Orthologous groups among nine arthropod genomes [i.e., Amphibalanus amphitrite (GCA_009805615.1), Daphnia pulex (GCA_900092285.2), Drosophila melanogaster (GCA_000001215.4), Lepas anserifera (this study), Parhyale hawaiensis (GCA_001587735.2), Penaeus vannamei (GCF_003789085.1), Portunus trituberculatus (GCA_008373055.1), Strigamia maritima (GCA_000239455.1), Tigriopus californicus (GCA_007210705.1)], and two barnacle transcriptomes [i.e., Semibalanus balanoides (GHBL00000000.1) and Pollicipes pollicipes (GGJN00000000.1)] and species tree were identified using OrthoFinder v2.2.7 (Emms and Kelly, 2015) with Diamond v0.9.24 BLASTp under “more-sensitive” mode, >50% identity and an E-value threshold of 1e-10 selected. All single-copy genes were aligned using MUSCLE v3.8.31 (Edgar, 2004) and trimmed using TrimAL v1.3 (Capella-Gutiérrez et al., 2009). The aligned sequences were concatenated and used for phylogenetic analyses. A maximum-likelihood method (ML) phylogenetic analysis was conducted using IQ-TREE v1.6.9 (Nguyen et al., 2014), with the best model of LG+F+G4 selected by ModelFinder (Kalyaanamoorthy et al., 2017) and 1000 bootstrapping replicates. A maximum parsimony (MP) analysis was conducted using PAUP4 (Swofford, 2001) with 1000 bootstrapping replicates. A Bayesian (BI) analysis was conducted using MrBayes v3.2.7 (Huelsenbeck and Ronquist, 2001) under the GTR+I+G model; four Markov chains were applied for 10 million generations, sampled every 1000 generations, and the first 25% discarded as the burn-in, respectively. MCMCtree implemented in PAML v4.8 (Yang, 2007) was used to estimate divergence times using the burn-in, sample frequency and number of samples as 10 million, 10,00 and 10,000, respectively. The node calibration among arthropods was based on the TIMETREE database (Hedges et al., 2006), i.e., 560–642 million year ago (MYA) for Arthropoda; 426–561 MYA for Pancrustacea; 467–494 MYA for Hexapoda. Based on the results of orthologous genes and estimated divergence times, gene family expansion and contraction were determined for each node using CAFÉ v4 (Han et al., 2013).
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