Abstract
BackgroundHyperaccumulation of trace elements is a rare trait among plants which is being investigated to advance our understanding of the regulation of metal accumulation and applications in phytotechnologies. Noccaea caerulescens (Brassicaceae) is an intensively studied hyperaccumulator model plant capable of attaining extremely high tissue concentrations of zinc and nickel with substantial genetic variation at the population-level. Micro-X-ray Fluorescence spectroscopy (µXRF) mapping is a sensitive high-resolution technique to obtain information of the spatial distribution of the plant metallome in hydrated samples. We used laboratory-based µXRF to characterize a collection of 86 genetically diverse Noccaea caerulescens accessions from across Europe. We developed an image-processing method to segment different plant substructures in the µXRF images. We introduced the concentration quotient (CQ) to quantify spatial patterns of metal accumulation and linked that to genetic variation.ResultsImage processing resulted in automated segmentation of µXRF plant images into petiole, leaf margin, leaf interveinal and leaf vasculature substructures. The harmonic means of recall and precision (F1 score) were 0.79, 0.80, 0.67, and 0.68, respectively. Spatial metal accumulation as determined by CQ is highly heritable in Noccaea caerulescens for all substructures, with broad-sense heritability (H2) ranging from 76 to 92%, and correlates only weakly with other heritable traits. Insertion of noise into the image segmentation algorithm barely decreases heritability scores of CQ for the segmented substructures, illustrating the robustness of the trait and the quantification method. Very low heritability was found for CQ if randomly generated substructures were compared, validating the approach.ConclusionsA strategy for segmenting µXRF images of Noccaea caerulescens is proposed and the concentration quotient is developed to provide a quantitative measure of metal accumulation pattern, which can be used to determine genetic variation for such pattern. The metric is robust to segmentation error and provides reliable H2 estimates. This strategy provides an avenue for quantifying XRF data for analysis of the genetics of metal distribution patterns in plants and the subsequent discovery of new genes that regulate metal homeostasis and sequestration in plants.
Highlights
Hyperaccumulation of trace elements is a rare trait among plants which is being investigated to advance our understanding of the regulation of metal accumulation and applications in phytotechnologies
We propose an image-processing method to segment the Micro-X-ray fluorescence microscopy (μXRF) images of N. caerulescens into four different substructures
The three plants per accession are highly comparable in plant size and appearance, between accessions there is considerable variation, reflecting the genetic variation that is expected for a diversity panel of accessions originating from the north-west of Spain to the south of Finland
Summary
Hyperaccumulation of trace elements is a rare trait among plants which is being investigated to advance our understanding of the regulation of metal accumulation and applications in phytotechnologies. There are, some plant species that are extremely tolerant to metal exposure and that hyperaccumulate certain trace elements to very high concentrations in their leaves. By understanding the plant physiology and the underlying genetics of metal accumulation, cultivars can be bred that contain higher contents of these micronutrients in their edible parts, which will benefit their nutritional value. Such biofortified cultivars can help fight mineral malnutrition, one of the major causes of human mortality worldwide [7]. To unlock these applications of metal accumulation, an improved understanding of the underlying genetics is required. The method cannot handle very small plants, which are completely mis-classified as “petiole”, but this only applied to three plants in the experiment
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