasma membrane, carbohydrate metabolism, mitochondrial respiration and oxidative stress, with an effort to link them together and emphasize the central role of reactive oxygen species accumulation in the control of dormancy progression.

A collection of European sweet cherry phenology data for assessing climate change

Professional and scientific networks built around the production of sweet cherry (Prunus avium L.) led to the collection of phenology data for a wide range of cultivars grown in experimental sites characterized by highly contrasted climatic conditions. We present a dataset of flowering and maturity dates, recorded each year for one tree when available, or the average of several trees for each cultivar, over a period of 37 years (1978–2015). Such a dataset is extremely valuable for characterizing the phenological response to climate change, and the plasticity of the different cultivars’ behaviour under different environmental conditions. In addition, this dataset will support the development of predictive models for sweet cherry phenology exploitable at the continental scale, and will help anticipate breeding strategies in order to maintain and improve sweet cherry production in Europe.

Multiscale digital Arabidopsis predicts individual organ and whole-organism growth (vol 111, pg E4127, 2014)

SYSTEMS BIOLOGY Correction for “Multiscale digital Arabidopsis predicts individual organ and whole-organism growth,” by Yin Hoon Chew, Bénédicte Wenden, Anna Flis, Virginie Mengin, Jasper Taylor, Christopher L. Davey, Christopher Tindal, Howard Thomas, Helen J. Ougham, Philippe de Reffye, Mark Stitt, Mathew Williams, Robert Muetzelfeldt, Karen J. Halliday, and Andrew J. Millar, which appeared in issue 39, September 30, 2014, of Proc Natl Acad Sci USA (111:E4127–E4136; first published September 2, 2014; 10.1073/ pnas.1410238111). The authors note that the affiliation for Philippe de Reffye should instead appear as “Cirad-Amis, Unité Mixte de Recherche, botAnique et bioinforMatique de l’Architecture des Plantes, F-34398 Montpellier Cedex 5, France.” The corrected author and affiliation lines appear below. The online version has been corrected.