Saguaro cactus within-species phylogenomics

Dataset

Description

Reconstructing accurate historical relationships between populations within a species poses numerous challenges, not least in many plant groups in which gene flow can extend well beyond species boundaries. Nonetheless, the extent of tree-like history within a species is an empirical question on which it is now possible to bring large amounts of genome sequence to bear. We assess phylogenetic structure across the geographic range of the saguaro cactus, an emblematic member of Cactaceae, a clade known for extensive hybridization and porous species boundaries. Using 200 Gb of whole genome resequencing data from 20 individuals sampled from 10 localities, we assembled two data sets comprising 150,000 biallelic single nucleotide polymorphisms (SNPs) from protein coding sequences. From these we infer a population tree and evaluate its significance and robustness using five qualitatively different inference methods. Despite the low sequence diversity, large census population sizes, and presence of wide-ranging pollen and seed dispersal agents, population trees were well resolved and highly consistent across both data sets and all methods. We inferred that the most likely root, based on marginal likelihood comparisons, is to the east and south of the region of highest genetic diversity, which lies along the coast of the Gulf of California. Together with striking decreases in marginal likelihood found to the north, this supports hypotheses that saguaro's current range reflects post-glacial expansion from the far south following retreat to refugia there. We conclude with observations about practical and theoretical issues raised by phylogenomic data sets within species, in which SNP-based methods must be used rather than gene tree methods that are widely used when sequence divergence is higher. These include computational scalability, inference of gene flow, and proper assessment of statistical support in the presence of linkage effects.
Date made availableApr 8 2022
PublisherZENODO

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