Abstract
The burgeoning field of remote sensing has opened new avenues for monitoring plant biodiversity and assessing plant responses to environmental stressors. This dissertation presents an integrative analysis of genetic variation and leaf spectral properties in plants, with a focus on two plant systems: wild coyote tobacco (Nicotiana attenuata), a well-studied ecological model plant, and European beech (Fagus sylvatica L.), one of the most common tree species in Europe. Utilizing a combination of high-throughput phenotyping, genome-wide association studies (GWAS), and spectroscopy, this research aims to investigate the genetic basis of leaf spectral properties and drought response in plants, providing novel insights with implications for biodiversity monitoring and understanding plant adaptation strategies. The first part of the dissertation employs a set of 360 inbred genotypes of N. attenuata, encompassing wild accessions, recombinant inbred lines (RILs), and transgenic lines with targeted gene expression changes. The study reveals substantial genetic and non-genetic influences on leaf spectral variation, highlighting the importance of environmental and experimental considerations in interpreting genetic associations. The visible spectral region is identified as the most variable, distinguishing both experimental settings and groups of genotypes. This research underscores the potential of field spectroscopy in assessing genetic variation in plant populations, setting a foundation for future functional validation and applications in biodiversity monitoring. The second part of the dissertation seeks to conduct a genetic association study on N. attenuata, employing a well-resolved genetic mapping population and a novel Hierarchical Spectral Clustering with Parallel Analysis (HSC-PA) method. This approach efficiently captures variation in high-dimensional spectral data, leading to the discovery of a novel association between a locus on chromosome 1 and the blue light absorption region of chlorophyll, indicative of genetic variation in photosynthetic efficiency. The study demonstrates the superiority of the HSC-PA method over traditional spectral indices and single wavelength approaches, representing a step towards a better understanding of the genetic determinants of leaf spectral variation. The third part of the dissertation focuses on European beech trees, utilizing a natural casecontrol design to investigate the genetic and phenotypic factors contributing to drought resilience. The study employs Pool-GWAS, phenotypic feature profiling, and leaf spectral analyses, revealing calcium as a key factor associated with tree health post-drought and spectral variation between healthy and stressed trees. Despite challenges posed by genetic variability and pool design, the research identifies 34 candidate genes potentially linked to drought resilience, highlighting regional variation in genetic associations with tree health. In summary, this dissertation provides an integrative analysis of the genetic basis of leaf spectral properties and drought response in plants, employing innovative methodologies and a multi-scale approach. The research advances our understanding of plant adaptation mechanisms, offers valuable insights for biodiversity conservation and ecosystem management practices, and sets the stage for future studies aimed at combining spectroscopy and genetics to elucidate the complex interactions between plants and their environment.
Li, Cheng