Biology subjects

Theeuwen, T. P. J. M.

Publications and source records attributed to Theeuwen, T. P. J. M..

8 recordsLinked to original sources

bioRxiv2026

Linking dynamic photosynthetic traits to biomass: a functional data framework that pinpoints when photosynthesis limits growth

Photosynthesis responds rapidly to environmental changes, such as light fluctuations, and these responses affect how much carbon plants gain over time. Modelling genetic variation in photosynthesis over time opens a route for selection on photosynthetic performance. High-throughput chlorophyll fluorescence has enabled measurements of photosynthetic processes at high time resolution, yet methods to model the temporal and genetic variation in these time-series data remain scarce. Here, we combined splines and functional principal component analysis (FPCA) to model genotype-specific trajectories of fluorescence traits and capture their main variation in a few components. We applied this approach to 412 Arabidopsis thaliana MAGIC lines under daily sinusoidal and fluctuating light. The first component captured differences in overall trait level, whereas subsequent components captured differences in how trait values changed across days, mainly in the early growing period. These component scores predicted final dry weight reasonably well (average r = 0.7224 under sinusoidal and 0.82 under fluctuating light). Information on changes across days added most predictive value when measurements were limited to a few days. Time-varying coefficients revealed that the associations between fluorescence traits and dry weight changed over time. For most traits, these associations were strongest early in the growing period. Our framework thus shows not only which photosynthetic processes are associated with biomass, but also when. This insight will point to the period in which photosynthesis limits growth and to the traits beneficial to select for.

genetics↗

bioRxiv2026

From Field Photosynthesis to Genetic Architecture: Insights from the First Dedicated Photosynthesis Hackathon

Photosynthesis is among the most consequential yet genetically complex traits in crop plants, and translating its natural variation into actionable genomic targets remains a central challenge for breeding climate-resilient varieties. To start addressing this, researchers are generating increasingly large, multi-environment field photosynthesis datasets. Yet, these data have been structurally under-analysed since their inception. Here we report the outcomes of the first dedicated hackathon focused on computational mining of such field data held in Accra, Ghana, in March 2026. Bringing together data scientists, plant physiologists, geneticists, and breeders from Europe and Africa, these interdisciplinary teams used photosynthetic data collected with hand-held fluorometers to genome-wide marker data across four crop species: cowpea (Vigna unguiculata), barley (Hordeum vulgare), common bean (Phaseolus vulgaris), and potato (Solanum tuberosum). Despite using different species and methods, independent teams identified the same three key findings. First, mechanism-informed feature engineering and dynamic modelling recover genetic signals that are not detected or discarded in standard analysis pipelines, resulting in traits with improved heritability and meaningful associations with yield. Secondly, machine learning methods proved effective at uncovering genetic associations, with temporally resolved features substantially outperforming single time-point measurements. Third, raw chlorophyll fluorescence and absorbance traces consistently contained more information and predictive power than the extracted parameters currently used. A defining feature of this event was having experimentalists and data scientists working together, enabling AI approaches to be grounded in domain knowledge and biological mechanisms rather than relying on data alone.

plant biology↗

bioRxiv2026

Multi-environment GWAS analysis for photosynthetic light use efficiency in Arabidopsis thaliana

Photosynthesis is acknowledged as a potential target to increase crop yield. Improved photosynthesis may be achieved by conventional breeding, exploiting the available natural genetic variation for photosynthesis traits. This approach is challenging for crops due to limitations in high-throughput photosynthesis phenotyping, the highly polygenic nature of photosynthesis, and its strongly dynamic response to environmental changes. Recent advancements in phenomics make accurate and detailed photosynthesis phenotyping more feasible, with the model species Arabidopsis thaliana paving the way for applications in crops. In this study, we examined photosynthesis parameters over time in the global Arabidopsis HapMap diversity panel exposed to three conditions: optimal nutrient supply, low phosphorus supply and low nitrogen supply. Combined with two previous studies on photosynthesis in response to low temperature, and to a one-step change in irradiance from low light to high light, five high-quality datasets were systematically analysed using the same approach (with one million-maker set, uni- and multi-variate analyses). Our findings emphasize the genetic complexity of photosynthesis, detecting hundreds of significant quantitative trait loci, only a small number of which are robust, and of which most are condition specific. Robust loci, found in multiple conditions, exemplify those suited for conferring higher all-round photosynthesis, and targets for marker-assisted selection, contributing to environmental resilience, while the multitude of small-effect conditional loci suggest that genomic selection approaches may be more suited to improve crop photosynthesis.

genetics↗

bioRxiv2024

Species wide inventory of Arabidopsis thaliana organellar variation reveals ample phenotypic variation for photosynthetic performance

Efforts to improve photosynthetic performance are increasingly employing natural genetic variation. However, genetic variation in the organellar genomes (plasmotypes) is often disregarded due to the difficulty of studying the plasmotypes and the lack of evidence that this is a worthwhile investment. Here, we systematically phenotyped plasmotype diversity using Arabidopsis thaliana as a model species. A reanalysis of whole genome resequencing data of 1,531 representative accessions shows that the genetic diversity amongst the mitochondrial genomes is eight times lower than amongst the chloroplast genomes. Plasmotype diversity of the accessions divides the species into two major phylogenetic clusters, within which highly divergent subclusters are distinguished. We combined plasmotypes from 60 A. thaliana accessions with the nuclear genomes (nucleotypes) of four A. thaliana accessions to create a panel of 232 novel cytonuclear genotypes (cybrids). The cybrid plants were grown in a range of different light and temperature conditions and phenotyped using high-throughput phenotyping platforms. Analysis of the phenotypes showed that several plasmotypes alone or in interaction with the nucleotypes have significant effects on photosynthesis, and that the effects are highly dependent on the environment. Moreover, we introduce Plasmotype Association Studies (PAS) as a novel method to reveal plasmotypic effects. Within A. thaliana, several organellar variants can influence photosynthetic phenotypes, which emphasizes the valuable role this variation has on improving photosynthetic performance. The increasing feasibility of producing cybrids in various species calls for further research into how these phenotypes may support breeding goals in crop species. Significance statementPhotosynthesis is one of the few crop traits that has been largely unaddressed which can contribute to increasing crop yield potential. Exploiting genetic variation within organellar genomes presents a promising, yet untapped resource to improve photosynthesis. However, the extent of organellar variation and its impact on photosynthesis within a species remains largely unknown. Using Arabidopsis thaliana as a model species, we revealed highly divergent clusters of organellar variation. We constructed 232 novel combinations of species representative organellar and nuclear genomes, referred to as cybrids. High-throughput phenotyping of these cybrids revealed that organellar variants can substantially impact photosynthesis in different environments. These findings indicate that organellar genomes may be a valuable resource for improving photosynthesis in crops.

plant biology↗

bioRxiv2023

Local adaptation of Arabidopsis thaliana in a small geographic region with mild environmental clines

Natural populations of Arabidopsis thaliana provide powerful systems to study adaptation of wild plant species. Previous research has predominantly focused on global populations or accessions collected from regions with diverse climates. However, little is known about the genetics underlying adaptation in regions with mild environmental clines. We have examined a diversity panel consisting of 192 A. thaliana accessions collected from the Netherlands, a region with limited climatic variation. Despite the relatively uniform climate, we identified compelling evidence of local adaptation within this population. Notably, semidwarf accessions, due to mutation of the GIBBERELLIC ACID REQUIRING 5 (GA5) gene, occur at a relatively high frequency near the coast and these displayed enhanced tolerance to high wind velocities. Additionally, we evaluated the performance of the population under iron deficiency conditions and found that allelic variation in the FE SUPEROXIDE DISMUTASE 3 (FSD3) gene affects tolerance to low iron levels. Moreover, we explored patterns of local adaptation to environmental clines in temperature and precipitation, observing that allelic variation at LA RELATED PROTEIN 1C (LARP1c) likely affects drought tolerance. Not only is the genetic variation observed in a diversity panel of A. thaliana collected in a region with mild environmental clines comparable to that in collections sampled over larger geographic ranges, it is also sufficiently rich to elucidate the genetic and environmental factors underlying natural plant adaptation.

plant biology↗

bioRxiv2022

The NDH complex reveals a trade-off that constrains maximising photosynthesis in Arabidopsis thaliana

The Green Revolution has resulted in major improvements in crop productivity, but left photosynthesis largely unimproved. Despite ample variation of photosynthetic performance in crops and their wild relatives, the photosynthetic capacity of elite breeding lines remains well below its theoretical maximum. As yield is often the primary selective trait, current plant breeding approaches result in photosynthetic trade-offs that prevent positive selection for photosynthetic performance itself. Currently, genetic variation for photosynthetic performance is seldomly validated at the genetic level, and as a result these photosynthetic trade-offs remain poorly understood. Here we reveal the physiological nature of a photosynthetic trade-off caused by the NAD(P)H dehydrogenase (NDH) complex. The use of an Arabidopsis thaliana cybrid panel revealed how a natural allele of the chloroplastic gene NAD(P)H-QUINONE OXIDOREDUCTASE SUBUNIT 6 - a subunit of the NDH complex - results in a faster recovery of photosystem II efficiency after a transition from high to low irradiances. This improvement is due to a reduction in NDH activity. Under low-light conditions this reduction in NDH activity has a neutral effect on biomass, while under highly fluctuating light conditions, including high irradiances, more NDH activity is favoured. This shows that while allelic variation in one gene can have beneficial effects on one aspect of photosynthesis, it can, depending on environmental conditions, have negative effects on other aspects of photosynthesis. As environmental conditions are hardly ever stable in agricultural systems, understanding photosynthetic trade-offs allows us to explore shifting photosynthetic performance closer to the theoretical maximum.

plant biology↗

bioRxiv2022

Plethora of QTLs found in Arabidopsis thaliana reveals complexity of genetic variation for photosynthesis in dynamic light conditions

The environments in which plant species evolved are now generally understood to be dynamic rather than static. Photosynthesis has to operate within these dynamic environments, such as sudden changes to light intensities. Plants have evolved photoprotection mechanisms that prevent damage caused by sudden changes to high light intensities. The extent of genetic variation within plants species to deal with these dynamic light conditions remains largely unexplored. Here we show that one accession of A. thaliana has a more efficient photoprotection mechanism in dynamic light conditions, compared to six other accessions. The construction of a doubled haploid population and subsequent phenotyping in a dynamically controlled high-throughput system reveals up to 15 QTLs for photoprotection. Identifying the causal gene underlying one of the major QTLs shows that an allelic variant of cpFtsY results in more efficient photoprotection under high and fluctuating light intensities. Further analyses reveal this allelic variant to be overprotecting, reducing biomass in a range of dynamic environmental conditions. This suggests that within nature, adaptation can occur to more stressful environments and that revealing the causal genes and mechanisms can help improve the general understanding of photosynthetic functioning. The other QTLs possess different photosynthetic properties, and thus together they show how there is ample intraspecific genetic variation for photosynthetic functioning in dynamic environments. With photosynthesis being one of the last unimproved components of crop yield, this amount of genetic variation for photosynthesis forms excellent input for breeding approaches. In these breeding approaches, the interactions with the environmental conditions should however be precisely assessed. Doing so correctly, allows us to tap into natures solution to challenging environmental conditions.

plant biology↗

bioRxiv2018

Reciprocal cybrids reveal how organellar genomes affect plant phenotypes

Assessing the impact of variation in chloroplast and mitochondrial DNA (collectively termed the plasmotype) on plant phenotypes is challenging due to the difficulty in separating their effect from nuclear derived variation (the nucleotype). Haploid inducer lines can be used as efficient plasmotype donors to generate new plasmotype-nucleotype combinations (cybrids)(Ravi et al., 2014). We generated a panel comprising all possible cybrids of seven Arabidopsis thaliana accessions and extensively phenotyped these lines for 1859 phenotypes under stable and fluctuating conditions. We show that natural variation in the plasmotype results in additive as well as epistatic effects across all phenotypic categories. Plasmotypes which induce more additive phenotypic changes also cause more significant epistatic effects, suggesting a possible common basis for both additive and epistatic effects. On average epistatic interactions explained twice as much of the variance in phenotypes as additive plasmotype effects. The impact of plasmotypic variation was also more pronounced under fluctuating and stressful environmental conditions. Thus, the phenotypic impact of variation in plasmotypes is the outcome of multilevel Nucleotype X Plasmotype X Environment interactions and, as such, the plasmotype is likely to serve as a reservoir of variation which is only exposed under certain conditions. The production of cybrids using haploid inducers is a quick and precise method for assessing the phenotypic effects of natural variation in organellar genomes. It will facilitate efficient screening of unique nucleotype-plasmotype combinations to both improve our understanding of natural variation in nucleotype plasmotype interactions and identify favourable combinations to improve plant performance.

genetics↗