Computational protocol: Evolution of morphological and climatic adaptations in Veronica L. (Plantaginaceae)

Similar protocols

Protocol publication

[…] A total of 81 individuals representing 81 species and all 12 subgenera of Veronica, were used to establish the phylogenetic tree in this study. Of these, sequences from 67 species were downloaded from GenBank from previous studies (), whereas sequences from 14 species, which were collected in Xinjiang Province of China, were newly generated for this study (see ). Six individuals of five other genera of Veroniceae (Lagotis, Picrorhiza, Wulfeniopsis, Wulfenia, and Veronicastrum) were designated as outgroups. Genomic DNA extraction and purification was carried out using commercial kits according to manufacturer’s instructions (D2485-02, OMEGA bio-tek). In accordance with the methods of , we carried out PCR, sequencing and phylogenetic tree reconstruction. DNA sequences of four regions were PCR-amplified, including nuclear ribosomal internal transcribed spacer region (ITS) with primers ITSA () and ITS4 (), plastid DNA (cpDNA) trnL-trnL-trnF with primers c and f (), rps16 with primers rpsF and rpsR2 (), psbA-trnH with primers psbA () and trnH (). A PCR program of 95 °C for 2 min, 36 cycles of: 95 °C for 1 min, 50–55 °C for 1 min, and 72 °C for 1.5–2 min, and finally 72 °C for 5 min and 10 °C hold, was used for all markers. DNA sequencing was performed by Sangon Biotech Co., Ltd (Shanghai, PR China). Bayesian inference methods were used to analyze the combined data set. Best fitting substitution models for the datasets were inferred using jModelTest 2.1.7 (). The Bayesian inference tree was built using MrBayes 3.2.5 () with the GTR+Γ model using the Markov chain Monte Carlo (MCMC) for 1,000,000 generations with a burn-in of 250,000. The posterior probability (PP) was used to estimate nodal robustness. The stationarity of the runs was assessed using Tracer version 1.6 (). We approximated divergence times using the function chronopl in the R package “ape” ().We obtained morphological traits from field measurements and referenced from various flora, such as Flora of China (), Flora d’Italia (), Flora of New Zealand (), New Zealand Plant Conservation Network ( Plant traits were coded for each species according to characters and character states used by . In total 9 binary characters about resource acquisition and reproductive characteristics were taken into consideration (character states and scoring matrix were shown in and ).We obtained GPS latitude/longitude data from the GBIF website ( for up to 500 occurrence records for each species using the function occ in the R package “spocc” (). Invalid, low accuracy or duplicate data were removed. GPS data of species collected by us were also added to the analysis. Bioclimatic variables were obtained for each of the geographical coordinates from WorldClim ( and processed using ArcGIS version 10.0. Climate data from each locality was acquired using the toolbox function “Extract Values to Points” and average values for each bioclimatic variable was calculated for each species. Drought and heat can affect annual and perennial relative fitness (; ; ; ), and 7 related bioclimatic variables were selected for analysis (GBIF localities and corresponding climate data, average data were shown in and ).We used the function ace in the R package “ape” () to estimate ancestral character states and the associated uncertainty for life history. Additionally, we also calculated phylogenetic signal using the function phylo.d in the package “caper” (). The R package “iteRates” was used to implement the parametric rate comparison test and visualize areas on a tree undergoing differential substitution (). We have conducted phylogenetic comparative analysis. The function binaryPGLMM in the R package “ape” was used to perform comparative tests of morphological traits between annual and perennial plants. We tested climate data differences between annual and perennial plants using the function aov.phylo in the package “geiger” (). […]

Pipeline specifications

Software tools jModelTest, MrBayes, GEIGER
Application Phylogenetics