Research Article
Research Article
Comparative analysis of the mitogenomes of two Corydoras (Siluriformes, Loricarioidei) with nine known Corydoras, and a phylogenetic analysis of Loricarioidei
expand article infoCheng-He Sun§, Qi Huang, Xiao-Shu Zeng, Sha Li|, Xiao-Li Zhang, Ya-Nan Zhang, Jian Liao, Chang-Hu Lu§, Bo-Ping Han, Qun Zhang
‡ Jinan University, Guangzhou, China
§ Nanjing Forestry University, Nanjing, China
| Hubei Key Laboratory of Three Gorges Project for Conservation of Fishes, Yichang, China
¶ Chinese Sturgeon Research Institute, China Three Gorges Corporation, Yichang, China
Open Access


Corydoras is a speciose catfish genus from South America with widely investigated phylogenetic and evolutionary relationships. The complete mitogenomes of C. aeneus and C. paleatus were sequenced, assembled, and annotated using next-generation sequencing. The genome arrangements, gene contents, genome structures, base compositions, evolutionary features, codon usage, and tRNA structures of the two mitogenomes were compared and analyzed with nine published mitogenomes of Corydoras. Phylogenetic analysis was performed using concatenated nucleotide sequences with 13 protein-coding genes and two rRNAs with 44 mitogenomes of Siluriformes. These results provide information on the mitogenomes of eleven Corydoras species and evolutionary relationships within the suborder Loricarioidei, which may be applicable for further phylogenetic and taxonomic studies on Siluriformes and Loricarioidei.


Corydoras aeneus, Corydoras paleatus, genome sequencing, mitochondrial DNA, Phylogenetic tree


Fish mitochondrial DNA shares characteristics with other vertebrate mitochondrial DNA (Anderson et al. 1981; Manchado et al. 2007; Xu et al. 2011), e.g., small molecular weight, simple structure, and compact arrangement. It exists in the form of a covalently closed circular supercoil structure and contains heavy and light chains. The genetic material can be replicated, transcribed, and translated independently from the nuclear DNA in the cell. With few exceptions, fish mitochondrial DNA comprises 13 protein-coding genes (PCGs), 22 transfer RNA genes, two ribosomal RNA genes, original region of light-strand replication, and control region (D-loop) (Ojala et al. 1981; Gadaleta et al. 1989; Wolstenholme 1992 Simon et al. 1994; De Rijk et al. 1995). The mitochondrial DNA mutates rapidly, nearly 10-fold faster than the nuclear DNA, and the fragment length and evolution rate differ for each gene, providing molecular evidence for studying different species (Brown et al. 1979; Pesole et al. 1999). In addition, mitochondrial DNA is highly heterogeneous and harbors the genetic characteristics associated with maternal traits (O’Brien 1971; Michot et al. 1990; Bartlett and Davidson 1991; Meyer 1993; Beheregaray and Sunnucks 2001; Liu et al. 2002; Yoshizawa and Johnson 2003). Hence, mitochondrial DNA can be used to identify fish groups at the molecular level and explore geographic distribution, species origin, and species differentiation (Avise et al. 1987; Kai et al. 2002; Hrbek et al. 2007). As fish are a large group with a complex origin in the vertebrate subphylum, studies on their phylogenetic and evolutionary relationships performed using traditional morphological methods often provide limited information. With advances in biotechnology, complete mitochondrial genome sequences have been determined as a useful tool to study the phylogeny and phylogeography of fish (Bermingham and Avise 1986; Xu et al. 2020).

Corydoras Lacépède, 1803, belongs to the order Siluriformes, suborder Loricarioidei, family Callichthyidae. Corydoras contains 175 valid species, which makes it the most species-rich genus of the family Callichthyidae (Lima and Britto 2020; Tencatt et al. 2021). The body of these fish is covered with bone plates, and the pectoral and dorsal fins have hard spines that can be used for protection. In addition, Corydoras can use the back end of their intestines, which is rich in blood vessels, to obtain oxygen from air taken in at the water surface, enabling survival under environmental stress, such as drought or insufficient dissolved oxygen content in water. Corydoras catfish are benthic omnivorous fish (Moreira et al. 2016b, 2017; Liu et al. 2019b, 2019c; Saitoh et al. 2003). Typically, Corydoras is active only during feeding, and otherwise hide while resting. Corydoras is primarily distributed in South America. Most species of Corydoras gather in the middle and lower reaches of the river where the current is relatively gentle, whereas a few live in the upper reaches of the river in rapids (Saitoh et al. 2003; Liu et al. 2019c). Corydoras is also valuable as an ornamental fish. Some phylogenetic relationships in Corydoras remain unclear. The number of species reported in relevant articles is small, which is not sufficient to reflect the phylogenetic variety of the genus Corydoras (Alexandrou et al. 2011; Lujan et al. 2015; Roxo et al. 2019). Therefore, a comprehensive understanding of the relationships between different species of Corydoras is essential.

In this study, the complete mitogenomes of two species of Corydoras (Bronze corydoras C. aeneus Gill, 1858 and peppered corydoras C. paleatus Jenyns, 1842) were sequenced, assembled, and annotated. The genome organization, gene contents, repeat sequences, and tRNA structures of the eleven mitogenomes were compared and analyzed in combination with nine published mitogenomes of Corydoras (Saitoh et al. 2003; Moreira et al. 2016a, 2017; Liu et al. 2019a, b, c, d; Chen et al. 2020; Lv et al. 2020). Determining the similarities and differences in gene orders, genetic structures, base compositions, evolutionary features, and codon usage can provide molecular insights into the taxonomic and phylogenetic characteristics of the order Siluriformes. Based on these data, and those obtained from the NCBI database, we examined the phylogenetic relationships among species in the suborder Loricarioidei. We also evaluated the mitogenomes of eleven species of Corydoras and evolutionary relationships within the suborder Loricarioidei, thereby providing a valuable basis for further evolutionary studies on Siluriformes and Loricarioidei.

Materials and methods

Sample collection and identification

Single specimens of C. aeneus and C. paleatus were collected from the temple of Confucius flower and wood fish market, Nanjing city, Jiangsu province, China (32°0'27.1"N, 118°50'11.5"E) in June 2020 and identified based on their morphological characteristics, according to the latest taxonomic classification of fish (Popazoglo and Boeger 2000; Huysentruyt and Adriaens 2005a, b). Their geographic data and specific origins were unknown. All fresh tissues were immediately stored at -80 °C in 95% ethanol until DNA extraction. Total DNA was extracted from the muscle tissue using a TIANamp Marine Animals DNA Kit DP324 (Tiangen Biotech Co., Ltd., Beijing, China) according to the manufacturer’s instructions. DNA integrity and purity were evaluated by 1% agarose gel electrophoresis, and DNA purity was determined with a NanoDrop 2000 (NanoDrop Technologies, Wilmington, DE, USA). DNA concentrations were quantified using a QubitR 2.0 Fluorometer (Life Technologies, Carlsbad, CA, USA). To ensure the accuracy of morphological identification, COI primers were designed based on the latest DNA barcoding database (NCBI and FishBase) and were amplified, sequenced, and compared. The COI sequences are provided in the Suppl. material 1. The results of the sequence alignment verify the accuracy of the morphological identification.

Genome sequencing and assembly

Next-generation sequencing was performed to determine the complete mitogenome sequence of the two species of Corydoras. The DNA libraries were sequenced on an Illumina sequencing platform by Novogene Co., Ltd. (Beijing, China). Briefly, the total DNA genome was quantified and fragmented into 250-base pair (bp) fragments using a Covaris M220 ultrasonic crushing system (Woburn, MA, USA) followed by whole-genome shotgun sequencing. According to the manufacturer’s instructions, a library was constructed based on two indices using an Illumina TruSeq DNA PCR-Free HT kit (San Diego, CA, USA). An Illumina Novaseq 6000 platform was used for sequencing of 150 paired-end reads approximately 4 Gb in size. Clean reads were generated as previously described, and the remaining high-quality reads were assembled using SPADES V3.15.2 (Bankevich et al. 2012) ( and SOAPDENOVO2 V2.01 (Luo et al. 2012) software. The preliminary assembly results were compared with the NT database, and looped sequences annotated as mitochondrial genomes were screened. CAP3 was used to merge the splicing results from the two software programs, and the assembly results were compared with those of related species using MUMMER v3.23 (Delcher et al. 2003). The mitogenome composition was confirmed, and a complete, high-quality map of the mitochondrial genome was obtained.

Genome annotation and analysis

The tRNA genes were verified using tRNASCAN-SE V1.3.1 (Lowe and Eddy 1997) with default settings for the vertebrate mitochondrial genetic code. The software, which integrates multiple analysis tools, can identify 99% of the tRNA genes with a very low number of false positives and predict the secondary structure of tRNAs. Protein-coding regions were re-identified using GLIMMER V3.0 (Ingram et al. 2009), and manual comparisons were performed using the SEQMAN program of LASERGENE V7.1 (Burland 2000) (DNAStar, Inc., Madison, WI, USA) based on the PCGs of nine species of Corydoras and translated into putative proteins via GenBank. The non-coding RNAs were verified using RFAM V12.0 (Griffiths-Jones et al. 2003) and INFERNAL V1.1 (Nawrocki and Eddy 2013). The rRNA genes were assumed to extend to the boundaries of flanking genes, similar to the homologous regions of other published mitogenomes of Corydoras in GenBank. The MITOS WebServer ( and MitoFish (Iwasaki et al. 2013) ( online tools were used for the final annotation of the entire mitogenome sequence of the two species of Corydoras, and the annotated mitogenomes were compared with nine published mitogenomes of Corydoras. Base compositions, genetic distances, and relative synonymous codon usage values were determined using MEGA V7.0 (Kumar et al. 1994). A graph comparing the relative synonymous codon usage was drawn using PHYLOSUITE V1.2.2 (Zhang et al. 2020). Strand asymmetry was analyzed using the formula: AT-skew = (A – T)/(A + T). The numbers of non-synonymous (Ka) and synonymous (Ks) substitutions and the ratio of Ka/Ks and nucleotide diversity for the nine species of Corydoras were calculated using DNASP 5.1 (Librado and Rozas 2009). The MitoFish ( online tool was used to generate circular mitogenome maps.

Phylogenetic analysis

Phylogenetic trees for the eleven mitogenomes of Corydoras within the family Callichthyidae and Suborder Loricarioidei were constructed by aligning 13 PCGs and two rRNA sequences with those of 42 species of Loricarioidei, 29 species from Loricariidae, and one species from Trichomycteridae (Table 1). The mitogenomes of Pterocryptis cochinchinensis (Resende et al. 2016) and Silurus asotus (Nakatani et al. 2011) (accession no. NC_027107.1 and NC_015806.1, respectively, suborder Siluroidei) were included as outgroups to root the Loricarioidei tree. All operations were performed in PHYLOSUITE V1.2.2 (Zhang et al. 2020) software package. The nucleotide sequences of 13 PCGs from 44 mitogenomes were aligned in batches with MAFFT V7.313 (Katoh and Standley 2013) ( using the codon alignment mode. The results were optimized using MACSE V2.03 (Ranwez et al. 2018). The nucleotide sequences of two rRNAs were aligned using the online tool MAFFT with default settings. Ambiguously aligned regions were removed via GBLOCKS 0.91 b with default settings. The resulting alignments were concatenated into a single dataset with PHYLOSUITE. The best partition schemes and optimal substitution models were selected by MODELFINDER (Kalyaanamoorthy et al. 2017) with the greedy algorithm and Bayesian information criterion (Watanabe 2013). The best substitution models applied to each partition are listed in Suppl. material 1: Table S1. Phylogenetic trees were constructed using two inference methods: maximum likelihood (ML) and Bayesian inference (BI). ML analyses were performed with IQ-TREE V1.6.8 with the models selected for each partition, and 1,000 bootstrap replicates were used to estimate node reliability. Bayesian analyses were performed using MRBAYES V3.2.6 (Huelsenbeck and Ronquist 2001). One million generations of two independent runs were performed with four chains and sampling trees every 100 generations. The initial 25% of trees generated prior to reaching stable log-likelihood values were discarded as burn-in. The remaining trees were used to calculate the Bayesian posterior probabilities. The resulting phylogenetic trees and gene orders were visualized and edited using iTOL (Letunic and Bork 2016).

Table 1.

Information on 44 Siluriformes species evaluated in the study.

No. Suborder Family Taxa GenBank accession no. Length (bp) Location/Reference
1 Loricarioidei Callichthyidae Corydoras aeneus MZ571336 16604 This study
2 Corydoras agassizii MN641875.1 16538 Lv et al. 2020
3 Corydoras arcuatus NC_049096.1 16177 Liu et al. 2019d
4 Corydoras duplicareus NC_049095.1 16632 Liu et al. 2019a
5 Corydoras nattereri KT239008.1 16557 Moreira et al. 2016a
6 Corydoras paleatus MZ571337 16320 This study
7 Corydoras panda NC_049097.1 16398 Liu et al. 2019b
8 Corydoras rabauti NC_004698.1 16711 Saitoh et al. 2003
9 Corydoras schwartzi KT239007.1 15671 Moreira et al. 2017
10 Corydoras sterbai NC_048967.1 16520 Liu et al. 2019c
11 Corydoras trilineatus NC_049098.1 15359 Chen et al. 2020
12 Hoplosternum littorale KX087170.1 16262 Parente et al. 2018
13 Loricariidae Ancistomus snethlageae KX087166.1 16464 Moreira et al. 2017
14 Ancistrus cryptophthalmus MF804392.1 16333 Lv et al. 2020
15 Ancistrus multispinis KT239006.1 16539 Moreira 2018
16 Ancistrus temminckii NC_051963.1 16439 Meng et al. 2021
17 Aphanotorulus emarginatus KT239019.1 16597 Moreira et al. 2017
18 Baryancistrus xanthellus KX087167.1 16167 Moreira et al. 2017
19 Dekeyseria amazonica KX087168.1 16409 Moreira 2018
20 Hemipsilichthys nimius KT239011.1 16477 Moreira et al. 2017
21 Hisonotus thayeri KX087173.1 16269 Moreira et al. 2017
22 Hypancistrus zebra KX611143.1 16202 Magalhães et al. 2017
23 Hypoptopoma incognitum NC_028072.1 16313 Moreira et al. 2016b
24 Hypostomus affinis KT239013.1 16330 Moreira et al. 2017
25 Hypostomus ancistroides NC_052710.1 16422 Rocha-Reis et al. 2020
26 Hypostomus francisci NC_045188.1 16916 Pereira et al. 2019
27 Hypostomus plecostomus NC_025584.1 16562 Liu et al. 2016
28 Kronichthys heylandi KT239014.1 16632 Moreira et al. 2017
29 Loricaria cataphracta KX087174.1 16831 Moreira et al. 2017
30 Loricariichthys castaneus KT239015.1 16521 Moreira et al. 2017
31 Loricariichthys platymetopon KT239018.1 16521 Moreira et al. 2017
32 Neoplecostomus microps KX087175.1 16523 Moreira et al. 2017
33 Otocinclus affinis MT323116.1 16501 Zhang et al. 2021
34 Pareiorhaphis garbei KX087178.1 16630 Moreira et al. 2017
35 Parotocinclus maculicauda KX087179.1 16541 Moreira et al. 2017
36 Peckoltia furcata KX087180.1 16497 Moreira et al. 2017
37 Pterygoplichthys anisitsi KT239003.1 16636 Parente et al. 2017
38 Pterygoplichthys disjunctivus NC_015747.1 16667 Nakatani et al. 2011
39 Pterygoplichthys pardalis KT239016.1 16822 Moreira et al. 2017
40 Schizolecis guntheri KT239017.1 16611 Moreira et al. 2017
41 Sturisomatichthys panamensis NC_045877.1 16526 Ren et al. 2019
42 Trichomycteridae Trichomycterus areolatus AP012026.1 16657 Nakatani et al. 2011
43 Siluroidei Siluridae Pterocryptis cochinchinensis NC_027107.1 16826 Resende et al. 2016
44 Silurus asotus NC_015806.1 16593 Nakatani et al. 2011

Results and discussion

Genome structure and organization

The complete mitogenomes of C. aeneus and C. paleatus comprising 16,604 and 16,593 bp, respectively, were submitted to GenBank (accession nos. MZ571336 and MZ571337, respectively) (Fig. 1, Table 2). The two mitogenomes were circular and contained 37 mitochondrial genes (13 PCGs, 22 tRNA genes, and two rRNA genes) and one D-loop. The position of each gene in the mitogenome was identical to that in other species of Corydoras (Saitoh et al. 2003; Moreira et al. 2016a, 2017; Liu et al. 2019a, b, c, d; Chen et al. 2020; Lv et al. 2020). One of the 13 PCGs (ND6) and eight tRNAs (tRNA-Ala, tRNA-Cys, tRNA-Glu, tRNA-Asn, tRNA-Pro, tRNA-Gln, tRNA-Ser(TGA), and tRNA-Tyr) were encoded by the light chain (-), whereas the other 28 genes, including 12 PCGs, 14 tRNAs, two rRNAs, and one D-loop, were encoded by the heavy chain (+) (Fig. 1, Table 2). The 44 mitogenomes of Siluriformes (Nakatani et al. 2011; Liu et al. 2016; Moreira et al 2016b, 2018; Resende et al. 2016; Magalhães et al. 2017; Parente et al. 2017; Parente et al. 2018; Pereira et al. 2019; Ren et al. 2019; Rocha-Reis et al. 2020; Meng et al. 2021; Zhang et al. 2021) used in this study were compared, and the gene composition and order were consistent (Suppl. material 1: Fig. S1). The nucleotide composition of the two entire mitogenomes was as follows: C. aeneus A = 5417 (32.63%), T = 4299 (25.89%), G = 2451 (14.76%), C = 4437 (26.72%) and C. paleatus A = 5380 (32.42%), T = 4282 (25.81%), G = 2481 (14.95%), C = 4450 (26.82%). The two mitogenomes (values for C. aeneus followed by values for C. paleatus) had high A+T contents of 58.52% and 58.23% (Suppl. material 1: Table S2), including 58.08% and 57.67% in PCGs, 56.97% and 57.04% in tRNA genes, 59.70% and 59.10% in 16S rRNA, 55.30% in 12S rRNA, and 67.51% and 68.21% in the D-loop, respectively, which agrees with the typical base bias of fish mitogenomes (Gadaleta et al. 1989; Manchado et al. 2007; Xu et al. 2011). The overall AT and GC skew values in the entire mitogenome of C. aeneus were 0.115 and -0.288 and in C. paleatus were 0.114 and -0.284, respectively. The GC skew value of the eleven mitogenomes of Corydoras, except for tRNA, was slightly negative (-0.014 to -0.288), showing a higher occurrence of C than of G. In contrast, AT skew value, except for the second codon position, was slightly positive (0.028 to 0.379), showing a higher content of A than of T. The K2P genetic distances of the eleven mitogenomes of Corydoras were all less than 0.12 (Suppl. material 1: Table S3). C. nattereri and C. sterbai and C. nattereri and C. trilineatus showed the largest K2P genetic distances among the eleven species of Corydoras.

Table 2.

Characteristic features of Corydoras aeneus and Corydoras paleatus mitogenomes (+ denotes heavy strand; - denotes light strand).

Feature Position Length (bp) Start codons Stop codons Anticodon Strand Intergenic nucleotides
C. aeneus C. paleatus C. aeneus C. paleatus C. a C. p C. a C. p
From to From to C. a C. p
tRNA-Phe 1 68 1 68 68 68 GAA + 0 0
12S rRNA 69 1014 69 1013 946 945 + 0 0
tRNA-Val 1015 1086 1014 1085 72 72 TAC + 0 0
16S rRNA 1087 2757 1086 2753 1671 1668 + 0 0
tRNA-Leu 2758 2832 2754 2828 75 75 TAA + 0 0
ND1 2833 3804 2829 3800 972 972 ATG ATG TAG TAG + 8 8
tRNA-Ile 3813 3884 3809 3880 72 72 GAT + -2 -2
tRNA-Gln 3883 3953 3879 3949 71 71 TTG - -1 -1
tRNA-Met 3953 4022 3949 4018 70 70 CAT + 0 0
ND2 4023 5067 4019 5063 1045 1045 ATG ATG T T + 0 0
tRNA-Trp 5068 5139 5064 5134 72 71 TCA + 1 1
tRNA-Ala 5141 5209 5136 5204 69 69 TGC - 1 1
tRNA-Asn 5211 5283 5206 5278 73 73 GTT - 30 31
tRNA-Cys 5314 5380 5310 5377 67 68 GCA - -1 -1
tRNA-Tyr 5380 5449 5377 5446 70 70 GTA - 1 1
COI 5451 7010 5448 7007 1560 1560 GTG GTG AGG AGG + -13 -13
tRNA-Ser 6998 7068 6995 7065 71 71 TGA - 4 4
tRNA-Asp 7073 7141 7070 7138 69 69 GTC + 4 6
COII 7146 7836 7145 7835 691 691 ATG ATG T T + 0 0
tRNA-Lys 7837 7910 7836 7909 74 74 TTT + 1 1
ATPase 8 7912 8079 7911 8078 168 168 ATG ATG TAA TAA + -10 -10
ATPase 6 8070 8753 8069 8752 684 684 ATG ATG TAA TAA + 17 21
COIII 8771 9554 8774 9557 784 784 ATG ATG T T + 0 0
tRNA-Gly 9555 9626 9558 9629 72 72 TCC + 0 0
ND3 9627 9975 9630 9978 349 349 ATG ATG T T + 0 0
tRNA-Arg 9976 10045 9979 10048 70 70 TCG + 0 0
ND4L 10046 10342 10049 10345 297 297 ATG ATG TAA TAA + -7 -7
ND4 10336 11716 10339 11719 1381 1381 ATG ATG T T + 0 0
tRNA-His 11717 11786 11720 11789 70 70 GTG + 0 0
tRNA-Ser 11787 11853 11790 11856 67 67 GCT + 1 1
tRNA-Leu 11855 11927 11858 11930 73 73 TAG + 0 0
ND5 11928 13754 11931 13757 1827 1827 ATG ATG TAA TAA + -4 -4
ND6 13751 14266 13754 14269 516 516 ATG ATG TAA TAA - 0 0
tRNA-Glu 14267 14335 14270 14337 69 68 TTC - 2 3
Cyt b 14338 15475 14341 15478 1138 1138 ATG ATG T T + 0 0
tRNA-Thr 15476 15548 15479 15550 73 72 TGT + -2 -2
tRNA-Pro 15547 15616 15549 15618 70 70 TGG - 0 0
D-loop 15617 16604 15619 16593 988 975 0 0
Figure 1. 

Gene maps of the two newly sequenced Corydoras species.

Protein-coding genes

The 13 PCGs of the two new mitogenomes and those of the previously published nine mitogenomes of Corydoras contained COI–COIII, ND1–ND6, ND4L, two ATPases, and one Cyt-b, similar to that in other Siluriformes (Nakatani et al. 2011; Liu et al. 2016; Moreira et al. 2016b; Resende et al. 2016; Magalhães et al. 2017; Parente et al. 2017; Moreira 2018; Parente et al. 2018; Pereira et al. 2019; Ren et al. 2019; Rocha-Reis et al. 2020; Meng et al. 2021; Zhang et al. 2021). The total lengths of PCGs in the eleven mitogenomes of Corydoras were 11,400–11,414 bp, accounting for 67.84–69.24% of the entire mitogenome. Similar to the mitogenomes of other species of Loricarioidei, ND5 and ATPase 8 were largest (1,827 bp) and smallest (168 bp), respectively. Most PCGs stringently start with an ATG start codon, except for all COIs, which start with GTG, C. nattereri COIII (Moreira et al. 2016a) which starts with GCA, and C. schwartzi COII (Moreira et al. 2017), which starts with CCA (Suppl. material 1: Table S4). Most PCGs are stringently terminated by the stop codon TAR (TAA/TAG) or an incomplete stop codon T, except for all COIs, which terminate with AGG and C. schwartzi ATPase 6 and C. nattereri ND3, which terminate with TA. The presence of a truncated stop codon is common among vertebrate mitochondrial genes and is thought to be introduced by posttranscriptional poly-adenylation.

Similar to most previously sequenced members of Loricarioidei, the AT-skews (0.033 to 0.052) and GC-skews (-0.268 to -0.299) of the PCGs were similar among the eleven species of Corydoras (Suppl. material 1: Table S2). Summaries of the relative synonymous codon usage and the number of amino acids in the annotated PCGs are presented in Suppl. material 1: Figs S2, S3. The PCGs of the eleven mitogenomes of Corydoras (Saitoh et al. 2003; Moreira et al. 2016a, 2017; Liu et al. 2019a, b, c, d; Chen et al. 2020; Lv et al. 2020) translate into 3,798–3,802 codons and showed very similar codon usage, excluding the stop codons (26–28 bp). Ile (310.82 ± 2.69 codons), Thr (312.64 ± 2.27 codons), Ala (312.73 ± 3.08 codons), and Leu1 (CUN) (475.45 ± 12.89 codons) were the four most predominant codon families and may be associated with the coding function of the chondriosome. In contrast, Cys (24.91 ± 0.79 codons) and Ser1 (AGN) (52.18 ± 0.83 codons) had the smallest number of codons. A/T rather than G/C bias was observed in the third position, as almost all frequently used codons ended with A/T. The synonymous codon preferences for the eleven species of Corydoras were conserved, possibly because of the close relationships among members of this genus.

To reveal the evolutionary pattern of the PCGs, the Ka/Ks, nucleotide diversity, and K2P genetic distance across all mitogenomes of Corydoras were calculated for each aligned PCG. The K2P genetic distances of 13 PCGs were all less than 0.12 (Fig. 2a). Among the PCGs detected, ND4 and ATPase 8 showed the largest K2P genetic distance among the eleven species of Corydoras, followed by ND2 and ND3. The nucleotide diversity of the 13 PCGs was less than 0.11 (Fig. 2b). ND4 showed the highest nucleotide diversity, whereas COII showed the lowest diversity. To investigate the selective pressure across species of Corydoras, the Ka/Ks ratios of the PCGs of each mitogenome were estimated (Fig. 2c). The Ka/Ks value was highest for ND6, followed by ND2; the lowest values were observed for COI, COIII, ND1, and ND4L. All 13 PCGs showed Ka/Ks << 1, suggesting that all PCGs of Corydoras evolved under purifying selection.

Figure 2. 

K2P genetic distance a nucleotide diversity b Ka/Ks ratio c analyses of protein-coding genes among the eleven Corydoras mitogenomes.

tRNAs, ribosomal RNAs, and control region

The total lengths of the 22 tRNA genes ranged from 1,438 (C. schwartzi) to 1,561 bp (C. arcuatus and C. panda), whereas individual tRNA genes typically ranged from 58 to 75 bp. All tRNA genes displayed the expected cloverleaf secondary structures with normal base pairing, except for tRNA-Ser(GCT), which lacked the DHU stem (Suppl. material 1: Fig. S4), forming a loop commonly found in other vertebrates (Ojala et al. 1981; Gadaleta et al. 1989; Wolstenholme 1992). The A+T contents of these tRNAs were 56.55–57.58%. All AT-skew and GC-skew values were slightly positive, indicating a slight bias toward the use of A and G in the tRNAs (Suppl. material 1: Table S2). These rRNA genes are between tRNA-Phe and tRNA-Leu(TAA) and are separated by tRNA-Val. The average total size of the two rRNAs was 2,614 bp, and the average A+T content was 57.89%. Like the tRNAs, all AT-skew values were positive, whereas all GC-skew values were negative, indicating that rRNAs favor C compared to tRNAs in Corydoras.

The control region (D-loop), also known as the A+T rich region that contains hypervariable non-coding sequences and regulates the replication and transcription of mitochondrial DNA, is the largest non-coding region and is located between tRNA-Pro and tRNA-Phe in these mitogenomes. Compared with PCGs, the D-loop displayed a higher mutation rate and the highest variation throughout the mitogenome; thus, this region is dominant and can be used to evaluate intraspecies variations. The D-loops in the eleven species of Corydoras were 718‒1,218 bp. Compared with the other four regions (entire genome, PCGs, tRNAs, and rRNAs), the control region showed the highest A+T content, ranging from 66.77% to 71.87%. Like the rRNAs, all AT-skew values were positive, and all GC-skew values were negative.

Phylogenetic analysis

To determine the phylogenetic relationships within the suborder Loricarioidei and family Callichthyidae, we obtained the concatenated nucleotide sequences of 13 PCGs and two rRNAs from 42 species of Loricarioidei. Phylogenetic analyses based on both ML and BI methods revealed same topologies, which also generally agreed with those presented in previous studies (Alexandrou et al. 2011; Lujan et al. 2015; Moreira et al. 2017; Roxo et al. 2019) (Figs 3, 4). These analyses confirmed that the genus Corydoras was part of the monophyletic family Callichthyidae.

Figure 3. 

Phylogenetic trees of 44 Siluriformes species using concatenated nucleotide sequences of 13 protein-coding genes and two rRNAs using the maximum likelihood method. Numbers in the ML tree represent SH-aLRT support/ultrafast bootstrap support values.

Both Callichthyidae and Loricariidae were recovered as monophyletic with very high support values (BI posterior probabilities, PP = 1; ML bootstrap, BS = 100). The 44 species of Siluriformes were divided into four major clades corresponding to the families Siluridae Callichthyidae, Trichomycteridae, and Loricariidae. The target species C. aeneus and C. paleatus were clustered into two clades (C. aeneus + C. rabauti) and (C. paleatus + C. nattereri) with a high nodal support value (PP = 1; BS = 100). The eleven species of the genus Corydoras clustered together quite well [((C. aeneus + C. rabauti) + (C. schwartzi + C. agassizii)) + (C. arcuatus + (C. panda + (C. duplicareus + (C. sterbai + C. trilineatus))))] + [(C. paleatus + C. nattereri)]. Corydoras trilineatus and C. sterbai have short, almost non-existent branch lengths; thus, they are likely the same species. The K2P genetic distances of these two species are 0.000 (Suppl. material 1: Table S3), which verifies that they are the same species. This may be caused by incorrect identification, taxonomic problems (these two species are, in fact, synonymous), and/or introgressive hybridization. Moreover, in the family Loricariidae, the genera Ancistrus and Loricariichthys were clustered into monophyletic clades [(A. cryptophthalmus + A. multispinis) + A. temminckii] and ( L. castaneus + L. platymetopon) with a high nodal support value (PP = 1; BS = 100). There was a paraphyletic relationship between the genera Hypostomus and Pterygoplichthys, [H. francisci + (H. ancistroides + H. affinis), P. pardalis + (H. plecostomus + (P. anisitsi + P. disjunctivus))]. Our results demonstrate that the concatenated nucleotide sequences of the 13 PCGs and two rRNAs were useful for determining the phylogenetic relationships of the order Siluriformes. These results can be used to improve classification of the families Callichthyidae and Loricariidae.

Figure 4. 

Phylogenetic tree of 44 Siluriformes species using concatenated nucleotide sequences of 13 protein-coding genes and two rRNAs via the Bayesian interference method. Applicable posterior probability values are shown.


Using next-generation sequencing methods, the complete mitogenomes of the bronze C. aeneus and peppered C. paleatus were analyzed and compared with those of nine members of Corydoras. The complete mitogenomes of C. aeneus and C. paleatus comprised 16,604 and 16,593 bp, respectively. The two mitogenomes had high A+T contents (58.52% in C. aeneus and 58.23% in C. paleatus), a phenomenon that agrees with the typical base bias of ichthyic mitogenomes. Our results indicate that the mitogenome features, including genome size, gene content, and gene arrangement, in Corydoras are highly conserved. Phylogenetic analysis was performed with 42 species of Loricarioidei and two outgroup species. These analyses confirmed the occurrence of the genus Corydoras within the monophyletic family Callichthyidae. The complete mitogenome information, including the gene content, gene orders, genome structure, base compositions, evolutionary features, codon usage, gene arrangement, and phylogenetic analyses, provides a basis for future studies on the population genetic and evolution of Corydoras and related groups.


This work was supported by the National Key R&D Program of China (Grant number 2018YFD0900802); Director’s Fund of the Hubei Key Laboratory of Three Gorges Project for Conservation of Fishes, China Three Gorges Corporation (0704157); Outstanding Innovative Talents Cultivation Funded Programs for Doctoral Students of Jinan University (Project No: 2021CXB022) and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). We gratefully acknowledge two reviewers for their constructive comments and would like to thank Editage ( for their support with language editing.


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Supplementary material

Supplementary material 1 

COI sequences of Corydoras aeneus and C. paleatus Tables S1–S4, Figs S1–S4

Cheng-He Sun, Qi Huang, Xiao-Shu Zeng, Sha Li, Xiao-Li Zhang, Ya-Nan Zhang, Jian Liao, Chang-Hu Lu, Bo-Ping Han, Qun Zhang

Data type: docx file

Explanation note: COI sequences of Corydoras aeneus and C. paleatus. Table S1. Best substitution models for Bayesian inference (BI) and maximum-likelihood (ML) analyses. Table S2. Summarized mitogenomic characteristics of the eleven Corydoras species investigated in this study. Table S3. The K2P genetic distances of the eleven mitogenomes of Corydoras. Table S4. Start nd stop codons of protein-coding genes in the eleven Corydoras mitogenomes. Figure S1. Gene orders of mitogenomes of the studied species. Figure S2. Relative synonymous codon usage of 13 protein-coding genes in the mitogenomes of eleven Corydoras species. Figure S3. Codon usage patterns of eleven Corydoras mitogenomes. Figure S4. Secondary structures of tRNA-Ser(GCT) in the two newly sequenced Corydoras species.

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