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Dryad

Data from: Phylogeny and evolutionary history of Pinaceae updated by transcriptomic analysis

Cite this dataset

Ran, Jin-Hua et al. (2018). Data from: Phylogeny and evolutionary history of Pinaceae updated by transcriptomic analysis [Dataset]. Dryad. https://doi.org/10.5061/dryad.q2s7q8m

Abstract

Pinaceae comprises 11 genera, and represents the largest family of conifers with an extensive wild distribution in the Northern Hemisphere. Intergeneric relationships of Pinaceae have been investigated using many morphological characters and molecular markers, but phylogenetic positions of four genera, including Cathaya, Cedrus, Nothotsuga and Pseudolarix, remain controversial or have not been completely resolved. To completely resolve the intergeneric relationships of Pinaceae, we conducted a comparative transcriptomic study of 14 species representing all Pinaceae genera. Multiple data sets, containing up to 6,369,681 sites across 4676 loci, were analyzed using concatenation and coalescent methods. Our study generated a robust topology, which divides Pinaceae into two clades, one (pinoid) including Cathaya, Larix, Picea, Pinus, and Pseudotsuga, and the other (abietoid) including Abies, Cedrus, Keteleeria, Nothotsuga, Pseudolarix, and Tsuga. Cathaya and Pinus form a clade sister to Picea; Cedrus is sister to the remaining abietoid genera, and the two genera Nothotsuga and Tsuga form a clade sister to Pseudolarix. The discordant positions of Cathaya, Cedrus and Pseudolarix in different gene trees could be explained by ancient radiation and/or molecular homoplastic evolution. The hybrid origin hypothesis of Nothotsuga is not supported. Based on molecular dating, extant Pinaceae genera diverged since about 206 Mya, earlier than the break-up of Pangea, and the divergence among the pinoid genera occurred earlier than the split among the abietoid genera. Moreover, our study indicates that two radiation events occurred in the evolution of Pinaceae genera, and some important morphological characters evolved multiple times based on ancestral state reconstruction.

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