Zoosyst. Evol. 100 (4) 2024, 1297-1314 | DOI 10.3897/zse.100.127201 Ate BERLIN Molecular systematics of Perinereis and an investigation of the status and relationships of the cultured species Perinereis wilsoni Glasby & Hsieh, 2006 (Annelida, Nereididae) Deyuan Yang'*, Sheng Zeng*, Zhi Wang, Yanjie Zhang*, Dazuo Yang°, Christopher J. Glasby’, Jiang-Shiou Hwang? ®, Lizhe Cai? Institute of Marine Biology, National Taiwan Ocean University, Keelung, Taiwan College of the Environment and Ecology, Xiamen University, Xiamen 361102, China State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen 361102, China School of Life and Health Sciences, Hainan University, Haikou, China Key Laboratory of Marine Bio-resource Restoration and Habitat Reparation in Liaoning Province, Dalian Ocean University, Dalian 116023, China Natural Sciences, Museum & Art Gallery Northern Territory, PO Box 4646, Darwin, NT 0801, Australia Australian Museum Research Institute, 1 William Street, NSW 2010, Sydney, Australia CON DO FP WDY Center of Excellence for the Oceans, National Taiwan Ocean University, Keelung, Taiwan https://zoobank. org/95 98 7 DF E-0752-4899-B07D-BC6C93DC8&C60 Corresponding authors: Lizhe Cai (cailizne@xmu.edu.cn); Jiang-Shiou Hwang (jshwang@mail.ntou.edu.tw); Christopher J. Glasby (chris.glasby@nt.gov.au) Academic editor: Greg Rouse # Received 9 May 2024 Accepted 16 August 2024 Published 13 September 2024 Abstract In this study, we conducted morphological and molecular analyses of Perinereis wilsoni, a species being considered for aquaculture in China. We found this species difficult to identify because of its close morphological similarity to the sympatric P. mictodonta and thus sought genetic markers to more easily distinguish it and to investigate its phylogenetic relationship to P. mictodonta and other nereidids. For the first time, we sequenced, assembled, and annotated the complete mitochondrial genome, nuclear ribosomal se- quences (/8S-ITS1-5.8S-JTS2-28S), and four nuclear histone genes (H3-H2A-H2B-H4) of P. wilsoni. Comprehensive bioinformatics methods were employed to assemble the genome-skimming data of P. wilsoni to ensure assembly quality. Phylogenetic analyses based on five datasets of the available mitochondrial genomes (32 taxa in Nereididae, including 8 taxa in Perineris), using maximum likelihood and Bayesian analyses, provide support for the monophyly of the genus Perinereis. In contrast, the P. nuntia species group, a subgroup within Perinereis, is nonmonophyletic. Perinereis wilsoni has a closer phylogenetic relationship with P. vancauri- ca and P. nuntia. Our study serves as a baseline for future work on the cultivation, reproductive biology, and phylogeny of P. wilsoni. Key Words Bioinformatic analyses, genome skimming, mitogenomes, Perinereis Introduction Recently, a local Perinereis species intended for large- scale aquaculture in China by the Key Laboratory of Marine Bio-resource Restoration and Habitat Repara- tion in Liaoning Province, Dalian Ocean University, was identified as P. wilsoni Glasby & Hsieh, 2006. The genus Perinereis Kinberg, 1865, belongs to the Nereididae. This family comprises over 700 described species and 45 gen- era (Wilson et al. 2023). Many nereidid species, particu- larly Perinereis, are of significant commercial and eco- logical importance for fishing bait, aquaculture feed, and wastewater treatment (Palmer 2010; Arias et al. 2013). In China, Perinereis aibuhitensis (Grube, 1878) is farmed Copyright Yang, D. et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 1298 and exported worldwide as fish bait, and 7v/orrhynchus heterochetus (Quatrefages, 1866) is consumed as food by people in Guangdong Province and other Southeast Asian countries (Glasby and Hsieh 2006; Wilson et al. 2023). Perinereis represents the second-largest genus in Nereididae, with approximately 100 species (Mahcene et al. 2023; Prajapat et al. 2023; Wilson et al. 2023; Tetxei- ra et al. 2024). Bakken and Wilson (2005) conducted a phylogenetic analysis based on morphological evidence, suggesting that Perinereis may be polyphyletic. This was supported by subsequent molecular studies (Glasby et al. 2013; Alves et al. 2020; Elgetany et al. 2022). For prac- tical identification purposes, Hutchings et al. (1991) first divided Perinereis into three species groups based on the number of pharyngeal Area VI paragnaths and further divided each group based on parapodial characters. The Perinereis nuntia species group was characterized by a distinctive arc of bar-shaped paragnaths on area VI (usu- ally numbering 6—14 on each side) (Hutchings et al. 1991; Wilson and Glasby 1993; Glasby and Hsieh 2006). This group has been reviewed by Wilson and Glasby (1993), Glasby and Hsieh (2006), and Villalobos-Guerrero (2019). Currently, it comprises approximately 20 recognized spe- cies (Villalobos-Guerrero 2019; Wilson et al. 2023), with the type localities of about 13 species in the Indo-West Pacific. These studies have significantly improved our understanding of this group. However, relying solely on a morphology-based approach may not be sufficient to re- solve the taxonomic status of these species because some key taxonomic characters used to distinguish species of- ten overlap, as they show ontogenetic and intraspecific variation (Tosuji et al. 2019; Tosuji et al. 2023). These morphology-defined species need to be re-evaluated using integrated taxonomic methods by taxonomic specialists. Recently, studies based on integrative taxonomy have re- vealed more new species in Nereididae (see Glasby et al. 2013; Teixeira et al. 2022a; Teixeira et al. 2022b). Perinereis wilsoni, a member of the P. nuntia species group, is morphologically very similar to Perinereis mict- odonta (Marenzeller, 1879), with no distinct morpholog- ical differences, although slight but statistically signifi- cant morphometric differences were found with respect to paragnath numbers and the relative length of the dorsal cirri (Glasby and Hsieh 2006). For this reason, these two species were primarily established based on the differ- ences in /TS (internal transcribed spacer) genes (Chen et al. 2002; Glasby and Hsieh 2006). Therefore, identifying these two species based solely on morphology presents a significant challenge. To date, only two studies have con- tributed molecular data: Chen et al. (2002) provided /TS genes. Tosuji et al. (2019) provided sequences for both the partial mitochondrial /6S ribosomal RNA (/6S) and ITS genes. Although Park and Kim (2007) researched P. wilsoni using the partial mitochondrial cytochrome oxidase I (COX/) gene, these sequences were not made publicly available. Moreover, there are some COX se- quences labeled P. wil/soni in the NCBI GenBank data- base, but these sequences remain pending verification. zse.pensoft.net Yang, D. et al.: Morphological and molecular studies of Perinereis wilsoni Given the considerable economic importance of Per- inereis species, accurate species identification is crucial because correct scientific names can facilitate the link- ing of subsequent physiological or reproductive studies, thus ensuring the reproducibility of these research ef- forts (Glasby and Hsieh 2006; Hutchings and Lavesque 2020). Therefore, we have focused on several key ques- tions regarding taxonomy: 1) Is the identification of P. wilsoni from Liaoning Province accurate? 2) Which mo- lecular markers are suitable for identifying this species? 3) What is the phylogenetic relationship of P. wilsoni to other nereidids? In this study, we used low-coverage whole genome sequencing, also known as genome skimming (Straub et al. 2012), which has been widely used in polychaete phylogeny studies because it is cost-effective and does not require fresh tissue (Richter et al. 2015; Coissac et al. 2016; Alves et al. 2020; Hektoen et al. 2024). Utiliz- ing this strategy, we provided more molecular informa- tion, including high-copy regions: mitochondrial genome (mitogenome), nuclear ribosomal sequences (/8S rRNA- ITS1-5.8S tRNA-ITS2-28S rRNA), and nuclear histone genes (H3-H2A-H2B-H4). Materials and methods Sample collection, identification, and sequencing The specimens of P. wi/soni were sampled from Dalian, Liaoning Province, China (38.8732°N, 121.6767°E) and identified by Deyuan Yang. All specimens were fixed di- rectly in 95% ethanol. Two specimens with a fully-evert- ed pharynx were used for morphological and molecu- lar studies. They were deposited at Xiamen University (XMU) under voucher numbers 23007-1 and 23007-2, respectively. Specimens were identified based on the key in Glasby and Hsieh (2006). Methods used in the mor- phological study were followed by Yang et al. (2022). In summary, whole worms were photographed with an Olympus E-M1 Mark II camera with a 60 mm mac- ro lens, detailed structures with a Zeiss Discovery V20 stereomicroscope, and a Nikon 801 compound micro- scope. Image stacks were obtained using Helicon Focus 7 (https://www.heliconsoft.com/heliconsoft-products/ helicon-focus/) and post-processed using Adobe Pho- toshop. The terminology of nereidid followed Wilson et al. (2023) generally. To better describe areas II, III, and VI of paragnaths, we introduced the notations ‘L:R’ and ‘L:M:R’. ‘L:R’ is for areas II and VI, and ‘L:M:R’ to describe the paragnath patch in area III, where ‘L’ rep- resents the number of paragnaths on the left, “M’ in the middle, and ‘R’ on the right. For example, for area II, ‘2:3’ signifies 2 paragnaths on the left and 3 on the right; for area III, ‘3:5,2R:7’ signifies 3 paragnaths on the left, a central patch with 5 paragnaths in 2 rows, and 7 parag- naths on the right. Zoosyst. Evol. 100 (4) 2024, 1297-1314 Before DNA extraction, each individual was cleaned with 95% ethanol. To avoid gut contamination, two to seven parapodia were clipped from the specimens. Whole genomic DNA was extracted using the TTANamp Genom- ic DNA Kit (TIANGEN, Beijing, China). Genome skim- ming was conducted on the Illumina NovaSeq X Plus with a PE150 strategy. DNA extraction and sequencing were performed at Novogene Bioinformatics Technology Co., Ltd. (Being, China). Our initial sequencing effort was to obtain 5 Gb of raw data for each sample. Voucher number 23007-2 was increased to 25 Gb to explore more universal single-copy ortholog genes. Assembly and annotation of mitochondrial and nuclear sequences Raw paired-end reads were removed from sequence adapters, and low-quality regions were trimmed us- ing Fastp v.0.23.4 (Chen et al. 2018). The quality of all cleaned reads was checked with FastQC v.0.12.1 (http:// www.bioinformatics.babraham.ac.uk/projects/fastqc/), and subsequently, FastQC results were summarized using MultiQC v.1.8 (Ewels et al. 2016) (Suppl. material 1). To ensure reliable assembly for the present data, vari- ous assemblers were used: 1) SPAdes v.3.15.5 (Bankev- ich et al. 2012), Ray v.2.3.1 (Boisvert et al. 2010), Mega- hit v.1.2.9 (Li et al. 2015), and IDBA-UD v.1.1.3 (Peng et al. 2012); 2) GetOrganelle v.1.7.6.1 (Jin et al. 2020); 3) MITObim v.1.9 (Hahn et al. 2013) and NovoPlasty v.4.3.1 (Dierckxsens et al. 2017), with 76S (GenBank ac- cession numbers: L.C482188) as the seed; 4) our new as- sembly pipeline, FastMitoAssembler (original version at https://github.com/suqingdong/FastMitoAssembler). The pipeline implemented in FastMitoAssembler involved the following steps: First, MEANGS v.1.2.1 (Song et al. 2022) was used to obtain and assemble mitochondrial genes, which then served as a seed input for NovoPlasty. Second, the results of NovoPlasty served as a seed input for GetOrganelle. Third, MitoZ v3.6 (Meng et al. 2019) was used for annotation. This workflow was managed using Snakemake (Koster and Rahmann 2012), which can handle large-scale samples with minimal input— only raw data. For de novo assembly results (SPAdes, Megahit, Ray, and IDBA-UD), we used MitoFinder v.1.4 (Allio et al. 2020) to extract mitochondrial contigs (mt contigs) and annotations, using the Platynereis dumerilii mitogenome (GenBank: NC 000931) as a reference. Unfortunately, no mt contigs were found from the Ray assembler. If the cir- cularization of a mt contig was not automatically complet- ed by MitoFinder, the circules.py script (https://github. com/chrishah/MITObim/tree/master/misc_ scripts) was used to assess the circularization of the contig. After obtaining mitogenomes from various assemblers, Quast v.5.2.0 (Gurevich et al. 2013) was employed for assembly quality evaluation (Suppl. material 2). A BLASTn query against GenBank in the NCBI (NCBI BLAST Analysis, 1299 https://BLAST.ncbi.nlm.nih.gov/BLAST.cgi) was also performed to check for contamination in the mitoge- nomes (Suppl. material 3: table S1). The GC content and read (per-base) coverage depth of mitogenome sequences were calculated using the visualize subcommand in Mi- toZ v.3.6 with default parameters. The mitogenome was annotated using MITOS2 (Donath et al. 2019), MitoFinder v.1.4.1, and MitoZ v.3.6. All annotation files (in .gb or .gbf formats) were reordered with COX1 as the start gene using PhyloSuite v.1.2.3 (Zhang et al. 2020). The reordered GenBank for- mat (gb) file was converted to a fasta file and uploaded to GeSeq (https://chlorobox.mpimp-golm.mpg.de/geseq. html) to combine the results of ARWEN v.1.2.3 and tR- NAscan-SE v.2.0.7 into a single gb file. This approach allowed us to compare tRNA annotations generated from three common methods (ARWEN, tRNAscan-SE, and MiTFi). All annotations were then loaded into Geneious Prime v.2022.2.2 for manual curation. First, we utilized the MAFFT plugin in Geneious to align these gb files. Then, we checked the coding region annotations with the assistance of the ORFs function based on the invertebrate mitochondrial genetic code table 5. Second, tRNAs were evaluated using the following criteria: tRNAscan-SE was given precedence over ARWEN and MiTFi, while MiT- Fi had precedence over ARWEN. Thus, if tRNAscan-SE identified a tRNA, its result was chosen. In cases where both MiTFi and ARWEN identified a tRNA, the result from MiTFi was selected. Subsequently, we imported other gb files of Perinereis into Geneious to compare each gene and manually edit them. The boundaries of each gene were determined by the following rules: 1) Protein-coding genes can overlap with each other but cannot overlap with tRNA genes. In Nerei- didae, only the ND4 and ND4L coding genes are allowed to overlap. 2) The boundaries of mitochondrial rRNA genes (/2S and /6S) were defined by flanking genes. 3) The large non-coding region (or putative control region) was determined by the boundaries of neighboring genes and a low GC region. The CGView Comparison Tool (CCT) (https://github. com/paulstothard/cgview_comparison_tool) (Grant et al. 2012) was employed to compare all accessible mitoge- nomes of Nereididae in NCBI (as of 15 January 2024) to evaluate the quality of annotations further. The high-copy nuclear markers (/8S to 28S genes and histone genes) were assembled using GetOrganelle v.1.7.6.1. Considering the lack of effective software or pipelines to annotate these genes, we manually annotat- ed nuclear rRNA genes in Geneious using primer pairs to define gene boundaries: 18S4 and /SSB (Medlin et al. 1988) for 18S, F63.2 and R3264.2 (Struck et al. 2006) for 28S, and ITSISSFPOLY and ITS28SRPOLY (Nygren et al. 2009) for the /TS/-5.8S-ITS2 region. After complet- ing one sequence annotation, we utilized the “Transfer annotations” function within Geneious Prime v.2022.2.2 to annotate other sequences. The histone genes were an- notated using the same function, with GenBank accession zse.pensoft.net 1300 number X58895 (Urechis caupo) as a reference at an 85% similarity threshold. If the number of gene annotations was incomplete in one sequence, we imported the cor- responding cleaned sequencing reads into Geneious and reassembled the sequence employing the “map to refer- ence” function in Geneious Prime v.2022.2.2 (mapper: Geneious, fine-tuning: iterate up to 25 times) and then re-annotated it. Once annotations were completed, each gene was extracted for NCBI BLAST analysis. The read (per-base) coverage depth of nuclear genes was calculat- ed using a custom script, which used BWA (L1 2013) and SAMtools (Li et al. 2009). BUSCO v.5.6 was employed to generate universal sin- gle-copy orthologs (USCOs) (Simao et al. 2015) using only the assembly results (contigs) from SPAdes with the following parameters: -| metazoan_odb10, -m genome, --augustus, -c 40. A total of 618 single-copy genes were searched. Phylogenetic analyses The phylogenetic analysis utilized two types of datasets: complete or near-complete mitogenomes of Nereididae and DNA barcoding sequences (COX/, 16S, and ITS) of Perinereis. All publicly available Nereididae mitog- enomes from GenBank (as of 15 January 2024), along with two outgroup species (Craseoschema thyasiricola NC 060815 and Leocrates chinensis NC 066969, be- longing to Chrysopetalidae and Hesionidae, respective- ly), were included in the phylogenetic analysis. The out- group taxa were selected based on previous hypotheses that Chrysopetalidae and Hesionidae are sister groups to Nereididae (Glasby 1993; Pleijel and Dahlgren 1998; Tilic et al. 2022). To ensure consistent annotation criteria and to correct potential errors in previous annotations of mitogenomes, we re-annotated all available Nereididae mitogenomes using the methods described above. Ulti- mately, Platynereis massiliensis (NC 051996) and Alitta succinea (NC 051993) from the Nereididae were exclud- ed from this study (Suppl. material 3: table S2). To identify potential taxonomically mislabeled se- quences in the mitogenomes dataset, we extracted the COX] and /6S genes and conducted NCBI BLAST anal- ysis. The results were downloaded as CSV files. For each sequence, the top 10 matching sequences were sorted based on identity using WEKits v.1.0 (https://github.com/ GP-sir/wekits/releases). Next, we retrieved the source in- formation (subjectAcc) for these matched sequences from NCBI. The species identification of each sequence was then manually verified in Microsoft Excel. Specifically, we focused on matched sequences with identity over 97% and checked whether they were supported by reliable tax- onomic references (Suppl. material 3: table S3, S4). All manually curated mitogenomes were imported into PhyloSuite v.1.2.3. The extracted protein-coding genes (PCGs) and two rRNAs (2R) from these sequences were aligned using MAFFT in normal mode. MACSE v.2 zse.pensoft.net Yang, D. et al.: Morphological and molecular studies of Perinereis wilsoni (Ranwez et al. 2018) was used to improve the multiple sequence alignment of 13 PCGs in the “refinement strate- gy.” After completing the alignment tasks, each alignment was manually checked in Geneious. Ambiguously aligned regions were removed using Gblocks with the default set- tings or trimAl v.1.2 (Capella-Gutiérrez et al. 2009) with the automated] setting (Suppl. material 3: table S5). Five mitogenomic datasets were used in the phylogenetic anal- yses: (1) 13PCGs: PCGs with all three codon positions; (ii) 13PCGs12: PCGs without 3 codon positions; (111) 13PCGs_2R: PCGs dataset plus two rRNA genes; (iv) 13PCG12_ 2R: PCG12 dataset plus two rRNA genes; and (v) 13PCGsAA: amino acid sequences translated from 13PCGs. The heterogeneity of each dataset was assessed using AliGROOVE v.1.08 (https://github.com/Patrick- Kueck/AliGROOVE) with the default settings. ModelFinder v.2.2.0 was used to select the best substi- tution models for each partition of the maximum likeli- hood (ML) and Bayesian inference (BI) analyses (Suppl. material 3: table S6). ML analysis was carried out in IQ- TREE v.2.2.2 under the edge-linked partition model with 20,000 ultrafast bootstraps. BI analysis was performed using MrBayes v.3.2.7a (Ronquist et al. 2012), with two parallel runs for at least 2,000,000 generations, ensuring the average standard deviation of split frequencies was below 0.01 (Ronquist et al. 2012). Considering the mitogenomes of Perinereis are lim- ited, shorter DNA sequences (DNA barcodes) were also used to explore the phylogenetic position of Perine- reis wilsoni. All available Perinereis genes from NCBI (https://www.ncbi.nlm.nih.gov/nuccore/?term=Perine- reis) were downloaded. The COX, 16S, 18S, 28S, H3, and ITS genes were further extracted because these molecular markers are widely employed in Annelida. To organize the data more efficiently, we used a custom script (Sup- pl. material 4) to categorize these data based on voucher numbers (treating isolates, clones, strains, and haplotypes as synonymous with voucher numbers). Ultimately, the COX1, 16S, and ITS genes were selected for phyloge- netic analysis due to their higher representation among taxa, and new sequences from this study were added to explore the phylogenetic position of Perinereis wilsoni (Suppl. material 3: table S7). The trees constructed with the COX], 16S, and JTS genes used the same methods as the mitogenome data. Multiple alignment summary statistics were generated using the alignment summary function in BioKIT (Steen- wyk et al. 2022), including the number of taxa (sequenc- es), alignment lengths, number of constant sites, number of parsimony informative sites and variable sites, and the frequency of all character states. Pairwise tree structure comparison was conducted us- ing the all.equal.phylo function in the ape v.5.7.1 package (Paradis and Schliep 2019), and topological differences were assessed using TreeSpace (Jombart et al. 2017), both implemented in R v.4.3.1 (R Core Team 2023). Finally, iTOL v.6 (Letunic and Bork 2021) was used to visualize the trees. Zoosyst. Evol. 100 (4) 2024, 1297-1314 Sequence analyses Strand asymmetries were calculated using the following formulae (Perna and Kocher 1995): AT-skew = (A - T) /(A + T); GC-skew = (G - C) / (G+ C). Codon usage and rel- ative synonymous codon usage (RSCU) of 13 PCGs were computed in PhyloSuite and visualized using the “ggplot2’ package (Wickham 2016) in R v.4.1.3 (R Core Team 2023). DnaSP v.6.0 (Rozas et al. 2017) was used to calculate the non-synonymous (Ka)/synonymous (Ks) substitution rates among the 13 PCGs of Nereididae and the nucleotide diver- sity (Pi) with a sliding window of 100 bp and a step size of 25 bp. A Ka/Ks ratio < 1 indicates purifying selection, while a ratio > 1 indicates positive selection. To determine which molecular marker is reliable for accurate species delimitation, all labeled P wilsoni and P. mictodonta COX1, 16S, and ITS genes in NCBI were used. We used the following criteria: 1) whether the presence of a barcode gap: the minimum interspecific genetic distance is greater than the maximum intraspecific genetic distance; 2) whether each species is recovered as monophyletic; and 3) whether there is a small overlap between intra- and interspe- cific distances and a large barcode gap, as recommended by dos Santos Vieira et al. (2020). Genetic distances (p-distance and Kimura 2-parameter) over sequence pairs were calcu- lated in MEGA X (Kumar et al. 2018). The heat maps were generated in TBtools v.2.080 (Chen et al. 2020). Results Morphological analyses Perinereis wilsoni Glasby & Hsieh, 2006 Fig. [A-K Material examined. * 23007-1 and 23007-2, both col- lected from Dalian, Liaoning, China (38.87315°N, 121.676671°E), 08 August 2023, preserved in95% ethanol. Description. Description based on 23007-1 and 23007-2. 23007-1 complete, 93 chaetigers, 7.0 cm in length, 2.9 mm wide at chaetiger 10 (excluding parapo- dia); and 4.0 mm wide at chaetiger 10 (including parap- odia) (Fig. 1A). 23007-2 complete, 6.5 cm in length, 98 chaetigers, 2.3 mm wide at chaetiger 10 (excluding parap- odia), 3.7 mm wide at chaetiger 10 (including parapodia). Prostomium and anterior dorsum with dark brown pig- mentation. Prostomium anterior margin entire, pear-shaped, wider than long, with shallow longitudinal groove in cen- tral area. Antennae conical, about one-third length relative to prostomium length. Palps longer than prostomium, biar- ticulate, with palpophores and palpostyles (Fig. 1A, C, J). Palpophores barrel-shaped, slightly wider basally, palpo- styles spherical (or globular). Eyes black (Fig. 1A). Pharynx fully everted (Fig. 1A, C—F, J-K). Jaws brown, with 7 teeth (based on 23007-1) (Fig. 1B). Ten- tacular cirri extend back 3—12 setigers; posterodorsal one extending to chaetiger 8-12. 1301 Paragnath counts (Fig. 1C—E, J—K): area I with 1 conical paragnath; area II with 9 or 11 conical paragnaths on left, 11 or 14 conical paragnaths on right (23007-1, Il =9:11; 23007- 2, Il = 11:14); area I] with 14-17 conical paragnaths, cen- tral patch with 9-12 in 2 rows, 2-3 laterally on either side (23007-1, HI = 3:9,2R:2; 23007-2, III = 2:12,2R:3); area IV with 18—22 conical paragnaths on each side (23007-1, IV = 18:25; 23007-2, I] = 22:22), bars absent; area V with 1 conical paragnath; area VI with 3—5 shield-shaped bars on each side (23007-1, VI = 5:3; 23007-2, VI = 5:5); area VII-VII with 19 conical paragnths in 2 rows. Notopodia with 2 lobes, prechaetal lobe absent. Dor- sal cirri longer than notopodial ligule, about 1.5 times length of the notopodial ligule throughout. Notopodial ligule similar to median ligule throughout. Neuropodial postchaetal lobe rounded, not projecting beyond acicular lobe. Ventral ligule similar in length to acicular ligule in all chaetigers (Fig. 1F, G, I). Notopodia homogomph spinigers only. Neuropodial heterogomph spinigers present throughout. At chaetiger 10, lower neurochaetae all heterogomph falcigers, upper neurochaetae with heterogomph falcigers, and hetero- gomph spinigers. At chaetiger 30 and following chaeti- gers, lower neurochaetae present heterogomph spinigers. Remarks. Perinereis wilsoni was established by Glas- by and Hsieh (2006), who provided a comprehensive de- scription and discussion. In this study, we initially iden- tified our specimens as P. wilsoni based on the key and description provided by Glasby and Hsieh (2006). Spe- cifically, in P wilsoni, the dorsal cirri are approximately 1.5 times the length of the dorsal notopodial lobe anteri- orly and 2-3 times longer posteriorly; Area IV has 29.8 (+ 3.6) conical paragnaths, and Area V has 1-3 conical paragnaths, usually in a longitudinal line. In contrast, in P. mictodonta, the dorsal cirri are either equal to or only slightly longer than the dorsal notopodial lobe throughout the body; Area IV has 35.3 (+ 6.8) conical paragnaths, and Area V has 3 conical paraganths, usually in a triangle arrangement. Our specimens more closely resemble P. wilsoni, having dorsal cirri about 1.5 times the length of the dorsal notopodial lobe throughout the body (or only increasing slightly in length posteriorly), Area [TV with 18-22 conical paragnaths, and Area V with 1 conical paragnath. However, despite the statistically significant difference in these morphometric characters (see pp. 573, Glasby and Hsieh 2006), the characters all show overlap (see pp. 560 & 572, Glasby and Hsieh 2006), and thus, morphology alone may not be sufficient to distinguish all specimens belonging to P. wilsoni and P. mictodonta. The /TS genes may presently be the most effective and reliable method for accurately identifying these species, as these sequences were generated from the paratypes of P. wilsoni (Chen et al. 2002; Glasby and Hsieh 2006). DNA sequence-based NCBI BLAST and phylogenetic analyses of JTS sequences also support our identification (see next sections). Distribution. Japan; China (based on /7S genes). Other records require validation using at least /7S data. zse.pensoft.net 1302 Yang, D. et al.: Morphological and molecular studies of Perinereis wilsoni Figure 1. Perinereis wilsoni Glasby & Hsieh, 2006; A-I. (except J, K) 23007-1; J, K. 23007-2; A. Entire body in dorsal view; B. Right jaw, ventral, and dorsal view; C. Anterior region with pharynx everted, dorsal view; D. Maxillary ring, frontal view; E. Anterior end with pharynx everted, ventral view; F. Left parapodium, posterior view, chaetiger 10; G. Right parapodium, posterior view, chaetiger 30; H. Sub-acicular neuropodial heterogomph falciger, chaetiger 30; I. Right parapodium, posterior view, chaetiger 80; J. Anterior view with pharynx everted, dorsal view; K. Anterior view with pharynx everted, ventral view. All photos were taken by Deyuan Yang. zse.pensoft.net Zoosyst. Evol. 100 (4) 2024, 1297-1314 Characteristics of the Perinereis wilsoni mitochondrial genome and nuclear genes The mitogenomes (23007-1 and 23007-2) generated from various assemblers yielded consistent results, except for the Ray assembler. They are 15,817 bp with an average coverage depth of 315x, and read mapping is 0.09% (Suppl. material 2). The genomes contain 13 protein-cod- ing genes (PCGs), two ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and one putative control region measuring 1160 bp. All genes are distributed on the heavy (H-) strand, similar to other Nereidinae spe- cies (Fig. 2A, Suppl. material 3: table S8). The nucleotide identity of 13 PCGs between P. wi/soni and the other 31 Nereididae species showed that the other species of Peri- nereis and Neanthes acuminata (OQ729916) have a high nucleotide identity with P. wilsoni (Fig. 2D). The NCBI BLAST results of the mitogenome revealed that the sequence identity with the published /6S' se- quences of P. wilsoni (LC482171—LC482183, Tosuji et al. 2019) ranged from 98.34% to 99.52%. However, the NCBI BLAST results for the full-length /6S indicated over 98% sequence identity with both P. mictodonta (e.g., LC482161—LC482168, Tosuji et al. 2019) and P. wilsoni (e.g., LC482171—LC482183, Tosuji et al. 2019). These results show that the /6S marker is not suitable for distin- guishing these two species. The nuclear rRNA contigs for the two specimens (23007-1 and 23007-2) yielded 10,983 bp and 10,820 bp with average coverages of 218.3 and 306x, respective- ly. Both results contained the full /8S, /TS/, 5.8S, [TS2, and 28S regions, with gene lengths of 1,849 bp, 358 bp, 160 bp, 305 bp, and 3,840 bp, respectively (Fig. 2B). The nuclear histone genes for both specimens were 6,399 bp, with coverage depths of 1,547.5x and 2,620x, respective- ly, incorporating complete sequences of H3 (411 bp), H2A (375 bp), H2B (372 bp), and H4 (312 bp) genes (Fig. 2C). The NCBI BLAST analysis of nuclear rRNA and histone genes showed that the /S.S sequence had over 99% sequence identity with eight species belonging to five genera, indicat- ing that /SS may not be suitable for species identification: 91.43% for 28S with Alitta virens (OW028578); 98.48%- 98.54% for JTS with P. wilsoni (AF332158—AF332162, Chen et al. 2002); 96%-98% for H3 genes with Perinereis sp. A ZW-2022 (OL546356), P. aibuhitensis (MW622055), and P. suluana (JX443591); approximately 92% for H2A and H2B with A. virens (OW028584), P. dumerilii (X53330); and 89.4% for H4 (Suppl. material 3: table S1). Mitochondrial genes and codon usage The mitochondrial genes in P. wi/soni exhibit a high A + T content of 64.6% (34.3% T and 30.3% A) and lower lev- els of C and G at 21.6% and 13.8%, respectively (Suppl. material 3: table S8). AT-skew and GC-skew are negative for the mitogenome (-0.062 and -0.221) and PCGs except for COX2 (-0.084 and -0.250), and AT-skew is positive 1303 for tRNAs and rRNAs (0.041 and 0.043) (Suppl. materi- al 3: table S8). The mitogenome is compact, with a total of three gene overlaps ranging in length from 2 to 7 bp. There are 12 gene spacers (259 bp in total) from 1 bp to 78 bp. All 13 PCGs start with the ATG codon and stop with T, TAA, or TAG (Suppl. material 3: table S9). A total of 22 tRNA genes with lengths ranging from 53 to 68 bp were identified in the mitogenome of P. wilsoni. The most frequently utilized amino acids in the mi- togenome of P. wilsoni are Leu (14.83%), lle (9.94%), Ser (8.60%), and Ala (7.84%). The least common amino acids are Cys (1.01%), Arg (1.78%), Asp (1.78%), and Gln (1.94%) (Fig. 3, Suppl. material 3: table S10). Rel- ative synonymous codon usage (RSCU) values for the 13 PCGs showed that UCU (Ser) and UUA (Lez) are the two most frequent codons, whereas UGG (7rp) and CCG (Pro) have the lowest frequencies (Fig. 3). Phylogenetic analyses and genetic distances Summary statistics for multiple alignments of various datasets are available in Suppl. material 3: table S11. The heterogeneity analysis of five mitogenome datasets revealed that datasets excluding the third codon position (13PCGs12, 13PCGs12_2R) exhibited lower heterogene- ity compared to those including the third codon position (13PCGs, 13PCGs_2R). The lowest heterogeneity was ob- served in the 13PCGsAA dataset (see Suppl. material 5). A total of ten ML and BI trees were inferred from five mitogenome datasets of Nereididae (see Suppl. material 6). These trees exhibit eight different topologies based on pairwise tree comparisons, indicating the significant in- fluence of the chosen mitogenomic dataset and tree-build- ing method on the inferred phylogenetic relationships. In general, ML and BI trees inferred from the same dataset are generally consistent, except for some obvious differ- ences observed in the 13PCGs_2R and 13PCGs12_ 2R datasets (see Suppl. material 6). In the 13PCGs12 dataset, we could not re-root the ML and BI trees using the out- group, which was excluded from TreeSpace analysis. The remaining eight trees were clustered into four groups, representing four types of trees (see Fig. 4B—F). The most common topology is depicted in Fig. 4A, D. Phylogenetic analyses based on five datasets of the available mitochondrial genomes (32 taxa in Nereididae, including 8 taxa in Perinereis) provide support for the monophyly of the genus Perinereis. Perinereis was either sister to the genus Nereis and the species Cheilonereis cy- clurus (MF538532) (Fig. 4C, E, F) or sister to the genera Platynereis, Hediste, Alitta, Nectoneanthes, and the species Laeonereis culveri (KU992689) (Fig. 4D). In all trees, P wilsoni was sister to P. vancaurica and P. nuntia with high nodal support values (BS > 94%, PP = 1) (Fig. 4 and Sup- pl. material 6). The P. nuntia species group was found not to be monophyletic. Specifically, P. linea (NC 063944), P. aibuhitensis (NC 023943), and P. vancaurica (ON611802) have two or three paragnaths on Area VI of the pharynx, zse.pensoft.net 1304 A 1200 Yang, D. et al.: Morphological and molecular studies of Perinereis wilsoni ® 800 o £ g (o) © 400 0 0 2000 4000 6000 8000 10000 12000 14000 15817 cox1 Ncox2c y/mpcox3anad6 cytb watp6rH nad5 FEPT \, nad4 12S v 16S tsat,nad1ix \ s, nad2 c atp8 nad4l nad3 5 600 @ 400 i@)] s $ fe] © 200 0 0 2000 4000 6000 8000 10000 10983. 18S ITs1 5.88 ITs2 28S C__ 2000 6000 @ e @ 4000 3 oO 2000 0 0 2000 4000 6000 6399 H3 H2, H2, H4 !) ccoc trnC(gca) |) pcos ND2 ioe COX1 ) cos fy tra trnK(uuu) ; I) rena trni(gau). A trnL(uaa). trnA(ugc)}. As A trnS(uga) aS rai (uations y rm16—___, trnV(uac). riilea- 2 BB Bast hit = 100% identical By Bast hit >= 98% identical BB east nit >= 96% identical BB Biast hit >= 94% identical I Biast hit >= 92% identical I) BLast hit >= 90% identical I BLast nit >= 88% identical D0) Bast hit >= 86% identical ___ BLAST hit >= 84% identical BLAST hit >= 82% identical BLAST hit >= 0% ND4 : ent / trnP(ugg trnE(uuc) identical wh and, trnHt a AT-rich region Perinereis nuntia Perinereis camiguinoides Perinereis vancaurica Perinereis aibuhitensis Perinereis linea Perinereis fayedensis Neanthes acuminata . Perinereis cultrifera 9. Alitta virens 10. Hediste diadroma 11. Hediste japonica . Hediste diversicolor . Platynereis cf. australis . Platynereis cf. australis . Platynereis sp.2 . Alitta succinea . Nectoneanthes multignatha . Platynereis sp.1 . Nectoneanthes uchiwa . Alitta succinea . Platynereis dumerilii . Platynereis bicanaliculata . Nereis zonata . Cheilonereis cyclurus . Nereis sp. . Laeonereis culveri . Paraleonnates uschakovi . Dendronereis chipolini . Neanthes glandicincta . Tylorrhynchus heterochaetus . Namalycastis abiuma trnN(guu) Lee ~ ‘N Peas SAOARwWNs 5 _-—tmy(gua) ATP8 trnM(cau) ;———trnD(guc) ; “dds namiennnnee nnn NE | fo SC OXKS ND6 a er Tek Sane ATP6 trn \ (gug) Figure 2. The gene map of Perinereis wilsoni (23007-1), 23007-2, is the same as 23007-1 but only shows one; A. Mitogenome; B. Nuclear rRNA cluster; C. And histone genes; D. CCT (CGView Comparison Tool) map and sequence identity compare the mitog- enome between P. wi/soni and the other nereidids. A-C. The green lines depict the distribution of coverage depth; D. Starting from the outermost ring, the feature rings depict: 1. COG (Clusters of Orthologous Groups of Proteins) functional categories for forward strand coding sequences; 2. Forward strand sequence features; 3. The remaining rings show regions of sequence similarity detected by BLAST comparisons between CDS translations from the reference genome and 31 comparison genomes. BLAST identities are organized from high to low, with higher values closer to the outer ring. zse.pensoft.net Zoosyst. Evol. 100 (4) 2024, 1297-1314 6 1305 245 202 lcac|cec|ucc acc|acc Guc UGG) | (GGAlUCA|AGA|ACA GUA oss ues acc|ace cus Figure 3. The relative synonymous codon usage (RSCU) in the mitogenome of Perinereis wilsoni. The numbers on the bars repre- sent amino acid composition. which belong to Perinereis Group 2 (Hutchings et al. 1991); all other Perinereis species (except Perinereis cul- trifera) in the trees belong to the P. nuntia group. Yet, the species of Group 2 were nested within the P. nuntia group. Phylogenetic trees (ML and BI) based on COX genes recovered that P. wilsoni (23007-1, 23007-2) have a closer relationship with P. mictodonta (KC800632, KC800630, KC800628), with nodal support values (BS = 83%, PP = 0.94). All taxa labeled P. wilsoni and P. mictodonta did not each form a monophyletic group, respectively; instead, they were divided into five distinct clades. This suggests the potential of cryptic species present within P. wilsoni and P. mictodonta or that the specimens were sampled from geographically distant localities with some degree of isolation. These five clades were also supported by genet- ic distances, which have a distinct barcode gap from each other (Fig. 5A, D, and Suppl. material 7). The phylogenet- ic trees (ML and BI) based on /6S genes suggested that P. wilsoni and P. mictodonta were each not monophyletic (Fig. 5B, E, and Suppl. material 8). Genetic distances also showed that the sequences of P. wilsoni and P. mictodon- ta had no barcode gap (Fig. 5B). The phylogenetic trees (ML and BI) based on JTS genes supported P. wilsoni as a sister to P. mictodonta (BS = 96%, PP = 1). Although P. wilsoni and P. mictodonta formed a monophyletic cluster with each other, the genetic distance analyses showed that these two species have no distinct barcode gap (Fig. 5C, F, and Suppl. material 9). Based on the dos Santos Vieira et al. (2020) methodology, optimal markers were selected based on an overlap criterion of less than 20%. However, the overlap between P. wilsoni and P. mictodonta exceed- ed 35%, indicating that COX], 16S, and JTS genes are not optimal molecular markers (Fig. 5A—C). The positions of Paraleonnates uschakovi (NC 032361) and Laeonereis culveri (KU992689) are un- stable, jumping across different phylogenies (Fig. 4, Suppl. material 6). Laeonereis culveri (KU992689) is closer to P. uschakovi (NC 032361) in four trees (13PCGs_2R_ ML, 13PCGs12 ML, 13PCGs12 2R_ ML, and 13PCGsAA_BI in Suppl. material 6), all with high nodal support. In contrast, in six other trees, L. culveri (KU992689) is more closely related to the genera Hediste, Alitta, and Nectoneanthes, also with high nodal support, except in the 13PCGs12_ ML and 13PCGs12 BI trees (Fig. 4, Suppl. material 6). Paraleonnates uschakovi is closer to the subfamilies Gymnonereidinae, Dendronereinae, and Nereidinae (8 of 10 trees), with low nodal support in ML trees but with high nodal support in BI trees. In 13PCGs12__ ML and 13PCGs12_BI trees, P. uschakovi was clus- tered with the outgroup, all with low nodal support (Suppl. material 6). There are two primary types of mitochondrial gene or- der in the known mitochondrial genomes of Nereididae, except for L. culveri (KU992689). The first type of gene order is observed in the subfamilies Gymnonereidinae, Dendronereinae, and P. uschakovi. The second type is found in the subfamily Nereidinae, except for L. culveri (see Fig. 4). Nucleotide diversity and evolutionary rate analyses The nucleotide diversity (Pi) analysis was conduct- ed using concatenated alignments of 13 PCGs and zse.pensoft.net 1306 Yang, D. et al.: Morphological and molecular studies of Perinereis wilsoni Outgroup "ee at: ? — 7 = = Gymhnonereidinae 81/4 7 Namanereidinae Namalycastis abiuma NC | Dendronereinae Nereidinae Tree scale: 0.5 jamalycastis abiuma NC 030040 feanthes glandicineta NC 035893 endronereis chipolini MW532064 Tylorrhynchus heterochaetus NC 025567 araleonnates uschakovi NC 032361 aeonereis culveri KU992689 latynereis bicanaliculata NC 051995 latynereis sp 1 MN@30365 Jatynereis dumerilii NC 000931 latynereis sp 2 MN&30366 Jatynereis cf australis NC 052845 vatynereis cf australis MN830369 lediste japonica NC 050679 lediste diversicolor NC 057074 araleonnates uschakovi NC 032361 aeonereis culveri KU992689 lectoneanthes uchiwa NC 082300 lectones jes multignatha NC 082301 Alitta succinea OQ729897 Alitta succinea NC 051993 lereis zonata NC 053360 jereis sp MF960765 heifonereis cyclurus MF§38532 13PCGs_2R_ML 13PCGs12_2R_ML Alitta succinea OQ729891 lediste diadroma NC 035507 litta virens OWO28587 fectoneanthes uchiwa NC 082300 ectoneanthes multignatha NC 082301 litta succinea OQ729891 litta succinea NC 051993 jereis zonata NC 053360 jereis sp MF960765 eilonereis cyclurus MF538532 i is cultrifera NC 051994 a NC 063944 uhitensis NC 023943 sis OQ729919 eanthes acuminata 0Q729916 D 13PCGs_2R_Bl E 13PCGs_BI 13PCGsAA_BI 13PCGs_ML 13PCGs12-2R-BI cyclurus MFS38532 587 NC 050679 Laeonereis culveri KU992689 ‘Nectoneanthes uchiwa NC 082300 jectoneanthes multignatha NC 082304 “Alita succinea OQ729891 “Alitta suecinea NC 051993 Figure 4. An analysis of phylogenies from five mitogenome datasets. A. Maximum likelihood (ML) and Bayesian inference (BI) tree of Nereididae based on the dataset 13PCGs. The GenBank accession numbers used are listed after the species names. The scale bar (0.5) corresponds to the estimated number of substitutions per site. Numbers at nodes are statistical support values for ML bootstrap support. Asterisks denote 100% bootstrap support. “-” indicates no support value. Color-coded clades are four subfamilies within Nereididae. The gene order is shown to the right. “?” indicates the deletion of a gene; B. A two-dimensional MDS plot of eight trees (excluding 13PCGs12_ML and 13PCGs12_BI), colored by different clusters. C-F. For each cluster identified in B., a representative tree was selected. Note: Neanthes glandicincta (NC 035893) is an incorrectly identified taxon, which should be the genus Dendronereis. Neanthes acuminata (OQ729916) and Perinereis fayedensis (OQ729919) should be Perinereis suezensis and Perinereis damietta, respectively. Perinereis aibuhitensis (NC 023943) should be Perinereis linea (NC 063944). two rRNAs of 32 Nereididae species. The sequence Discussion variation ratio exhibits variable nucleotide diversi- ty between the Nereididae, with Pi values for the 100 The taxonomic status of Perinereis wilsoni bp windows ranging from 0.061 to 0.563 (Fig. 6A). COX] (Pi = 0.211), COX3 (0.235), CYTB (0.238), and COX2 (0.239) exhibit a comparatively low sequence variability, whereas ATPS (0.405), ND2 (0.386), and 30 species concepts having been proposed (Hong 2020), ND6 (0.378) have a comparatively high sequence vari- _ the scientific community has not reached a consensus on ability. This 1s corroborated by the non-synonymous/ defining a species. Our study adopts the Gen-morph species synonymous (Ka/Ks) ratio analysis, which shows that concept, initially proposed by Deyuan Hong (Hong 2020), COX] (Ka/Ks = 0.036), COX3 (0.038), CYTB (0.053), | which requires at least two each of independent morpho- and COX2 (0.065) are evolving comparatively slowly, logical characteristics and genetic markers for species defi- whereas ATPS (0.270), ND2 (0.196), and ND6 (0.173) nition. According to this concept, morphological characters are evolving comparatively fast (Fig. 6B). All genes are —_ include quantitative morphological features that have been under purifying selection. shown to be statistically different between species. Before discussing this topic, it 1s crucial to specify the spe- cies concept employed in this study. Despite approximately zse.pensoft.net Zoosyst. Evol. 100 (4) 2024, 1297-1314 P. wilsoni MN256543 [lI A A A ||| | P. wilsoni MN256542 i P. wilsoni MN256541 [i ||| P. wilsoni Ky129689 A) | P. wilson’ KY 129888, |) P. wilsoni KY129887 P. wilsoni KC800637 aa wilsoni KCa00629 fi, P. wilsoni o2oeeze il {Barcode gap ial Distance overlap 0,10 100 0.05 0.15 0.10 0.05 0.00 0 0.00 Pw P.m SSS SSeS SSS Ses esses esse eseeeceeeenenan snes anenenaanad B P.wisoniLc4e21s6M | P. wilsoni LC482187 || P. wilsoni LC482186 Tt fe P. wilsoni 6462 (05 en || P. wilsoni LC482184. P. wilsoni LC482783 I P. wilsoni LC482182 9) OO P. wilsoni (oS P. wilsoni LC462700 I P. wilsoni LC482179 P. wilsoni LC482178 (|) P. wilsoni LC482177 i P. wilsoni LC482176 Barcode gap 8 Distance overlap 0.10 100 0.04 P. wilsoni KC833494. P, wilsoni 23007_2 P. wilsoni 23007_1 P. mictodonta ieano ical 0.03 P. mictodonta JX503026 a NG JX503025 | P. mictodonta JX503024 1307 Perinereis mictodonta JX503024 Perinereis mictodonta JX503026 | Clade 1 Perinereis mictodonta JX503025 Perinereis wilsoni MN256543 Perinereis wilsoni KY129888 Perinereis wilsoni KY129887 Perinereis wilsoni MN256542 Perinereis wilsoni MN256541 Perinereis wilsoni KY129889 Perinereis wilsoni KC800623 Perinereis wilsoni KC800631 | Perinereis wilsoni KC800629 Perinereis wilsoni 23007_1 Perinereis wilsoni 23007_2 Perinereis mictodonta KC800628 Perinereis mictodonta KC800632 | Clade 5 Perinereis mictodonta KC800630 Clade 2 Clade 3 | Clade 4 Perinereis wilsoni KC833497 Perinereis mictodonta LC482168 pau Perinereis mictodonta LC482167 _ Perinereis mictodonta LC482166 ay Perinereis wilsoni KC833494 Oe Perinereis mictodonta LC482163 0.0 Perinereis mictodonta LC482161 006 Perinereis mictodonta LC482164 wen Perinereis mictodonta LC482162 Perinereis mictodonta LC482165 Perinereis wilsoni LC482180 Perinereis wilsoni LC482178 05 Perinereis mictodonta KC833496 O79 Perinereis wilsoni LC482179 O08 in Perinereis mictodonta KC833498 b Perinereis wilsoni LC482189 098 Perinereis wilsoni LC482188 me Perinereis wilsoni LC482187 Perinereis wilsoni LC482185 Perinereis wilsoni LC482186 pes Perinereis wilsoni LC482184 Perinereis wilsoni LC482181 75 Perinereis wilsoni LC482183 0: Perinereis wilsoni LC482182 086 Perinereis wilsoni LC482170 m P. mictodonta LC482167 ME EEEES” P. mictodonta LC482166 BEERS P. mictodonta LC482165E EE P. mictodonta LC482164EE P. mictodonta LC482163 P. mictodonta LC482162M P. mictodonta LC482161 P. mictodonta KC833498 0.05 0.02 0.01 Perinereis wilsoni LC482169 Perinereis wilsoni LC482172 Perinereis wilsoni LC482171 Perinereis wilsoni LC482176 Perinereis wilsoni LC482174 Perinereis wilsoni LC482173 0,00 0 0.00 Pow Pm See ese eee eee S288 SF FFF SF FEE SEE FEESEGG 88888288288 88228888288 82888882 Ff U.06 P. wilson .c482304 I RR C P. wilsoni LC482144 RR a 6B P. wilsoni LC482143 ITS P. wilsoni AF332162 P. wilsoni AF3321619 P. wilsoni AF332160 i i P. wilsoni AF332159 i P. wilsoni AF332158 P. wilsoni 23007_2 P. wilsoni 23007_1 P. mictodonta LC482149 P. mictodonta .c482144 0 8) Barcode gap B Distance overlap 0.10 100 0.05 50 0.00 0 0.04 0.03 P. mictodonta KC833496 P. mictodonta Lc482147, I Ei P. mictodonta Lc4821460) P. mictodonta LC482145) A pie P. mictodonta AF332167 P. mictodonta AF332166 i) 0.01 P. mictodonta AF332165 || 0.00 P. mictodonta AF 332164 ij P. mictodonta AF 332163 Perinereis wilsoni LC482177 Perinereis wilsoni LC482175 v- Perinereis wilsoni 23007_1 a Perinereis wilsoni 23007_2 F Perinereis wilsoni LC482144 bee Perinereis wilsoni AF332159 7 Perinereis wilsoni LC482304 Perinereis wilsoni LC482143 Perinereis wilsoni 23007_1 Perinereis wilsoni AF332160 a4 Perinereis wilsoni AF332158 0.45 Perinereis wilsoni 23007_2 0.62 Perinereis wilsoni AF 332162 0.28 Perinereis wilsoni AF332161 Perinereis mictodonta LC482146 0.96 Perinereis sp Chuwei AF332166 0.98 Perinereis mictodonta LC482145 1 Perinereis mictodonta AF332165 Perinereis mictodonta LC482149 Perinereis mictodonta LC482148 Perinereis mictodonta AF332167 Perinereis mictodonta AF332164 O98 Perinereis mictodonta LC482147 0.48 Perinereis mictodonta AF332163 0.32 0.42 0.29 0.34 0.99 0.83 Figure 5. The heatmap of COX] A, /6S B., and /TS C. p-distance for Perinereis wilsoni and P. mictodonta, with the barcode gap and distance overlap of them on the left. Bayesian inference (BI) phylogenetic trees for the two species, based on sequences of COX1 D, 16S E, and ITS F, are excerpted from Suppl. materials 7-9. Sequences from P. wilsoni are depicted in black, those from P. mictodonta in green, with sequences from this study highlighted in bold. Perinereis wilsoni and P. mictodonta were initially es- tablished as separate species based on statistically vali- dated morphometric differences and the results of the /7S genes (Glasby and Hsieh 2006). Subsequent studies by Park and Kim (2007) and Tosuji et al. (2019) demonstrat- ed that COX], 16S, and JTS genes can distinguish these two species, respectively. However, the COX/ sequences used in Park and Kim (2007) have not been made pub- licly available. Moreover, their study relied solely on morphological characteristics for species identification and did not validate these identifications with /T7S gene analysis, casting doubt on the reliability of their findings. Our re-analysis of sequences from (Tosuji et al. 2019) showed that the /6S was insufficient to distinguish the zse.pensoft.net 1308 > Nucleotide diversity (Pi) S S © AN) N) S S S S S S N) S SN) N) S \N) N) N) S S ZN & oS RY we we Ry Yang, D. et al.: Morphological and molecular studies of Perinereis wilsoni Nucleotide Position Ka/Ks i COxX1 COX2 ATP8 COX3 ND6 CYTB ATP6 ND5 ND4L ND4 ND1 Genes ND3 ND2 Figure 6. Nucleotide diversity analysis: A. Of 13 PCGs + two rRNAs and Ka/Ks rates; B. Of 13 PCGs based on 32 Nereididae species. The Pi values for the 13 PCGs + two rRNAs are shown on the graph. The red line represents the value of nucleotide diversity (Pi) (window size = 100 bp, step size = 20 bp). The pink, purple, and green columns represent the values of Ka, Ks, and Ka/Ks, respectively. two species. To date, only /7S genes have proven effec- tive in distinguishing P. wi/soni and P. mictodonta (Chen et al. 2002; Glasby and Hsieh 2006; Tosuji et al. 2019). Considering the Gen-morph species concept, P. wilsoni may not be a “good” species until a second genetic mark- er (and a more optimal one than /7S; see below) can be found. Therefore, comprehensive specimen sampling from various geographical locations is still required to assess its taxonomic status thoroughly (Deyuan Yang et al. in preparation). Which molecular markers suit Perinereis wilsoni Glasby & Hsieh, 2006 identification? Partial mitochondrial genes, like COX/ and /6S, and nuclear genes, like /S&S, 28S, JTS, and H3, are widely used in Nereididae for species discovery and phyloge- netic studies (Glasby et al. 2013; Elgetany et al. 2022; Teixeira et al. 2022a; Teixeira et al. 2022b; Teixeira et al. 2024). Among these genes, the /8S and 28S genes are typically used in higher-taxon phylogenetic analyses. A comprehensive assessment of the effectiveness of these molecular markers in differentiating species, both closely and distantly related across various genera and families, remains limited (Halanych and Janosik 2006). zse.pensoft.net Given that species within the P. nuntia complex are morphologically similar and not easily distinguishable based on morphology alone, molecular-based identifica- tion can offer a faster and more reliable method for species identification when reliable molecular references are avail- able. Our analyses were unable to confirm the discrim- inative capability of the COX/ gene between P. wilsoni and P. mictodonta, as the sequences sourced from public databases were not linked to morphological and /7S gene data, thus limiting our further study. Additionally, the /6S gene was proven to be insufficient to distinguish these two species. Although /7S genes have been found effective in distinguishing cryptic species (Chen et al. 2002; Pleiyel et al. 2009; Nygren and Pleijel 2011; Nygren 2014), they may not be the optimal molecular marker in distinguishing P. wilsoni and P. mictodonta due to the lack of a distinctive barcoding gap between these two species. Furthermore, there are only a few available sequences of Polychaeta JTS genes in the public database, possibly due to difficulties in amplifying these sequences by PCR. We found that the primer sets /7S/SSFPOLY and ITS2SSRPOLY (Nygren et al. 2009) may be more effective than the one provided by Chen et al. (2002) for amplifying /7S genes in Perinereis. With advances in sequencing technologies, high-through- put sequencing (HTS) is more efficient than PCR-based Sanger sequencing in obtaining molecular markers. Recently, Zoosyst. Evol. 100 (4) 2024, 1297-1314 some new molecular markers have been proposed, such as nearly universal single-copy nuclear protein-coding genes (Eberle et al. 2020) and organelle genomes (Margaryan et al. 2021). In this paper, we found the genome-skimming approach makes it easier to explore the mitogenome, com- plete nuclear ribosomal DNA (/8S-/TS1-5.8S-ITS2-28S), and complete histone genes. However, it is more difficult to explore universal single-copy nuclear protein-coding genes, even with sequencing data increased to 25 Gb. The phylogeny of Perinereis and the systematic position of Perinereis wilsoni Currently, a robust phylogenetic backbone of the genus Perinereis, based on phylogenomic methods and exten- sive taxon sampling encompassing major species in all five informal grouping schemes proposed by Hutchings et al. (1991), is still lacking. Traditionally, the genus Perinereis has been considered polyphyletic (Bakken and Wilson 2005; Glasby et al. 2013; Alves et al. 2020; Elgetany et al. 2022). However, this view is largely based on morphological evidence or a limited number of loci and/or may include assembly errors in their datasets. In this study, although our curated mitogenome datasets support the monophyly of the genus Perinereis, the data- set includes only 8 species, whereas the genus currently comprises 103 species (Prajapat et al. 2024). Further- more, morphological diversity within the genus has been unevenly sampled. Hutchings et al. (1991) proposed an informal grouping scheme with five groups. Our mitoge- nome dataset includes Group 1A, represented by | taxon (P. cultrifera), Group 2A, represented by 4 taxa (P. linea, P. aibuhitensis (should be P. linea), P. camiguinoides, and P. vancuarica), and Group 3A, represented by 4 taxa (P. fayedensis, N. acuminata (=P. suezensis), P. wilsoni, and P. nuntia). However, Groups 1B and 3B are not represent- ed. To confidently establish the monophyly of the genus, future analyses should include multiple representatives from each of these informal morphological groupings. Based on the available mitogenome datasets, Perinereis wilsoni is a sister group to P. vancaurica and P. nuntia, with high nodal support in all phylogenetic trees. In contrast, single-gene phylogenetic trees suggest that P. wilsoni is more closely related to P. mictodonta, with low nodal sup- port. Although including more taxa, single-gene trees do not provide sufficient resolution in phylogeny. In summary, the phylogenetic relationships of P. wilsoni remain poorly understood due to the limited number of Perinereis species or other Nereididae for which genomic data are available. The phylogeny of Nereididae A deep discussion of the phylogeny of Nereididae is be- yond the scope of our current work. Here, we provide a brief discussion. The positions of P. uschakovi and L. cul- veri (KU992689) were observed to be unstable in the trees, inferred from different mitogenome datasets in this study. 1309 In detail, LZ. culveri always nested within the subfam- ily Nereidinae, which was also found in previous stud- ies using different datasets, such as COX/, 16S, and 18S (Wang et al. 2021; Alves et al. 2023; Villalobos-Guerrero et al. 2024), as well as mitogenome datasets (Alves et al. 2020). L. culveri is also a sister group to the Gymnone- reidinae, Dendronereinae, and Nereidinae subfamilies, along with P. uschakovi (this study; Villalobos-Guerrero et al. 2024). P. uschakovi was always found as a sister group to other subfamilies (Alves et al. 2020; Wang et al. 2021; Alves et al. 2023; Villalobos-Guerrero et al. 2024: this study). However, it occasionally grouped with the outgroup Craseoschema thyasiricola (NC 060815, see Suppl. material 6: 13PCGs12_ ML tree and 13PCGs12_ BI tree) or formed a single clade with the Gymnonereidi- nae and Dendronereinae subfamilies (see Suppl. material 6: 13PCGsAA_ML tree), which appears to be supported by mitochondrial genome gene order. Alves et al. (2020) also found this situation when removing outgroups. In- spired by a morphological phylogenetic tree proposed by Wu et al. (1981), which is based on the characteristics of pharyngeal armature, we propose a hypothesis that Para- leonnates and Laeonereis (KU992689) may represent early branching members of Nereidinae. The lack of suf- ficient data on such taxa may be causing their uncertain placements within the phylogenetic framework. In this study, we uncovered potential errors in assembly and annotation within GenBank. However, the absence of corresponding Sequence Read Archive (SRA) data in public databases hampers accurate confirmation of these errors. Consequently, we filtered these sequences based solely on our expertise. Therefore, I (Deyuan Yang) advo- cate for the uploading of original data (raw data) to public databases, such as NCBI. Even if some authors are unwill- ing to upload their data, various assembly methods should be employed to ensure the accuracy of the assemblies. Additionally, we emphasize that carefully curated datasets (verifying the taxonomic identification of the Species used in the phylogenetic study), especially those from public databases, are crucial before conducting phy- logenetic studies, as taxonomic misidentifications can lead to incorrect conclusions. For example, Alves et al. (2020) concluded that Gymnonereidinae was non-mono- phyletic, a finding that was impacted by the inclusion of an incorrectly identified taxon, Neanthes glandicincta (NC 035893), which should have been classified under the genus Dendronereis Peters, 1854 (Zhen et al. 2022; this study). Additionally, in this study, 1f we had not ques- tioned the name Neanthes acuminata (OQ729916), we would have concluded that Perinereis is non-monophy- letic. However, N. acuminata should be re-identified as Perinereis suezensis (Elgetany et al. 2022). Author Contribution D.Y.Y. and S.Z. wrote the manuscript, and S.Z. wrote the part on mitochondrial genes, codon usage, nucleotide di- versity, and evolutionary rate analyses. D.Y.Y. and S.Z. zse.pensoft.net 1310 analyzed the data. Z.W., Y.J.Z., and D.Z.Y. participated in the discussion and reviewed the manuscript. C.J.G., J.S.H., and L.Z.C. conceived and designed, supervised the work, and reviewed drafts of the paper. 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Glasby, Jiang- Shiou Hwang, Lizhe Cai Data type: pdf Explanation note: (a) Basic information on clean data, including duplicate reads (%, Dups), average GC con- tent (%, GC), and total sequences (millions, M Seqs). (b) Sequence counts for each sample. Duplicate read counts are an estimate only. Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow us- ers to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://do1.org/10.3897/zse.100.127201.suppl1 Supplementary material 2 The report of Quast Authors: Deyuan Yang, Sheng Zeng, Zhi Wang, Yanjie Zhang, Dazuo Yang, Christopher J. Glasby, Jiang- Shiou Hwang, Lizhe Cai Data type: pdf Explanation note: (a) Basic information of various assem- blers. (b) The cumulative length of each assembler. All statistics are based on contigs of size >= 500 bp, unless otherwise noted (e.g., "# contigs (>= 0 bp)" and "Total length (>= 0 bp)" include all contigs). Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow us- ers to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zse.100.127201.suppl2 1313 Supplementary material 3 Additional information Authors: Deyuan Yang, Sheng Zeng, Zhi Wang, Yanjie Zhang, Dazuo Yang, Christopher J. Glasby, Jiang- Shiou Hwang, Lizhe Cai Data type: xlsx Explanation note: table S1. The Blast results of mitochondrial gene, 18S, 28S, ITS, and histone genes (Only 20 sequences are shown). table 82. List of 32 species and two outgroups used in this paper. table S3. Sequence Information from NCBI BLAST Analysis of the COX] Gene. table S4. Sequence Information from NCBI BLAST Analysis of the /6S Gene. table S5. Original and Gblock lengths of the PCGs and PCGsAA sequences. table S6. Best partitioning schemes and models based on different datasets for maximum likelihood and Bayesian inference analysis. table S7. COJ, 16S, 18S, 28S, TS, and H3 gene sequences information of Perinereis. table S8. Nucleotide composition and skewness comparison of different elements of the mitochondrial genomes of P. wilsoni. table S9. Features of the P. wilsoni mitogenome. table S10. Codon numbers and relative synonymous codon usage (RSCU) of 13 PCGs in the P. wilsoni mitogenome. table S11. Summary statistics for multiple alignment of various datasets. Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow us- ers to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://do1.org/10.3897/zse.100.127201.suppl3 Supplementary material 4 The Python script for categorizing data Authors: Deyuan Yang, Sheng Zeng, Zhi Wang, Yanjie Zhang, Dazuo Yang, Christopher J. Glasby, Jiang- Shiou Hwang, Lizhe Cai Data type: docx Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow us- ers to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://do1.org/10.3897/zse.100.127201.suppl4 zse.pensoft.net 1314 Supplementary material 5 Heterogeneity of sequence composition of mitochondrial genomes for 5 different data sets Authors: Deyuan Yang, Sheng Zeng, Zhi Wang, Yanjie Zhang, Dazuo Yang, Christopher J. Glasby, Jiang- Shiou Hwang, Lizhe Cai Data type: pdf Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow us- ers to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://do1.org/10.3897/zse.100.127201.suppl5 Supplementary material 6 10 trees from different datasets and tree- building methods Authors: Deyuan Yang, Sheng Zeng, Zhi Wang, Yanjie Zhang, Dazuo Yang, Christopher J. Glasby, Jiang- Shiou Hwang, Lizhe Cai Data type: pdf Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow us- ers to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://do1.org/10.3897/zse.100.127201.suppl6 Supplementary material 7 Phylogenetic trees of Perinereis based on the COX! dataset Authors: Deyuan Yang, Sheng Zeng, Zhi Wang, Yanjie Zhang, Dazuo Yang, Christopher J. Glasby, Jiang- Shiou Hwang, Lizhe Cai Data type: pdf Explanation note: (a) Bayesian inference (BI, left) and (b) maximum likelihood (ML, right) method Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow us- ers to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zse.100.127201.suppl7 zse.pensoft.net Yang, D. et al.: Morphological and molecular studies of Perinereis wilsoni Supplementary material 8 Phylogenetic trees of Perinereis based on the 16S dataset Authors: Deyuan Yang, Sheng Zeng, Zhi Wang, Yanjie Zhang, Dazuo Yang, Christopher J. Glasby, Jiang- Shiou Hwang, Lizhe Cai Data type: pdf Explanation note: (a) Bayesian inference (BI, left) and (b) maximum likelihood (ML, right) methods. Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow us- ers to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://do1.org/10.3897/zse.100.127201.suppl8 Supplementary material 9 Phylogenetic trees of Perinereis based on the ITS dataset Authors: Deyuan Yang, Sheng Zeng, Zhi Wang, Yanjie Zhang, Dazuo Yang, Christopher J. Glasby, Jiang- Shiou Hwang, Lizhe Cai Data type: pdf Explanation note: (a) maximum likelihood (ML, left) and (b) Bayesian inference (BI, right) methods. Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow us- ers to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zse.100.127201.suppl9