Predicting how cells spread and migrate

Efficient cell migration is central to the normal development of tissues and organs and is involved in a wide range of human diseases, including cancer metastasis, immune responses, and cardiovascular disorders. Mesenchymal migration is modulated by focal-adhesion proteins, which organize into large integrin-rich protein complexes at the basal surface of adherent cells. Whether the extent of clustering of focal-adhesion proteins is actually required for effective migration is unclear. We recently demonstrated that the depletion of major focal-adhesion proteins, as well as modulation of matrix compliance, actin assembly, mitochondrial activity, and DNA recombination, all converged into highly predictable, inter-related, biphasic changes in focal adhesion size and cell migration. Herein, we further discuss the role of focal adhesions in controlling cell spreading and test their potential role in cell migration.     

Phenoscope: an automated large‐scale phenotyping platform offering high spatial homogeneity

Increased phenotyping accuracy and throughput are necessary to improve our understanding of quantitative variation and to be able to deconstruct complex traits such as those involved in growth responses to the environment. Still, only a few facilities are known to handle individual plants of small stature for non‐destructive, real‐time phenotype acquisition from plants grown in precisely adjusted and variable experimental conditions. Here, we describe Phenoscope, a high‐throughput phenotyping platform that has the unique feature of continuously rotating 735 individual pots over a table. It automatically adjusts watering and is equipped with a zenithal imaging system to monitor rosette size and expansion rate during the vegetative stage, with automatic image analysis allowing manual correction. When applied to Arabidopsis thaliana, we show that rotating the pots strongly reduced micro‐environmental disparity: heterogeneity in evaporation was cut by a factor of 2.5 and the number of replicates needed to detect a specific mild genotypic effect was reduced by a factor of 3. In addition, by controlling a large proportion of the micro‐environmental variance, other tangible sources of variance become noticeable. Overall, Phenoscope makes it possible to perform large‐scale experiments that would not be possible or reproducible by hand. When applied to a typical quantitative trait loci (QTL) mapping experiment, we show that mapping power is more limited by genetic complexity than phenotyping accuracy. This will help to draw a more general picture as to how genetic diversity shapes phenotypic variation.     

MyROOT: a method and software for the semiautomatic measurement of primary root length in Arabidopsis seedlings

Root analysis is essential for both academic and agricultural research. Despite the great advances in root phenotyping and imaging, calculating root length is still performed manually and involves considerable amounts of labor and time. To overcome these limitations, we developed MyROOT, a software for the semiautomatic quantification of root growth of seedlings growing directly on agar plates. Our method automatically determines the scale from the image of the plate, and subsequently measures the root length of the individual plants. To this aim, MyROOT combines a bottom‐up root tracking approach with a hypocotyl detection algorithm. At the same time as providing accurate root measurements, MyROOT also significantly minimizes the user intervention required during the process. Using Arabidopsis, we tested MyROOT with seedlings from different growth stages and experimental conditions. When comparing the data obtained from this software with that of manual root measurements, we found a high correlation between both methods (R² = 0.997). When compared with previous developed software with similar features (BRAT and EZ‐Rhizo), MyROOT offered an improved accuracy for root length measurements. Therefore, MyROOT will be of great use to the plant science community by permitting high‐throughput root length measurements while saving both labor and time.     

Genetic and genomic resources of sorghum to connect genotype with phenotype in contrasting environments

With the recent development of genomic resources and high‐throughput phenotyping platforms, the 21st century is primed for major breakthroughs in the discovery, understanding and utilization of plant genetic variation. Significant advances in agriculture remain at the forefront to increase crop production and quality to satisfy the global food demand in a changing climate all while reducing the environmental impacts of the world's food production. Sorghum, a resilient C₄ grain and grass important for food and energy production, is being extensively dissected genetically and phenomically to help connect the relationship between genetic and phenotypic variation. Unlike genetically modified crops such as corn or soybean, sorghum improvement has relied heavily on public research; thus, many of the genetic resources serve a dual purpose for both academic and commercial pursuits. Genetic and genomic resources not only provide the foundation to identify and understand the genes underlying variation, but also serve as novel sources of genetic and phenotypic diversity in plant breeding programs. To better disseminate the collective information of this community, we discuss: (i) the genomic resources of sorghum that are at the disposal of the research community; (ii) the suite of sorghum traits as potential targets for increasing productivity in contrasting environments; and (iii) the prospective approaches and technologies that will help to dissect the genotype–phenotype relationship as well as those that will apply foundational knowledge for sorghum improvement.     

Functional mapping of N deficiency‐induced response in wheat yield‐component traits by implementing high‐throughput phenotyping

As overfertilization leads to environmental concerns and the cost of N fertilizer increases, the issue of how to select crop cultivars that can produce high yields on N‐deficient soils has become crucially important. However, little information is known about the genetic mechanisms by which crops respond to environmental changes induced by N signaling. Here, we dissected the genetic architecture of N‐induced phenotypic plasticity in bread wheat (Triticum aestivum L.) by integrating functional mapping and semiautomatic high‐throughput phenotyping data of yield‐related canopy architecture. We identified a set of quantitative trait loci (QTLs) that determined the pattern and magnitude of how wheat cultivars responded to low N stress from normal N supply throughout the wheat life cycle. This analysis highlighted the phenological landscape of genetic effects exerted by individual QTLs, as well as their interactions with N‐induced signals and with canopy measurement angles. This information may shed light on our mechanistic understanding of plant adaptation and provide valuable information for the breeding of N‐deficiency tolerant wheat varieties.     

Estimating wall guidance and attraction in mouse free locomotor behavior

In this study, we estimate the influence exerted by the wall of the Open Field on the trajectory of the mouse. The wall exerts two types of influence on the mouse's path: one of guidance and one of attraction. The guiding influence is expressed by the tendency of mice to progress in parallel to the wall. This tendency wanes with increasing distance from the wall but is observed at large distances from it. The more parallel the mouse is to the wall the higher is its speed, even when distant from the wall. This association between heading direction and speed shows that the mouse controls its heading in reference to the wall. It is also observed in some blind strains, revealing that wall-guidance is not based exclusively on vision. The attraction influence is reflected by movement along the wall and by the asymmetry between speed during movement toward, and during movement away from the wall: sighted mice move faster toward the wall, whereas blind mice use similar speeds in both directions. Measures characterizing these influences are presented for five inbred strains, revealing heritable components that are replicable across laboratories. The revealed structure can lead to the identification of distinct groups of genes that mediate the distinct influences of guidance and attraction exerted by the wall. It can also serve as a framework for the decoding of electrophysiological data recorded in free moving rodents in the Open Field.