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. 2013 Nov 1;3:95–103. doi: 10.1016/j.rinim.2013.10.001

Transcriptome analysis of neoplastic hemocytes in soft-shell clams Mya arenaria: Focus on cell cycle molecular mechanism☆

Ahmed Siah a,b,*, Patty McKenna b, Franck CJ Berthe c, Luis OB Afonso d, Jean-Michel Danger e
PMCID: PMC3908331  PMID: 24600564

Abstract

In North America, a high mortality of soft-shell clams Mya arenaria was found to be related to the disease known as disseminated neoplasia (DN). Disseminated neoplasia is commonly recognized as a tetraploid disorder related to a disruption of the cell cycle. However, the molecular mechanisms by which hemocytes of clams are transformed in the course of DN remain by far unknown. This study aims at identifying the transcripts related to DN in soft shell clams’ hemocytes using next generation of sequencing (Illumina HiSeq2000). This study mainly focuses on transcripts and molecular mechanisms involved in cell cycle. Using Illumina next generation of sequencing, more than 95,399,159 reads count with an average length of 45  bp was generated from three groups of hemocytes: (1) a healthy group with less than 10% of tetraploid cells; (2) an intermediate group with tetraploid hemocytes ranging between 10% and 50% and (3) a diseased group with more than 50% of tetraploid cells. After the reads were cleaned by removing the adapters, de novo assembly was performed on the sequences and more than 73,696 contigs were generated with a mean contig length estimated at 585 bp ranging from 189 bp to 14,773 bp. Once a Blastx search against NCBI Non Redundant database was performed and the duplicates removed, 18,378 annotated sequences matched known sequences, 3078 were hypothetical and 9002 were uncharacterized sequences. Fifty percent and 41% of known sequences match sequences from Mollusca and Gastropoda respectively. Among the bivalvia, 33%, 17%, 17% and 15% of the contigs match sequences from Ostreoida, Veneroida, Pectinoida and Mytiloida respectively. Gene ontology analysis showed that metabolic, cellular, transport, cell communication and cell cycle represent 33%, 15%, 9%, 8.5% and 7% respectively of the total biological process. Approximately 70% of the component process is related to intracellular process and 15% is linked to protein and ribonucleoprotein complex. Catalytic activities and binding molecular processes represent 39% and 33% of the total molecular functions. Interestingly, nucleic acid binding represents more than 18% of the total protein class. Transcripts involved in the molecular mechanisms of cell cycle are discussed providing new avenues for future investigations.

Keywords: Transcriptomic, Neoplasia, Tetraploidy, Mya arenaria, Cell cycle, Molecular mechanisms

1. Introduction

Disseminated neoplasia (DN) is defined as a leukemia-like disease affecting hemocytes of soft-shell clams. This disease is mainly characterized by a high number of circulating hemocytes containing pleomorphic nuclei with a high nucleus–cytoplasm ratio [1,2]. These abnormal circulating cells lose their function of phagocytosis [3] and exhibit higher DNA contents and mitosis rates than normal cells resulting in the formation of tetraploid cells [4,5]. During normal cell cycle, chromosomes segregate only when an adequate kinetochore-microtubule attachment exists enabling cells to pass the spindle assembly checkpoint [6]. However, after prolonged arrest at the spindle assembly checkpoint that promotes cytokinesis failure, cells become tetraploid [7].

The etiology of DN in Mya arenaria remains unknown although several factors such as retrovirus infection or contamination seem to contribute to the development of the disease. Retroviral infection was shown as the main factor [8] of DN development; however, other studies did not succeed in detecting retroviral components in diseased clams [9]. In addition, studies stipulate that environmental contamination by pesticides could be the main cause of DN in soft shell clams collected from Prince Edward Island [10,11].

Many studies have investigated the molecular mechanisms involved in the development of the disease [12–18]. For instance, some studies have shown that the proliferation of hemocytes in clams is due to the sequestration of p53 by mortalin [13,14], whereas other studies demonstrated that p53's pathways were disrupted by the activation of the Mouse Double Minute 2 (MDM2) proto-oncogene [15]. Our recent investigation using subtractive suppressive hybridization techniques suggested the involvement of proto-oncogene such as RAS like protein members, c-myc and c-jun in the development of DN [17]. It was hypothesized that the proto-oncogenes were regulated by the presence of transposase whose gene expression was increased in tetraploid hemocytes [16]. Briefly, although several studies have been initiated, the molecular mechanisms by which hemocytes become neoplastic are still to be unravelled. Unfortunately, little is known on the transcriptome of soft shell clams. Only few sequences are available in GenBank represented mainly by Map53 (Acc# AF253323.1), Map73 (Acc# AF253324.1), and mortalin (Acc # EF576660).

The development of the new generation of sequencing technologies represents a great opportunity to increase the number of transcript sequences and would provide a basis platform for molecular mechanisms studies involved in DN in soft shell clams.

Thus, this study aims at increasing the numbers of transcript sequences in hemocytes of soft shell clams affected by DN. Our approach focused specifically on sequencing mRNA isolated from different groups of hemocytes characterized by their tetraploid status. The sequences generated in this study will constitute a baseline in unravelling the molecular pathway(s) involved in DN as well as a source of potential target transcripts which could be involved in hemocytes' immune system of soft shell clams, M. arenaria.

2. Materials and methods

2.1. Sampling

Approximately 5-cm-long specimens of M. arenaria were collected at low tide at a depth of 15–20 cm using a hand rake from May to November 2011 in North River (46°15′10″N, 63°10′42″W) (Charlottetown, Prince Edward Island, Canada). Clams were washed with seawater and transported to the Atlantic Veterinary College at the University of Prince Edward Island for further analysis.

2.2. Flow cytometry

Flow cytometric (FCM) analysis was used to assess the ploidy status of M. arenaria's haemocytes according to the methods described by Delaporte et al. [5]. This technique enables the screening of cell populations for DNA content. The protocol is based on the binding properties of propidium iodide (PI), which stains by intercalating into DNA strands. The PI fluorescence intensity is proportional to the DNA content in the cell. Briefly, hemolymph (500 μL) was withdrawn from individual clams using a 3 mL syringe fitted with a 25-gauge needle. Haemocytes were fixed in 2.5 mL of cold absolute ethanol and stored at −20 °C for at least 30  min. Fixed cells were centrifuged (400g for 10 min at room temperature), and the supernatant was discarded. Haemocyte pellets were re-suspended in 0.01 M phosphate-buffered saline (PBS) and the cells were allowed to re-hydrate for 30 min at room temperature. After two washes in PBS (400g for 10 min at room temperature), cells were re-suspended in 380 μL of PBS solution and transferred to flow cytometer tubes by filtering through an 80 μm nylon mesh. Propidium iodide (50 μg mL−1) and DNAse-Free RNase A (50 μg mL−1) were added to each tube before the mixtures were incubated in the dark until optimal PI staining for 30 min. PI fluorescence, which is related to the DNA content of each cell, was detected on the orange photomultiplicator of a FACSCalibur flow cytometer (BD Biosciences) at a wavelength ranging between 550 and 600 nm. For each sample, 10,000 particles were counted at low flow rate (15 μL min−1). For each cell event, a single pulse of PI fluorescence was represented according to its area and width. The pulse width needs to be compared with the pulse area in order to discriminate the cells in the phase G2/M from doublets of G0/G1 cells represented by the same DNA quantity. To gate single haemocytes, PI fluorescence intensities were plotted as a FL2-area vs. FL2- width dot-plot. The region R1 was drawn in order to discriminate single cells from the doublets. The single cells gated in R1 were plotted on a FL2-area histogram and used to estimate the percentage of normal and tetraploid haemocytes in the analyzed cell population. Results are presented as the percentage of tetraploid haemocytes per clam. Three different classes of clams were distinguished according to the percentage of tetraploid hemocytes.

2.3. RNA extraction

Based on their tetraploid status, 3 groups of clams were selected: (1) Group C (healthy clams considered as control) with a low percentage of tetraploid hemocytes (<10%); Group D (disease in development): individuals presenting a percentage of tetraploid cells ranging between 10% and 50%; and Group E (established disease): clams with a high percentage of tetraploid hemocytes (>50%). Hemolymph (2 mL) was withdrawn from individual clams using a 3 mL syringe fitted with a 25-gauge needle. Hemolymph was centrifuged at 400g for 15 min at 4 °C in order to isolate hemocytes from the serum. Total RNAs were extracted from hemocytes using RNeasy purification kit (Qiagen, USA), treated with DNaseI and the quality of RNA was analyzed using the bioanalyser Experion (Biorad, Canada). RNA concentrations were analyzed using a Nanodrop (ND 1000, USA) spectrophotometer.

Samples with high quality (RNA quality index higher or equal at 8) and concentration higher than 100 ng mL−1 was selected. Based on these criteria, 6 samples were pooled for the group C (0–10%), 7 samples for the group D (10–50%) and 3 samples for the group E (>50%).

2.4. Library preparation and sequencing

Library preparation and next generation of sequencing were carried out by Eurofin (Alabama, US). Three individual libraries (one from each group) were prepared with NuGEN Ovation RNA-Seq system V2 according to the manufacturer's recommendations. NuGEN Ovation RNA-Seq system V2 corresponds to three main steps: first strand cDNA synthesis, second strand cDNA synthesis and purification and SPIA amplification and purification. Briefly, First Strand Primer Mix was mixed to RNA (100 ng). The mixture was warmed at 65° C for 5 min. First Strand Master Mix (3 mL) was added to each tube and placed in a thermal cycler at 4 ° C for 1 min, 25 °C for 10 min, 42 °C for 10 min, and 70 °C for 15 min. Second Strand Master Mix (10 mL) was added to each First Strand reaction tube. The mixture was added and placed in a thermal cycler at 4 °C for 1 min, 25 °C for 10 min, 50 °C for 30 min, and 80 °C for 20 min. Second strand cDNA was purified using Agencourt RNAClean XP purification beads provided with a NuGEN Ovation RNA-Seq system V2 kit. Finally, SPIA Master Mix (40 μL) was added to each tube containing the double-stranded cDNA bound to the dried beads and placed in a thermo cycler at 4 °C for 1 min, 47 °C for 60 min, and 80 °C for 20 min. SPIA cDNA was purified using QIAGEN MinElute Reaction Cleanup Kit (Qiagen, USA). SPIA cDNA was sequenced on Illumina HiSeq2000 with 2 × 50 bp according to the manufacturer's recommendations.

2.5. Sequence analysis and bioinformatics

Reads generated from Illumina HiSeq2000 sequencing were assembled using the CLC Genomics Workbench software v5.5. Adaptors and primer sequences were trimmed as well as low quality and duplicates removed. De novo sequence assembly was performed using de Bruijn graphs as described in [19–21]. The generated contigs and isotigs were blasted against NCBI Non-Redundant database including Swissprot, Metazoan Refseq and UniprotKB/Trembl protein databases using the GenomeQuest bioinformatic platform (US) with a cut-off of 10−6. Gene ontology searches were performed using the Panther Pathway [22]. Sequences were submitted to BLAST comparison against the KEGG GENES database to obtain KO (KEGG Orthology) assignments and to generate KEGG pathways. The threshold >60 was applied to BLAST bit scores. Reads per kilobase per million mapped reads (RPKM) were quantified from the three groups. Ratio to the healthy group C were calculated for group D and group E. Data are reported in a histogram representing Log2 RPKM ratio.

3. Results and discussion

3.1. De novo assembly

The tetraploid status of hemocytes has been screened using flow cytometry. Three groups of hemocytes were determined: Group C, a healthy group with less than 10% of tetraploid cells; Group D, an intermediate group with tetraploid hemocytes ranging between 10% and 50% and group E, a diseased group with more than 50% of tetraploid cells. More than 95,399,159 reads count were generated from the three groups with an average length of 45 bp.

The bioinformatic analysis of the sequences was performed using the CLC Genomics Workbench software v5.5. The adaptors and primers were trimmed; in addition, duplicates and low quality sequences were removed from the data set. Upon cleaning, de novo assembly was performed on the sequences using de Bruijn graphs. More than 73,696 contigs were generated with a mean contig length estimated at 585 bp ranging from 189 bp to 14,773 bp. More than 90.3% of the contigs (66,612 sequences) had a length ranging from 189 to 1268 bp and less than 9.7% were longer than 1268 bp (Fig. 1).

Fig. 1.

Fig. 1

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Contigs length distribution after de novo assembly.

The emergence of the next generation of sequencing has dramatically increased the knowledge and information on bacteria, invertebrate and vertebrate organisms' transcriptome. Although the number of Expressed Sequence Tags (ESTs) has increased during the last decade, the knowledge on mollusk bivalvia in particular M. arenaria is still limited. GenBank database contains only 248,489 nucleotides and 373,300 ESTs related to Bivalvia (4/15/2013). Ostreoida and Mytiloida represent the most representative groups with 223,017 (59.7%) and 71,328 (19.1%) ESTs respectively. Among the Ostreoida, Crassostrea is the main representative group with 222,785 (99.9%) ESTs and Mytilus have been mainly sequenced in the Mytiloida family with 67,990 (95.3%). Unfortunately, the number of ESTs related to M. arenaria is very poor with 100 entries represented mainly by cytochrome oxidase, microsatellite and ribosomal RNA. Among the 100 entries, only 10 transcripts have been recorded in GenBank (4/15/2013) represented by M. arenaria p53 tumor suppressor homolog (Myap53) mRNA, partial cds (U45237.1); M. arenaria voltage-dependent sodium channel mRNA, partial cds (AY847740.1); M. arenaria p73-like protein mRNA, complete cds (AF253324.1); M. arenaria E3 ubiquitin-protein ligase mRNA, complete cds (AF154109.2); M. arenaria aryl hydrocarbon receptor-like protein mRNA, complete cds (AF261769.1); M. arenaria p53 tumor suppressor-like protein mRNA, complete cds (AF253323.1); M. arenaria ribosomal protein S19 (S19) mRNA, complete cds (U63092.1); M. arenaria mitochondrial mortalin-2 precursor (Mot-2) mRNA, complete cds, nuclear gene for mitochondrial product (AY326398.2); M. arenaria mitochondrial mortalin splice variant mRNA, complete cds, alternatively spliced, nuclear gene for mitochondrial product (EF576660.1); and M. arenaria Rack1 gene for Receptor of Activated Kinase C 1 (AM404081.1). Most of the messengers cited above are related to the p53-like molecular mechanisms involved in DN in soft shell clams M. arenaria [12,23,24]. However, the number of sequences remains by far unrepresentative of M. arenaria's transcriptome, which therefore makes it difficult to understand the molecular mechanisms by which hemocytes become neoplastic. This study attempts to populate M. arenaria's sequence database in particular in the field of clams’ pathology such as disseminated neoplasia. These sequences could be used in studies interested in molecular mechanisms involved in disseminated neoplasia but also in ecotoxicogenomics where M. arenaria is used as a sentinel species for biosurveillance programmes.

3.2. Annotation

A Blastx search was performed against NCBI Non Redundant database including Swissprot, Metazoan Refseq and UniprotKB/Trembl protein databases. The GenomeQuest bioinformatic platform was used for the Blastx search and a cut-off of 10−6 was applied for the analysis. Once the duplicates were removed, 18,378 annotated sequences matched known sequences, 3078 were hypothetical and 9002 were uncharacterized sequences. Eighty-five percent of the annotated sequences are among eukaryote identities (Fig. 2A) with 18% and 5% linked to arthropoda and mollusca phylla (Fig. 2B).

Fig. 2.

Fig. 2

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Phylogenetic distribution of the best hit in animal kingdom (A) and eukaryota (B) based on BlastX search in the NCBI nr database.

Data showed that 50% and 41% of known sequences match with sequences from Mollusca and Gastropoda respectively (Fig. 3A). Among the bivalvia, 33%, 17%, 17% and 15% of the contigs match sequences from Ostreoida, Veneroida, Pectinoida and Mytiloida respectively (Fig. 3B).

Fig. 3.

Fig. 3

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Species distribution based on BlastX alignment in Bivalvia (A) and Mollusca (B) NCBI nr database.

3.3. Gene ontology

Gene ontology analysis showed that metabolic, cellular, transport, cell communication and cell cycle represent 33%, 15%, 9%, 8.5% and 7% of the total biological process respectively (Fig. 4A). The majority (around 70%) of the component process is related to intracellular processes and approximately 15% linked to protein and ribonucleoprotein complex respectively (Fig. 4B). Catalytic activities and binding molecular processes represent 39% and 33% of the total molecular functions respectively (Fig. 4C). Interestingly, nucleic acid binding represents more than 18% of the total protein class (Fig. 5).

Fig. 4.

Fig. 4

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Percentage representation of gene ontology mapping (A) biological processes, (B) cellular component and (C) molecular functions.

Fig. 5.

Fig. 5

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Distribution of best hits annotated protein class based on the BlastX alignment and gene ontology mapping.

3.4. Gene expression and cell cycle

Tetraploid cells with double DNA quantity can lead to tumorgenesis under a non-functional p53 gene [25]. Several studies have shown the link between the increase of tetraploid tumor cells and the failure of p53 or downstream gene such as p21 in mammalians [26]. The same observations were described in soft shell clams M. arenaria where p53 function was affected by high level of mortalin in the cytoplasm or high expression of MDM2 [13,15]. The formation of tetraploid cells is a consequence of cell fusion, endoreduplication, cytokinesis failure or mitotic slippage [26]. During the cell cycle, the chromosome segregation is under control of mitotic checkpoint genes .

3.4.1. Transcripts involved in G1– S phase of cell cycle

At the G1 phase also known as the growth phase which corresponds to a high rate of biosynthesis, the CDK4,6 like proteins were identified in our database. CDK4,6 linked to cyclin D is the first serine-threonine kinases activated during the cell cycle. CDK4,6-cyclin D complex under proliferative signal activation allow the cell to enter the cell cycle at its first G1 phase [27]. Once activated, CDK4,6-Cyclin D initiates a sequential activation of downstream of cyclin E-CDK2, which regulates the G1–S transition and centrosome duplication. In our study, cyclin D2 and cyclin E transcripts were 4.6 and 3.8 times respectively higher than the control during the development phase of the disease (Fig. 6). Once the disease was established, the expression level of cyclin D2 and E was 2.3 and 2.5 higher than the control respectively. The regulation of centrosome duplication is key in the regulation of chromosome segregation. Several types of cancer were found to be related to centrosome amplification triggering aneuploidy [28]. It was shown that cyclin E-CDK2 complex is a key regulator in centrosome duplication and DNA replication [29]. It was demonstrated that cyclin E can bind the centrosome using the centrosomal localization signal (CLS) and then initiate the S-phase of the cell cycle [30]. In addition, CLS domain allows cyclin E to bind the minimichrosome maintenance 5 (MCM 5) recognised as a DNA pre-replication complex factor [31]. It was shown that the expression of MCM5 inhibits centrosome amplification in CHO cells arrested in S-phase corroborating the essential role of MCM5 on the centrosome regulation [31]. However, in our study, MCM5 transcript level was similar to the control. Furthermore, our data showed an overexpression of c-myc in groups D and E hemocytes (Fig. 6) corroborating our previous findings [17].

Fig. 6.

Fig. 6

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Expression levels of gene identified in our sequence database during the phase G1–S. Histogram represents Log2 RPKM ratio of group D (disease in development) and E (established disease) to group C (control). GSK3b: glycogen synthase kinase 3 beta; RBL1 (p107): retinoblastoma-like protein 1; E2F4/5: transcription factor E2F4/5; c-Myc: Myc proto-oncogene protein; Miz1: zinc finger and BTB domain-containing protein 17; SMAD 2/3: SMAD 2/3: mothers against decapentaplegic homolog 2/3; SMAD4: mothers against decapentaplegic homolog 4; CycD2: cyclin D2; CDK4: cyclin-dependent kinase 4; CycE: cyclin E; CDK2: cyclin-dependent kinase 2; SCF: S-phase kinase-associated protein 1; RBL2 (p107-p130): retinoblastoma-like protein 2; E2F4/5: transcription factor E2F4/5; and E2F3: transcription factor E2F3.

3.4.2. Transcripts involved in S–G2 phase of cell cycle

In late G1 phase, chromosome duplication is triggered by a specific cdk protein known as S-phase promoting cdks. DNA replication is initiated by the formation of the pre-replicative complex (pre-RC). This complex activity is dependent on the association of Cdc6 with the Origin Recognition Complex (ORC) [32]. Protein kinase such as Dbf4-Cdc7 and Clb5/6(B-cyclin)-Cdc28 phosphorylate and activate proteins within the pre-RC initiating then the DNA replication in phase S [33]. Cdc7 is a serine-threonine kinase which phosphorylates MCM2. MCM2 is a key component of the DNA replicative helicase, which plays a central role in genome duplication. The transcript level of Cdc7 in hemocytes from group D (disease in development) is 19.1 times higher than the control, whereas this level is 5 times higher in diseased hemocytes with a tetraploidy status higher than 50% (Fig. 7). Interestingly, Cdc7 gene and protein are highly expressed in tumor cells including leukemia [34,35]. Several investigations targeted Cdc7 as a cancer therapy by inhibiting Cdc7 expression in cancer cells [36]. In G1–S transition phase, Cdc6 is a key component in DNA replication. Cdc 6 is an ATPase belonging to the AAA family with chaperone like activities as well as a role in transcriptional regulation [37]. As shown for Cdc7, the level of Cdc6 transcript is 8.8 and 3.5 higher in groups D and E respectively (Fig. 7). In cancer cells, overexpression of Cdc6 inhibits expression of p16INKa/p15INKb bot activator of retinoblastoma pathway and a p53 stimulator, ARF [38]. In addition, it was shown that the overexpression of Cdc6 has a synergistic effect with mutant p53 in tumor progression and chromosome instability [39].

Fig. 7.

Fig. 7

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Expression levels of gene identified in our sequence database during the phase S–G2. Histogram represents Log2 RPKM ratio of group D (disease in development) and E (established disease) to group C (control). Cyc H: cyclin H; CycA cyclin A; CDC7 cell division control protein 7; CDC6: cell division control protein 6; ORC5: origin recognition complex subunit 5; ORC3: origin recognition complex subunit 3; ORC2: origin recognition complex subunit 2; ORC1: origin recognition complex subunit 1; MCM4: DNA replication licensing factor; MCM5: DNA replication licensing factor; MCM2: DNA replication licensing factor; MCM6: DNA replication licensing factor; MCM7: DNA replication licensing factor MCM7; MCM3: DNA replication licensing factor; Cdk7: cyclin-dependent kinase 7; CDK2: cyclin-dependent kinase 2; GADD45: growth arrest and DNA-damage-inducible protein; RBL2: retinoblastoma-like protein 2; RBL1: retinoblastoma-like protein 1; Rb: retinoblastoma-associated protein; MDM2: MDM2 Binding Protein; p300: E1A/CREB-binding protein; DNA-PK: DNA-dependent protein kinase catalytic subunit; ATM/ATR: ataxia telangiectasia mutated family protein; Chk1: serine/threonine-protein kinase; CDK1: cyclin-dependent kinase 1; and Wee: wee1-like protein kinase.

The growth arrest and DNA damage inducible gene (GADD45) is a group of genes that are activated by genomic damage compounds such as UV radiations, chemotherapeutic agents and growth factors [40]. Under activation by p53, GADD45 interacts with Cdc2 which is cleaved from Cyclin B1 and the complex GADD45/Cdc2 acts on the cell cycle by arresting the division at the checkpoint G2/M [41]. The high expression of GADD45 recorded in group D (hemocytes with tetraploidy status ranging between 10% and 50%).

3.4.3. Transcripts involved in G2–M phase of cell cycle

G2 phase is mainly controlled by CycA/CDK1 and CycB/CDK1. Cyclin B1 is expressed at very low levels and its expression increases at the G2–M phase [42]. However, in tumor cells, cyclin B1 is mainly localized in the cytoplasm and overexpressed throughout the cell cycle due to the inactive state of p53 [43]. It was shown that cyclin A is key in the progression of male germ cells through meiosis [44]. Over-expression of cyclin A was found in leukemic cells in more than 50% of acute myeloid leukemia patients [44]. In our study, both cyclin A (Fig. 7) and B (Fig. 8) as well as CDK1 (Fig. 8) are highly expressed in hemocytes with a tetraploid status ranging between 10% and 15%. The overexpression of cyclin B seems to coincide with a high expression of c-myc (Fig. 6). It was shown that cyclin B1 is a c-myc target whose overexpression induces chromosomal activity and tetraploidy [45].

Fig. 8.

Fig. 8

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Expression levels of gene identified in our sequence database during the phase G2–M. Histogram represents Log2 RPKM ratio of group D (disease in development) and E (established disease) to group C (control). MPS1: serine/threonine-protein kinase; MAD1: mitotic spindle assembly checkpoint protein; MAD2: mitotic spindle assembly checkpoint protein; BUB3: cell cycle arrest protein; BUB1: checkpoint serine/threonine-protein kinase; BUB1β/BUBR1: mitotic checkpoint serine/threonine-protein kinase; 14–3–3 β−τ−ζ: 14–3–3 protein beta/theta/zeta; CycB: cyclin B; CDK1: cyclin-dependent kinase 1; Myt1: membrane-associated tyrosine- and threonine-specific cdc2-inhibitory kinase; PLK1: polo-like kinase 1; SMC1: structural maintenance of chromosome 1; SMC3: structural maintenance of chromosome 3 (chondroitin sulfate proteoglycan 6); STAG1/2: cohesin complex subunit; Rad21: cohesin complex subunit SCC1; ESP1: separase; APC/C4: anaphase-promoting complex subunit 4; APC/C2: anaphase-promoting complex subunit 2; APC/C6: anaphase-promoting complex subunit 6; APC/C8: anaphase-promoting complex subunit 8; APC/C3: anaphase-promoting complex subunit 3; APC/C10: anaphase-promoting complex subunit 10; APC/C1: anaphase-promoting complex subunit 1; APC/C7: anaphase-promoting complex subunit 7; Cdh1/CDC20: cell division cycle 20, cofactor of APC complex; and CDC 14: cell division cycle 14.

In the M phase, the anaphase promoting complex/cyclosome (APC/C) is an E3 ubiquitin ligase complex that targets the degradation of protein involved in the cell cycle during the M phase. APC/C's activation depends on two WD-40 domain proteins, CDC20 and CDH1. In our study, APC/C family members identified in our database and in particular APC/C sub-unit 7 showed a high expression level in hemocyte with tetraploid status ranging between 10% and 50% as well as in diseased organisms with more than 50% tetraploid hemocytes (Fig. 8). Similarly, Cdh1/Cdc20 is also higher in both groups D and E (Fig. 8). In yeast mitosis, CDC20 and CDH1 bind to the APC/C, which is activated during the mitosis process [46]. Cdc20 activates APC/C during early mitosis, while Cdh1 plays a key role and controls several phases from late mitosis to G1/S transition [47]. It was shown that the deregulation of Cdh1 impaired centrosome formation, cytokinesis and DNA re-replication [48]. Overall, the disruption of APC/Cdh1 activity may lead to cell cycle instability and thus the development of neoplastic cells [49].

On the other hand, the expression level of separin (Esp1) is high (Log2 ratio Med/Neg = 3.58) in hemocytes with a tetraploidy ranging from 10% to 50% (Fig. 8). Separin is among the protein complexes known as cohesin. This complex maintains the cohesion between the sister chromatid which is important for equal segregation of sister chromatids in anaphase [50]. Separin related proteins have been identified in yeast [51], Aspergillus nidulans [52], Xenopus, and human [53] and now in M. arenaria (this study) suggesting that the mechanism of chromatid segregation is evolutionarily conserved among organisms.

3.5. Cell cycle molecular pathway in hemocytes of M. arenaria

Cell cycle progression is mainly regulated by the complex cyclin-CDK (cyclin-dependent kinase). These kinases are under control of mitogenic signals and play a central role in cell proliferation [27].

Pathways were generated once the sequences were blasted against KEGG Genes database. Focusing on pathways related to cell cycle, 77 transcripts were identified from our sequence database. Based on the KEGG pathways, these sequences are involved at different phases of the cell cycle: G1–S–G2–M (Fig. 9).

Fig. 9.

Fig. 9

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KEGG mapping for cell cycle pathway. The green boxes represent the annotated protein found in our library. The white boxes are the unidentified proteins in our database sequences.

In this study, individual variability was not taken into account because individuals were pooled in three different pools based on their tetraploidy status. However, sequences and data generated from this study provided a snapshot of molecular mechanisms involved in cell cycle in hemocytes of soft-shell clams M. arenaria. Overall, apart from few transcripts, the majority of the identified genes were highly expressed in group D where the population of hemocytes is ranging between 10% and 50% of tetraploid cells. This corroborates our previous study showing an up-regulation of p53, p73 and mortalin in clams with a moderate percentage (15–50%) of tetraploid cells [18].

4. Conclusion

During this study, 18,378 annotated sequences matched known sequences were generated from hemocytes of soft-shell clams, M. arenaria including sequences related to the development of DN. Focusing on sequences related to cell cycle, the majority of the cell cycle pathways described in vertebrates have been identified in M. arenaria. Overall, gene expression levels of the majority of the transcripts identified in cell cycle are higher during the development of the disease (tetraploidy ranging between 10% and 50%). Further studies are needed to investigate specific molecular mechanisms involved in cell cycle in relation with the development of hemic neoplasia in soft shell clams, M. arenaria. This study will increase M. arenaria's sequences for studies involved in molecular pathology, ecotoxicogenomics as well as in identifying biomarkers for biosurveillance programmes.

Footnotes

☆

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-No Derivative Works License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

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