Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform

The plant kingdom contains a stunning array of complex morphologies easily observed above-ground, but more challenging to visualize below-ground. Understanding the magnitude of diversity in root distribution within the soil, termed root system architecture (RSA), is fundamental in determining how this trait contributes to species adaptation in local environments. Roots are the interface between the soil environment and the shoot system and therefore play a key role in anchorage, resource uptake, and stress resilience. Previously, we presented the GLO-Roots (Growth and Luminescence Observatory for Roots) system to study the RSA of soil-grown Arabidopsis thaliana plants from germination to maturity (Rellán-Álvarez et al., 2015). In this study, we present the automation of GLO-Roots using robotics and the development of image analysis pipelines in order to examine the temporal dynamic regulation of RSA and the broader natural variation of RSA in Arabidopsis, over time. These datasets describe the developmental dynamics of two independent panels of accessions and reveal highly complex and polygenic RSA traits that show significant correlation with climate variables of the accessions’ respective origins

Evolutionary genomics can improve prediction of species' responses to climate change

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco-evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large-scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco-evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions

Effector-Triggered Immune Response in Arabidopsis thaliana Is a Quantitative Trait

We identified loci responsible for natural variation in Arabidopsis thaliana (Arabidopsis) responses to a bacterial pathogen virulence factor, HopAM1. HopAM1 is a type III effector protein secreted by the virulent Pseudomonas syringae strain Pto DC3000. Delivery of HopAM1 from disarmed Pseudomonas strains leads to local cell death, meristem chlorosis, or both, with varying intensities in different Arabidopsis accessions. These phenotypes are not associated with differences in bacterial growth restriction. We treated the two phenotypes as quantitative traits to identify host loci controlling responses to HopAM1. Genome-wide association (GWA) of 64 Arabidopsis accessions identified independent variants highly correlated with response to each phenotype. Quantitative trait locus (QTL) mapping in a recombinant inbred population between Bur-0 and Col-0 accessions revealed genetic linkage to regions distinct from the top GWA hits. Two major QTL associated with HopAM1-induced cell death were also associated with HopAM1-induced chlorosis. HopAM1-induced changes in Arabidopsis gene expression showed that rapid HopAM1-dependent cell death in Bur-0 is correlated with effector-triggered immune responses. Studies of the effect of mutations in known plant immune system genes showed, surprisingly, that both cell death and chlorosis phenotypes are enhanced by loss of EDS1, a regulatory hub in the plant immune-signaling network. Our results reveal complex genetic architecture for response to this particular type III virulence effector, in contrast to the typical monogenic control of cell death and disease resistance triggered by most type III effectors

Vision, challenges and opportunities for a Plant Cell Atlas

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them.National Science Foundation 1916797 David W Ehrhardt, Kenneth D Birnbaum, Seung Yon Rhee; National Science Foundation 2052590 Seung Yon Rhe

Vision, challenges and opportunities for a Plant Cell Atlas

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them.</jats:p

On climate change and genetic evolution in Arabidopsis thaliana

Global climate change is already impacting Earth’s biodiversity, but we are still struggling to understand which species will perish and which will thrive. As many species will not tolerate a rapidly-changing climate nor migrate fast enough to escape it, survival will depend on whether populations are able to genetically adapt. Some species, however, seem to rapidly adapt and spread in the new status quo of human-dominated ecosystems. We are just beginning to understand the genomic footprints of past adaptation to climates and how this has prepared populations for future rapid adaptation, but many questions still need to be answered. Furthermore, evolution and adaptation knowledge is rarely integrated into predictive biodiversity models, even though that would increase the accuracy of predictions and help design better conservation strategies. Here I aim to tackle those challenges using the mustard-related plant Arabidopsis thaliana, for which there are public genomic sequences, geographic information, and seed collections of thousands of individuals. Chapter One was my first approach to understand how populations of the same species might respond to climate change. I examined survival of 220 natural Arabidopsis thaliana lines whose genomes are known to a simulated extreme drought in the greenhouse. Severe droughts are being forecast as some of the most drastic threats for plant communities as a consequence of global change. Extending the use of environmental niche models in combination with genome-wide association techniques, I found the hotspots of adaptive variants are primarily at the North and South margins of the species’ distribution range. The populations at those areas, that live in more extreme environments, will perhaps become reservoirs of adaptive variation under future, more hostile climates. In Chapter Two, I carried out a large-scale field experiment to directly quantify climate-driven selection in natural conditions. We planted a global panel of 517 natural A. thaliana lines in rainfall-manipulated common gardens both in a region with a moderate climate, in Central Europe, and in a region with a more extreme environment, the Mediterranean. Using image analysis to estimate reproductive success, I generated close to 25,000 fitness measurements. Combining fitness and genomic data, I could infer massive changes in genome-wide allele frequencies within one generation, especially under hot temperatures and reduced precipitation where many Central European genotypes died. Integrating the theory of local adaptation with machine learning tools, I showed that a significant portion of natural selection is predictable from the climate at the geographic areas where genetic variants are found. Following a decrease in rainfall in the future, I then predicted that the intensity of natural selection will increase the most in transition areas from the Mediterranean to Central Europe, putting populations at evolutionary risk. This is in stark contrast to the generally accepted notion that marginal “warming” populations are at higher risk of extinction than populations at the center of the geographic distribution. Chapter Three, in contrast to the previous chapters that studied the adaptive value of pre-existent variants to future climate change, focuses on how novel mutations could directly contribute to adaptation. Using herbarium samples as genetic snapshots in time, I studied a 400-year-old lineage of A. thaliana that was isolated in North America. I was able to identify over 5,000 new mutations, some of which generated novel morphological differences likely related to adaptation to the newly colonized continent. I concluded that even large organisms such as plants might evolve and adapt from new mutations in contemporary timescales. This work advances our knowledge on how and whether different populations of a species will genetically adapt to the changing climate. Some of the insights generated here include (1) that adaptation to climate occurs thanks to hundreds of genetic variants (polygenic adaptation), (2) that new mutations occur often enough that they could contribute to rapid adaptation in colonizing populations, and (3) that statistical models that learn the relationship between current climates and genetic variants can be used to predict whether populations will have the appropriate genetic makeup to adapt to climate change or whether they will be at evolutionary risk. All in all, these studies move us one step closer to address ecological challenges using the genetic theory of evolution

Spatio-temporal variation in fitness responses to contrasting environments in Arabidopsis thaliana

The evolutionary response of organisms to global climate change is expected to be strongly conditioned by preexisting standing genetic variation. In addition, natural selection imposed by global climate change on fitness‐related traits can be heterogeneous over time. We estimated selection of life‐history traits of an entire genetic lineage of the plant Arabidopsis thaliana occurring in north‐western Iberian Peninsula that were transplanted over multiple years into two environmentally contrasting field sites in southern Spain, as southern environments are expected to move progressively northwards with climate change in the Iberian Peninsula. The results indicated that natural selection on flowering time prevailed over that on recruitment. Selection favored early flowering in six of eight experiments and late flowering in the other two. Such heterogeneity of selection for flowering time might be a powerful mechanism for maintaining genetic diversity in the long run. We also found that north‐western A. thaliana accessions from warmer environments exhibited higher fitness and higher phenotypic plasticity for flowering time in southern experimental facilities. Overall, our transplant experiments suggested that north‐western Iberian A. thaliana has the means to cope with increasingly warmer environments in the region as predicted by trends in global climate change models