This project will functionally analyze gene regulatory networks (GRNs) that act in plant shoot meristems to control the switch to flowering. We have defined an intricate network involving transcription factors and microRNAs that controls this developmental transition in Arabidopsis and its perennial relatives. The project will address how the activity of these GRNs are controlled by environmental cues, such as day length, and internal cues, such as phytohormones and metabolites, to initiate the earliest stages of the floral transition. The project involves constructing transgenic plants to control the temporal and quantitative expression of network components, testing regulatory connections in orthogonal systems, imaging the transition by confocal microscopy and collaboration with computational biologists modelling GRN activity.
Qualifications needed: Molecular biology, confocal imaging, computational capability
Contact person: George Coupland
The number of grains per spike is among the most variable and important traits determining final yield in cereal crops. Grain number is controlled by complex developmental processes including the regulation of meristem size, of branching and floret fertility. Grass mutants affecting inflorescence architecture have provided insights into the genes and gene networks regulating inflorescence architecture and seed number. This project uses the important cereal crop barley with a vast collection of developmental mutants to understand how the interplay between hormonal signalling and nutrient allocation to meristems controls yield in crop plants. The project will be carried out in close collaboration with a second Postdoc (project 3) across three research groups with expertise in developmental genetics, imaging, transport and signaling.
Qualifications needed: molecular plant biology, grass genetics, plant development, imaging
Contact persons: Maria von Korff-Schmising, Rüdiger Simon
Variation in grain number in cereal crops is determined by the activities of the shoot apical and axillary meristems that eventually form inflorescences. Inflorescence architecture is controlled by complex developmental processes including the regulation of meristem size, branching and floret fertility. This project aims to decipher the interrelationship of meristem development with metabolism and hormonal balance in barley and rice. The project includes the generation and imaging of fluorescent biosensors for calcium, sugars and hormones with the aim to study their transport and metabolism in relation to developmental programs. The work will generate important new insights into growth regulation and development. The postdocs will collaborate closely with a second Postdoc across three research groups with expertise in developmental genetics, imaging, transport and signaling.
Qualifications needed: molecular technologies: essential; advanced imaging, synthetic biology: advantageous
Contact persons: Wolf B Frommer
We have previously characterized process underlying diversity in leaf form between and within species and have identified genetic pathways influencing this trait. Here we propose to investigate the possible physiological and metabolic significance of this variation as well as possible feedbacks between metabolism and leaf form. The project will involve comparative studies of Cardamine hirsuta and Arabidopsis thaliana. References: Vuolo F, et al., (2016) Genes Dev. 30, 2370-75. 2. Gan X, et al., (2016) Nat Plants 2, 16167. 3. Rast-Somssich, M.I et al., (2015). Genes Dev 29, 2391-2404 Cartolano, M., et al., 4. 2015 PNAS 112, 10539-44. 5. Vlad D, et al., (2014) Science 343, 780-3.
Qualifications needed: Plant Molecular/Developmental Genetics (especially in Arabidopsis), Metabolic Physiology, NGS data analysis
Contact persons: Miltos Tsiantis, Ismene Karakasilioti
The plant apoplast is a metabolically active compartment where microbial and plant enzymes converge to a common metabolic network integral to plant growth, development, and immunity. In this project we will combine genetic, biochemical, metabolic, and cytological approaches to (1) determine apoplastic metabolic fluxes in multipartite interactions; (2) construct metabolic models with a focus on carbohydrate, purine and iron metabolism; (3) construct cell wall/apoplast-targeted sugar, purine and iron sensors to monitor root nutritional status over time during multipartite interactions and to (4) understand the role of specific metabolites in the establishment and function of plant-microbe interactions with focus on root beneficial and pathogenic fungi. Microbial and plant key regulators will be analyzed by genome mining and manipulation of host and microbe pathways.
Qualifications needed: fungal and/or plant genetics, R-statistics, immunity/stress and/or effector biology
Contact person: Alga Zuccaro
Plants recruit beneficial microbes to their roots but they also need to protect tissues against invasive pathogens causing disease. There is emerging evidence that nutrient availability and delivery/uptake systems impact the decision-making between plant-microbial accommodation (eg. symbioses) and immunity (defensive) programs. This project examines genetic, molecular and metabolic processes underpinning Arabidopsis root colonisation by fungal and bacterial endophytes. A major focus will be on signaling and metabolic interplay between host and microbe in response to the key micronutrient iron (Fe) and Fe-related polyamines, impacting accommodation vs defense outcomes. The project involves microbial genome mining, manipulation of host and microbe pathways, and metabolite profiling of root-endophyte systems.
Qualifications needed: microbiology, plant genetics, R-statistics, immunity/stress biology
Contact person: Jane Parker
Photosynthetic organisms ranging from land plants to microscopic algae are able to engage in mutualistic interactions with microbial communities derived from soil. In this project we will employ the unicellular, soil-borne green algae Chlamydomonas reinhardtii as a model organism and a whole-genome-sequenced culture collection of bacteria in a reductionist system that is amenable to high-throughput experimentation and genetic transformation of all interacting partners. The aim of this project is to use this novel experimental system to elucidate plant-microbe metabolic interdependencies, extract fundamental principles governing microbial community establishment and dynamics, and deepen our understanding of evolutionarily conserved mechanisms of plant-microbiota interactions.
Qualifications needed: Plant microbiota; microbiology; gnotobiotic systems; high-throughput sequencing data
Contact person: Ruben Garrido-Oter
The goal of this project is to obtain a quantitative understanding of plant signalling systems, in particular transcriptional networks involved in the regulation of floral development and leaf-shape variation. For this a combination of engineering synthetic networks in orthogonal cellular systems, advanced microscopy approaches and mathematical modelling will be implemented. The knowledge generated in this work will inform us how the effects of genetic variation at the level of gene regulatory networks translate into differential pathway function and hence phenotype, and be used to instruct experimental in planta studies.
Qualifications needed: Experience in plant/mammalian cell culture, molecular and cellbiology, synthetic biology and mathematical modelling.
Contact person: Matias Zurbriggen
This project aims at obtaining a mechanistic understanding of the differentiation of non-photosynthetic to photosynthetic cells. This involves the high-resolution description and reconstruction of gene-regulatory networks underpinning the differentiation of photosynthetic leaf mesophyll cells from undifferentiated cells and ii) the testing of hypotheses in newly established in vitro models employing concepts of synthetic biology, such as the optogenetic control of protein lifetimes, and single-cell analyses. The knowledge generated in this work will enable the targeted activation of photosynthesis in any plant cell type.
Qualifications needed: Experience in single-cell analysis, including single-cell transcriptome profiling is desired. A strong background in plant cell biology and in concepts of large-scale data analysis is required. Previous experience with microfluidic devices and in the application of synthetic biology tools is beneficial for this project.
Contact person: Andreas Weber
Assimilated C is allocated to numerous cellular sinks including sucrose for export, starch for transient energy storage, and cell-wall polymers for structural integrity of the cell. While the biosynthetic pathways to these carbon sinks have been well characterized, the question how a cell partitions carbon to all of these cellular sinks remains to be elucidated. Mechanisms regulating carbon allocation within the cell will be investigated by introducing plant carbon sinks into heterologous model organisms. These sinks will not only include multiple cell wall polymers and starch, but also cellular carbon supply and export. The obtained metabolic data will be used to generate pathway models to inform us how to modify the system/ add additional genes to advance our knowledge.
Qualifications needed: Biochemistry, Molecular Biology, Metabolite Analysis, first author publication(s)
Contact person: Markus Pauly
Plants sequester up of a third of their photosynthates into the soil. A large fraction of the secreted molecules comprises soluble carbohydrates and organic acids. One hypothesis is that carbon secreted by the plants is used to feed beneficial microbiota. While some of the transporters responsible for organic acid secretion are known, none of the carbohydrate export systems has been identified. Moreover, it is hypothesized that carbohydrates that are delivered from the photosynthetic organism travel via plasmodesmata to the cells that secrete them. The goal of this project is to use a combination of optogenetics, biosensors, synthetic molecular tools and advanced microscopy to identify and manipulate the plasmodesmatal and export mechanisms and explore the effect on colonization by microbes.
Qualifications needed: molecular technologies: essential; advanced imaging, synthetic biology: advantageous
Contact person: Wolf B Frommer
Genome sequences are key resources to understand functional processes and divergent trait evolution within and between different species. Within CEPLAS, many high-quality genome assemblies of closely related species of the Brassicaceae and other plant families are being generated. This makes it possible, in principle, to reveal intra-family similarities and structural variations from pairwise whole-genome alignments (WGA) as a major step towards family pangenome representations. However, even though efficient whole-genome alignment solutions exist there are no computational approaches that would annotate all genomic differences including the obvious hierarchy ranging from small single nucleotide changes to large complex rearrangements. The project will therefore extend SyRI, an existing algorithm for genome-wide structural rearrangement identification to solve this efficiently.
Qualifications needed: good algorithmic background, programming skills, basic knowledge in bioinformatics , Plus: experience with genomic data and/or plant genomics
Contact person: Gunnar Klau, Korbinian Schneeberger
Plant-associated microbial communities are complex systems in which populations of diverse microbes interact with each other and with the host, giving rise to emergent properties that have an impact on host fitness and nutrient cycling in soil. However, it is not currently understood how these properties arise and what is their mechanistic and genetic basis. We will take advantage of recent advances in the establishment of comprehensive culture collections of whole-genome sequenced microbes derived from soil and synthetic microbial community reconstruction experiments. The aim of this project is to develop the necessary computational framework to integrate phenotypic, genomic, metabolic and transcriptomic data into predictive models to identify the underlying principles governing plant-microbiota interactions at the molecular level.
Qualifications needed: Metabolic modeling (genome-scale model reconstruction; constraint-based models; dynamic FBA); next generation sequencing data; comparative genomics; microbiota
Contact person: Ruben Garrido-Oter
Plants need to allocate their resources on many different levels. A photosynthetic cell has to decide whether to export carbon or use it locally, during development, sink-source transitions in leaves, inflorescence induction and seed filling need to be timed.
The successful candidate will closely collaborate with researchers, in particular within CEPLAS RAs 1 (metabolism and development) & 3 (carbon allocation in a single cell), to develop mathematical models that represent the decision making processes and, as far as they are known, the molecular mechanisms underlying these. The models shall serve to investigate and understand the trade-offs that are involved in optimising resource allocation, and shall lead to predictions how these processes are affected by environmental or genetic perturbations, and how they can be optimise to increase plant performance.
Qualifications needed: Experience in developing and analysing mathematical models of biological systems. Differential equations, Flux Balance Analysis, Multivariate and non-linear optimisation. Programming skills.
Contact person: Oliver Ebenhöh
Within RA1 genome variation will be exploited across a wide area of species and within a complementary project in RA4, a genome comparison pipeline based on co-linear blocks is being developed to study synthenic relationships.
Here, we will complete our Mercator4 framework for functional annotation to allow almost complete classification of plant genes. We will leverage the underlying protein sub-family information to directly identify plant gene sub-families in the genome without prior gene calling. This will allow (a) obtaining an almost complete gene set of a new species with almost zero effort (b) with the co-linear blocks identified by the RA4 project, we will identify functional “orthologs” which provides the basis for a network analysis of these genes using expression information. Using the functional annotation we will tune network learning using sequence based functional annotat.
Qualifications needed: Computer and/or Data Science; C/C++/Java; phyton; machine learning/LTSM, hidden Markov models
Contact person: Björn Usadel