Corresponding author: Yi Yang (
Academic editor: Graham Oliver
Different from the true oyster (family
This research was funded by the Hainan Provincial Natural Science Foundation of China (322QN260), the Key Research and Development Project of Hainan Province (ZDYF2021SHFZ269), the National Key Research and Development Program of China (2019YFD0901301) and the Hainan Province Graduate Innovation Project (Qhys2022-124).
The authors report no conflicts of interest.
Oysters belong to superfamily
Previous studies have implied the effectiveness of mitochondrial DNA (mtDNA) as the molecular marker to reveal genetic diversity (
Despite the existence of one complete mitochondrial genome within
to characterise the mitogenomic features of to explore the gene order rearrangements within
The specimen of
Whole genomic DNA was extracted from the adductor muscle of one individual using TIANamp Marine Animals DNA Kit (Tiangen, Beijing, China) in accordance with the manufacturer’s instructions. The genomic DNA was visualised on 1% agarose gel for quality inspection.
Genomic DNA of
Due to the existence of a duplicated region, which is more than 2,000 bp, this mitogenome is not able to be completely assembled only with the Illumina short reads. Therefore, a long PCR amplification was intended to fill the assembled gap using the 1F forward (5′-GGGGGTAAGATATTTTGTGCAGCGA-3′) and 1R reverse (5′-TCGACAGGTGGGCTAGACTTAACGC-3′) specific primers designed in the present study. The long PCR reactions contained 2.5 μl of 10× buffer (Mg2+ plus), 3 μl of dNTPs (2.5 mM), 0.5 μl of each primer (10 μM), 0.8 μl of template DNA (25–40 ng/μl), 0.2 μl of TaKaRa LA Taq DNA polymerase (5 U/μl) and DEPC (Diethypyrocarbonate) water up to 25 μl. Long PCR reactions were conducted by initial denaturation step at 94°C for 60 s, followed by 35 cycles of: 10 s at 98°C, 30 s at 57°C and 5 min at 68°C, then a final extension step at 68°C for 10 min. The PCR products were purified by ethanol precipitation and sequenced at Beijing Liuhe BGI (Beijing, China). The PCR primers were used as sequence primers.
The mitogenome of
The nucleotide composition of the whole complete mitogenome, PCGs, rRNA and tRNA genes was computed using MEGA X (
A total of 21 ostreoid species was included for phylogenetic reconstruction (Table
The Maximum Likelihood method (ML) and Bayesian Inference method (BI) were used for phylogenetic reconstruction. ML trees were constructed by IQtree 1.6.12 (
Misidentifications are quite frequent in oyster mitogenomics. This is the case for the example of the recently-published mitogenome of
This mitogenome was firstly assembled. based on the next-generation data using two different types of software, resulting in almost identical results. However, two repetitive sequences that corresponded to the partial
The total length of
The overall AT content of the
The AT content of the concatenated PCGs is 57.0% (Table
The PCG start/stop codon usage preference of
The AT content of the concatenated tRNAs is 56.3%, while the AT skew and GC skew are -0.14 and 0.19, respectively (Table
The
According to the BIC, the best partition scheme is the one combining genes by subunits, but analysing each codon position separately (Suppl. material
The phylogenetic relationships within
Within
Within
Fengping Li and Hongyue Liu contributed equally to this work and should be considered co-first authors. AW and YY designed the study; XH, YZ, MF, SW, ZG and CL collected the data; FL and HL performed the analyses; FL, HL and YY wrote the first draft of the manuscript; and all authors contributed intellectually to the manuscript.
The authors report no conflicts of interest.
The image of
Mitochondrial genome map of
Inferred secondary structures of 26 transfer RNAs from
Relative synonymous codon usage (RSCU) of mitochondrial genome for
Alignment of
Phylogenetic relationships of
Linearised PCG order of
List of mitochondrial genomes used in this study.
|
|||||||
|
|
|
|
|
|||
|
|
30,385 | June 2022 |
|
|||
|
|||||||
|
|
|
|
||||
|
|
22,185 |
|
||||
|
|
16,338 |
|
||||
|
|
18,225 |
|
||||
|
|
18,225 |
|
||||
|
|
18,617 |
|
||||
|
|
22,420 |
|
||||
|
|
21,020 |
|
||||
|
|
20,030 |
|
||||
|
|
22,446 |
|
||||
|
|
18,414 |
|
||||
|
|
18,243 |
|
||||
|
|
18,225 |
|
||||
|
|
17,685 |
|
||||
|
|
17,244 |
|
||||
|
|
16,277 |
|
||||
|
|
16,320 |
|
||||
|
|
16,344 |
|
||||
|
|
16,532 |
|
||||
|
|
16,396 |
|
||||
|
|
16,260 |
|
||||
|
|
15,680 |
|
||||
|
|
16,994 |
|
Gene annotations of the complete mt genome of
|
|
|
|
|
|
|
|
H | 1-1986 | 1986 | ATG | TAA | 1936 |
tRNA- |
H | 3923-3989 | 67 | 842 | ||
tRNA- |
H | 4832-4898 | 67 | 81 | ||
tRNA- |
H | 4944-5006 | 63 | 0 | ||
|
H | 5007-6335 | 1329 | 212 | ||
|
H | 6548-7491 | 944 | 74 | ||
tRNA- |
H | 7566-7632 | 67 | 97 | ||
tRNA- |
H | 7730-7799 | 70 | 105 | ||
|
H | 7905-8978 | 1074 | ATG | TAG | 185 |
tRNA- |
H | 9164-9230 | 67 | 220 | ||
tRNA- |
H | 9451-9539 | 89 | 54 | ||
tRNA- |
H | 9594-9682 | 89 | 203 | ||
tRNA- |
H | 9886-9948 | 63 | 37 | ||
tRNA- |
H | 9986-10051 | 66 | 9 | ||
tRNA- |
H | 10061-10125 | 65 | 16 | ||
|
H | 10142-11507 | 1366 | 192 | ||
|
H | 11700-12643 | 944 | 164 | ||
tRNA- |
H | 12808-12870 | 63 | 179 | ||
tRNA- |
H | 13050-13115 | 66 | 91 | ||
tRNA- |
H | 13207-13269 | 63 | 537 | ||
tRNA- |
H | 13807-13874 | 68 | 1112 | ||
tRNA- |
H | 14987-15049 | 63 | 3901 | ||
|
H | 18951-19290 | 340 | ATT | T | 444 |
tRNA- |
H | 19735-19801 | 67 | 2 | ||
tRNA- |
H | 19804-19869 | 66 | 7 | ||
tRNA- |
H | 19877-19946 | 70 | 25 | ||
tRNA- |
H | 19972-20039 | 68 | 13 | ||
tRNA- |
H | 20053-20115 | 63 | 29 | ||
tRNA- |
H | 20145-20211 | 67 | 30 | ||
tRNA- |
H | 20242-20305 | 64 | 27 | ||
|
H | 20333-21028 | 696 | ATG | TAG | 125 |
|
H | 21154-22785 | 1632 | ATA | TAG | 78 |
|
H | 22864-23883 | 1020 | ATT | TAA | 14 |
tRNA- |
H | 23898-23965 | 68 | 6 | ||
|
H | 23975-25828 | 1857 | TTG | TAG | 96 |
|
H | 25925-26527 | 603 | ATG | TAG | 30 |
tRNA- |
H | 26558-26620 | 63 | 1 | ||
|
H | 26622-27965 | 1344 | ATG | TAG | 74 |
|
H | 28040-28786 | 747 | ATG | TAG | |
|
H | 28855-29145 | 291 | TTG | TAG | 35 |
tRNA- |
H | 29181-29243 | 63 | 209 | ||
|
H | 29453-30331 | 879 | TTT | TAA | 54 |
List of AT content, AT skew and GC skew of
Feature | (A+T)% | AT skew | GC skew |
Whole genome | 57.2 | -0.15 | 0.27 |
PCGs | 57.0 | -0.23 | 0.29 |
PCGs1 | 55.7 | -0.24 | 0.40 |
PCGs2 | 56.4 | -0.13 | 0.28 |
PCGs3 | 58.7 | -0.31 | 0.19 |
|
60.3 | -0.26 | 0.39 |
|
58.4 | -0.16 | 0.24 |
|
57.8 | -0.25 | 0.29 |
|
56.2 | -0.30 | 0.20 |
|
57.1 | -0.16 | 0.23 |
|
55.8 | -0.18 | 0.21 |
|
57.5 | -0.29 | 0.26 |
|
55.8 | -0.35 | 0.44 |
|
55.5 | -0.30 | 0.34 |
|
54.7 | -0.17 | 0.45 |
|
56.3 | -0.25 | 0.37 |
|
56.2 | -0.15 | 0.39 |
tRNAs | 56.3 | -0.14 | 0.19 |
|
57.6 | -0.03 | 0.20 |
|
52.8 | 0.09 | 0.13 |
|
58.4 | -0.02 | 0.20 |
|
52.6 | 0.10 | 0.13 |
Codon and relative synonymous codon usage (RSCU) of 12 protein-coding genes (PCGs) in the mtDNA of
Amino Acid | Codon | Count (RSCU) | Amino Acid | Codon | Count (RSCU) |
Phe | UUU | 254.0(1.69) | Ala | GCU | 101.0(1.54) |
UUC | 47.0(0.31) | GCC | 47.0(0.71) | ||
Leu | UUA | 83.0(1.06) | GCA | 47.0(0.71) | |
UUG | 189.0(2.42) | GCG | 68.0(1.03) | ||
CUU | 66.0(0.84) | Gly | GGU | 73.0(0.83) | |
CUC | 21.0(0.27) | GGC | 47.0(0.53) | ||
CUA | 39.0(0.50) | GGA | 82.0(0.93) | ||
CUG | 71.0(0.91) | GGG | 151.0(1.71) | ||
Ile | AUU | 191.0(1.65) | Arg | CGU | 35.0(1.26) |
AUC | 40.0(0.35) | CGC | 20.0(0.72) | ||
Met | AUA | 63.0(0.57) | CGA | 30.0(1.08) | |
AUG | 159.0(1.43) | CGG | 26.0(0.94) | ||
Val | GUU | 151.0(1.52) | Tyr | UAU | 136.0(1.50) |
GUC | 48.0(0.48) | UAC | 45.0(0.50) | ||
GUA | 69.0(0.69) | His | CAU | 47.0(1.08) | |
GUG | 130.0(1.31) | CAC | 40.0(0.92) | ||
Ser | UCU | 90.0(1.97) | Gln | CAA | 22.0(0.80) |
UCC | 21.0(0.46) | CAG | 33.0(1.20) | ||
UCA | 29.0(0.63) | Asn | AAU | 77.0(1.43) | |
UCG | 43.0(0.94) | AAC | 31.0(0.57) | ||
AGU | 27.0(0.59) | Lys | AAA | 86.0(0.98) | |
AGC | 20.0(0.44) | AAG | 89.0(1.02) | ||
AGA | 73.0(1.60) | Asp | GAU | 75.0(1.61) | |
AGG | 63.0(1.38) | GAC | 18.0(0.39) | ||
Pro | CCU | 65.0(1.70) | Glu | GAA | 57.0(0.77) |
CCC | 26.0(0.68) | GAG | 92.0(1.23) | ||
CCA | 28.0(0.73) | Cys | UGU | 64.0(1.28) | |
CCG | 34.0(0.89) | UGC | 36.0(0.72) | ||
Thr | ACU | 70.0(1.74) | Trp | UGA | 62.0(0.73) |
ACC | 27.0(0.67) | UGG | 107.0(1.27) | ||
ACA | 28.0(0.70) | * | UAA | 3.0(0.55) | |
ACG | 36.0(0.89) | UAG | 8.0(1.45) |
Table
File: oo_801937.docx