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. 2023 May 15;2023:gigabyte81. doi: 10.46471/gigabyte.81

The Crown Pearl V2: an improved genome assembly of the European freshwater pearl mussel Margaritifera margaritifera (Linnaeus, 1758)

André Gomes-dos-Santos 1,2,*, Manuel Lopes-Lima 3,4, André M Machado 1, Thomas Forest 5,6,7, Guillaume Achaz 5,6, Amílcar Teixeira 8, Vincent Prié 3,4, L Filipe C Castro 1,2, Elsa Froufe 1,*
PMCID: PMC10189783  PMID: 37207176

Abstract

Contiguous assemblies are fundamental to deciphering the composition of extant genomes. In molluscs, this is considerably challenging owing to the large size of their genomes, heterozygosity, and widespread repetitive content. Consequently, long-read sequencing technologies are fundamental for high contiguity and quality. The first genome assembly of Margaritifera margaritifera (Linnaeus, 1758) (Mollusca: Bivalvia: Unionida), a culturally relevant, widespread, and highly threatened species of freshwater mussels, was recently generated. However, the resulting genome is highly fragmented since the assembly relied on short-read approaches. Here, an improved reference genome assembly was generated using a combination of PacBio CLR long reads and Illumina paired-end short reads. This genome assembly is 2.4 Gb long, organized into 1,700 scaffolds with a contig N50 length of 3.4 Mbp. The ab initio gene prediction resulted in 48,314 protein-coding genes. Our new assembly is a substantial improvement and an essential resource for studying this species’ unique biological and evolutionary features, helping promote its conservation.

Data description

Background and context

Initial efforts to sequence molluscan genomes relied primarily on short-read approaches, which, despite their unarguable value, frequently result in highly fragmented assemblies [1–4]. Consequently, long-read sequencing approaches, such as Pacific Bioscience (PacBio) or Oxford Nanopore Technology, are becoming the common ground of emerging studies of molluscan genome assemblies [1–4]. This is further facilitated by the decreasing cost trend, coupled with the increasing sequencing accuracy of these approaches [5]. Additionally, the structural information provided by long-reads is crucial to span large indels or inform about long structural variants [6–8], which is particularly relevant for molluscans that have large, heterozygous, and highly repetitive genomes (reviewed in [4]). Consequently, long-read-based reference assemblies have reduced fragmentation levels, fewer missing and truncated genes, and reduced chances of chimerically assembled regions [6, 7].

Bivalves from the order Unionida, commonly known as freshwater mussels, are the most diverse group of strictly freshwater bivalves, with over 1,000 species distributed across all continents except Antarctica [9, 10]. The freshwater pearl mussel Margaritifera margaritifera (Linnaeus, 1758) (NCBI:txid2505931) is perhaps the most emblematic, culturally significant, and known species of freshwater mussels. The freshwater pearl mussel is also the only species of the group that inhabits both European and North American freshwater systems [11, 12] (Figure 1), mainly cool oligotrophic waters. Moreover, this species holds a series of distinctive biological features, such as the ability to produce pearls (with an ancient history of pearl harvesting [13, 14]), a long lifespan (reaching over 200 years [15]) with negligible signs of cellular senescence [16], and, as all other freshwater mussels, an obligatory parasitic life stage on salmonid fish species [12, 17]. In the past, the freshwater pearl mussel was highly abundant across its Holarctic distribution [12]. However, during the last century, the species has suffered massive declines due to the many human-mediated threats impacting the freshwater ecosystems [11, 12]. As a result, the species is listed as critically endangered in Europe and included in the European Habitats Directive under Annexes II and V, and the Appendix III of the Bern Convention [11].

Figure 1.

Figure 1.

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Top left: The M. margaritifera specimen used for the whole genome assembly of this study. Top right: A specimen of M. margaritifera in its natural habitat (Photos by André Gomes-dos-Santos). Bottom: Map of the potential distribution of the freshwater pearl mussel, produced by overlapping points of recent presence records [11] with Hydrobasins level 5 polygons [27]. The potential distribution for Europe was retrieved from [11] and for North America from [28].

Despite the cultural significance and poor conservation status of the freshwater pearl mussel, the availability of genomic resources to study this species is still limited [13, 18–22]. Also, almost nothing is known about the molecular mechanism governing the regulation and functioning of its many relevant biological features. Genomic resources provide benchmarking tools to monitor, identify, and classify conservation units as well as classify genetic elements with conservation relevance and adaptive potential [23, 24]. Hence, genomics provides invaluable tools to improve the success of conservation efforts. The sequencing of the first genome for the freshwater pearl mussel represented a fundamental resource for the study of its biology and evolution and, ultimately, promoted its conservation [13]. However, although the quality of this first assembly is good (validated with several statistics), it was produced using solely short-read sequencing (i.e., Illumina paired-end and mate-pair sequencing), thus hampering its overall contiguity [13]. The subsequent release of the highly contiguous genome assembly of the freshwater mussel Potamilus streckersoni [25], which relied on PacBio long-read sequencing, demonstrated how using longer reads is critical to ensure improved contiguity of genome assemblies to study freshwater mussels [26].

In this study, we aimed to improve the genome assembly of the freshwater pearl mussel M. margaritifera. Therefore, the genome of a new individual from this species was sequenced using PacBio CLR and Illumina paired-end short reads. As a result, we generated the most contiguous genome assembly of freshwater mussels available to date, significantly improving its contiguity and completeness [13].

Methods

Animal sampling

One individual of M. margaritifera was collected from the Tuela River in Portugal (Table 1) and transported alive to the laboratory, where tissues were separated, flash-frozen, and stored at −80 °C. The shell and tissues are deposited in the CIIMAR tissue and mussels’ collection.

Table 1.

Sample details for the freshwater pearl mussel M. margaritifera specimen used for our whole genome sequencing (WGS).

Sample Margaritifera margaritifera
Investigation_type Eukaryote
Lat_lon 41.862414; −6.931596
Geo_loc_name Portugal
Collection_date 06/07/2021
Env_package Water
Collector Amílcar Teixeira
Sex Undetermined
Maturity Mature
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DNA extraction and sequencing

For the PacBio sequencing, the mantle tissue was sent to Brigham Young University (BYU, USA). High-molecular-weight DNA extraction was performed, and PacBio library construction was achieved following the single-molecule real-time (SMRT) bell construction protocol [29]. The library was sequenced using an SMRT cell of a PacBio Sequel II system v.9.0. The genomic DNA for short-read sequencing was extracted from the muscle tissue using the Qiagen MagAttract HMW DNA Kit, following the manufacturer’s instructions. The extracted DNA was sent to Macrogen Inc. for standard Illumina Truseq Nano DNA library preparation, and the WGS of 150 bp paired-end reads on the Illumina Novaseq 6,000 machine (Table 2).

Table 2.

General statistics of the raw sequencing reads used for the M. margaritifera genome assembly.

Sample Sequencing type Library type Platform Insert size (bp) Number of reads Application
PacBio CLR WGS Long reads PacBio Sequel II system 14,339 7,892,056 Genome assembly, Genome polishing
Illumina PE WGS Short reads Novaseq 6000 450 1,369,564,530 Genome size estimation, Genome polishing
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Genome assembly and annotation

The overall pipeline used to obtain the genome assembly and annotation is provided in Figure 2.

Figure 2.

Figure 2.

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Bioinformatics pipeline used for the genome assembly and annotation.

Genome size and heterozygosity estimation

Before the assembly, the characteristics of the genome were accessed with a k-mer frequency spectrum using the paired-end reads. First, the quality of the reads was evaluated using FastQC (v.0.11.8; RRID:SCR_014583) [30]. The reads were then quality trimmed with Trimmomatic (v.0.38; RRID:SCR_011848) [31], specifying the parameters “LEADING: 5 TRAILING: 5 SLIDINGWINDOW: 5:20 MINLEN: 36”. Finally, the quality of the clean reads was validated using FastQC and then used for the genome size estimation with Jellyfish (v2.2.10; RRID:SCR_005491) and GenomeScope2 [32], specifying the k-mer length of 21.

Genome assembly

The primary genome assembly was constructed using the raw PacBio reads with NextDenovo v2.4.0 [33], with default parameters and specifying an estimated genome size of 2.4 Gbp. Polishing of the resulting assembly was performed in two steps. First, we used the PacBio reads with three iterations of GCpp v2.0.2 [34], and then we used the clean paired-end reads with two iterations of NextPolish v1.2.3 [35]. Specifically, the PacBio read alignments were performed with pbmm2 v1.4.0 [36], and the paired-end read alignments were performed with Burrows-Wheeler Aligner (BWA; v0.7.17; RRID:SCR_010910) [37], both with default parameters.

The general statistics and completeness of the final genome assembly were estimated with QUAST (v5.0.2; RRID:SCR_001228) [38], BUSCO (v5.2.2; RRID:SCR_015008) [39], and using the paired-end reads for read-back mapping with BWA, and a k-mer frequency distribution analysis with the K-mer Analysis Toolkit (KAT) [40].

Masking of repetitive elements, gene models’ predictions, and annotation

To mask repetitive elements, a de novo library of repeats was created for final genome assembly with RepeatModeler (v2.0.133; RRID:SCR_015027) [41]. Next, the genome was soft masked with RepeatMasker (v4.0.734; RRID:SCR_012954) [42], combining the de novo library with the ‘Bivalvia’ libraries from Dfam [43] (Dfam_consensus-20170127) and RepBase [44] (RepBaseRepeatMaskerEdition-20181026).

Gene prediction was performed on the soft-masked genome assembly using the BRAKER2 pipeline v2.1.6 [45]. First, all the available RNA-seq data of M. margaritifera from GenBank [22, 46] and Gomes-dos-Santos et al. [18] (the latter used the same M. margaritifera individual used for the genome assembly of this study) was retrieved and quality trimmed with Trimmomatic v.0.38 (parameters described above). Next, the clean reads were aligned to the masked genome using Hisat2 (v.2.2.0; RRID:SCR_015530) with the default parameters [47]. Furthermore, the complete proteomes of 14 mollusc species and three reference Metazoan species (Homo sapiens, Ciona intestinalis, Strongylocentrotus purpuratus), downloaded from public databases (Table 3), were used as additional evidence for gene prediction. The BRAKER2 pipeline was then applied, specifying the parameters “–etpmode; –softmasking;”. Gene predictions were renamed (Mma), cleaned, and filtered using AGAT v.0.8.0 [48], correcting overlapping predictions and removing incomplete gene predictions (i.e., without start and/or stop codons). Finally, proteins were extracted from the genome using AGAT, and a functional annotation was performed using InterProScan (v.5.44.80; RRID:SCR_005829) [49] and BLASTP (RRID:SCR_001010) searches against the RefSeq database [50]. Homology searches were performed using DIAMOND (v.2.0.11.149; RRID:SCR_016071) [51], specifying the parameters “–k 1, –b 20, –e 1e-5, –sensitive, –outfmt 6”. Finally, BUSCO scores were estimated for the predicted proteins [39].

Table 3.

List of the proteomes used for the BRAKER2 gene prediction pipeline.

Phylum Class Order Species GenBank/RefSeq
Mollusca Bivalvia
Ostreida Crassostrea gigas GCF_902806645.1
Crassostrea virginica GCF_002022765.2
Pectinida Mizuhopecten yessoensis GCF_000457365.1
Pecten maximus GCF_902652985.1
Veneroida Dreissena polymorpha GCF_020536995.1
Mercenaria mercenaria GCF_014805675.1
Unionida Margaritifera margaritifera GCA_015947965.1
Megalonaias nervosa GCA_016617855.1
Gastropod Biomphalaria glabrata GCF_000457365.1
Pomacea canaliculata GCF_003073045.1
Gigantopelta aegis GCF_016097555.1
Cephalopod Octopus bimaculoides GCF_001194135.1
Octopus sinensis GCF_006345805.1
Polyplacophora Acanthopleura granulata GCA_016165875.1
Chordata Homo sapiens GCF_000001405.40
Chordata Ciona intestinalis GCF_000224145.3
Echinodermata     Strongylocentrotus purpuratus GCF_000002235.4
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Data validation

Sequencing results and genome assembly

The raw sequencing outputs resulted in 103 Gbp of raw PacBio and 203 Gbp of raw paired-end reads. A total of 201 Gbp of paired-end reads were maintained after trimming and quality filtering. Similarly to the results of Gomes-dos-Santos et al. [13], the GenomeScope2 estimated genome size was ∼2.36 Gb, and the heterozygosity levels were low, i.e., ∼0.163% (Figure 3a).

Figure 3.

Figure 3.

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(a) GenomeScope2 k-mer () distribution displaying the estimation of the genome size (len), the homozygosity (aa), the heterozygosity (ab), the mean coverage of k-mer for heterozygous bases (kcov), the read error rate (err), the average rate of read duplications (dup), the size of the k-mer used on the run (k), the ploidy (p), and percentage of the genome that is unique (not repetitive) (uniq). (b) M. margaritifera genome assembly assessment using the KAT comp tool to compare the Illumina paired-end k-mer content within the genome assembly. Different colours represent the read k-mer frequency in the assembly.

The final genome assembly (hereafter referred to as Genome V2) has a total size of 2.45 Gbp, similar to the genome size reported in a previous assembly [13] (hereafter referred to as Genome V1). Regarding the contiguity, Genome V2 shows a contig N50 of 3.42 Mbp (Table 4), representing a ∼202-fold increase in contig N50 and ∼11-fold increase in scaffold N50 relative to Genome V1 (Table 4). Additionally, Genome V2 represents the most contiguous freshwater mussel genome assembly currently available [13, 26, 52, 53]. Genome V2 shows a ∼1.66-fold increase in N50 length compared to the other PacBio-based genome assembly, i.e., from P. streckersoni [26]. This observation is striking considering that the Genome V2 is larger (nearly 4 Mbp longer), has more repetitive elements (nearly 7% more) (Tables 4 and 5) and similar heterozygosity (nearly 0.43% less) (Figure 3).

Table 4.

General statistics of the two M. margaritifera genome assemblies, including read alignment, gene prediction, and annotation.

Genome V2 contig* Genome V1 contig Genome V1 scaffold Megalonaias nervosa Potamilus streckersoni Venustaconcha ellipsiformis
Total number of sequences ≥ 1,000 bp 1,700 265,718 105,185 90,895 2,366 371,427
Total number of sequences ≥ 10,000 bp 1,700 66,019 15,384 54,764 2,162 26,952
Total number of sequences ≥ 25,000 bp 1,202 18,725 11,583 29,042 1,831 5,073
Total number of sequences ≥ 50,000 bp 1,570 4,284 9,265 12,699 1,641 1,456
Total length ≥ 1,000 bp 2.45 Gb 2.2 Gb 2.47 Gb 2.36 Gb 1.77 Gb 1.59 Gb
Total length ≥ 10,000 bp 2.45 Gb 1.52 Gb 2.29 Gb 2.19 Gb 1.77 Gb 0.54 Gb
Total length ≥ 25,000 bp 2.45 Gb 789 Mb 2.23 Gb 1.76 Gb 1.76 Gb 0.23 Gb
Total length ≥ 50,000 bp 2.44 Gb 299 Mb 2.15 Gb 1.19 Gb 1.76 Gb 0.10 Gb
N50 length (bp) 3.42 Mb 16 Kb 288 Kb 50 Kb 2.05 Mb 6,657
L50 207 34,910 2,393 12,463 245 58,531
Largest contig (bp) 23 Mb 0.209 Mb 2.5 Mb 0.588 Mb 10 Mb 313,274
GC content, % 35.3 35.42 35.42 35.82 33.79 34.19
Clean paired-end (PE) Reads Alignment Stats
Percentage of Mapped RNA-seq PE (%) - Average 96.94 - 97.75 - -
Percentage of Mapped WGS PE (%) - 99.69 - 97.75 - -
Total BUSCO for the genome assembly (%)
#Euk database - C:99.2% [S:97.6%, D:1.6%], F:0.4% - C:86.8% [S:85.8%, D:1.0%], F:5.9% C:70.6% [S:70.2%, D:0.4%], F:14.9% C:98.1% [S:97.3%, D:0.8%], F:0.8% C:45.9% [S:45.5%, D:0.4%], F:36.9%
#Met database - C:96.9% [S:95.5%, D:1.4%], F:2.0% - C:84.9% [S:83.8%, D:1.1%], F:4.9% C:71.5% [S:70.1%, D:1.4%], F:14.5% C:95.0% [S:93.6%, D:1.4%], F:2.3% C:53.7% [S:52.8%, D:0.9%], F:29.7%
Masking Repetitive Regions and Gene Prediction
Percentage masked bases (%) - 57.32 - 59.07 25.00 51.03 36.29
Number of mRNAs - 48,314 - 40,544 49,149 41,065 41,697
Protein coding genes (CDS) - 48,314 - 35,119 49,149 41,065 -
Functional annotated genes 35,649 - 31,584 - - -
Total gene length (bp) - 1.13 Gb - 902 Mb - - -
Total BUSCO for the predicted proteins (%)
+ Euk database - C:97.6% [S:83.9%, D:13.7%], F:2.0% - C:90.6% (S:81.2%, D:9.4%), F:3.9% - - -
+ Met database - C:98.7% [S:84.7%, D:14.0%], F:0.8% - C:92.6% (S:82.3%, D:10.3%), F:3.2% - - -
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*Genome V2 refers to the new assembly here produced and is solely at the contig level, i.e., has no scaffolds; Genome V1 refers to the first M. margaritifera genome [13]; #Euk: From a total of 303 genes of Eukaryota library profile; #Met: From a total of 978 genes of Metazoa library profile; + Euk: From a total of 255 genes of Eukaryota library profile; + Met: From a total of 954 genes of Metazoa library profile; #,+ C: Complete; S: Single; D: Duplicated; F: Fragmented.

Table 5.

RepeatMasker report of the content of repetitive elements in the new M. margaritifera genome assembly.

Number of elements Length occupies Percentage of sequence
SINEs: 99,204 18,473,640 bp 0.75%
ALUs 0 0 bp 0.00%
MIRs 48,204 8,371,356 bp 0.34%
LINEs: 345,367 143,734,167 bp 5.86%
LINE1 12,130 3,357,131 bp 0.14%
LINE2 100,340 30,227,268 bp 1.23%
L3/CR1 8,437 3,557,603 bp 0.14%
LTR elements: 211,377 145,957,516 bp 5.95%
ERVL 6 360 bp 0.00%
ERVL-MaLRs 0 0 bp 0.00%
ERV_classI 19,402 1,295,486 bp 0.05%
ERV_classII 5,672 1,603,072 bp 0.07%
DNA elements: 1,603,010 421,567,495 bp 17.18%
hAT-Charlie 32,085 3,719,809 bp 0.15%
TcMar-Tigger 52,635 2,0922,832 bp 0.85%
Unclassified: 2,158,454 668,949,483 bp 27.26%
Total interspersed repeats:
Small RNA: 52,314 10,622,911 bp 0.43%
Satellites: 15,462 4,216,424 bp 0.17%
Simple repeats: 40,358 10,377,834 bp 0.42%
Low complexity:   149 24,863 bp 0.00%
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Genome V2 also shows a considerable increase in the BUSCO scores, with nearly no fragmented nor missing hits for both the eukaryotic and metazoan curated lists of near-universal single-copy orthologous genes (Table 4). Short-read back-mapping percentages resulted in an almost complete read mapping and a 99.69% alignment rate (Table 4). The KAT k-mer distribution spectrum revealed that almost all read information was included in the final assembly (Figure 3b). Overall, these general statistics validate the high completeness, low redundancy, and quality of the Genome V2.

Repeat masking, gene models prediction, and annotation

RepeatModeler/RepeatMasker masked 57.32% of Genome V2, 1.75% less than the values reported for Genome V1. This result was likely a consequence of the new assembly being able to resolve repetitive regions more accurately (Table 5). Furthermore, this value was considerably higher than the estimated duplications of GenomeScope, i.e., 36.2% (Figure 3a, Table 5). These differences have been observed in other assemblies of freshwater mussel genomes [4, 26, 52] and are likely due to the inaccurate estimation of repeat content when applying k-mer frequency spectrum analysis in highly repetitive genomes using short reads. Similarly to Genome V1, most repeats in Genome V2 were unclassified (27.26%, ∼668 Mgp), followed by DNA elements (17.18%, ∼421 Mgp), long terminal repeats (5.95%, ∼145 Mgp), long interspersed nuclear elements (5.86%, ∼143 Mgp), and short interspersed nuclear elements (0.75%, ∼18 Mgp) (Table 5). BRAKER2 gene prediction identified 48,314 CDS, an increase compared with Genome V1 and closer to the predictions of the other two freshwater mussel assemblies (Tables 4 and 6). This result probably reflects the higher contiguity and completeness of Genome V2, as evidenced by the high BUSCO scores for protein predictions, with almost no missing hits for either of the near-universal single-copy orthologous databases used (Table 3). The number of functionally annotated genes was also higher than those of Genome V1, with 4,065 additional genes annotated (Tables 4, 6 and 7). Overall, the numbers of both predicted and annotated genes are within the expected range for bivalves (reviewed in [4]), as well as within the records of other freshwater mussel assemblies [26, 53].

Table 6.

Structural annotation report of the new M. margaritifera genome assembly.

Structural annotation Number
Number of genes 40,165
Number of mRNAs 48,314
Number of CDSs 48,314
Number of exons 328,489
Number of introns 280,173
Number of start_codons 48,314
Number of stop_codons 48,314
Number of exons in CDSs 328,489
Number of introns in CDSs 280,175
Number of introns in exon 280,175
Number of introns in intron 240,261
Number gene overlapping 440
Number of single exon gene 8,092
Number of single exon mRNAs 8,402
Mean mRNAs per gene 1.2
Mean CDSs per mRNA 1.0
Mean exons per mRNA 6.8
Mean introns per mRNA 5.8
Mean exons per CDS 6.8
Mean introns in CDSs per mRNA 5.8
Mean introns in exons per mRNA 5.8
Mean introns in introns per mRNA 5.0
Total gene length 1,134,996,674
Total mRNA length 1,399,972,668
Total CDS length 65,168,232
Total exon length 65,168,232
Total intron length 1,334,804,372
Total start_codon length 144,942
Total stop_codon length 144,942
Total intron length per CDS 1,334,804,436
Total intron length per exon 1,334,804,436
Total intron length per intron 38,816,274
Mean gene length 28,258
Mean mRNA length 28,976
Mean CDS length 1,348
Mean exon length 198
Mean intron length 4,764
Mean CDS piece length 198
Mean intron in CDS length 4,764
Mean intron in exon length 4,764
Mean intron in intron length 161
Longest gene 492,278
Longest mRNA 492,278
Longest CDS 50,892
Longest exon 14,931
Longest intron 270,677
Longest CDS piece 14,931
Longest intron into CDS part 270,677
Longest intron into exon part 270,677
Longest intron into intron part 14,931
Shortest gene 123
Shortest mRNA 123
Shortest CDS 9
Shortest exon 3
Shortest intron 33
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Table 7.

Functional annotation report of M. margaritifera genome assembly.

Functional annotation Number
Swissprot/RefSeq 21,050
CDD 11,151
Coils 7,148
GO 18,024
Gene3D 23,613
Hamap 383
InterPro 29,030
KEGG 1,495
MetaCyc 1,445
MobiDBLite 12,555
PIRSF 973
PRINTS 5,250
Pfam 25,322
ProSitePatterns 6,471
ProSiteProfiles 15,115
Reactome 5,837
SFLD 110
SMART 12,494
SUPERFAMILY 23,283
TIGRFAM 1,148
Total 34,137
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Conclusion

In this report, a new and highly improved genome assembly for the freshwater pearl mussel is presented. This genome assembly, produced using PacBio long-read sequencing, significantly improves contiguity without scaffolding. Unlike other freshwater mussels’ genomes, the one presented here has not been scaffolded (i.e., it has no gaps of undetermined size), thus representing an ideal framework to employ chromosome anchoring approaches, such as Hi-C sequencing. This new genome represents a key resource to start exploring the many biological, ecological, and evolutionary features of this highly threatened group of organisms, for which the availability of genomic resources still falls far behind other molluscs.

Acknowledgements

The authors thank the two reviewers for the helpful remarks and suggestions, which have significantly improved the manuscript.

Funding Statement

AGS was funded by the Portuguese Foundation for Science and Technology (FCT) under the grant SFRH/BD/137935/2018 and COVID/DB/152933/2022, which also supported MLL (2020.03608.CEECIND) and EF (CEECINST/00027/2021). This research was developed under the project EdgeOmics - Freshwater Bivalves at the Edge: Adaptation genomics under climate-change scenarios (PTDC/CTA-AMB/3065/2020) funded by FCT through national funds. Additional strategic funding was provided by FCT UIDB/04423/2020 and UIDP/04423/2020.

Data Availability

All software with respective versions and parameters used for producing the resources presented here (i.e., transcriptome assembly, pre- and post-assembly processing stages, and transcriptome annotation) are listed in the methods section. Software programs with no parameters associated were used with the default settings.

The raw sequencing reads were deposited at the National Center for Biotechnology Information (NCBI) Sequence Read Archive with the accession numbers SRR23176563 (Illumina PE) and SRR23176561 (PacBio CLR). The new genome assembly is also available on NCBI under the accession number JAQPZY000000000. The BioSample accession number is SAMN32798282, and the BioProject one is PRJNA925505. All the remaining data has been uploaded to figshare [54], including the final unmasked and masked genome assemblies (Mma.fa and Mma_SM.fa), the annotation file (Mma_annotation_v1.gff3), the predicted genes (Mma_genes_v1.fasta), the predicted messenger RNA (Mma_mrna_v1.fasta), the predicted open reading frames (Mma_cds_v1.fasta), the predicted proteins (Mma_proteins_v1.fasta), as well as the full table reports for the Braker gene predictions, the InterProScan functional annotations (Mma_annotation_v1_InterPro_report.txt), and the RepeatMasker predictions (Mma_annotation_v1_RepeatMasker.tbl). Data supporting this work are openly available in the GigaDB repository [55].

List of abbreviations

AGAT: Another Gtf/Gff Analysis Toolkit; BUSCO: Benchmarking Universal Single-Copy Ortholog; BWA: Burrows-Wheeler Aligner; CDS: Coding sequences; KAT: K-mer analyses toolkit; NCBI: National Center for Biotechnology Information; PacBio: Pacific Biosciences; PE: paired-end; QUAST: Quality Assessment Tool for Genome Assemblies; SMRT: Single Molecule, Real-Time; WGS: whole genome sequencing.

Declarations

Ethical approval

This work has been approved by the CIIMAR ethical committee and by CIIMAR Managing Animal Welfare Body (ORBEA) according to the European Union Directive 2010/63/EU.

Competing Interests

The authors declare that they have no competing interests.

Authors’ contributions

EF, MLL, and LFCC designed and conceived this work. MLL, VP, and AT were responsible for the field sampling. AGS and AMM carried out the bioinformatics analyses. LFCC, EF, GA, and TF revised the bioinformatics analyses. AGS and EF wrote the first version of the manuscript. All authors read, revised, and approved the final manuscript.

Funding

AGS was funded by the Portuguese Foundation for Science and Technology (FCT) under the grant SFRH/BD/137935/2018 and COVID/DB/152933/2022, which also supported MLL (2020.03608.CEECIND) and EF (CEECINST/00027/2021). This research was developed under the project EdgeOmics - Freshwater Bivalves at the Edge: Adaptation genomics under climate-change scenarios (PTDC/CTA-AMB/3065/2020) funded by FCT through national funds. Additional strategic funding was provided by FCT UIDB/04423/2020 and UIDP/04423/2020.

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Reviewer name and names of any other individual's who aided in reviewer Jin Sun
Do you understand and agree to our policy of having open and named reviews, and having your review included with the published papers. (If no, please inform the editor that you cannot review this manuscript.) Yes
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Please add additional comments on language quality to clarify if needed
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Are the data and metadata consistent with relevant minimum information or reporting standards? See GigaDB checklists for examples <a href="http://gigadb.org/site/guide" target="_blank">http://gigadb.org/site/guide</a> Yes
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Is the data acquisition clear, complete and methodologically sound? Yes
Additional Comments
Is there sufficient detail in the methods and data-processing steps to allow reproduction? Yes
Additional Comments
Is there sufficient data validation and statistical analyses of data quality? Yes
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Is the validation suitable for this type of data? Yes
Additional Comments
Is there sufficient information for others to reuse this dataset or integrate it with other data? No
Additional Comments
Any Additional Overall Comments to the Author Gomes-dos-Santos et al., have upgraded the freshwater mussel Margaritifera margaritifera genome with the usage of long-read sequencing. Overall, this version has been dramatically improved compared to the former one, with the increased N50 value and BUSCO score and decreased No. of contigs. Considering the important economic value of M. margaritifera and the high quality of assembly, I must congratulate the authors on this. However, in contrast to the high-quality assembly, I am a bit aware of the genome annotation part. To me, the number of gene models predicted is a bit higher compared with other molluscan genomes. This can also be reflected by the low proportion of gene models that can be annotated by Swissprot or GO etc. I suspect that the high number of gene models could be the consequence that only the ab initio evidence was applied in the current study. More sophisticated ways, such as EVM or maker, shall be used to see whether the number of gene models can be reduced without sacrificing the BUSCO scores on the gene models. Line 76, The official name shall be “Oxford Nanopore Technology (ONT)”. Fig. 1, it is interesting to see the wide distribution of M. margaritifera. I am a bit interested to know whether there are any genetic differentiations between the European population and the North American population.
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Do you understand and agree to our policy of having open and named reviews, and having your review included with the published papers. (If no, please inform the editor that you cannot review this manuscript.) Yes
Is the language of sufficient quality? Yes
Please add additional comments on language quality to clarify if needed
Are all data available and do they match the descriptions in the paper? Yes
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Are the data and metadata consistent with relevant minimum information or reporting standards? See GigaDB checklists for examples <a href="http://gigadb.org/site/guide" target="_blank">http://gigadb.org/site/guide</a> Yes
Additional Comments
Is the data acquisition clear, complete and methodologically sound? Yes
Additional Comments
Is there sufficient detail in the methods and data-processing steps to allow reproduction? Yes
Additional Comments All methods seem standard and high quality for a genome release.
Is there sufficient data validation and statistical analyses of data quality? Yes
Additional Comments If the authors could add a table comparing with other Unio genomes, that might be helpful. Gene numbers, busco scores, N50s, and other relevant stats. It will help readers see the value of this more contiguous genome -V. ellipsiforma (Renaut et al.) -M nervosa -P. streckersonii
Is the validation suitable for this type of data? Yes
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Is there sufficient information for others to reuse this dataset or integrate it with other data? Yes
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Comments to the Author Please check the referencing and figures carefully.
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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Availability Statement

    All software with respective versions and parameters used for producing the resources presented here (i.e., transcriptome assembly, pre- and post-assembly processing stages, and transcriptome annotation) are listed in the methods section. Software programs with no parameters associated were used with the default settings.

    The raw sequencing reads were deposited at the National Center for Biotechnology Information (NCBI) Sequence Read Archive with the accession numbers SRR23176563 (Illumina PE) and SRR23176561 (PacBio CLR). The new genome assembly is also available on NCBI under the accession number JAQPZY000000000. The BioSample accession number is SAMN32798282, and the BioProject one is PRJNA925505. All the remaining data has been uploaded to figshare [54], including the final unmasked and masked genome assemblies (Mma.fa and Mma_SM.fa), the annotation file (Mma_annotation_v1.gff3), the predicted genes (Mma_genes_v1.fasta), the predicted messenger RNA (Mma_mrna_v1.fasta), the predicted open reading frames (Mma_cds_v1.fasta), the predicted proteins (Mma_proteins_v1.fasta), as well as the full table reports for the Braker gene predictions, the InterProScan functional annotations (Mma_annotation_v1_InterPro_report.txt), and the RepeatMasker predictions (Mma_annotation_v1_RepeatMasker.tbl). Data supporting this work are openly available in the GigaDB repository [55].

    Articles from GigaByte are provided here courtesy of Gigascience Press

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