A mitochondrial genome phylogeny of owlet moths (Lepidoptera: Noctuoidea), and examination of the utility of mitochondrial genomes for lepidopteran phylogeneticsContents lists available at ScienceDirect
Molecular Phylogenetics and Evolution
A mitochondrial genome phylogeny of owlet moths (Lepidoptera: Noctuoidea), and examination of the utility of mitochondrial genomes for lepidopteran phylogenetics
http://dx.doi.org/10.1016/j.ympev.2015.02.005 1055-7903/ 2015 Elsevier Inc. All rights reserved.
⇑ Corresponding author. E-mail address: hanhx@ioz.ac.cn (H. Han).
1 These authors contributed equally to this work.
Xiushuai Yang a,1, Stephen L. Cameron b,1, David C. Lees c,1, Dayong Xue a, Hongxiang Han a,⇑ a Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China b Earth, Environmental & Biological Sciences School, Science & Engineering Faculty, Queensland University of Technology, GPO Box 2434, Brisbane, QLD 4001, Australia c Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, United Kingdom
a r t i c l e i n f o
Article history: Received 15 April 2014 Revised 27 January 2015 Accepted 6 February 2015 Available online 17 February 2015
Keywords: Noctuoidea Mitochondrial genome Phylogeny MAFFT Gblocks Gaps
a b s t r a c t
A phylogenetic hypothesis for the lepidopteran superfamily Noctuoidea was inferred based on the com- plete mitochondrial (mt) genomes of 12 species (six newly sequenced). The monophyly of each noctuoid family in the latest classification was well supported. Novel and robust relationships were recovered at the family level, in contrast to previous analyses using nuclear genes. Erebidae was recovered as sister to (Nolidae + (Euteliidae + Noctuidae)), while Notodontidae was sister to all these taxa (the putatively basalmost lineage Oenosandridae was not included). In order to improve phylogenetic resolution using mt genomes, various analytical approaches were tested: Bayesian inference (BI) vs. maximum likelihood (ML), excluding vs. including RNA genes (rRNA or tRNA), and Gblocks treatment. The evolutionary signal within mt genomes had low sensitivity to analytical changes. Inference methods had the most significant influence. Inclusion of tRNAs positively increased the congruence of topologies, while inclusion of rRNAs resulted in a range of phylogenetic relationships varying depending on other analytical factors. The two Gblocks parameter settings had opposite effects on nodal support between the two inference methods. The relaxed parameter (GBRA) resulted in higher support values in BI analyses, while the strict parameter (GBDH) resulted in higher support values in ML analyses.
2015 Elsevier Inc. All rights reserved.
1. Introduction
The application of molecular markers in phylogenetics has made a tremendous contribution to our knowledge of the evolu- tion of life on Earth (Delsuc et al., 2005; Wheat and Wahlberg, 2013). Inference of phylogenetic relationships within Lepidoptera (butterflies and moths), as well their macroevolutionary history (Wahlberg et al., 2013), have been greatly improved by a series of studies based on an ever-increasing numbers of molecular markers, largely nuclear protein-coding genes (PCGs) (Mutanen et al., 2010; Regier et al., 2013). For example, a comprehensive phy- logenetic study of Bombycoidea (silkworms and hawkmoths) based on a combination of up to 25 nuclear genes (19.3 kb total), the largest to date for a lepidopteran superfamily, found stronger nodal support for many more subclades (families and subfamilies) than either a parallel 5-gene analyses or previous studies (Regier
et al., 2008; Zwick et al., 2011). Surprisingly, the relationships of Bombycidae, Saturniidae, and Sphingidae are still contentious (e.g. Timmermans et al., 2014), although Breinholt and Kawahara (2013) found phylogenomic evidence for a sister relationship of the last two. The most recent transcriptomic analysis using 46 lepi- dopteran taxa recovered a novel placement of butterflies and established a preliminary framework to understand the evolution of butterflies and moths (Kawahara and Breinholt, 2014).
Noctuoidea is the biggest superfamily of Lepidoptera, number- ing over 42,400 species (Nieukerken et al., 2011). Many species are pests of considerable importance in agriculture and forestry, such as armyworms (Spodoptera spp.), bollworms (Helicoverpa spp.) and cutworms (Agrotis spp.) (Zhang, 1994). The superfamily also includes the tiger moths (Arctiinae), one of the more attractive groups of day-flying moths. The taxonomic history of Noctuoidea is complicated, but at present six families are recognized: Oenosan- dridae, Notodontidae, Erebidae, Euteliidae, Nolidae and Noctuidae (Nieukerken et al., 2011; Zahiri et al., 2011). Several other well- known noctuoid groups, including the Lymantriinae and Arctiinae, previously accorded family rank are now treated as erebid sub- families (Zahiri et al., 2012).
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Phylogenetic studies of Noctuoidea have followed the trend of increased reliance on molecular markers over morphological char- acters during the past few decades. The monophyly of Noctuoidea (sensu lato) is supported by the presence of a metathoracic tympa- nal organ, which is regarded as uniquely gained apomorphic char- acter (Miller, 1991). Speidel et al. (1996) conducted an analysis of 30 subfamilies based on 10 morphological characters and con- firmed the monophyly of Noctuidae, but found poor resolution among subordinate groups. Kitching et al. (1998) extended Speidel’s (1996) dataset with larval characters for resolving the monophyly of the families Arctiidae, Nolidae, Lymantriidae and Pantheidae, as well as their interrelationships. Lafontaine and Fibiger found further support for the respective monophyly of the ‘trifid’ noctuoids (Oenosandridae and Notodontidae, with an apparently 3-branching forewing cubital vein) and ‘quadrifids’ (with a 4-branching forewing cubital vein) based on adult and larval characters (Fig. 1B and C) (Fibiger and Lafontaine, 2005; Lafontaine and Fibiger, 2006). In their system, all quadrifid moths, including the families Arctiidae, Lymantriidae and Aganaidae, were redefined as subfamilies of Noctuidae, and therefore Noctuidae (sensu lato) became the largest (38,000 of 42,000 species) and most complex noctuoid family (48 subfamilies and 79 tribes).
Molecular studies of Noctuoidea were initially based on one or two genes, and limited taxon sampling (three families, 29–49 spe- cies) (Fang et al., 2000; Mitchell et al., 1997, 2000; Weller et al., 1994). Mitchell et al. (2000, 2006) initially conducted comprehen- sive systematic analysis of Noctuidae based on two nuclear genes and a wide range of taxon sampling. Besides finding strong support for the monophyly of its subfamilies, the ‘‘LAQ’’ clade was proposed for the first time. Lymantriidae and Arctiidae became subordinate subfamilies within the quadrifid noctuids (Fig. 1D). Mitchell’s research, in concert with that of Lafontaine and Fibiger (Fibiger and Lafontaine, 2005), has greatly clarified several hitherto elusive relationships within Noctuoidea. However, the support values above the subfamily level were low, possibly resulting from a sam- pling biased towards ‘trifine’ species (with an apparently 3-branch- ing hindwing cubital vein), with relatively few ‘quadrifines’ (with a 4-branching hindwing cubital vein), and/or a result of the limits of phylogenetic resolution from the two nuclear genes sequenced. Recently however, Zahiri et al. (2011) conducted the most exten- sive molecular phylogenetic analyses of Noctuoidea to date, based both on combined sequences of eight PCGs (nuclear and mitochon- drial) and on comprehensive sampling of 152 species, which cov- ered nearly all of the subfamilies recognized within Noctuoidea. Zahiri et al.’s (2011) results differed significantly from all previous studies, both morphological and molecular ones (Fig. 1E). The tra- ditional group of quadrifid noctuids was broken up, and the families Nolidae and Erebidae (the last family newly defined to encompass a still vast clade of some 18 subfamilies and about 24,500 species) were reconstituted and Euteliidae was newly rec- ognized (previously a noctuid subfamily) (Zahiri et al., 2012). In so doing, they proposed a novel six-family system that has current- ly been accepted within synoptic classifications of Lepidoptera (Nieukerken et al., 2011). While the datasets of Zahiri et al. (2011, 2012, 2013a,b) provide strong support for the monophyly of the six families and most of the subfamilies, nodal support for Erebidae + Nolidae and most inter-subfamily relationships was not significant. This is despite a sizeable molecular dataset (6407 bp) including most of the nuclear genes shown to be most effective at deep phylogenetic levels within Lepidoptera (Mutanen et al., 2010; Wahlberg et al., 2009a); further resolution of noctuoid relationships thus requires novel data sources. An additional outcome of Zahiri et al. (2011, 2012, 2013a,b) was that morphological and molecular studies were contradictory, with no morphological support for Erebidae. In practice, the Erebidae is impossible to recognize without comprehensive faunal knowledge
(Barbut and Lalanne-Cassou, 2011; Holloway, 2011). Although some potential autapomorphies were proposed in a recent study, such as the loss of a muscle in the male genitalia, none was indis- putable and they were absent in some subfamilies or some taxa (Minet et al., 2012). Despite rapid acceptance by a range of lepi- dopteran systematists, the higher-level phylogenetic relationships of Noctuoidea were once again potentially contentious.
Complete mitochondrial (mt) genomes have been increasingly used to address phylogenetic questions where multi-gene analyses have been either unresolved or poorly supported. They have been widely used in invertebrates in general and insects in particular (Cameron, 2014). Within Lepidoptera, multiple studies have used mt genomes to address relationships between superfamilies and within major families such as Nymphalidae (Tian et al., 2012; Yang et al., 2009). These studies have demonstrated significant and novel findings, including the first strong evidence for the non-monophyly of Macrolepidoptera, primarily due to an earlier diverging position of the butterflies (Papilionoidea) than tradition- ally thought (Yang et al., 2009), a position subsequently confirmed by analyses of nuclear PCGs (Mutanen et al., 2010; Regier et al., 2009). Most recently, a comprehensive phylogenetic study of Lepi- doptera was conducted using mt genomes of 106 species from 24 subfamilies (Timmermans et al., 2014). The topologies are highly congruent with prior nuclear and/or morphological studies.
Various analytical approaches using insect mt genomes to resolve phylogeny have been tested (Cameron, 2014); however, optimal approaches appear to vary between insect lineages. For example, the inclusion of third codon positions positively affected phylogenetic resolution in Orthoptera, Lepidoptera and Diptera (Cameron et al., 2007; Fenn et al., 2008; Yang et al., 2013), while the exclusion of third codon positions performed better in Dicty- optera and Hymenoptera (Cameron et al., 2012; Dowton et al., 2009). So reporting sensitivity tests for partitioning is of interest for different lineages and at different taxonomic scales. In this study, we present six new noctuoid mt genomes, including repre- sentatives of two newly sequenced families (Euteliidae and Noli- dae), and three additional erebid subfamilies. We conducted phylogenetic analyses of mt genomes from 57 lepidopteran taxa. Our aim was to address the infraordinal relationships within Lepi- doptera, particularly the family-level relationships within Noc- tuoidea and subfamily relationships within Erebidae (the largest noctuoid family) using mt genome data. In addition, we employ a range of analytical approaches to explore the phylogenetic utility of mt genomes.
2. Materials and methods
2.1. Samples and sequencing
Complete mt genomes were sequenced for six noctuoid species: Asota plana lacteata (Erebidae, Aganainae), Agylla virilis (Erebidae, Arctiinae), Catocala deuteronympha (Erebidae, Erebinae), Eutelia adulatricoides (Euteliidae, Euteliinae), Gabala argentata (Nolidae, Chloephorinae), and Risoba prominens (Nolidae, Risobinae). Three legs from each specimen were removed and preserved in 100% ethanol during collection. Legs were stored at 20 C until DNA extraction, and voucher specimens were deposited at the Museum of the Institute of Zoology, Chinese Academy of Sciences. Total genomic DNA was extracted from the leg muscle tissue with the DNeasy Blood and Tissue Kit (QIAGEN, USA). Mt genomes were amplified and sequenced as described in our previous study (Yang et al., 2013). Generally, primer walking was employed for long fragments; fragments containing the control region were cloned using TOPO TA Cloning Kit (Invitrogen, USA), and the resultant plasmid DNA was isolated using the TIANpure Midi Plas- mid Kit (Tiangen, China). The sequence data have been deposited in
Fig. 1. Previous hypotheses of phylogenetic relationships within Noctuoidea: (A) Speidel et al. (1996); note: Noctuidae in this study includes the quadrifine groups; (B) Fibiger and Lafontaine (2005); (C) Lafontaine and Fibiger (2006); (D) Mitchell et al. (2006); (E) Zahiri et al. (2011) and (F) Zahiri et al. (2013b). Family and subfamily names are as Zahiri et al. (2011). Terminals were changed from the original publication to track Zahiri et al. (2011) and allow easy comparison between studies.
232 X. Yang et al. / Molecular Phylogenetics and Evolution 85 (2015) 230–237
GenBank under accession numbers KJ173908 (A. plana lacteata), KJ185131 (E. adulatricoides), KJ396197 (R. prominens), KJ410747 (G. argentata), KJ364659 (A. virilis), and KJ432280 (C. deuteronympha).
2.2. Annotation and alignment
Sequence assembly and mt genome annotation followed our previous study (Yang et al., 2013). Alignments of individual genes were performed using MAFFT (Katoh et al., 2002). Q-INS-i, the RNA structural alignment method implemented in MAFFT, was explored for rRNA and tRNA alignments and PCGs were aligned with the default settings (Katoh and Toh, 2008). Three different datasets were generated to test the effect of data inclusion/exclusion on topology and nodal support: (1) 13PCG123, complete 13 PCGs (all RNA genes omitted); (2) 13PCG123tRNA, 13PCG123 + tRNA genes (rRNA genes omitted); (3) 13PCG123LRSR, 13PCG123 + rRNA genes (tRNA genes omitted).
In order to remove unreliably aligned regions within the data- sets, we used Gblocks (Castresana, 2000) to identify the conserved regions with the two following parameter settings: GBDH, default parameter settings except allowing gaps at a given position in up to half of the aligned species; GBRA, relaxed parameter settings (Minimum Number Of Sequence For A Conserved Position: mini- mum; Minimum Number Of Sequence For A Flank Position: mini- mum; Maximum Number Of Contiguous Nonconserved Positions: default; Minimum Length Of A Block: minimum; Allowed Gap Positions: all). Additionally, datasets analyzed without Gblocks treatments were adjusted manually to remove the non- homologous regions at the beginning and the end of each aligned gene.
2.3. Phylogenetic analyses
Each dataset was analyzed using two inference methods, Baye- sian inference (BI) and maximum likelihood (ML). Analyses were performed using MrBayes v 3.2.2 (Ronquist et al., 2012) and RAxML-HPC2 v 7.6.3 (Stamatakis, 2006) on XSEDE via the Cyberin- frastructure for Phylogenetic Research (CIPRES) Science gateway portal (Miller et al., 2010). Two rRNA, 22 tRNA genes and 13 PCGs were treated as 4 partitions, lrRNA, srRNA, a combined partition of the 22 tRNA genes, and a combined partition of 13 PCGs. Model
selection was via Akaike Information Criterion implemented in MrModeltest 2.3 (Nylander, 2004). For BI analyses, Ahamus yunna- nensis (Hepialidae) was selected as the outgroup (Lee et al., 2006). Four independent runs were conducted for 1,000,000 generations, and each was sampled every 1000 generations. Convergence was determined using Tracer ver. 1.5 (Rambaut and Drummond, 2007) and all analyses had converged within 1,000,000 gen- erations. Posterior probabilities over 0.95 were interpreted as strongly-supported (Erixon et al., 2003). For ML analyses, two Hepialidae species Ahamus yunnanensis and Thitarodes renzhiensis were selected as outgroups, and 1000 replicate bootstraps were conducted under GTRCAT. Nodes with a bootstrap percentage (BP) of at least 70% were considered well-supported in the ML ana- lyses (Hillis and Bull, 1993).
3. Results
3.1. Gene order and variation
The six noctuoid species were all completely sequenced, and all of them possessed the typical metazoan mt genome composition of 13 PCGs, 22 transfer RNAs, two ribosomal RNAs and a single A + T- rich region (putative control region) (Fig. 2) (Boore, 1999). The A + T rich regions of noctuoid species were routinely short with a range of 311–541 bp, as well as a high AT content of 90.6–96.1%. The mt gene order was identical to other noctuoid species previ- ously published, which possessed the gene rearrangement of tRNAMet found in many lepidopterans. This character, once sug- gested to be synapomorphic for Lepidoptera (Gong et al., 2012), has recently been found to be restricted to the more derived clade Ditrysia (Cao et al., 2012) and their close relatives Tischerioidea and Palaephatoidea (Timmermans et al., 2014).
3.2. Problematic mt genomes within the first dataset
A range of preliminary analyses were conducted using the six newly sequenced mt genomes in this study plus all complete mt genomes of Lepidoptera in GenBank (61 species by March 2013). However, some taxa were obviously misplaced in all analyses. For example, in no case was a monophyletic Hesperiidae (Ochlodes venata and Ctenoptilum vasava) recovered. Instead, all datasets
Fig. 2. Mt genome organization and mt genome sizes for the six newly sequenced noctuoid species.
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supported the grouping of O. venata and three Lycaenidae species (Fig. S1). Sequence blasting of the 50 COI of the O. venata mt genome published on GenBank does not closely match other sam- ples identified to this species or genus on BOLD (http://www. boldsystems.org) (Ratnasingham and Hebert, 2007). The monophyly of Hesperiidae is not in dispute (Heikkilä et al., 2012; Warren et al., 2008, 2009). Similarly, one of the lycaenid species (Celastrina hersilia) grouped with Papilionidae. BLAST identification of this sequence suggested it was from another genus (Cyaniris). The controversial placements of O. venata and C. hersilia need further investigation (see below) to determine whether they are caused by contamination during sequencing, or specimen misidentification.
Finally, we found that the divergence between two mt genomes of Parnassius bremeri (GenBank accession nos. HM243588 and NC_014053) reached 4.0%, which was quite unexpected for con- specific taxa. Further alignment analysis showed that the region from the tRNA cluster ARNSEF to lrRNA of NC_014053 was the most divergent region (8.2%), while the rest of the mt genome was only 0.5% divergent. Further blasting analysis showed that the divergent region of NC_014053 had 94% identity to C. hersilia, while only as much as 87% to other species of Papilionidae. This suggests that the sequence deposited on GenBank might be a chimera, due to a contig formed of long PCR resulting from more than one species.
In the preliminary analyses, most of the problems were within the unpublished data deposited in GenBank, so we conducted analyses (57 taxa) excluding the unpublished data in this study (Table S1). We recommend careful checking and revision before conducting the phylogenetic analyses with lepidopteran mt genomes from GenBank, especially those associated with unpub- lished studies.
3.3. Methodological effects of various approaches
Fourteen independent phylogenetic analyses were performed to test sensitivity to inference methods, data treatment approaches, and variable region exclusion with Gblocks. A total of eight different tree topologies were recovered (Figs. 3, S2 and S3). A brief summary of the datasets is displayed in Table 1.
The two inference methods (BI and ML) resulted in different tree topologies for the same dataset. The monophyly of Yponomeu- toidea was supported by all the BI analyses (although not sig- nificantly in 13PCG123maGBDH and 13PCG123LRSRmaGBDH) whereas as it was never significantly supported in the ML analyses and the superfamily did not emerge as monophyletic (Plutella xylostella was sister to Apoditrysia) in 13PCG123tRNAmaGBDH and 13PCG123LRSRmaGBDH. Relationships within Papilionoidea
also varied between inference methods. For the M13PCG123ma and 13PCG123tRNAGBRA datasets, Pieridae and Lycaenidae were recovered as a sister group (the B2-type relationship is presented in Fig. 3) in ML analyses, whereas BI analyses recovered Nym- phalidae and Lycaenidae (the B1-type relationship is presented in Fig. 3) as sister groups (these relationships, however, also vary between datasets for the same inference methods, see below, and note due to our cutoff for public sequences we did not include a recently published sequence for Lycaenidae’s widely considered sister group, Riodinidae). Relationships within families showed little sensitivity to inference method, however the relationships within Olethreutinae (Tortricidae) and the placement of Libythea celtis within Nymphalidae were divergent in the two inference methods, while the placement of Noctuidae within Noctuoidea was another example in BI analyses (Fig. 3).
For the different data treatments, we compared the effect of inclusion of rRNA or tRNA genes in combined analyses of PCGs + rRNA and PCGs + tRNA against PCGs alone. Inclusion of tRNA genes had no effect on tree topology and slight effect on nodal support when the datasets including third codon positions were analyzed using BI (13PCG123tRNAmaGBDH vs. 13PCG123maGBDH and 13PCG123tRNAmaGBRA vs. 13PCG123maGBRA). However, different relationships were recovered within Noctuoidea, Nym- phalidae and Tortricidae when rRNA genes were included (13PCG123LRSRmaGBDH and 13PCG123LRSRmaGBRA). In BI ana- lyses, Euteliidae and Nolidae were recovered as sister groups (the D2-type relationship is presented in Fig. 3) in 13PCG123LRSR- maGBDH and 13PCG123LRSRmaGBRA, while Noctuidae and Nolidae were recovered as a sister group (the D1-type relationship is pre- sented in Fig. 3) from the other datasets (PCGs + tRNA and PCGs alone). Diverse interfamily and intrafamily relationships were recovered across the different data treatments using ML analyses. The B2-type relationship (Lycaenidae + (Pieridae + Nymphalidae)) was recovered from PCGs + tRNA (13PCG123tRNAmaGBDH and 13PCG123tRNAmaGBRA), while the B1-type relationship ((Lycaenidae +Pieridae) + Nymphalidae) was recovered from PCGs + rRNA (13PCG123LRSRmaGBDH and 13PCG123LRSR- maGBRA). More diverse relationships were recovered within Nym- phalidae in ML analyses. 13PCG123tRNAmaGBDH recovered L. celtis to be the sister group of the remaining nymphalids (exclud- ing Euploea mulciber) (the C1-type relationship is presented in Fig. 3), while 13PCG123maGBDH and 13PCG123LRSRmaGBDH recovered L. celtis as the sister group of a clade consisting of Calinaga davidis plus Hipparchia autonoe (the C3-type relationship is presented in Fig. 3).
Using Gblocks with two different parameter settings appeared to have limited effect on phylogenetic reconstruction under the Bayesian framework. The only difference found was between PCGs
Fig. 3. Summary of different phylogenetic relationships recovered in this study. The entire tree was inferred from the Bayesian analysis of the 13PCG123maGBRA dataset, and different types of relationships recovered in the Bayesian and maximum likelihood analyses from the other datasets are displayed on the left.
Table 1 Brief summary of the datasets established from the mt genomes of 57 species.
Dataset name Dataset size (bp)
M13PCG123ma 11,263 13PCG123maGBDH 10,959 13PCG123maGBRA 11,258 13PCG123tRNAmaGBDH 12,159 13PCG123tRNAmaGBRA 12,947 13PCG123LRSRmaGBDH 12,558 13PCG123LRSRmaGBRA 13,604
Abbreviation and explanation: ‘M’, manually (manually adjusted the genes after alignment); ‘ma’, MAFFT (genes were aligned by MAFFT); ‘GBDH’, Gblocks masking with the strict parameter settings; ‘GBRA’, Gblocks masking with the relaxed parameter settings; ‘LR’, large subunit ribosomal RNA; ‘SR’, small subunit ribosomal RNA.
234 X. Yang et al. / Molecular Phylogenetics and Evolution 85 (2015) 230–237
and PCGs + tRNA. Datasets with the strict parameter settings (13PCG123maGBDH and 13PCG123tRNAmaGBDH) recovered the C2-type relationship within Nymphalidae (C. davidis plus H. auto- noe sister to all Nymphalidae except E. mulciber), while datasets with the relaxed parameter settings (13PCG123maGBRA and 13PCG123tRNAmaGBRA) recovered the C1-type relationship (see above). For the three PCGs datasets, the dataset generated by Gblocks with the relaxed parameter settings (13PCG123maGBRA) did not influence topology but generally increased nodal support values when compared with the dataset manually adjusted (M13PCG123ma). In ML analyses, Gblocks also had limited influ- ence among the three PCGs datasets. However, the PCGs dataset with the strict parameter settings of Gblocks (13PCG123maGBDH) inferred a tree with less weakly supported nodes than the one with the relaxed parameter settings (13PCG123maGBRA), and the same pattern was found for the other datasets (13PCG123tRNAmaGBDH
vs. 13PCG123tRNAmaGBRA and 13PCG123LRSRmaGBDH vs. 13PCG123LRSRmaGBRA). In addition, Gblocks treatments moder- ately affected topology when tRNA or rRNA genes were included. The strict parameter Gblocks (GBDH) ML analyses failed to recover the monophyly of Yponomeutoidea from PCGs + tRNA and PCGs + rRNA datasets (Fig. S3). These results indicate that ML analysis is more sensitive to gaps than BI analysis.
3.4. Phylogeny
Phylogenetic analyses were performed using 57 complete mt genomes, representing eight lepidopteran superfamilies. The monophyly of each superfamily was generally well supported, except for two ML analyses, in which Yponomeutoidea became paraphyletic, with Leucoptera malifoliella sister to Plutella xylostel- la + other six ingroup superfamilies. Relationships inferred at the superfamily level were highly consistent among all analyses. How- ever, we do not expect a robust phylogenetic relationship at the superfamily level due to only a small proportion of the lepidopter- an superfamilies being represented in this study. The monophyly of Yponomeutoidea is well supported after the removal of certain problematic taxa. Relationships within Bombycoidea, Geometroi- dea and Pyraloidea were almost identical to our previous study (Yang et al., 2013). Relationships within Olethreutinae (Tortricidae, Tortricoidea) were sensitive to different analytical approaches (Fig. 3, A1–A4). However, we found some novel relationships with- in Noctuoidea and Papilionoidea.
Novel relationships were found for the Noctuoidea families (Fig. 3) compared to previous molecular phylogenies of this super- family. The redefined family Noctuidae grouped with the recently recognized family Euteliidae. Noctuidae + Euteliidae was sister to the reconstituted family Nolidae, and the recently reconstituted
X. Yang et al. / Molecular Phylogenetics and Evolution 85 (2015) 230–237 235
family Erebidae was sister to the clade of (Nolidae + (Euteli- idae + Noctuidae)). Notodontidae was the sister group of the other four noctuoid families. Within Erebidae, only four subfamilies were analyzed, and their relationships were as follows: (Arctiinae + (Ere- binae + (Lymantriinae + Aganainae))). Phylogenetic relationships within Noctuoidea were consistent among most of the datasets except those including rRNA genes (13PCG123LRSRmaGBDH and 13PCG123LRSRmaGBRA) in BI analyses (Euteliidae was sister to Nolidae, the D2-type relationship Fig. 3), and received strong sup- port from all PCG123 datasets in the BI analyses and in most of ML analyses (Figs. 3 and S2).
In the present analyses, a total of 21 Papilionoidea species were included representing five families and 12 subfamilies. However, two controversial nodes within Papilionoidea that have been found in previous analyses of mt genomes still remained (Yang et al., 2013). In particular, the position of L. celtis was unstable with respect to Danainae (represented by E. mulciber) and Calinaginae + Satyrinae (represented by C. davidis and H. autonoe respectively), and three dif- ferent possible relationships were inferred (Fig. 3). The C1-type rela- tionship (Danainae + (Libytheinae + remaining Nymphalidae)) received the highest support from both BI and ML analyses. The other unstable relationships were among Pieridae, Lycaenidae and Nymphalidae. The B1-type, more morphologically intuitive relationship (Pieridae + (Lycaenidae + Nymphalidae)) was well sup- ported in most of the BI analyses (Fig. S2). However, in ML analyses, the B1-type relationship received strong support just in 13PCG123LRSRmaGBRA, and the B2-type relationship ((Pieridae + Lycaenidae) + Nymphalidae)) was well supported in three datasets (M13PCG123ma, 13PCG123maGBDH, and 13PCG123tRNA- maGBDH) (Fig. S3).
4. Discussion
4.1. Methodological effects of various approaches
In our previous study (Yang et al., 2013), we have tested the effect of inference and alignment methods on phylogenetic recon- struction, including or excluding the 3rd codon positions from PCGs. Those results showed that inference using BI and ML, align- ment using Muscle and MAFFT, and including third codon positions all performed better than maximum parsimony analysis, Clustal alignment and excluding third codon positions, respectively. The most recent research on Noctuidae based on COI and seven nuclear genes arrived at a similar conclusion that removing the third codon positions resulted in unstable phylogeny and weakened support values (Zahiri et al., 2013b). In the present study, we extended our exploration of mt genome phylogenetic utility by testing two inference methods (BI and ML), the inclusion of rRNA or tRNA genes and Gblocks removal of variable regions. Overall, lepidopter- an mt genomes have low sensitivity to these various analytical approaches, and thus are of high utility in resolving higher-level relationships between and within the lepidopteran superfamilies (Timmermans et al., 2014; Yang et al., 2013). We found that infer- ence method was the most significant factor, which is consistent with a previous study of neuropteridan mt genomes (Cameron et al., 2009). In all instances, BI analyses recovered a more consis- tent tree topology across different datasets, and nodal support was impressively high for the majority of nodes. However, it has been suggested in several recent studies that posterior probabilities are generally too liberal (Cummings et al., 2003; Simmons et al., 2004). Thus, caution should be used if BI analysis is solely applied. In contrast, ML analyses revealed many more topological differ- ences among varying datasets. Additionally, for none of the seven datasets was the same topology recovered between the two infer- ence methods. This is different from our previous study where the two inference methods recovered identical tree topologies for
some datasets, indicating that this incongruence is the result of more comprehensive taxon sampling. Therefore, it will be impor- tant to employ different inference methods to evaluate the phylo- genetic signal as ever larger taxon datasets are analyzed.
Whether to use gene or codon exclusion is an ongoing debate in relation to the accuracy of phylogenetic analyses using mt genomes. Our previous study indicated that it was not essential to exclude third codon positions in reconstructing lepidopteran phylogeny (Yang et al., 2013). In this study, we further tested the effect of gene exclusion by comparing the combined analyses of PCGs + rRNA/ tRNA with analyses of PCGs alone. rRNAs and tRNAs are often excluded in phylogenetic analyses of insects. However, analyses of dipteran mt genomes suggested including rRNAs and tRNAs improved resolution and nodal support (Cameron et al., 2007). Simi- lar conclusions were also obtained by other studies of Orthoptera and Neuropterida (Cameron et al., 2009; Fenn et al., 2008). In our analyses, the inclusion of tRNAs positively increased the congruence of topologies, indicating tRNAs contribute signal to phylogenetic analyses. By contrast, inclusion of rRNAs resulted in more diverse and poorly supported phylogenetic relationships compared with other datasets. Three candidate explanations might be responsible for noisy signals in rRNAs. First, rRNAs have long been a challenge to align accurately. Although incorporating structural information into alignment promises to improve the accuracy, this is difficult to apply for more distantly related taxa (Cameron et al., 2009). Another possible reason is that rRNA genes have much higher levels of homoplasy than either PCGs or tRNA genes (Cameron et al., 2007). A further reason is that compensatory substitutions in paired regions of RNA genes are not directly accounted for by the phyloge- netic inference methods unless explicitly modeled, such as the dou- blet model (Schöniger and Von Haeseler, 1994) used by Letsch et al. (2010). Therefore, substitutions at each site are assumed to be inde- pendent of one another possibly resulting in conflicting signal to the PCGs partition (Hudelot et al., 2003).
Gblocks was used to improve signal-to-noise ratio by removing highly variable regions, caused by poor alignment or inaccurately defined gene boundaries. For example, most CO1 genes in Lepi- doptera have been predicted to start with the nonstandard start codon-CGA, while others were predicted to start with the standard start codon-ATN (Fig. S4). Therefore, the relatively arbitrary defini- tion of a gene boundary might or might not include variable regions at the gene’s 50 end. Similar problems exist in many other genes, such as ND2, ND4, ND4L, and ND5. However, recent com- parative analyses suggest that removing variable regions has a negative impact on phylogenetic accuracy (Dessimoz and Gil, 2010). We employed two different parameter settings of Gblocks in our analyses. The results showed that the relaxed parameters, GBRA, resulted in variant relationships and poor support values in ML analyses, while the strict parameter, GBDH, had a beneficial effect, increasing nodal support. By contrast, the two parameter settings both resulted in more variable topologies and poorer nodal support in BI analyses. A similar conclusion was drawn by Dwivedi and Gadagkar (2009), and they suggested that the possible reason for the opposite effects was due to the different criteria for treating gaps as missing data in the different inference methods.
4.2. Phylogeny
The phylogeny and classification of Noctuoidea has experienced a chaotic history, changing rapidly with the implementation of molecular markers and the discovery of morphological synapo- morphies. The status of Noctuidae (sensu stricto), including all tri- fine noctuids and some ‘pseudoquadrifine’ noctuids, tends to be consistent with recent morphological and molecular researches (Fibiger and Lafontaine, 2005; Lafontaine and Fibiger, 2006; Mitchell et al., 2006; Zahiri et al., 2011, 2013b). Noctuoidea with
236 X. Yang et al. / Molecular Phylogenetics and Evolution 85 (2015) 230–237
a quadrifid forewing and a quadrifine hindwing, consisting of the most species-rich groups such as Lymantriinae and Arctiinae, are also the lineages most often subject to change between different classification schemes. In addition, various noctuoid classification schemes have not tended towards a consensus of relationships at family or subfamily levels. To date, the most comprehensive mole- cular phylogenetic analyses of Noctuoidea were conducted by Zahiri et al. (2011), from which a novel classification system for this giant superfamily was proposed. Support values for each of the six major clades were strong, although least so (0.96 posterior probability) for Erebidae, and monophyly of each erebid subfamily was moderately to strongly supported (Zahiri et al., 2011). Zahiri et al.’s (2011) family system was however well supported by our mitochondrial phylogeny, despite our limited taxon sampling. Novel and robust relationships were, however, recovered at both family and subfamily levels that are in conflict with Zahiri et al. (2011). In our analyses, the position of Notodontidae as sister to the remaining noctuoid families and the sister grouping of Noctu- idae plus Euteliidae were congruent with the ML analyses in Zahiri et al. (2011). In contrast, Nolidae was found to have a closer rela- tionship with the clade (Noctuidae + Euteliidae), rather than with Erebidae as suggested by the BI analyses of Zahiri et al. (2013b). A different relationship between Noctuidae and quadrifine noctu- ids was recovered in our BI analyses of datasets 13PCG123tRNA- maGBRA and 13PCG123LRSRmaGBRA, with Noctuidae recovered as the sister group to the clade (Euteliidae + Nolidae). In the pre- sent study, Arctiinae was recovered as the sister of the remaining erebid subfamilies, which is consistent with the recent analyses based on 19 nuclear PCGs in Regier et al. (2013). Interestingly, Aga- nainae and Lymantriinae were here grouped together for the first time, whereas Aganainae was found to have a closer relationship with Arctiinae in recent molecular and morphological studies (Figs. 1 and 3) (Fibiger and Lafontaine, 2005; Zahiri et al., 2012). Zahiri et al. (2011) proposed that trifine noctuids evolved from quad- rifines multiple times, due to hindwing vein reduction in some quad- rifines and the position of quadrifine species within some trifine subfamilies. This proposal is also supported by our mt genome phy- logenies as the trifine groups Arctiinae and Nolidae never formed a monophyletic group; however, the multiple origins of these wing venation patterns in Noctuidae still needs more research. These questions can probably be resolved by extending both taxon sam- pling (especially additional representatives of subfamilies/tribes within the massive groups Erebidae and Noctuidae families) and the number of molecular markers. The combination of mt genomes with nuclear genes (at least when a limited proportion of the nuclear genome or transcriptome is used) could be an effective way to refine the classification of noctuoid families and test the robustness of interfamily relationships. A stable and informative classification of Noctuoidea will ultimately help interpret and/or discover relevant morphological autapomorphies, especially for Erebidae and Nolidae.
Many previous studies have demonstrated great differences in phylogenetic signal between mitochondrial and nuclear genes (Lin and Danforth, 2004; Rubinoff and Holland, 2005; Shaw, 2002; Wahlberg et al., 2009b). However, the mitochondrial phy- logeny of Noctuoidea in the present study shows promising con- gruence with the previous, almost entirely nuclear PCG-based studies (Zahiri et al., 2011), suggesting that greater integration of nuclear and mt genomes will indeed lead to an improvement in our knowledge of insect evolution and phylogeny, although the importance of growing amounts of nuclear data (e.g. Kawahara and Breinholt, 2014) cannot be understated.
Acknowledgments
This study was supported by the grants from the National Nat- ural Science Foundation of China (Nos. 31272288, 31071952, and
31372176) and the Key Laboratory of the Zoological Systematics and Evolution of the Chinese Academy of Sciences (No. O529YX5105). David Lees was funded by ERC Grant #250325 (Bel- gium) during the writing of this study. Stephen Cameron was fund- ed by an Australian Research Council Future Fellowship (FT120100746).
Appendix A. Supplementary material
Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ympev.2015.02. 005.
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1 Introduction
3.2 Problematic mt genomes within the first dataset
3.3 Methodological effects of various approaches
3.4 Phylogeny
4 Discussion
4.2 Phylogeny