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Structural Analysis and Phylogenetic Relationships of a Teleost Fish, Pethia stoliczkana Based on the Complete Mitochondrial Genome Sequence

PJZ_56_2_853-860

Structural Analysis and Phylogenetic Relationships of a Teleost Fish, Pethia stoliczkana Based on the Complete Mitochondrial Genome Sequence

Zhenglei Qiao*, Jie Xing and Fang Li

College of Life Science and Technology, Mudanjiang Normal University, Mudanjiang 157012, China

ABSTRACT

In this study, the whole mitochondrial genome sequence of Pethia stoliczkana was obtained using high-throughput sequencing technology, and its structure and characteristics were analyzed. The P. stoliczkana mitochondrial genome contained a total of 16,966 base pairs, including 13 protein-coding genes, 22 transport RNA genes, two ribosomal RNA genes, and one control region. The A+T content (59.7%) of the whole mitochondrial genome was greater than the G+C content (40.3%), indicating an obvious A+T preference. The mitochondrial genome of P. stoliczkana is similar to that of most teleost fish, and no gene rearrangements were detected. The phylogenetic relationship tree of Smiliogastrinae fish was constructed based on 13 protein-coding genes using the Bayesian inference and maximum likelihood methods. We found that P. stoliczkana was closely related to Pethia ticto and Pethia padamya. These results enrich the mitochondrial genome database of Smiliogastrinae fish and provide reference materials for systematic classification of this group of fish.


Article Information

Received 02 March 2023

Revised 21 March 2023

Accepted 03 April 2023

Available online 21 July 2023

(early access)

Published 16 February 2024

Authors’ Contribution

ZQ collected and analysed the data and wrote the manuscript. JX and FL supervised the study, analysed the data, and edited the manuscript.

Key words

Mitogenome, mtDNA, Next-generation sequencing, Phylogeny

DOI: https://dx.doi.org/10.17582/journal.pjz/20230302100304

* Corresponding author: qzlqzqjr@126.com

0030-9923/2024/0002-0853 $ 9.00/0

Copyright 2024 by the authors. Licensee Zoological Society of Pakistan.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).



Introduction

Pethia stoliczkana (Day, 1871) belongs to the order Cypriniformes, family Cyprinidae, and subfamily Smiliogastrinae. This tropical benthic freshwater fish is mainly distributed in Laos, Thailand, Myanmar, and India (Nath et al., 2022). The main morphological characteristics of P. stoliczkana species are as follows: Flank behind gill opening with vertically elongated black blotch; caudal peduncle with vertically elongated black blotch; dorsal fin of sexually active male is red with black margin and two rows of black spots; no barbels; and last simple dorsal ray serrated posteriorly; this fish has important economic and ornamental value (Atkore et al., 2015; Nath et al., 2022).

Mitochondrial DNA (mtDNA) is the only genetic material outside of the cell nucleus in animals that can replicate and transcribe independently. In contrast to nuclear DNA, mtDNA is maternally inherited, has a simple molecular structure, undergoes rapid evolution, and exhibits unorganized specificity. mtDNA is a powerful tool for studying the origin and phylogeny of species, genetic differentiation between related species and intraspecific populations, species identification, and genetic diversity (Funk and Omland, 2003; Wolstenholme, 1992). Fish mtDNA is useful for studying evolutionary genetics; particularly, the mitochondrial genome sequence contains more information than a single gene and more comprehensively reflects the genetic characteristics of species and phylogenetic relationships at different taxonomic levels (Avise et al., 1987). In the past ten years, the mitochondrial genomes of fish have been widely studied using high-flux sequencing technology, leading to an increase in reports on completed mitochondrial genome sequences of fish.

In this study, we determined the full mitochondrial genome sequence of P. stoliczkana using high-throughput sequencing technology and analyzed its gene composition and structural characteristics. Combined with mitochondrial sequence information of related species, the phylogenetic relationships of Smiliogastrinae fish were determined using the protein-coding genome sequence. These results fill a knowledge gap in the molecular biology of P. stoliczkana and complement and improve the limited mitochondrial genome data on Smiliogastrinae fish. This sequence provides molecular evidence and a theoretical reference for classification and identification, germplasm resource evaluation and development, and utilization of this group of fish.

Materials and Methods

Experimental materials, DNA extraction, and species identification

Samples were purchased from a flower, bird, fish, and insect Market in Mudanjiang, China in June 2022 and preliminarily identified on site based on their morphological characteristics. Genomic DNA was extracted from the fish fins using a noninvasive extraction method. The quality and concentration of the extracted DNA were determined using 1% agarose gel electrophoresis and a NanoDrop 2000 nucleic acid analyzer (Thermo Fisher Scientific, Waltham, MA, USA), respectively. DNA barcoding technology was performed to further identify the species.

Sequencing

DNA samples were sent to Wuhan Beina Biotechnology Co., Ltd. to construct a 350 bp small fragment sequencing library and for high-throughput sequencing. Using sequencing by synthesis technology and an Illumina HiSeq X sequencing platform (San Diego, CA, USA), the constructed sequencing library was sequenced by 150 bp at both ends, and the original sequencing data were filtered using NGS QC Toolkit 2.3.3 (Patel and Jain, 2012) to remove adapter sequences, low-quality terminals, reads with N >10%, and fragments of less than 25 bp.

Assembly, annotation, and feature analysis

Leverage SPAdes v3.11.1 (http://cab.spbu.ru/software/spades/) (Bankevich et al., 2012) was used to splice clean reads to build contigs. SSPACE (Boetzer et al., 2011) was used to extend the contigs and obtain the final complete mitochondrial genome sequence. MITOS (Bernt et al., 2013) was used to annotate the mitochondrial genome sequence. The results were verified by homology comparison with the mitochondrial genes of known Smiliogastrinae species. tRNAscan-SE software (http://lowelab.ucsc.edu/tRNAscan-SE/) (Lowe and Chan, 2016) was used to search for the tRNA gene. Mega 11 (Tamura et al., 2021) was used to calculate the base composition, codon usage frequency, AT-skew, and GC-skew of each coding gene in the mitochondrial genome of P. stoliczkana.

 

Table I. Origins of mitochondrial genomes of Cyprinidae fishes.

Taxon (Species)

Size (bp)

AT %

AT-Skew

GC-Skew

Accession number

Cyprinidae

Smiliogastrinae

Barbodes binotatus

16573

57

0.159

-0.281

KY305681

Barbodes semifasciolatus

16594

58.2

0.103

-0.256

KC113209

Dawkinsia denisonii

16899

58.6

0.126

-0.263

KF019637

Enteromius thysi

16688

60.5

0.085

-0.22

OP819561

Enteromius trimaculatus

16417

60.8

0.049

-0.188

AB239600

Hampala macrolepidota

16766

58.2

0.151

-0.285

KF670818

Hampala salweenensis

16913

58.9

0.14

-0.284

MW548258

Oliotius oligolepis

16636

58.4

0.102

-0.247

ON864407

Oreichthys crenuchoides

16596

60.2

0.087

-0.209

MK456608

Osteobrama belangeri

16602

60.7

0.091

-0.239

KY887473

Osteobrama belangeri

16594

60.7

0.091

-0.239

MK749691

Pethia padamya

16792

58.6

0.109

-0.225

ON864408

Pethia stoliczkana

16996

59.7

0.109

-0.247

OP785085

Pethia ticto

17302

60

0.109

-0.249

AB238969

Puntigrus tetrazona

16550

59.8

0.095

-0.242

EU287909

Puntius sachsii

16587

58.2

0.103

-0.256

MZ364158

Puntius snyderi

16578

59.3

0.097

-0.251

KC113210

Sahyadria chalakkudiensis

16989

59.9

0.112

-0.259

JX311437

Systomus sarana

16590

58.6

0.122

-0.256

KU886061

Cyprininae (outgroup)

Sinocyclocheilus bicornutus

17426

57.9

0.119

-0.273

KX528071

Schizopygopsinae

Gymnocypris eckloni

16686

56.1

0.024

-0.179

JQ004279

 

Phylogenetic analysis

To examine the phylogenetic status of P. stoliczkana in Smiliogastrinae, the nucleotide sequences of 13 protein-coding genes (PCGs) in the mitochondrial genome were used for phylogenetic analysis. The mitochondrial genomes from 18 species of Smiliogastrinae were selected as reference sequences, and a phylogenetic tree was constructed using the maximum likelihood (ML) and Bayesian (BI) methods, with Sinocyclius bicornutus and Gymnocypris eckloni as the outgroup (Table I). After multiple nucleotide sequence alignments using Cluster X 2.0 (Larkin et al., 2007), the results were filtered using Gblocks v0.91b (Castresana, 2000), and the alignment results for each gene were concatenated using SequenceMatrix v1.7 (Vaidya et al., 2011). Using SMS software (Lefort et al., 2017) and ModelFinder (Kalyaanamoorthy et al., 2017), the most suitable alternative model obtained from the evaluation of the tree-building dataset was GTR+I+G. The ML phylogenetic tree was built through 50,000 bootstrap operations using PhyML 3.0 (Guindon et al., 2010). MrBayes3 (Ronquist and Huelsenbeck, 2003) was used to calculate 20,000,000 generations, with the sequences sampled and saved every 100 generations; we discarded 25% of the aging samples and built a BI phylogenetic tree.

Results

Gene structure and composition

The mitochondrial genome of P. stoliczkana obtained using high-throughput sequencing was 16,993 bp in length (Fig. 1) and contained 22 tRNA genes (tRNAs), 13PCGs, two ribosomal RNA genes (rRNAs), and one control region.

 

Table II. Characteristics of the mitochondrial genome of Pethia stoliczkana.

Gene

Position

Size

Intergenic nucleotides

Codon

From

To

Start

Stop

Strand

tRNA-Phe

1

69

69

0

H

12S RNA

70

1025

956

0

H

tRNA-Val

1026

1097

72

0

H

16S RNA

1098

2780

1683

0

H

tRNA-Leu2

2781

2855

75

1

H

ND1

2857

3831

975

12

ATG

TAA

H

tRNA-Ile

3844

3915

72

-1

H

tRNA-Gln

3915

3985

71

1

L

tRNA-Met

3987

4055

69

0

H

ND2

4056

5100

1045

0

ATG

T

H

tRNA-Trp

5101

5171

71

1

H

tRNA-Ala

5173

5241

69

1

L

tRNA-Asn

5243

5315

73

31

L

tRNA-Cys

5347

5413

67

-1

L

tRNA-Tyr

5413

5482

70

1

L

COI

5484

7034

1551

0

GTG

TAA

H

tRNA-Ser2

7035

7105

71

1

L

tRNA-Asp

7107

7178

72

9

H

COII

7188

7878

691

0

ATG

T

H

tRNA-Lys

7879

7954

76

1

H

ATP8

7956

8120

165

-7

ATG

TAG

H

ATP6

8114

8796

683

0

ATG

TA

H

COIII

8797

9580

784

0

ATG

T

H

tRNA-Gly

9581

9653

73

0

H

ND3

9654

10002

349

0

ATG

T

H

tRNA-Arg

10003

10072

70

0

H

ND4L

10073

10369

297

-7

ATG

TAA

H

ND4

10363

11743

1381

0

ATG

T

H

tRNA-His

11744

11812

69

0

H

tRNA-Ser1

11813

11880

68

1

H

tRNA-Leu1

11882

11954

73

3

H

ND5

11958

13781

1824

-4

ATG

TAA

H

ND6

13778

14299

522

0

ATG

TAA

L

tRNA-Glu

14300

14368

69

6

L

Cyt b

14375

15515

1141

0

ATG

T

H

tRNA-Thr

15516

15587

72

-1

H

tRNA-Pro

15587

15656

70

0

L

D-loop

15657

16996

1340

0

H

 

In the control region, eight tRNAs and ND6 genes were in the light chain (L chain) and the remaining 28 genes were in the heavy chain (H chain) (Table II). There were six gene overlaps and 13 gene gaps in the whole mitochondrial genome of P. stoliczkana (Fig. 1, Table II). The total length of the gene interval was 69 bp, with a maximum interval of 31 bp between tRNA-Asn and tRNA-Cys. The total length of gene overlap was 21 bp. Large overlaps were observed between ATP8 and ATP6, ND4L, and ND4. The base number of the overlap was 7 bp. The A+T content (59.7%) was higher than the G+C content (40.3%) in the mitochondrial genome of P. stoliczkana, revealing a preference for A+T and base anti-G bias. These results are consistent with the preference for A+T bases in vertebrates (Sun et al., 2020, 2022, 2023).

 

Table III. Nucleotide composition of protein-coding genes and rRNA in Pethia stoliczkana.

Gene

length (bp)

T (%)

C (%)

A (%)

G (%)

AT (%)

GC (%)

AT skew

GC skew

ATP6

683

29.6

26.1

32.5

11.9

62.1

38

0.047

-0.375

ATP8

165

27.9

26.1

35.8

10.3

63.7

36.4

0.124

-0.433

COⅠ

1551

30.3

23.8

28.4

17.5

58.7

41.3

-0.032

-0.153

COⅡ

691

27.1

24.6

33.6

14.8

60.7

39.4

0.107

-0.25

COⅢ

784

27.4

26.9

30.1

15.6

57.5

42.5

0.047

-0.267

Cyt b

1141

29.4

26.6

30.8

13.2

60.2

39.8

0.023

-0.336

ND1

975

27.4

26.2

31.9

14.6

59.3

40.8

0.076

-0.285

ND2

1045

24.5

28.4

35.3

11.8

59.8

40.2

0.181

-0.414

ND3

349

32.7

24.4

30.4

12.6

63.1

37

-0.036

-0.318

ND4

1381

27.5

27.2

30.9

14.4

58.4

41.6

0.058

-0.307

ND4L

297

27.9

27.9

27.6

16.5

55.5

44.4

-0.006

-0.258

ND5

1824

27.2

25.3

35

12.5

62.2

37.8

0.125

-0.339

ND6

522

43.1

11.5

15.9

29.5

59

41

-0.461

0.439

16S RNA

1683

21.5

22.5

36.8

19.3

58.3

41.8

0.262

-0.077

12S RNA

956

19.8

26.6

32.5

21.1

52.3

47.7

0.244

-0.114

 

PCGs

The total length of the 13 PCGs in the mitochondrial genome of P. stoliczkana was 11,408 bp. Except for ND6, which is in the L chain, all genes were in the H chain. Among the 13PCGs, the start codon of the COI gene was GTG, and the remaining start codons were ATG. Deletion of the termination codon is typically thought to be caused by polyadenylation. We found that the termination codons of the ND2, CO II, ATP6, CO III, ND3, ND4, and Cyt b genes in the mitochondrial genome of P. stoliczkana had the incomplete codons T or TA (Table II), which is common in the mitochondrial genomes of metazoa and similar to the termination codons of most mitochondrial PCGs in teleost fish. The uneven distribution of bases is one of the most characteristic features of coding regions. Although the base contents of the different gene fragments differed, they all presented a lower G content and higher A+T enrichment (Table III).

Codon usage and amino acid composition

The relative synonymous codon usage of the P. stoliczkana mitochondrial genome was analyzed using MEGA to determine the ratio of the expected frequency of amino acids using synonymous codons to their observed frequency (Table IV, Fig. 2). There were 25 preferred codons (relative synonymous codon usage ≥1) (Behura and Severson, 2013) in the 13 PCGs of P. stoliczkana. The 11,408-bp gene sequence encoded 3794 amino acids. The most common amino acid in the mitochondrial genome of P. stoliczkana was leucine (Leu), with a content of (11.12%), whereas the least used amino acid was cysteine (Cys), with a content of only 0.66%.

 

Table IV. Frequency of codon usage in 13 protein-coding genes.

Codon

Count

RSCU

Codon

Count

RSCU

Codon

Count

RSCU

Codon

Count

RSCU

UUU(F)

128

1.09

UCU(S)

34

0.89

UAU(Y)

56

0.96

UGU(C)

9

0.72

UUC(F)

106

0.91

UCC(S)

42

1.1

UAC(Y)

61

1.04

UGC(C)

16

1.28

UUA(L)

184

1.8

UCA(S)

105

2.74

UAA(*)

5

3.33

UGA(W)

105

1.78

UUG(L)

7

0.07

UCG(S)

3

0.08

UAG(*)

1

0.67

UGG(W)

13

0.22

CUU(L)

86

0.84

CCU(P)

22

0.43

CAU(H)

34

0.64

CGU(R)

9

0.49

CUC(L)

63

0.62

CCC(P)

32

0.62

CAC(H)

73

1.36

CGC(R)

4

0.22

CUA(L)

239

2.34

CCA(P)

144

2.81

CAA(Q)

96

1.88

CGA(R)

53

2.86

CUG(L)

34

0.33

CCG(P)

7

0.14

CAG(Q)

6

0.12

CGG(R)

8

0.43

AUU(I)

205

1.41

ACU(T)

52

0.66

AAU(N)

47

0.79

AGU(S)

10

0.26

AUC(I)

86

0.59

ACC(T)

101

1.28

AAC(N)

72

1.21

AGC(S)

36

0.94

AUA(M)

154

1.61

ACA(T)

157

1.99

AAA(K)

83

1.95

AGA(*)

0

0

AUG(M)

37

0.39

ACG(T)

5

0.06

AAG(K)

2

0.05

AGG(*)

0

0

GUU(V)

52

0.98

GCU(A)

58

0.69

GAU(D)

21

0.56

GGU(G)

29

0.48

GUC(V)

34

0.64

GCC(A)

127

1.52

GAC(D)

54

1.44

GGC(G)

36

0.6

GUA(V)

111

2.08

GCA(A)

142

1.7

GAA(E)

91

1.75

GGA(G)

125

2.07

GUG(V)

16

0.3

GCG(A)

8

0.1

GAG(E)

13

0.25

GGG(G)

51

0.85

 

 

rRNA, tRNA, and control region

Similar to those in common bony fish, the mitochondrial genome of P. stoliczkana contained 12S rRNA and 16S rRNA, which were between tRNA-Phe and tRNA-Leu2 on the H chain and separated from each other by tRNA-Val. The 12S rRNA sequence was 956 bp in length, its position in the mitochondrial sequence was 69–1025 bp, the length of the 16S rRNA sequence was 1683 bp, and its position in the mitochondrial sequence was 1098–2780 bp. The mitochondrial genome of P. stoliczkana was found to contain 22 tRNAs with a length of 67–76 bp. The 1340-bp control region was between tRNA-Pro and tRNA-Phe.

Phylogenetic relationships

ML and BI phylogenetic trees of Smiliogastrinae were constructed based on the nucleotide tandem sequences of the 13 PCGs. The two tree-building methods generated consistent topological structures (Figs. 3 and 4). Pethia stoliczkana and Pethia ticto were clustered into one branch together with P. padamya, with confidence values of 100%. Except for the genus Puntius, all genera were clustered into one branch with a high confidence value.

 

 

Discussion

With advancements in DNA sequencing technology and the rapid development of bioinformatics, fish mitochondrial genomes have been widely studied in the fields of fish germplasm protection, species identification, population polymorphism, and phylogenetic development. Previous studies showed that the mitochondrial genome of fish is typically 15–20 kb, often has a double-stranded closed circular structure, is closely arranged, and has a low molecular weight. The mitochondrial genomes of different species vary widely and contain tandem repeats, base insertions, and deletions (Peng et al., 2006). Each PCG has a different evolution rate. Zardoya and Meyer (1996) divided the evolution rates of 13 PCGs into good, medium, and poor groups, in which COI, ND2, ND4, Cytb, and ND5 genes were good, and COII, COIII, ND1, and ND6 were medium. ATP6, ATP8, ND3, and ND4L levels were poor. The evolution rate of most PCGs was between that in the control region and RNA, showing a moderate evolution rate. Pethia stoliczkana genes, such as CO I, Cyt b, and ND, which exhibit a rapid evolution rate, can be used as molecular markers to distinguish these fish from other Smiliogastrinae fishes and provide a reference for their germplasm resource protection. However, the 16S rRNA sequence in the mitochondrial genome is not a PCG and is not affected by codon selection pressure. Most mutations were neutral. In addition, the evolution rate of mtDNA is significantly higher than that of nuclear DNA. Therefore, the homology of mitochondrial 16S rRNA sequences can be compared to study phylogenetic relationships between species.

The system information contained in a single gene is too small to reflect the entire level of biological molecular evolution; thus, the results obtained by analyzing gene sequences encoded by multiple genomes are more reliable. In fish, the whole mitochondrial genome is widely used to study phylogenetic relationships at different stages. This study provides a basis for germplasm identification, phylogenetic evolution analysis, genetic diversity evaluation, and utilization of P. stoliczkana.

Conclusion

The whole mitochondrial genome of P. stoliczkana was obtained using second-generation sequencing. The arrangement pattern of genes in the mitochondrial genome was the same as that of P. ticto and P. padamya and was consistent with the ancestral pattern. Phylogenetic analysis supports the monophyly of the genus Pethia.

Acknowledgements

This research was funded by the Doctoral Research Fund of Mudanjiang Normal University [grant number 1002319042]. We would like to thank Editage (www.editage.cn) for English language editing.

Funding

This research was funded by the Doctoral Research Fund of Mudanjiang Normal University [grant number 1002319042].

IRB approval

All experiments were approved by the Animal Ethics Committee of the Mudanjiang Normal University and conducted in compliance with relevant animal welfare and protection laws.

Ethical statement

All experiments were conducted in accordance with Chinese laws.

Statement of conflict of interest

The authors have declared no conflict of interest.

References

Atkore, V.M., Knight, J.M., Devi, K.R. and Krishnaswamy, J., 2015. A new species of Pethia from the western Ghats, India (Teleostei: Cyprinidae). Copeia, 103: 290-296. https://doi.org/10.1643/OT-12-172

Avise, J.C., Arnold, J., Ball, R.M., Bermingham, E., Lamb, T., Neigel, J.E., Reeb, C.A. and Saunders, N.C., 1987. Intraspecific phylogeography: The mitochondrial DNA bridge between population genetics and systematics. Annu. Rev. Ecol. Syst., 18: 489-522. https://doi.org/10.1146/annurev.es.18.110187.002421

Bankevich, A., Nurk, S., Antipov, D., Gurevich, A.A., Dvorkin, M., Kulikov, A.S., Lesin, V.M., Nikolenko, S.I., Pham, S., Prjibelski, A.D., Pyshkin, A.V., Sirotkin, A.V., Vyahhi, N., Tesler, G., Alekseyev, M.A. and Pevzner, P.A., 2012. SPAdes: A new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol., 19: 455-477. https://doi.org/10.1089/cmb.2012.0021

Behura, S.K. and Severson, D.W., 2013. Codon usage bias: Causative factors, quantification methods and genome-wide patterns with emphasis on insect genomes. Biol. Rev., 88: 49-61. https://doi.org/10.1111/j.1469-185X.2012.00242.x

Bernt, M., Donath, A., Jühling, F., Externbrink, F., Florentz, C., Fritzsch, G., Pütz, J., Middendorf, M. and Stadler, P.F., 2013. MITOS: Improved de novo metazoan mitochondrial genome annotation. Mol. Phylogenet. Evol., 69: 313-319. https://doi.org/10.1016/j.ympev.2012.08.023

Boetzer, M., Henkel, C.V., Jansen, H.J., Butler, D. and Pirovano, W., 2011. Scaffolding pre-assembled contigs using SSPACE. Bioinformatics, 27: 578-579. https://doi.org/10.1093/bioinformatics/btq683

Castresana, J., 2000. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol., 17: 540-552. https://doi.org/10.1093/oxfordjournals.molbev.a026334

Funk, D.J. and Omland, K.E., 2003. Species-level paraphyly and polyphyly: Frequency, causes, and consequences, with insights from animal mitochondrial DNA. Annls Rev. Ecol. Evol. Syst., 34: 397-423. https://doi.org/10.1146/annurev.ecolsys.34.011802.132421

Guindon, S., Dufayard, J.F., Lefort, V., Anisimova, M., Hordijk, W. and Gascuel, O., 2010. New algorithms and methods to estimate maximum-likelihood phylogenies: Assessing the performance of PhyML 3.0. Syst. Biol., 59: 307-321. https://doi.org/10.1093/sysbio/syq010

Kalyaanamoorthy, S., Minh, B.Q., Wong, T.K., Von Haeseler, A. and Jermiin, L.S., 2017. Model finder: Fast model selection for accurate phylogenetic estimates. Nat. Methods, 14: 587-589. https://doi.org/10.1038/nmeth.4285

Larkin, M.A., Blackshields, G., Brown, N.P., Chenna, R., McGettigan, P.A., McWilliam, H., Valentin, F., Wallace, I.M., Wilm, A., Lopez, R., Thompson, J.D., Gibson, T.J. and Higgins, D.G., 2007. Clustal W and Clustal X version 2.0. Bioinformatics, 23: 2947-2948. https://doi.org/10.1093/bioinformatics/btm404

Lefort, V., Longueville, J.E. and Gascuel, O., 2017. SMS: smart model selection in PhyML. Mol. Biol. Evol., 34: 2422-2424. https://doi.org/10.1093/molbev/msx149

Lowe, T.M. and Chan, P., 2016. tRNAscan-SE On-line: Integrating search and context for analysis of transfer RNA genes. Nucl. Acids Res., 44: W54-W57. https://doi.org/10.1093/nar/gkw413

Nath, D., Dutta, R., Sarmah, R., Ahmed, A.M., Pokhrel, H., Mudoi, L.P. and Bhagabati, S.K., 2022. First record of a barb, Pethia stoliczkana (Day) from Brahmaputra drainage, Assam, India. J. appl. Ichthyol., 38: 609-614. https://doi.org/10.1111/jai.14363

Patel, R.K. and Jain, M., 2012. NGS QC Toolkit: A toolkit for quality control of next generation sequencing data. PLoS One, 7: e30619. https://doi.org/10.1371/journal.pone.0030619

Peng, Z., Wang, J. and He, S., 2006. The complete mitochondrial genome of the helmet catfish Cranoglanis bouderius (Siluriformes: Cranoglanididae) and the phylogeny of otophysan fishes. Gene, 376: 290-297. https://doi.org/10.1016/j.gene.2006.04.014

Ronquist, F. and Huelsenbeck, J.P., 2003. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics, 19: 1572-1574. https://doi.org/10.1093/bioinformatics/btg180

Sun, C.H., Huang, Q., Zeng, X.S., Li, S., Zhang, X.L., Zhang, Y.N., Liao, J., Lu, C.H., Han, B.P. and Zhang, Q., 2022. Comparative analysis of the mitogenomes of two Corydoras (Siluriformes, Loricarioidei) with nine known Corydoras, and a phylogenetic analysis of Loricarioidei. Zookeys, 1083: 89–107. https://doi.org/10.3897/zookeys.1083.76887

Sun, C.H., Liu, H.Y. and Lu, C.H., 2020. Five new mitogenomes of Phylloscopus (Passeriformes, Phylloscopidae): Sequence, structure, and phylogenetic analyses. Int. J. Biol. Macromol., 146: 638-647. https://doi.org/10.1016/j.ijbiomac.2019.12.253

Sun, C.H., Sun, P.Y., Lao, Y.L., Wu, T., Zhang, Y.N., Huang, Q. and Zhang, Q., 2023. Mitogenome of a monotypic genus, Oliotius Kottelat, 2013 (Cypriniformes: Cyprinidae): Genomic characterization and phylogenetic position. Gene, 851: 147035. https://doi.org/10.1016/j.gene.2022.147035

Tamura, K., Stecher, G. and Kumar, S., 2021. MEGA11: molecular evolutionary genetics analysis version 11. Mol. Biol. Evol., 38: 3022-3027. https://doi.org/10.1093/molbev/msab120

Vaidya, G., Lohman, D.J. and Meier, R., 2011. Sequence matrix: Concatenation software for the fast assembly of multi-gene datasets with character set and codon information. Cladistics, 27: 171-180. https://doi.org/10.1111/j.1096-0031.2010.00329.x

Wolstenholme, D.R., 1992. Animal mitochondrial DNA: Structure and evolution. Int. Rev. Cytol., 141: 173-216. https://doi.org/10.1016/S0074-7696(08)62066-5

Zardoya, R. and Meyer, A., 1996. Phylogenetic performance of mitochondrial protein-coding genes in resolving relationships among vertebrates. Mol. Biol. Evol., 13: 933-942. https://doi.org/10.1093/oxfordjournals.molbev.a025661

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Pakistan Journal of Zoology

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Pakistan J. Zool., Vol. 56, Iss. 5, pp. 2001-2500

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