Refine
Has Fulltext
- no (56) (remove)
Year of publication
- 2023 (56) (remove)
Document Type
- Doctoral Thesis (56) (remove)
Language
- English (56) (remove)
Is part of the Bibliography
- yes (56)
Keywords
- photosynthesis (3)
- Arabidopsis thaliana (2)
- Photosynthese (2)
- fluctuating light (2)
- metabolomics (2)
- transcriptomics (2)
- (Xeno)Hormone (1)
- (xeno)hormones (1)
- Affordances (1)
- African weakly electric fish (1)
Institute
- Institut für Biochemie und Biologie (28)
- Institut für Physik und Astronomie (8)
- Institut für Chemie (4)
- Extern (2)
- Fachgruppe Betriebswirtschaftslehre (2)
- Institut für Ernährungswissenschaft (2)
- Institut für Geowissenschaften (2)
- Department Psychologie (1)
- Department Sport- und Gesundheitswissenschaften (1)
- Fachgruppe Politik- & Verwaltungswissenschaft (1)
Light is the essential energy source for plants to drive photosynthesis. In nature, light availability is highly variable and often fluctuates on very short time scales. As a result, plants developed mechanisms to cope with these fluctuations. Understanding how to improve light use efficiency in natural fluctuating light (FL) conditions is a major target for agronomy.
In the first project, we identified an Arabidopsis thaliana plant that showed reduced levels of rapidly inducible non-photochemical quenching (NPQ). This plant was devoid of any T-DNA insertion. Using a mapping-by-sequencing approach, we successfully located the causal genomic region near the end of chromosome 4. Through variant investigations in that region, we identified a deletion of about 20 kb encompassing 9 genes. By complementation analysis, we confirmed that one of the deleted genes, VTC2, is the causal gene responsible for the low NPQ. Loss of VTC2 decreased NPQ particularly in old leaves, with young leaves being only slightly affected. Additionally, ascorbate levels were almost abolished in old leaves, likely causing the NPQ decrease by reducing the activity of the xanthophyll cycle. Although ascorbate levels in younger leaves were reduced compared to wild-type plants, they remained at a comparably higher level. This difference may be due to the VTC2 paralog VTC5, which is expressed at a higher level in young leaves than in old ones.
Plants require the PROTON GRADIENT REGULATION 5 (PGR5) protein for survival in FL. pgr5 mutants die because they fail to increase the luminal proton concentration in response to high light (HL) phases. A rapid elevation in ∆pH is needed to slow down electron transport through the Cytochrome b6 f complex (photosynthetic control). In FL, such lack of control in the pgr5 mutants results in photosystem I (PSI) overreduction, reactive oxygen species (ROS) production, and cell death. Decreases in photosystem II (PSII) activity introduced by crossing pgr5 with PSII deficient mutants
rescued the lethality of pgr5 in FL. PGR5 was suggested to act as part of the ferredoxin-plastoquinone reductase (FQR), involved in cyclic electron transfer around PSI. However, the proposed molecular role of PGR5 remains highly debated. To learn more about PGR5 function, we performed a forward genetic screen in Arabidopsis thaliana to identify EMS-induced suppressor mutants surviving longer when grown in FL compared to pgr5 mutants (referred to as ”suppressor of pgr5 lethality in fluctuating light”, splf ). 11 different candidate genes were identified in a total of 22 splf plants.
Mutants of seven of these genes in the pgr5 background showed low Fv/Fm values when grown in non-fluctuating low light (LL). Five of these 4genes were previously reported to have a role in PSII biogenesis or function. Two others, RPH1 and a DEAD/DEAH box helicase (AT3G02060), have not been linked to PSII function before. Three of splf candidate genes link to primary metabolism, fructose-2,6-bisphosphatase (F2KP ), udp-glucose pyrophosphorylase 1 (UGP1 ) and ferredoxin-dependent glutamate synthase (Fd-GOGAT ). They are characterized by the fact that they survive longer in FL than pgr5 mutants but do not procede beyond the early vegetative
phase and then die.
Plant metabolism serves as the primary mechanism for converting assimilated carbon into essential compounds crucial for plant growth and ultimately, crop yield. This renders it a focal point of research with significant implications. Despite notable strides in comprehending the genetic principles underpinning metabolism and yield, there remains a dearth of knowledge regarding the genetic factors responsible for trait variation under varying environmental conditions. Given the burgeoning global population and the advancing challenges posed by climate change, unraveling the intricacies of metabolic and yield responses to water scarcity became increasingly important in safeguarding food security.
Our research group has recently started to work on the genetic resources of legume species. To this end, the study presented here investigates the metabolic diversity across five different legume species at a tissue level, identifying species-specific biosynthesis of alkaloids as well as iso-/flavonoids with diverse functional groups, namely prenylation, phenylacylation as well as methoxylation, to create a resource for follow up studies investigation the metabolic diversity in natural diverse populations of legume species.
Following this, the second study investigates the genetic architecture of drought-induced changes in a global common bean population. Here, a plethora of quantitative trait loci (QTL) associated with various traits are identified by performing genome-wide association studies (GWAS), including for lipid signaling. On this site, overexpression of candidates highlighted the induction of several oxylipins reported to be pivotal in coping with harsh environmental conditions such as water scarcity.
Diverging from the common bean and GWAS, the following study focuses on identifying drought-related QTL in tomato using a bi-parental breeding population. This descriptive study highlights novel multi-omic QTL, including metabolism, photosynthesis as well as fruit setting, some of which are uniquely assigned under drought. Compared to conventional approaches using the bi-parental IL population, the study presented improves the resolution by assessing further backcrossed ILs, named sub-ILs.
In the final study, a photosynthetic gene, namely a PetM subunit of the cytochrome b6f complex encoding gene, involved in electron flow is characterized in an horticultural important crop. While several advances have been made in model organisms, this study highlights the transition of this fundamental knowledge to horticultural important crops, such as tomato, and investigates its function under differing light conditions. Overall, the presented thesis combines different strategies in unveiling the genetic components in multi-omic traits under drought using conventional breeding populations as well as a diverse global population. To this end, it allows a comparison of either approach and highlights their strengths and weaknesses.
Nowadays, innovative and entrepreneurial activities and their actors are embedded in interdependent systems to drive joint value creation. Innovation ecosystems and entrepreneurial ecosystems have become established system-level concepts in management research to explain how value transpires between different actors and institutions in distinct contexts. Despite the popularity of the concepts, researchers have critiqued their theoretical depth, conceptual distinctiveness, as well as operationalization and measurement (Autio & Thomas, 2022; Klimas & Czakon, 2022). Furthermore, in light of current-day challenges, research has yet to address how context impacts innovation and entrepreneurial ecosystems and their actors and elements (Wurth et al., 2022).
The aim of this cumulative thesis is to provide a deeper understanding of the conceptualization, operationalization, and measurement of innovation and entrepreneurial ecosystems and investigate how contextual factors can influence the overall ecosystem and its key actors. To this end, bibliometric and empirical-qualitative methods, as well as narrative and systematic literature reviews, are employed. After introducing the research scope and key concepts in Chapter 1, a systematic literature review to operationalize and measure the concept of innovation ecosystems is conducted, and an integrative framework of its composition is introduced in Chapter 2. In Chapter 3, the innovation journal network is outlined by means of science mapping to determine current and emerging research areas characterizing innovation studies. In Chapters 4 and 5, the interplay between the temporal context of the Covid-19 pandemic and the spatial context of entrepreneurial ecosystems is assessed by focusing on the role of organizational resilience and affordances. The findings shed new light on the dynamics and boundaries of entrepreneurial ecosystems as they move between the spatial and digital realm. Building on this, an integrative framework of digital entrepreneurial ecosystems is presented in Chapter 6. The concluding Chapter 7 summarizes my thesis’s conceptual, theoretical, and empirical insights, highlighting implications, limitations, and promising future research avenues.
The findings of this cumulative thesis contribute to the theoretical and conceptual advancement of ecosystems in innovation and entrepreneurship by providing insights into the measurement and operationalization of its elements. Furthermore, the results show that contextual factors, such as crisis events or institutional circumstances, influence innovation and entrepreneurial ecosystems and their actors, calling for a more nuanced consideration of ecosystem configurations and dynamics. By drawing from the theory of affordances, the elements that actually afford value to the actors and how they shift between the physical and digital realm are portrayed. Based on these findings, this thesis introduces novel frameworks and conceptual advancements of the configurations and boundaries of innovation and (digital) entrepreneurial ecosystems, laying the foundation for a renewed understanding of how to design, orchestrate, and evaluate ecosystems today and in the future.
Seasonal forecasts are of great interest in many areas. Knowing the amount of precipitation for the upcoming season in regions of water scarcity would facilitate a better water management. If farmers knew the weather conditions of the upcoming summer at sowing time, they could select those cereal species that are best adapted to these conditions. This would allow farmers to improve the harvest and potentially even reduce the amount of pesticides used. However, the undoubted advantages of seasonal forecasts are often opposed by their high degree of uncertainty. The great challenge of generating seasonal forecasts with lead times of several months mainly originates from the chaotic nature of the earth system. In a chaotic system, even tiny differences in the initial conditions can lead to strong deviations in the system’s state in the long run.
In this dissertation we propose an emergent machine learning approach for seasonal forecasting, called the AnlgModel. The AnlgModel combines the analogue method with myopic feature selection and bootstrapping. To benchmark the abilities of the AnlgModel we apply it to seasonal cyclone activity forecasts in the North Atlantic and Northwest Pacific. The AnlgModel demonstrates competitive hindcast skills with two operational forecasts and even outperforms these for long lead times.
In the second chapter we comprehend the forecasting strategy of the Anlg-Model. We thereby analyse the analogue selection process for the 2017 North Atlantic and the 2018 Northwest Pacific seasonal cyclone activity. The analysis shows that those climate indices which are known to influence the seasonal cyclone activity, such as the Niño 3.4 SST, are correctly represented among the selected analogues. Furthermore the selected analogues reflect large-scale climate patterns that were identified by expert reports as being determinative for these particular seasons.
In the third chapter we analyse the features that are used by the AnlgModel for its predictions. We therefore inspect the feature relevance (FR). The FR patterns learned by the AnlgModel show a high congruence with the predictor regions used by the operational forecasts. However, the AnlgModel also discovered new features, such as the SST anomaly in the Gulf of Guinea during November. This SST pattern exhibits a remarkably high predictive potential for the upcoming Atlantic hurricane activity.
In the final chapter we investigate potential mechanisms, that link two of these regions with high feature relevance to the Atlantic hurricane activity. We mainly focus on ocean surface transport. The ocean surface flow paths are calculated using Lagrangian particle analysis. We demonstrate that the FR patterns in the region of the Canary islands do not correspond with ocean surface transport. It is instead likely that these FR patterns fingerprint a wind transport of latent heat. The second region to be studied is situated in the Gulf of Guinea. Our analysis shows that the FR patterns seen there do fingerprint ocean surface transport. However, our simulations also show that at least one other mechanism is involved in linking the Gulf of Guinea SST anomaly in November to the hurricane activity of the upcoming season.
In this work the AnlgModel does not only demonstrate its outstanding forecast skills but also shows its capabilities as research tool for detecting oceanic and atmospheric mechanisms.
The development of seeds in angiosperms starts with a complex process of double fertilization, involving the fusion of the maternal egg cell and central cell with two paternal sperm cells. This gives rise to the embryo and the nourishing endosperm, which are then enclosed by the seed coat, derived from the maternal integuments. The growth of the seed coat in Arabidopsis thaliana (Arabidopsis) is actively inhibited before fertilization by epigenetic regulators known as Polycomb Group (PcG) proteins. These proteins deposit a repressive histone mark called H3K27me3, which must be removed to enable seed coat formation. In this thesis, I explored the mechanism of removal of H3K27me3 marks from the integument cells following fertilization, which allows for seed coat formation. We hypothesized that this removal should be primarily facilitated by histone demethylases from the JMJ family and potentially influenced by the plant hormones Brassinosteroids (BRs). This hypothesis was supported by the expression patterns of the JMJ protein REF6 and of BR related genes, which are specifically expressed in the integuments and in the seed coat. Moreover, mutations in both these pathways lead to developmental defects, such as reduced ovule viability and delayed seed coat growth. Our research provides evidence suggesting that BR signalling is likely involved in recruiting JMJ-type histone demethylases to target loci responsible for seed coat growth. Moreover, we have discovered an additional pathway through which BRs regulate seed coat development, independent of their influence on H3K27me3 marks. This finding emphasizes the diverse roles of BRs in coordinating seed development, extending beyond their well-known involvement in plant growth and development. Furthermore, I explored the role of another epigenetic mark, DNA methylation, in fertilization-independent (or autonomous) seed formation in Arabidopsis. For this, we utilized epigenetic Recombinant Inbred Lines (epiRILs) and thus identified an epigenetic Quantitative Trait Locus (epiQTL) on chromosome II, potentially responsible for the larger autonomous seed size observed in DNA methylation mutants. Overall, this thesis significantly enhances our comprehension of the intricate relationship between epigenetic modifications, hormonal signaling, and plant reproductive processes. It offers valuable insights into the genetic mechanisms governing both sexual and asexual seed formation, while also presenting potential avenues for the engineer of advantageous traits in agricultural crops.