Using natural variation to unravel the dynamic regulation of plant performance in diverse environments

Summary All plants are able to respond to changes in their environment by adjusting their morphology and metabolism, but large differences are observed in the effectiveness of these responses in the light of plant fitness. Between and within species large differences are observed in plant responses to drought, heat and other abiotic stresses. This natural variation is partly due to variation in the genetic composition of individuals. Within-species variation can be used to identify and study genes involved in the genetic regulation of plant performance. Growth of the world population will, in the coming years, lead to an increased demand for food, feed and other natural products. In addition, extreme weather conditions with, amongst others, more and prolonged periods of drought and heat are expected to occur due to climate change. Therefore breeders are challenged to produce stress tolerant cultivars with improved yield under sub-optimal conditions. Knowledge about the mechanisms and genes that underlie tolerance to drought, heat and other abiotic stresses will ease this challenge. The aim of this thesis was to identify and study the role of genes that are underlying natural variation in plant performance under drought, salt and heat stress. To reach this goal a genome wide association (GWA) mapping approach was taken in the model species Arabidopsis thaliana. A population of 350 natural accessions of Arabidopsis, genotyped with 215k SNPs, was grown under control and several stress conditions and plant performance was evaluated by phenotyping one or several plant traits per environment. Genes located in the genomic regions that were significantly associated with plant performance, were studied in more detail. Plant performance was first evaluated upon osmotic stress (Chapter 2). This treatment resulted not only in a reduced plant size, but also caused the colour of the rosette leaves to change from green to purple-red due to anthocyanin accumulation. The latter was visually quantified and subsequent GWA mapping revealed that a large part of the variation in anthocyanin accumulation could be explained by a small genomic region on chromosome 1. The analysis of re-sequence data allowed us to associate the second most frequent allele of MYB90 with higher anthocyanin accumulation and to identify the causal SNP. Interestingly MYB75, a close relative of MYB90, was not identified by GWA mapping, although causal sequence variation of this gene for anthocyanin accumulation was identified in the Cvi x Ler and Ler x Eri-1 RIL populations. Re-sequence data revealed that one allele of MYB75 was dominating the population and that the MYB75 alleles of Cvi and Ler were both rare, explaining the lack of association at this locus in GWA mapping. For MYB90, two alleles were present in a substantial part of the population, suggesting balancing selection between them. Next, the natural population was exposed to short-term heat stress during flowering (Chapter 3). This short-term stress has a large impact on seed set, while it hardly affects the vegetative tissues. Natural variation for tolerance against the effect of heat on seed set was evaluated by measuring the length of all siliques along the inflorescence in both heat-treated and control plants. Because the flower that opened during the treatment was tagged, we could analyse the heat response for several developmental stages separately. GWA mapping revealed that the heat response before and after anthesis involved different genes. For the heat response before anthesis strong evidence was gained that FLC, a flowering time regulator and QUL2, a gene suggested to play a role in vascular tissue development, were causal for two strong associations. Furthermore, the impact of moderate drought on plant performance was evaluated in the plant phenotyping platform PHENOPSIS. Homogeneous drought was assured by tight regulation of climate cell conditions and the robotic weighing and watering of the pots twice a day. Because plant growth is a dynamic trait it was monitored over time by top-view imaging under both moderate drought and control conditions (Chapter 4 and 5). To characterise growth it was modelled with an exponential function. GWA mapping of temporal growth data resulted in the detection of time-dependent QTLs whereas mapping of model parameters resulted in another set of QTLs related to the entire growth period. Most of these QTLs would not have been identified if plant size had only been determined on a single day. For the QTLs detected under control conditions eight candidate genes with a growth-related mutant or overexpression phenotype were identified (Chapter 4). Genes in the support window of the drought-QTLs were prioritized based on previously reported gene expression data (Chapter 5). Additional validation experiments are needed to confirm causality of the candidate genes. Next, to search for genes that determine plant size across many environments, biomass accumulation in the natural population was determined in 25 different environments (Chapter 6). Joint analysis of these data by multi-environment GWA mapping resulted in the detection of 106 strongly associated SNPs with significant effects in 7 to 16 environments. Several genes involved in starch metabolism, leaf size control and flowering time determination were located in close proximity of the associated SNPs. Two genes, RPM1 and ACD6, were located in close proximity of SNPs with significant GxE effects. For both genes, alleles have been identified that increase resistance to bacterial infection, but that reduce biomass accumulation. The sign of the allelic effect is therefore dependent on the environmental conditions. Whole genome predictions revealed that most of the GxE interactions observed at the phenotypic level were not the consequence of strong associations with strong QxE effects, but of moderate and weak associations with weak QxE effects. Finally, in Chapter 7 I discuss the usefulness of GWA mapping in the identification of genes underlying natural variation in plant performance under drought, heat stress and a number of other environments. Strong associations were observed for both environment-specific as well as common plant performance regulators. Some choices in phenotyping and experimental design were crucial for our success, like evaluation of plant performance over time and simplification of the quantification of the phenotype. It is suggested that follow-up work should focus on the functional characterization of the causal genes, because such analyses would be helpful to identify pathways in which the causal genes are involved and to understand why sequence variation results in changes at the phenotype level. Although translation of the findings to applications in crops is challenging, this thesis contributes to the understanding of the genetic regulation of stress response and therefore will likely contribute to the development of stress tolerant and stable yielding crops.