Phenotypic Trait Variation as a Response to Altitude-Related Constraints in Arabidopsis Populations

Extent of intraspecific trait variability in ecologically central and marginal populations of a dominant alpine plant across European mountains

BACKGROUND AND AIMS

Studying trait variability and restricted gene flow between populations of species can reveal species dynamics. Peripheral populations commonly exhibit lower genetic diversity and trait variability due to isolation and ecological marginality, unlike central populations experiencing gene flow and optimal conditions. This study focused on Carex curvula, the dominant species in alpine acidic meadows of European mountain regions. The species is sparser in dry areas such as the Pyrenees and Balkans, compared to the Central-Eastern Alps and Carpathians. We hypothesized that distinct population groups could be identified based on their mean functional trait values and their correlation with the environment; we predicted that ecologically marginal populations would have stronger trait correlations, lower within-population trait variability (intraspecific trait variability, ITV) and lower genetic diversity than populations of optimal habitats.

METHODS

Sampling was conducted in 34 populations that spanned the entire distribution range of C. curvula. We used hierarchical clustering to identify emergent functional groups of populations, defined by combinations of multiple traits associated with nutrient economy and drought tolerance (e.g. specific leaf area, anatomy). We contrasted the geographical distribution of these groups in relation to environment and genetic structure. We compared pairwise trait relationships, within-population trait variation (ITV) and neutral genetic diversity between groups.

KEY RESULTS

Our study identified emergent functional groups of populations. Those in the southernmost ranges, specifically the Pyrenees and Balkan region, showed drought-tolerant trait syndromes and correlated with indicators of limited water availability. While we noted a decline in population genetic diversity, we did not observe any significant changes in ITV in ecologically marginal (peripheral) populations.

CONCLUSIONS

Our research exemplifies the relationship between ecological marginality and geographical peripherality, which in this case study is linked to genetic depauperation but not to reduced ITV. Understanding these relationships is crucial for understanding the biogeographical factors shaping trait variation.

Environmental Conditions Modulate Plant Virus Vertical Transmission and Survival of Infected Seeds

Seed transmission is a major mode for plant virus persistence and dispersal, as it allows for virus survival within the seed in unfavorable conditions and facilitates spread when they become more favorable. To access these benefits, viruses require infected seeds to remain viable and germinate in altered environmental conditions, which may also be advantageous for the plant. However, how environmental conditions and virus infection affect seed viability, and whether these effects modulate seed transmission rate and plant fitness, is unknown. To address these questions, we utilized turnip mosaic virus, cucumber mosaic virus, and Arabidopsis thaliana as model systems. Using seeds from plants infected by these viruses, we analyzed seed germination rates, as a proxy of seed viability, and virus seed transmission rate under standard and altered temperature, CO2, and light intensity. With these data, we developed and parameterized a mathematical epidemiological model to explore the consequences of the observed alterations on virus prevalence and persistence. Altered conditions generally reduced overall seed viability and increased virus transmission rate compared with standard conditions, which indicated that under environmental stress, infected seeds are more viable. Hence, virus presence may be beneficial for the host. Subsequent simulations predicted that enhanced viability of infected seeds and higher virus transmission rate may increase virus prevalence and persistence in the host population under altered conditions. This work provides novel information on the influence of the environment in plant virus epidemics. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

45S rDNA Diversity In Natura as One Step towards Ribosomal Heterogeneity in Arabidopsis thaliana

The keystone of ribosome biogenesis is the transcription of 45S rDNA. The Arabidopsis thaliana genome contains hundreds of 45S rDNA units; however, they are not all transcribed. Notably, 45S rDNA units contain insertions/deletions revealing the existence of heterogeneous rRNA genes and, likely, heterogeneous ribosomes for rRNAs. In order to obtain an overall picture of 45S rDNA diversity sustaining the synthesis of rRNAs and, subsequently, of ribosomes in natura, we took advantage of 320 new occurrences of Arabidopsis thaliana as a metapopulation named At66, sampled from 0 to 1900 m of altitude in the eastern Pyrenees in France. We found that the 45S rDNA copy number is very dynamic in natura and identified new genotypes for both 5' and 3' External Transcribed Spacers (ETS). Interestingly, the highest 5'ETS genotype diversity is found in altitude while the highest 3'ETS genotype diversity is found at sea level. Structural analysis of 45S rDNA also shows conservation in natura of specific 5'ETS and 3'ETS sequences/features required to control rDNA expression and the processing of rRNAs. In conclusion, At66 is a worthwhile natural laboratory, and unraveled 45S rDNA diversity represents an interesting starting material to select subsets for rDNA transcription and alter the rRNA composition of ribosomes both intra- and inter-site.

Foliar Phenotypic Plasticity Reflects Adaptation to Environmental Variability

Arabidopsis thaliana ecotypes adapted to native habitats with different daylengths, temperatures, and precipitation were grown experimentally under seven combinations of light intensity and leaf temperature to assess their acclimatory phenotypic plasticity in foliar structure and function. There were no differences among ecotypes when plants developed under moderate conditions of 400 µmol photons m-2 s-1 and 25 °C. However, in response to more extreme light or temperature regimes, ecotypes that evolved in habitats with pronounced differences in either the magnitude of changes in daylength or temperature or in precipitation level exhibited pronounced adjustments in photosynthesis and transpiration, as well as anatomical traits supporting these functions. Specifically, when grown under extremes of light intensity (100 versus 1000 µmol photons m-2 s-1) or temperature (8 °C versus 35 °C), ecotypes from sites with the greatest range of daylengths and temperature over the growing season exhibited the greatest differences in functional and structural features related to photosynthesis (light- and CO2-saturated capacity of oxygen evolution, leaf dry mass per area or thickness, phloem cells per minor vein, and water-use efficiency of CO2 uptake). On the other hand, the ecotype from the habitat with the lowest precipitation showed the greatest plasticity in features related to water transport and loss (vein density, ratio of water to sugar conduits in foliar minor veins, and transpiration rate). Despite these differences, common structure-function relationships existed across all ecotypes and growth conditions, with significant positive, linear correlations (i) between photosynthetic capacity (ranging from 10 to 110 µmol O2 m-2 s-1) and leaf dry mass per area (from 10 to 75 g m-2), leaf thickness (from 170 to 500 µm), and carbohydrate-export infrastructure (from 6 to 14 sieve elements per minor vein, from 2.5 to 8 µm2 cross-sectional area per sieve element, and from 16 to 82 µm2 cross-sectional area of sieve elements per minor vein); (ii) between transpiration rate (from 1 to 17 mmol H2O m-2 s-1) and water-transport infrastructure (from 3.5 to 8 tracheary elements per minor vein, from 13.5 to 28 µm2 cross-sectional area per tracheary element, and from 55 to 200 µm2 cross-sectional area of tracheary elements per minor vein); (iii) between the ratio of transpirational water loss to CO2 fixation (from 0.2 to 0.7 mol H2O to mmol-1 CO2) and the ratio of water to sugar conduits in minor veins (from 0.4 to 1.1 tracheary to sieve elements, from 4 to 6 µm2 cross-sectional area of tracheary to sieve elements, and from 2 to 6 µm2 cross-sectional area of tracheary elements to sieve elements per minor vein); (iv) between sugar conduits and sugar-loading cells; and (v) between water conducting and sugar conducting cells. Additionally, the proportion of water conduits to sugar conduits was greater for all ecotypes grown experimentally under warm-to-hot versus cold temperature. Thus, developmental acclimation to the growth environment included ecotype-dependent foliar structural and functional adjustments resulting in multiple common structural and functional relationships.

Multi-omics Data Integration in the Context of Plant Abiotic Stress Signaling

In order to answer new biological questions, high-throughput data generated by new biotechnologies can be very meaningful but require specific and adapted statistical treatments. Thus, in the context of abiotic stress signaling studies, understanding the integration of cascading mechanisms from stress perception to biochemical and physiological adjustments necessarily entails efficient and valid analysis of multilevel and heterogeneous data. In this chapter, we propose examples to manage, analyze, and integrate multi-omics heterogeneous data. This workflow suggests and follows different general biological questions or issues answered with detailed code, data analysis, multiple visualizations, and always followed by brief interpretations. We illustrated this using the mixOmics package for the R software, as it specifically provides tools to address vertical and horizontal data integration issues. In order to illustrate this workflow, we used the usual omics datasets biologists can generate (phenomics, metabolomics, proteomics, and transcriptomics). These data were collected from two organs (leaf rosettes, floral stems) of five ecotypes of the model plant Arabidopsis thaliana exposed to two temperature growth conditions. They are available in the R package WallOmicsData. The workflow presented here is not limited to Arabidopsis thaliana and can be applied to any plant species. It can even be largely deployed to whatever the organisms of interest and the biological questions may be.

Class III Peroxidases in Response to Multiple Abiotic Stresses in Arabidopsis thaliana Pyrenean Populations

Class III peroxidases constitute a plant-specific multigene family, where 73 genes have been identified in Arabidopsis thaliana. These genes are members of the reactive oxygen species (ROS) regulatory network in the whole plant, but more importantly, at the root level. In response to abiotic stresses such as cold, heat, and salinity, their expression is significantly modified. To learn more about their transcriptional regulation, an integrative phenotypic, genomic, and transcriptomic study was executed on the roots of A. thaliana Pyrenean populations. Initially, the root phenotyping highlighted 3 Pyrenean populations to be tolerant to cold (Eaux), heat (Herr), and salt (Grip) stresses. Then, the RNA-seq analyses on these three populations, in addition to Col-0, displayed variations in CIII Prxs expression under stressful treatments and between different genotypes. Consequently, several CIII Prxs were particularly upregulated in the tolerant populations, suggesting novel and specific roles of these genes in plant tolerance against abiotic stresses.

An integrative Study Showing the Adaptation to Sub-Optimal Growth Conditions of Natural Populations of Arabidopsis thaliana: A Focus on Cell Wall Changes

In the global warming context, plant adaptation occurs, but the underlying molecular mechanisms are poorly described. Studying natural variation of the model plant Arabidopsisthaliana adapted to various environments along an altitudinal gradient should contribute to the identification of new traits related to adaptation to contrasted growth conditions. The study was focused on the cell wall (CW) which plays major roles in the response to environmental changes. Rosettes and floral stems of four newly-described populations collected at different altitudinal levels in the Pyrenees Mountains were studied in laboratory conditions at two growth temperatures (22 vs. 15 °C) and compared to the well-described Col ecotype. Multi-omic analyses combining phenomics, metabolomics, CW proteomics, and transcriptomics were carried out to perform an integrative study to understand the mechanisms of plant adaptation to contrasted growth temperature. Different developmental responses of rosettes and floral stems were observed, especially at the CW level. In addition, specific population responses are shown in relation with their environment and their genetics. Candidate genes or proteins playing roles in the CW dynamics were identified and will deserve functional validation. Using a powerful framework of data integration has led to conclusions that could not have been reached using standard statistical approaches.

A powerful framework for an integrative study with heterogeneous omics data: from univariate statistics to multi-block analysis

High-throughput data generated by new biotechnologies require specific and adapted statistical treatment in order to be efficiently used in biological studies. In this article, we propose a powerful framework to manage and analyse multi-omics heterogeneous data to carry out an integrative analysis. We have illustrated this using the mixOmics package for R software as it specifically addresses data integration issues. Our work also aims at applying the most recent functionalities of mixOmics to real datasets. Although multi-block integrative methodologies exist, we hope to encourage a more widespread use of such approaches in an operational framework by biologists. We have used natural populations of the model plant Arabidopsis thaliana in this work, but the framework proposed is not limited to this plant and can be deployed whatever the organisms of interest and the biological question may be. Four omics datasets (phenomics, metabolomics, cell wall proteomics and transcriptomics) were collected, analysed and integrated to study the cell wall plasticity of plants exposed to sub-optimal temperature growth conditions. The methodologies presented here start from basic univariate statistics leading to multi-block integration analysis. We have also highlighted the fact that each method, either unsupervised or supervised, is associated with one biological issue. Using this powerful framework enabled us to arrive at novel conclusions on the biological system, which would not have been possible using standard statistical approaches.

Transcriptomic and cell wall proteomic datasets of rosettes and floral stems from five Arabidopsis thaliana ecotypes grown at optimal or sub-optimal temperature

This article provides experimental data describing the RNA and the cell wall protein profiles of rosettes and flower stems of five Arabidopsis thaliana ecotypes. Four newly-described Pyrenees ecotypes [1] are analyzed in addition to the well-described and sequenced Columbia (Col) ecotype of A. thaliana. All five ecotypes have been grown at two different temperatures, 22 °C and 15 °C. We provide transcriptomics and cell wall proteomics data regarding (i) rosettes at the bolting stage, and (ii) floral stems at the first flower stage. These data are a valuable resource to study the adaptation of A. thaliana ecotypes to sub-optimal temperature growth conditions.

Phenotyping and cell wall polysaccharide composition dataset of five arabidopsis ecotypes grown at optimal or sub-optimal temperatures

This article presents experimental data describing the morphology and the cell wall monosaccharide content of rosettes and flower stems of five Arabidopsis thaliana ecotypes grown at two contrasted temperatures. Besides, cell wall polysaccharides are reconstructed from data of monosaccharide quantification. The well-described and sequenced Columbia (Col) ecotype and four newly-described Pyrenees ecotypes (Duruflé et al., 2019) have been grown at two different temperatures (15 °C and 22 °C). For macrophenotyping, we provide dataset regarding (i) rosettes such as measurement of diameter and fresh mass as well as number of leaves just before bolting and (ii) floral stems at the first flower stage such as length, number of cauline leaves, mass and diameter at its base. Regarding cell wall composition, we provide data of quantification of seven monosaccharides and the reconstruction three polysaccharides. All these data are markers to differentiate both growth temperatures and the different ecotypes. They constitute a valuable resource for the community to study the adaptation of A. thaliana ecotypes to sub-optimal temperature growth conditions.