Biology subjects

Marchadier, E.

Publications and source records attributed to Marchadier, E..

6 recordsLinked to original sources

bioRxiv2026

Genomic forecasting links climate-associated variation to spring phenology in the European wild apple, a crop wild relative of the cultivated apple

Climate-associated genomic variation is often used as a proxy for adaptive potential, yet whether it reflects adaptation with phenotypic consequences, rather than demography alone, is rarely tested in long-lived species. Genomic offsets forecast climate maladaptation from genotype-environment models but are seldom validated against phenotypes. We combined whole-genome resequencing, SNP and transposable element insertion polymorphism (TIP) variation, landscape genomics, genome-wide association, genomic offset, and common-garden phenotyping in the European wild apple (Malus sylvestris Mill.), a crop wild relative with a complex demographic history, to test this. Results: Of 148 resequenced accessions (135 wild, 13 cultivated), 89 wild individuals formed the core dataset. Population structure was associated with Last Glacial Maximum precipitation rather than contemporary climate, and genetic diversity increased from west to east. Genome-environment associations across 9.75 million SNPs identified climate-associated loci enriched in photoperiod-related flowering-time genes, with limited overlap with phenotype-associated loci. SNP-based genomic offset was associated with bud-break timing in the Saclay common garden (marginal R2 = 0.31), with higher offsets corresponding to earlier bud break, but not with growth or ecophysiological traits. This association depended on Austrian and Romanian populations and was clearest in non-admixed wild individuals. Offsets based on TIPs or glacial climate did not predict measured phenotypes. Conclusions: Climate association, phenotypic relevance, and predictive power of genomic variation are separable. In a long-lived tree, genomic offset predicted spring phenology, a key adaptive trait, but this signal varied across provenances and ancestries and was absent for transposable elements. Genomic offsets can therefore forecast potential phenological maladaptation, provided they are validated against phenotypes such as bud break.

ecology↗

bioRxiv2026

Climate drives plasticity and genetic adaptation in apple trees

BackgroundPerennial crops respond to climate change through phenotypic plasticity and local adaptation, yet how these responses are orchestrated at the molecular level and reshaped by domestication remains poorly understood. ResultsWe grew 1,249 seedlings from five populations of M. domestica, M. orientalis, and M. sylvestris under four simulated European climates, quantified 12 phenotypic traits, performed RNA sequencing on 96 individuals, and integrated these data with previously published genome-wide polymorphism data from M. sylvestris to disentangle conserved climate responses from local adaptation. Climate was the dominant driver of phenotypic and transcriptional variation, revealing 344 conserved climate-responsive genes enriched for stress responses, nutrient metabolism, and cell wall biosynthesis. These genes are under strong purifying selection and carry fewer deleterious mutations. In contrast, genome-environment association analyses identified 217 loci associated with temperature and precipitation gradients, only a subset of which showed climate-responsive expression and elevated genomic differentiation. Population-level expression divergence closely mirrored neutral genetic differentiation, indicating that most transcriptomic divergence reflects demographic history rather than adaptive regulatory evolution. Domestication reshaped molecular diversity and mutation load without disrupting the conserved climate-response program. ConclusionsClimate responses in apple are primarily mediated by an evolutionarily conserved transcriptional program maintained by strong purifying selection, whereas local adaptation relies on largely distinct, population-specific loci. These findings reveal that conserved plasticity constitutes the dominant molecular response to climatic variation, whereas local adaptation contributes a secondary, population-specific layer of evolutionary change.

evolutionary biology↗

bioRxiv2021

A stochastic process modelling of maize phyllochron enables to characterize environmental and genetic effects.

The times between appearance of successive leaves or phyllochron characterize the vegetative development of annual plants. Hypothesis testing models, which enables to compare phyllochron between genetic groups or conditions, are usually based on regression of thermal time on the number of leaves, most of the time assuming a constant leaf appearance rate. However these models are both statistically biased and inappropriate in terms of modelling. We propose a stochastic process model in which the emergence of new leaves is considered as successive time-to-events, which provides a flexible and more accurate modelling as well as unbiased testing procedures. The model was applied on an original maize dataset collected in fields for three years on plants originating from two divergent selection experiments for flowering time conducted in two maize inbred lines. We showed that the main differences in phyllochron were not observed between selection populations (Early or Late), but rather between ancestral lines, years of experimentation, and leaf ranks. Our results highlight a strong departure from the assumption of a constant leaf appearance rate in one year that could be related to climate variations, even if the impact of each climatic variables individually was not clearly elucidated.

plant biology↗

bioRxiv2019

Transcriptional natural variation at FLM induces synergistic pleiotropy in Arabidopsis thaliana

Investigating the evolution of complex phenotypes and the underlying molecular bases of their variation is critical to understand how organisms adapt to the environment. We used leaf growth as a model trait as it is highly integrative of internal and external cues and relies on functions at different levels of the plant organization. Applying classical quantitative genetics on a recombinant inbred line population derived from a Can-0 x Col-0 cross, we identified the MADS-box transcription factor FLOWERING LOCUS M (FLM) as a player of the phenotypic variation for leaf growth and colour. Interestingly, we showed that allelic variation at FLM modulates plant growth strategy along the leaf economics spectrum, a trade-off between resource acquisition and resource conservation observable across thousands of plant species. We demonstrated that the functional differences at FLM relies on a single intronic substitution, disturbing transcript splicing and leading to a low expression of the active FLM transcript. Using phenotypic and climatic data across Arabidopsis natural populations, our work shows how noncoding genetic variation of a single gene may be adaptive through synergistic pleiotropy.

plant biology↗

bioRxiv2018

Transcriptomic response to divergent selection for flowering time in maize reveals convergence and key players of the underlying gene regulatory network

Artificial selection experiments are designed to investigate phenotypic evolution of complex traits and its genetic bases. Here we focused on flowering time, a trait of key importance for plant adaptation and life-cycle shifts. We undertook divergent selection experiments (Saclay DSEs) from two maize inbred lines. After 13 generations of selection, we obtained we obtained a time-lag of roughly two weeks between Early- and Late-populations. We used this material to characterize the genome-wide transcriptomic response to selection in the shoot apical meristem (SAM) before, during and after floral transition in realistic field conditions during two consecutive years. We validated the reliability of performing RNA-sequencing in uncontrolled conditions. We found that roughly half of maize genes were expressed in the SAM, 59.3% of which were differentially expressed. We detected a majority of genes with differential expression between inbreds and across meristem status, and retrieved a subset of 2,451 genes involved in the response to selection. Among these, we found a significant enrichment for genes with known function in maize flowering time. Furthermore, they were more often shared between inbreds than expected by chance, suggesting convergence of gene expression. We discuss new insights into the expression pattern of key players of the underlying gene regulatory network including ZCN8, RAP2.7, ZMM4, KN1, GA2ox1, as well as alternative scenarios for genetic convergence.

plant biology↗

bioRxiv2018

The complex genetic architecture of shoot growth natural variation in Arabidopsis thaliana

One of the main outcome of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, interactions with the genetic background, environment or age... Linkage or association mapping strategies will be more or less sensitive to this complexity, so that we still have an unclear picture of its extent. By combining high-throughput phenotyping under two environmental conditions with classical QTL mapping approaches in multiple Arabidopsis thaliana segregating populations as well as advanced near isogenic lines construction and survey, we have attempted to push back the limits of our understanding of quantitative phenotypic variation. Integrative traits such as those related to vegetative growth used in this work (highlighting either cumulative growth, growth rate or morphology) all showed complex and dynamic genetic architecture with respect to the segregating population and condition. The more resolutive our mapping approach, the more complexity we uncover, with several instances of QTLs visible in near isogenic lines but not detected with the initial QTL mapping, indicating that our phenotyping resolution was less limiting than the mapping resolution with respect to the underlying genetic architecture. In an ultimate approach to resolve this complexity, we intensified our phenotyping effort to target specifically a 3Mb-region known to segregate for a major quantitative trait gene, using a series of selected lines recombined every 100kb. We discovered that at least 3 other independent QTLs had remained hidden in this region, some with trait- or condition-specific effects, or opposite allelic effects. If we were to extrapolate the figures obtained on this specific region in this particular cross to the genome- and species-scale, we would predict hundreds of causative loci of detectable phenotypic effect controlling these growth-related phenotypes.

genetics↗