Population genomics highlights structural variations in local adaptation to saline coastal environments in woolly grape

Structural variations(SVs)are a feature of plant genomes that has been largely unexplored despite their significant impact on plant phenotypic traits and local adaptation to abiotic and biotic stress.In this study,we employed woolly grape(Vitis retordii),a species native to the tropical and subtropical regions of East Asia with both coastal and inland habitats,as a valuable model for examining the impact of SVs on local adaptation.We assembled a haplotype-resolved chromosomal reference genome for woolly grape,and conducted population genetic analyses based on whole-genome sequencing(WGS)data from coastal and inland populations.The demographic analyses revealed recent bottlenecks in all populations and asymmetric gene flow from the inland to the coastal population.In total,1,035 genes associated with plant adaptive regulation for salt stress,radiation,and environmental adaptation were detected underlying local selection by SVs and SNPs in the coastal population,of which 37.29% and 65.26% were detected by SVs and SNPs,respectively.Candidate genes such as FSD2,RGA1,and AAP8 associated with salt tolerance were found to be highly differentiated and selected during the process of local adaptation to coastal habitats in SV regions.Our study highlights the importance of SVs in local adaptation;candidate genes related to salt stress and climatic adaptation to tropical and subtropical environments are important genomic resources for future breeding programs of grapevine and its rootstocks.

Specht Triangle Approximation of Large Bending Isometries

We propose a Specht triangle discretization for a geometrically nonlinear Kirchhoff plate model with large bending isometry.A combination of an adaptive time-stepping gradient flow and a Newton’s method is employed to solve the ensuing nonlinear minimization problem.Γ−convergence of the Specht triangle discretization and the unconditional stability of the gradient flow algorithm are proved.We present several numerical examples to demonstrate that our approach significantly enhances both the computational efficiency and accuracy.