bioRxivPlant BiologyPreprint
Water stress-associated isolation barriers between two sympatric oak species
G. LE PROVOST, B. Brachi, I. Lesur, C. Lalanne, K. Labadie, J. M. Aury, C. Da Silva, D. Postolache, T. Leroy, C. Plomion
Abstract
Drought and waterlogging impede tree growth and may even lead to tree death. With climate change, these environmental factors are a growing source of concern, particularly for temperate forests. Oaks, an emblematic group of tree species, have evolved a range of adaptations to cope with these constraints. The two most widely distributed European species -- pedunculate oak (PO) and sessile oaks (SO) -- have overlapping ranges, but are highly constrained locally by soil water content variation. These differences in local ecological requirements provide a powerful biological model for studying the role of ecological barriers in speciation. We used an experimental set-up mimicking the ecological preferences of these species, in which seedlings were subjected to waterlogging and drought. We studied gene expression in roots by RNA-seq and identified genes differentially expressed between treatments with different outcomes depending on species. These "species x environment"-responsive genes revealed adaptive molecular strategies involving adventitious and lateral root formation, aerenchyma formation in PO, and osmoregulation and ABA regulation in SO. With this experimental design, we also identified genes with expression profiles presenting a "species" effect regardless of imposed constraints with important roles in intrinsic reproductive barriers. Finally, we compared our findings with those for a genome scan of species divergence and found that the candidate genes were enriched in highly differentiated SNPs. This suggests that many of the genes involved in the contrasting transcriptomic responses are subject to natural selection and that gene regulation helps to maintain these two different oak species in sympatry.
- organism: multiple species
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
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