Analysis of the leaf metabolome in Arabidopsis thaliana mutation accumulation lines reveals association of metabolic disruption and fitness consequence

• Published in: Evolutionary ecology 2022-10, Vol.36 (5), p.845-857
• Main Authors: Kreutzmann, Sydney, Pompa, Elizabeth, Nguyen, Nhan D., Tilahun, Liya, Rutter, Matthew T., Weng, Mao-Lun, Fenster, Charles B., Olson-Manning, Carrie F.
• Format: Article
• Language: English
• Subjects: Accumulation; Animal Ecology; Annotations; Arabidopsis thaliana; Biomedical and Life Sciences; Developmental biology; Ecology; Evolutionary Biology; Fitness; Genetic aspects; Genetic diversity; leaves; Life Sciences; Metabolic pathways; Metabolism; Metabolites; metabolome; Mutation; mutation accumulation; Original Paper; phenotypic variation; Phenotypic variations; Plant Sciences; Reproductive fitness
• ISSN: 0269-7653; 1573-8477; 1573-8477
• DOI: 10.1007/s10682-022-10210-8

Understanding the mechanisms by which mutations affect fitness and the distribution of mutational effects are central goals in evolutionary biology. Mutation accumulation (MA) lines have long been an important tool for understanding the effect of new mutations on fitness, phenotypic variation, and mutational parameters. However, there is a clear gap in predicting the effect of specific new mutations to their effects on fitness. In an attempt to directly connect the effect of spontaneous mutations to their fitness effects, we quantified the metabolic expression of 386 known compounds in primary and secondary metabolism in Arabidopsis thaliana MA lines that had consistently higher and lower relative fitness than the progenitor. The high and low fitness lines do not have a difference in the average number of mutations and share the same types of metabolic pathways disrupted. However, compared to the progenitor, low fitness lines have significantly more metabolic subpathways disrupted than lines with higher fitness. These results suggest that the effect of a new mutation on fitness depends less on the specific metabolic pathways disrupted and potentially more on the number of disrupted pathways. We fail to identify any direct connection of mutations in or near well annotated genes to their effect on well-characterized biochemical pathways, possibly due to incomplete annotations of molecular function or to non-genetic variation controlling metabolic expression. Our findings indicate that organisms can explore a considerable amount of physiological space with only a few mutations.