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. 2025 Sep 1;15(9):e72094. doi: 10.1002/ece3.72094

Complete Mitochondrial Genomes and Phylogenetic Relationships of Myotis siligorensis and Myotis laniger

Xiao‐Die Chen 1, Cheng‐He Sun 1,✉, Tai‐Yu Chen 1, Zhen‐Yu Sun 1, Chang‐Hu Lu 1,✉
PMCID: PMC12401660  PMID: 40904373

ABSTRACT

Bats belong to the order Chiroptera, which represents the second most diverse order among mammals. Bats provide critical ecosystem services through mosquito population control, suppression of agricultural arthropod pests, pollination facilitation, and seed dispersal, while also contributing to human health preservation and economic well‐being. Moreover, they have an essential function in the ecosystem of the Earth. However, the NCBI database contains 36 mitochondrial genomes of the genus Myotis Kaup, 1829, and additional data are necessary to conserve the species diversity. To elucidate the phylogenetic positions of Myotis siligorensis (Horsfield, 1855) and Myotis laniger Peters, 1870 within Myotis, high‐throughput sequencing technology was employed in this study to obtain the mitochondrial genomes of these two species and to reconstruct a phylogenetic tree of this genus based on 13 protein‐coding genes (PCGs). The mitochondrial genomes of M. siligorensis and M. laniger were determined to be 17,067 and 17,104 base pairs in length, respectively, including 22 transfer RNA genes, 13 PCGs, 2 ribosomal RNAs, and a D‐loop. Base composition revealed a marked preference for A and T nucleotides, with the highest A + T content in the D‐loop (65.6%). Using Bayesian inference and maximum likelihood methods to reconstruct the phylogenetic tree, the results indicated that Myotis is monophyletic, with early speciation events occurring within the group. M. siligorensis , Myotis davidii (Peters, 1869) and M. laniger formed one clade, with M. siligorensis and M. davidii exhibiting a closer phylogenetic relationship with each other than with M. laniger . Our analytical data enhance the foundational database of Myotis mitochondrial genomes, enhancing our understanding of the evolutionary relationships among species within this genus. Highlighting the evolutionary relationships among different species of Myotis provides a solid foundation for subsequent studies on the adaptive evolution and selective pressure in bats.

Keywords: bat, evolutionary relationships, mitochondrial genome, Myotis, phylogenetic analysis

The complete mitochondrial genome of Myotis siligorensis and Myotis laniger with comments on its characteristics and phylogenetic.

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1. Introduction

The order Chiroptera, commonly known as bats, is classified under the class Mammalia and is divided into two suborders, Yinpterochiroptera and Yangochiroptera (Hao et al. 2024), encompassing more than 1400 species (Abdurahman et al. 2024). This makes them the second most diverse group of mammals, being the only true flying mammals. Bat species are widely distributed globally, except in Antarctica, with species diversity and numbers decreasing from low to high latitudes and increasing in tropical regions (Fang et al. 2020). Moreover, they have unique biological traits such as echolocation, flight, and longevity (Wang et al. 2017), and are known to harbor various zoonotic viruses (Yan et al. 2021). The interplay between genetic and phenotypic characteristics constitutes a significant model system (Wilkinson et al. 2021) that provides indispensable components for ecosystem functionality, and is a robust indicator of environmental health (Gibb et al. 2020).

The genus Myotis, belonging to the order Chiroptera, suborder Yangochiroptera, and family Vespertilionidae, according to the “bat species of the world: a taxonomic and geographic database” (Simmons and Cirranello 2025), there are about 139 species of bats. Which are found on all continents except Antarctica. These species occupy diverse ecological niches and exhibit a range of dietary specializations (Korstian et al. 2022), primarily being insectivorous, with some species exhibiting unique dietary habits, such as the fish‐eating Myotis ricketti (Hao 2019). Furthermore, they play crucial roles in controlling nocturnal pests and maintaining ecosystem stability (Martínez‐Fonseca et al. 2024). However, their low reproductive rates and sensitivity to environmental changes indicate that species diversity can be severely threatened by multiple factors (Bogoni et al. 2021). The challenge of classifying this genus is exacerbated by the limited availability of genetic sequence databases (Frick et al. 2020), making molecular species identification and phylogenetic analysis crucial for assessing biodiversity and formulating conservation strategies.

Advancements in modern scientific technology have led to the widespread use of molecular methods for species identification and phylogenetic analysis. Genes such as COX1, CYTB, and 16S rRNA in the mitochondrial genome have been extensively studied because of their sequence length, evolutionary rate, and inheritance patterns (Zhang et al. 2022). The mammalian mitochondrial genome has a specific structure and composition, and contains various genes and control regions, including protein‐coding genes (PCGs), ribosomal RNA (rRNA), transfer RNA (tRNA), and D‐loop (Zhang et al. 2020). Guan et al. (2025) systematically elucidated the phylogenetic relationships within the order Chiroptera by integrating 219 mitochondrial genomes (covering 187 bat species, including 54 newly sequenced) and 200 orthologous nuclear genes, and Zhang (2020) re‐sequenced the OXPHOS‐associated genes in bats, suggesting that energy metabolism genes are significant factors in the origin of bat flight. Mitochondrial genomes offer high‐resolution information, which is more conducive to constructing phylogenetic trees and analyzing species relationships (Monzel et al. 2023). However, the NCBI database currently contains 36 mitochondrial genomes of Myotis (Martínez‐Cárdenas et al. 2024). Accordingly, further enrichment and improvement of the mitochondrial genome database are necessary to conserve the diversity of Chiroptera species.

In this study, high‐throughput sequencing technology was employed to assess the mitochondrial genomes of two Myotis species and analyze their genetic compositions and structural characteristics. The obtained data were integrated with 36 published Myotis mitochondrial genomes in the NCBI database to ascertain their phylogenetic relationships. We constructed a phylogenetic tree to explore the phylogenetic relationships and evolutionary status of Myotis, providing foundational data for updating its taxonomic system. This study also provides a theoretical foundation for the effective conservation of Vespertilionidae biodiversity and the scientific evaluation of germplasm resources, advancing research and practical applications in related fields.

2. Materials and Methods

2.1. Sample Collection

All specimens in this study were collected in accordance with Chinese laws. The specimens were collected, sampled, reviewed, and approved by the Animal Ethics Committee of Nanjing Forestry University. All the experiments were conducted with respect to animal welfare and care. Specimens of Myotis siligorensis and Myotis laniger , both from the Fangshan Scenic Area in Nanjing, Jiangsu Province (118.873358° E, 31.895283° N), were sourced from roadkill carcasses obtained during the faunal surveys. Detailed information on the specimens is provided (Table 1). These specimens were preliminarily identified based on morphological analysis, which entailed an assessment of physical characteristics such as body size, facial features, ear morphology, and rostral structure, as well as measured fundamental skeletal and wing length data. M. siligorensis is characterized by its smaller stature, deep brown basal fur on the back, black basal fur on the ventral side, ears that fold forward to reach the rostrum, a furry snout, and smaller hind limbs (Ding et al. 2024). In contrast, M. laniger has a smaller physique, with dark brown fur on the head and back, blackish‐brown ventral fur, elongated ears that can reach the rostrum when folded forward, a lack of dense long fur on the snout, and relatively long hind limbs (Yang et al. 2022).

TABLE 1.

Information on the collection of the two Myotis species specimens.

Specimen number Species Sampling time Longitude and latitude
FS‐1 Myotis siligorensis 2024.09.28 118.873358° E, 31.895283° N
FS‐2 Myotis laniger 2024.09.28
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2.2. DNA Extraction

Genomic DNA was extracted from muscle tissue using DNAiso Reagent from Takara Biomedical Technology (Beijing) Co. Ltd. following the manufacturer's instructions, and stored at −20°C. To verify the accuracy of morphological identification, the primers CYTB‐F (5′‐TAG AAT ATC AGC TTT GGG TG‐3′) and CYTB‐R (5′‐AAA TCA CCG TTG TAC TTC AAC‐3′) (Xin et al. 2009) were used to amplify the CYTB gene in both Myotis specimens. The amplicons were sequenced at Nanjing Qingke Biological Company, and the results were subjected to BLAST alignment via NCBI, which confirmed that specimen FS‐1 corresponded to M. siligorensis and specimen FS‐2 corresponded to M. laniger .

2.3. Mitochondrial Genome Sequencing and Assembly

Muscular tissue samples were submitted to Nanjing Personalbio Technology Co. Ltd. for next‐generation sequencing. Using the Illumina NovaSeq 6000 platform, a genomic DNA library with insert fragments of 350 bp was constructed and sequenced to a depth of 8× (15G). After sequencing, the raw read data generated using the PE150 strategy were exported in the FASTQ format. Subsequently, the reads were processed using Fastp v.0.19.7 (Chen et al. 2018) to filter out adapter, highly repetitive, N‐rich, and low‐quality reads. Thereafter, the mitochondrial genomes were assembled using Geneious 2024 utilizing the “Map to Reference” tool, and the mitochondrial genome of Myotis davidii (NC_025568) was used as the reference sequence (Wang et al. 2016). Following assembly, ORFfinder and BLAST from the NCBI database were used to predict and annotate 13 PCGs, whereas tRNAscan‐SE identified 22 tRNA genes and their corresponding secondary structures. To ensure accuracy, all genes were manually inspected using MITOS WebServer (Bernt et al. 2013). Sequence alignment analysis was performed using MEGA v11. The mitochondrial genomes of M. siligorensis and M. laniger were visualized using the MITOfish and MITOS platforms.

2.4. Sequence Analysis

To ascertain the base compositions of the genomes, MEGA v11 was utilized to calculate the base content and nucleotide skew, according to the formulas “AT‐skew = (A − T)/(A + T)” and “GC‐skew = (G − C)/(G + C)”. The evolutionary characteristics of the genomes were further analyzed using DNAsp (Librado and Rozas 2009), and the rate of evolution was assessed based on the Ka/Ks ratio. The analysis of codon usage was conducted using MEGA v11 to calculate the relative synonymous codon usage (RSCU), and PhyloSuite v1.2.3 (Zhang et al. 2020) was employed to visualize the results. The Mauve multiple genome alignment method (Darling et al. 2004) within Geneious 2024 (Kearse et al. 2012) was applied to detect rearrangements and collinearity in the mitochondrial genomes, with the degree of collinearity between the two species serving as a measure of evolutionary distance, thereby allowing for analysis of the phylogenetic relationships between the species.

2.5. Phylogenetic Analysis

Using Bayesian inference (BI) and maximum likelihood (ML) methods, 38 effective mitochondrial genomes from Myotis, along with the mitochondrial genomes of Vespertilio sinensis (KM092493) and Harpiocephalus harpia (MN885881) as outgroups, were used to reconstruct the phylogenetic tree based on the 13 PCGs, as shown in Table 2. Construct phylogenetic trees using amino acid sequences. All operations were completed using PhyloSuite v1.2.3, which involved downloading GenBank sequences from NCBI, importing and curating them in PhyloSuite v1.2.3, conducting multiple sequence alignments of PCGs with MAFFT, followed by optimization with MACSE, and trimming with Gblocks. The ModelFinder (Kalyaanamoorthy et al. 2017) BIC criterion model was further selected, and BI and ML methods were applied to each dataset for phylogenetic analysis. Model selection using BIC identified GTR + F + I + G4 and GTR + F + R4 as optimal models for BI and ML analyses, respectively. The BI tree was constructed using MrBayes 3.2.6, running for 5,000,000 generations (Huelsenbeck and Ronquist 2001), and the ML tree was constructed using IQ‐TREE, with 5000 ultrafast bootstrap replicates (Nguyen et al. 2015).

TABLE 2.

Mitochondrial genome information for the 38 Myotis species and two outgroup species involved in this study.

Family Genus Species Size (bp) Accession No.
Vespertilionidae Myotis Myotis californicus 16,972 MF143469
Myotis melanorhinus 17,018 MF143489
Myotis dasycneme 17,024 MN122855
Myotis daubentonii 17,116 MN122860
Myotis blythii 16,752 MT588108
Myotis mystacinus 16,168 MT628544
Myotis formosus 17,159 NC_015828
Myotis ikonnikovi 16,584 NC_022698
Myotis brandtii 17,470 NC_025308
Myotis davidii 17,531 NC_025568
Myotis bombinus 17,128 NC_029342
Myotis myotis 17,213 NC_029346
Myotis muricola 17,224 NC_029422
Myotis lucifugus 17,038 NC_029849
Myotis bechsteinii 17,151 NC_034227
Myotis dominicensis 16,999 NC_036312
Myotis evotis 17,039 NC_036313
Myotis keaysi 17,057 NC_036314
Myotis ruber 16,984 NC_036315
Myotis oxyotus 17,067 NC_036316
Myotis riparius 17,074 NC_036317
Myotis nigricans 17,067 NC_036318
Myotis yumanensis 17,268 NC_036319
Myotis auriculus 17,289 NC_036320
Myotis leibii 16,997 NC_036321
Myotis atacamensis 17,100 NC_036324
Myotis horsfieldii 17,083 NC_036325
Myotis volans 17,443 NC_036326
Myotis albescens 17,126 NC_036327
Myotis martiniquensis 17,170 NC_036328
Myotis frater 17,089 NC_041638
Myotis septentrionalis 17,150 NC_049871
Myotis ricketti 17,098 NC_056111
Myotis petax 17,299 NC_056773
Myotis aurascens 16,771 NC_060697
Myotis nattereri 17,213 OP919323
Myotis siligorensis 17,067 PQ496902
Myotis laniger 17,104 PQ496903
Vespertilio Vespertilio sinensis 17,146 KM092493
Harpiocephalus Harpiocephalus harpia 16,446 MN885881
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Note: Bold text specifically refers to the species information sequenced in this study.

3. Results

3.1. Genomic Structure and Base Composition

The two Myotis mitochondrial genomes were typical double‐stranded circular molecules with sizes of 17,067 base pairs (bp) for M. siligorensis and 17,104 bp for M. laniger (Figure 1). The mitochondrial genomes of the two Myotis species comprised 13 PCGs, 22 tRNAs, two rRNAs, and a D‐loop. Eight tRNAs (Gln, Ala, Asn, Cys, Tyr, Ser1, Glu, and Pro) and ND6 were encoded by the minor strand, whereas the remaining genes were located on the major strand (Table 3). The newly sequenced mitochondrial genomes of Myotis sp. had similar sequence lengths and gene arrangements.

FIGURE 1.

FIGURE 1

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Mitochondrial genome information diagram of Myotis siligorensis and Myotis laniger . Species photographs were provided by Tai‐Yu Chen. Outer ring gene: Encoded by L‐strand. Inner circle gene: encoded by H‐strand.

TABLE 3.

General characteristics of the mitochondrial genomes of Myotis siligorensis and Myotis laniger .

Gene Position Size (bp) Intergenic nucleotides Codon Strand
From To Initiation Termination
tRNA‐Phe 1/1 69/68 69/68 0/0 +/+
12S rRNA 70/69 1034/1033 965/965 0/0 +/+
tRNA‐Val 1035/1034 1102/1102 68/69 0/0 +/+
16S rRNA 1103/1103 2666/2669 1564/1567 0/0 +/+
tRNA‐Leu 2667/2670 2741/2744 75/75 0/0 +/+
ND1 2747/2750 3702/3705 956/956 5/5 ATG/ATG TA/TA +/+
tRNA‐Ile 3703/3706 3771/3774 69/69 0/0 +/+
tRNA‐Gln 3769/3772 3842/3845 74/74 −3/−3 −/−
tRNA‐Met 3843/3846 3912/3915 70/70 0/0 +/+
ND2 3913/3916 4954/4957 1042/1042 0/0 ATT/ATT T/T +/+
tRNA‐Trp 4955/4958 5022/5025 68/68 0/0 +/+
tRNA‐Ala 5028/5031 5096/5099 69/69 5/5 −/−
tRNA‐Asn 5098/5101 5170/5173 73/73 1/1 −/−
tRNA‐Cys 5203/5206 5268/5271 66/66 32/32 −/−
tRNA‐Tyr 5269/5272 5335/5339 67/68 0/0 −/−
COX1 5337/5341 6881/6885 1545/1545 1/1 ATG/ATG TAA/TAA +/+
tRNA‐Ser1 6895/6899 6963/6967 69/69 13/13 −/−
tRNA‐Asp 6971/6975 7037/7041 67/67 7/7 +/+
COX2 7038/7042 7721/7725 684/684 0/0 ATG/ATG TAA/TAA +/+
tRNA‐Lys 7725/7729 7792/7796 68/68 3/3 +/+
ATP8 7794/7798 7997/8004 204/207 1/1 ATG/ATG TAA/TAG +/+
ATP6 7955/7959 8634/8638 680/680 −43/−46 ATG/ATG TA/TA +/+
COX3 8635/8639 9418/9422 784/784 0/0 ATG/ATG T/T +/+
tRNA‐Gly 9419/9423 9487/9491 69/69 0/0 +/+
ND3 9488/9492 9834/9838 347/347 0/0 ATA/ATA TA/TA +/+
tRNA‐Arg 9835/9839 9903/9907 69/69 0/0 +/+
ND4L 9905/9909 10,201/10,205 297/297 1/1 ATG/ATG TAA/TAA +/+
ND4 10,195/10,199 11,572/11,576 1378/1378 −7/−7 ATG/ATG T/T +/+
tRNA‐His 11,573/11,577 11,640/11644 68/68 0/0 +/+
tRNA‐Ser2 11,641/11,645 11,700/11,703 60/59 0/0 +/+
tRNA‐Leu2 11,702/11,705 11,771/11,774 70/70 1/1 +/+
ND5 11,772/11,775 13,592/13,595 1821/1821 0/0 ATA/ATA TAA/TAA +/+
ND6 13,576/13,579 14,103/14,106 528/528 −17/−17 ATG/ATG TAA/TAA −/−
tRNA‐Glu 14,104/14,107 14,172/14,175 69/69 0/0 −/−
CYTB 14,180/14,183 15,319/15,322 1140/1140 7/7 ATG/ATG AGA/AGA +/+
tRNA‐Thr 15,320/15,323 15,389/15,393 70/71 0/0 +/+
tRNA‐Pro 15,389/15,393 15,454/15,458 66/66 −1/−1 −/−
D‐loop 15,455/15,459 17,067/17,104 1613/1646 0/0
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Both mitochondrial genomes had five gene overlaps and 12 intergenic spaces (Table 3). The overlaps were situated between tRNA‐Ile and tRNA‐Gln (3 bp), ATP8 and ATP6 (43 bp for M. siligorensis and 46 bp for M. laniger ), ND4L and ND4 (7 bp), ND5 and ND6 (17 bp), and tRNA‐Thr and tRNA‐Pro (1 bp). The longest and shortest sequences were 46 and 1 bp, respectively. The intergenic spaces were determined to be located between tRNA‐Leu and ND1 (5 bp).

3.2. Nucleotide Composition

Nucleotide composition analysis of the two Myotis bat species revealed a greater AT skew than GC skew in the mitochondrial genomes (Table 4), indicating a preference for A and T nucleotides. Both mitochondrial genomes exhibited an AT bias (A + T > G + C), which was also evident in PCGs, rRNAs, and D‐loops. The highest A + T content in the D‐loop was observed in M. siligorensis (65.6%), whereas the highest A + T content within the tRNAs was observed in M. laniger (64.7%). The AT skew ranged from −0.019 to 0.215, and the GC skew ranged from −0.285 to 0.076 in the two mitochondrial genomes (Table 4). Gene collinearity analysis (Figure 2) demonstrated a high degree of similarity between the genomes of the two Myotis species, with no evidence of gene rearrangement.

TABLE 4.

Structural components and skew of the mitochondrial genomes of the two Myotis species.

Species Region Size (bp) A T(U) C G A + T% AT‐Skew GC‐Skew
Myotis siligorensis Total genome 17,067 33.7 29.8 23.4 13.1 63.5 0.061 −0.282
PCGs 11,406 31.1 32.0 23.7 13.2 63.1 −0.014 −0.285
tRNAs 1513 32.7 31.6 16.6 19.2 64.3 0.017 0.073
rRNAs 2529 38.0 25.4 19.8 16.8 63.4 0.199 −0.082
D‐loop 1613 38.1 27.5 23.1 11.3 65.6 0.162 −0.343
Myotis laniger Total genome 17,104 33.4 29.6 23.6 13.4 63.0 0.060 −0.276
PCGs 11,400 30.7 32.0 23.9 13.4 62.7 −0.019 −0.282
tRNAs 1514 33.0 31.7 16.3 19.0 64.7 0.020 0.076
rRNAs 2532 38.3 24.9 20.1 16.7 63.2 0.212 −0.092
D‐loop 1646 37.1 27.1 23.4 12.5 64.2 0.156 −0.304
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FIGURE 2.

FIGURE 2

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Collinearity analysis comparing Myotis siligorensis , Myotis laniger , and the outgroup species Vespertilio sinensis and Harpiocephalus harpia .

3.3. Protein‐Coding Genes and Codon Usage Patterns

The aggregate lengths of the 13 PCGs in the mitochondrial genomes of M. siligorensis and M. laniger were 11,406 bp and 11,400 bp, constituting 63.1% and 62.7% of the mitochondrial genome sequence length, respectively. Except for ND6, which was encoded by the minor strand, all the other PCGs were encoded by the major strand (Table 3). Among the PCGs of the two mitochondrial genomes, ND2 was initiated with an ATT codon, ND3 and ND5 were initiated with an ATA codon, and all other start codons were ATG (Table 3). Five types of termination codons were present in the two Myotis species, namely TA, T, TAA, AGA, and TAG, with the following distributions: ND1, ATP6, and ND3 used TA as the termination codon; ND2, COX3, and ND4 used T; COX1, COX2, ND4L, ND5, ND6, and ATP8 of M. siligorensis used TAA; CYTB terminated with AGA; and ATP8 of M. laniger terminated with TAG. The TAA termination codon was the most frequent, whereas TAG was the least frequent (Table 3). Using RSCU analysis, we investigated the codon usage patterns of two Myotis mitochondrial genomes (Figure 3) and found a high degree of similarity. The codon CUA was associated with the highest RSCU values in both M. siligorensis (2.49) and M. laniger (2.38), whereas the codon UCG was associated with the lowest RSCU values, at 0.11 and 0.09, respectively (Tables 5 and 6). The evolutionary patterns of the two Myotis species were analyzed based on the Ka/Ks ratios. All PCGs had Ka/Ks ratios less than 1 (Figure 4), with ATP8 having the highest Ka/Ks ratio at 0.118 and COX1 having the lowest at 0.018.

FIGURE 3.

FIGURE 3

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Relative synonymous codon usage analysis results for two Myotis species. The x‐axis refers to 64 synonymous codons (arranged in the order of amino acids, and termination codons are usually excluded).

TABLE 5.

Frequency of Myotis siligorensis codon usage.

Codon Count RSCU Codon Count RSCU Codon Count RSCU Codon Count RSCU
UUU(F) 139 1.22 UCU(S) 80 1.72 UAU(Y) 83 1.17 UGU(C) 10 0.91
UUC(F) 88 0.78 UCC(S) 45 0.97 UAC(Y) 59 0.83 UGC(C) 12 1.09
UUA(L) 160 1.59 UCA(S) 93 2 UAA(*) 6 3.43 UGA(W) 94 1.83
UUG(L) 16 0.16 UCG(S) 5 0.11 UAG(*) 0 0 UGG(W) 9 0.17
CUU(L) 82 0.82 CCU(P) 68 1.38 CAU(H) 50 1.04 CGU(R) 5 0.31
CUC(L) 46 0.46 CCC(P) 52 1.06 CAC(H) 46 0.96 CGC(R) 16 0.98
CUA(L) 250 2.49 CCA(P) 73 1.48 CAA(Q) 74 1.66 CGA(R) 39 2.4
CUG(L) 48 0.48 CCG(P) 4 0.08 CAG(Q) 15 0.34 CGG(R) 5 0.31
AUU(I) 237 1.41 ACU(T) 92 1.15 AAU(N) 79 1.03 AGU(S) 29 0.62
AUC(I) 99 0.59 ACC(T) 81 1.01 AAC(N) 75 0.97 AGC(S) 27 0.58
AUA(M) 223 1.7 ACA(T) 137 1.71 AAA(K) 83 1.71 AGA(*) 1 0.57
AUG(M) 39 0.3 ACG(T) 10 0.12 AAG(K) 14 0.29 AGG(*) 0 0
GUU(V) 43 0.93 GCU(A) 65 1.07 GAU(D) 30 0.95 GGU(G) 45 0.83
GUC(V) 39 0.84 GCC(A) 78 1.29 GAC(D) 33 1.05 GGC(G) 54 1
GUA(V) 88 1.9 GCA(A) 92 1.52 GAA(E) 74 1.56 GGA(G) 86 1.59
GUG(V) 15 0.32 GCG(A) 7 0.12 GAG(E) 21 0.44 GGG(G) 31 0.57
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TABLE 6.

Codon usage frequencies for Myotis laniger .

Codon Count RSCU Codon Count RSCU Codon Count RSCU Codon Count RSCU
UUU(F) 134 1.19 UCU(S) 72 1.56 UAU(Y) 78 1.1 UGU(C) 9 0.78
UUC(F) 92 0.81 UCC(S) 53 1.15 UAC(Y) 64 0.9 UGC(C) 14 1.22
UUA(L) 164 1.62 UCA(S) 91 1.97 UAA(*) 5 2.86 UGA(W) 87 1.69
UUG(L) 23 0.23 UCG(S) 4 0.09 UAG(*) 1 0.57 UGG(W) 16 0.31
CUU(L) 91 0.9 CCU(P) 59 1.2 CAU(H) 42 0.87 CGU(R) 10 0.62
CUC(L) 40 0.4 CCC(P) 63 1.28 CAC(H) 55 1.13 CGC(R) 13 0.8
CUA(L) 240 2.38 CCA(P) 70 1.42 CAA(Q) 72 1.64 CGA(R) 40 2.46
CUG(L) 48 0.48 CCG(P) 5 0.1 CAG(Q) 16 0.36 CGG(R) 2 0.12
AUU(I) 227 1.37 ACU(T) 83 1.04 AAU(N) 83 1.1 AGU(S) 27 0.58
AUC(I) 105 0.63 ACC(T) 87 1.09 AAC(N) 68 0.9 AGC(S) 30 0.65
AUA(M) 210 1.66 ACA(T) 139 1.74 AAA(K) 87 1.79 AGA(*) 1 0.57
AUG(M) 43 0.34 ACG(T) 11 0.14 AAG(K) 10 0.21 AGG(*) 0 0
GUU(V) 53 1.09 GCU(A) 78 1.27 GAU(D) 33 1.02 GGU(G) 40 0.75
GUC(V) 37 0.76 GCC(A) 70 1.14 GAC(D) 32 0.98 GGC(G) 58 1.08
GUA(V) 82 1.69 GCA(A) 91 1.49 GAA(E) 76 1.6 GGA(G) 93 1.74
GUG(V) 22 0.45 GCG(A) 6 0.1 GAG(E) 19 0.4 GGG(G) 23 0.43
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FIGURE 4.

FIGURE 4

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Analysis of Ka/Ks ratios for 13 protein‐coding genes across 38 species of Myotis. Solid gray and black lines indicate the mean and median values, respectively.

3.4. rRNA, tRNA, and D‐Loops

The two rRNAs (12S rRNA and 16S rRNA) were located between tRNA‐Phe and tRNA‐Val, and between tRNA‐Val and tRNA‐Leu, respectively (Table 3). The sizes of 12S rRNA were 965 and 965 bp, and those of 16S rRNA were 1564 and 1567 bp, respectively. The sizes of the 22 tRNAs ranged from 60 to 75 bp in M. siligorensis and from 59 to 75 bp in M. laniger , with 14 tRNAs originating from the major strand and eight from the minor strand (Table 3). The total length of the tRNAs was 1513 bp in M. siligorensis and 1514 bp in M. laniger (Table 4), accounting for 8.87% and 8.85% of the mitochondrial genomes, respectively. The D‐loop was situated between the tRNA‐Pro and tRNA‐Phe genes (Table 3), with sizes of 1613 and 1646 bp in the two species, respectively (Table 4).

3.5. Phylogenetic Relationships

Using V. sinensis and H. harpia as outgroups and integrating the genetic sequences of the two Myotis species sequenced in this study, phylogenetic analysis was conducted on the 36 Myotis species based on the 13 PCGs retrieved from GenBank (Table 2). The results indicate that the BI (Figure 5) and ML trees (Figure 6) were fundamentally consistent in their topological structures, with each branch exhibiting robust support values. The 38 Myotis species analyzed in this study formed a monophyletic group. Moreover, intrageneric speciation events in Myotis occurred early in its evolution, resulting in its divergence into two major clades. Further, M. siligorensis and M. laniger were clustered with Myotis davidii within the same clade, with a closer phylogenetic relationship observed between M. siligorensis and M. davidii compared to that with M. laniger .

FIGURE 5.

FIGURE 5

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Bayesian inference (BI) tree constructed from 13 protein‐coding genes of 40 species. The values on the branches represent posterior probabilities (PP), with only nodes having PP ≥ 0.95 displayed. The numbers following the species names are GenBank accession numbers. The outgroups are Harplocephalus harpia (MN885881) and Vespertilio sinensis (KM092493).

FIGURE 6.

FIGURE 6

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Maximum likelihood (ML) tree constructed from 13 protein‐coding genes of 40 species. The values on the branches represent bootstrap support (BS), with only nodes having BS ≥ 70% displayed. The numbers following the species names are GenBank accession numbers. The outgroups are Harplocephalus harpia (MN885881) and Vespertilio sinensis (KM092493).

4. Discussion

Myotis serves as an exemplary model for the study of species formation, with the characteristics of long‐living mammals, making it an important model for research on aging. The mitochondrial genome of Myotis is a vital resource for molecular phylogenetic and evolutionary (Cooper et al. 2024). This study represents the first acquisition and characterization of the mitochondrial genomes of M. siligorensis and M. laniger , enriching the mitochondrial genomic information for these species and clarifying their phylogenetic status and kinship within Myotis. These findings provide foundational data pertaining to the systematic molecular evolution of the Vespertilionidae family for subsequent research.

Phylogenetic analysis corroborated the evolutionary relationships within the genus Myotis, confirming that it is a monophyletic group, with all species sharing a recent common ancestor, which is consistent with previous findings (Vargas‐Trejo et al. 2023; Korstian et al. 2022). The genus Myotis underwent early divergence into two major clades, with close relationships observed between M. davidii / Myotis myotis and Myotis blythii / M. ricketti (Hao et al. 2024). It is noteworthy that resolving the phylogenetic relationships of closely related species often poses significant challenges, as different genetic markers may support conflicting topologies due to variations in their evolutionary characteristics. For instance, in the study by Liu et al. (2023) based on the mitochondrial CYTB gene, M. davidii exhibited a distant relationship with M. siligorensis, whereas our analysis combining 13 protein‐coding genes supported a closer phylogenetic affinity between M. davidii and M. siligorensis . Some scholars have pointed out that the Quaternary glaciations influenced clade divergence, particularly in M. siligorensis and M. davidii (Zhang and Feng 2011; Fu and Wen 2023). Additionally, phylogenetic analyses by other researchers have revealed key speciation events in the genus Myotis, including the split between Old World and New World lineages, as well as the later formation of the Nearctic/Neotropical subclade prior to the emergence of the Isthmus of Panama (Lack et al. 2010; Jiang et al. 2019; Luo et al. 2023).

The limited availability of genomic data for bat species, particularly those within the Myotis genus, has hindered in‐depth research into their evolutionary processes (Gutiérrez et al. 2024). Previous studies on bats have primarily focused on acquiring and comparing genomic data to establish correlations for multifaceted adaptive research (Thomas 2010). Although this study provides new mitochondrial genome data, contributing to a better understanding of interspecies relationships and offering insights for biodiversity conservation and germplasm resource assessment, the lack of more comprehensive genomic information remains a limitation. Future efforts should prioritize supplementing and refining genomic datasets to enhance our understanding of bat evolution, speciation, and adaptive mechanisms.

Author Contributions

Xiao‐Die Chen: formal analysis (lead), writing – original draft (lead), writing – review and editing (lead). Cheng‐He Sun: conceptualization (equal), data curation (equal), formal analysis (equal), funding acquisition (equal), methodology (equal), writing – review and editing (equal). Tai‐Yu Chen: investigation (lead), writing – review and editing (supporting). Zhen‐Yu Sun: investigation (lead), writing – review and editing (supporting). Chang‐Hu Lu: funding acquisition (lead), writing – review and editing (supporting).

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgments

We kindly acknowledge anonymous reviewers for their fruitful and critical comments. We would like to thank Editage (www.editage.com) for their editing support.

Chen, X.‐D. , Sun C.‐H., Chen T.‐Y., Sun Z.‐Y., and Lu C.‐H.. 2025. “Complete Mitochondrial Genomes and Phylogenetic Relationships of Myotis siligorensis and Myotis laniger .” Ecology and Evolution 15, no. 9: e72094. 10.1002/ece3.72094.

Funding: This study was supported by the Nanjing Wildlife Resources Survey Service in 2024 (JSZC‐320100‐NJRJ‐C2024‐0030) and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

Contributor Information

Cheng‐He Sun, Email: sch543116411@yeah.net, Email: sunchenghe@njfu.edu.cn.

Chang‐Hu Lu, Email: luchanghu@njfu.com.cn.

Data Availability Statement

The data presented in this study were deposited in the NCBI repository (accession numbers PQ496902 and PQ496903).

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data presented in this study were deposited in the NCBI repository (accession numbers PQ496902 and PQ496903).

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