Data from: Phylogenetics support the description of a new Sichuanese species, Susanne’s Gentian, Gentiana susanneae (Gentianaceae)
Favre, Adrien; Pringle, James; Fu, Pengcheng (2022), Data from: Phylogenetics support the description of a new Sichuanese species, Susanne’s Gentian, Gentiana susanneae (Gentianaceae), Dryad, Dataset, https://doi.org/10.5061/dryad.xksn02vgj
The region of the Qinghai-Tibet Plateau hosts a remarkable biodiversity, including a plethora of endemics. There, the process of documenting biodiversity is still ongoing, and recently, an unusual plant of Gentiana section Frigida was discovered at Cuopu Lakes (Sichuan, China). Although Flora of China identified these specimens as G. algida based upon unmistakable traits (e.g. corolla colour and length, sessile flowers), it was obvious that the Sichuanese plants strongly differed morphologically from G. algida specimens from Siberia and North America. In order to clarify their relationships, we used an integrative approach, investigating not only morphological traits, but also phylogenetic relationships (based upon plastome and rDNA-cistron), as well as chloroplast structure. Whereas the rDNA-cistron phylogeny was poorly resolved, the plastome phylogeny was well supported in both Bayesian Inference and maximum likelihood analyses. Our findings indicate that the Cuopu Lakes samples of G. algida are morphologically and genetically distinct from those collected elsewhere, supporting the recognition of a new species, G. susanneae.
From the raw genomic data, we extracted the entire plastid genomes and rDNA cistron. We used Geneious Prime® 2019.0.4 (https://www.geneious.com) and mapped the reads to sequences of closely related species already available on GenBank (Favre et al. 2020). We aligned sequences in Geneious Prime using MAFFT v.7 (Katoh and Standley 2013), including a few sequences available on Genbank. We inspected the resulting alignments and edited them wherever necessary in Geneious Prime® 2019.0.4. Only few ambiguous positions had to be removed, particularly in non-coding regions.
The German Science Foundation, Award: FA1117/1-2