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Article

Phylogenetic Analysis of the Family Lepidostomatidae (Trichoptera: Integripalpia) Using Whole Mitochondrial Genomes

by
Xinyu Ge
1,
Jingyuan Wang
1,
Zhen Deng
2,
Lu Chai
1,
Wei Cao
1,
Wenbin Liu
1,
Jiwei Zhang
3,* and
Chuncai Yan
1,*
1
Tianjin Key Laboratory of Conservation and Utilization of Animal Diversity, College of Life Sciences, Tianjin Normal University, Tianjin 300387, China
2
Department of Entomology, College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, China
3
Changjiang Basin Ecology and Environment Monitoring and Scientific Research Center, Changjiang Basin Ecology and Environment Administration, Ministry of Ecology and Environment, Wuhan 430010, China
*
Authors to whom correspondence should be addressed.
Insects 2025, 16(5), 536; https://doi.org/10.3390/insects16050536
Submission received: 25 March 2025 / Revised: 15 May 2025 / Accepted: 16 May 2025 / Published: 19 May 2025
(This article belongs to the Section Insect Systematics, Phylogeny and Evolution)
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Simple Summary

This study sought to clarify the fundamental characteristics and phylogenetic relationships of the mitochondrial genome within the family Lepidostomatidae. We have for the first time reported the mitochondrial genomes of 13 species of the genus Lepidostoma and 1 species of the genus Paraphlegopteryx. Through a comprehensive comparative genomic analysis of Lepidostomatidae, we systematically studied their mitogenome base composition, codon usage, and evolutionary rate. Furthermore, we integrated all available lepidostomatid mitogenomes and reconstructed their phylogenetic relationships using maximum likelihood and Bayesian inference methods. This study significantly increased the mitogenomic data of Lepidostomatidae, providing a scientific basis for the identification of females and larvae of Lepidostomatidae and offering new insights into the phylogenetic relationships within the family Lepidostomatidae.

Abstract

Lepidostomatidae is a relatively large family of the infraorder Plenitentoria (Integripalpia), comprising four fossil genera and seven extant genera. Lepidostomatid adults exhibit pronounced sexual dimorphism and have thus been referred to as the ‘cabinet of curiosities’ within Trichoptera. However, only five annotated mitogenomes of Lepidostoma have been recorded in the GeneBank database, and some of these mitogenomes are incomplete. To better understand the structure of mitogenome and phylogenetic relationships of Lepidostomatidae, we present mitogenomes of 13 Lepidostoma species and one Paraphlegopteryx species for the first time. We combined these new mitogenomes with previously published data for a comparative analysis. The results showed that the structure of mitogenome was relatively conserved, the nucleotide composition was significantly AT biased, and the control region showed the highest A + T content. Evolutionary rate analysis showed that all protein-coding genes underwent purification selection. The phylogenetic relationships supported the monophyly of Lepidostomatidae and restored the taxonomic positions of the two subfamilies. Meanwhile, two monophyletic branches (Lepidostoma ferox branch and Lepidostoma hirtum branch) within the genus Lepidostoma were also strongly supported. These findings significantly advance our understanding of the mitogenome and phylogeny of Lepidostomatidae.

1. Introduction

Well known for their diversity and abundance, Trichoptera is a prominent group of insects inhabiting various global aquatic ecosystems and is extensively utilized for assessing the impact of pollutants within these systems [1,2]. Ulmer first described Lepidostomidae as a subfamily of Sericostomidae [3]. The family Lepidostomatidae is divided into two subfamilies (Lepidostomatinae Ulmer, 1903 and Theliopsychinae Weaver, 1993), including four fossil genera and seven extant genera. Among them, four fossil genera were reported from the Baltic region (†Archaeocrunoecia Ulmer, 1912, †Electrocrunoecia Ulmer, 1912 and †Maniconeurodes Ulmer, 1912) and United Kingdom (†Eucrunoecia Sukatsheva & Jarzemboski, 2001), respectively [4]. In seven extant genera, the genus Lepidostoma Rambur, 1842 is the largest genus of Lepidostomatidae, exhibiting a cosmopolitan distribution. In contrast, the genus Hummeliella Forsslund, 1936 were merely reported from China [5]. The genus Paraphlegopteryx Ulmer, 1907 and the genus Zephyropsyche Weaver, 1993 were reported from the East Palearctic region and Oriental region. The genus Theliopsyche Banks, 1911, Martynomyia Fischer, 1970, and the genus Crunoecia McLachlan, 1876 were reported from Nearctic region and West Palearctic region, respectively.
The lepidostomatid larvae most often occur in cool streams (Figure 1A), usually in low-flow areas, but they are also found in lakes and in temporary pools [6,7,8,9]. Larvae generally have a univoltine life cycle and use dead plant material and grit to construct portable tubular cases [10,11]. Most early instar larvae use grit to build cylindrical cases, while late-instar larvae construct quadrangular cases made of square pieces of bark or leaves attached at the front (Figure 1B) [12,13]. These larvae are primarily detritivorous, feeding on decomposing organic matter within their habitat [14]. The lepidostomatid adult exhibits striking sexual dimorphism, especially adult males, of the maxillary palps, antennal scapes, wings, and forelegs, and is therefore also known as the “cabinet of curiosities” within the order Trichoptera [15,16]. Adult males of different Lepidostoma species exhibit pronounced variation in antennal scape morphology and maxillary palp structure (Figure 1C,D) [17]. The secondary sexual characteristics of this genus are highly specialized, which provides an important basis for identifying closely related species with similar genital structures. In contrast, adult females and larvae show minimal interspecific differentiation in morphological traits, posing significant challenges for species-level identification.
At present, accurate species identification and the determination of phylogenetic relationships among some genera within Lepidostomatidae still are challenges. Previous studies on this family have mainly focused on morphological analyses. For instance, Weaver presented a synopsis of the North American Lepidostomatidae species and later synonymized the caddisflies of the genus Lepidostoma [15,18]. Additionally, larval stages of this family have been extensively documented in stream ecology studies due to their ecological significance [19]. However, molecular data within the family Lepidostomatidae are severely lacking [20].
Mitochondrial genomes (mitogenomes) generally contain 13 protein-coding genes (PCGs), 22 transfer RNAs (tRNAs), two ribosomal RNAs (rRNAs), and one or more control regions (CRs) [21,22]. Because of the importance of cellular energy production, a mitogenome exhibits strong evolutionary conservation in both gene content and arrangement [23]. The full-length mitogenome sequence can be more phylogenetically informative than the shorter sequences of individual molecular markers, which has been widely used for inferring phylogenetic relationship and species identification within Trichoptera at different taxonomic levels [24,25,26]. In Trichoptera, a large number of mitochondrial genome data have been published in the last two years, and these data have contributed significantly to species classification, larval matching, phylogenetic indications, and environmental DNA metabarcoding technology for water quality monitoring [2]. However, only five annotated mitogenomes of Lepidostoma species have been recorded in the NCBI database. Compared with other families of the suborder Integripalpia, mitogenomes of Lepidostomatidae are relatively rare, especially the Chinese species and the mitochondrial gene order and base composition of other genera within the Lepidostomatidae remain unknown. This limits research on the classification and phylogeny of the family.
In this study, 14 lepidostomatid species of mitogenomes were assembled and annotated; among them, seven species have never had any molecular data reported. Notably, this work presents the first mitogenome report for the genus Paraphlegopteryx. In addition, we also annotated the published mitogenome of Crunoecia irrorata Curtis, 1834. Combination with published, partial mitogenomes of Lepidostomatidae (including three species from GenBank), we analyzed the features of the mitogenomes, including nucleotide composition, and evolutionary rates. Subsequently, a phylogeny of the genus level within the Lepidostomatidae was reestablished using maximum likelihood (ML) and Bayesian inference (BI) models. This study not only enriches the mitogenome database of Lepidostomatidae but also provides understanding of the lepidostomatid phylogeny. The results will facilitate robust molecular identification of females and larvae and support the application of environmental DNA (eDNA) metabarcoding for biodiversity monitoring and conservation efforts.

2. Materials and Methods

2.1. Taxon Sampling and DNA Extraction

A total of 14 species from Lepidostomatidae were collected using Malaise traps, light traps (with a white tent and 250 W high-pressure mercury lamp), or pan traps (with 15 W ultraviolet light tubes) in China between July 2022 and August 2024 (Supplementary Table S1). All specimens were preserved in 100% ethanol and stored at −70 °C before DNA extraction. Morphological identification of the samples was conducted for Xinyu Ge by diagnostic keys of Yang and Weaver [17]. Genomic DNA was extracted from the legs of the specimen, using the TIANamp Genomic DNA Kit (DP304; TIANGEN, Beijing, China). Specimen vouchers and surplus DNA from each sequenced species have been deposited in the College of Life Science, Tianjin normal University, Tianjin, China.

2.2. Sequencing, Assembly, and Annotation

Genomic sequencing was performed at Novogene Co., Ltd. (Tianjin, China), using the Illumina NovaSeq x plus platform (Illumina Company, San Diego, CA, USA) and the DNBSEQ-T7 platform (Beijing Genomics Institution, Beijing, China), with 350 bp inserts and a paired-end 150 bp reads sequencing strategy. About 6 Gb (10× coverage per sample) of clean data was obtained for each sample. De novo assembly of mitogenomes used NOVOPlasty v3.8.3 (Brussel, Belgium) [27], with k-mer = 39 (default parameters), and with mtCOI as seed sequences. To check the accuracy of mitogenomes, we used IDBA-UD v1.1.3 (HongKong, China) [28] to independently assemble the genome and filtered out mitogenomes in Geneious v2025.2.1 (Boston, MA, USA) [29]. The raw mitogenome of C. irrorata was downloaded from NCBI. The tRNA genes were identified using the MITOS2 webserver [30], while PCGs and rRNA genes were annotated by alignment to related species in Geneious. All mitogenome sequences were deposited in GenBank (Table S2). Finally, the mitogenome maps were generated using CG-view (https://cgview.ca/, accessed on 30 January 2025).

2.3. Comparative Mitogenomic Analyses

Mitochondrial nucleotide composition and strand asymmetry were calculated with SeqKit v2.8.2 (Chongqing, China) [31]. The composition skew values were calculated by the following formulas: GC skew = G − C/G + C and AT skew = A − T/A + T [32]. The rates of the non-synonymous substitution rate (Ka)/synonymous substitution rate (Ks) and the nucleotide diversity for 13 PCG of the 14 lepidostomatid species were calculated using DnaSP v6.0. (Barcelona, Spain) [33]. The relative synonymous codon usage (RSCU) of the 14 lepidostomatid species were calculated and visualized using MEGA X (Philadelphia, PA, USA) and R v4.0.3 [34], respectively.

2.4. Phylogenetic Analyses

A total of 27 species were selected for phylogenetic analyses, 18 species as ingroups, and 9 species (seven genera) from the other four families (Phryganopsychidae Wiggins, 1959, Phryganeidae Leach, 1815, Pisuliidae Ross, 1967, Brachycentridae Ulmer, 1903) as outgroups, based on the phylogeny of Trichoptera (Table S2) [2]. Two rRNAs and 13 PCGs from each species were individually aligned using MAFFT v7.470 (Osaka, Japan) [35] (L-INS-I model) and trimmed using trimAl v1.4.1 (Barcelona, Spain) (default parameters) [36]. FASconCAT-G v1.05 (Bonn, Germany) [37] was applied to concatenate aligned sequences from each gene, and five datasets were generated. Five datasets were used for phylogenetic analyses: (1) PCG (all codon positions of the PCGs), (2) PCG12 (the 1st and 2nd codon positions of the PCGs), (3) PCG123R (all codon positions of the PCGs and rRNAs), (4) PCG12R (the 1st and 2nd codon positions of the PCGs and rRNAs), and (5) AA (amino acid sequences of the PCGs). The heterogeneity analysis of five datasets, using ALIGROOVE v1.0.7 [38] (Bonn, Germany) and DAMBE v.7.2.32 (Ottawa, ON, Canada) [39], was assessed to evaluate the substitution saturation of nucleotide datasets.
Phylogenetic relationship reconstruction was carried out with the ML and BI method. The best partitioning scheme and the best-fit substitution model for each partition were tested using ModelFinder [40]. ML analysis using IQ-TREE v 2.2.0.8 (Canberra, ACT, Australia) [41] used the best-fit substitution model and 1000 bootstrap replicates [42]. BI analysis was conducted using Phylobayes-MPI v1.9 (Montréal, QC, Canada) [43], run with MCMC (Markov chain Monte Carlo) analysis, and stopped after the two runs had satisfactorily converged (maxdiff < 0.3; effsize > 50). The initial 25% of trees were discarded as burn-in, and a strict consensus tree was generated from the remaining trees. Phylogenetic results are displayed in Figtree v1.4.3 (Oxford, UK) [44].

3. Results and Discussion

3.1. Mitogenome Features and Base Composition of Lepidostomatidae

We obtained novel mitogenomes for 14 species (two genera) from Lepidostomatidae, with Paraphlegopteryx reported for the first time (Figure 2, Figures S1 and S2). Newly sequenced mitogenomes contained the entire set of 37 genes (13 PCGs, 22 tRNA genes, and 2 rRNA genes). The mitogenome of Lepidostoma found no gene rearrangement of gene order, which was the same as the ancestral gene order of Drosophila yakuba Burla, 1954 [45]. The gene cluster trnR-trnN-trnS1-trnE-trnA-trnF was found in the mitogenome of Paraphlegopteryx. The newly sequenced 14 mitogenomes of lepidostomatid ranged in length from 15,053 bp Lepidostoma albardanum Ulmer, 1906 to 16,495 bp Paraphlegopteryx subcircularis Schmid, 1965 (Table 1). Among them, the CRs of Lepidostoma elongatum Martynov, 1935 and L. albardanum could not complete the sequencing due to their complex structure and high AT content [46]. The incomplete CR did not affect subsequent phylogenetic analyses. The AT content varies from 76.59% in Lepidostoma reductum Martynov, 1915 to 80.40% in P. subcircularis. The AT content of whole mitogenomes were similar in other Plenitentoria species [26]. In the mitogenomes of lepidostomatid species, the AT skew was positive, while the GC skew was negative.

3.2. Protein-Coding Genes and Codon Usage

In the mitogenome, there are great variations in the length of each PCGs, which range from 165 bp (ATP8) to 1734 bp (ND5). There was no significant difference in the total length of 13 PCGs, ranging from 11,197 (Lepidostoma aranos Oláh, 2013) to 11,249 bp (P. subcircularis) (Table S3). For ATP6, COX1, COX2 CYTB, ND1, ND2, ND4L, and ND5, a fixed start codon is used in each gene, and more than two start codons are used in other genes (Figure S3). Except for COX2, the start codon of other PCGs is ATN mode. The termination codon for most PCGs, excluding ND1, is typically TAA or TAG, with TAA being the most frequently used. A single T is used as a termination of ND1 in all species of Lepidostoma, while the common TAA was only used in ND1 in Paraphlegopteryx, demonstrating inter-genus variability and intra-genus conservation. These incomplete stop codons are thought to have been filled with polyadenylation during mRNA maturation [24].
We used the Ka/Ks ratio to estimate the evolutionary rate of 13 PCGs (Figure 3). Our results showed that the Ka/Ks of 13 PCGs in the mitogenome of lepidostomatid species was less than 1, indicating that these genes were in a state of purified selection. The evolutionary rate of ATP8 (0.55) is the highest, and the evolutionary rate of COX1 (0.04) is the lowest, indicating that ND6 has the lowest purification selection pressure, and COX1 has the highest purification selection pressure, which has also been observed in other species of Integripalpia [2].
The analysis of nucleotide diversity based on 13 PCGs from 14 lepidostomatid species showed pi values ranging from 0.137 (ND1) to 0.241 (ATP8) (Table S4). The highest nucleotide diversity of ATP8 gene indicates a large variation region, while ND1 is a conserved gene in Lepidostomatidae. Therefore, ND1 may be an effective molecular marker for species identification. The RSCU of these 14 species suggests a strong AT bias in the nucleotide composition of the mitogenome (Figures S4 and S5). The third codon position shows obvious A and T base dominance; TTA, ATT, TTT, ATA, and AAT are the most commonly used codons of these species. The results showed that Leu2, Phe, Ile, and Asn were the most commonly used amino acids.

3.3. Transfer RNAs and Ribosomal RNAs and Control Regions

The mitogenomes of each lepidostomatid species contain 22 tRNA genes, with lengths varying between 59 and 73 bp. Among the 22 tRNAs in the 14 mitogenomes, only the length of trnV is constant, and the length of the other tRNAs varies greatly or slightly. The GC-skew (0.171–0.101) and AT-skew (0.007–0.039) of tRNA genes were positive, and the AT content exceeded 82% (Table S3). The l-rRNA gene exhibits a size variation spanning from 1456 bp in Lepidostoma propriopalpum Hwang, 1957 to 1372 bp in P. subcircularis. In contrast, the s-rRNA gene shows a short variation, with the sequence observed ranging from 790 bp (P. subcircularis) to 804 bp (L. reductum). The nucleotide composition patterns in rRNA genes exhibit distinct differences compared to those in tRNA genes within the mitogenome. Analysis of rRNA genes revealed positive values for both GC-skew (ranging from 0.31 to 0.38) and AT-skew (ranging from 0.03 to 0.07), with the AT content surpassing 86% across all sequences. The lengths of the CR range from 159 bp to 1517 bp. The AT content of this region was the highest, ranging from 84.86% (L. flavum) to 91.61% (L. hirtum). Considering the length variation in tRNA and rRNA, the length variation in mitochondria is due to the length of the control region and gene spacer region, which is consistent with the results of other mitochondrial studies in metabiological animals.

3.4. Phylogenetic Analyses of Lepidostomatidae

In order to evaluate and understand the heterogeneity patterns of different datasets, we used AliGROOVE to perform heterogeneity analysis on the five generated datasets, (Figure 4) and the results showed that the amino acid dataset was the lowest in the five datasets, which was due to the amino acid sequence conservation caused by the use of synonymous codons [47]. Compared with the PCG123 dataset, the elimination of the third codon position can reduce the heterogeneity, which indicated that the evolution rate of the third codon position is faster. The nucleotide datasets with rRNA genes were less heterogeneous than those without rRNA genes. This is consistent with the results of mitogenome study in the Apataniidae by Ge et al. [2], suggesting that the addition of the rRNA gene can reduce heterogeneity during the reconstruction of the phylogenetic relationship using mitogenomes.
Notably, Silvatares holzenthali Rázuri-Gonzales, Ngera & Pauls, 2022 and C. irrorata showed significantly high sequence heterogeneity across all datasets. This phenomenon may be attributed to the accelerated rate of evolution of this species or limited phylogenetic resolution due to under-sampling of representatives of Pisuliidae and Theliopsychinae [2,48]. Saturation substitution analysis of the nucleotide dataset showed that the simple index of substitution saturation (ISS) was less than the critical ISS value (ISs.c), p < 0.05 (Figures S6 and S7). This suggests that these datasets were not saturated in terms of nucleotide substitution.
In this study, phylogenetic trees were reconstructed using ML and BI methods based on five datasets. The best partitions of five datasets for the ML analysis are listed in Table S5. The results of the phylogenetic tree show roughly similar topologies. In this study, the Lepidostomatidae was consistently recovered as monophyletic groups in all phylogenetic trees, which had high nodal support values (posterior probabilities PPs ≥ 95; bootstrap probabilities BPs ≥ 75). In the BI tree based on the PCG12R, S. holzenthali and two Phryanea species were recovered as an unresolved trichotomy (Figure S8). The phylogenetic tree based on the PCG123R dataset using the BI method supported topology (Phryganopsychidae + (Phryganeidae + Pisuliidae) + (Brachycentridae + Lepidostomatidae)) (Figure 5), while the ML trees based on the all datasets and BI tree based on PCG, PCG12, and AA datasets both supported topology (Phryganopsychidae + (((Phryganeidae + Pisuliidae) + Brachycentridae) + Lepidostomatidae)) (Figures S9–S16). When mitogenome is used in phylogenetic studies, different genes, coding position, and models may be selected to obtain different topologies. In the phylogenetic studies of insect groups, the use of two rRNA genes is more common than that of short tRNA genes with a lower evolutionary rate. Additionally, in phylogenetic studies of the orders Hemiptera and Hymenoptera, removal of the third codon position did not affect or even optimize the results, while in Diptera, this selection reduced the phylogenetic sign [49,50,51]. Comparing the studies of Paul and Ge et al. [52,53], we believe that the use of the BI model and the addition of the rRNA gene can improve the phylogenetic resolution in the study of trichopteran phylogeny (without an unresolved trichotomy, Figure 5). Therefore, we infer that Lepidostomatidae is a monophyletic family that is the sister group to Brachycentridae.
Within Lepidostomatidae, the monophyly of two subfamilies (Lepidostomatinae and Theliopsychinae) was strongly supported in all topologies. In Lepidostoma, four large species groups are distinguished by the structure of male forewings, with the most significant differences lying in the anal region. These varying forewing structures form a transitional series, which likely evolved in the sequence outlined below: Lepidostoma vernale branch, Lepidostoma podagrum branch, Lepidostoma ferox branch, and Lepidostoma hirtum branch. Weaver considered that the L. vernale and L. hirtum branches are each monophyletic, but suspected that the L. podagrum branch is not monophyletic [15]. The results of a phylogenetic analysis of most North American species using mtDNA by Myers and Sperling indicate that the L. ferox branch and L. hirtum branch are monophyletic [15,20].
Our phylogenetic results recovered monophyletic L. ferox and the L. hirtum branches, which is consistent with the results of Myers and Sperling [20]. The unnamed species Lepidostoma sp. XG-2025 might be classified under the L. ferox branch. It also indicates that the mitochondrial phylogenomics has provided effective data to help resolve some issues in the genus level phylogeny of Lepidostomatinae. Furthermore, we reconstructed the ML tree using Theliopsychinae as the outer group and Lepidostomatinae as the inner group (Figures S17–S21). The interspecific phylogenetic relationships in these phylogenetic trees are roughly the same. In the L. hirtum branch, Lepidostoma inops species group (L. tanmounense + (L. inops + L. propriopalpum)) was recovered a monophyletic group, which supports the classification of the species group. In the L. ferox branch, Species with similar geographical distributions (L. albardanum and L. elongatum; L. sichuanense and L. pusillum) have a closer genetic relationship. In our initial phylogenetic study, the L. vernale and L. podagrum branches distributed in North America were not included. Although the L. ferox and L. hirtum branches were restored to sister groups in this study, this might not reflect the true phylogenetic relationship among each branch. Therefore, the current molecular studies on Lepidostomatidae are limited. In this study, the mitogenome of Lepidostomatidae was added, which provides scientific basis for female and larval identification and evolutionary trend of Lepidostomatidae. However, the sample and molecular data in this study are limited. Future studies should include more taxa samples (Paraphlegopteryx, Zephyropsyche, Theliopsyche and Lepidostoma species) and more molecular data (Universal Single-Copy Orthologs or Ultra-Conserved Elements) to facilitate the understanding of phylogenetic relationships in Lepidostomatidae.

4. Conclusions

In this study, we sequenced and compared the mitogenomes of 14 lepidostomatid species and reported the mitogenome structure of Paraphlegopteryx for the first time. The results showed that the mitogenome of Lepidostomatidae was similar to that of most other insects. The phylogenetic relationship of Lepidostomatidae was reconstructed using ML and BI methods based on mitogenomes. Phylogenetic results showed that the family Lepidostomatidae was consistently recovered as monophyletic groups, and the taxonomic position of the two subfamilies was strongly supported. In addition, we recovered monophyletic L. ferox and L. hirtum branches. This preliminary result suggests that future studies need to clarify phylogenetic relationships within Lepidostomatidae by increasing the number of taxon samples and integrate more molecular data.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/insects16050536/s1. Table S1. The taxonomic information and sampling metadata of the sequenced samples. Table S2. Detailed taxonomic resources used in phylogeny analysis. Table S3. Nucleotide composition of 14 lepidostomatid mitogenomes. Table S4. Nucleotide diversity (Pi) values of 14 lepidostomatid species mitogenomes. Table S5. The best partitions of five datasets for the ML analysis. Figures S1 and S2. The mitogenome map of the 12 lepidostomatid species mitogenome. Figure S3. Strat codons and termination codons of PCGs among 14 lepidostomatid species mitogenomes. Figures S4 and S5. The relative synonymous codon usage of the PCGs of 14 lepidostomatid species. Figures S6 and S7. Substitution saturation plots of PCG123 and PCG12 datasets. Figures S8–S11. The BI trees based on the PCG12R, PCG12, PCG, and AA dataset, using the CAT + GTR model. Figures S12–S16. The ML trees based on the PCG123R, PCG12R, PCG12, PCG, and AA dataset, using the Partitioning model. Figures S17–S21. The ML tree based on the AA, PCG, PCG123R, PCG12, PCG12R dataset of Lepidostomatidae, using the Partitioning model. The numbers above nodes are bootstrap probabilities.

Author Contributions

Conceptualization, X.G., J.Z. and C.Y.; methodology, X.G. and J.W.; software, J.W. and W.L.; validation, X.G. and J.W.; formal analysis, L.C., J.W. and W.C.; investigation, X.G., Z.D. and W.C.; data curation, Z.D., W.L. and J.W.; writing—original draft preparation, X.G.; writing—review and editing, X.G., C.Y. and J.Z.; visualization, J.W., W.L. and L.C.; supervision, X.G., J.Z. and C.Y.; funding acquisition, X.G. and C.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (32400357, 32170473, and 32370489).

Data Availability Statement

The data of this study are available under the NCBI accession numbers (PV364373, PV364374 and PV366289–PV366300).

Acknowledgments

We sincerely thank the editors and reviewers for their valuable comments on this study. We greatly thank Dr. Dewen Gong and Prof. Zhulidezi Aishan for their help in collecting some samples. Thanks, are also extended to Qianle Lu for providing the L. longipilosum photos.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Morse, J.C.; Frandsen, P.B.; Graf, W.; Thomas, J.A. Diversity and Ecosystem Services of Trichoptera. Insects 2019, 10, 125. [Google Scholar] [CrossRef] [PubMed]
  2. Ge, X.; Peng, L.; Vogler, A.P.; Morse, J.C.; Yang, L.; Sun, C.; Wang, B. Massive gene rearrangements of mitochondrial genomes and implications for the phylogeny of Trichoptera (Insecta). Syst. Entomol. 2023, 48, 278–295. [Google Scholar] [CrossRef]
  3. Ulmer, G.F.F. Über die Metamorphose der Trichopteren; Hardpress Publishing: Miami, FL, USA, 1903; Volume 18, pp. 1–154. [Google Scholar]
  4. Morse, J.C. Trichoptera World Checklist. Available online: https://trichopt.app.clemson.edu/welcome.php (accessed on 21 June 2022).
  5. Holzenthal, R.W.; Blahnik, R.J.; Prather, A.L.; Kjer, K.M. Order trichoptera kirby, 1813 (insecta), caddisflies. Zootaxa 2007, 1668, 639–698. [Google Scholar] [CrossRef]
  6. Mackay, R.J. Aquatic Insect Communities of a Small Stream on Mont St. Hilaire, Quebec. J. Fish. Board Can. 1969, 26, 1157–1183. [Google Scholar] [CrossRef]
  7. Ito, T. Six new species of the genus Lepidostoma Rambur (Trichoptera, Lepidostomatidae) from Japan. Zoosymposia 2011, 5, 158–170. [Google Scholar] [CrossRef]
  8. Karaouzas, I.; Waringer, J. The larva of Lepidostoma doehleri Malicky 1976 (Trichoptera: Lepidostomatidae) with notes on ecology and a key to larvae for species of the genus in Greece. Zootaxa 2016, 4189, 588–592. [Google Scholar] [CrossRef]
  9. Terefe, Y.; Vitecek, S.; Graf, W. Description of the larva of Oecetis mizrain Malicky & Graf, 2012 (Trichoptera, Leptoceridae) and Lepidostoma scotti (Ulmer, 1930) (Trichoptera, Lepidostomatidae) from Chilimo Forest, Central Ethiopia. Zookeys 2018, 766, 63–77. [Google Scholar] [CrossRef]
  10. Grafius, E.J.; Anderson, N.H. Population dynamics and role of two species of Lepidostoma (Trichoptera: Lepidostomatidae) in an Orgeon coniferous forest stream [Lepidostoma cascadense, Lepidostoma unicolor; Oregon]. Ecology 1980, 61, 808–816. [Google Scholar] [CrossRef]
  11. Malicky, H. Phänologische Studien an tropischen Trichopteren: Chiangmai Zoo (Thailand). Braueria 2021, 48, 46–58. [Google Scholar]
  12. Wiggins, G.B. Larvae of the North American Caddisfly Genera (Trichoptera); University of Toronto: Toronto, ON, Canada, 1996. [Google Scholar]
  13. Dinakaran, S.; Sankarappan, A.; Balachandran, C. A new species of Caddisfly (Trichoptera: Lepidostomatidae: Lepidostoma) from Tamil Nadu, India. J. Threat. Taxa 2013, 5, 3531–3535. [Google Scholar] [CrossRef]
  14. Anderson, N.H.; Grafius, E.J. Utilization and processing of allochthonous material by stream Trichoptera. Int. Ver. Theor. Und Angew. Limnol. Verhandlungen 1975, 19, 3083–3088. [Google Scholar] [CrossRef]
  15. Weaver, J. A synonymy of the caddisfly genus Lepidostoma Rambur (Trichoptera: Lepidostomatidae), including a species checklist. Tijdschr. Entomol. 2002, 145, 173–192. [Google Scholar] [CrossRef]
  16. McLachlan, R. A Monographic Revision and Synopsis of the Trichoptera of the European Fauna; John van Voorst: London, UK, 1876; Volume 5. [Google Scholar]
  17. Yang, L.; Weaver, J., III. The Chinese Lepidostomatidae (Trichoptera). Tijdschr. Entomol. 2002, 145, 267–352. [Google Scholar] [CrossRef]
  18. Weaver, J. A synopsis of the North American Lepidostomatidae (Trichoptera). Contrib. Am. Entomol. Inst. 1988, 24, 1–141. [Google Scholar]
  19. Suwannarat, N.; Laudee, P. Larval morphology, life cycle and nutritional values of Lepidostoma abruptum Banks 1931 (Trichoptera: Lepidostomatidae) from Lower-Hill Evergreen Forests of Southern Thailand. Zootaxa 2022, 5200, 63–72. [Google Scholar] [CrossRef]
  20. Myers, M.J.; Sperling, F.A. Preliminary evaluation of subgeneric designations within the caddisfly genus Lepidostoma (Rambur) (Trichoptera: Lepidostomatidae) based on mtDNA sequences. In Nova Supplementa Entomologica (Proceedings of the 10th International Symposium on Trichoptera); Antiquariat Geock & Evers: Pforzheim, Germany, 2002; pp. 187–194. [Google Scholar]
  21. Cameron, S.L. Insect Mitochondrial Genomics: A Decade of Progress. Annu. Rev. Entomol. 2025, 70, 83–101. [Google Scholar] [CrossRef]
  22. Cameron, S.L. Insect mitochondrial genomics: Implications for evolution and phylogeny. Annu. Rev. Entomol. 2014, 59, 95–117. [Google Scholar] [CrossRef] [PubMed]
  23. Françoso, E.; Zuntini, A.R.; Ricardo, P.C.; Santos, P.K.F.; de Souza Araujo, N.; Silva, J.P.N.; Gonçalves, L.T.; Brito, R.; Gloag, R.; Taylor, B.A.; et al. Rapid evolution, rearrangements and whole mitogenome duplication in the Australian stingless bees Tetragonula (Hymenoptera: Apidae): A steppingstone towards understanding mitochondrial function and evolution. Int. J. Biol. Macromol. 2023, 242, 124568. [Google Scholar] [CrossRef]
  24. Peng, L.; Ge, X.; Shi, F.; Wang, L.; Zang, H.; Sun, C.; Wang, B. New Mitogenome Features of Philopotamidae (Insecta: Trichoptera) with Two New Species of Gunungiella. Insects 2022, 13, 1101. [Google Scholar] [CrossRef]
  25. Ge, X.; Zang, H.; Ye, X.; Peng, L.; Wang, B.; Lian, G.; Sun, C. Comparative Mitogenomic Analyses of Hydropsychidae Revealing the Novel Rearrangement of Protein-Coding Gene and tRNA (Trichoptera: Annulipalpia). Insects 2022, 13, 759. [Google Scholar] [CrossRef]
  26. Ge, X.; Wang, J.; Zang, H.; Chai, L.; Liu, W.; Zhang, J.; Yan, C.; Wang, B. Mitogenomics Provide New Phylogenetic Insights of the Family Apataniidae (Trichoptera: Integripalpia). Insects 2024, 15, 973. [Google Scholar] [CrossRef] [PubMed]
  27. Dierckxsens, N.; Mardulyn, P.; Smits, G. NOVOPlasty: De novo assembly of organelle genomes from whole genome data. Nucleic Acids Res. 2016, 45, e18. [Google Scholar] [CrossRef]
  28. Peng, Y.; Leung, H.C.; Yiu, S.M.; Chin, F.Y. IDBA-UD: A de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics 2012, 28, 1420–1428. [Google Scholar] [CrossRef]
  29. Kearse, M.; Moir, R.; Wilson, A.; Stones-Havas, S.; Cheung, M.; Sturrock, S.; Buxton, S.; Cooper, A.; Markowitz, S.; Duran, C.; et al. Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 2012, 28, 1647–1649. [Google Scholar] [CrossRef] [PubMed]
  30. Donath, A.; Jühling, F.; Al-Arab, M.; Bernhart, S.H.; Reinhardt, F.; Stadler, P.F.; Middendorf, M.; Bernt, M. Improved annotation of protein-coding genes boundaries in metazoan mitochondrial genomes. Nucleic Acids Res. 2019, 47, 10543–10552. [Google Scholar] [CrossRef]
  31. Shen, W.; Le, S.; Li, Y.; Hu, F. SeqKit: A Cross-Platform and Ultrafast Toolkit for FASTA/Q File Manipulation. PLoS ONE 2016, 11, e0163962. [Google Scholar] [CrossRef]
  32. Perna, N.T.; Kocher, T.D. Patterns of nucleotide composition at fourfold degenerate sites of animal mitochondrial genomes. J. Mol. Evol. 1995, 41, 353–358. [Google Scholar] [CrossRef]
  33. Rozas, J.; Ferrer-Mata, A.; Sánchez-DelBarrio, J.C.; Guirao-Rico, S.; Librado, P.; Ramos-Onsins, S.E.; Sánchez-Gracia, A. DnaSP 6: DNA Sequence Polymorphism Analysis of Large Data Sets. Mol. Biol. Evol. 2017, 34, 3299–3302. [Google Scholar] [CrossRef]
  34. Team, R.C. R: A Language and Environment for Statistical Computing; Foundation for Statistical Computing: Vienna, Austria, 2013; Volume 1. [Google Scholar]
  35. Katoh, K.; Standley, D.M. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Mol. Biol. Evol. 2013, 30, 772–780. [Google Scholar] [CrossRef]
  36. Capella-Gutiérrez, S.; Silla-Martínez, J.M.; Gabaldón, T. trimAl: A tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 2009, 25, 1972–1973. [Google Scholar] [CrossRef]
  37. Kück, P.; Longo, G.C. FASconCAT-G: Extensive functions for multiple sequence alignment preparations concerning phylogenetic studies. Front. Zool. 2014, 11, 81. [Google Scholar] [CrossRef] [PubMed]
  38. Kück, P.; Meid, S.; Christian, G.; Wägele, J.W.; Misof, B. AliGROOVE—Visualization of heterogeneous sequence divergence within multiple sequence alignments and detection of inflated branch support. BMC Bioinform. 2014, 15, 294. [Google Scholar] [CrossRef]
  39. Xia, X. DAMBE7: New and Improved Tools for Data Analysis in Molecular Biology and Evolution. Mol. Biol. Evol. 2018, 35, 1550–1552. [Google Scholar] [CrossRef] [PubMed]
  40. Kalyaanamoorthy, S.; Minh, B.Q.; Wong, T.K.F.; von Haeseler, A.; Jermiin, L.S. ModelFinder: Fast model selection for accurate phylogenetic estimates. Nat. Methods 2017, 14, 587–589. [Google Scholar] [CrossRef] [PubMed]
  41. Minh, B.Q.; Schmidt, H.A.; Chernomor, O.; Schrempf, D.; Woodhams, M.D.; von Haeseler, A.; Lanfear, R. IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era. Mol. Biol. Evol 2020, 37, 1530–1534. [Google Scholar] [CrossRef]
  42. Hoang, D.T.; Chernomor, O.; von Haeseler, A.; Minh, B.Q.; Vinh, L.S. UFBoot2: Improving the Ultrafast Bootstrap Approximation. Mol. Biol. Evol. 2017, 35, 518–522. [Google Scholar] [CrossRef]
  43. Lartillot, N.; Rodrigue, N.; Stubbs, D.; Richer, J. PhyloBayes MPI: Phylogenetic Reconstruction with Infinite Mixtures of Profiles in a Parallel Environment. Syst. Biol. 2013, 62, 611–615. [Google Scholar] [CrossRef]
  44. Rambaut, A. FigTree Version 1.4.3. Computer Program Distributed by the Author. Available online: http://tree.bio.ed.ac.uk/software/figtree/ (accessed on 25 November 2018).
  45. Clary, D.O.; Wolstenholme, D.R. The mitochondrial DNA molecule of Drosophila yakuba: Nucleotide sequence, gene organization, and genetic code. J. Mol. Evol. 1985, 22, 252–271. [Google Scholar] [CrossRef]
  46. Lin, X.L.; Liu, Z.; Yan, L.P.; Duan, X.; Bu, W.J.; Wang, X.H.; Zheng, C.G. Mitogenomes provide new insights of evolutionary history of Boreheptagyiini and Diamesini (Diptera: Chironomidae: Diamesinae). Ecol. Evol. 2022, 12, e8957. [Google Scholar] [CrossRef]
  47. Xiao, X.R.; Chen, M.H.; Li, S.Y.; Guo, B.X.; Zhang, Y.; Zhang, Z.C.; Qiao, Y.J.; Lin, X.L. Comparative Mitogenomic Analyses of Tanypodinae (Diptera: Chironomidae). Insects 2025, 16, 203. [Google Scholar] [CrossRef]
  48. Song, N.; Zhang, H.; Zhao, T. Insights into the phylogeny of Hemiptera from increased mitogenomic taxon sampling. Mol. Phylogenet. Evol. 2019, 137, 236–249. [Google Scholar] [CrossRef] [PubMed]
  49. Cameron, S.L.; Sullivan, J.; Song, H.; Miller, K.B.; Whiting, M.F. A mitochondrial genome phylogeny of the Neuropterida (lace-wings, alderflies and snakeflies) and their relationship to the other holometabolous insect orders. Zool. Scr. 2009, 38, 575–590. [Google Scholar] [CrossRef]
  50. Cameron, S.L.; Johnson, K.P.; Whiting, M.F. The Mitochondrial Genome of the Screamer Louse Bothriometopus (Phthiraptera: Ischnocera): Effects of Extensive Gene Rearrangements on the Evolution of the Genome. J. Mol. Evol. 2007, 65, 589–604. [Google Scholar] [CrossRef]
  51. Mao, M.; Valerio, A.; Austin, A.D.; Dowton, M.; Johnson, N.F. The first mitochondrial genome for the wasp superfamily Platygastroidea: The egg parasitoid Trissolcus basalis. Genome 2012, 55, 194–204. [Google Scholar] [CrossRef] [PubMed]
  52. Frandsen, P.B.; Holzenthal, R.W.; Espeland, M.; Breinholt, J.; Thomas Thorpe, J.A.; Simon, S.; Kawahara, A.Y.; Plotkin, D.; Hotaling, S.; Li, Y.; et al. Phylogenomics recovers multiple origins of portable case making in caddisflies (Insecta: Trichoptera), nature’s underwater architects. Roy. Soc. B—Biol. Sci. 2024, 291, 20240514. [Google Scholar] [CrossRef]
  53. Ge, X.; Peng, L.; Morse, J.C.; Wang, J.; Zang, H.; Yang, L.; Sun, C.; Wang, B. Phylogenomics resolves a 100-year-old debate regarding the evolutionary history of caddisflies (Insecta: Trichoptera). Mol. Phylogenet. Evol. 2024, 201, 108196. [Google Scholar] [CrossRef]
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Figure 1. (A) Habitat of Lepidostomatidae; (B) larva of the genus Lepidostoma; (C) Lepidostoma sichuanense, male, from Sichuan, China, (photographed by Wei Cao); (D) Lepidostoma longipilosum, male, from Hebei, China, (photographed by Qianle Lu).
Figure 1. (A) Habitat of Lepidostomatidae; (B) larva of the genus Lepidostoma; (C) Lepidostoma sichuanense, male, from Sichuan, China, (photographed by Wei Cao); (D) Lepidostoma longipilosum, male, from Hebei, China, (photographed by Qianle Lu).
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Figure 2. The mitogenome map of two lepidostomatid species. The arrow served as a guide, pointing to the orientation of gene transcription. We used standardized abbreviations to denote PCGs and rRNAs, while single-letter abbreviations were chosen for tRNAs.
Figure 2. The mitogenome map of two lepidostomatid species. The arrow served as a guide, pointing to the orientation of gene transcription. We used standardized abbreviations to denote PCGs and rRNAs, while single-letter abbreviations were chosen for tRNAs.
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Figure 3. The evolution rate of PCGs of Lepidostomatidae. The abscissa represents the 13 PCGs, and the ordinate represents Ka/Ks values.
Figure 3. The evolution rate of PCGs of Lepidostomatidae. The abscissa represents the 13 PCGs, and the ordinate represents Ka/Ks values.
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Figure 4. The evaluation of the heterogeneity among the five datasets. The degree of sequence similarity was visually represented through colored blocks, with scores in a spectrum from 0 (signaling major heterogeneity between datasets, represented by light blue) to +1 (signaling minor heterogeneity between datasets, depicted in dark blue). (A) PCG12; (B) PCG12R; (C) AA; (D) PCG123; (E) PCG123R.
Figure 4. The evaluation of the heterogeneity among the five datasets. The degree of sequence similarity was visually represented through colored blocks, with scores in a spectrum from 0 (signaling major heterogeneity between datasets, represented by light blue) to +1 (signaling minor heterogeneity between datasets, depicted in dark blue). (A) PCG12; (B) PCG12R; (C) AA; (D) PCG123; (E) PCG123R.
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Figure 5. The BI tree based on the PCG123R dataset, using the CAT + GTR model. The numbers above nodes are Bayesian posterior probabilities. A: the Lepidostoma hirtum branch; B: the Lepidostoma ferox branch.
Figure 5. The BI tree based on the PCG123R dataset, using the CAT + GTR model. The numbers above nodes are Bayesian posterior probabilities. A: the Lepidostoma hirtum branch; B: the Lepidostoma ferox branch.
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Table 1. Nucleotide composition of 14 species of Lepidostomatinae.
Table 1. Nucleotide composition of 14 species of Lepidostomatinae.
SpeciesLength (bp)A (%)T (%)C (%)G (%)A + T (%)GC-SkewAT-Skew
Lepidostoma albardanum15,053 38.82 39.40 14.34 7.43 78.22 −0.317 −0.007
Lepidostoma elongatum15,234 39.13 40.47 13.13 7.26 79.60 −0.288 −0.017
Lepidostoma aranos15,870 38.49 39.19 15.00 7.30 77.67 −0.345 −0.009
Lepidostoma cornigerum15,325 38.04 39.11 15.37 7.48 77.15 −0.346 −0.014
Lepidostoma flavum15,816 38.12 40.05 14.53 7.23 78.17 −0.335 −0.025
Lepidostoma hirtum15,663 38.75 39.45 14.45 7.35 78.20 −0.325 −0.009
Lepidostoma penicillatum15,875 39.04 40.34 13.44 7.15 79.38 −0.305 −0.016
Lepidostoma propriopalpum15,158 39.12 40.32 13.28 7.27 79.44 −0.293 −0.015
Lepidostoma pusillum16,036 38.83 39.92 13.81 7.39 78.74 −0.303 −0.014
Lepidostoma reductum15,077 38.56 38.03 15.24 8.17 76.59 −0.302 0.007
Lepidostoma sichuanense16,165 38.47 39.65 14.24 7.52 78.11 −0.309 −0.015
Lepidostoma sp. XG-202515,115 38.86 39.05 14.49 7.61 77.90 −0.311 −0.002
Lepidostoma tanmounense15,065 38.58 40.07 13.88 7.47 78.65 −0.300 −0.019
Paraphlegopteryx subcircularis16,495 38.87 41.53 12.57 6.80 80.40 −0.298 −0.033
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Ge, X.; Wang, J.; Deng, Z.; Chai, L.; Cao, W.; Liu, W.; Zhang, J.; Yan, C. Phylogenetic Analysis of the Family Lepidostomatidae (Trichoptera: Integripalpia) Using Whole Mitochondrial Genomes. Insects 2025, 16, 536. https://doi.org/10.3390/insects16050536

AMA Style

Ge X, Wang J, Deng Z, Chai L, Cao W, Liu W, Zhang J, Yan C. Phylogenetic Analysis of the Family Lepidostomatidae (Trichoptera: Integripalpia) Using Whole Mitochondrial Genomes. Insects. 2025; 16(5):536. https://doi.org/10.3390/insects16050536

Chicago/Turabian Style

Ge, Xinyu, Jingyuan Wang, Zhen Deng, Lu Chai, Wei Cao, Wenbin Liu, Jiwei Zhang, and Chuncai Yan. 2025. "Phylogenetic Analysis of the Family Lepidostomatidae (Trichoptera: Integripalpia) Using Whole Mitochondrial Genomes" Insects 16, no. 5: 536. https://doi.org/10.3390/insects16050536

APA Style

Ge, X., Wang, J., Deng, Z., Chai, L., Cao, W., Liu, W., Zhang, J., & Yan, C. (2025). Phylogenetic Analysis of the Family Lepidostomatidae (Trichoptera: Integripalpia) Using Whole Mitochondrial Genomes. Insects, 16(5), 536. https://doi.org/10.3390/insects16050536

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