Comprehending Cornales: Phylogenetic Reconstruction Of The Order Using The Angiosperms353 Probe Set

AMERICAN JOURNAL OF BOTANY(2021)

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摘要
Premise Cornales is an order of flowering plants containing ecologically and horticulturally important families, including Cornaceae (dogwoods) and Hydrangeaceae (hydrangeas), among others. While many relationships in Cornales are strongly supported by previous studies, some uncertainty remains with regards to the placement of Hydrostachyaceae and to relationships among families in Cornales and within Cornaceae. Here we analyzed hundreds of nuclear loci to test published phylogenetic hypotheses and estimated a robust species tree for Cornales. Methods Using the Angiosperms353 probe set and existing data sets, we generated phylogenomic data for 158 samples, representing all families in the Cornales, with intensive sampling in the Cornaceae. Results We curated an average of 312 genes per sample, constructed maximum likelihood gene trees, and inferred a species tree using the summary approach implemented in ASTRAL-III, a method statistically consistent with the multispecies coalescent model. Conclusions The species tree we constructed generally shows high support values and a high degree of concordance among individual nuclear gene trees. Relationships among families are largely congruent with previous molecular studies, except for the placement of the nyssoids and the Grubbiaceae-Curtisiaceae clades. Furthermore, we were able to place Hydrostachyaceae within Cornales, and within Cornaceae, the monophyly of known morphogroups was well supported. However, patterns of gene tree discordance suggest potential ancient reticulation, gene flow, and/or ILS in the Hydrostachyaceae lineage and the early diversification of Cornus. Our findings reveal new insights into the diversification process across Cornales and demonstrate the utility of the Angiosperms353 probe set.
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关键词
ancient reticulation, Angiosperms353, asterids, coalescence, Cornales, gene flow, incomplete lineage sorting, phylogenomics, species tree estimation, target capture
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