SUN Shao’e, LI Qi, 2), *, and KONG Lingfeng

Relaxation of Selective Constraint on the Ultra-Large Mitochondrial Genomes of Arcidae (Mollusca: Bivalvia)

SUN Shao’e1), LI Qi1), 2), *, and KONG Lingfeng1)

1),,,266003,2),,266237,

The mitochondrial genomes (mitogenomes) are purportedly under selection for smallersize to improve their replication and translation efficiency. However, the mitogenomes of Arcidae species are larger than those of other bivalves, and are among the largest metazoan mitogenomes reported to date. In order to explore the differences of base composition and selective constraints between the large and small mitogenomes, we compared the mitogenomes of 9 large arcid mitogenomes and 77 small bivalves mitogenomes. Base composition analyses indicated that Arcidae mitogenomes have significantly greater GC skews in both their whole genomes and coding sequences. This result suggeststhat the replication of the large mitogenomes in Arcidae may be slower than those in other bivalves, exposing the parental strand to deamination for a longer time. Selection pressure analyses showed that the mitochondrial protein-coding genes of Arcidae species have significantly highera/s ratios than other bivalves, suggesting that they have accumulated more nonsynonymous nucleotide substitutions. Seven protein-coding genes (,,,and) show significant difference fora/s ratios between the Arcidae and non-Arcidae groups. However, these divergences are not observed in the nuclear gene within histone H3. From these observations, we concluded that the large mitogenomes of Arcidae species experienced more relaxed selective constraints. As some Arcidae species are more tolerant to hypoxia that can lead to low metabolic rate, the relaxed selective constraints of mitogenomes may be energy-related. This study provides new insights into the evolution of Arcidae mitogenomes.

Arcidae; mitochondrial genome; genome size; relaxed selective constraint

1 Introduction

The mitochondrial genomes (mitogenomes) of most bi- laterian animals include a standard set of 13 protein-co-ding genes (PCGs), 2 ribosomal RNA (rRNA) genes, 22transfer RNA (tRNA) genes, and an A+T-rich region (Boore, 1999). Although there are exceptions, most mitogenomes size are from 14 to 17kb. Typically, few intergenic nucleo- tides exist except for a single large non-coding region, whichwere thought to contain elements that control the initia-tion of replication and transcription of the mitogenome (Boore, 1999; Lavrov, 2007). This consistency in gene con- tent across distantly related lineages, as well as the lack of intergenic spacers, suggests that the mitogenome is under selection for compact size (Rand and Harrison, 1986). Com- pared with nuclear genome, the mitogenome has several advantages including conserved gene content, maternal in- heritance, lack of extensive recombination, and relatively high nucleotide substitution rates (Boore, 1999; Curole and Kocher, 1999; Gissi., 2008). These advantages make it a good model for the studies of evolutionary genomics (Saccone., 1999; Gissi., 2008; Cameron, 2014).

Molluscs, especially bivalves, usually display an extra- ordinary amount of variation in mitogenome structure and size, even with differences in the closely related species (Gissi., 2008; Simison and Boore, 2008). The size of the bivalve mitogenomes are highly variable, ranging from14622 in(Park and Ahn, 2015) to 46985bp in(Liu., 2013) in length. Several bivalve species have showed large sizes of mitogenomes (greater than 20kb). The mitogenome size of the deep sea scallopis up to 40725bp (Smith and Snyder, 2007) and the mitogenome of Zhikong scallopis 21695bp (Xu., 2011). The mitogenome size of Manila clamis 22676bp in female type and 21441bp in male type (Passamonti and Scali, 2001). The mitogenome of, Clavagellidae, is at least 31969bp long (Wil- liams., 2017). The size of Arcidae mitogenomes are more unusual, of which the largest mitogenome size is 46985bp () (Liu., 2013). The bivalve species have a sedentary lifestyle, with low meta- bolic rate (Sun., 2017). The previous researches pro- posed that the large mitogenome of bivalves perhaps experience weak purifying selection, which may be correlated with their low metabolic rates (Strotz., 2018; Kong., 2020).

Ark shells are among the oldest bivalve lineages, rea- ching back to the lower Ordovician which is about 450Myr (Morton., 1998). The species of Arcidae are glo- bally distributed, predominantly in the tropical shallow wa- ters and warm temperate seas, containing approximately 260 species and 31 genera (Oliver and Holmes, 2006). Mi- togenomes of ark shell species are among the largest me- tazoan mitogenomes reported to date, ranging from 18 to 56kb in length (Kong., 2020). It has been argued that animal mitogenomes are characterized by a tightly packed collection of conserved genes and other functional ele-ments, accompanying with drastic mitogenome size reduc- tion in evolutionary history of animal (Burger., 2003; Schneider and Ebert, 2004; Signorovitch., 2007). Ar- cidae presented a challenge to the point of selection favoring compact genomes by virtue of large mitogenome size. In our previous studies, we found the mitogenome size is positively correlated with the combined length of,and, the length of, and the combined length ofand(Sun., 2016). Researchers have found the inverted repeat sequences might facilitate the mitogenome expansions (Kong., 2020). It has been believed that metabolic rates influence the selective con- straints acting on the mitogenome, and purify selection act on small genome size (Rand, 1993). However, the natural selection act on the large mitogenome of Arcidae remains unexplored.

The large size of Arcidae mitogenomes lead to several questions. Firstly, whether the nucleotide compositions of large Arcidae mitochondrial DNA (mtDNA) are different from those of other bivalve species with small ones? Se- condly, what’s the difference in substitution rate of mtDNAbetween Arcidae and other bivalve species? Thirdly, do all the mitochondrial genes of Arcidae experience the same selection pressure? In order to address these questions, we conducted a comparative genomic analysis and test the roles of the evolutionary constraints on the mtDNA of Arcidae to provide a complete view of molecular evolution in the mtDNA.

2 Materials and Methods

2.1 Source of Data

The mtDNA sequences (Table 1) and nuclear gene (his- tone H3) (Table 2) of bivalves were downloaded from Gen- Bank. All the mitochondrial protein-coding genes were ex- tracted from each mitogenome.

2.2 Base Composition

AT and GC skew were calculated according to the for- mula defined by Perna and Kocher (1995), AT skew=(A?T)/(A+T) and GC skew=(G?C)/(G+C), which provides an index of compositional asymmetry between strands. Skews were calculated for all sites, and also for fourfold degenerate sites, which are expected to be less constrain- ed (Reyes, 1998). We then compared these measures of nucleotide skew between Arcoidae and non-Arcoidae taxa. All statistical analyses were performed with IBM SPSS Statistics, release 19.0.0.1.

Table 1 The mtDNA sequences of bivalves downloaded from GenBank

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SpeciesAccestion no.Ka/KsKaKsatp6cox-1cox-2cox-3cytbnd1nd2nd3nd4nd4lnd5nd6 Chlamys farreriEU7152520.0447 0.0635 1.4216 0.0919 0.0160 0.0688 0.0228 0.0640 0.0291 0.1366 0.0387 0.0374 0.0428 0.0729 0.0382 Mizuhopecten yessoensisAB2717690.0453 0.0571 1.2599 0.0529 0.0189 0.0532 0.0673 0.0564 0.0271 0.0809 0.0303 0.0326 0.0473 0.0454 0.0835 Argopecten irradiansEU0239150.0443 0.0340 0.7672 0.0065 0.0006 0.0887 0.0001 0.0087 –0.0278 0.6156 0.0135 0.0099 0.0439 – Argopecten purpuratusKF6012460.0240 0.0171 0.7128 0.0511 0.0031 0.0157 0.0001 0.0205 0.0372 ––0.0581 –0.0142 0.0405 Argopecten ventricosusKT1612610.0238 0.0061 0.2578 0.0094 0.0083 0.0146 0.0136 0.0408 0.0108 0.1215 0.0262 0.0087 0.0234 0.0373 0.3601 Pinctada margaritiferaHM4678380.0512 0.0648 1.2652 0.2361 0.0034 0.0963 0.0416 0.0429 0.0374 0.0354 0.0053 0.0518 0.0232 0.0419 0.0952 Pinctada maximaGQ4528470.0420 0.0596 1.4187 0.0689 0.0137 0.0321 0.0107 0.0168 0.0361 –0.0493 0.0155 0.0456 0.0071 0.0460 Mytilus trossulusGU9366250.0217 0.0119 0.5481 0.0152 0.0035 0.0026 0.0001 0.0113 0.0145 0.0683 –0.0494 0.0170 0.0424 0.0682 Mytilus californianusGQ5271720.0209 0.0100 0.4802 0.0340 0.0063 0.0078 0.0020 0.0128 0.0323 0.0367 0.0027 0.0186 0.0202 0.0390 0.0266 Mytilus edulisAY4847470.0042 0.0173 4.1351 0.0001 0.0167 0.0001 –0.7360 0.0001 0.4733 0.0001 0.2050 0.0001 0.0530 – Mytilus galloprovincialisAY4972920.0589 0.0006 0.0105 0.0001 0.0001 0.0537 0.0001 0.0001 0.0001 0.2241 0.0001 0.0476 0.0001 0.4803 0.0001 Mytilus coruscusKJ5775490.0406 0.0274 0.6756 0.0060 0.0023 0.0033 0.0076 0.0086 0.0204 0.0453 0.2561 0.1965 0.0226 0.0556 0.0245 Brachidontes exustusKM2336360.0187 0.0803 4.3003 0.0709 0.0101 0.0659 0.0300 0.0057 0.0208 0.0388 0.0121 0.0633 0.0275 0.0362 0.0509 Perna viridisJQ9704250.0328 0.1890 5.7562 0.0037 0.0154 0.0436 0.0477 0.0470 0.0233 0.0176 0.0200 0.0377 0.0017 0.0442 0.0547 Perna pernaKM6558410.0151 0.0801 5.3151 0.0402 0.0106 0.1130 0.0475 0.0013 0.0246 0.0164 0.0257 0.0366 0.0657 0.0140 0.0247 Musculista senhousiaGU0019540.0512 0.2326 4.5476 0.0687 0.0203 0.0706 0.0709 0.0287 0.0702 0.0792 0.0052 0.0777 0.0105 0.0540 0.0585 Meretrix petechialisEU1459770.0803 0.0001 0.0009 0.0000 0.0001 0.0001 0.0000 0.5377 –0.1904 0.0002 0.0002 0.0000 0.0000 0.0001 Meretrix lamarckiiGU0712810.0920 0.0059 0.0638 0.0780 0.0457 0.2167 0.1385 0.0828 0.0066 0.1492 0.0612 0.0442 0.1590 0.0790 0.0142 Meretrix meretrixGQ4635980.0332 0.0000 0.0005 0.2694 0.0000 0.0000 0.0001 0.0001 0.0000 0.0940 0.1328 0.0001 0.0001 0.1120 0.0588 Meretrix lusoriaGQ9033390.0602 0.0008 0.0129 0.0370 0.0251 0.0961 0.0195 0.0499 0.0222 0.0985 0.0001 0.2169 0.1643 0.0792 0.2989 Meretrix lyrataKC8323170.0573 0.0031 0.0541 –0.0473 0.0760 0.1010 0.0476 0.0259 0.1848 0.0084 0.0438 0.0793 0.0350 0.0995 Paphia euglyptaGU2692710.0274 0.0010 0.0375 0.0138 0.0085 0.0448 0.0227 0.0176 0.0327 0.0880 0.0178 0.0762 0.0001 0.0277 0.0646 Paphia undulataJF9692780.0276 0.0010 0.0345 0.0197 0.0088 0.0325 –0.0113 0.0316 0.0492 0.0106 0.0141 –0.0361 0.0311 Paphia textileJF9692770.0282 0.0008 0.0298 0.0208 0.0062 0.0703 0.0048 0.0213 0.0273 0.0315 0.0066 0.0395 0.0146 0.0479 0.0987 Paphia amabilisJF9692760.0600 0.0025 0.0411 0.0222 0.0598 0.0411 0.0369 0.0672 0.0266 0.0408 0.0270 0.0224 –0.0693 0.1035 Venerupis philippinarumAB0653750.0357 0.0078 0.2178 0.0598 0.0073 0.0228 0.0332 0.0277 0.0503 0.0608 0.0861 0.0227 1.1707 0.0070 0.3303 Saxidomus purpuratusKP4199330.0239 0.0031 0.1295 0.0216 0.0169 0.0567 0.0204 0.0452 0.0318 0.1331 0.0966 0.0174 0.0028 0.0184 0.1631 Solenaia oleivoraKF2963200.0556 0.0016 0.0286 0.0426 0.0017 0.0373 0.0269 0.0368 0.0359 0.1227 0.0841 0.0649 0.0559 0.0574 0.0617 Solen strictusJN7863770.0331 0.0011 0.0326 0.0938 0.0042 0.0044 –0.0334 0.0279 0.1669 0.0571 0.0048 0.0135 0.0138 0.0348 Solen grandisHQ7030120.0183 0.0005 0.0263 0.0160 0.0010 –0.0055 0.0123 0.0188 0.0505 0.0109 0.0078 0.0057 0.0072 0.0179 Solenaia carinatusKC8486540.0542 0.0014 0.0251 0.0621 0.0055 0.0319 0.0445 0.0706 0.0395 0.1073 0.1692 0.0374 0.0356 0.0602 0.0910 Lucinella divaricataEF0433420.0094 0.0004 0.0424 0.1626 0.0053 0.0046 0.0027 0.0159 0.0209 0.0647 0.0040 0.0091 0.0233 0.0041 0.2772 Loripes lacteusEF0433410.0105 0.0006 0.0553 0.0124 0.0001 0.0085 0.0017 0.0102 0.0817 0.0926 0.0099 0.0096 0.0178 0.0009 0.0389 Acanthocardia tuberculataDQ6327430.0481 0.0087 0.1819 0.0097 0.0208 0.0074 0.0157 0.0211 0.0478 0.1627 0.0234 0.0751 0.4939 0.1067 0.2459 Fulvia muticaAB8090770.0382 0.0065 0.1699 0.0364 0.0192 0.0072 0.0339 0.0213 0.0555 0.0041 0.0026 0.0377 0.1013 0.0500 0.3063 Tridacna squamosaKP2054280.0624 0.0568 0.9115 0.0054 0.0058 0.0142 0.0487 0.0218 0.3568 0.3273 0.5336 0.1362 0.7820 0.0161 – Semele scabraJN3983650.0185 0.0022 0.1184 0.0081 0.0075 0.0157 0.0167 0.0342 0.0598 0.0711 0.0082 0.0214 0.0453 0.0069 0.0745 Nuttallia olivaceaJN3983640.0176 0.0024 0.1339 0.0559 0.0121 0.0101 0.0112 0.0253 0.0400 0.0916 0.0129 0.0201 0.0359 0.0128 0.0258 Soletellina diphosJN3983630.0134 0.0010 0.0723 0.0137 0.0087 0.0359 0.0905 0.0197 0.0293 0.0881 0.1082 0.0122 0.0265 0.0167 0.0341 Moerella iridescensJN3983620.0151 0.0013 0.0839 0.0241 0.0061 0.0096 0.0031 0.0070 0.0229 0.0085 0.0346 0.0259 0.0015 0.0233 0.0728 Solecurtus divaricatusJN3983670.0169 0.0012 0.0705 0.0202 0.0128 0.0206 0.0990 0.0422 0.0579 0.0764 0.0308 0.0198 0.0445 0.0022 0.0400 Sinonovacula constrictaEU8802780.0385 0.0071 0.1852 0.0165 0.0170 0.0056 0.0139 0.0433 0.0856 0.1151 0.1165 0.0141 0.0168 0.0556 0.1046 Coelomactra antiquataJQ4234600.0122 0.0007 0.0609 0.0006 0.0030 0.0389 0.0067 0.0180 0.0178 0.0509 0.1096 0.0104 0.0583 0.0185 0.0123 Mactra chinensisKJ7548230.0128 0.0007 0.0565 0.0025 0.0010 0.0316 0.0029 0.0167 0.0313 0.0582 0.0054 0.0038 0.0112 0.0269 0.0523 Lutraria rhynchaenaHG7990890.0278 0.0039 0.1406 0.1280 0.0081 0.0222 0.0312 0.0306 0.0820 0.0507 0.0316 0.0172 0.1027 0.0447 0.1188 Arctica islandicaKF3639510.0248 0.0034 0.1386 0.0310 0.0173 0.0093 0.0075 0.0232 0.0169 0.0535 0.0245 0.0270 0.0165 0.0367 0.1801 Calyptogena magnificaKR8623680.0650 0.0181 0.2790 0.1005 0.0383 0.0891 0.0394 0.0681 0.0818 0.1309 0.0365 0.0207 0.0513 0.1166 0.1257 Mya arenariaKJ7559960.0905 0.0363 0.4006 0.1179 0.0732 0.0445 0.1039 0.1126 0.0038 0.2250 0.1928 0.0663 0.0367 0.0564 0.4209 Hiatella arcticaDQ6327420.0990 0.0441 0.4451 0.2868 0.0464 0.1977 0.0127 0.1309 0.0811 0.1201 0.5193 0.1167 –0.0894 0.3495 Panopea generosaKM5800670.0095 0.0005 0.0503 0.0232 0.0030 0.1959 0.0005 0.0399 0.0289 0.0491 0.0068 0.0294 0.0013 0.0071 0.0371 Panopea globosaKM5800680.0080 0.0004 0.0457 0.0039 0.0011 0.0160 0.0024 0.0319 0.0295 0.0961 0.0087 0.0348 0.1062 0.0148 0.0591 Anodonta anatinaKF0309640.0543 0.0015 0.0279 0.0496 0.0090 0.0212 0.0185 0.0405 0.0548 0.0510 0.0301 0.0877 0.1430 0.0665 0.0957 Anodonta arcaeformisKF6675300.0766 0.0003 0.0039 0.1123 0.0145 0.0001 0.0001 0.0442 0.1493 0.1044 0.1981 0.1005 0.3934 0.0886 0.0330 Anodonta lucidaKF6675290.0819 0.0039 0.0473 0.1482 0.0110 0.0603 0.0380 0.0580 0.0938 0.1221 0.1266 0.0470 0.0760 0.1020 0.1669 Anodonta euscaphysKP1878510.0923 0.0007 0.0079 0.1726 0.0891 –0.1114 0.1095 0.0805 0.3326 0.0001 0.4194 –0.1384 0.2573 Hyriopsis cumingiiHM3476680.0596 0.0008 0.0126 0.1685 0.0001 0.0234 0.0119 0.0430 0.1631 0.1192 0.0211 0.0873 –0.0698 0.0650 Hyriopsis schlegeliiHQ6414060.0459 0.0005 0.0115 0.0198 0.0035 0.0531 0.0105 0.0319 0.0351 0.0596 –0.0475 0.0001 0.0514 0.0674 Utterbackia imbecillisHM8566370.0754 0.0029 0.0380 0.1575 0.0081 0.0267 0.0421 0.1127 0.0677 0.0885 0.0812 0.0905 0.1471 0.1252 0.1197 Utterbackia peninsularisHM8566350.0496 0.0102 0.2065 0.0177 0.0191 0.0416 0.0020 0.1196 0.0822 0.1027 0.1512 0.0209 0.3393 0.0371 0.0389 Unio pictorumHM0141300.0561 0.0018 0.0313 0.0910 0.0092 0.0333 0.0171 0.0524 0.0699 0.0522 0.0714 0.0500 0.1272 0.0630 0.1158 Unio douglasiaeKM6579540.0519 0.0015 0.0295 0.0713 0.0085 0.0027 0.0087 0.0712 0.0250 0.0597 0.0245 0.0608 0.0354 0.0560 0.0873

Note: –, not available.

Table 2 The nuclear gene (histone H3) of bivalves downloaded from GenBank

2.3 Estimation of Nonsynonymous/Synonymous Substitutions Ratios (Ka/Ks)

The maximum-likelihood phylogenetic relationships werereconstructed based on nucleotide sequences of twelveprotein-coding genes using RAxML v.7.0.4 (Stamatakis, 2006). The twelve-partitioned nucleotide sequences were aligned with ClustalX (Thompson., 1997). The ratios of nonsynonymous to synonymous substitutions (a/s) were estimated for each branch using CodeML implement- ed in the PAML package (Yang, 2007). Model 1 was used, which allows a freea/s ratio. Onlya/s ands va- lues of the external branches were selected in the following analyses,., deleterious mutations (a/s) between modern species and their most recent ancestors. The statistical analyses were performed with IBM SPSS Statistics, release 19.0.0.1.

3 Results and Discussion

3.1 Relationship Between Genome Size and Nucleotide Composition in Arcidae

Arcidae species poss larger mitogenomes than that found in typical animals, challenging the conventional hypo-thesis that a compact mitogenome is a common feature among all animals. The increased size of Arcidae mito- genome is due to the presence of long noncoding regions. Genomic coverage by mitochondrial noncoding regionscan reach up to 71% (33046bp) for(Sun., 2014). Larger size molecules are usually considered to be at a selective disadvantage simply because they take longer time to replicate, leaving fewer copies to be trans- mitted (Boyce., 1989). On the contrary, smaller sized mtDNA molecules are with replicative or selective advan- tage (Boyce., 1989).

In order to explore if the large Arcidae mtDNA can af- fect replication mechanics, we compared the nucleotide skew of whole genome sequences (PmtDNA), the protein- coding genes at all codon positions (P123), and the four- fold codon positions (P4FD) between Arcidae species and the other bivalve species (Table 3). AT skews for the PmtDNAare the same between Arcidae and non-Arcidae groups (Mann-Whitney U-test,=0.904, Fig.1A);however, the GC skews of Arcidae species are significantly greater than that of the non-Arcidae group (=0.003, Fig.1B). The GC skews of P123in Arcidae species are also significantly greater than those of non-Arcidae group (=0.001, Fig.1C), while AT skews do not differ (=0.076, Fig.1D). This pat- tern is similar when analysis is restricted to the P4FD, which are presumed to be under weaker selection, with the trend toward greater GC skew in Arcidae species (=0.001, Fig.1E) and little difference in AT skew (=0.048, Fig.1F).

The asymmetric mechanism of mtDNA replication, in which the parental strand is exposed to mutation while it is in a single-stranded state, can account for the strong com- positional asymmetry observed in mitogenomes (Reyes., 1998). According to this hypothesis, a possible explanation for the marked nucleotide skew in Arcidae species migth be that the mitogenome replication in Arcidae is slower than thosein other bivalves, exposing the paren- tal strand to deamination for a longer time. Thus, the data of the compositional asymmetry of Arcidae and non-Ar- cidae group indicated that the presence of the exceptional long no-coding regions may affect replication mechanics. However, the large size of mitogenomes in the Arcidae spe- cies does notmean a significant replicative disadvantage.The exceptional long no-coding regions may provide ad- ditional replication initiation signals, which can increasethe number of genome replicates per template genome (Jiang., 2007; Eberhard and Wright, 2016). This is really ad- vantageous if the replication of Arcidae mtDNA is parti- cularly slow, as reflected by the marked nucleotide skew that were found in Arcidae mitogenomes. One way to test this idea is to map replication initiation sites to see whe- ther Arcidae mitogenomes have more replication initiation zones in the non-coding regions.

Table 3 The bivalves mitochondrial genomes included in the analysis of strand asymmetry in nucleotide composition

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SpeciesAccession no.mtDNAP123P4FD AT skewGC skewAT skewGC skewAT skewGC skew Lucinella divaricataEF043342?0.240.33?0.310.32?0.310.31 Loripes lacteusEF043341?0.230.32?0.310.33?0.310.46 Acanthocardia tuberculataDQ632743?0.180.17?0.250.18?0.110.25 Fulvia muticaAB809077?0.130.28?0.240.29?0.160.38 Tridacna squamosaKP205428?0.120.19?0.190.26?0.050.34 Semele scabraJN398365?0.230.43?0.320.43?0.360.62 Nuttallia olivaceaJN398364?0.150.32?0.210.33?0.100.54 Soletellina diphosJN398363?0.260.37?0.330.38?0.450.60 Moerella iridescensJN398362?0.220.35?0.300.32?0.360.34 Solecurtus divaricatusJN398367?0.290.38?0.370.39?0.550.50 Sinonovacula constrictaEU880278?0.230.36?0.320.37?0.360.63 Coelomactra antiquataJQ423460?0.200.30?0.290.29?0.270.50 Mactra chinensisKJ754823?0.220.26?0.320.25?0.360.40 Lutraria rhynchaenaHG799089?0.280.40?0.370.40?0.470.60 Arctica islandicaKF363951?0.160.30?0.240.31?0.160.43 Calyptogena magnificaKR862368?0.200.39?0.290.39?0.350.64 Mya arenariaKJ755996?0.130.32?0.200.33?0.250.28 Hiatella arcticaDQ632742?0.150.29?0.220.31?0.280.29 Panopea generosaKM580067?0.210.38?0.290.39?0.310.33 Panopea globosaKM580068?0.270.44?0.350.45?0.380.40 Anodonta anatinaKF030964?0.150.30?0.240.18?0.210.20 Anodonta arcaeformisKF667530?0.120.27?0.240.18?0.180.26 Anodonta lucidaKF667529?0.130.28?0.230.16?0.190.16 Anodonta euscaphysKP187851?0.120.26?0.280.18?0.160.19 Hyriopsis cumingiiHM347668?0.230.36?0.300.21?0.270.30 Hyriopsis schlegeliiHQ641406?0.230.35?0.310.22?0.290.35 Utterbackia imbecillisHM856637?0.150.28?0.230.18?0.200.21 Utterbackia peninsularisHM856635?0.130.26?0.190.13?0.150.18 Unio pictorumHM014130?0.190.32?0.250.19?0.250.22 Unio douglasiaeKM657954?0.180.32?0.250.19?0.240.21

Fig.1 Nucleotide skew values of the whole mtDNA and protein-coding genes of Arcidae and non-Arcidae bivalve mitochondrial genomes. A, GC skews for mtDNA; B, AT skews for mtDNA; C, GC skews for all sites (P123); D, AT skews for all sites (P123); E, GC skews for the fourfold degenerate sites (P4FD); F, AT skews for the fourfold degenerate sites (P4FD). The average values of each group are indicated along with standard error bars.

3.2 Relaxed Selective Constraint on Large Mitogenomes of Arcidae

Previous studies have shown that the mitogenomes are under selection for smaller size, which can cause higher replication and translation efficiency (Rand, 1993). Ac-cording to this hypothesis, the large mitogenomes of Ar- cidae species may under different selective constraint com- pared with small mitogenomes in other bivalves. In order to explore this difference, we assembled a data set of 86 mitogenomes of bivalves and constructed the Maximum Likelihood (ML) phylogenetic tree (Fig.2).

The ratio of nonsynonymous (change in amino acid) and synonymous (silent) substitutions (a/s) is generally used to measure the selective constraints acting on the protein- coding sequences. The mitochondrial data set of bivalves (listed in Supplementary Table 1) were first divided into ‘Arcidae (large mitogenome)’ and ‘non-Arcidae (small mi- togenome)’ groups to represent groups with different mi- togenome sizes (Fig.2). The Arcidae group has a signifi- cant higher mean value ofa/s (0.0705) than the non- Arcidae group (0.0421) (=0.002, Mann-Whitney U-test, Fig.3A). The mean value fora is also significantly dif- ferent between Arcidae and non-Arcidae groups (0.1094. 0.0238,<0.001, Fig.3B), suggesting that the mitochondrial protein-coding genes of Arcidae accumulate more non-synonymous mutations compared with other bivalves. Con-sidering that the divergences of synonymous mutation rate may bias the results, we compared the averages betweenArcidae and non-Arcidae groups. The mean value ofs in Arcidae group (1.8945) is significantly higher than that of the non-Arcidae group (0.7524;=0.003). The greaters may result in a smallera/s ratio in Arcidae group, making the results more conservative. Therefore, our ana- lyses suggest that the highera/s values in Arcidae groupare not simply originated from the divergences in synony- mous mutation rates.

To identify which mitochondrial protein-coding genes aremost affected by the selective constraints, we tested thea/s ratio for each of the 12 mitochondrial genes (Table 1). Seven protein-coding genes (,–,,and) show significantly highera/s ratios in Arcidae species (Fig.4). This result suggests that these genes may have experienced more relaxed functional con- straints.

In order to determine whether thea/s variations de- pend upon the mitogenome size, or they just reflect a ge- neral pattern of molecular evolution for bivalves, we repeated the above analysis for histone H3, a nuclear gene from 49 bivalves, which is independent of mitogenome size(listed in Table 2). However, thea/s ratio of histone H3 gene is not significantly different between the two groups (0.0001. 0.0085,=0.142).

An alternative hypothesis to explain this finding is that the selective constraints are relaxed on the large mitoge- nomes of Arcidae species. Because mitochondria play a crucial role in energy generation, mitochondrial genes are more sensitive to the energy-related selective pressures. Higher rates of nonsynonymous substitutions in mtDNA genes may lead to more radical amino acid substitutions (Hanada., 2007), resulting a reduction in electron- transferring respiratory chain activity (Weber., 1997; Brown., 2000). Previous study has showed that low metabolic rates is correlated with relaxed selective con- straints on mitochondrial genes (Chong and Mueller, 2012).Based on this hypothesis, Arcidae species may be more likely to survive and reproduce with lower metabolic re- quirementsthan other bivalvesunder similar environment. This coincides with the biological characteristics of Arci- dae species. Some Arcidae species are more tolerant to as- phyxiation as they can moreeconomically consume oxy- gen, such as the arcid clam, whichcan adaptwell to oxygen content change in the water (Ani- stratenko and Khaliman, 2006; Soldatov., 2009). Whenthe organisms expose to environmental hypoxia, the en- ergy production in mitochondria is slowed, and metabolic rate will be suppressed (Richards, 2011). We thus deducedthat the relaxation of selective constraint on large mito- genomes of arcid species is related to their low metabolic rates. The relaxation of selective constraints contributes to generate ‘new’ (adapted) mitochondrial genes, and posi- tive selection is the basis of adaptive evolution (Shen., 2010). Thus the positive selection may have occurred on some mitochondrial genes in Arcidae species to generate the adapted genes.

4 Conclusions

In the present study, we conducted a comparative ana- lysis of 86 bivalve mitogenomes (including 9 arcid mito- genomes) to explore the differences of base composition and selective constraints between the large mitogenomes in Arcidae and small ones in other bivalves. Arcidae mito- genomes have significantly greater GC skews in their co- ding sequences. The mitochondrial protein-coding genes of Arcidae species had significant highera/s than other bi- valves. Seven protein-coding genes (,,,and) are most affected by the selective con- straints. These divergences are not observed in the nu- clear gene (histone H3). The replication of the large mito- genomes in Arcidae may be slower than those in other bivalves. The large mitogenomes of Arcidae experienced more relaxed selective constraints, which is supposed to be related to their low metabolic rates, a response to hypoxia exposure.

Fig.2 Bivalve phylogenetic tree constructed from 12 mitochondrial protein-coding genes with the Maximum Likelihood method. Arcidae species are marked in blue. The mitogenome size of each bivalve species are indicated. The average mitogenome size of Arcidae and non-Arcidae groups are presented.

Fig.3 Comparisons of Ka/Ks ratios (A) and Ka (B) between Arcidae and non-Arcidae groups. *0.01

Fig.4 Comparisons of Ka/Ks ratios of the 12 mitochondrial protein-coding genes between Arcidae and non-Arcidae groups. *0.01

Acknowledgements

This work was supported by research grants from the National Natural Science Foundation of China (No. 3177 2414), the Natural Science Foundation of Qingdao City(No. 20-3-4-16-nsh), and the Fundamental Research Funds for the Central Universities (No. 201964001).

Anistratenko, V. V., and Khaliman, I. A., 2006. Bivalve mollusk(Bivalvia, Arcidae) in the northern part of the Sea of Azov: Final colonization of the Azov-Black Sea basin., 40 (5): 505-511.

Boore, J. L., 1999. Animal mitochondrial genomes., 27 (8): 1767-1780, DOI: 10.1093/nar/27.8.1767.

Boyce, T. M., Zwick, M. E., and Aquadro, C. F., 1989. Mitochon-drial DNA in the bark weevils: Size, structure and heteroplasmy., 123 (4): 825-836, DOI: 10.1101/gad.3.12b.2218.

Brown, M. D., Trounce, I. A., Jun, A. S., Allen, J. C., and Wallace, D. C., 2000. Functional analysis of lymphoblast and cybrid mitochondria containing the 3460, 11778, or 14484 Leber’s hereditary optic neuropathy mitochondrial DNA mutation., 275 (51): 39831-39836, DOI: 10.1074/jbc.M006476200.

Burger, G., Gray, M. W., and Lang, B. F., 2003. Mitochondrial ge- nomes: Anything goes., 19 (12): 709-716, DOI: 10.1016/j.tig.2003.10.012.

Cameron, S. L., 2014. Insect mitochondrial genomics: Implications for evolution and phylogeny., 59 (1): 95-117, DOI: 10.1146/annurev-ento-011613-162 007.

Chong, R. A., and Mueller, R. L., 2012. Low metabolic rates in salamanders are correlated with weak selective constraints on mitochondrial genes., 67 (3): 894-899, DOI: 10.1111/ j.1558-5646.2012.01830.x.

Curole, J. P., and Kocher, T. D., 1999. Mitogenomics: Digging deeper with complete mitochondrial genomes., 14 (10): 394-398, DOI: 10.1016/S0169- 5347(99)01660-2.

Eberhard, J. R., and Wright, T. F., 2016. Rearrangement and evo- lution of mitochondrial genomes in parrots., 94: 34-46, DOI: 10.1016/j.ympev. 2015.08.011.

Gissi, C., Iannelli, F., and Pesole, G., 2008. Evolution of the mi- tochondrial genome of Metazoa as exemplified by comparison of congeneric species., 101 (4): 301-320, DOI: 10. 1038/hdy.2008.62.

Hanada, K., Shiu, S. H., and Li, W. H., 2007. The nonsynonymous/synonymous substitution rate ratio versus the radical/ conservative replacement rate ratio in the evolution of mammalian genes.,24 (10): 2235- 2241, DOI: 10.1093/molbev/msm152.

Jiang, Z. J., Castoe, T. A., Austin, C. C., Burbrink, F. T., Herron, M. D., McGuire, J. A.,., 2007. Comparative mitochondrial genomics of snakes: Extraordinary substitution rate dynamics and functionality of the duplicate control region., 7: 123, DOI: 10.1186/1471-2148-7-123.

Kong, L., Li, Y., Kocot, K. M., Yang, Y., Qi, L., Li, Q.,., 2020. Mitogenomics reveals phylogenetic relationships of Ar- coida (Mollusca, Bivalvia) and multiple independent expansions and contractions in mitochondrial genome size,, 150: 106857, DOI: 10. 1016/j.ympev.2020.106857.

Lavrov, D. V., 2007. Key transitions in animal evolution: A mitochondrial DNA perspective., 47 (5): 734-743, DOI: 10.1093/icb/icm045.

Liu, Y. G., Kurokawa, T., Sekino, M., Tanabe, T., and Watanabe, K., 2013. Complete mitochondrial DNA sequence of the ark shell: An ultra large metazoan mitochondrial genome., 8 (1): 72-81, DOI: 10.1016/j.cbd.2012.12.003.

Morton, B. S., Prezant, R. S., and Wilson, B., 1998. Class Bival- via. In:. Beesley, P. L.,.,eds., Fauna of Australia, Vol. 5. CSIRO Publishing, Melbourne, 195-234.

Oliver, P. G., and Holmes, A. M., 2006. The Arcoidea (Mollusca: Bivalvia): A review of the current phenetic-based systematics., 148 (3): 237-251, DOI: 10.1111/j.1096-3642.2006.00256.x.

Park, H., and Ahn, D. H., 2015. Complete mitochondrial geno- me of the antarctic soft-shelled clam,(Bivalvia; Laternulidae)., 26 (4): 2, DOI: 10. 3109/19401736.2013.836515.

Passamonti, M., and Scali, V., 2001. Gender-associated mitochon- drial DNA heteroplasmy in the venerid clam(Mollusca Bivalvia)., 39: 117-124, DOI: 10.1097/00000539-200210000-00038.

Rand, D. M., 1993. Endotherms, ectotherms, and mitochondrial genome-size variation., 37 (3): 281-295, DOI: 10.1007/BF00175505.

Rand, D. M., and Harrison, R. G., 1986. Mitochondrial DNA trans- mission in crickets., 114 (3): 955-970, DOI: 10.1016/ 0735-0651(86)90016-6.

Reyes, A., Gissi, C., Pesole, G., and Saccone, C., 1998. Asymme- trical directional mutation pressure in the mitochondrial genome of mammals., 15 (8): 957-966, DOI: 10.1093/oxfordjournals.molbev.a026011.

Richards, G. J., 2011. HYPOXIA|Metabolic rate suppression as a mechanism for surviving hypoxia. In:. Farren, A. P.,., eds., Academic Press, Amster-dam, 1764-1770, DOI: 10.1016/B978-0-12-374553-8.00155-6.

Saccone, C., Giorgi, C. D., Gissi, C., Pesole, G., and Reyes, A., 1999. Evolutionary genomics in metazoa: The mitochondrial DNA as a model system., 238 (1): 195-209, DOI: 10.10 16/S0378-1119(99)00270-X.

Schneider, A., and Ebert, D., 2004. Covariation of mitochondrial genome size with gene lengths: Evidence for gene length reduction during mitochondrial evolution., 59 (1): 90-96, DOI: 10.1007/s00239-004-2607-x.

Shen, Y. Y., Liang, L., Zhu, Z. H., Zhou, W. P., Irwin, D. M., and Zhang, Y. P., 2010. Adaptive evolution of energy metabolism genes and the origin of flight in bats., 107 (19): 8666-8671, DOI: 10.1073/pnas.0912613107.

Signorovitch, A. Y., Buss, L. W., and Dellaporta, S. L., 2007. Com- parative genomics of large mitochondria in placozoans., 3 (1): e13, DOI: 10.1371/journal.pgen.0030013.

Simison, W. B., and Boore, J. L., 2008. Molluscan evolutionary genomics. In:. Pon- der, W., and Lindberg, D. R., eds., University of California Press, Berkeley, 447-461.

Smith, D. R., and Snyder, M., 2007. Complete mitochondrial DNA sequence of the scallop: Evidence of transposition leading to an uncharacteristically large mitochondrial genome., 65: 380- 391, DOI: 10.1007/s00239-007-9016-x.

Soldatov, A. A., Andreenko, T. I., Sysoeva, I. V., and Sysoev, A. A., 2009. Tissue specificity of metabolism in the bivalve mol- luscBr. under conditions of experimen- tal anoxia., 45: 349-355, DOI: 10.1134/S002209300903003X.

Stamatakis, A., 2006. RAxML-VI-HPC: Maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models., 22 (21): 2688-2690, DOI: 10.1093/ bioinformatics/btl446.

Strotz, L. C., Saupe, E. E., Kimmig, J., and Lieberman, B. S., 2018. Metabolic rates, climate and macroevolution: A case study us- ing Neogene molluscs., 285 (1885): 20181292, DOI: 10.1098/rspb. 2018.1292.

Sun, S., Kong, L., Yu, H., and Li, Q., 2014. The complete mitochondrial genome of(Bivalvia: Arcidae)., 26 (6): 957-958, DOI: 10.3109/ 19401736.2013.865174.

Sun, S., Li, Q., Kong, L., and Yu, H., 2016. Complete mitochon- drial genomes ofand: Varied mitochondrial genome size and highly rearranged gene order in Arcidae., 6 (1): 33794, DOI: 10.1038/srep 33794.

Sun, S., Li, Q., Kong, L., and Yu, H., 2017. Limited locomotive ability relaxed selective constraints on molluscs mitochondrial genomes., 7 (1): 10628, DOI: 10.1038/s415 98-017-11117-z.

Thompson, J. D., Gibson, T. J., Plewniak, F., Jeanmougin, F., and Higgins, D. G., 1997. The CLUSTAL_X windows interface: Flexible strategies for multiple sequence alignment aided by quality analysis tools., 25 (24): 4876- 4882, DOI: 10.1093/nar/25.24.4876.

Weber, K., Wilson, J. N., Taylor, L., Brierley, E., Johnson, M. A., Turnbull, D. M.,., 1997. A new mtDNA mutation showing accumulation with time and restriction to skeletal muscle., 60 (2): 373-380, DOI: 10.1016/S0027-5107(96)00239-4.

Williams, S. T., Foster, P. G., Hughes, C., Harper, E. M., Taylor, J. D., Littlewood, D. T. J.,., 2017. Curious bivalves: Sys- tematic utility and unusual properties of anomalodesmatan mi- tochondrial genomes., 110: 60-72, DOI: 10.1016/j.ympev.2017.03.004.

Xu, K. F., Kanno, M., Yu, H., Li, Q., and Kijima, A., 2011. Com- plete mitochondrial DNA sequence and phylogenetic analysis of Zhikong scallop(Bivalvia: Pectinidae)., 38 (5): 3067-3074, DOI: 10.1007/ s11033-010-9974-8.

Yang, Z., 2007. PAML 4: Phylogenetic analysis by maximum like- lihood., 24 (8): 1586-1591, DOI: 10.1093/molbev/msm088.

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