Variation and plasticity in life-history traits and fitness of wild Arabidopsis thaliana populations are not related to their genotypic and ecological diversity.

BACKGROUND: Despite its implications for population dynamics and evolution, the relationship between genetic and phenotypic variation in wild populations remains unclear. Here, we estimated variation and plasticity in life-history traits and fitness of the annual plant Arabidopsis thaliana in two common garden experiments that differed in environmental conditions. We used up to 306 maternal inbred lines from six Iberian populations characterized by low and high genotypic (based on whole-genome sequences) and ecological (vegetation type) diversity. RESULTS: Low and high genotypic and ecological diversity was found in edge and core Iberian environments, respectively. Given that selection is expected to be stronger in edge environments and that ecological diversity may enhance both phenotypic variation and plasticity, we expected genotypic diversity to be positively associated with phenotypic variation and plasticity. However, maternal lines, irrespective of the genotypic and ecological diversity of their population of origin, exhibited a substantial amount of phenotypic variation and plasticity for all traits. Furthermore, all populations harbored maternal lines with canalization (robustness) or sensitivity in response to harsher environmental conditions in one of the two experiments. CONCLUSIONS: Overall, we conclude that the environmental attributes of each population probably determine their genotypic diversity, but all populations maintain substantial phenotypic variation and plasticity for all traits, which represents an asset to endure in changing environments.

The trichome pattern diversity of Cardamine shares genetic mechanisms with Arabidopsis but differs in environmental drivers.

Natural variation in trichome pattern (amount and distribution) is prominent among populations of many angiosperms. However, the degree of parallelism in the genetic mechanisms underlying this diversity and its environmental drivers in different species remain unclear. To address these questions, we analyzed the genomic and environmental bases of leaf trichome pattern diversity in Cardamine hirsuta, a relative of Arabidopsis (Arabidopsis thaliana). We characterized 123 wild accessions for their genomic diversity, leaf trichome patterns at different temperatures, and environmental adjustments. Nucleotide diversities and biogeographical distribution models identified two major genetic lineages with distinct demographic and adaptive histories. Additionally, C. hirsuta showed substantial variation in trichome pattern and plasticity to temperature. Trichome amount in C. hirsuta correlated positively with spring precipitation but negatively with temperature, which is opposite to climatic patterns in A. thaliana. Contrastingly, genetic analysis of C. hirsuta glabrous accessions indicated that, like for A. thaliana, glabrousness is caused by null mutations in ChGLABRA1 (ChGL1). Phenotypic genome-wide association studies (GWAS) further identified a ChGL1 haplogroup associated with low trichome density and ChGL1 expression. Therefore, a ChGL1 series of null and partial loss-of-function alleles accounts for the parallel evolution of leaf trichome pattern in C. hirsuta and A. thaliana. Finally, GWAS also detected other candidate genes (e.g. ChETC3, ChCLE17) that might affect trichome pattern. Accordingly, the evolution of this trait in C. hirsuta and A. thaliana shows partially conserved genetic mechanisms but is likely involved in adaptation to different environments.

Unravelling plant diversification: Intraspecific genetic differentiation in hybridizing Anacyclus species in the western Mediterranean Basin.

PREMISE: The interfertile species Anacyclus clavatus, A. homogamos, and A. valentinus represent a plant complex coexisting in large anthropic areas of the western Mediterranean Basin with phenotypically mixed populations exhibiting a great floral variation. The goal of this study was to estimate the genetic identity of each species, to infer the role of hybridization in the observed phenotypic diversity, and to explore the effect of climate on the geographic distribution of species and genetic clusters. METHODS: We used eight nuclear microsatellites to genotype 585 individuals from 31 populations of three Anacyclus species for population genetic analyses by using clustering algorithms based on Bayesian models and ordination methods. In addition, we used ecological niche models and niche overlap analyses for both the species and genetic clusters. We used an expanded data set, including 721 individuals from 129 populations for ecological niche models of the genetic clusters. RESULTS: We found a clear correspondence between species and genetic clusters, except for A. clavatus that included up to three genetic clusters. We detected individuals with admixed genetic ancestry in A. clavatus and in mixed populations. Ecological niche models predicted similar distributions for species and genetic clusters. For the two specific genetic clusters of A. clavatus, ecological niche models predicted remarkably different areas. CONCLUSIONS: Gene flow between Anacyclus species likely explains phenotypic diversity in contact areas. In addition, we suggest that introgression could be involved in the origin of one of the two A. clavatus genetic clusters, which also showed ecological differentiation.

Ali-Bey - an open collaborative georeferencing web application.

Background: Georeferencing preserved specimens represents a major effort at the Museu de Ciències Naturals de Barcelona (MCNB), given the available resources and limited staff that can be allocated to the task. Georeferencing is a labour-intensive and hard-to-automate task that requires software tools that can help in making it as efficient as possible. The tool we present, Ali-Bey, has been slowly developed over 15 years and its functionalities have been gradually built in a process of development, testing, use in production and refinement, rather than as a single development cycle out of a comprehensive specifications requirement document. At the start, the MCNB could not find a tool that fully satisfied the requirements listed as essential and made the decision to develop a custom tool. At the end, the initiative has proved successful since it has delivered a new georeferencing tool that meets the MCNB's needs, all in a context of yearly scarce availability of funds. The tool has been gradually matured and developed over the years, in line with the scarce financing. Only recently, after reaching a notable set of novel features, we considered to release it as an open-source project. The MCNB has supported its development up until this date and decided to open it in order to give the NHC community the opportunity to contribute to its development. New information: We present the software tool Ali-Bey that provides new functionality for the georeferencing of specimens in Natural History Collections, namely the possibility of cooperation between different institutions, the traceability of georeferences and the capability of managing different versions of a same site name, namely for historical reasons. The tool is an open-source web application implemented in Python and the Django framework that leverages other commonly-used specialised geodatabase and map server tools. An API provides access to the geodatabase to externally-developed tools. In addition, for an easy installation, the tool is provided as a multi-container Docker application.

Ecological, genetic and evolutionary drivers of regional genetic differentiation in Arabidopsis thaliana.

BACKGROUND: Disentangling the drivers of genetic differentiation is one of the cornerstones in evolution. This is because genetic diversity, and the way in which it is partitioned within and among populations across space, is an important asset for the ability of populations to adapt and persist in changing environments. We tested three major hypotheses accounting for genetic differentiation-isolation-by-distance (IBD), isolation-by-environment (IBE) and isolation-by-resistance (IBR)-in the annual plant Arabidopsis thaliana across the Iberian Peninsula, the region with the largest genomic diversity. To that end, we sampled, genotyped with genome-wide SNPs, and analyzed 1772 individuals from 278 populations distributed across the Iberian Peninsula. RESULTS: IBD, and to a lesser extent IBE, were the most important drivers of genetic differentiation in A. thaliana. In other words, dispersal limitation, genetic drift, and to a lesser extent local adaptation to environmental gradients, accounted for the within- and among-population distribution of genetic diversity. Analyses applied to the four Iberian genetic clusters, which represent the joint outcome of the long demographic and adaptive history of the species in the region, showed similar results except for one cluster, in which IBR (a function of landscape heterogeneity) was the most important driver of genetic differentiation. Using spatial hierarchical Bayesian models, we found that precipitation seasonality and topsoil pH chiefly accounted for the geographic distribution of genetic diversity in Iberian A. thaliana. CONCLUSIONS: Overall, the interplay between the influence of precipitation seasonality on genetic diversity and the effect of restricted dispersal and genetic drift on genetic differentiation emerges as the major forces underlying the evolutionary trajectory of Iberian A. thaliana.

A hierarchical Bayesian Beta regression approach to study the effects of geographical genetic structure and spatial autocorrelation on species distribution range shifts.

Global climate change (GCC) may be causing distribution range shifts in many organisms worldwide. Multiple efforts are currently focused on the development of models to better predict distribution range shifts due to GCC. We addressed this issue by including intraspecific genetic structure and spatial autocorrelation (SAC) of data in distribution range models. Both factors reflect the joint effect of ecoevolutionary processes on the geographical heterogeneity of populations. We used a collection of 301 georeferenced accessions of the annual plant Arabidopsis thaliana in its Iberian Peninsula range, where the species shows strong geographical genetic structure. We developed spatial and nonspatial hierarchical Bayesian models (HBMs) to depict current and future distribution ranges for the four genetic clusters detected. We also compared the performance of HBMs with Maxent (a presence-only model). Maxent and nonspatial HBMs presented some shortcomings, such as the loss of accessions with high genetic admixture in the case of Maxent and the presence of residual SAC for both. As spatial HBMs removed residual SAC, these models showed higher accuracy than nonspatial HBMs and handled the spatial effect on model outcomes. The ease of modelling and the consistency among model outputs for each genetic cluster was conditioned by the sparseness of the populations across the distribution range. Our HBMs enrich the toolbox of software available to evaluate GCC-induced distribution range shifts by considering both genetic heterogeneity and SAC, two inherent properties of any organism that should not be overlooked.

Quantifying temporal change in plant population attributes: insights from a resurrection approach.

Rapid evolution in annual plants can be quantified by comparing phenotypic and genetic changes between past and contemporary individuals from the same populations over several generations. Such knowledge will help understand the response of plants to rapid environmental shifts, such as the ones imposed by global climate change. To that end, we undertook a resurrection approach in Spanish populations of the annual plant Arabidopsis thaliana that were sampled twice over a decade. Annual weather records were compared to their historical records to extract patterns of climatic shifts over time. We evaluated the differences between samplings in flowering time, a key life-history trait with adaptive significance, with a field experiment. We also estimated genetic diversity and differentiation based on neutral nuclear markers and nucleotide diversity in candidate flowering time (FRI and FLC) and seed dormancy (DOG1) genes. The role of genetic drift was estimated by computing effective population sizes with the temporal method. Overall, two climatic scenarios were detected: intense warming with increased precipitation and moderate warming with decreased precipitation. The average flowering time varied little between samplings. Instead, within-population variation in flowering time exhibited a decreasing trend over time. Substantial temporal changes in genetic diversity and differentiation were observed with both nuclear microsatellites and candidate genes in all populations, which were interpreted as the result of natural demographic fluctuations. We conclude that drought stress caused by moderate warming with decreased precipitation may have the potential to reduce within-population variation in key life-cycle traits, perhaps as a result of stabilizing selection on them, and to constrain the genetic differentiation over time. Besides, the demographic behaviour of populations probably accounts for the substantial temporal patterns of genetic variation, while keeping rather constant those of phenotypic variation.

Genome-wide signatures of flowering adaptation to climate temperature: Regional analyses in a highly diverse native range of Arabidopsis thaliana.

Current global change is fueling an interest to understand the genetic and molecular mechanisms of plant adaptation to climate. In particular, altered flowering time is a common strategy for escape from unfavourable climate temperature. In order to determine the genomic bases underlying flowering time adaptation to this climatic factor, we have systematically analysed a collection of 174 highly diverse Arabidopsis thaliana accessions from the Iberian Peninsula. Analyses of 1.88 million single nucleotide polymorphisms provide evidence for a spatially heterogeneous contribution of demographic and adaptive processes to geographic patterns of genetic variation. Mountains appear to be allele dispersal barriers, whereas the relationship between flowering time and temperature depended on the precise temperature range. Environmental genome-wide associations supported an overall genome adaptation to temperature, with 9.4% of the genes showing significant associations. Furthermore, phenotypic genome-wide associations provided a catalogue of candidate genes underlying flowering time variation. Finally, comparison of environmental and phenotypic genome-wide associations identified known (Twin Sister of FT, FRIGIDA-like 1, and Casein Kinase II Beta chain 1) and new (Epithiospecifer Modifier 1 and Voltage-Dependent Anion Channel 5) genes as candidates for adaptation to climate temperature by altered flowering time. Thus, this regional collection provides an excellent resource to address the spatial complexity of climate adaptation in annual plants.

Tackling intraspecific genetic structure in distribution models better reflects species geographical range.

Genetic diversity provides insight into heterogeneous demographic and adaptive history across organisms' distribution ranges. For this reason, decomposing single species into genetic units may represent a powerful tool to better understand biogeographical patterns as well as improve predictions of the effects of GCC (global climate change) on biodiversity loss. Using 279 georeferenced Iberian accessions, we used classes of three intraspecific genetic units of the annual plant Arabidopsis thaliana obtained from the genetic analyses of nuclear SNPs (single nucleotide polymorphisms), chloroplast SNPs, and the vernalization requirement for flowering. We used SDM (species distribution models), including climate, vegetation, and soil data, at the whole-species and genetic-unit levels. We compared model outputs for present environmental conditions and with a particularly severe GCC scenario. SDM accuracy was high for genetic units with smaller distribution ranges. Kernel density plots identified the environmental variables underpinning potential distribution ranges of genetic units. Combinations of environmental variables accounted for potential distribution ranges of genetic units, which shrank dramatically with GCC at almost all levels. Only two genetic clusters increased their potential distribution ranges with GCC. The application of SDM to intraspecific genetic units provides a detailed picture on the biogeographical patterns of distinct genetic groups based on different genetic criteria. Our approach also allowed us to pinpoint the genetic changes, in terms of genetic background and physiological requirements for flowering, that Iberian A. thaliana may experience with a GCC scenario applying SDM to intraspecific genetic units.

Deciphering the adjustment between environment and life history in annuals: lessons from a geographically-explicit approach in Arabidopsis thaliana.

The role that different life-history traits may have in the process of adaptation caused by divergent selection can be assessed by using extensive collections of geographically-explicit populations. This is because adaptive phenotypic variation shifts gradually across space as a result of the geographic patterns of variation in environmental selective pressures. Hence, large-scale experiments are needed to identify relevant adaptive life-history traits as well as their relationships with putative selective agents. We conducted a field experiment with 279 geo-referenced accessions of the annual plant Arabidopsis thaliana collected across a native region of its distribution range, the Iberian Peninsula. We quantified variation in life-history traits throughout the entire life cycle. We built a geographic information system to generate an environmental data set encompassing climate, vegetation and soil data. We analysed the spatial autocorrelation patterns of environmental variables and life-history traits, as well as the relationship between environmental and phenotypic data. Almost all environmental variables were significantly spatially autocorrelated. By contrast, only two life-history traits, seed weight and flowering time, exhibited significant spatial autocorrelation. Flowering time, and to a lower extent seed weight, were the life-history traits with the highest significant correlation coefficients with environmental factors, in particular with annual mean temperature. In general, individual fitness was higher for accessions with more vigorous seed germination, higher recruitment and later flowering times. Variation in flowering time mediated by temperature appears to be the main life-history trait by which A. thaliana adjusts its life history to the varying Iberian environmental conditions. The use of extensive geographically-explicit data sets obtained from field experiments represents a powerful approach to unravel adaptive patterns of variation. In a context of current global warming, geographically-explicit approaches, evaluating the match between organisms and the environments where they live, may contribute to better assess and predict the consequences of global warming.