Spatial genomic structure along uplift vs. non-uplift habitats
We performed several approaches to document the extent of genetic
differentiation among uplifted versus non-uplifted sites and to
characterize uplift associated genetic structuring in the holdfast
epifauna. We used principal component analysis (PCA) to explore SNP
variation among individuals for each species separately using the R
package adegenet v.2.1.1 (Jombart 2008). We applied the spare
non-negative matrix factorization (sNMF) algorithm implemented in the R
package LEA v.2.8.0 (Frichot et al. 2014; Frichot & François
2015) to infer individual ancestry coefficients and delineate putative
genomic clusters. We tested for 1-15 ancestral populations (K )
with 50 replicates per each K value and chose the best Kby using a cross-entropy criterion. To evaluate the robustness of our
results we ran the analysis using four values for the alpha
regularization parameter (1, 10, 100 and 1000). Bar plots were
visualized using the R package pophelper v.2.3.0 (Francis 2017).
We inferred phylogenetic relationships among populations by constructing
neighbor joining trees using SplitsTree v.4.16.1 (Huson & Bryant 2006).