A Comprehensive Approach to Assess Arabidopsis Survival Phenotype in Water-Limited Condition Using a Non-invasive High-Throughput Phenomics Platform

Abstract

With the rapid rise in global population and the challenges caused by climate changes, the maximization of plant productivity and the development of sustainable agriculture strategies are vital for food security. One of the resources more affected in this new environment will be the limitation of water. In this study, we describe the use of non-invasive technologies exploiting sensors for visible, fluorescent, and near-infrared lights to accurately screen survival phenotypes in Arabidopsis thaliana exposed to water-limited conditions. We implemented two drought protocols and a robust analysis methodology that enabled us to clearly assess the wilting or dryness status of the plants at different time points using a phenomics platform. In conclusion, our approach has shown to be very accurate and suitable for experiments where hundred of samples have to be screened making a manual evaluation unthinkable. This approach can be used not only in functional genomics studies but also in agricultural applications.

Abiotic Stress Phenotypes Are Associated with Conserved Genes Derived from Transposable Elements

“…We also developed a custom phenotypic data analysis pipeline using the acquired images as input for each assay (Figure 1 ) (see section Materials and Methods). The use of a phenomics platform increased the reproducibility of the measurements, such that different measurements like leaf size, color, and root length, were more comparable (Fahlgren et al, 2015 ; Vello et al, 2015 ; Flood et al, 2016 ) The pipeline of a phenomics analysis requires three steps, namely: image analysis, data mining, and statistical analysis (Figure 1A ). Image analysis has two major components: first, segmentation, where the image is partitioned into sets of pixels to select those representing the plant (i.e., the digital plant), and second, the calculation of the morpho-colorimetric features (e.g., projected leaf area), based on the digital plant.…”

“…Data mining techniques do not require human intervention to evaluate the phenotype and are amenable to high-throughput protocols. For the arsenic and salt assays, a cluster of color classification has been shown to be optimal to assess germination and survivability, respectively (Berger et al, 2012 ; Vello et al, 2015 ). In the former case, a seed is represented by a brown color whereas a seedling's predominant color is green.…”

Phenotyping in Arabidopsis and Crops—Are We Addressing the Same Traits? A Case Study in Tomato

“…In these cases, fast stress can be achieved by limiting the size of pots. In Arabidopsis studies, the use of peat pellets allows to achieve faster soil dehydration than in soil-filled pots, with very comparable results [26,40,47]. Surely, this is not always possible in plants, such as tomato.…”

“…In Arabidopsis, LI-COR gas exchange systems were used in several studies to assess leaf gas exchange under drought [117,118]. In tomato, carbon assimilation under drought stress is studied across different scales and levels of environmental control, from chambers with artificially elevated CO 2 [100] to greenhouse and field [25,26]. As carbon assimilation is highly influenced by irradiation and temperature, studies in greenhouses and in the field should be conducted in reproducible weather conditions, ideally during sunny days and virtually at the same time.…”

“…For studies in the field, hand-held devices are the most practical choice. Good care has to be taken when comparing leaf gas exchange values across studies: a study on tomato [26] reports 0.15-0.25 µmol H 2 O m −2 s −1 , with slight differences between control and drought, while a study on Arabidopsis [99] reports a more than four-fold increase during drought stress, but still lower absolute values of stomatal conductance than any tested tomato (0.02-0.09 µmol H 2 O m −2 s −1 ). As drought stress protocols, instrument settings (e.g., photon flux density) and growth systems are inconsistent across studies, the comparison of absolute carbon assimilation rates across studies (and species) is inappropriate.…”