Bioinformatics analysis of hemocyte miRNAs of scallop Chlamys farreri against acute viral necrobiotic virus (AVNV)

Fish & Shellfish Immunology 37 (2014) 75e86

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Short sequence report

Bioinformatics analysis of hemocyte miRNAs of scallop Chlamys farreri against acute viral necrobiotic virus (AVNV) Guofu Chen a, Chunyun Zhang a, *, Fengjuan Jiang a, Yuanyuan Wang a, Zhong Xu a, Chongming Wang b a b

School of Marine Science and Technology, Harbin Institute of Technology at Weihai, Weihai 264209, PR China Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, PR China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 13 September 2013 Received in revised form 1 December 2013 Accepted 2 January 2014 Available online 21 January 2014

The sustainable development of the scallop Chlamys farreri industry in China is hindered by mass mortality mainly caused by a novel pathogen known as acute viral necrosis virus (AVNV). A better understanding of host-virus interactions, especially those at the molecular level, may facilitate the prevention and cure of AVNV infections. MicroRNAs (miRNAs) represent a class of small RNA molecules involved in several biological processes, including mediating host-pathogen responses. In this study, two hemocyte small RNA libraries were constructed from control (control library, CL) and AVNV-infected (infection library, IL) C. farreri for high throughput sequencing using Solexa technology. Acquired data were further used to identify conserved and novel miRNAs, screen differentially expressed miRNAs, and predict their target genes through bioinformatics analysis. Solexa sequencing produced 19,485,719 and 20,594,513 clean reads representing 2,248,814 and 1,510,256 unique small RNAs from CL and IL, respectively. A total of 57 conserved miRNAs were identified in both libraries, among which only two were unique to IL. Novel miRNA prediction using the Crassostrea gigas genome as a reference revealed 11 candidate miRNAs, 10 of which were validated by RT-PCR. Differential expression (p < 0.001) between libraries was observed in 37 miRNAs, among which 30 and 7 miRNAs were up- and downregulated, respectively. Expression differences were further confirmed by qRT-PCR. A sequence homology search against available C. farreri ESTs showed that these differentially expressed miRNAs may target 177 genes involved in a broad range of biological processes including immune defense and stress response. This study is the first to characterize C. farreri miRNAs and miRNA expression profiles in response to AVNV infection by deep sequencing. The results presented here will deepen our understanding of the pathogenesis of AVNV at the molecular level and provide new insights into the molecular basis of hostpathogen interactions in C. farreri. Ó 2014 Elsevier Ltd. All rights reserved.

Keywords: Chlamys farreri Acute viral necrobiotic virus miRNA Deep sequencing Immune response

1. Introduction The scallop (Chlamys farreri) industry has grown rapidly in the coastal provinces of northern China over the past several years and is now one of the biggest industries in Chinese marine culture. However, the mass mortality of scallop has become fairly common since the mid-1990s because of the deterioration of the environment and the development of intensive culture. Acute virus necrobiotic disease (AVND) is diagnosed according to typical symptoms of ill individuals [1]. Prevalent AVND is devastating and

* Corresponding author. School of Marine Science and Technology, Harbin Institute of Technology at Weihai, Wenhua West Road, 2#, Weihai, Shandong Province, PR China. Tel./fax: þ86 631 5687059. E-mail addresses: [email protected] (G. Chen), [email protected] (C. Zhang). 1050-4648/$ e see front matter Ó 2014 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.fsi.2014.01.002

often results in over 90% cumulative mortality within a short period of time [2]. Thus, the disease is considered one of the factors limiting the sustainable development of scallop culture. The etiology of AVND has previously been elucidated. Among multiple factors suspected to be possible cause of high mortality cultured scallops [3], acute viral necrosis virus (AVNV) has been verified to be a very important pathogen [4,5]. Comprehensive studies on the epidemiology [4], pathology [3,6], physicochemical and biological factors in ambient environments [4], and detection methods of AVNV using polyclonal and monoclonal antibodies [7,8] have been performed. Ren et al. [9,10] recently obtained the whole genome sequence of AVNV. The molecular data obtained has allowed the establishment of multiple molecular detection protocols including polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), and fluorescence quantitative polymerase chain reaction (FQ-PCR) [9,11] for AVNV. The

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transmission routes of AVNV have also been clarified recently [12e 15] by the molecular methods. Gene expression regulation is believed to occur at the transcriptional and post-transcriptional levels. The recent discovery of various endogenous non-protein-coding small RNAs, such as microRNA (miRNA), small interfering RNA (siRNA), and Piwiinteracting RNA (piRNA) [16], has resulted in interest in posttranscriptional gene expression regulation during development and other biological processes. Interestingly, miRNAs, which are typically 22e25 nt in length, can negatively regulate gene expression at the post-transcriptional level by blocking translation through incomplete binding with the 30 -UTR of a target gene mRNA or by directing degradation of a target gene [17e20]. Since the first miRNA was demonstrated in Caenorhabditis elegans [21], miRNAs have attracted significant research attention. Numerous miRNAs have been identified from a broad spectrum of organisms including animals, plants, and even viruses [22]. A total of 21,264 miRNA database entries are currently available, representing hairpin precursor miRNAs expressing 25,141 mature miRNA products, in 193 species (ftp://mirbase.org/pub/mirbase/CURRENT/README). As conserved molecules in organisms, miRNAs are involved in diverse biological processes, including developmental timing [23], cell proliferation [24], apoptosis [24,25], metabolism [25,26], morphogenesis [27,28], DNA repair [29], and stress responses [30,31]. Previous studies have indicated that miRNAs play important roles in immune responses [32], including antivirus response [33,34]. To date, research on the functions of miRNAs in the hostpathogen interactions implicated in marine invertebrates remains relatively new [35e37]. Therefore, the main objective of this study is to investigate scallop miRNA and provide novel insights into the molecular basis of host-pathogen interactions in C. farreri. Two hemocyte small RNA libraries were constructed from normal (control) and AVNV-infected C. farreri, and then deep sequenced using Illumina Solexa technology. Finally, the obtained data were analyzed using bioinformatics analysis to identify both conserved and novel miRNAs, screen differentially expressed miRNAs, and predict their target genes. 2. Materials and methods

were diluted fivefold with sterilized filtered seawater and infected into the adductor muscles of scallops (100 mL per individual) in the control and infection groups. The infection experiments were terminated 24 h post-infection, and the infected conditions of the scallops were verified by PCR [37]. 2.3. Hemocyte sampling and RNA isolation Hemocytes of all living individuals from the infection and control groups were pooled for RNA isolation. Briefly, hemolymph was withdrawn from the adductor muscle sinus of scallops with a 21gauge needle attached to a 1 mL sterilized syringe. The hemocyte mixture was then centrifuged for 10 min at 800 g at 4  C to collect hemocyte pellet. Total RNA was extracted from the hemocyte pellet using TRIzol Reagent (Invitrogen) according to the manufacturer’s instructions. The RNA concentration and purity were determined photometrically by measurement of the absorbance of the samples at 260 nm and determination of the A260/A280 ratio using a Nanodrop 2000 microspectrophotometer (Thermo Fisher Scientific, MA, USA). RNA integrity was evaluated using Agilent 2100 bioanalyzer (Agilent Technologies). RNA extracts showing values of 28S/18S  0.7 and RIN  7.0, respectively, were considered qualified for small RNA library construction, and RNA samples were stored at 80  C until use. 2.4. Small RNA library construction and sequencing Approximately 10 mg of total RNA from each group was subjected to 15% Tris-borate-EDTA (TBE) urea gel electrophoresis, and small RNA fragments of 18e28 nt were enriched and purified. A 50 adapter (Illumina, San Diego, CA, USA) was ligated to the purified small RNAs followed by purification of the ligation products in 15% TBE urea gel. A 30 adapter (Illumina) was ligated to the 50 ligation products, and products with both adapters were purified from 10% TBE urea gel (Invitrogen). The ligation products were subsequently reverse-transcribed and PCR amplified using an Illumina sequencing kit (Illumina). The amplification products were excised from 6% TBE urea gel (Invitrogen), and purified DNA fragments were clustered and sequenced by Illumina Genome Analyzer in Shanghai Biotechnology Corporation (Shanghai, China).

2.1. Scallop samples 2.5. Preprocessing of sequencing data and annotation analysis C. farreri scallops of nearly uniform size (about 30 g) were obtained from a local shellfish farm at Weihai, Shandong Province, China. The health of the scallops was assessed by tissue observation and specific virus (AVNV) detection following methods described by Chen et al. [38] to ensure that the test animals were healthy, AVNV-free, and competent for subsequent challenge. The scallops were acclimated in 25 L fiberglass tanks containing 15 L of aerated filtered seawater at 25  C under a constant photoperiod of 12:12 light/dark. During the acclimation period, salinity was maintained at 30&, dissolved oxygen was maintained above 6 mg L1, and pH was maintained between 7.5 and 8.1. 2.2. AVNV challenge A virus solution was prepared from AVNV-infected C. farreri belonging to the same batch of frozen scallops used in our previous study [38]. Scallops that were confirmed virus-free by PCR were used for control solution preparation. Methods used for preparing the viral and control solutions are described by Chen et al. [38]. Obtained samples were kept at 70  C prior to the AVNV challenge experiments. After acclimatization for 7 d, 50 living scallops were randomly divided into two groups (control group and infection group), each of which contained 25 individuals. The virus and control solutions

The small RNA sequence reads were pre-processed using FASTXToolkit (fastx_toolkit-0.0.13.2; http://hannonlab.cshl.edu/fastx_ toolkit/commandline.html), excluding low-quality reads (ambiguous N, quality < 10 nt, and length <18 nt) as well as 30 adapter, 50 adapter and poly(A) sequences. Further annotation analyses were performed using the commercial software CLC Genomic Workbench 5.5. Briefly, the resulting clean reads were aligned against various databases, including ncRNA, piRNA, and Rfam, allowing a maximum mismatch of 2 nt to remove noncoding RNA, such as rRNA, tRNA, snRNA, and snoRNA. Obtained sequences were then compared with scallop ESTs to classify mRNA degradation. The remaining sequences were analyzed by BLAST search against Sanger miRBase (version 19.0). Sequences in our libraries that were identical or related (four or fewer nucleotide substitutions) to sequences from Lottia gigantea and Haliotis rufescens were identified as conserved miRNAs. Reads that did not match any database above were marked as non-annotation. 2.6. Identification of novel miRNAs Non-annotated sequences were searched against the Crassostrea gigas genome using the miRCat program included in the sRNA

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Table 1 Primers used in the RT-PCR and qRT-PCR. Target genes

RT primers (50 e30 )

Forward primers (50 e30 )

Reverse primers (50 e30 )

Amplification type

scaffold1144-220102

AAGCAGTGGTATCAACGCAGA GTGGCCGAGG CGGCC (T)20V N (V ¼ A, G or C; N ¼ A, C, G, or T) As above As above As above As above As above As above As above As above As above As above As above As above As above As above As above As above As above As above As above As above CGCTTCGGCAGCACATA

AAATGCCCCCAGAAATCCTAAA

AAGCAGTGGTATCAACGCAGAGT

RT-PCR

TGAAAGACTAGAGGCTCTCGAGA TTGAACCTCCTTCGTGCTAGGG TGGAAGACTAGTGATTTTGTTGT TGCCCTATCCGTCAGTCGCTGC GTGAGGACCAGTGTCAGAGGT CTGAAGACAGTGTCAGGCGGGGA TTAGTACTTGGATGGGTGACC CGCCGGAGTTGCTTCAATGACT AGAGAAGATTAGCATGGCCCCTG ATTTTTTAGTGTGGGGGTCTG AATTGCACTTGTCCCGGCCTGC AGCTGCCAAATGAAGGGCTGTG TCACAACCTGCATGAATGAGGAC TGCCCTATCCGTCAGTCGCTGC TTGGTCCCCTTCAACCAGCTGT TATCACAGCCTGCTTGGATCAGT AGCTGCCTGATGAAGAGCTGT TGACTAGATCCACACTCATCCA TGAGATTCAACTCCTCCAACTGC TATCACAGCCAGCTTTGATGAGT CCGTGCGTGTCATCCTT

As As As As As As As As As As As As As As As As As As As As As

As above As above As above As above As above As above As above As above As above As above qRT-PCR As above As above As above As above As above As above As above As above As above As above

scaffold1449-525 scaffold1520-30954 scaffold1896-30954 scaffold339-658238 scaffold365-4775 scaffold37400-90107 scaffold40680-341693 C24718-2851 scaffold1533-213741 scaffold40948-91902 cfa-miR-92 cfa-miR-745b cfa-miR-67 scaffold339-658238 cfa-miR-133-3p cfa-miR-2d cfa-miR-745a cfa-miR-279 cfa-miR-1175-3p cfa-miR-2c U6

Toolkit (http://srna-tools.cmp.uea.ac.uk/animal/cgi-bin/srna-tools. cgi?rm¼input_formandtool¼mircat). Using default settings, 100 nucleotides of genomic sequence flanking each side of the sequences were extracted for RNA secondary structure prediction using RNAfold [39]. The predicted precursors were deemed with high probability and stem-loop hairpins were considered typical when their minimum free energy and Randfold p-value were lower than 20 kcal mol1 and 0.1, respectively. 2.7. Detection of miRNA differential expression Differences in miRNA expression levels between the control and infection samples were determined using the program DEGseq (http://www.bioconductor.org/packages/2.6/bioc/html/DEGseq. html) by assessing read counts as described by Zhu et al. [40]. In brief, the expression level of each identified miRNA including conserved and novel miRNAs was normalized by dividing the absolute read count with the total read count of the sample and multiplying the result by 1,000,000. Normalized sequence counts were used to perform a two-tailed Student t-test to determine the significance of difference. In this study, a specific miRNA was considered significantly differentially expressed when the p-value obtained by this method was less than 0.001. 2.8. Target gene prediction of differentially expressed miRNAs Unigene sequences from the EST database of C. farreri were used to predict miRNA target genes of differentially expressed miRNAs without distinguishing the 30 UTR from the protein coding region using miRanda (http://cbio.mskcc.org/tools/micrornas/index.html). A miRanda score of greater than 140 and a dimer binding free energy of less than 20 were used to select unigene targets. 2.9. RT-PCR and qRT-PCR To confirm the expression of miRNAs identified by the deep sequencing, all novel miRNAs and representative differentially expressed miRNAs (p < 0.001) were selected for analysis by RT-PCR and qRT-PCR using the same total RNA samples used for sequencing library construction. Total RNA extracts were polyadenylated with

above above above above above above above above above above above above above above above above above above above above above

ATP by Escherichia coli poly(A) polymerase (Biolabs, New England). Polyadenylated RNAs were reverse-transcribed with RT M-MLV (Fermentas, Canada) and one universal primer. The RT products were amplified using a specific primer (miRNA analog) and a universal primer. Detailed information of all test miRNAs and amplification primers used during RT-PCR and qRT-PCR are summarized in Table 1 qRT-PCR was performed using SYBR Premix Ex TaqÔ (Tli RNaseH Plus) (Takara, Dalian, China) on an ABI 7500 sequence detection system (Applied Biosystems, Foster City, CA, USA) according to the manufacturer’s instructions. U6 small nuclear RNA was used as an endogenous control for miRNAs. The expression levels of ten miRNAs were measured in terms of threshold cycle value (Ct) and normalized to that of U6 RNA using the comparative Ct method. One-way ANOVA and a two-tailed Student’s t test were used to compare differences in expression levels between control and infection groups. All statistical calculations were performed with SPSS 13.0 software. 3. Results and discussion The mass mortality of C. farreri caused by AVND is considered one of the major hindrances to the sustainable development of Chinese scallop culture. Despite great progress in determining the etiology, epidemiology, pathology, diagnosis and detection, and transmission route of the disease, our understanding of this AVND, especially at the molecular level is remains limited. Knowledge of molecular defense mechanisms can improve understanding of the host-pathogen interactions and immune responses. The activities of immune-associated enzymes activities [41] as well as the physiological reactions [5] of C. farreri in response to AVNV infection have been investigated. We recently analyzed the protein [38] and gene (unpublished data) expression profiles of C. farreri in the response to AVNV. Considering that miRNAs play important roles in a wide spectrum of biological processes including immune responses, the present study attempts to introduce novel high throughput deep sequencing technologies to investigate miRNAs in C. farreri, particularly hostresponsive miRNAs during AVNV infection. These results will certainly improve the current understanding of this virusassociated disease.

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To survey small RNAs in C. farreri, Illumina technology was used to sequence small RNA libraries from the control and infection groups. A preliminary analysis of the sequencing data is summarized in Table 2. Deep sequencing yielded 19,485,719 clean reads from CL and 20,594,513 clean reads from IL after the removal of low-quality and empty adapter sequences. A total of 7,817,641 reads accounting for 40.1% of total clean reads in CL, and 14,147,880 reads accounting for 68.7% of the total clean reads in IL could be annotated by searching against all types of RNA databases. The annotated reads represented 2,248,814 unique sequences in CL and 1,510,256 unique sequences in IL. Significant differences in length distribution were observed between CL and IL (Fig. 1). The read lengths peaked at 29 nt, followed by 22 nt in CL. By contrast, 22 nt of small RNAs were enriched, followed by 23 nt in IL. Current deep sequencing data indicate that small RNAs, at least in animals, have similar size distribution patterns. For example, 21 nt RNAs were found to be the peak molecule in small RNA libraries from Clonorchis sinensis [42], Apostichopus japonicus [37], and Eriocheir sinensis [36], whereas the most typical molecules were 22 nt long in the small RNA libraries of Locusta migratoria [27], Aedes albopictus [43], Culex quinquefasciatus [43], and Blattella germanica [28]. However, some species, such as C. farreri, may present an exception to this trend. In addition, other species display similar size distribution patterns of small RNAs under different conditions [28,37,43]. Such findings differ from the observations in this study. A dramatic change in expression profile between both libraries suggests that miRNAs are active factor that affect the response of C. farreri against AVNV. 3.2. Identification of conserved microRNAs

A

3000000

2500000

Number of reads

3.1. Profile characteristics of small RNAs from C. farreri

2000000

1500000

1000000

500000

0 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

Read length

B

10000000

8000000

Number of reads

78

6000000

4000000

2000000

Selection of miRNA data from related species guarantees the precision of identifying conserved miRNAs. Unfortunately, only two mollusks, namely, H. rufescens and L. gigantean, currently have miRNAs deposited in miRbase 19.0. Five miRNAs from H. rufescens and 60 miRNAs from L. gigantean allowed identification of a total of 57 conserved miRNAs ranging from 20 nt to 24 nt in length, 55 of which were common to both libraries and 2 (cfa-miR-137 and cfamiR-242a) of which were unique to the IL (Table 3). Most of the identified miRNAs could be observed in scallop, which also supports the conservation of miRNAs among related species. miRNA expression levels determined based on numbers of reads varied greatly and spanned over seven orders of magnitude for both libraries. The orders of miRNA abundance were almost identical in both libraries. Among the conserved miRNAs found, cfa-miR-184 was the most highly expressed miRNA, representing 1,317,498 reads in CL and 8,165,961 reads in IL. This miRNA was followed by cfa-miR-67 and cfa-miR-137. In particular, miR-184 (cfa-miR-184), as a conserved miRNA observed in organisms from insects to vertebrates, has thus far been identified from more than 40 organisms [43]. It is also the most abundant miRNA in invertebrate organisms

Table 2 Summary of preliminary analysis of Solexa high-throughput sequencing of hemocyte small libraries from control (CL) and AVNV infected (IL) C. farreri. Category

CL

IL

Clean reads Annotated Unique small RNAs Annotated Conserved miRNAs Novel miRNAs

19,485,719 7,817,641 (40.1%) 2,248,814 135,482 (6.0%) 55 9

20,594,513 14,147,880 (68.7%) 1,510,256 80,405 (5.3%) 57 8

0 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

Read length Fig. 1. Read length profiling of unique small RNA sequences (18e35 nt) in CL (A) and IL (B).

such as Ae. aegypti, Cx. quinquefasciatus [43] and E. sinensis [36]. However, the definitive role of this highly abundant miRNA in gene regulation has yet to be determined. 3.3. Discovery and validation of novel microRNAs An important feature that distinguishes miRNAs from other small RNAs is the ability of the miRNA flanking sequences to fold back into a hairpin structure [44]. Therefore, candidate miRNAs can be identified by mapping to genomes of target species to predict quantified secondary structures. To date, the sequencing of C. farreri genome has not yet been completed. Fortunately, the genome sequence of C. gigas, a species related to C. farreri, was released recently [45]. Hence, non-annotated small RNAs representing 11,668,078 clean reads in CL and 6,446,633 clean reads in IL were used to search against the C. gigas genome sequence to determine the folding properties of pre-miRNA hairpins. Each candidate miRNA should meet both expression and biogenesis criteria for identifying new miRNAs [44,46,47]: (1) a small RNA of appropriate and discrete length (19e24 nt); (2) arising from one arm of hairpin precursor; (3) presence of the star strand, and (4) evolutionary conservation. Finally, 11 novel miRNAs mapped to the C. gigas

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Table 3 Conserved miRNA candidates identified in the hemocytes of control (IL) and AVNV infected (IL) C. farreri. Genes

Expression values in CL

Expression values in IL

Sequences (50 / 30 )

Length (nt)

cfa-miR-1 cfa-miR-2c cfa-miR-2d cfa-miR-7 cfa-miR-8 cfa-miR-9 cfa-miR-10 cfa-miR-12 cfa-miR-29 cfa-miR-31 cfa-miR-33-5p cfa-miR-34 cfa-miR-67 cfa-miR-71 cfa-miR-79 cfa-miR-87 cfa-miR-92 cfa-miR-96a cfa-miR-96b cfa-miR-100 cfa-miR-124 cfa-miR-133-3p cfa-miR-137 cfa-miR-153 cfa-miR-182 cfa-miR-183 cfa-miR-184 cfa-miR-190 cfa-miR-193 cfa-miR-216a cfa-miR-216b cfa-miR-242a cfa-miR-278 cfa-miR-279 cfa-miR-281-5p cfa-miR-281-3p cfa-miR-315 cfa-miR-317 cfa-miR-745a cfa-miR-745b cfa-miR-750 cfa-miR-981 cfa-miR-1175-5p cfa-miR-1175-3p cfa-let-7 cfa-miR-375 cfa-miR-252b cfa-miR-1992 cfa-miR-1993 cfa-miR-1994a cfa-miR-1994b cfa-miR-1984 cfa-miR-1985 cfa-miR-1989 cfa-miR-2001 cfa-miR-1991 cfa-miR-2722

926 504 6488 17 3093 61 27114 2144 30 435 10 3 119807 1 4 1 22129 22038 3282 44789 25 13859 0 110 2039 7917 1317498 10958 302 1115 1303 0 222 2372 549 22 1604 74 2090 7970 114 39573 8 1463 52 81 11 5 32 126 97 2 19346 2 2750 6 7

5841 3784 62688 41 14512 249 23123 3853 258 2009 52 6 1139639 5 79 25 228171 94521 7408 282596 26 121427 2 582 4323 6256 8165961 22908 2126 3674 2730 13 1712 24152 3821 128 3587 233 24712 107743 261 87031 72 11584 218 147 46 23 36 654 510 21 71857 61 10355 25 28

UGGAAUGUAAAGAAGUAUGUAU UAUCACAGCCAGCUUUGAUGAGU UAUCACAGCCUGCUUGGAUCAGU UGGAAGACUAGUGAUUUUGUUGUU UAAUACUGUCAGGUAAAGAUGUC UCUUUGGUUAUCUAGCUGUAUGA UACCCUGUAGAUCCGAAUUUGU UGAGUAUUACAUCAGGUACUGA UAGCACCAUUUGAAAUCAGUUU AGGCAAGAUGUUGGCAUAGCU GUGCAUUGUAGUUGCAUUGCAU UGGCAGUGUGGUUAGCUGGUAGU UCACAACCUGCAUGAAUGAGGAC UGAAAGACAAGGGUAGUGAGAUG AUAAAGCUAGGUUACCAAAGGC GUGAGCAAAGUUUCAGGUGUAU AAUUGCACUUGUCCCGGCCUGC CUUGGCACUGGCGGAAUAAUCA AUUUGGCACUUGUGGAAUAAUCG AACCCGUAGAUCCGAACUUGUG UAAGGCACGCGGUGAAUGCCA UUGGUCCCCUUCAACCAGCUGU UAUUGCUUGAGAAUACACGUAA UUGCAUAGUCACAAAAGUGAUC CUUGGCACUGGUAGAAUUCACUG AAUGGCACUGGUAGAAUUCACGG UGGACGGAGAACUGAUAAGGGC AGAUAUGUUUGAUAUACUUGGU UACUGGCCUGCAAAAUCCCAAC UAAUCUCAGCUGGUAAUUCUGAG UAAUAUCAGCUGGUAAUCCUGAG UUGCGUAGGCGUUGUGCACAG UCGGUGGGACUUUCGUUCGUCU UGACUAGAUCCACACUCAUCCA AAGGGAGCAUCUGUCGACAGU UGUCAUGGAGUUGCUCUCUUUA UUUUGAUUGUUGCUCAGAAAGCC UGAACACAGCUGGUGGUAUCUUCU AGCUGCCUGAUGAAGAGCUGU AGCUGCCAAAUGAAGGGCUGUG CAGAUCUAACUCUUCCAGCUCA UUCGUUGUCGACGAAACCUGCCU AGUGGAGAGAGUUUUAUCUCAU UGAGAUUCAACUCCUCCAACUGC UGAGGUAGUAGGUUGUAUAGUU UUUGUUCGUUCGGCUCGCGUUA AUAAGUAGUGGUGCCGCAGGUA UCAGCAGUUGUACCACUGAUUUG UAUUAUGCUGAUAUUCACGAGA UGAGACAGUGUGUCCUCCCUUG UGAGACAGUGUGUCCUCCCUCA UGCCCUAUCCGUCAGGAACUGUG UGCCAUUUUUAUCAGUCACUGUGA UCAGCUGUCAUGAUGCCUUC UUGUGACCGUUAUAAUGGGCAUU GUUACCCUGUUAAUCGAAGAAGU UGGCGCCGUGGAAACAUCUACC

22 23 23 24 23 23 22 22 22 21 22 23 23 23 22 22 22 22 23 22 21 22 22 22 23 23 22 22 22 23 23 21 22 22 21 22 23 24 21 22 22 23 22 23 22 22 22 23 22 22 22 23 24 20 23 23 22

genome were identified from the CL and IL libraries (Table 4). Among these miRNAs, 6 (scaffold1144-220102, scaffold1896-30954, scaffold339-658238, scaffold365-4775, scaffold37400-90107, and scaffold40680-341693) were common to both libraries while 3 (C24718-2851, scaffold1533-213741, and scaffold40948-91902) and 2 (scaffold1449-525 and scaffold1520-30954) were unique to CL and IL, respectively. The length of novel miRNAs ranged from 21 nt to 23 nt. The secondary structures of miRNA precursors of some candidates with relatively high expression (more than 100 reads), including scaffold1144-220102, scaffold1896-30954, scaffold339658238, scaffold365-4775, scaffold37400-90107, scaffold40680341693, and scaffold1533-213741, were shown in Fig. 2AeG. The

miRNA precursor scaffold339-658238 was one of the most frequently recovered miRNAs, representing 150,959 reads in CL and 1,233,300 reads in IL, three to four orders of magnitude greater than other candidates. Northern blot and RT-PCR are commonly used methods for validating of miRNAs. Considering their methodologies, RT-PCR is more sensitive than Northern blot, which is unsuitable for detecting very low amounts of miRNA. Moreover, RT-PCR is competent for parallel detection of several miRNAs. Therefore, this study applied RT-PCR to further confirm all predicted novel miRNA candidates. Expected DNA fragments with sizes of 77e 79 bp could be produced by RT-PCR if the detected miRNAs were

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Table 4 Novel miRNAs predicted in the hemocytes of control (IL) and AVNV infected (IL) C. farreri. Genes

Expression values in the normal group

Expression values in the infected

Sequences (50 / 30 )

Length (nt)

Minimum free energy

Randfold p-value

scaffold1144-220102 scaffold1449-525 scaffold1520-30954 scaffold1896-30954 scaffold339-658238 scaffold365-4775 scaffold37400-90107 C24718-2851 scaffold40680-341693 scaffold1533-213741 scaffold40948-91902

107 0 0 55 150959 35 158 13 108 122 11

637 16 12 160 1233300 187 8 0 23 0 0

AAAUGCCCCCAGAAAUCCUAAA UGAAAGACUAGAGGCUCUCGAGA UUGAACCUCCUUCGUGCUAGGG UGGAAGACUAGUGAUUUUGUUGU UGCCCUAUCCGUCAGUCGCUGC GUGAGGACCAGUGUCAGAGGU CUGAAGACAGUGUCAGGCGGGGA CGCCGGAGUUGCUUCAAUGACU UUAGUACUUGGAUGGGUGACC AGAGAAGAUUAGCAUGGCCCCUG AUUUUUUAGUGUGGGGGUCUG

22 23 22 23 22 21 23 22 21 23 21

39.00 280.30 55.50 74.32 39.70 51.20 62.00 42.90 20.20 33.00 18.40

0.009901 0.009901 0.009901 0.029703 0.009901 0.009901 0.009901 0.059406 0.059406 0.009901 0.009901

present in the samples; by contrast, no target DNA was amplified for blank controls to which ddH2O instead of RT templates had been added. Because we did not optimize the RT-PCR conditions, many blank controls produced dimers (Fig. 3). However, this condition did not affect the assessment of positive results. All but one novel miRNA candidate (C24718-2851) were detected, producing RT-PCR products with sizes between 50 and 100 bp (Fig. 3).

The successful detection of three miRNAs (scaffold1449-525, scaffold1520-30954, and scaffold40948-91902) with low expression levels confirms the sensitivity of RT-PCR. In general, both high-throughput sequencing and RT-PCR showed the existence of the predicted novel miRNAs. Future studies will focus on their roles in scallop, especially in terms of immune responses to pathogens.

Fig. 2. Predicted step-loop secondary structures of pre-sequences of representative novel candidate miRNAs with high expression frequency more than 100 reads. A: scaffold1144220102; B: scaffold1896-30954; C: scaffold339-658238; D: scaffold365-4775; E: scaffold37400-90107; F: scaffold40680-341693; G: caffold1533-213741. The mature miRNAs were located in the green regions. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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81

Table 6 Confirmation of differentially expressed miRNAs by qRT-PCR. Gene

Fig. 3. Validation of novel miRNAs by RT-PCR. M: DL500 DNA Marker; L1e11 are scaffold1144-220102, scaffold1449-525, scaffold1520-30954, scaffold1896-30954, scaffold339-658238, scaffold365-4775, scaffold37400-90107, C24718-2851, scaffold40680-341693, scaffold1533-213741, scaffold40948-91902, and for each miRNA, the right lane is the negative control.

3.4. Differential expression of miRNAs miRNAs are known to be important regulators of development [21] and have proven to be involved in several biological processes [29,31]. In this work, we focused on the roles of miRNAs in antiinfection immune responses, especially in marine invertebrates. miRNA expression profiles are altered in sea cucumber A. japonicus suffering from skin ulceration syndrome [37] and crab E. sinensis challenged with Spiroplasma eriocheiris [36]. Based on these previous studies, we explored whether or not miRNAs in C. farreri are aberrantly expressed during AVNV infection was also explored in this study. Deep sequencing is a favorable tool for identifying small RNAs and a reliable quantification method for miRNA expression based

Table 5 Differentially expressed miRNA (p < 0.001) in the hemocytes of control and AVNV infected C. farreri. Genes

Fold_changea,b

p-Value

Regulationc

cfa-miR-981 cfa-miR-96b cfa-miR-96a cfa-miR-92 cfa-miR-745b cfa-miR-67 cfa-miR-1985 cfa-miR-190 cfa-miR-184 cfa-miR-183 cfa-miR-12 cfa-miR-10 scaffold339-658238 cfa-miR-182 cfa-miR-133-3p cfa-miR-2d cfa-miR-315 cfa-miR-216b cfa-miR-745a scaffold37400-90107 cfa-miR-2001 cfa-miR-279 scaffold1533-213741 cfa-miR-216a scaffold40680-90107 cfa-miR-8 cfa-miR-750 cfa-miR-375 cfa-miR-1175-3p C24718-2851 cfa-miR-1993 scaffold40948-91902 cfa-miR-124 cfa-miR-31 cfa-miR-317 scaffold1896-30954 cfa-miR-2c

2.20 2.26 4.29 10.31 13.52 9.51 3.71 2.09 6.20 0.79 1.80 0.85 8.17 2.12 8.76 9.66 2.24 2.10 11.82 0.05 3.77 10.18 NA 3.30 0.21 4.69 2.29 1.81 7.92 NA 1.13 NA 1.04 4.62 3.15 2.91 7.51

0 0 0 0 0 0 0 0 0 0 0 0 0 4.63E-315 1.06E-292 1.89E-244 2.68E-229 2.04E-205 1.49E-189 1.52E-125 4.37E-122 1.13E-116 8.08E-107 1.41E-74 1.10E-70 2.94E-52 2.09E-17 4.08E-17 4.67E-15 4.96E-12 2.45E-11 2.72E-10 1.23E-09 2.48E-09 5.97E-07 2.02E-06 6.80E-04

[ [ [ [ [ [ [ [ [ Y [ Y [ [ [ [ [ [ [ Y [ [ Y [ Y [ [ [ [ Y [ Y [ [ [ [ [

a

The ratio of read counts in IL to that in CL. No read count was observed in IL. “[” denotes the upregulated miRNAs, and “Y” denotes the downregulated miRNAs. b c

Fold_changea p-Value

cfa-miR-92 9.12 cfa-miR-745b 15.34 cfa-miR-67 6.54 scaffold339-658238 6.54 cfa-miR-133-3p 7.88 cfa-miR-2d 6.88 cfa-miR-745a 11.86 cfa-miR-279 10.14 cfa-miR-1175-3p 9.92 cfa-miR-2c 9.44

5.46E-05 2.88E-06 1.85E-04 3.16E-02 1.06E-05 1.89E-04 1.49E-06 1.13E-04 4.67E-05 6.80E-04

Regulationb Significance levelc [ [ [ [ [ [ [ [ [ [

** ** ** * ** ** ** ** ** **

a Comparative Ct method was used to calculate the fold change between the infection and control samples. b “[” denotes the upregulated miRNAs, and “Y” denotes the downregulated miRNAs. c “**” and “*” denote a significant difference of p < 0.01 and p < 0.05, respectively.

on the number of reads gained [28,48,49]. A comparison of expression of expression profiles of conserved and novel miRNAs between small RNA libraries by a two-tailed Student t-test revealed that the expression patterns of 37 miRNAs (30 conserved miRNAs and 7 novel miRNAs) are altered by AVNV infection (Table 5). Among these altered miRNAs, 30 were upregulated and 7 were downregulated. In particular, the expression of three deduced novel miRNAs (scaffold1533-213741, C24718-2851, and scaffold40948-91902) in IL was suppressed. By contrast, highthroughput sequencing showed the tenfold increase of four conserved miRNAs in IL, namely, cfa-miR-92, cfa-miR-745b, cfamiR-745a, and cfa-miR-279. Real-time PCR is a direct method for the precise measurement of differentially expressed miRNAs [28,36]. Therefore, qRT-PCR assay was used to confirm the differentially expressed miRNAs between the control and infected hemocyte samples of C. farreri by selection of then upregulated miRNAs, namely, cfa-miR-92, cfa-miR-745b, cfa-miR-67, scaffold339-658238, cfa-miR-133-3p, cfa-miR-2d, cfamiR-745a, cfa-miR-279, cfa-miR-1175-3p, and cfa-miR-2c. The relative quantitative results are summarized in Table 6. All of the test miRNAs were upregulated, despite minor differences in fold change between deep sequencing analysis and qRT-PCR. In particular, a difference in significance level was detected only for scaffold339-658238. General consistency was observed between the results of quantitative assay and deep sequencing analysis for the ten miRNAs in terms of directions of regulation and significance. While the targets of the markedly altered miRNAs remain unknown, some of them have been suggested to be immune-related. For example, miR-92 expression, which is associated with associated with embryogenesis [50], oncogenesis, and cellular proliferation [51], is upregulated in West Nile virus-infected Cx. Quinquefasciatus. Significant higher expressions of miR-745b and miR-279 have been observed in white spot syndrome virusinfected Marsupenaeus japonicus [35] and S. eriocheiris-infected E. sinensis [36]. Given these findings, speculation that these miRNAs play roles in mediating host responses to viral and bacterial infection is reasonable. 3.5. Target gene prediction The activities of immune-related enzymes, such as acid phosphatase, the oxygen consumption rate, and the ammoniumnitrogen excretion rate were all enhanced significantly at early stages of AVNV infection [5,41]. Responsive proteins [38] and genes (unpublished data) in C. farreri against AVNV have also been determined. All of these results strongly suggest that interactions

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Table 7 Predicted target genes of differentially expressed miRNAs in C. farreri against AVNV. Genes

Accession no. of miRNA targets

Protein annotation

cfa-miR-981

FJ607953

Tumor necrosis factor receptor Alpha tubulin C-type lectin 5 Proline-rich transmembrane protein 1 Carboxypeptidase SAM pointed domaincontaining Ets transcription factor ATPase Hþ transporting lysosomal vacuolar proton pump S-adenosylmethionine synthetase isoform type-1 Predicted: malate dehydrogenase Cat eye syndrome critical region protein 5 Heat shock protein 90 Ribosomal protein S30 Kazal-type serine proteinase inhibitor Serine protease inhibitor1S Serine protease inhibitor1L Toll receptor Hypothetical protein CGI_10025387 17beta-hydroxysteroid dehydrogenase 4 Predicted: mitochondrial carrier homolog 2-like Latrophilin-2 Alpha macroglobulin Hypothetical protein CGI_10026131 C-type lectin B Cytochrome c oxidase subunit I DNA-binding protein inhibitor ID-2 Probable Bax inhibitor-1 Sigma class glutathione-stransferase 2 GST4 Probable Bax inhibitor-1 Hypothetical protein CGI Matrix metalloproteinase Nose resistant to fluoxetine protein 6 ATP synthase-like protein Dopamine beta hydroxylase Myosin VI Monocarboxylate transporter 12 Myostatin Translocon-associated protein subunit gamma Periodic tryptophan protein 2-like protein KRUEPPEL-like factor 15 Myosin VI Putative phosphopantothenate cysteine ligase C-type lectin C Serine/threonine-protein kinase RIO2 40S ribosomal protein SA Protein BTG1

AY395572 DT717228 DT716288

cfa-miR-96b

cfa-miR-96a

DT716304 DT716231

DT716770

DT716540 DT716562 DT716344 AY362761 DT718865 EU183309 DQ236244 DQ236243 DQ350772 DT718403 DT717880 DT716555 DT716121 AY395573 DT716455 cfa-miR-92

DQ209290 JK729625 DT716158

cfa-miR-745b

AF526247 GQ240292 EU183307 DT716098 DT716360 DQ080208 DT718080 DT718903 GU131142 DQ066721 DT716495 DQ988329 DT716168 DT718140

cfa-miR-67

DT716665 DQ066721 DT717253

DQ209291 DT718591

cfa-miR-1985

DT716437 DT716384

Table 7 (continued ) Genes

Accession no. of miRNA targets

Protein annotation

DT716530

S-adenosylhomocysteine hydrolase ETS-family transcription factor Beta-1,3galactosyltransferase 1 Serine protease CFSP3 Peptidyl-prolyl cis-trans isomerase B Thioester-containing protein

AY656697 DT716773 DT718320 DT719117 FJ848740 cfa-miR-190 cfa-miR-184

No hit DT718056 DT717026

DT717243 DT716577 DT718701 DT716077 DT717232 DT717219 JF273492 DT718479 DT716942 cfa-miR-183

DT716364 DT718957 DT717324 DT716369 EU935468 DT716482 DT718921 AY835660 DT717186 DT716887

cfa-miR-12 cfa-miR-10

DT716272 FJ848740 DQ452383 DT716599 DT718896 DT718701

scaffold339-59463

GU131146 DT717444

cfa-miR-182

DT716229 GQ227743 JN604668 DQ988329 DT718196 DT716562

DT716231

JK729499 DT716540 DT716121 DQ209290 DQ350772

Alkaline phosphatase Putative asparagine-linked glycosylation 1 log beta-14mannosyltransfer Tyrosinase Predicted: UPF0515 protein C19orf66 homolog Hypothetical protein BRAFLDRAFT_83370 Glutathione peroxidase 1 Arylsulfatase B 33 kDa inner dynein arm light chain, axonemal Vitellogenin variant Axonemal 84 kDa protein ADP-ribosylation factorlike protein 15 Thioredoxin Solute carrier family 15 member 4 Acyl-CoA dehydrogenase family member 10 Long-chain specific acylCoA dehydrogenase Cathepsin D Countin-1 Isoleucyl-tRNA synthetase Selenium-binding protein Solute carrier family 28 member 3 Microsomal glutathione-stransferase SCO-spondin like Thioester-containing protein Vasa Plastin-3 Deiodinase Hypothetical protein BRAFLDRAFT_83370 Nicotinic acetylcholine receptor Intraflagellar transport protein 80-like protein Aldose reductase Vitellogenin Deiodinase Myostatin Fructose-bisphosphate aldolase Predicted: malate dehydrogenase, mitochondrial-like SAM pointed domaincontaining Ets transcription factor Pyruvate kinase 2 S-adenosylmethionine synthetase isoform type-1 Latrophilin-2 C-type lectin B Toll receptor

G. Chen et al. / Fish & Shellfish Immunology 37 (2014) 75e86 Table 7 (continued ) Genes

Table 7 (continued ) Accession no. of miRNA targets

Protein annotation

EU183309

Kazal-type serine proteinase inhibitor Serine protease inhibitor1S Serine protease inhibitor1L Predicted: mitochondrial carrier homolog 2-like 17 beta hydroxysteroid dehydrogenase 4 Ribosomal protein S30 LPS-induced TNF-alpha factor Alpha macroglobulin Ribosomal protein S17 Beta-catenin S-adenosylmethionine synthetase isoform type-1 Periodic tryptophan protein 2-like protein Thyroid receptorinteracting protein 11 Eukaryotic translation initiation factor 3 subunit I Protein deltex-3-like protein Tropomyosin Hypothetical protein CGI_10006559 Perlucin 4 Profilin Leucine rich repeat containing protein 3 Leucine rich repeat containing protein Glycoprotein 3-alpha-Lfucosyltransferase A C-type lectin D1 C-type lectin D2 Cytosolic non-specific dipeptidase Caseinolytic peptidase Blike protein Glutamate-ammonia ligase Tumor necrosis factor receptor-associated factor 6 Vacuolar Hþ ATPase Regulator of microtubule dynamics protein 1 Hypothetical protein DAPPUDRAFT_67127 18S ribosomal RNA Goose-type lysozyme Arginine kinase Hypothetical protein CGI_10014468 Myostatin Histone H3 Small nuclear ribonucleoprotein polypeptide F Ester hydrolase C11orf54like protein Vasa Hypothetical protein CGI_10023584 Leucine rich repeat containing protein 2 Small nuclear ribonucleoprotein polypeptide F Heat shock 70 kDa protein 12A

DQ236244 DQ236243 DT716555 DT717880

cfa-miR-133-3p

DT716455 DT717389 AY395573 AY395570 DT718886 DT716540 DT718140 DT716228 DT716126 DT717983 DT716630 DT717306 DT716507 DT716624 DT716174 GQ240295 DT717573 DQ209292 DQ209293 DT716309 DT718982

cfa-miR-2d

83

DT716450 DQ350773 DT716354 DT716291 DT716632 AF526251 DQ227696 JN863297 DT718169 DQ988329 DQ407914 DT717130

DT717465 DQ452383 DT716199 GQ240294 DT717130

cfa-miR-315

DT717380

cfa-miR-216b

DT718296

Genes

Accession no. of miRNA targets

DT716261 DT716431 DT717940 cfa-miR-745a

DT719225 DT716217 AY206871 DT718766

scaffold37400-90107

DT716170 AY395573 DT716116 DT716278 DT717644 DT719116

DT716133 FJ848740 AY965263 DT719129 DT716565 DT716200 DT718140 DT717147 DT716155 DT716304 GQ240294 DT716201 DT716230 cfa-miR-2001

FJ516744 CN782372 jDT716300

DT716461 DQ852572 GR211386 GU131146 AF526248 DT718244 DT716104

cfa-miR-279

DT719226 AY362759 DT716344 DT717346

scaffold1533-213741

GU131146

Protein annotation Transcriptional activator protein Pur-alpha Cyclophilin-like protein Peptidase S1 and S6 chymotrypsin/Hap Hypothetical protein CGI_10005022 Stress response protein nhaX T-complex protein 1 subunit eta Heat shock protein 70 Predicted: ceruloplasminlike Histone H3 Alpha macroglobulin Endoglucanase Predicted: deoxycytidylate deaminase-like S-adenosylhomocysteine hydrolase Dolichyldiphosphooligosaccharideprotein glycosyltransferase subunit 2 Ribosomal protein S9 Thioester-containing protein Tryptophan 2,3dioxygenase Predicted: protein FAM32A-like Hypothetical protein CGI_10007269 Annexin A7 Periodic tryptophan protein 2-like protein Calmodulin-2 Alkyl/aryl-sulfatase BDS1 Hypothetical protein DAPPUDRAFT_224487 Leucine rich repeat containing protein 2 Cold shock domain protein Proteasome subunit alpha type-5 Estrogen receptor Ribosomal protein L3 Non-neuronal cytoplasmic intermediate filament protein Putative prohibitin-like protein Inhibitor protein kappa Blike protein Lipopolysaccharideinduced TNF-alpha factor Nicotinic acetylcholine receptor alpha subunit Ribosomal protein L4 DNA polymerase eta Nucleolar GTP-binding protein 1 Carboxypeptidase A1 Cyclophilin A Cat eye syndrome critical region protein 5 RNA-binding protein Nova1 Nicotinic acetylcholine receptor alpha subunit

DT716122 (continued on next page)

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Table 7 (continued ) Genes

Table 7 (continued ) Accession no. of miRNA targets

DT716106 DT718256 DQ452383 DT716086 cfa-miR-216a

EF199621 DQ418455.1 GQ240294.1

scaffold40680-90107

AF526250.1 DT716235 DT716398 DT718515 DT719050

cfa-miR-8 cfa-miR-750

No hit DT718989 DQ350772 DT717827 DT717198

cfa-miR-375

cfa-miR-1175-3p

C24718-2851

DT716218 AY206871 DT718587 DT716384 DT717228 DT719213 AY676311 DT717610 EU263907 DT716412 DT716187 DT716579 FJ848740

cfa-miR-1993 scaffold40948-91902

DT716264 AY653293 No hit DT716419

cfa-miR-124

DT717629

cfa-miR-31 cfa-miR-317

DT716143 DT718852 DT716068 DT716482 DT717289 DT717833 DT716337 GH736357 GU131145 DQ350773 DT716540 DT716223 DT716565

Protein annotation Leucine-rich repeats and immunoglobulin-like domains protein 3 Tryptophanyl-tRNA synthetase Hypothetical protein CGI_10004573 Vasa Predicted: uncharacterized protein LOC581977 Retrotransposon gypsy-like CFG1 Core histone gene cluster Leucine rich repeat containing protein 2 Ribosomal protein S20 Tropomyosin GST4 Hypothetical protein BRAFLDRAFT_87528 Hypothetical protein CGI_10013259 e Predicted: checkpoint protein HUS1-like Toll receptor Small ubiquitin-related modifier protein Non-specific lipid-transfer protein Hypothetical protein BRAFLDRAFT_115113 Heat shock protein 70 Cytochrome P450 Protein BTG1 C-type lectin 5 Annexin A7 C-type lectin Adenosylhomocysteinase A Allograft inflammatory factor-1 Sarcoplasmic calciumbinding protein GST3 Predicted: hypothetical protein Thioester-containing protein Ferritin 1 Ferritin CFA Hypothetical protein BRAFLDRAFT_124447 Estradiol 17-betadehydrogenase 8 Elongation factor 2 Calcyphosin-like protein Serine protease inhibitor Countin-1 Kinesin-related protein 1 Ribosomal protein S19 Proteasome subunit beta type-6 Acyl-CoA synthetase family member 2, mitochondrial Nicotinic acetylcholine receptor alpha subunit Tumor necrosis factor receptor-associated factor 6 S-adenosylmethionine synthetase Cytochrome c oxidase Hypothetical protein CGI_10007269

Genes

Accession no. of miRNA targets

Protein annotation

CO790309 DT718426

Ribosomal protein L4 Zinc-binding alcohol dehydrogenase domaincontaining protein 2 Predicted: cholesterol 24hydroxylase-like Ferritin CFA Arylsulfatase B Asparaginyl-tRNA synthetase Metallothionein Dolichyldiphosphooligosaccharide– protein glycosyltransferase subunit 2 Predicted: cadherin EGF LAG seven-pass G-type receptor 1 Tumor necrosis factor receptor-associated factor 6 Regulator of microtubule dynamics protein 1 Histone H3 Hypothetical protein CGI Myostatin Glutamine synthetase Serine protease inhibitor Serine protease inhibitor CFSPI3 Predicted: TRZ1 (TRNASE Z 1); 3-tRNA processing endoribonuclease-like Mechanosensory protein 2 Arginine kinase Mitochondrial-processing peptidase subunit alpha HBS1-like protein Aryl hydrocarbon receptor Ester hydrolase C11orf54like protein

DT718167 AY653293 DT717232 DT716550

scaffold1896-30954

DT716060 DT718480

DT716175

miR-2c

DQ350773 DT716291 DQ407914 DT718169 DQ988329/U563852 DT716450 DQ302098 DQ280151 DT716601

DT716302 JN863297 DT716951 DT717735 FJ588640 DT717465

between the host and pathogen become active upon AVNV infection. Similarly, differentially expressed miRNAs may play important roles in the AVNV response of scallop. miRNAs in animals are believed to bind target genes in the 30 untranslated region (30 -UTR) to regulate their expression [52,53]. However, binding to protein-coding regions may present another model for regulating gene expression [27]. To identify the potential targets of differentially expressed miRNAs, we searched unigene sequences from ESTs available in GenBank using miRanda because no 30 UTR database is yet available. Finally, 177 unigenes (Table 7) were identified as potential targets for AVNV-responsive miRNAs. In general, most of the miRNAs had up to 18 target genes, and many of them had common target genes, likely forming an intricate interaction network. Four miRNAs, namely, cfa-miR-96b, cfa-miR12, cfa-miR-315, and scaffold40948-91902, had only one target gene, whereas three miRNAs, including cfa-miR-190, cfa-miR-8, and cfa-miR-1993, did not appear to have target genes. Potential miRNAs that mediate genes can be classified into at least 13 categories based on their GO annotations of biological processes and molecular functions (Fig. 4 and Table 7). Among these genes, those coding immune- and stress response-related proteins were the most abundant, accounting for 10% of all of the target genes, second only to the genes involving lipid or carbohydrate transport and metabolism. These genes include allograft inflammatory factor-1, cathepsin D, C-type lectin, glutathione peroxidase 1, LPS-induced tumor necrosis factor (TNF)-alpha factor, stress response protein

G. Chen et al. / Fish & Shellfish Immunology 37 (2014) 75e86 Immune defense and stress response 10 %

Function unknown 11%

Ungrouped 8%

85

Posttranslational modification, protein turnover and chaperones 7%

Cellular protein metabolism 6%

Cell adhesion and signaling 4% Amino acid transport and metabolism 6%

Lipid/carbohydrate transport and metabolism 17%

Cell proliferation and apoptosis 2% Translation, ribosomal structure and biogenesis Transcription 7% regulation and RNA processing 7%

Development and cell differentiation 2%

Cytoskeleton 6%

DNA replication and repair 2%

Inorganic ion transport and metabolism 5%

Fig. 4. Functional classification of the predicted target genes.

nhaX, Toll receptor, TNF receptor-associated factor (TRAF) and TNF receptor associated protein, TNF receptor, and TRAF 6. These results indicated that miRNAs play important roles in the immune regulation of scallop against AVNV. Some predicted targets obtained by searching against ESTs of C. farreri show high false positive rates for two reasons: (1) none of the present bioinformatics tools, including miRanda, can predict miRNA targets accurately because of the complicated interaction mechanism between miRNA and their target transcript, and (2) most miRNAs target the 30 UTR sequences of mRNAs in animals so prediction of the targets of C. farreri miRNAs without a complete 30 UTR database is difficult to achieve. As such, validation of the relationship between miRNAs and mRNA transcripts expressed differentially between the control and infected hemocyte samples needs more experimental evidence using other methods, such as qRT-PCR, to achieve conclusive results. Acknowledgments This work was supported by the Basic research of Harbin Institute of Technology outstanding talents cultivation plan of class III, Modern Agro-industry Technology Research System of China (Grant nycytx-47), the Research and Development Special Fund for Public Welfare Industry (Agriculture) of China (Grant nyhyzx07047), Technology and Development Program of Weihai (IMJQ01110013). References [1] Song WB, Wang CM, Wang XH, Li Y, Li J. New research progress on massive mortality of cultured scallop Chlamys farreri. Mar Sci 2001;25:23e6. [2] Wang CM, Wang XH, Ai HX, Li Y, He GZ, Huang JY, et al. The viral pathogen of massive mortality in Chlamys farreri. J Fish China 2004;28:547e53. [3] Wang CM, Wang XH, Song XL, Huang J, Song WB. Purification and ultrastructure of a spherical virus in cultured scallop Chlamys farreri. J Fish China 2002;26:180e4. [4] Wang XH, Wang CM, Li J, Wang XH, Zheng GL, Hu XZ, et al. Epidemiological study on massive death of the cultured scallop Chlamys farreri in the Jiaozhou Bay. J Fish China 2002;26:149e55.

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