Biology subjects

Ressayre, A.

Publications and source records attributed to Ressayre, A..

3 recordsLinked to original sources

bioRxiv2023

The coupling between mutations effects and environment guides the exploration of the phenotypic space as evidenced in artificial selection experiments

Quantitative genetics models have shown that long-term selection responses depend on initial variance and mutational influx. Understanding limits of selection requires quantifying the role of mutational variance. However, correlative responses to selection on non-focal traits can perturb the selection response on the focal trait; and generations are often confounded with selection environments so that genotype by environment (GxE) interactions are ignored. The Saclay Divergent Selection Experiments (DSE) on maize flowering time were used to track the fate of individual mutations combining genotyping data and phenotyping data from yearly measurements (DSEYM) and common garden experiments (DSECG) with four objectives (1) to quantify the relative contribution of standing and mutational variance to the selection response, (2) to estimate genotypic mutation effects, (3) to study the impact of GxE interactions in the selection response, (4) to analyze how trait correlations modulate the exploration of the phenotypic space. We validated experimentally the expected enrichment of fixed beneficial mutations with an average effect of +0.278 and +0.299 days to flowering, depending on the genetic background. Fixation of unfavorable mutations reached up to 25% of incoming mutations, a genetic load possibly due to antagonistic pleiotropy, whereby mutations fixed in the selection environment (DSEYM) turned to be unfavorable in the evaluation environment (DSECG). Global patterns of trait correlations were conserved across genetic backgrounds but exhibited temporal patterns. Traits weakly or uncorrelated with flowering time triggered stochastic exploration of the phenotypic space, owing to microenvironment-specific fixation of standing variants and pleiotropic mutational input.

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↗

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↗