Skip to main content
NCBI home page
Journal of Insect Science logoLink to Journal of Insect Science
. 2021 Jan 11;21(1):5. doi: 10.1093/jisesa/ieaa138

Characterization and Phylogenetic Analysis of the Complete Mitochondrial Genome of Laelia suffusa (Lepidoptera: Erebidae, Lymantriinae)

Jing Li 1, Qing Lv 1, Xiao-man Zhang 1, Hui-lin Han 2, Ai-bing Zhang 1,✉
Editor: Margaret Allen
PMCID: PMC7799433  PMID: 33428744

Abstract

In this study, the complete mitochondrial genome of a white tussock moth, Laelia suffusa (Walker, 1855) (Lepidoptera: Erebidae, Lymantriinae), was sequenced and annotated. The genome sequence was 15,502 bp in length and comprised 13 PCGs, 2 rRNAs, 22 tRNAs, and a single noncoding control region (CR). The nucleotide composition of the genome was highly A + T biased, accounting for 79.04% of the whole genome and with a slightly positive AT skewness (0.015). Comparing the gene order with the basal species of Lepidoptera, a typical trnM rearrangement was detected in the mitogenome of L. suffusa. Besides, the trnM rearrangement was found at the head of trnI and trnQ, rather than at the back. The 13 PCGs used ATN as their start codons, except for the cox1 which used CGA. Out of the 22 tRNAs, only 1 tRNA (trnS1) failed to fold in a typical cloverleaf secondary structure. The conserved motif ‘ATAGA + poly-T’ was detected at the start of the control region which was similar to other Lepidoptera species. In total, 10 overlapping regions and 19 intergenic spacers were identified, ranging from 1 to 41 and 2 to 73 bp, respectively. Phylogenetic analysis showed that Lymantriinae was a monophyletic group with a high support value and L. suffusa was closely related to tribe Orgyiini (Erebidae, Lymantriinae). Moreover, the phylogenetic relationship of Noctuoidea (Lepidoptera) species was reconstructed using two datasets (13 PCGs and 37 genes) and these supported the topology of (Notodontidae + (Erebidae + (Nolidae + (Euteliidae + Noctuidae)))).

Keywords: Laelia suffusa, Lepidoptera, Erebidae, mitogenome, phylogeny

Lepidopteran, including moths and butterflies, are globally distributed phytophagous insects and one of the four largest holometabolous orders (Kristensen et al. 2007). More than 180,000 species of Lepidoptera are described and are only second in the class Insecta (Scoble 1992, Pogue 2009, Mullen and Zaspel 2019). Laelia (Lepidoptera: Erebidae, Lymantriinae) is a genus of tussock moths in the family Erebidae, whose distribution spans throughout Europe and Asia (Chao 1987, 2003). Laelia suffusa is a white tussock moth that is mainly distributed in the south and southeast of Asia (Chao 1987, Ahmed et al. 2002). Besides, it is regarded as one of the main pasture and rice fields pests and can cause significant economic losses if not well managed, which are associated with its larvae behavior, short life cycle, population explosion, and can have six to seven generations per year (Chao 1987, Ahmed et al. 2002). A high population of L. suffusa can consume leaves from culms and tillers regardless of leaf age or plant (Ahmed et al. 2002). The larvae are covered with yellow hairs on their backs and can cause cutaneous eruptions outbreaks (Dubois and Dean 1995, Yanar et al. 2017). Previous studies have focused on species diversity (Fox 2013, Ju et al. 2016, Singh and Navkiran 2019, Zhang et al. 2019), pest control (Li and Yan 1991, Armstrong et al. 2003, Yu et al. 2019, Sun et al. 2020), species identification and genetic variations (Singh and Navkiran 2019), and insect physiological adaption (Zapletalová et al. 2016) of Laelia. However, very limited research has been conducted on the phylogenetic relationship of genus Laelia. Considering that L. suffusa is an important pest of rice in Asia, it is important to identify its classification using molecular approaches. This information might provide further understanding of the origin and genetic differentiation with other Lepidoptera pests and a basis for biological pest control.

Phylogenetic hypothesis of the superfamily Lepidoptera revealed that there were six strongly supported clades: Noctuidae, Erebidae, Notodontidae, Euteliidae, Nolidae, and Oenosandridae (Zahiri et al. 2011). Previously, Lymantriidae was considered as a family-level classification unit, however, based on morphological and molecular evidence, it was classified as a subfamily of Erebidae (Mitter et al. 2017, Regier et al. 2017). However, the phylogenetic relationships within Lymantriinae are still under active debate. Initially, it was believed that five tribes were included in the subfamily Lymantriinae: Arctornithini, Lymantriini, Leucomini, Nygmiini, and Orgyiini (Zahiri et al. 2011, Zahiri et al. 2012, Wang et al. 2015). However, based on the phylogenetic analysis using several mitochondrial and nuclear genes, the phylogenetic relationship within Lymantriinae could be illustrated as follows: Arctornithini was a sister group to Orgyiini + Nygmiini together with Lymantriini + Leucomini (Zahiri et al. 2011, 2012; Wang et al. 2015). However, the phylogenetic relationship based on various molecular markers and taxonomy has often been found to be conflicting, leading to a serious debate on their relative positions (Fibiger and Lafontaine 2005, Mitchell et al. 2006).

Owing to some unique features as maternal inheritance, rapid mutation rate, and limited recombination compared with nuclear genes, mitochondrial DNA markers, and mitogenome have been extensively used in phylogenetic analysis, comparative genomics studies, and species identification (Avise 2009, Cameron, 2014, Qin et al. 2019, Tyagi et al. 2020). The insect mitogenome has a relatively stable structure that encodes 37 genes and a noncoding control region scattered on the circular DNA molecule and with a length of 15,000–18,000. The 37 genes generally include 13 protein-coding genes (PCGs): cytochrome c oxidase genes (cox1, cox2, and cox3), NADH dehydrogenase genes (nad1, nad2, nad3, nad4, nad4L, nad5, and nad6), cytochrome B genes (cytb), ATPase genes (atp6 and atp8), 22 transfer RNA genes (tRNAs), and 2 ribosomal RNA genes (rRNAs, rrnL and rrnS). Besides, a large noncoding region controls replication and transcription (CR region, also named A + T-rich region; Wolstenholme 1992, Ballard and Whitlock 2004, da Fonseca et al. 2008, Cameron 2014). Compared with the single molecular markers from plastids and the nuclear genome, mitogenome can provide information on evolutionary and speciation events required in insect phylogenetic studies (Boore 2006, Qin et al. 2019). Recently, the rapid development of sequencing technologies such as the next-generation sequencing technology has triggered an increase in the available mitochondrial genome data (Cameron 2014).

In this study, the complete mitogenome of L. suffusa was sequenced, annotated, and characterized. Using the newly sequenced mitogenome, phylogenetic relationships of Noctuoidea were reconstructed using both the 13 PCGs and whole genomes. The mitogenome of L. suffusa provided information for future research on species identification, diversity conservation, and population genetics of Erebidae and Noctuoidea.

Materials and Methods

Sampling and DNA Extraction

The specimens of L. suffusa were collected from Mt. Luofu, Guangdong Province, P. R. China, and identified based on morphological characteristics. All the collected samples were preserved in 95% ethanol in the field and stored at −20°C. Total genomic DNA was extracted from the leg muscle tissue using the Genomic DNA Extraction Kit (QIAGEN, Hilden, Germany) following the manufacturer’s instructions.

Mitogenome Sequencing, Assembly

The purified DNA samples were used to prepared an Illumina TruSeq library and sequenced on the Illumina HiSeq2500 platform. The sequencing platform generated a total of 15-Gb paired-end reads of 150-bp length. Trimmomatic software was used to read trimming the adapters (Fragkostefanakis et al. 2012, Bolger et al. 2014). NGSQC-Toolkit v2.3.336 software and Prinseq were used to conduct rapid quality control of the raw reads. Low quality (ambiguous bases) and short reads (shorter than 95 bp) were filtered during quality control (Schmieder and Edwards 2011). Finally, high-quality reads not less than 8 Gb were adopted in the de novo assembly and annotation using MitoZ software (Meng et al. 2019). Sequences from the cox1, cytb and rrnS fragments of L. suffusa were used as checkout markers for mitogenome assemblies and they were amplified and sequenced using PCR and Sanger sequencing, respectively.

Mitogenome Analysis

MEGA v8.0 was used to analyze the base composition and codon usage of the L. suffusa mitogenome (Kumar et al. 2016). Besides, the start and stop codons of the protein-coding genes were identified and validated by comparing with mitogenomes of other Erebidae species. tRNAscan-SE v1.21 software was used to predict the secondary structures of the 22 tRNA genes (Lowe and Chan 2016). The AT and GC asymmetry were represented by the values of AT-skew and GC-skew, calculated as follows: AT-skew = (A−T)/(A+T) and GC skew = (G−C)/(G+C) (Perna and Kocher 1995). The Tandem Repeats Finder program was used to predict the tandem repeats of the control region using the default parameters (Benson 1999).

Phylogenetic Analysis

The phylogenetic tree of 52 lepidopteran species (25 species of Erebidae, 19 species of Noctuidae, 2 species of Nolidae, 3 species of Notodontidae, single species of Euteliidae, and 2 outgroups) was reconstructed to confirm the phylogenetic position of the genus Laelia within the superfamily Noctuoidea (Table 1). We aligned nucleotide sequences of the 13 PCGs with MAFFT. The nonprotein coding regions were aligned using MUSCLE and default parameters were used (Edgar 2004). SequenceMatrix was used to concatenate the separated genes and partitions (Vaidya et al. 2011). The concatenated sets of nucleotides were organized into two datasets: one dataset included the 13 PCGs while the other represented all the 37 genes (13 PCGs, 22 tRNAs, and 2 rRNAs). DAMBE was used to examine the substitution saturations of the two datasets (Xia and Xie 2001). Both datasets were used to perform phylogenetic analyses using maximum likelihood (ML) and Bayesian inference (BI) (Ronquist and Huelsenbeck 2003). ML and BI analyses were performed using RAxML v7.9.6 and MrBayes v 3.2.2, respectively (Stamatakis 2006, Ronquist et al. 2012). The GTR+G+I model was selected in the two datasets and 1,000 bootstrap replicates were used in RaxML. BI analysis was conducted using four independent Markov chains were set to run for 10 million generations with sampling every 1,000 generations. The first 25% of the sampled trees were discarded as burn-in. All runs were stable after 10 million generations, determined by Tracer v1.5.0. FigTree v1.4.2 was used to visualize the topologies of the phylogenetic trees (Rambaut 2014).

Table 1.

Taxonomy, GenBank accession numbers, mitogenome sizes, and related information of 52 moths mitochondrial genomes used for the phylogenetic analysis

Superfamily Family Subfamily GBAN Length A+T% AT-skew GC-skew
Noctuoidea Erebidae Lymantriinae Laelia suffusa MN908152 15,502 79.0 0.015 −0.294
Lymantria dispar FJ617240 15,569 79.9 0.016 −0.248
Lymantria umbrosa KY923066 15,642 79.9 −0.015 0.251
Dasorgyia alpherakii KJ957168 15,755 81.4 0.004 −0.263
Euproctis pseudoconspersa KJ716847 15,461 79.9 0.011 −0.242
Euproctis similis KT258910 15,437 80.2 0.000 −0.243
Gynaephora menyuanensis KC185412 15,740 81.5 0.003 −0.270
Gynaephora minora KY688086 15,801 81.5 0.006 −0.269
Gynaephora jiuzhiensis KY688085 15,859 81.5 0.003 −0.272
Gynaephora ruoergensis KY688083 15,803 81.5 0.007 −0.273
Gynaephora qumalaiensis KJ507134 15,753 81.4 0.007 −0.268
Gynaephora qinghaiensis KJ507133 15,747 81.3 0.005 −0.271
Gynaephora aureata NC029162 15,773 81.4 0.006 −0.272
Aganainae Asota plana lacteata KJ173908 15,416 80.3 −0.002 −0.238
Arctiinae Amata formosae KC513737 15,463 79.5 −0.027 −0.266
Lemyra melli NC026692 15,418 78.7 0.001 −0.225
Callimorpha dominula KP973953 15,496 81.0 −0.011 −0.201
Vamuna virilis KJ364659 15,417 80.4 0.000 −0.229
Nyctemera albofasciata KM244681 15,295 80.8 −0.015 −0.227
Cyana sp. KM244679 15,494 81.2 −0.014 −0.223
Hyphantria cunea GU592049 15,481 80.4 0.010 −0.230
Calpinae Eudocima phalonia NC032382 15,575 80.7 −0.013 −0.219
Erebinae Catocala deuteronympha KJ432280 15,671 81.1 −0.022 −0.231
Grammodes geometrica KY888135 15,728 80.5 −0.003 −0.220
Hypeninae Paragabara curvicornuta KT362742 15,532 80.4 −0.008 −0.226
Noctuidae Noctuinae Sesamia inferens JN039362 15,413 80.2 −0.001 −0.230
Spodoptera frugiperda KM362176 15,365 81.1 0.004 −0.192
Spodoptera litura JQ647918 15,388 81.0 0.013 −0.195
Spodoptera exigua JX316220 15,365 80.9 0.010 −0.195
Agrotis ipsilon KF163965 15,377 81.3 −0.006 −0.177
Agrotis segetum KC894725 15,378 80.7 −0.004 −0.192
Noctua pronuba KJ508057 15,315 81.1 −0.018 −0.170
Striacosta albicosta KM488268 15,553 79.3 0.012 −0.238
Athetis lepigone MF152842 15,589 81.3 −0.024 −0.188
Mythimna separata KM099034 15,332 81.0 −0.012 −0.193
Protegira songi KY379907 15,410 80.2 0.000 −0.206
Heliothinae Helicoverpa punctigera KF977797 15,382 81.4 0.001 −0.187
Helicoverpa zea KJ930516 15,343 81.0 0.002 −0.202
Helicoverpa assulta KR149448 15,373 80.8 −0.003 −0.191
Chloridea subflexa KT598688 15,323 80.7 0.002 −0.189
Helicoverpa armigera GU188273 15,347 81.0 0.001 −0.192
Plusiinae Ctenoplusia limbirena KM244665 15,306 81.0 −0.036 −0.174
Ctenoplusia agnata KC414791 15,261 81.1 −0.024 −0.185
Acronictinae Acronicta psi KJ508060 15,350 79.1 0.034 −0.246
Euteliidae Euteliinae Eutelia adulatricoides KJ185131 15,360 80.9 −0.006 −0.184
Nolidae Chloephorinae Gabala argentata KJ410747 15,337 81.7 −0.030 −0.174
Risobinae Risoba prominens KJ396197 15,343 81.1 −0.007 −0.176
Notodontidae Pygaerinae Clostera anachoreta KX108766 15,456 80.7 −0.019 −0.217
Phalerinae Phalera flavescens JF440342 15,659 80.9 −0.009 −0.177
Thaumetopoeinae Ochrogaster lunifer AM946601 15,593 77.8 0.030 −0.318
Pyraloidea Crambidae Chilo suppressalis NC015612 15,395 80.7 0.008 −0.235
Tortricoidea Tortricidae Adoxophyes honmai NC008141 15,680 80.4 −0.001 −0.196
Open in a new tab

Note: Nyctemera arctata albofasciat was used to in sequence of KJ173908, which was modified to Nyctemera albofasciat according to subsequent revision of species list. Similarly, Heliothis subflexa of KT598688 was amended to Chloridea subflexa, and Lachana alpherakii was modified to Dasorgyia alpherakii. The species in bold was first sequenced in this study.

Result

Genome Organization and Base Composition

The L. suffusa mitogenome was a typical circular DNA molecule of 15,502 bp in length (GenBank MN908152; Table 1; Fig. 1). The newly sequenced mitogenome coded the 37 genes, 13 PCGs, 22 tRNAs, and 2 rRNAs (small ribosomal RNA [rrnS] and large ribosomal RNA [rrnL]), and the A+T-rich noncoding region (Table 2). In total, 23 genes (9 PCGs and 14 tRNAs) were transcribed on the major strand (J-strand) and the remaining 14 genes were transcribed on the minor strand (N-strand). There were 9 genes overlapping regions and 19 noncoding regions in the mitogenome of L. suffusa. Besides the control region, the largest noncoding region was located between gene trnQ and nad2, which was 73 bp in length (Table 2). The gene order of the genome was identical to that previously published of Lymantriidae mitogenome sequences (Fig. 2). The nucleotide composition of the L. suffusa sequence was highly A + T biased: A = 6,218 (40.11%), G = 1,147 (7.40%), T = 6,035 (38.93%), and C = 2,102 (13.56%) (Table 3). Furthermore, the mitogenome showed a was slightly positive AT-skew (0.015), illustrating there were more As than Ts. The GC-skew was negative (−0.294), declaring a higher frequency of base C than G when compared with other species of Noctuoidea (Table 1).

Fig. 1.

Fig. 1.

Open in a new tab

Circular map of the Laelia suffusa mitogenome. Protein coding and ribosomal genes are shown with standard abbreviations. tRNA genes are exhibited as single-letter abbreviations, except for the S1 = AGN, S2 = UCN, L1 = CUN, and L2 = UUR. The thick lines outside the circle indicate the major strand, whereas those inside the circle indicate the minor strand.

Table 2.

Annotation and gene organization of the Laelia suffusa mitogenome

Gene Strand Nucleotide number Size (bp) Intergenic nucleotides Anticodon Start codon Stop codon
trnM J 1–67 67 4 CAU – –
trnI J 72–137 66 −3 GAU – –
trnQ N 135–203 69 73 UUG – –
nad2 J 277–1,290 1014 ±2 – ATT TAA
trnW J 1,289–1,354 66 −8 UCA
trnC N 1,347–1,411 65 6 GCA
trnY N 1,418–1,482 65 −41 GUA
cox1 J 1,442–3,020 1579 3 – CGA T
trnL2(UUR) J 3,016–3,082 67 0 UAA
cox2 J 3,083–3,748 702 16 – ATA T
trnK J 3,765–3,835 71 −1 CUU
trnD J 3,835–3,902 68 0 GUC
atp8 J 3,903–4,067 165 −7 – ATA TAA
atp6 J 4,061–4,,738 678 4 – ATG TAA
cox3 J 4,743–5,531 789 2 – ATG TAA
trnG J 5,534–5,601 68 0 UCC
nad3 J 5,602–5,955 354 14 – ATA TAA
trnA J 5,970–6,035 66 12 UGC
trnR J 6,048–6,112 65 5 UCG
trnN J 6,118–6,182 65 10 GUU
trnS1(AGN) J 6,193–6,259 67 5 GCU
trnE J 6,265–6,333 69 6 UUC
trnF N 6,340–6,406 67 −20 GAA
nad5 N 6,387–8,147 1761 0 – ATA TAA
trnH N 8,148–8,215 68 −1 GUG
nad4 N 8,215–9,557 1343 14 – ATG TA
nad4l N 9,572–9,859 288 6 – ATG TAA
trnT J 9,866–9,929 64 0 UGU
trnP N 9,930–9,994 65 4 UGG
nad6 J 9,999–10,529 531 7 ATG TAA
cytb J 10,537–11,688 1152 7 ATG TAA
trnS2(UCN) J 11,696–11,760 65 19 UGA
nad1 N 11,780–12,718 939 0 ATT TAA
trnL1(CUN) N 12,719–12,787 69 −21 UAG
rrnL N 12,767–14,157 1391 0
trnV N 14,158–14,225 68 −1 UAC
rrnS N 14,225–15,022 798 0
A + T-rich 15,023–15,502 480
Open in a new tab

Strand of the genes is presented as J for majority and N for minority strand. IN, negative numbers indicate that adjacent genes overlap, positive numbers indicate intergenic sequences.

Fig. 2.

Fig. 2.

Open in a new tab

The gene order of Laelia suffusa mitogenome and other 13 lepidopteran species.

Table 3.

Base composition and skewness of the Laelia suffusa mitogenome

Size (bp) A (bp) G (bp) T (bp) C (bp) A% G% T% C% A+T% AT-Skew GC-Skew
Whole genome 15,502 6,218 1,147 6,035 2,102 40.11 7.40 38.93 13.56 79.04 0.015 −0.294
PCGs 11,295 3,739 1,307 4,945 1,304 33.10 11.57 43.78 11.54 76.88 −0.139 0.001
tRNA genes 1,470 612 160 585 113 41.63 10.88 39.80 7.69 81.43 0.023 0.172
rRNA genes 2,189 912 254 920 103 41.66 11.60 42.03 4.71 83.69 −0.004 0.422
Control region 480 203 17 223 37 42.29 3.54 46.46 7.71 88.75 −0.047 −0.370
Open in a new tab

Gene rearrangement was detected in L. suffusa mitogenome compared with species from Hepialoidea and Nepticuloidea. In L. suffusa mitogenome, the control region gene order was trnM, trnI, and trnQ, which was different from the basal lepidopteran species (such as Stigmella roborella, Ahamus yunnanensis, and Thitarodes gonggaensis) (Fig. 2).

Protein-Coding Genes and Codon Usage

The 13 PCGs were 11,295 bp in length, accounting for 72.86% of the complete L. suffusa mitogenome. Nine out of the 13 PCGs (cox1, cox2, cox3, nad2, nad3, nad6, atp6, atp8, and cytb) were scattered on the major strand, whereas four genes (nad1, nad4, nad4l, and nad5) were on the minor strand. The start and stop codons of all PCGs are shown in Table 2. The standard ATN start codon was used for most of the PCGs such as ATT for nad1, nad2, ATG for cox3, nad4, nad4l, nad6, atp6, cytb, and ATA for cox2, nad3, nad5, atp8. The only exception was in cox1 which had CGA (arginine). Three out of the 13 PCGs used incomplete stop codons (T for cox1, cox2, and TA for nad4), and only nad4 used incomplete termination codon (TA), whereas others used the typical stop codon (TAA).

The average A + T content of the 13 PCGs was 76.88%, and the AT-skew was negative (−0.139), indicating more Ts than As (Table 3). The relative synonymous codon usage of L. suffusa was tested based on the 3,605 codons in 13 PCGs, and only codons ACG, UAA, and UAG were not presented (Table 4). The codon usage analysis demonstrated that isoleucine (I; Ile; 11.26%), leucine 2 (L; Leu2; 11.15%), phenylalanine (F; Phe; 8.21%), methionine (M; Met; 6.77%), and asparagine (N; Asn; 5.46%) were the most frequently used, whereas cysteine (C; Cys; 0.78%) was the least used (Figs. 3 and 4, Table 4). Codon distribution was consistent with other lepidopteran insects mitogenome.

Table 4.

Codon usage of the protein-coding genes in Laelia suffusa

Codon (aa) n % RSCU Codon (aa) n % RSCU
UUU (F) 296 8.21 1.75 UAU (Y) 155 4.30 1.72
UUC (F) 42 1.17 0.25 UAC (Y) 25 0.69 0.28
UUA (L) 402 11.15 4.56 UAA (*) 0 0.00 0.00
UUG (L) 36 1.00 0.41 UAG (*) 0 0.00 0.00
CUU (L) 47 1.30 0.53 CAU (H) 45 1.25 1.30
CUC (L) 8 0.22 0.09 CAC (H) 24 0.67 0.70
CUA (L) 33 0.92 0.37 CAA (Q) 54 1.50 1.83
CUG (L) 3 0.08 0.03 CAG (Q) 5 0.14 0.17
AUU (I) 406 11.26 1.77 AAU (N) 197 5.46 1.63
AUC (I) 39 1.08 0.17 AAC (N) 45 1.25 0.37
AUA (M) 244 6.77 1.06 AAA (K) 78 2.16 1.70
AUG (M) 25 0.69 1.00 AAG (K) 14 0.39 0.30
GUU (V) 74 2.05 1.89 GAU (D) 58 1.61 1.84
GUC (V) 2 0.06 0.05 GAC (D) 5 0.14 0.16
GUA (V) 69 1.91 1.76 GAA (E) 60 1.66 1.64
GUG (V) 12 0.33 0.31 GAG (E) 13 0.36 0.36
UCU (S) 91 2.52 2.37 UGU (C) 24 0.67 1.71
UCC (S) 17 0.47 0.44 UGC (C) 4 0.11 0.29
UCA (S) 83 2.30 2.17 UGA (W) 85 2.36 3.00
UCG (S) 2 0.06 0.05 UGG (W) 9 0.25 1.00
CCU (P) 63 1.75 2.03 CGU (R) 16 0.44 0.71
CCC (P) 26 0.72 0.84 CGC (R) 2 0.06 0.09
CCA (P) 33 0.92 1.06 CGA (R) 32 0.89 1.41
CCG (P) 2 0.06 0.06 CGG (R) 2 0.06 0.09
ACU (T) 77 2.14 2.04 AGU (S) 36 1.00 0.94
ACC (T) 20 0.55 0.53 AGC (S) 1 0.03 0.03
ACA (T) 54 1.50 1.43 AGA (S) 83 2.30 3.66
ACG (T) 0 0.00 0.00 AGG (S) 1 0.03 0.04
GCU (A) 72 2.00 2.34 GGU (G) 49 1.36 0.97
GCC (A) 11 0.31 0.36 GGC (G) 5 0.14 0.10
GCA (A) 36 1.00 1.17 GGA (G) 110 3.05 2.17
GCG (A) 4 0.11 0.13 GGG (G) 39 1.08 0.77
Open in a new tab

In total, 3,605 codons were analyzed. RSCU stands for relative synonymous codon usage. * stands for termination codon. The codons in bold were the most commonly used in the mitogenome of L. suffusa.

Fig. 3.

Fig. 3.

Open in a new tab

The relative synonymous codon usage in the mitogenome of Laelia suffusa. Codon families are provided on the X-axis.

Fig. 4.

Fig. 4.

Open in a new tab

Codon distribution in Laelia suffusa mitogenome. Numbers to the left refer to the total number of the codon. Codon families are provided on the X-axis.

Transfer RNAs and ribosomal RNAs

The L. suffusa mitogenome contained 22 tRNA genes that were scattered throughout the entire genome. The tRNA length varied from 64 bp (trnT) to 71 bp (trnK), and this was consistent with previously reported Lepidoptera mitogenomes. In total, 14 tRNAs were encoded on the major chain and the rests were on the minor chain. The combined sequence of the 22 tRNAs was 1,470 bp, and the A + T content was 81.43% with a positive AT-skew and negative GC-skew. The A + T content of the two rRNAs genes was slightly higher than that in tRNAs, accounting for 83.69% of the total 2,189-bp sequence (Table 3).

Almost all of the 22 tRNAs formed the typical clover-leaf secondary structures, except for the trnS1(AGN) (Fig. 5). The dihydorouridine (DHU) arm of trnS1 formed a loop instead of a couple of paired bases. The amino acid acceptor (AA) arm length of the tRNAs was unified (7 bp). Several anticodons (AC) loops comprised of six nucleotides except for five tRNAs (trnC, trnI, trnK, trnR, and trnN) whose AA stem was 7 bp, as well as trnS1(AGN) with eight nucleotides. The TψC (T) length and its arm ranged from 2 to 9 bp and 4 to 5 bp, respectively. The DHU stem length varied from 3 to 4 bp except in trnS1(AGN) with 2 to 8 bp. The AC arms were all 5 bp except for trnL2(UUR) whose AC stem was 4 bp.

Fig. 5.

Fig. 5.

Open in a new tab

Putative secondary structures for the tRNA genes of the Laelia suffusa mitogenome.

Both rRNA genes were encoded on the N strand. The large ribosomal RNA (rrnL), with a length of 1,391 bp was located between trnL1 and trnV, whereas the small ribosomal RNA (rrnS), with a length of 798 bp, was located between trnV and the control region (Table 2). The rrnL and rrnS showed significant high A+T content (83.03 and 84.84%, respectively) bias; however, the AT-skew was different (−0.020 and 0.022).

Overlapping and Noncoding Regions

In total, 10 overlapping regions were detected in the L. suffusa mitogenome which varied between 1 and 41 bp. The longest overlapping region was 41 bp, located between the trnY and cox1 (Table 2). There were 19 intergenic spacers scattered throughout the L. suffusa mitogenome and ranging from 2 to 73 bp. The longest spacer region was detected to be located between gene trnQ and nad2, which was an A + T-rich region.

The control region (A + T-rich region) of L. suffusa located between the rrnS and trnM genes was the longest noncoding region (480 bp) in the entire mitogenome (Fig. 1, Table 2). This highest AT content (88.75%) was also found in this region, with a negative AT-skew (−0.047) and GC-skew (−0.370). In the L. suffusa mitogenome, an ATAGA motif close to gene rrnS was also detected and found to be a conserved feature of lepidopteran’s mitogenomes (Cameron and Whiting 2008). An 18-bp poly-T stretch following the ATAGA motif and a 12-bp poly-A string followed by trnM were reported. Three microsatellite-like repetitive elements were also found (Fig. 6).

Fig. 6.

Fig. 6.

Open in a new tab

Features present in the AT-rich region of the Laelia suffusa mitogenome. Colored nucleotides indicate the ATATA motif (yellow), the poly-T stretch (green) and microsatellite A/T repeat sequences were underlined. Three tandem repeats are indicated in different colors.

Phylogenetic Analyses

The phylogenetic relationships among the 52 Lepidoptera species (Table 1) were reconstructed based on the two nucleotide sequences (13 PCGs and 37 genes) datasets using the Maximum Likelihood (ML) and Bayesian Inference (BI) approaches. Besides, Chilo suppressalis and Adoxophyes honmai, which belong to Pyraloidea and Tortricoidea, respectively, were used as outgroups. All the other 50 species were from Noctuoidea. Phylogenetic analysis based on different algorithms (ML and BI analysis) showed approximately identical topologies. Phylogenetic relationships based on the two nucleotide datasets are shown in Figs. 7 and 8. Noctuoidea species were clustered into five families (Erebidae, Noctuidae, Euteliidae, Nolidae, and Notodontidae). The monophyly of Erebidae was well supported based on the topology of the phylogenetic tree. Within the Erebidae, the subfamilies Lymantriinae, Arctinae, and Erebinae were also monophyletic (Figs. 7 and 8). The phylogenetic relationships obtained were based on the two datasets (13 PCGs and 37 genes) and they were found to be consistent within the Noctuidae. All of the four families (Plusiinae, Heliothinae, Noctuinae, and Acronictinae) in Noctuidae were all monophyletic clades.

Fig. 7.

Fig. 7.

Open in a new tab

Phylogenetic tree inferred from nucleotide sequences of 13 PCGs of using the ML and BI analysis. Numbers on the branches are ML bootstrap support and BI posterior probability.

Fig. 8.

Fig. 8.

Open in a new tab

Phylogenetic tree inferred from nucleotide sequences of 37 genes (13 PCGs + 22tRNA + 2 rRNA) using the ML and BI analysis. Numbers on the branches are ML bootstrap support and BI posterior probability.

Besides the phylogenetic relationships among the Noctuoidae families were reconstructed, the results revealed three main clades in Lymantriinae: Nygmiini + (Lymantriini + Orgyiini). Laelia suffusa, Dasorgyia alpherakii, and seven species of Gynaephora clustered in one lineage, which supported that L. suffusa belongs to Orgyiini. Moreover, there was no clear threshold between Gynaephora and Dasorgyia due to the mixture of the two genera. Within the Lymantriinae, Orgyiini was the most closely related to Lymantriini, and Nygmiini was a sister group. Further, among these subfamilies, Hypeninae was closely related to Lymantriinae even though the support was not very strong.

Discussion

Among the 13 species of the Lymantriinae subfamily, the L. suffusa mitogenome length (15,502 bp) was slightly smaller than the others, except for E. pseudoconspersa (15,461 bp) and E. similis (15,437 bp). The difference was attributed to the variable sequences in the noncoding regions and the control region (CR) (Rand 1993, McKnight and Shafer 1997). Moreover, the positive AT-skew (0.015) was associated with a higher frequency of guanine compared with thymine, which is a common phenomenon in Noctuoidea mitogenomes.

Gene rearrangement was also detected in L. suffusa when compared with the basal taxon of Lepidoptera, such as Hepialoidea and Nepticuloidea (Fig. 2). In lepidopteran mitogenomes, gene rearrangement mainly occurred in three tRNA genes: trnM, trnI, trnQ (Timmermans and Vogler 2012), as identified in the L. suffusa mitogenome. Only two mitogenomes from Nepticuloidea were chosen for the gene rearrangement analysis, and the results were inconsistent. Astrotischeria sp. showed a similar pattern of L. suffusa. However, Thitarodes gonggaensis (The other species chosen from Nepticuloidea) shared similar gene order with Hepialoidea, which was considered to be the ancestral pattern (CR-trnI-trnQ-trnM) (Fig. 2; Zhu et al. 2017, Yang et al. 2019). Based on the phylogenetic results of Mitter et al. (2017), this gene rearrangement likely occurred after the diverging of Hepialoidea superfamily from other lepidopteran lineages. Many models and hypotheses have been used to explain the mitogenome gene rearrangement, such as the tandem duplication-random loss (TDRL) model (Boore 2000), the duplication-nonrandom loss model (Lavrov et al. 2002), and the recombination (Cantatore et al. 1987) and illicit priming of replication by tRNA genes (Dowton et al. 2009). The gene rearrangement of L. suffusa mitogenome can be well explained by a combination of the TDRL model and recombination.

The AT-skew value of the 13 PCGs was −0.139 in the L. suffusa mitogenome was lower than that reported in previously sequenced Lymantriinae mitogenomes. Meanwhile, the slightly positive GC-skew of 0.001 was also higher than that reported in other species. The gene cox1 had a different start codon (CGA) compared with the other 12 protein-coding genes and this is similar to other Lymantriinae insects (Yuan et al. 2018). The incomplete stop codons were observed in Lepidoptera mitogenomes (Ronquist and Huelsenbeck 2003, Stamatakis 2006, Ronquist et al. 2012, Yuan et al. 2018). In the newly sequenced mitogenome, three genes were associated with the incomplete stop codons. For example, cox1 and cox2 used single T and nad4 used TA. The common interpretation for the high frequency of the TAA stop codon is that the TAA terminator is created via post-transcriptional polyadenylation (Ojala et al. 1981). All tRNA genes were predicted to have formed the typical clover-leaf structure, except for trnS1, whose dihydorouridine (DHU) arm formed a loop instead of a couple of paired bases. This is a universal phenomenon occurring in insect mitogenomes and metazoan mitogenomes (Wolstenholme 1992, Ronquist and Huelsenbeck 2003, Stamatakis 2006, Ronquist et al. 2012, Tang et al. 2017). Furthermore, the intergenic spacer located between atp6 and atp8 contained a conserved seven-nucleotide structure (ATGATAA), which is also reported in other lepidopteran mitogenomes. This implies a stable evolutionary structure and potential molecular marker for Lepidoptera of mitogenome (Stamatakis 2006, Ronquist et al. 2012). Noctuoidea is the largest in the Lepidoptera superfamily and includes 4,200 genera and up to 42,400 species (Kitching and Rawlins 1998). Currently, it was widely believed that there were six families in Noctuoidea: Oenosandridae (include 4 genera), Notodontidae (704 genera), Erebidae (1,760 genera), Euteliidae (29 genera), Nolidae (186 genera), and Noctuidae (704 genera) (Kitching and Rawlins 1998; Zahiri et al. 2011, 2012). However, a change in the molecular markers or sampling taxon might lead to different phylogenetic structures. The phylogenetic relationship among the families within Noctuoidea has been debated for a long time (Liu et al. 2016). The monophyly of Noctuidae was confirmed based on the morphological characteristics of the adult and larva; however, the relationships among subfamilies and genera showed poor resolutions (Speidel et al. 1996, Fibiger et al. 2005, Zahiri et al. 2011). Zahiri et al. (2011) revealed that the phylogenetic relationship of Noctuidae was as follows: (Notodontidae + (Euteliidae + (Noctuidae + (Erebidae + Nolidae). This study was based on a single mitochondrial gene (cox1) and seven nuclear genes. However, different taxon and molecular markers have been identified various phylogenetic relationships, including (Notodontidae + (Noctuidae + (Nolidae + (Erebidae +Euteliidae)))) (Mitchell et al. 2006); (Notodontidae + (Nolidae + (Noctuidae + (Erebidae +Euteliidae)))) (Fibiger et al. 2005); (Notodontidae + (Erebidae + (Noctuidae + (Euteliidae + Nolidae)))) (Regier et al. 2017).

In this study, the robust phylogenetic relationships obtained based on the two datasets were similar. The relationships of Noctuoidea were described as (Notodontidae + (Erebidae + (Nolidae + (Noctuidae +Euteliidae). These results were consistent with those reported recently, supporting that Noctuoidae and Euteliidae were the closest taxa, and the Notodontidae was the ancestral family in Noctuoidea (Zahiri et al. 2011, Yang et al. 2019).

The concatenated nucleotide sequences of the 13 PCGs and 37 genes using ML and BI methods provided a well-supported outline of Erebidae. The 25 species of Erebidae were divided into two groups: Erebinae + Calpinae + Aganainae +Arctiinae, which were clustered as one group, and the other two subfamilies Lymantriinae and Hypeninae clustered in the other group and these findings were similar to those reported in previous studies (Zahiri et al. 2011, 2012; Wang et al. 2015). Initially, L. suffusa was classified into the family Lymantriidae, which later became Erebidae, and subfamily Lymantriinae (Mitter et al. 2017, Regier et al. 2017). These findings provide strong evidence for the classification of L. suffusa, which belongs to the Orgyiini of Lymantriinae. All the 13 species of Lymantriinae clustered into a stable monophyletic group which was supported with strong evidence (PP = 1.0, BS = 100). There were three sister clades included in this group: the first one included L. suffusa as a sister group of the Dasorgyia alpherakii and the genus Gynaephora, which was well supported (PP = 1.0, BS = 100) by ML and BI analysis; and in the second clade, Euproctis similis was at the basal position and a sister to Lymantria dispar + Lymantria umbrosa; in the last clade, a single species Euproctis pseudoconspersa, was the basal taxa of Lymantriinae. However, the evolutionary history and phylogenetic relationship of Erebidae and Lymantriinae have attracted great attention and remained unclear (Kitching and Rawlins 1998, Mitter et al. 2017, Regier et al. 2017). Therefore, more advanced studies using larger sample sizes and genetic information are imperative to solve the phylogenetic relationship of Noctuoidea.

Acknowledgments

This work was sponsored by the Natural Science Foundation of China (31772501 and 31400191), China National Funds for Distinguished Young Scientists (31425023), Program of Ministry of Science and Technology of China (2018FY100403), Academy for Multidisciplinary Studies, Capital Normal University to Ai-bing ZHANG, Capacity Building for Sci-Tech Innovation- Fundamental Scientific Research Funds (No. 20530290051), Joint Fund of the Beijing Municipal Natural Science Foundation and Beijing Municipal Education Commission (KZ 201810028046), Beijing Municipal Natural Science Foundation (517200).

Author Contributions

AB Zhang and JL conceived the original idea. QL carried out the experiment. JL wrote the manuscript with support from HLH and ABZ. XMZ offered great in data analysis.

References Cited

  1. Ahmed, N., M. Z.  Hasan, and Z.  Islam. . 2002. Rice Hairy Caterpillar, Laelia suffusa Walker (Lepidoptera: Lymantriidae), a new recorded rice defoliator in Bangladesh. SAIC Newsletter. 12: 9. [Google Scholar]
  2. Armstrong, K. F., P.  McHugh, W.  Chinn, E. R.  Frampton, and P. J.  Walsh. . 2003. Tussock moth species arriving on imported used vehicles determined by DNA analysis. New Zealand Plant Protect. 56: 16–20. [Google Scholar]
  3. Avise, J. C 2009. Phylogeography: retrospect and prospect. J. Biogeogr. 36: 3–15. [Google Scholar]
  4. Ballard, J. W., and M. C.  Whitlock. . 2004. The incomplete natural history of mitochondria. Mol. Ecol. 13: 729–744. [DOI] [PubMed] [Google Scholar]
  5. Benson, G 1999. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 27: 573–580. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Bolger, A. M., M.  Lohse, and B.  Usadel. . 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 30: 2114–2120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Boore, J. L 2000. The duplication/random loss model for gene rearrangement exemplified by mitochondrial genomes of deuterostome animals. Comp. Genomics. 12: 133–147. [Google Scholar]
  8. Boore, J. L 2006. The use of genome-level characters for phylogenetic reconstruction. Trends Ecol. Evol. 21: 439–446. [DOI] [PubMed] [Google Scholar]
  9. Cameron, S. L 2014. Insect mitochondrial genomics: implications for evolution and phylogeny. Annu. Rev. Entomol. 59: 95–117. [DOI] [PubMed] [Google Scholar]
  10. Cameron, S. L., and M. F.  Whiting. . 2008. The complete mitochondrial genome of the tobacco hornworm, Manduca sexta, (Insecta: Lepidoptera: Sphingidae), and an examination of mitochondrial gene variability within butterflies and moths. Gene. 408: 112–123. [DOI] [PubMed] [Google Scholar]
  11. Cantatore, P., M. N.  Gadaleta, M.  Roberti, C.  Saccone, and A. C.  Wilson. . 1987. Duplication and remoulding of tRNA genes during the evolutionary rearrangement of mitochondrial genomes. Nature. 329: 853–855. [DOI] [PubMed] [Google Scholar]
  12. Chao, C. L 1987. Economic insect fauna of China (in Chinese). Science Press, Beijing, China. [Google Scholar]
  13. Chao, C. L 2003. Fauna sinica insect (in Chinese), Beijing. Science Press, Beijing, China. [Google Scholar]
  14. Dowton, M., S. L.  Cameron, J. I.  Dowavic, A. D.  Austin, and M. F.  Whiting. . 2009. Characterization of 67 mitochondrial tRNA gene rearrangements in the Hymenoptera suggests that mitochondrial tRNA gene position is selectively neutral. Mol. Biol. Evol. 26: 1607–1617. [DOI] [PubMed] [Google Scholar]
  15. Dubois, N. R., and D. H.  Dean. . 1995. Synergism between cryia insecticidal crystal proteins and spores of bacillus thuringiensis, other bacterial spores, and vegetative cells against Lymantria dispar (Lepidoptera: Lymantriidae) Larvae. Environ. Entomol. 24: 1741–1747. [Google Scholar]
  16. Edgar, R. C 2004. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics. 5: 113. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Fibiger, M., and J. D.  Lafontaine. . 2005. A review of the higher classification of the Noctuoidea (Lepidoptera) with special reference to the Holarctic fauna. Esperiana. 11: 7–92. [Google Scholar]
  18. da Fonseca, R. R., W. E.  Johnson, S. J.  O’Brien, M. J.  Ramos, and A.  Antunes. . 2008. The adaptive evolution of the mammalian mitochondrial genome. BMC Genomics. 9: 119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Fox, R 2013. The decline of moths in Great Britain: a review of possible causes. Insect. Conserv. Div. 6: 5–19. [Google Scholar]
  20. Fragkostefanakis, S., F.  Dandachi, and P.  Kalaitzis. . 2012. Expression of arabinogalactan proteins during tomato fruit ripening and in response to mechanical wounding, hypoxia and anoxia. Plant Physiol. Biochem. 52: 112–118. [DOI] [PubMed] [Google Scholar]
  21. Ju, R. T., Y. Y.  Chen, L.  Gao, and B.  Li. . 2016. The extended phenology of Spartina invasion alters a native herbivorous insect’s abundance and diet in a Chinese salt marsh. Biol. Invasions. 18: 2229–2236. [Google Scholar]
  22. Kitching, I. J., and J. E.  Rawlins. . 1998. The Noctuoidea. Walter de Gruyter, New York. [Google Scholar]
  23. Kristensen, N. P., M. J.  Scoble, and O.  Karsholt. . 2007. Lepidoptera phylogeny and systematics: the state of inventorying moth and butterfly diversity. Zootaxa. 1668: 699–747. [Google Scholar]
  24. Kumar, S., G.  Stecher, and K.  Tamura. . 2016. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 33: 1870–1874. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Lavrov, D. V., J. L.  Boore, and W. M.  Brown. . 2002. Complete mtDNA sequences of two millipedes suggest a new model for mitochondrial gene rearrangements: duplication and nonrandom loss. Mol. Biol. Evol. 19: 163–169. [DOI] [PubMed] [Google Scholar]
  26. Li, H. K., and J. Y.  Yan. . 1991. A study of Paecilomyces farinousu on Laelia coenosa.  Nat. Enem. Insects. 13: 51–53. [Google Scholar]
  27. Liu, Q. N., X. Y.  Chai, D. D.  Bian, B. M.  De, C. L.  Zhou, and B. P.  Tang. . 2016. The complete mitochondrial genome of fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae). Genes. Genomics  38: 205–216. [Google Scholar]
  28. Lowe, T. M., and P. P.  Chan. . 2016. tRNAscan-SE On-line: search and contextual analysis of transfer RNA genes. Nucleic. Acids. Res. 44: 54–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. McKnight, M. L., and H. B.  Shaffer. . 1997. Large, rapidly evolving intergenic spacers in the mitochondrial DNA of the salamander family Ambystomatidae (Amphibia: Caudata). Mol. Biol. Evol. 14: 1167–1176. [DOI] [PubMed] [Google Scholar]
  30. Meng, G., Y.  Li, C.  Yang, and S.  Liu. . 2019. MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization. Nucleic Acids Res. 47: e63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Mitchell, A., C.  Mitter, and J. C.  Regier. . 2006. Systematics and evolution of the cutworm moths (Lepidoptera: Noctuidae): evidence from two protein-coding nuclear genes. Syst. Entomol. 31:21–46. [Google Scholar]
  32. Mitter, C., D. R.  Davis, and M. P.  Cummings. . 2017. Phylogeny and evolution of Lepidoptera. Annu. Rev. Entomol. 62: 265–283. [DOI] [PubMed] [Google Scholar]
  33. Mullen, G. R., and J. M.  Zaspel. . 2019. Moths and Butterflies (Lepidoptera) in Medical and Veterinary Entomology, third edition. Academic Press, New York. [Google Scholar]
  34. Ojala, D., J.  Montoya, and G.  Attardi. . 1981. tRNA punctuation model of RNA processing in human mitochondria. Nature. 290: 470–474. [DOI] [PubMed] [Google Scholar]
  35. Perna, N. T., and T. D.  Kocher. . 1995. Patterns of nucleotide composition at fourfold degenerate sites of animal mitochondrial genomes. J. Mol. Evol. 41: 353–358. [DOI] [PubMed] [Google Scholar]
  36. Pogue, M. G 2009. Lepidoptera biodiversity.  Blackwell Science Publishing, Oxford, United Kingdom. [Google Scholar]
  37. Qin, J., J.  Li, Q.  Gao, J. J.  Wilson, and A. B.  Zhang. . 2019. Mitochondrial phylogeny and comparative mitogenomics of closely related pine moth pests (Lepidoptera: Dendrolimus). Peerj. 7: e7317. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Rambaut, A 2014. FigTree 1.4. 2 software. Institute of Evolutionary Biology, University of Edinburgh, United Kingdom. [Google Scholar]
  39. Rand, D. M 1993. Endotherms, ectotherms, and mitochondrial genome size variation. J. Mol. Evol. 37: 281–295. [DOI] [PubMed] [Google Scholar]
  40. Regier, J. C., C.  Mitter, K.  Mitter, M. P.  Cummings, A. L.  Bazinet, W.  Hallwachs, D. H.  Janzen, and A.  Zwick. . 2017. Further progress on the phylogeny of Noctuoidea (Insecta: Lepidoptera) using an expanded gene sample. Syst. Entomol. 42: 82–93. [Google Scholar]
  41. Ronquist, F., and J. P.  Huelsenbeck. . 2003. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics. 19: 1572–1574. [DOI] [PubMed] [Google Scholar]
  42. Ronquist, F., M.  Teslenko, P.  van der Mark, D. L.  Ayres, A.  Darling, S.  Höhna, B.  Larget, L.  Liu, M. A.  Suchard, and J. P.  Huelsenbeck. . 2012. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 61: 539–542. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Schmieder, R., and R.  Edwards. . 2011. Quality control and preprocessing of metagenomic datasets. Bioinformatics. 27: 863–864. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Scoble, M. J 1992. The Lepidoptera: form, function and diversity. Oxford University Press, Oxford, United Kingdom. [Google Scholar]
  45. Singh, K. A., and K.  Navkiran. . 2019. Studies on internal genitalic features of two species of genus Laelia Stephens (Lymantriidae: Lepidoptera) from India. J. Entomol. Res. 43: 387–390. [Google Scholar]
  46. Speidel, W., H.  Fanger, and C. M.  Naumann. . 1996. The phylogeny of the Noctuidae (Lepidoptera). Syst. Entomol. 21: 219–251. [Google Scholar]
  47. Stamatakis, A 2006. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics. 22: 2688–2690. [DOI] [PubMed] [Google Scholar]
  48. Sun, K. K., W. S.  Yu, J. J.  Jiang, C.  Richards, S.  Evan, J.  Ma, B.  Li, and R. T.  Ju. . 2020. Mismatches between the resources for adult herbivores and their offspring suggest invasive Spartina alterniflora is an ecological trap. J. Ecol. 108:719–732. [Google Scholar]
  49. Tang, B. P., Z. Z. Xin, Y. Liu, D. Z. Zhang, Z. F. Wang, H. B. Zhang, X. Y. Chai, C. L. Zhou, and Q. N. Liu. 2017. The complete mitochondrial genome of Sesarmops sinensis reveals gene rearrangements and phylogenetic relationships in Brachyura. PLoS One. 12: e0179800. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Timmermans, M. J., and A. P.  Vogler. . 2012. Phylogenetically informative rearrangements in mitochondrial genomes of Coleoptera, and monophyly of aquatic elateriform beetles (Dryopoidea). Mol. Phylogenet. Evol. 63: 299–304. [DOI] [PubMed] [Google Scholar]
  51. Tyagi, K., R.  Chakraborty, S. L.  Cameron, A. D.  Sweet, K.  Chandra, and V.  Kumar. . 2020. Rearrangement and evolution of mitochondrial genomes in Thysanoptera (Insecta). Sci. Rep. 10: 695. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Vaidya, G., D. J.  Lohman, and R.  Meier. . 2011. SequenceMatrix: concatenation software for the fast assembly of multi-gene datasets with character set and codon information. Cladistics. 27: 171–180. [DOI] [PubMed] [Google Scholar]
  53. Wang, H. S., N.  Wahlberg, J. D.  Holloway, J.  Bergsten, X. L.  Fan, D. H.  Janzen, W.  Hallwachs, L. J.  Wen, W.  Wang, and S.  Nylin. . 2015. Molecular phylogeny of Lymantriinae (Lepidoptera, Noctuoidea, Erebidae) inferred from eight gene regions. Cladistics. 31: 579–592. [DOI] [PubMed] [Google Scholar]
  54. Wolstenholme, D. R 1992. Animal mitochondrial DNA: structure and evolution. Int. Rev. Cytol. 141: 173–216. [DOI] [PubMed] [Google Scholar]
  55. Xia, X., and Z.  Xie. . 2001. DAMBE: software package for data analysis in molecular biology and evolution. J. Hered. 92: 371–373. [DOI] [PubMed] [Google Scholar]
  56. Yanar, O., S.  Gömeç, E. F.  Topkara, G.  Solmaz, and I.  Demir. . 2017. The effect of plant quality on survival of Lymantria dispar larvae infected by Bacillus thuringiensis.  Appl. Ecol. Env. Res. 15: 837–847. [Google Scholar]
  57. Yang, Z. H., T. T.  Yang, Y.  Liu, H. B.  Zhang, B. P.  Tang, Q. N.  Liu, and Y. F.  Ma. . 2019. The complete mitochondrial genome of Sinna extrema (Lepidoptera: Nolidae) and its implications for the phylogenetic relationships of Noctuoidea species. Int. J. Biol. Macromol. 137: 317–326. [DOI] [PubMed] [Google Scholar]
  58. Yu, W. S., Y. L.  Guo, K. K.  Jiang, K. K.  Sun, and R. T.  Ju. . 2019. Comparison of the life history of a native insect Laelia coenosa with a native plant Phragmites australis and an invasive plant Spartina alterniflora. Biodivers. Sci. 27: 433–438. [Google Scholar]
  59. Yuan, M. L., Q. L.  Zhang, L.  Zhang, C. L.  Jia, X. P.  Li, X. Z.  Yang, and R. Q.  Feng. . 2018. Mitochondrial phylogeny, divergence history and high-altitude adaptation of grassland caterpillars (Lepidoptera: Lymantriinae: Gynaephora) inhabiting the Tibetan Plateau. Mol. Phylogenet. Evol. 122: 116–124. [DOI] [PubMed] [Google Scholar]
  60. Zahiri, R., I. J.  Kitching, J. D.  Lafontaine, M.  Mutanen, L.  Kaila, J. D.  Holloway, and N.  Wahlberg. . 2011. A new molecular phylogeny offers hope for a stable family level classification of the Noctuoidea (Lepidoptera). Zoo. Scri. 40: 158–173. [Google Scholar]
  61. Zahiri, R., J. D.  Holloway, I. J.  Kitching, J. D.  Lafontaine, M.  Mutanen, and N.  Wahlberg. . 2012. Molecular phylogenetics of Erebidae (Lepidoptera, Noctuoidea). Syst. Entomol. 37: 102–124. [Google Scholar]
  62. Zapletalová, L., M.  Zapletal, and M.  Konvička. . 2016. Habitat impact on ultraviolet reflectance in moths. Environ. Entomol. 12: 1–6. [DOI] [PubMed] [Google Scholar]
  63. Zhang, J., R.  Ju, H.  Pan, S. F.  Pan, and J.  Wu. . 2019. Enemy-free space is important in driving the host expansion of a generalist herbivore to an inferior exotic plant in a wetland of Yangtze Estuary. Biol. Invasions. 21: 547–559. [Google Scholar]
  64. Zhu, X. Y., Z. Z.  Xin, Y.  Wang, H. B.  Zhang, D. Z.  Zhang, Z. F.  Wang, C. L.  Zhou, B. P.  Tang, and Q. N.  Liu. . 2017. The complete mitochondrial genome of Clostera anachoreta (Lepidoptera: Notodontidae) and phylogenetic implications for Noctuoidea species. Genomics. 109: 221–226. [DOI] [PubMed] [Google Scholar]

Articles from Journal of Insect Science are provided here courtesy of University of Wisconsin Libraries

RESOURCES