Discovering variation of secondary metabolite diversity and its relationship with disease resistance in Cornus florida L

• Published in: Ecology and evolution 2018-06, Vol.8 (11), p.5619-5636
• Main Authors: Pais, Andrew L., Li, Xu, (Jenny) Xiang, Qiu‐Yun
• Format: Article
• Language: English
• Subjects: adaptation; Biodiversity; Biological evolution; Biomarkers; Chemical composition; Clustering; Cornus florida; Correlation; Disease resistance; ecological genomics; Ecological monitoring; Evolution; Genetic diversity; Genotypes; Glucosides; Glycosides; Hypotheses; Intraspecific relationships; Liquid chromatography; Mass spectrometry; Mass spectroscopy; Metabolites; Metabolomics; Molecular chains; Natural populations; Organic chemistry; Original Research; Plant diseases; Plants (botany); population genetics; Predictive control; secondary metabolism; single nucleotide polymorphisms; Single-nucleotide polymorphism; Subpopulations
• ISSN: 2045-7758; 2045-7758
• DOI: 10.1002/ece3.4090

Understanding intraspecific relationships between genetic and functional diversity is a major goal in the field of evolutionary biology and is important for conserving biodiversity. Linking intraspecific molecular patterns of plants to ecological pressures and trait variation remains difficult due to environment‐driven plasticity. Next‐generation sequencing, untargeted liquid chromatography–mass spectrometry (LC‐MS) profiling, and interdisciplinary approaches integrating population genomics, metabolomics, and community ecology permit novel strategies to tackle this problem. We analyzed six natural populations of the disease‐threatened Cornus florida L. from distinct ecological regions using genotype‐by‐sequencing markers and LC‐MS‐based untargeted metabolite profiling. We tested the hypothesis that higher genetic diversity in C. florida yielded higher chemical diversity and less disease susceptibility (screening hypothesis), and we also determined whether genetically similar subpopulations were similar in chemical composition. Most importantly, we identified metabolites that were associated with candidate loci or were predictive biomarkers of healthy or diseased plants after controlling for environment. Subpopulation clustering patterns based on genetic or chemical distances were largely congruent. While differences in genetic diversity were small among subpopulations, we did observe notable similarities in patterns between subpopulation averages of rarefied‐allelic and chemical richness. More specifically, we found that the most abundant compound of a correlated group of putative terpenoid glycosides and derivatives was correlated with tree health when considering chemodiversity. Random forest biomarker and genomewide association tests suggested that this putative iridoid glucoside and other closely associated chemical features were correlated to SNPs under selection. We analyzed six natural populations of the disease‐threatened Cornus florida L. from distinct ecological regions using genotype‐by‐sequencing markers and LC‐MS‐based untargeted metabolite profiling. We identified metabolites that were associated with candidate loci or were predictive biomarkers of healthy or diseased plants. When considering chemodiversity of a correlated group of putative terpenoid glycosides and derivatives, we found that the most abundant compound of this group was correlated with tree health.