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.