Comparative mitochondrial genomics unveils the phylogenetic relationships of lepidopteran moths

doi:10.21203/rs.3.rs-4611600/v1

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Comparative mitochondrial genomics unveils the phylogenetic relationships of lepidopteran moths

https://doi.org/10.21203/rs.3.rs-4611600/v1

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Background

Moths constitute the largest group within Lepidoptera and play a crucial role in natural ecosystems. However, the current high-level classification system of Lepidopteran insects necessitates systematic research supported by comprehensive data.

Results

In this study, we determined the complete mitochondrial genomes of 80 lepidopteran moth species, spanning 68 genera across 13 families. Through a synthesis of published data, we conducted a comparative analysis encompassing 211 moth species from 12 superfamilies. Our analysis unveiled a mitochondrial genome length range of 15,027 to 17,049 bp, with an AT content varying between 77.02% and 83.52%. While gene composition and arrangement were largely conserved, we observed tRNA rearrangement (trnS1-trnE inversion) in Zygaenidae and Gelechiidae families. Phylogenetic analyses highlighted the monophyly of 9 superfamilies, with exceptions for Tineoidea, Pyraloidea, and Drepanoidea. Divergence time estimations suggest an origin of the 12 Lepidopteran superfamilies in the mid-Cretaceous period, approximately 122.27 million years ago (95% CI: 102.43-153.23 Mya). Furthermore, we propose reclassifications to refine the taxonomic status of certain families. This includes reclassifying Gracillariidae and Thyrididae as independent from the Tineoidea and Pyraloidea superfamilies, respectively, and relocating the family Epicopeiidae to the Geometroidea superfamily from Drepanoidea.

Conclusion

We performed a comprehensive comparative analysis of mitochondrial genomes from 211 moth species. Using various tree-building methods and datasets, we reconstructed the higher-level phylogeny of moths across 12 superfamilies of Lepidoptera and further proposed taxonomic revisions for several groups. Our study significantly enriches the molecular dataset for moth systematics and offers new insights into the evolutionary history and phylogeny of Lepidoptera.

Lepidoptera

moths

mitochondrial genome

monophyly

phylogeny

Lepidoptera is the second largest order in the Insecta class, following Coleoptera. There are over 160,000 described species of Lepidoptera worldwide (Kawahara et al., 2014), primarily consisting of moths and butterflies, with moths accounting for about 90% of the species (Yan et al., 2022). The majority of Lepidopteran insects are either agricultural and forest pests or pollinators, representing a wide variety of species (Hu et al., 2010). They play significant roles in human activities and ecosystems, making them valuable subjects for research.

Species within the Lepidoptera are among the most widely distributed insects with rich species diversity, making them an ideal target for molecular systematics research. Currently, the Lepidoptera classification system is divided into four suborders based on adult wing venation and wing-lock systems: Glossata, Aglossata, Heterobathmiina, and Zeugloptera (van Nieukerken et al., 2011). This classification system is also adopted by the NCBI database. Among these, Ditrysia, a branch of the suborder Glossata, is the most significant subgroup of Lepidoptera (Minet, 1991; Kristensen, 1999). While most family-level clades within Ditrysia are accurately and widely accepted, the relationships between various higher-order taxa and the taxonomic status of specific species remain unclear and require further clarification.

Early phylogenetic studies of Lepidoptera were primarily based on morphological characteristics (Minet, 1986; 1991; Kristensen, 2003). Subsequently, molecular data analysis using multi-gene combinations has become increasingly mainstream. Notably, many studies have utilized mitochondrial genes for phylogenetic analysis (Hong et al., 2008; Regier et al., 2009; Li et al., 2010; Feng et al., 2010; Wang et al., 2019; Bao et al., 2020). Concurrently, the joint analysis of mitochondrial and nuclear genes has also become relatively common (Abraham et al., 2001; Mutanen et al., 2010; Wu et al., 2010; Wang et al., 2015; Rota et al., 2016; Kawahara et al., 2017). Furthermore, comprehensive analyses incorporating various datasets, including genomes, transcriptomes, and supplementary morphological data, have provided robust support for elucidating phylogenetic relationships in Lepidoptera (Cho et al., 2011; Regier et al., 2013, 2015; Bazinet et al., 2013; Kawahara et al., 2019).

Mitter et al. (2017) summarized the research progress on the systematic evolution of Lepidoptera since 1975. Their review encompasses 43 superfamilies and 133 families, revealing that Ditrysia is the most reliably defined branch within the Lepidoptera classification system. This group includes nearly 98% of Lepidoptera species, spanning 29 superfamilies. However, phylogenetic relationships at the superfamily level indicate that the monophyly of some superfamilies, such as Tineoidea, Choreutoidea, and Immoidea, remains uncertain. Additionally, research based on molecular data strongly supports the transfer of Epicopeiidae from the superfamily Drepanoidea to Drepanoidea (Bazinet et al., 2013; Regier et al., 2013). Despite this, there are inconsistencies in the genetic relationships among Bombycoidea, Geometroidea, and Noctuoidea, with different datasets yielding varying results (Cho et al., 2010; Mutanen et al., 2010; Bazinet et al., 2013; Regier et al., 2013, 2015; Kawahara et al., 2019; Yang et al., 2019). Therefore, within the suborder Ditrysia, the higher-level evolutionary relationships at the superfamily level require further investigation.

Estimating species divergence times is a critical area of research in biological systematics. It aids in understanding species divergence times and explores the influence of geological history on species evolution. The sparse fossil record of Lepidoptera presents a challenge to estimating accurate divergence times (Kristensen & Skalski, 1998; Sohn et al., 2012). The oldest recorded Lepidoptera fossil, found in the UK, dates back to the Early Jurassic, approximately 190 million years ago (Wang & Zhang, 2018). Misof et al. (2014) investigated insect phylogenetic relationships using 1478 protein-coding genes and suggested that Lepidoptera originated in the Early Cretaceous. Later, Kawahara et al. (2019) studied the evolutionary relationships of 186 Lepidoptera species using transcriptome and genome data, proposing that the earliest Lepidoptera appeared in the Late Carboniferous, around 300 million years ago, co-evolving with angiosperms. Additionally, Barber et al. (2022) examined the anti-bat ultrasound responses of 252 moth genera, providing further insights into the origins of eight subfamilies. These studies collectively offer reliable data resources for calibrating divergence times in Lepidoptera.

Mitochondrial genes, characterized by their simple structure and rapid evolution, are widely used in species identification, population genetics, systematics, and adaptive evolution studies. Advances in sequencing technology have made it easier and more cost-effective to obtain complete mitochondrial genome sequences, facilitating research at the whole mitochondrial genome level. Recently, there has been an increasing number of studies on higher-level phylogenetic relationships in insects using entire mitochondrial genomes (Cameron, 2014; Li et al., 2017; Bourguignon et al., 2018). For instance, Timmermans et al. (2014) reconstructed the phylogenetic relationships of 105 species across 24 superfamilies of Lepidoptera using complete mitochondrial genomes. Similarly, Yang et al. (2019) conducted a phylogenetic analysis of the group Macroheterocera, encompassing 41 species in 6 superfamilies within the Lepidoptera, and Du et al. (2019) constructed a phylogenetic tree for 50 species in 13 Lepidoptera families. However, current phylogenetic studies often involve a limited number of species with uneven distribution across taxa. The lack of comprehensive mitochondrial genome data has become a significant constraint. To better understand the phylogenetic relationships within Lepidoptera, it is essential to collect data from a broader range of species and across more comparative dimensions.

This study focuses on the primary group of lepidopteran moths, Ditrysia. By utilizing newly sequenced mitochondrial genome data and integrating it with existing published data, we conducted a comprehensive comparative mitochondrial genome analysis of representative moth species within Lepidoptera. We reconstructed the phylogeny of moths across 12 superfamilies of Lepidoptera using various tree-building methods. This research provides molecular evidence at the full mitochondrial genome level for the phylogenetic evolution of different lepidopteran moth groups and includes a divergence time analysis. Our study enhances the molecular resource data in moth systematics research and offers valuable insights for the evolution and phylogeny of Lepidoptera moth species.

Sequencing and assembly of mitochondrial genomes

Through species identification and sequencing assembly, we successfully obtained 80 circularized moth mitochondrial genomes, representing 68 genera in 13 families across 6 superfamilies (Table 1). Notably, this dataset includes representative species from Zygaenoidea (2) and Drepanoidea (1), thus enhancing the diversity of available genomic resources. Additionally, our dataset enriches the representation of 7 species each from Bombycoidea and Geometroidea, while significantly augmenting the data for 59 species within Noctuoidea. Of these genomes, 66 species were determined for the first time in this study, thereby expanding the available mitochondrial data resources for lepidopteran moths. All newly sequenced mitochondrial genomes consist of circular double-stranded DNA molecules, with lengths ranging from 15,192 to 16,397 bp and an AT content ranging from 78.92–82.07%. Each genome comprises a total of 37 genes, including 13 protein-coding genes, 22 tRNA genes, and 2 rRNA genes. For detailed information, please refer to Table 1.

Table 1

Information of mitochondrial genomes of 80 lepidopteran moths sequenced in this study
No.	Sample No.	Species	Superfamily	Date	Location	Length (bp)	AT (%)	Genbank
1	J23	Parasa consocia	Zygaenoidea	11/2020	Jilin Province	15548	80.79	OK149235.1
2	BZ119	Eterusia aedea	Zygaenoidea	06/04/2021	Yunnan Province	15192	79.59	MZ964410.1
3	BZ37	Lamoria adaptella^*	Pyraloidea	03/04/2021	Yunnan Province	15439	80.11	MZ853170.1
4	J21	Endotricha kuznetzovi^*	Pyraloidea	11/2020	Jilin Province	15244	80.75	OK149233.1
5	H8	Sitochroa verticalis^*	Pyraloidea	12/2020	Heilongjiang Province	15275	80.56	OK235314.1
6	QJ32	Pygospila tyres^*	Pyraloidea	11/2021	Yunnan Province	15287	81.33	ON939556.1
7	J22	Tethea albicostata^*	Drepanoidea	11/2020	Jilin Province	15308	80.53	OK149234.1
8	BZ1	Lyssa zampa	Geometroidea	03/04/2021	Yunnan Province	15571	81.74	MZ713634.1
9	BZ6	Amraica recursaria^*	Geometroidea	03/04/2021	Yunnan Province	15609	81.46	MZ713635.1
10	BZ8	Cleora fraterna^*	Geometroidea	03/04/2021	Yunnan Province	15513	79.66	MZ779035.1
11	BZ187	Chorodna fulgurita^*	Geometroidea	07/04/2021	Yunnan Province	15719	81.47	OK011998.1
12	J24	Biston regalis^*	Geometroidea	11/2020	Jilin Province	15532	80.76	OK149236.1
13	J33	Ophthalmitis albosignaria^*	Geometroidea	11/2020	Jilin Province	15569	81.48	OK235308.1
14	BZ42	Tanaorhinus viridiluteata^*	Geometroidea	03/04/2021	Yunnan Province	16397	81.69	MZ927090.1
15	BZ47	Trabala vishnou	Bombycoidea	03/04/2021	Yunnan Province	15282	80.76	MZ927091.1
16	JJC103	Theretra alecto^*	Bombycoidea	10/2020	Yunnan Province	15287	80.65	MZ562563.1
17	JJC105	Theretra clotho^*	Bombycoidea	10/2020	Yunnan Province	15318	80.96	MZ562564.1
18	J28	Theretra japonica	Bombycoidea	11/2020	Jilin Province	15393	80.37	OK149238.1
19	BZ46	Acosmeryx shervillii^*	Bombycoidea	03/04/2021	Yunnan Province	16349	81.44	OP310070.1
20	BZ181	Ambulyx liturata	Bombycoidea	07/04/2021	Yunnan Province	15361	81.22	OK011996.1
21	BZ188	Polyptychus trilineatus^*	Bombycoidea	07/04/2021	Yunnan Province	15289	80.93	OK011999.1
22	BZ11	Syntypistis chambae^*	Noctuoidea	03/04/2021	Yunnan Province	15938	81.32	MZ779034.1
23	J11	Neocerura liturata^*	Noctuoidea	11/2020	Jilin Province	15427	80.03	OK094456.1
24	J25	Pheosia rimosa^*	Noctuoidea	11/2020	Jilin Province	15510	79.46	OK149237.1
25	J30	Peridea elzet^*	Noctuoidea	11/2020	Jilin Province	15210	80.34	OK235306.1
26	JGJC48	Risoba prominens	Noctuoidea	10/2020	Yunnan Province	15345	81.06	MZ618262.1
27	BZ173	Eligma narcissus^*	Noctuoidea	07/04/2021	Yunnan Province	15346	80.86	OK011994.1
28	J13	Pseudoips prasinanus^*	Noctuoidea	11/2020	Jilin Province	15239	80.75	OK094458.1
29	BZ183	Carea varipes^*	Noctuoidea	07/04/2021	Yunnan Province	15318	80.4	ON939555.1
30	H4	Earias clorana^*	Noctuoidea	11/2020	Heilongjiang Province	15561	81.45	OK235312.1
31	JJC16	Helicoverpa assulta	Noctuoidea	10/2020	Yunnan Province	15410	80.96	MZ618264.1
32	J9	Pyrrhia umbra^*	Noctuoidea	11/2020	Jilin Province	15370	80.9	OK053112.1
33	JJC236	Condica illecta	Noctuoidea	10/2020	Yunnan Province	15364	80.98	MZ562566.1
34	JJC240	Condica capensis^*	Noctuoidea	10/2020	Yunnan Province	15312	80.96	MZ571410.1
35	JJC114	Spodoptera litura	Noctuoidea	10/2020	Yunnan Province	15382	81.08	MZ618263.1
36	J2	Spodoptera depravata^*	Noctuoidea	11/2020	Jilin Province	15460	81.61	OK053108.1
37	JJC17	Agrotis munda^*	Noctuoidea	10/2020	Yunnan Province	15402	81.27	MZ397914.1
38	BZ92	Agrotis ipsilon	Noctuoidea	04/04/2021	Yunnan Province	15379	81.24	MZ959071.1
39	H3	Agrotis trifurca^*	Noctuoidea	11/2020	Heilongjiang Province	15390	80.66	OK235311.1
40	JJC244	Athetis thoracica^*	Noctuoidea	10/2020	Yunnan Province	15364	81.32	MZ571409.1
41	H11	Abrostola triplasia^*	Noctuoidea	11/2020	Heilongjiang Province	15363	80.73	OK235316.1
42	J3	Mamestra brassicae^*	Noctuoidea	11/2020	Jilin Province	15342	81.2	OK053109.1
43	J35	Melanchra persicariae^*	Noctuoidea	11/2020	Jilin Province	15355	81.33	OK235309.1
44	BZ31	Mythimna loreyi	Noctuoidea	03/04/2021	Yunnan Province	15312	80.93	MZ853169.1
45	BZ140	Tiracola plagiata^*	Noctuoidea	06/04/2021	Yunnan Province	15377	79.96	MZ964414.1
46	BZ169	Tiracola aureata^*	Noctuoidea	06/04/2021	Yunnan Province	15384	80.2	OK011993.1
47	BZ28	Acronicta major^*	Noctuoidea	03/04/2021	Yunnan Province	15397	78.98	MZ853168.1
48	H5	Acronicta rumicis^*	Noctuoidea	11/2020	Heilongjiang Province	15388	80.62	OK235313.1
49	BZ184	Actinotia intermediata^*	Noctuoidea	07/04/2021	Yunnan Province	15352	81.47	OK011997.1
50	H9	Niphonyx segregata^*	Noctuoidea	11/2020	Heilongjiang Province	15322	80.37	OK235315.1
51	J31	Cosmia restituta^*	Noctuoidea	11/2020	Jilin Province	15408	80	OK235307.1
52	J29	Eucarta virgo^*	Noctuoidea	11/2020	Jilin Province	15435	82.07	OK235305.1
53	J14	Sphragifera sigillata^*	Noctuoidea	11/2020	Jilin Province	15368	81.55	OK149231.1
54	JJC254	Xanthodes intersepta^*	Noctuoidea	10/2020	Yunnan Province	15366	81.59	MZ571408.1
55	BZ53	Amerila alberti^*	Noctuoidea	04/04/2021	Yunnan Province	15503	80.61	MZ927092.1
56	JJC23	Nyctemera adversata^*	Noctuoidea	10/2020	Yunnan Province	15429	79.21	MZ562560.1
57	JJC116	Pareuchaetes insulata^*	Noctuoidea	06/04/2021	Yunnan Province	15299	80.62	MZ964412.1
58	J12	Phragmatobia fuliginosa^*	Noctuoidea	11/2020	Jilin Province	15469	80.98	OK094457.1
59	BZ77	Spilarctia casigneta^*	Noctuoidea	04/04/2021	Yunnan Province	15402	80.38	MZ959068.1
60	BZ63	Artena dotata^*	Noctuoidea	04/04/2021	Yunnan Province	15629	80.71	MZ944875.1
61	BZ96	Chilkasa falcata^*	Noctuoidea	04/04/2021	Yunnan Province	15603	81.02	MZ959073.1
62	BZ139	Chrysopera combinans^*	Noctuoidea	06/04/2021	Yunnan Province	15815	81.2	MZ964413.1
63	BZ84	Daddala lucilla^*	Noctuoidea	04/04/2021	Yunnan Province	15643	80.77	MZ959069.1
64	BZ3	Daddala brevicauda^*	Noctuoidea	03/04/2021	Yunnan Province	15642	81.26	ON109239.1
65	BZ116	Erebus caprimulgus^*	Noctuoidea	06/04/2021	Yunnan Province	15958	81.09	MZ959074.1
66	J16	Mocis ancilla^*	Noctuoidea	11/2020	Jilin Province	15726	81.09	OK149232.1
67	BZ93	Parallelia stuposa	Noctuoidea	04/04/2021	Yunnan Province	15682	80.37	MZ959072.1
68	BZ16	Thyas honesta^*	Noctuoidea	03/04/2021	Yunnan Province	15582	81.89	MZ779036.1
69	BZ59	Calyptra minuticornis^*	Noctuoidea	04/04/2021	Yunnan Province	15931	81.85	MZ944874.1
70	BZ87	Dysgonia illibata^*	Noctuoidea	04/04/2021	Yunnan Province	15917	80.47	ON109240.1
71	BZ117	Bastilla crameri^*	Noctuoidea	04/04/2021	Yunnan Province	15655	80.17	ON109241.1
72	BZ191	Lacera procellosa^*	Noctuoidea	07/04/2021	Yunnan Province	15754	81.48	ON109242.1
73	BZ7	Asota caricae^*	Noctuoidea	03/04/2021	Yunnan Province	15409	80.26	MZ779033.1
74	BZ56	Asota plana plana	Noctuoidea	04/04/2021	Yunnan Province	15421	80.28	MZ927093.1
75	BZ75	Asota paliura^*	Noctuoidea	04/04/2021	Yunnan Province	15399	80.16	MZ944876.1
76	H1	Simplicia niphona^*	Noctuoidea	11/2020	Heilongjiang Province	15552	81.08	OK235310.1
77	J4	Simplicia rectalis^*	Noctuoidea	11/2020	Jilin Province	15546	81.04	OK053110.1
78	BZ175	Anomis mesogona^*	Noctuoidea	07/04/2021	Yunnan Province	15626	81.16	OK011995.1
79	BZ26	Pida apicalis^*	Noctuoidea	03/04/2021	Yunnan Province	15618	80.47	ON109243.1
80	BZ86	Arcte coerula^*	Noctuoidea	04/04/2021	Yunnan Province	15266	78.92	MZ959070.1
^* indicates species for which the mitogenome is being published for the first time in this study.

Comparative mitochondrial genomes

By combining representative publicly available mitochondrial genomes with newly determined data from this study, we conducted a comparative analysis of mitochondrial genomes across 211 moth species (Table S1). Our results revealed a mitochondrial genome length ranging from 15,027 to 17,049 bp, with variations primarily observed in the intergenic spacer region between 12s rRNA and trnM. This region, characterized by A + T enrichment, also encompasses the mitochondrial genome control region, which exhibited lengths ranging from 160 to 1,397 bp. Furthermore, we identified two relatively conserved overlapping regions within the mitochondrial genome. The first overlaps 7 bases (ATGATAA) between the atp8 and atp6 genes, while the second overlaps 8 bases (AAGCCTTA) between the trnW and trnC genes. Notably, these two overlapping regions were highly prevalent, with proportions reaching 98.1% and 93.4%, respectively, among the 211 species.

The mitochondrial genomes of the 211 moth species analyzed in this study are characterized as double-stranded circular DNA molecules, featuring a total of 37 genes. The gene order is highly conserved across all species, with one notable exception observed in four species belonging to the Zygaenidae and Gelechiidae families (Fig. 1). In these species, a tRNA rearrangement is present, specifically an inversion located in the region containing six tandem tRNAs between the nad3 and nad5 genes. This rearrangement manifests as the inversion of trnS1-trnE, altering the sequence from trnA-trnR-trnN-trnS1-trnE-trnF to trnA-trnR-trnN-trnE-trnS1-trnF. Aside from this inversion event, all other genes maintain an identical arrangement across species.

Among the start codons of the 13 mitochondrial protein-coding genes, ATG is the most frequently used, accounting for 47.80%, followed by ATT at 26.39%. ATA and ATC are less common, comprising 13.34% and 4.78% respectively, while the cox1 gene predominantly initiates with CGA (Figure S1). Regarding stop codons, TAA is the most prevalent, utilized in 72.26% of cases, followed by T (24.79%) and TAG (2.95%). There is a discernible distribution pattern of start and stop codons across different moth groups. For instance, species within the Pyraloidea and Noctuoidea superfamilies show a preference for retaining ATT as the start codon in the cox2 gene, while moths belonging to the Noctuoidea superfamily tend to retain the incomplete T as the stop codon in the nad3 gene. Within the superfamily Noctuoidea, the cox3 gene in Nolidae and the cytb gene in Notodontidae tend to use ATA as the start codon (Fig. 2a). The cox1 genes in Erebidae and Nolidae often use TAG instead of T as the stop codon. Similarly, the nad4 gene in Notodontidae and the nad5 gene in both Euteliidae and Noctuidae tend to avoid using T as the stop codon (Fig. 2b).

The lengths of the 13 protein-coding genes vary among different species. Changes in the number of tandem repeats of triplet codons are a common form of length variation in the coding sequence (CDS) region within the mitochondrial genome (Figure S2). Such variations are widespread across different genes, including atp6, atp8, nad2, nad5, nad6, cox2, and cytb. Through the calculation of evolutionary rates (dN/dS) of these 13 protein-coding genes, it was observed that the atp8 gene exhibits the fastest evolutionary rate (Figure S3). Conversely, the cox1-3 genes demonstrate a relatively slow evolutionary rate, accompanied by a low proportion of non-synonymous mutation sites. This suggests that these three genes may be subject to strong natural selection pressure.

Phylogeny and monophyly inferred from mitochondrial genomes

The heterogeneity analysis revealed low compositional heterogeneity in both the 13 protein-coding genes and the complete mitochondrial sequence datasets, indicating their suitability for constructing phylogenetic trees (Figure S4-S5). The Maximum Likelihood (ML) tree based on the mitochondrial whole-genome sequence dataset effectively grouped the 211 species into distinct branches corresponding to their respective superfamilies, with each branch receiving high support values (Fig. 3; Figure S6). At the superfamily level, our study confirmed the monophyly of 9 superfamilies, excluding Tineoidea, Pyraloidea, and Drepanoidea. Additionally, we determined the monophyly of 33 families at the family level, with the exception of Oecophoridae, which was not found to be monophyletic.

Comparing the phylogenetic trees obtained from different datasets using ML and Bayesian Inference (BI) methods, the topological relationship of (Bombycoidea + (Geometroidea + Noctuoidea)) is consistently supported by four evolutionary trees (Figure S7-S10). Similarly, the sister group relationship between the moth family Gracillariidae and the superfamily Yponomeutoidea is also consistently supported across four results. Additionally, Epicopeiidae consistently appear nested within the clade Geometroidea, although their exact position within this clade may vary slightly across the four trees. However, while the ML tree results suggest that Copromorphoidea and Tortricoidea are sister groups (Figure S7-S8), the BI tree indicates that Copromorphoidea and Thyrididae share a sister group relationship (Figure S9-S10). Overall, the BI results exhibit multiple instances of paraphyly, whereas the ML results do not show paraphyly.

Overall, the topological structures of evolutionary trees based on different datasets and methods exhibit general consistency (Figure S7-S10). For the three superfamilies that are not monophyletic, Tineoidea appears at the base of the evolutionary tree, dividing into multiple clades. Notably, the family Gracillariidae consistently clusters with the superfamily Yponomeutoidea, indicating the independence of Gracillariidae from Yponomeutoidea. Similarly, within the superfamily Pyraloidea, Thyrididae consistently forms a separate branch from Crambidae and Pyralidae, either grouping with Gelechioidea (in ML trees) or Copromorphoidea (in BI trees), suggesting the independence of Thyrididae from Pyraloidea. Lastly, the superfamily Drepanoidea consistently divides into two distinct branches, Drepanidae and Epicopeiidae, with Epicopeiidae showing closer affinity to Geometroidea. Therefore, it is recommended to reclassify the family Epicopeiidae from Drepanoidea to Geometroidea.

Furthermore, this study suggests revising the taxonomic status of Arcte coerula from Erebidae to Noctuidae. The results from various evolutionary trees consistently group A. coerula within the internal branch of Noctuidae, supported by its morphological characteristics aligning with those of Noctuidae species. Additionally, both ML and BI trees, based on different datasets, place Pida apicalis within the Lymantriinae branch of the Erebidae subfamily. Therefore, it is proposed to establish the subfamily classification status of P. apicalis as Lymantriinae (Figure S7-S10), which was previously unspecified.

Divergence time estimation

The divergence time estimation analysis suggests that the Lepidopteran moths across the 12 superfamilies originated in the mid-Cretaceous, around 122.27 million years ago (95% CI: 102.43-153.23 Mya). With the exception of the Tortricoidea superfamily, the divergence of the other 11 superfamilies occurred during the middle and late Cretaceous period, predating the third mass extinction event (K-Pg crisis) approximately 70 million years ago (Fig. 4; Figure S11). Notably, the superfamily Noctuoidea, containing many important agricultural and forestry pests, diverged around 74.01 Mya (95% CI: 65.4-79.56 Mya). Additionally, the Gracillariidae and Yponomeutoidea originated approximately 102.5 Mya (95% CI: 88.4-113.96 Mya), while the Thyrididae and Gelechioidea diverged around 84.95 Mya (95% CI: 73.74–93.66 Mya). Lastly, the common ancestor of Epicopeiidae and Geometroidea originated approximately 76.09 Mya (95% CI: 66.91–81.76 Mya).

The current study employed high-throughput sequencing to obtain complete mitochondrial genome sequences from 80 species of Lepidopteran moths, greatly contributing to the systematic evolutionary analysis of Lepidoptera. Typically, the genome size of these moths ranges from 300 to 1500 Mb. Each species was sequenced at approximately 15 Gb, providing coverage of the entire genome at 10 to 50×. Evaluation of mitochondrial assembly integrity showed coverage depths between 450 and 5866×, confirming the suitability of the 15 Gb data for precise extraction and circularization of the mitochondrial genome.

The gene order within insect mitochondrial genomes is typically highly conserved, with previous studies primarily focusing on tRNA rearrangements. A frequently observed rearrangement region in Lepidopteran species involves the gene cluster trnA-trnR-trnN-trnS1-trnE-trnF (Timmermans et al., 2014; Park et al., 2016), encompassing events such as trnE-trnS1 ectopy, trnR duplication, and trnE deletion (Timmermans et al., 2014; Kim et al., 2017; Zhou et al., 2020; Chen et al., 2022). In this study, the identified trnS1-trnE inversion also occurs within this gene cluster, precisely within a region with opposite transcriptional direction, suggesting it may represent a hypervariable zone of the mitochondrial genome. Furthermore, our analysis reveals that all three species of Zygaenidae (E. aedea, H. rhodope, and P. atratus) exhibit the trnS1-trnE inversion, indicating that this inversion likely predates the divergence of Zygaenidae species. Conversely, among the four species of Gelechiidae studied, only M. albilinella displays this inversion, suggesting it occurred after the divergence of Gelechiidae species.

The protein-coding genes within mitochondrial genomes are typically highly conserved. In our study, all 13 protein-coding genes across all species lacked introns, and any length variation observed primarily occurred through the insertion or deletion of triplet codons, thus avoiding frameshift mutations. Moreover, variations in the number of tandem repeats of triplet codons emerged as the primary mechanism driving length variation in these protein-coding genes. Similarly, the tandem duplication or deletion of short segments represented a common mode of length variation in non-coding regions of the mitochondrial genome, such as tRNA genes. Notably, these variations are also frequently observed in lower plants, including algae (Zhang et al., 2015).

The high-level phylogenetic analysis conducted in this study confirms the monophyly of nine superfamilies, including Yponomeutoidea, Tortricoidea, Zygaenoidea, Cossoidea, Gelechioidea, Bombycoidea, Geometroidea, and Noctuoidea, which aligns with findings from previous research (Li et al., 2010; Mitter et al., 2017; Kawahara er al., 2019). However, due to the limited number of samples, the positioning of Copromorphoidea within the tree varied depending on the construction method used. Specifically, results from both ML and BI methods suggested different relationships for Copromorphoidea: ML placed it closely related to Tortricoidea, whereas BI linked it with Gelechioidea. Given the uncertainty surrounding the taxonomic status of Copromorphoidea based on previous morphological and molecular data, further research with an expanded sample size from this superfamily is warranted to achieve a more comprehensive understanding of its phylogenetic relationships.

The findings of this study, derived from mitochondrial genome data, strongly support the proposed topological arrangement of (Bombycoidea + (Geometroidea + Noctuoidea)). However, previous analyses based on nuclear genomic data presented a different evolutionary relationship, suggesting (Geometroidea + (Noctuoidea + Bombycoidea)) (Cho et al., 2011; Regier et al., 2013). Additionally, the ML tree resulting from joint transcriptome and nuclear genome data analysis displayed the configuration: (Noctuoidea + (Geometroidea + Bombycoidea)) (Bazinet et al., 2013; Kawahara et al., 2019). A comprehensive comparison of these various research outcomes reveals discrepancies in the phylogenetic relationships among lepidopteran moths, potentially attributed to differing mutation rates across mitochondrial genes, transcriptomes, and nuclear genes. Nonetheless, the results of this study offer insights into the higher-level phylogenetic relationships among lepidopteran moths, as evidenced by mitochondrial whole-genome data analysis.

The monophyly of the superfamily Tineoidea has faced challenges in previous research (Bazinet et al., 2013; Regier et al., 2015), particularly concerning the taxonomic status of the family Gracillariidae within this superfamily. Stainton (1854) initially proposed the taxonomic classification of Gracillariidae, elevating it to superfamily status (Scoble, 1992). However, in 1996, Gracillariidae was reassigned from Microlepidoptera to Tineoidea (Nielsen & Rangsi, 1996). The current study's findings strongly support the affinity between Gracillariidae and Yponomeutoidea as sister groups (Regier et al., 2013), a conclusion corroborated by prior nuclear genome phylogenetic analyses (van Nieukerken et al., 2011; Mitter et al., 2017). The recognition of Gracillarioidea as a superfamily in prior studies lends additional support to our proposal to separate Gracillariidae from Tineoidea and reclassify it within Gracillarioidea.

There have long been divergent views on the taxonomic classification of Thyrididae. Initially proposed by Herrich-Schäffer (1845), Thyrididae was later placed within the superfamily Pyraloidea based on morphological traits (Common, 1970; Whalley, 1976). However, the taxon Thyridoidea has been used in most studies (van Nieukerken et al., 2011; Heikkilä et al., 2015; Leley, 2016; Santos et al., 2021). The findings of our current study strongly uphold the monophyly of Thyrididae, distinguishing it significantly from other groups within Pyraloidea. This aligns with previous research based on mitochondrial or nuclear genome data (Mutanen et al., 2010; Timmermans et al., 2014; Heikkilä et al., 2015). Therefore, our study advocates for separating Thyrididae from the superfamily Pyraloidea and relocating it to the superfamily Thyridoidea.

Migration plays important role in the survival and reproduction of insects, facilitating the spread of many alien species. In our study, all 80 newly identified moth species were collected within China. Remarkably, six of these species, S. chambae, C. capensis, A. munda, A. alberti, P. insulata, and C. falcata, had not previously been recorded in China. These specimens were collected in Jiangcheng County, Pu'er City, Yunnan Province, using light trapping methods. Situated in the border region between China, Vietnam, and Laos, this area serves as a potential entry point for migratory species. Thus, it is plausible that these six moth species entered China through migration, highlighting their status as potential alien species.

In summary, this study contributes to the resource of mitochondrial genome data available for moth phylogeny. However, it's important to note that the sample coverage across taxa is not uniform, with significant variation in the number of species, particularly in superfamilies such as Copromorphoidea and Tineoidea, where samples are relatively scarce. Additionally, our focus on comparative analysis at the mitochondrial genome level means that suggestions for revising the existing classification system are primarily informed by molecular data. Moving forward, the inclusion of more morphological data is anticipated. Integrating biological characteristics with whole-genome data will offer more robust evidence for understanding the evolution and phylogeny of lepidopteran moth species across different taxonomic levels.

In this study, we have significantly expanded the molecular resources for the systematic study of Lepidoptera by determining the complete mitochondrial genomes of 80 moth species. Our comprehensive analysis offers a detailed view of mitochondrial genome characteristics and phylogenetic relationships within 12 superfamilies. Our phylogenetic analyses confirmed the monophyly of nine superfamilies, with divergence time estimates placing the origin of these 12 superfamilies in the mid-Cretaceous. Importantly, our findings support several taxonomic revisions, including the reclassification of Gracillariidae, Thyrididae, and Epicopeiidae. These proposed changes aim to refine the understanding of evolutionary relationships within Lepidoptera.

Moth collection and identification

Adult moths in this study were collected using high-altitude light traps at night between 2020 and 2021. The collection locations in China included Changchun City, Jilin Province (43°48ʹ38ʺN, 125°24ʹ14″E), Harbin City, Heilongjiang Province (45°39ʹ10ʺN, 126°24ʹ42ʺE), and Pu'er City, Yunnan Province (22°34ʹ31ʺN, 101°51ʹ31ʺE). The collected samples were individually placed into 1.5 mL or 5 mL centrifuge tubes and stored at -20°C. DNA was extracted from one leg of each sample, and COI markers were used for molecular identification via PCR and Sanger sequencing. Each sample underwent species identification using both morphological characteristics and molecular markers. For sample details, see Table 1.

DNA extraction and sequencing

For samples that could be accurately identified at the species level, the head of each moth was used to extract whole genome DNA using a DNeasy Blood and Tissue Kit (Cat. no.69506; Qiagen, Hilden, Gemany). The purity and concentration of the DNA were then assessed using a NanoDrop One UV-Vis spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). A total of 0.5 µg of genomic DNA from each sample was used to construct a library with a 350 bp insert size. The library was sequenced on the NovaSeq 6000 platform (lllumina, San Diego, CA,USA) with 150 bp paired-end reads, generating a sequencing data volume of 15 Gb per sample.

Mito-genome assembly and annotation

The clean sequencing data were assembled using NOVOPlasty v2.5.6 software (Dierckxsens et al., 2017), with the COI fragment from earlier molecular identification of the same sample used as a seed file. Various kmer values were set to obtain the circularized mitochondrial genome sequence, which was then manually corrected. Gene annotation was performed online using MITOS2 software (http://mitos2.bioinf.uni-leipzig.de/index.py) (Donath et al., 2019). The start codons and stop codons of protein-coding genes were verified manually. All sequence and annotation files were submitted to the NCBI database.

Comparative mitochondrial genome analysis

The total length comparison of the mitochondrial genome sequences, AT content, and codon statistics were conducted using MEGA11.0 software (Tamura et al., 2021). Sequence alignment was performed by separately aligning genes and intergenic regions with MAFFT 7.505 (Katoh & Standley, 2013), followed by concatenation using MEGA11.0. The gene evolutionary rate was also calculated with MEGA11.0 software. Each protein-coding gene was individually analyzed to calculate the dN/dS value, allowing for the comparison of evolutionary rates across different genes.

Phylogenetic analysis

The datasets utilized for phylogenetic analysis in this study encompass two types: 1) Mitochondrial whole-genome data, with the removal of the AT-rich intergenic spacer region between 12s rRNA and trnM, resulting in a total sequence alignment length of 22,028 bp; 2) Nucleic acid sequences of the 13 protein-coding genes, with a total length of 12,077 bp. Before conducting phylogenetic analysis, heterogeneity analysis of the different datasets was evaluated using AliGROOVE software (Kück et al., 2014).

The maximum likelihood method (ML) and the Bayesian method (BI) were employed for phylogenetic analysis using two distinct datasets. Three species from the Exopore order of Lepidoptera were chosen as outgroups. The ML evolutionary tree was constructed using IQ-TREE v1.6.10 software (Nguyen et al., 2015), with the Akaike Information Criterion (AIC) used to determine the best-fitting model (GTR + F + I + G4). Bootstrap resampling was conducted with 500 tests to evaluate each branch point. Bayesian analysis was performed using PhyloBayes MPI 1.4f (Lartillot et al., 2013), employing the CAT + GTR heterogeneous mixed model. Three Markov (MCMC) chains were run independently for over 10,000 generations, halting when the maxdiff value fell below 0.3. Trees were stored every 1000 generations, with the first 20% discarded using the burn-in parameter, followed by computation of the unified tree. The ML and BI phylogenetic trees obtained were visualized using iTol v6.5.2 online software (https://itol.embl.de/).

Divergence time estimation

Based on the ML tree topology generated from 13 protein-coding genes, we used MCMCTREE in the PAML4.9 software package for divergence time estimation (Yang, 2007; dos Reis et al., 2014). We selected 20 fossil calibration points using TimeTree (http://www.timetree.org/) (Kumar et al., 2022) for divergence time correction (Table S2). TreeAnnotator v1.10.4 (Helfrich et al. 2018) was employed to discard the first 10% of the sampling trees and then merge them. The results were visualized with FigTree v1.4.4 (Rambaut, 2018), with a 95% confidence interval.

Ethics approval and consent to participate

Not applicable.

Consent for publication

All authors consent to the publication of the article. No individual person’s data were used.

Competing interests

The authors declare no competing interests.

Supplementary Information

Table S1. Mitochondrial genome information of representative lepidopteran moths downloaded from GenBank. ^* indicates the three outgroup taxa utilized in this study.

Funding

This work was supported by the Agricultural Science and Technology Innovation Program and STI 2030-Major Projects (grant number: 2022ZD04021)

Author Contribution

X.L. and L.Z. collected and identified the specimens; X.L. and Z.L. analyzed the data; X.L. and L.Z. wrote the manuscript; L.Z. and Z.L. revised the manuscript. Y.X. conceived and designed the project, and finally approved the version to be published.

Acknowledgement

We would like to express our gratitude to Prof. Hu Li from China Agricultural University for assisting with the morphological identification of moth specimens in this study.

Availability of data and materials

All data generated or analyzed during this study are included in this published article and its supplementary information files.

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No competing interests reported.

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Comparative mitochondrial genomics unveils the phylogenetic relationships of lepidopteran moths

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Abstract

Background

Results

Conclusion

Figures

Background

Results

Sequencing and assembly of mitochondrial genomes

Comparative mitochondrial genomes

Phylogeny and monophyly inferred from mitochondrial genomes

Divergence time estimation

Discussion

Conclusions

Materials and methods

Moth collection and identification

DNA extraction and sequencing

Mito-genome assembly and annotation

Comparative mitochondrial genome analysis

Phylogenetic analysis

Divergence time estimation

Declarations

Ethics approval and consent to participate

Supplementary Information

Funding

Author Contribution

Acknowledgement

Availability of data and materials

References

Additional Declarations

Supplementary Files

Status:

Version 1