2.4 Phylogenetic analysis
Phylogenetic analysis is routinely applied to illustrate evolutionary and taxonomic questions. We carried out phylogenetic analysis for the new species and its affinitive species within the Triticeae based on three unlinked single-copy nuclear genes (Acc1 , plastid Acetyl-CoA carboxylase; DMC1 , disrupted meiotic cDNA;GBSSI , Granule-Bound Starch Synthase I) and three chloroplast regions [trn L-F, trn L (UAA)-trn F (GAA);mat K, maturase coding gene; rbc L, ribulose-1, 5-bisphosphate carboxylase/oxygenase]. Prior to phylogenetic analysis, The Acc1 , DMC1 , GBSSI , trn L-F, mat K, and rbc L sequences were amplified by polymerase chain reaction (PCR) using the primers listed in Table S2 under cycling conditions reported previously (Sha et al., 2016; Sha et al., 2017), and PCR products were cloned into the pMD18-T vector (TaKaRa, Dalian, China) following the manufacture’s instruction. At least 10 random independent clones were selected for commercially sequencing. For each gene fragment, in cases when multiple identical sequences resulted from cloned PCR products of each accession, only one sequence was included in the data matrix.
Multiple sequence alignment was conducted using ClustalX (Thompson et al., 1999), with default parameters and additional manual edits to minimize gaps. Phylogenetic analyses were conducted using Maximum likelihood (ML) and Bayesian inference (BI). ML analysis was performed using RAxML v8.2.8 under the GTR + GAMMA model on the XSEDE supercomputer at the CIPRES Science Gateway platform (Miller et al., 2010). Analyses included inference of the ‘best tree’ and generation of 1,000 bootstrap replicates to obtain node support measures. BI analysis was conducted with MrBayes v3.2.7a under the same evolutionary model and supercomputer platform (Miller et al., 2010) as ML analysis. Four MCMC (Markov Chain Monte Carlo) chains were run for 2,000,000 generations. Trees were sampled every 1,000 generation until reaching the convergence parameters (standard deviation less than 0.01). The first 25% of generated trees representing the burn-in phase were discarded, and the remaining trees were used to construct the 50%-majority rule consensus trees. The statistical confidence in nodes was evaluated by posterior probabilities (PP). PP-value less than 90% was not included in figures.