Unraveling the secrets of plant roots: Simplified method for large scale root exudate sampling and analysis in Arabidopsis thaliana.

Background: Plants exude a plethora of compounds to communicate with their environment. Although much is known about above-ground plant communication, we are only beginning to fathom the complexities of below-ground chemical communication channels. Studying root-exuded compounds and their role in plant communication has been difficult due to the lack of standardized methodologies. Here, we develop an interdisciplinary workflow to explore the natural variation in root exudate chemical composition of the model plant Arabidopsis thaliana. We highlight key challenges associated with sampling strategies and develop a framework for analyzing both narrow- and broad-scale patterns of root exudate composition in a large set of natural A. thaliana accessions. Methods: Our method involves cultivating individual seedlings in vitro inside a plastic mesh, followed by a short hydroponic sampling period in small quantities of ultrapure water. The mesh makes it easy to handle plants of different sizes and allows for large-scale characterization of individual plant root exudates under axenic conditions. This setup can also be easily extended for prolonged temporal exudate collection experiments. Furthermore, the short sampling time minimizes the duration of the experiment while still providing sufficient signal even with small volume of the sampling solution. We used ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) for untargeted metabolic profiling, followed by tentative compound identification using MZmine3 and SIRIUS 5 software, to capture a broad overview of root exudate composition in A. thaliana accessions. Results: Based on 28 replicates of the Columbia genotype (Col-0) compared with 10 random controls, MZmine3 annotated 354 metabolites to be present only in Col-0 by negative ionization. Of these, 254 compounds could be annotated by SIRIUS 5 software. Conclusions: The methodology developed in this study can be used to broadly investigate the role of root exudates as chemical signals in plant belowground interactions.

Plants exude many compounds to communicate with their surroundings. For decades, our understanding of this chemical communication was limited to studying the aboveground parts of plants, as roots are hidden within the soil, which makes them difficult to study. We are only beginning to comprehend the complexities and importance of below ground communication channels (including plant-microbes, plant-insects, and plant-plants). Identifying the chemical compounds plant exude belowground (called root exudates) is important for us to fully comprehend their potential roles in a plant´s life. Here, we developed a simplified and easy-to-manage setup for collecting and analyzing root exudates from individual Arabidopsis thaliana plants.

Toward Unifying Evolutionary Ecology and Genomics to Understand Positive Plant-Plant Interactions Within Wild Species.

In a local environment, plant networks include interactions among individuals of different species and among genotypes of the same species. While interspecific interactions are recognized as main drivers of plant community patterns, intraspecific interactions have recently gained attention in explaining plant community dynamics. However, an overview of intraspecific genotype-by-genotype interaction patterns within wild plant species is still missing. From the literature, we identified 91 experiments that were mainly designed to investigate the presence of positive interactions based on two contrasting hypotheses. Kin selection theory predicts partisan help given to a genealogical relative. The rationale behind this hypothesis relies on kin/non-kin recognition, with the positive outcome of kin cooperation substantiating it. On the other hand, the elbow-room hypothesis supports intraspecific niche partitioning leading to positive outcome when genetically distant genotypes interact. Positive diversity-productivity relationship rationalizes this hypothesis, notably with the outcome of overyielding. We found that both these hypotheses have been highly supported in experimental studies despite their opposite predictions between the extent of genetic relatedness among neighbors and the level of positive interactions. Interestingly, we identified a highly significant effect of breeding system, with a high proportion of selfing species associated with the presence of kin cooperation. Nonetheless, we identified several shortcomings regardless of the species considered, such as the lack of a reliable estimate of genetic relatedness among genotypes and ecological characterization of the natural habitats from which genotypes were collected, thereby impeding the identification of selective drivers of positive interactions. We therefore propose a framework combining evolutionary ecology and genomics to establish the eco-genomic landscape of positive GxG interactions in wild plant species.

The genetics underlying natural variation of plant-plant interactions, a beloved but forgotten member of the family of biotic interactions.

Despite the importance of plant-plant interactions on crop yield and plant community dynamics, our understanding of the genetic and molecular bases underlying natural variation of plant-plant interactions is largely limited in comparison with other types of biotic interactions. By listing 63 quantitative trait loci (QTL) mapping and global gene expression studies based on plants directly challenged by other plants, we explored whether the genetic architecture and the function of the candidate genes underlying natural plant-plant interactions depend on the type of interactions between two plants (competition versus commensalism versus reciprocal helping versus asymmetry). The 16 transcriptomic studies are unevenly distributed between competitive interactions (n = 12) and asymmetric interactions (n = 4, all focusing on response to parasitic plants). By contrast, 17 and 30 QTL studies were identified for competitive interactions and asymmetric interactions (either weed suppressive ability or response to parasitic plants), respectively. Surprisingly, no studies have been carried out on the identification of genetic and molecular bases underlying natural variation in positive interactions. The candidate genes underlying natural plant-plant interactions can be classified into seven categories of plant function that have been identified in artificial environments simulating plant-plant interactions either frequently (photosynthesis, hormones), only recently (cell wall modification and degradation, defense pathways against pathogens) or rarely (ABC transporters, histone modification and meristem identity/life history traits). Finally, we introduce several avenues that need to be explored in the future to obtain a thorough understanding of the genetic and molecular bases underlying plant-plant interactions within the context of realistic community complexity.