Abstract
Soil is a heterogeneous reservoir of essential elements needed for plant growth and development. Plants have evolved mechanisms to balance their nutritional needs based on availability of nutrients. This has led to genetically based variation in the elemental composition, the 'ionome', of plants, both within and between species. We explore this natural variation using a panel of wild-collected, geographically widespread Arabidopsis thaliana accessions from the 1001 Genomes Project including over 1,135 accessions, and the 19 parental accessions of the Multi-parent Advanced Generation Inter-Cross (MAGIC) panel, all with full-genome sequences available. We present an experimental design pipeline for high-throughput ionomic screenings and analyses with improved normalisation procedures to account for errors and variability in conditions often encountered in large-scale, high-throughput data collection. We report quantification of the complete leaf and seed ionome of the entire collection using this pipeline and a digital tool, IonExplorer, to interact with the dataset. We describe the pattern of natural ionomic variation across the A. thaliana species and identify several accessions with extreme ionomic profiles. It forms a valuable resource for exploratory genetic mapping studies to identify genes underlying natural variation in leaf and seed ionome and genetic adaptation of plants to soil conditions.
Highlights
The ionome represents the sum of all mineral nutrient and trace elements of biological or environmental importance in an organism (Lahner et al, 2003)
We propose an experimental design and a two-step normalisation procedure for high-throughput ionomic studies, which extend previously described normalisation procedures such as restricted maximum likelihood (REML) normalisation (Broadley et al, 2010), by using a samplebased approach to normalise for spatial variation between and within experimental blocks and a control-based approach to evaluate the normalisation
We aimed to provide a unique referential dataset of this large natural population that forms a valuable phenotypic resource to enable large-scale genome-wide association studies (GWAS) to identify the genetic basis of ionomic traits
Summary
The ionome represents the sum of all mineral nutrient and trace elements of biological or environmental importance in an organism (Lahner et al, 2003). Plants, being sessile organisms, have evolved intricate regulatory mechanisms to balance uptake and distribution of mineral nutrients and trace elements in response to physical and chemical variation of the soil. Arabidopsis thaliana is a non-crop, genetic model plant species extensively used in plant biology due to its small genome size and extensive genetic resources. Ionomic studies in this species have led to the identification of genes involved in numerous processes, such as
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