Dna extraction

Docot, R. V. A., Banag, C. I., Tandang, D. N., Funakoshi, H. & Poulsen, A. D., 2019, Recircumscription and revision of the genus Vanoverberghia (Zingiberaceae), Blumea 64 (2), pp. 140-157 : 141-142

DNA extraction , amplification and sequencing

Total genomic DNA was extracted using DNeasy Plant Mini Kit (Qiagen ®, Germany) following the manufacturer’s protocol. Amplification of the ITS region was accomplished using ITS4 and ITS5 primers ( White et al. 1990) in 25 μL volumes and mix as follows: 15.8 μL of dH 2 O; 2.5 μL of 10 by PCR buffer; 2 μL of 25 mM MgCl 2; 2 μL of 10 mM dNTP; 1 μL each of 10 mM forward and reverse primers; 0.5 μL Kapa Taq (KAPA Biosystems ©); and 1 μL DNA . The thermal cycling profile for the ITS region was set under initial denaturation at 94 °C for 5 min, followed by 30 cycles of denaturation at 94 °C for 1 min, primer annealing at 55 °C for 1 min, and DNA strand extension at 72 °C for 1 min with a final extension of 10 min at 72 °C. The chloroplast trn K intron and mat K gene were amplified in short sections using primers from Leong-Škorničková et al. (2011: table 2) in 50 μL volumes and mix as follows: 24.25 μL of dH 2 O; 5 μL of 10 × PCR buffer; 5 μL of 25 mM MgCl 2; 4 μL of 10 mM dNTP; 0.5 μL of 0.1 mg /ml bovine serum albumin (BSA); 5 μL of 5 mM tertramethylammonium chloride (TMACl); 0.5 μL each of 10 mM forward and reverse primers; 0.25 μL Kapa Taq; and 5 μL of DNA . PCR thermal profile for the trn K/ mat K region was set under initial denaturation at 95 °C for 5 min, followed by 40 cycles of denaturation at 95 °C for 30 s, primer annealing from 50–60 °C for 40 s and DNA strand extension at 72 °C for 1 min with a final extension of 7 min at 72 °C. All PCR reactions were performed in Biometra T-Gradient thermocycler. PCR products were purified using QIA-quick Purification Kit (Qiagen ®, Germany) following manufacturer’s protocol and were sent to Macrogen © (Seoul, Korea) for sequencing.

Sequence assembly, alignment, and phylogenetic analyses A total of sixteen newly generated sequences (ITS = 8; trn K/ mat K = 8) was edited and assembled in Codon Code Aligner v. 4.1.1 (Codon-Code 2013). The sequences were then aligned, using Mesquite v. 3.04 ( Maddison & Maddison 2016), to sequence data from previous phylogenetic studies on Zingiberaceae downloaded from GenBank (see Table 1 for complete accession details of sequences). A total of 61 accessions from the ITS and 58 for the trn K/ mat K region (59 taxa) were used to construct the phylogenetic tree of the tribe Alpinieae with emphasis on the Alpinia eubractea clade. Genera with only one taxon in the analysis, including Aframomum K.Schum. , Amomum Roxb. , Etlingera Giseke , Geocharis (K.Schum.) Ridl. , Geostachys (Baker) Ridl. , Hornstedtia Retz. , Lanxangia M.F.Newman & Škorničk. , Leptosolena C.Presl , Plagiostachys Ridl. , Siliquamomum Baill. , Renealmia L.f. and Wurfbainia Giseke , were included to demonstrate generic boundaries inside the tribe Alpinieae . Moreover, six outgroups from the tribes Globbeae , Riedelieae , Siphonochiloideae, Tamijioideae and Zingiberoideae were included.

The phylogeny of the tribe Alpinieae was constructed using Maximum likelihood (ML) for bootstrap supports and Bayesian inference analysis (BI) for posterior probabilities. Modeltest v. 3.06 ( Posada & Crandall 1998) determined the most ap- propriate molecular model for each dataset. A general time reversible model (GTR+I+Γ) was used for both ITS and trn K/ mat K in ML and BI analysis. Maximum likelihood tree searches and bootstrapping of the combined data were obtained by running 1 000 replicates using RaxML-HPC2 v. 8.2.10 ( Stamatakis 2014), while BI analysis was carried out using MrBayes v. 3.2.6 ( Huelsenbeck & Ronquist 2001), both on the CIPRES portal ( Miller et al. 2010). For ML analysis, bootstrap values were categorised according to Kress et al.’s (2002) standard cut-off values. For BI analysis, data was partitioned in order to accommodate differing evolutionary rates for the respective datasets. Four Markov Chain Monte Carlo (MCMC) were performed for ten million generations with trees sampled every 1 000th generations. Values for Potential Scale Reduction Factor (PSRF) and standard deviation of the split frequencies between two runs were considered to confirm convergence.Additional convergence diagnostics was performed using Tracer v. 1.7.1 ( Rambaut et al. 2018) to check if each parameter had an effective sample size (ESS)> 100. Trees saved prior to convergence were discarded as burn-in (10 000 trees), creating a 50 % majority rule consensus tree constructed from the remaining trees.