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MicroRNA profile analysis of a feline kidney cell line before and after infection with mink enteritis virus
Gene 539 (2014) 224–229
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Gene journal homepage: www.elsevier.com/locate/gene
MicroRNA profile analysis of a feline kidney cell line before and after infection with mink enteritis virus Jia-zeng Sun, Jigui Wang, Shuang Wang, Daoli Yuan, Basse Mame Birame, Zhili Li, Bao Yi, Weiquan Liu ⁎ State Key Laboratory of Agrobiotechnology, Department of Biochemistry and Molecular Biology, College of Biological Sciences, China Agricultural University, Beijing 100193, China
a r t i c l e
i n f o
Article history: Received 28 October 2013 Received in revised form 19 December 2013 Accepted 28 January 2014 Available online 11 February 2014 Keywords: Feline kidney (F81) cell line Mink enteritis virus (MEV) MicroRNA
a b s t r a c t MicroRNAs (miRNAs) are small regulatory RNAs that play a significant role in eukaryotes by targeting mRNAs for cleavage or translational repression. Recent studies have also shown them to be associated with cellular changes following viral infection. Mink enteritis virus (MEV) is one of the most important viral pathogens in the mink industry. To study the involvement of miRNAs in the MEV infection process, we used Illumina's ultrahigh throughput approach to sequencing miRNA libraries from the feline kidney (F81) cell line before and after infection with MEV. Using this bioinformatics approach we identified 196 known mammalian miRNA orthologs belonging to 152 miRNA families in F81 cells. Additionally, 97 miRNA*s of these miRNAs were detected. As well as known miRNAs, 384 and 398 novel miRNA precursor candidates were identified in uninfected and MEV-infected F81 cells respectively that have not been reported in other mammals. In MEV-infected cells 3 miRNAs were significantly down-regulated and 4 up-regulated including 3 significantly. The majority (12 of 16) of randomly selected miRNA expression profiles by qRT-PCR were consistent with those identified by deep sequencing. A total of 88 miRNAs were predicted to target interferon-associated genes; 6 appear to target the 3′UTR of MEV-specific receptor transferring receptor mRNAs; and 8 to target the MEV mRNA coding region. No miRNAs coded by MEV itself were detected. © 2014 Elsevier B.V. All rights reserved.
1. Introduction MiRNAs are endogenous small RNAs of about 22 nucleotides (nt) that regulate gene expression by sequence-specific targeting of the 3′ UTR of mRNAs in the RNA-induced silencing complex. They can affect many cellular functions, such as proliferation, hematopoiesis and development of the nervous system (Ambros, 2004; Bartel, 2007; Krol et al., 2010). Recent studies have also focused on the role of miRNAs as modulators of host cell-virus interaction networks (Scaria et al., 2006). Evidence suggests that not only host cells but also viruses can encode miRNAs (Lei et al., 2010; Lu et al., 2010; Song et al., 2010). Since propagation of a virus is highly dependent on its host cell, the complex cellular regulatory network can have a major effect on viral replication. Cellular regulators such as miRNAs play a role in the self-protection process (Lagos et al., 2010). To combat these, some viruses respond via a Abbreviations: miRNA, microRNA; F81 cell line, feline kidney cell line; MEV, mink enteritis virus; nt, nucleotides; MEM, minimum essential medium; C3, uninfected cells; V3, virus-infected cells; PAGE, polyacrylamide gel electrophoresis; U, uridine; G, guanine; qRT-PCR, quantitative RT-PCR. ⁎ Corresponding author at: State Key Laboratory of Agrobiotechnology, Department of Biochemistry and Molecular Biology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China. Tel.: +86 10 62732676. E-mail address: [email protected] (W. Liu).
http://dx.doi.org/10.1016/j.gene.2014.01.074 0378-1119/© 2014 Elsevier B.V. All rights reserved.
miRNA–mRNA cross-talk function (Grey et al., 2010). The study of miRNA-mediated host-virus interactions therefore contribute to an understanding of the mechanism of virus infection and host counteraction. Mink enteritis virus (MEV) is one of the most important viral pathogens in the mink industry. It is a single stranded DNA virus of the genus Parvovirus with a genome of about 5 kb (Zhang, 1997), both ends of which contain hairpin structures. The genome is comprised mainly of 2 open reading frames, the left coding for proteins NS1 and NS2 and the right for VP1 and VP2. VP2 is the major structural protein of the virion; NS1 is the main non-structural one. MEV infection results in a high rate of morbidity and mortality, exhibits a rapid clinical course and can spread rapidly (Rivera et al., 1987; Schofield, 1949; Zuo et al., 2010). Vaccines have been developed to prevent spread of the disease within animal facilities (Barker et al., 1983; Horiuchi et al., 1997; Langeveld et al., 1995; Parrish et al., 1982; Zhang, 1997). Little research has been done using domestic cats (Felis catus) as an experimental animal or a source of cell cultures. The entire feline genome has, however, been sequenced (Pontius and O'Brien, 2007; Pontius et al., 2007). With this as a basis, therefore, our first aim was to construct a repertoire of miRNAs expressed in the F81 cell line, and to use this to study the responses of the latter to MEV infection. We utilized Illumina's ultrahigh throughput approach to sequencing and analysis of two miRNA libraries, from uninfected and MEV-infected cells.
J. Sun et al. / Gene 539 (2014) 224–229
2. Materials and methods
225
Table 1 Primer sequences for miRNA qRT-PCR.
2.1. Virus and cells MEV strain L (MEV-L) is a strain of MEV originally isolated from an infected mink in a mink farm, Liaoning province, China. The entire genome has been sequenced in our laboratory and found to be highly homologous with MEV strain Abashiri (GenBank accession, D00765.1). F81 cells are feline kidney cells, obtained from the American Type Culture Collection (ATCC). For construction of small RNA libraries, F81 cells were cultured in 6-well plastic dishes (Costar) in minimum essential medium (MEM) (GIBCO, CA) containing 10% FBS (Hyclone, Logan, UT) and 1% penicillin–streptomycin (GIBCO, CA) at 37 °C in a 5% CO2 atmosphere. Three wells of a dish were infected with MEV-L at an m.o.i. of 1 pfu/cell: the other 3 were left uninfected. At 24 h postinfection, virus-infected (V3) and uninfected (C3) cells were pooled separately for the following total RNA extraction.
2.2. Small RNA ultrahigh throughput sequencing and analysis of sequencing data (Glazov et al., 2008) 2.2.1. RNA preparation Total RNAs of C3 and V3 samples were isolated using TRIzol reagent (Invitrogen) according to the manufacturer's instructions, and quantitated by Nanodrop 2000 (Thermo). Two RNA samples were subjected to polyacrylamide gel electrophoresis (PAGE) for isolation of molecules of 18–30 nt length.
2.2.2. Small RNA library construction and sequencing Small (18–30 nt) RNAs of each library, prepared from 10 μg of each RNA sample, were submitted to Solexa (Illumina Inc.) for the following sequencing. Proprietary adapters were ligated to both ends of the small RNA samples which were then transcribed to cDNA and amplified by 18 PCR cycles to produce sequencing libraries that were subjected to Solexa's proprietary sequencing-by-synthesis procedure.
2.2.3. Mapping the Solexa reads onto the feline genome Adapter sequences were removed from both ends of the reads. All identical sequences were counted and duplication eliminated. The resulting set of unique sequences with associated read counts, referred to as sequence tags, were mapped onto the feline genome (Pontius and O'Brien, 2007; Pontius et al., 2007) using the program Short Oligonucleotide Analysis Package (SOAP) (Li et al., 2008).
2.2.4. Known miRNA identification Perfectly matched reads were mapped onto miRNAs of six reference species (Homo sapiens, Canis familiaris, Mus musculus, Rattus norvegicus, Bos taurus and Sus scrofa) of the Sanger miRBase (Release 18) using the program Patscan (Bland et al., 2007).
Primer names
Sequences (5′–3′)
U6 F U6 R universal adapter miR-181a miR-181b miR-181c miR-181d miR-23a miR-99a miR-99b miR-301 miR-26a miR-26b miR-21 miR-29a miR-29b miR-125b miR-320a miR-140
CTCGCTTCGGCAGCACA AACGCTTCACGAATTTGCGT GCGAGCACAGAATTAATACGACTCAC GCGAGCACAGAATTAATACGACTCACTATAGGTTTTTTTTTTTTVN AACATTCAACGCTGTCGGTGAGTA AACATTCATTGCTGTCGGTGGG AACATTCAACCTGTCGGTGAGTAAA AACATTCATTGTTGTCGGTGGGTA ATCACATTGCCAGGGATTTCCA AACCCGTAGATCCGATCTTGTGAA CACCCGTAGAACCGACCTTGC CGCAGTGCAATAGTATTGTCAAAGC CGGTTCAAGTAATCCAGGATAGGCT CGCGTTCAAGTAATTCAGGATAGGTA CGCGTAGCTTATCAGACTGATGTTG CGTAGCACCATCTGAAATCGGTTA CGTAGCACCATTTGAAATCAGTGTTA TCCCTGAGACCCTAACTTGTGAAAA AAAAGCGGGGAGAGGGCG CAGTGGTTTTACCCTATGGTAGAAA
2.2.5. Prediction and annotation of known miRNA targets Targetscan (Lewis et al., 2005) software was used for prediction and annotation of known miRNA targets in the reference species.
2.2.6. Novel miRNA prediction To avoid repeated prediction and to reduce the amount of calculations, we then searched against the genome and combined candidate unique reads whose distance in the reference genome was less than 100 bp. The 100 nt upstream and downstream sequences of the unique reads were included for secondary structure analysis. RNAfold (Hofacker, 2003) software was used to find inverted repeats. Unique reads in the inverted repeats were evaluated by miReap and mirCheck (Jones-Rhoades and Bartel, 2004) using modified parameters.
2.2.7. Prediction of miRNA targets of MEV and its specific receptor RNAhybrid (Krueger and Rehmsmeier, 2006) was used to predict miRNA targets of MEV and its specific receptor following the rules of no mismatch and G/U complementarity in miRNA seed sequences.
2.3. Quantitative RT-PCR (qRT-PCR) of miRNAs Total RNAs of the two samples were extracted and quantitated as described above, then polyadenylated using polyA polymerase (NEB) and reverse-transcribed using adapter primers with MLV reverse transcriptase (TaKaRa) (Yang et al., 2010). Selected miRNAs were subjected to qRT-PCR using Fast SYBR Green Mix (CWBIO) with ABI ViiA7. U6 small RNA was used as an internal control. Three independent biological replicates were conducted. All primers used are listed in Table 1.
Table 2 Small RNA signatures that match various RNAs. Type
C3
Percent of total reads
V3
Percent of total reads
Total reads Low quality Adaptor3 null Insert null 5′ adaptor contaminants Size b 18 nt polyA Clean.txt, size N = 18 nt
6591749 71327 4642 154726 2605 55872 1151 6301426
100% 1.08% 0.07% 2.37% 0.04% 0.86% 0.02% 96.64%
7553048 95029 2886 60710 3151 237390 182 7153700
100% 1.26% 0.04% 0.81% 0.04% 3.18% 0.00% 95.92%
C3, uninfected F81 cells; V3, MEV-infected F81 cells.
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3. Results and discussion To facilitate analysis of the vast sequencing data, the C3 and V3 libraries were sorted to tag-unique sequences according to alignment rules. These unique tags were mapped onto the feline and MEV reference genomes (Kariatsumari et al., 1991; Pontius and O'Brien, 2007; Pontius et al., 2007). As expected, most of the mapped sequence tags derived from the feline genome and only a small fraction (b0.5%) mapped onto the MEV genome. To identify the miRNAs involved in both C3 and V3, small RNA libraries from the two samples were sequenced side by side using the Illumina platform. The statistics of the small RNA sequences from the two libraries are summarized in Tables 2 and 3 and Fig. 1. A total of 6,591,749 and 7,553,048 raw reads were obtained from C3 and V3, respectively. After removing low quality sequences, adapter sequences, and sequences smaller than 18 nt, the remaining clean reads from the two libraries were aligned to the feline genome. A total of 6,301,426 (C3) and 7,153,700 (V3) clean reads were perfectly matched to the feline genome, F. catus (GenBank assembly ID: GCA_000181335.2). Sizes of the small RNAs were not evenly distributed in both libraries; however, overall size distribution of the sequenced reads from the two sequencing sets was very similar. Most (75%) of the small RNAs from both libraries were 21–23 nt in length, with 22 nt being the most abundant (Fig. 1). This result is consistent with recent reports in other mammals (Ahn et al., 2010; Friedlaender et al., 2008; Landgraf et al., 2007; Lui et al., 2007; Qiu et al., 2009; Strozzi et al., 2009).
Fig. 1. Length distribution and abundance of small RNAs from C3 and V3 libraries.
has been assumed that the 5′ terminal nucleotide reflects the biogenesis mechanism for miRNAs (Mi et al., 2008). Notably, guanine (G) was not the favored first base in 18–25 nt length miRNAs and miRNA*s in this study. The endogenous miRNAs exhibited significant base bias, especially in 19–23 nt miRNAs and miRNA*s (Fig. 5). Although the identified conserved miRNA families in C3 and V3 showed similarities in several aspects, significant differences existed as shown in the following results.
3.1. Feline orthologs of known mammalian miRNAs 3.2. Newly identified miRNAs Conserved miRNA families are found in many vertebrate species and have important functions in vertebrate development. To identify conserved miRNAs in our dataset, all small RNA sequences were searched for alignment with known mature miRNAs and miRNA*s of H. sapiens, C. familiaris, M. musculus, R. norvegicus, B. taurus and S. scrofa in the miRNA database miRBase 18.0. There were 152 families containing 196 known miRNAs and 97 miRNA*s in both libraries (Supplemental Table S1). Aligning small RNA sequences to known miRNAs and miRNA*s resulted in 3,249,086 and 2,649,794 matches for C3 and V3, respectively. The statistics of the conserved miRNA families in C3 and V3 are listed in Supplemental Table S2. Conserved miRNAs from C3 and V3 had the following features. First, 256 miRNAs and miRNA*s were identified in both libraries, with 16 C3-specific and 21 V3-specific (Fig. 2). The conserved miRNA families in both libraries showed a similar distribution but with a few differences. The most abundant miRNAs were miR-21, let-7c, miR-29a, miR-125b, let-7g, miR-29c, let-7i, miR221, miR-23a and miR-19a in the C3 library and miR-29a, miR-21, miR-125b, miR-29c, miR-23a, miR-93 and miR-320a in V3 (Figs. 3 and 4). A first nucleotide bias analysis of the 292 known miRNAs and miRNA*s in both libraries (18–25 nt) is presented in Fig. 5. The miRNAs and miRNA*s possessed different biases. Uridine (U) dominated the first position of the known miRNAs and miRNA*s of 21 and 22 nt length. It
Release 18.0 of miRBase lists 1527 precursors and 1921 mature miRNAs in the human database although there are likely many more. Some common features of miRNAs have been explored and different miRNA prediction programs have been developed to predict novel miRNAs. Several studies have shown that miRNA precursors can fold into inverted repeat stemloop hairpin secondary structures and have low folding free energy, the latter being considered an important characteristic of miRNAs (Bonnet et al., 2004). Following these criteria, inverted repeat secondary structures were predicted using RNAfold (Hofacker, 2003) and unique reads within these were identified by miReap and mirCheck (Jones-Rhoades and Bartel, 2004). Based on these criteria, 384 and 398 novel miRNAs were predicted from C3 and V3 respectively (Supplemental Tables S3 and S4). We also mapped to the feline genome and identified the positions of the novel miRNAs in the chromosomes. The novel precursor miRNA candidates with secondary structures and the copy numbers of mature miRNAs are listed in Supplemental Tables S3 and S4. More than half began with 5′ U, which is a characteristic feature of miRNAs (Bonnet et al., 2004; Zhang et al., 2006).
Table 3 Length distribution of small RNA. Length (nt)
C3
Percent
V3
Percent
18 19 20 21 22 23 24 25 26 27 28
89166 144312 244415 780866 3168988 1409484 319155 93947 34717 12845 4682
1.41% 2.29% 3.88% 12.39% 50.28% 22.36% 5.06% 1.49% 0.55% 0.20% 0.07%
339581 414041 479756 1003112 3207541 1196334 366204 103180 32704 9260 2169
4.75% 5.79% 6.71% 14.02% 44.84% 16.72% 5.12% 1.44% 0.46% 0.13% 0.03%
C3, uninfected F81 cells; V3, MEV-infected F81 cells.
Fig. 2. Comparison of known miRNAs between C3 and V3 libraries.
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Fig. 3. Relative abundance of miRNAs in C3 library based. TPM: tags per million; i.e., miRNA reads number/million total reads.
3.3. Computational analysis validating the miRNA targets and mRNAs To assess the function of the miRNAs in C3 and V3, putative targets of miRNAs were predicted using Targetscan software (Lewis et al., 2005) according to reference species program. Selection of genes with possible antiviral functional roles, such as interferon and interferon related genes, was predicted to contain a few miRNA candidate targets (Supplemental
Table S5). Using RNAhybrid (Krueger and Rehmsmeier, 2006) and following the rules of no mismatch and G/U complementarity in miRNAs seed sequences, 8 miRNAs (miR-130, miR-148, miR-362, miR-454 and miR-181) were predicted to target MEV mRNA (Fig. S1) and 6 (miR320, miR-140, miR-145, miR-152 miR-182 and miR-194) were predicted to target MEV receptor-transferrin receptor mRNA (Fig. S2). These miRNAs may play a role in the process of MEV infection.
Fig. 4. Relative abundance of miRNAs in V3 library based. TPM: tags per million; i.e., miRNA reads number/million total reads.
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Fig. 5. The first nucleotide bias of known miRNAs of 18–25 nt length.
families in feline kidney (F81) cells with 97 miRNA*s of the miRNAs also being detected. In addition, 384 and 398 miRNA precursor candidates that have not been reported in other mammals were identified in uninfected and MEV-infected F81 cells respectively. Although these new miRNA precursor candidates mapped to the feline genome and had the predicted secondary structure, future verification is required to ensure their authenticity. Data analyses were performed to identify miRNAs with different expression levels in the two libraries and the results were partially validated by qRT-PCR. Results showed that MEV infection resulted in changes in miRNA expression profiles in F81 cells. Some miRNAs were predicted to target genes involved in MEV infection. In summary, we studied a repertoire of F81 cell line miRNAs expressed in uninfected cells or following MEV infection, and have performed a preliminary analysis of the functions of these miRNAs. These data provide a foundation for further investigations on host and virus interaction. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2014.01.074.
3.4. Validation of miRNAs Conflict of interest To validate conserved predicted miRNAs, qRT-PCR was performed on 16 randomly selected miRNAs in C3 and V3 libraries. Fig. 6 shows that 3 (miR-181b, miR-181d and miR-301) were significantly downregulated, and 4 (miR-29b, miR-125b, miR-320a and miR-140) upregulated including 3 (miR-29b, miR-125b and miR-320a) significantly. It seems likely that these 7 miRNAs have some function in MEV infection. The majority (12 of 16) of the randomly selected miRNA expression profiles by qRT-PCR were consistent with those obtained by deep sequencing. 3.5. Absence of MEV derived miRNA From the V3 library, 20 small unique RNAs were mapped to the MEV genome; however, no miRNA was identified using miReap software prediction. These results indicate that MEV does not encode miRNA. A possible reason is that, as a very small DNA virus with a genome of only about 5 kb, MEV must make highly efficient use of its available coding capacity. A functional non-coding RNA would not be an effective use of such a genome. 4. Conclusions Using Illumina's ultrahigh throughput approach we have identified 196 known mammalian miRNA orthologs belonging to 152 miRNA
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Fig. 6. qRT-PCR of miRNAs in C3 and V3 libraries. Expression of selected miRNAs in the F81 cell line infected with MEV (V3) or uninfected (C3) was tested for validity by qRT-PCR using a specific primer for each miRNA. Fold increase/decrease was calculated based on U6 endogenous control normalization. Data are from 3 independent experiments (mean ± SD). Statistical significance was analyzed by Student's t test; *P b 0.05; **P b 0.01; ***P b 0.001.
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Contents lists available at ScienceDirect
Gene journal homepage: www.elsevier.com/locate/gene
MicroRNA profile analysis of a feline kidney cell line before and after infection with mink enteritis virus Jia-zeng Sun, Jigui Wang, Shuang Wang, Daoli Yuan, Basse Mame Birame, Zhili Li, Bao Yi, Weiquan Liu ⁎ State Key Laboratory of Agrobiotechnology, Department of Biochemistry and Molecular Biology, College of Biological Sciences, China Agricultural University, Beijing 100193, China
a r t i c l e
i n f o
Article history: Received 28 October 2013 Received in revised form 19 December 2013 Accepted 28 January 2014 Available online 11 February 2014 Keywords: Feline kidney (F81) cell line Mink enteritis virus (MEV) MicroRNA
a b s t r a c t MicroRNAs (miRNAs) are small regulatory RNAs that play a significant role in eukaryotes by targeting mRNAs for cleavage or translational repression. Recent studies have also shown them to be associated with cellular changes following viral infection. Mink enteritis virus (MEV) is one of the most important viral pathogens in the mink industry. To study the involvement of miRNAs in the MEV infection process, we used Illumina's ultrahigh throughput approach to sequencing miRNA libraries from the feline kidney (F81) cell line before and after infection with MEV. Using this bioinformatics approach we identified 196 known mammalian miRNA orthologs belonging to 152 miRNA families in F81 cells. Additionally, 97 miRNA*s of these miRNAs were detected. As well as known miRNAs, 384 and 398 novel miRNA precursor candidates were identified in uninfected and MEV-infected F81 cells respectively that have not been reported in other mammals. In MEV-infected cells 3 miRNAs were significantly down-regulated and 4 up-regulated including 3 significantly. The majority (12 of 16) of randomly selected miRNA expression profiles by qRT-PCR were consistent with those identified by deep sequencing. A total of 88 miRNAs were predicted to target interferon-associated genes; 6 appear to target the 3′UTR of MEV-specific receptor transferring receptor mRNAs; and 8 to target the MEV mRNA coding region. No miRNAs coded by MEV itself were detected. © 2014 Elsevier B.V. All rights reserved.
1. Introduction MiRNAs are endogenous small RNAs of about 22 nucleotides (nt) that regulate gene expression by sequence-specific targeting of the 3′ UTR of mRNAs in the RNA-induced silencing complex. They can affect many cellular functions, such as proliferation, hematopoiesis and development of the nervous system (Ambros, 2004; Bartel, 2007; Krol et al., 2010). Recent studies have also focused on the role of miRNAs as modulators of host cell-virus interaction networks (Scaria et al., 2006). Evidence suggests that not only host cells but also viruses can encode miRNAs (Lei et al., 2010; Lu et al., 2010; Song et al., 2010). Since propagation of a virus is highly dependent on its host cell, the complex cellular regulatory network can have a major effect on viral replication. Cellular regulators such as miRNAs play a role in the self-protection process (Lagos et al., 2010). To combat these, some viruses respond via a Abbreviations: miRNA, microRNA; F81 cell line, feline kidney cell line; MEV, mink enteritis virus; nt, nucleotides; MEM, minimum essential medium; C3, uninfected cells; V3, virus-infected cells; PAGE, polyacrylamide gel electrophoresis; U, uridine; G, guanine; qRT-PCR, quantitative RT-PCR. ⁎ Corresponding author at: State Key Laboratory of Agrobiotechnology, Department of Biochemistry and Molecular Biology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing 100193, China. Tel.: +86 10 62732676. E-mail address: [email protected] (W. Liu).
http://dx.doi.org/10.1016/j.gene.2014.01.074 0378-1119/© 2014 Elsevier B.V. All rights reserved.
miRNA–mRNA cross-talk function (Grey et al., 2010). The study of miRNA-mediated host-virus interactions therefore contribute to an understanding of the mechanism of virus infection and host counteraction. Mink enteritis virus (MEV) is one of the most important viral pathogens in the mink industry. It is a single stranded DNA virus of the genus Parvovirus with a genome of about 5 kb (Zhang, 1997), both ends of which contain hairpin structures. The genome is comprised mainly of 2 open reading frames, the left coding for proteins NS1 and NS2 and the right for VP1 and VP2. VP2 is the major structural protein of the virion; NS1 is the main non-structural one. MEV infection results in a high rate of morbidity and mortality, exhibits a rapid clinical course and can spread rapidly (Rivera et al., 1987; Schofield, 1949; Zuo et al., 2010). Vaccines have been developed to prevent spread of the disease within animal facilities (Barker et al., 1983; Horiuchi et al., 1997; Langeveld et al., 1995; Parrish et al., 1982; Zhang, 1997). Little research has been done using domestic cats (Felis catus) as an experimental animal or a source of cell cultures. The entire feline genome has, however, been sequenced (Pontius and O'Brien, 2007; Pontius et al., 2007). With this as a basis, therefore, our first aim was to construct a repertoire of miRNAs expressed in the F81 cell line, and to use this to study the responses of the latter to MEV infection. We utilized Illumina's ultrahigh throughput approach to sequencing and analysis of two miRNA libraries, from uninfected and MEV-infected cells.
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2. Materials and methods
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Table 1 Primer sequences for miRNA qRT-PCR.
2.1. Virus and cells MEV strain L (MEV-L) is a strain of MEV originally isolated from an infected mink in a mink farm, Liaoning province, China. The entire genome has been sequenced in our laboratory and found to be highly homologous with MEV strain Abashiri (GenBank accession, D00765.1). F81 cells are feline kidney cells, obtained from the American Type Culture Collection (ATCC). For construction of small RNA libraries, F81 cells were cultured in 6-well plastic dishes (Costar) in minimum essential medium (MEM) (GIBCO, CA) containing 10% FBS (Hyclone, Logan, UT) and 1% penicillin–streptomycin (GIBCO, CA) at 37 °C in a 5% CO2 atmosphere. Three wells of a dish were infected with MEV-L at an m.o.i. of 1 pfu/cell: the other 3 were left uninfected. At 24 h postinfection, virus-infected (V3) and uninfected (C3) cells were pooled separately for the following total RNA extraction.
2.2. Small RNA ultrahigh throughput sequencing and analysis of sequencing data (Glazov et al., 2008) 2.2.1. RNA preparation Total RNAs of C3 and V3 samples were isolated using TRIzol reagent (Invitrogen) according to the manufacturer's instructions, and quantitated by Nanodrop 2000 (Thermo). Two RNA samples were subjected to polyacrylamide gel electrophoresis (PAGE) for isolation of molecules of 18–30 nt length.
2.2.2. Small RNA library construction and sequencing Small (18–30 nt) RNAs of each library, prepared from 10 μg of each RNA sample, were submitted to Solexa (Illumina Inc.) for the following sequencing. Proprietary adapters were ligated to both ends of the small RNA samples which were then transcribed to cDNA and amplified by 18 PCR cycles to produce sequencing libraries that were subjected to Solexa's proprietary sequencing-by-synthesis procedure.
2.2.3. Mapping the Solexa reads onto the feline genome Adapter sequences were removed from both ends of the reads. All identical sequences were counted and duplication eliminated. The resulting set of unique sequences with associated read counts, referred to as sequence tags, were mapped onto the feline genome (Pontius and O'Brien, 2007; Pontius et al., 2007) using the program Short Oligonucleotide Analysis Package (SOAP) (Li et al., 2008).
2.2.4. Known miRNA identification Perfectly matched reads were mapped onto miRNAs of six reference species (Homo sapiens, Canis familiaris, Mus musculus, Rattus norvegicus, Bos taurus and Sus scrofa) of the Sanger miRBase (Release 18) using the program Patscan (Bland et al., 2007).
Primer names
Sequences (5′–3′)
U6 F U6 R universal adapter miR-181a miR-181b miR-181c miR-181d miR-23a miR-99a miR-99b miR-301 miR-26a miR-26b miR-21 miR-29a miR-29b miR-125b miR-320a miR-140
CTCGCTTCGGCAGCACA AACGCTTCACGAATTTGCGT GCGAGCACAGAATTAATACGACTCAC GCGAGCACAGAATTAATACGACTCACTATAGGTTTTTTTTTTTTVN AACATTCAACGCTGTCGGTGAGTA AACATTCATTGCTGTCGGTGGG AACATTCAACCTGTCGGTGAGTAAA AACATTCATTGTTGTCGGTGGGTA ATCACATTGCCAGGGATTTCCA AACCCGTAGATCCGATCTTGTGAA CACCCGTAGAACCGACCTTGC CGCAGTGCAATAGTATTGTCAAAGC CGGTTCAAGTAATCCAGGATAGGCT CGCGTTCAAGTAATTCAGGATAGGTA CGCGTAGCTTATCAGACTGATGTTG CGTAGCACCATCTGAAATCGGTTA CGTAGCACCATTTGAAATCAGTGTTA TCCCTGAGACCCTAACTTGTGAAAA AAAAGCGGGGAGAGGGCG CAGTGGTTTTACCCTATGGTAGAAA
2.2.5. Prediction and annotation of known miRNA targets Targetscan (Lewis et al., 2005) software was used for prediction and annotation of known miRNA targets in the reference species.
2.2.6. Novel miRNA prediction To avoid repeated prediction and to reduce the amount of calculations, we then searched against the genome and combined candidate unique reads whose distance in the reference genome was less than 100 bp. The 100 nt upstream and downstream sequences of the unique reads were included for secondary structure analysis. RNAfold (Hofacker, 2003) software was used to find inverted repeats. Unique reads in the inverted repeats were evaluated by miReap and mirCheck (Jones-Rhoades and Bartel, 2004) using modified parameters.
2.2.7. Prediction of miRNA targets of MEV and its specific receptor RNAhybrid (Krueger and Rehmsmeier, 2006) was used to predict miRNA targets of MEV and its specific receptor following the rules of no mismatch and G/U complementarity in miRNA seed sequences.
2.3. Quantitative RT-PCR (qRT-PCR) of miRNAs Total RNAs of the two samples were extracted and quantitated as described above, then polyadenylated using polyA polymerase (NEB) and reverse-transcribed using adapter primers with MLV reverse transcriptase (TaKaRa) (Yang et al., 2010). Selected miRNAs were subjected to qRT-PCR using Fast SYBR Green Mix (CWBIO) with ABI ViiA7. U6 small RNA was used as an internal control. Three independent biological replicates were conducted. All primers used are listed in Table 1.
Table 2 Small RNA signatures that match various RNAs. Type
C3
Percent of total reads
V3
Percent of total reads
Total reads Low quality Adaptor3 null Insert null 5′ adaptor contaminants Size b 18 nt polyA Clean.txt, size N = 18 nt
6591749 71327 4642 154726 2605 55872 1151 6301426
100% 1.08% 0.07% 2.37% 0.04% 0.86% 0.02% 96.64%
7553048 95029 2886 60710 3151 237390 182 7153700
100% 1.26% 0.04% 0.81% 0.04% 3.18% 0.00% 95.92%
C3, uninfected F81 cells; V3, MEV-infected F81 cells.
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3. Results and discussion To facilitate analysis of the vast sequencing data, the C3 and V3 libraries were sorted to tag-unique sequences according to alignment rules. These unique tags were mapped onto the feline and MEV reference genomes (Kariatsumari et al., 1991; Pontius and O'Brien, 2007; Pontius et al., 2007). As expected, most of the mapped sequence tags derived from the feline genome and only a small fraction (b0.5%) mapped onto the MEV genome. To identify the miRNAs involved in both C3 and V3, small RNA libraries from the two samples were sequenced side by side using the Illumina platform. The statistics of the small RNA sequences from the two libraries are summarized in Tables 2 and 3 and Fig. 1. A total of 6,591,749 and 7,553,048 raw reads were obtained from C3 and V3, respectively. After removing low quality sequences, adapter sequences, and sequences smaller than 18 nt, the remaining clean reads from the two libraries were aligned to the feline genome. A total of 6,301,426 (C3) and 7,153,700 (V3) clean reads were perfectly matched to the feline genome, F. catus (GenBank assembly ID: GCA_000181335.2). Sizes of the small RNAs were not evenly distributed in both libraries; however, overall size distribution of the sequenced reads from the two sequencing sets was very similar. Most (75%) of the small RNAs from both libraries were 21–23 nt in length, with 22 nt being the most abundant (Fig. 1). This result is consistent with recent reports in other mammals (Ahn et al., 2010; Friedlaender et al., 2008; Landgraf et al., 2007; Lui et al., 2007; Qiu et al., 2009; Strozzi et al., 2009).
Fig. 1. Length distribution and abundance of small RNAs from C3 and V3 libraries.
has been assumed that the 5′ terminal nucleotide reflects the biogenesis mechanism for miRNAs (Mi et al., 2008). Notably, guanine (G) was not the favored first base in 18–25 nt length miRNAs and miRNA*s in this study. The endogenous miRNAs exhibited significant base bias, especially in 19–23 nt miRNAs and miRNA*s (Fig. 5). Although the identified conserved miRNA families in C3 and V3 showed similarities in several aspects, significant differences existed as shown in the following results.
3.1. Feline orthologs of known mammalian miRNAs 3.2. Newly identified miRNAs Conserved miRNA families are found in many vertebrate species and have important functions in vertebrate development. To identify conserved miRNAs in our dataset, all small RNA sequences were searched for alignment with known mature miRNAs and miRNA*s of H. sapiens, C. familiaris, M. musculus, R. norvegicus, B. taurus and S. scrofa in the miRNA database miRBase 18.0. There were 152 families containing 196 known miRNAs and 97 miRNA*s in both libraries (Supplemental Table S1). Aligning small RNA sequences to known miRNAs and miRNA*s resulted in 3,249,086 and 2,649,794 matches for C3 and V3, respectively. The statistics of the conserved miRNA families in C3 and V3 are listed in Supplemental Table S2. Conserved miRNAs from C3 and V3 had the following features. First, 256 miRNAs and miRNA*s were identified in both libraries, with 16 C3-specific and 21 V3-specific (Fig. 2). The conserved miRNA families in both libraries showed a similar distribution but with a few differences. The most abundant miRNAs were miR-21, let-7c, miR-29a, miR-125b, let-7g, miR-29c, let-7i, miR221, miR-23a and miR-19a in the C3 library and miR-29a, miR-21, miR-125b, miR-29c, miR-23a, miR-93 and miR-320a in V3 (Figs. 3 and 4). A first nucleotide bias analysis of the 292 known miRNAs and miRNA*s in both libraries (18–25 nt) is presented in Fig. 5. The miRNAs and miRNA*s possessed different biases. Uridine (U) dominated the first position of the known miRNAs and miRNA*s of 21 and 22 nt length. It
Release 18.0 of miRBase lists 1527 precursors and 1921 mature miRNAs in the human database although there are likely many more. Some common features of miRNAs have been explored and different miRNA prediction programs have been developed to predict novel miRNAs. Several studies have shown that miRNA precursors can fold into inverted repeat stemloop hairpin secondary structures and have low folding free energy, the latter being considered an important characteristic of miRNAs (Bonnet et al., 2004). Following these criteria, inverted repeat secondary structures were predicted using RNAfold (Hofacker, 2003) and unique reads within these were identified by miReap and mirCheck (Jones-Rhoades and Bartel, 2004). Based on these criteria, 384 and 398 novel miRNAs were predicted from C3 and V3 respectively (Supplemental Tables S3 and S4). We also mapped to the feline genome and identified the positions of the novel miRNAs in the chromosomes. The novel precursor miRNA candidates with secondary structures and the copy numbers of mature miRNAs are listed in Supplemental Tables S3 and S4. More than half began with 5′ U, which is a characteristic feature of miRNAs (Bonnet et al., 2004; Zhang et al., 2006).
Table 3 Length distribution of small RNA. Length (nt)
C3
Percent
V3
Percent
18 19 20 21 22 23 24 25 26 27 28
89166 144312 244415 780866 3168988 1409484 319155 93947 34717 12845 4682
1.41% 2.29% 3.88% 12.39% 50.28% 22.36% 5.06% 1.49% 0.55% 0.20% 0.07%
339581 414041 479756 1003112 3207541 1196334 366204 103180 32704 9260 2169
4.75% 5.79% 6.71% 14.02% 44.84% 16.72% 5.12% 1.44% 0.46% 0.13% 0.03%
C3, uninfected F81 cells; V3, MEV-infected F81 cells.
Fig. 2. Comparison of known miRNAs between C3 and V3 libraries.
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Fig. 3. Relative abundance of miRNAs in C3 library based. TPM: tags per million; i.e., miRNA reads number/million total reads.
3.3. Computational analysis validating the miRNA targets and mRNAs To assess the function of the miRNAs in C3 and V3, putative targets of miRNAs were predicted using Targetscan software (Lewis et al., 2005) according to reference species program. Selection of genes with possible antiviral functional roles, such as interferon and interferon related genes, was predicted to contain a few miRNA candidate targets (Supplemental
Table S5). Using RNAhybrid (Krueger and Rehmsmeier, 2006) and following the rules of no mismatch and G/U complementarity in miRNAs seed sequences, 8 miRNAs (miR-130, miR-148, miR-362, miR-454 and miR-181) were predicted to target MEV mRNA (Fig. S1) and 6 (miR320, miR-140, miR-145, miR-152 miR-182 and miR-194) were predicted to target MEV receptor-transferrin receptor mRNA (Fig. S2). These miRNAs may play a role in the process of MEV infection.
Fig. 4. Relative abundance of miRNAs in V3 library based. TPM: tags per million; i.e., miRNA reads number/million total reads.
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Fig. 5. The first nucleotide bias of known miRNAs of 18–25 nt length.
families in feline kidney (F81) cells with 97 miRNA*s of the miRNAs also being detected. In addition, 384 and 398 miRNA precursor candidates that have not been reported in other mammals were identified in uninfected and MEV-infected F81 cells respectively. Although these new miRNA precursor candidates mapped to the feline genome and had the predicted secondary structure, future verification is required to ensure their authenticity. Data analyses were performed to identify miRNAs with different expression levels in the two libraries and the results were partially validated by qRT-PCR. Results showed that MEV infection resulted in changes in miRNA expression profiles in F81 cells. Some miRNAs were predicted to target genes involved in MEV infection. In summary, we studied a repertoire of F81 cell line miRNAs expressed in uninfected cells or following MEV infection, and have performed a preliminary analysis of the functions of these miRNAs. These data provide a foundation for further investigations on host and virus interaction. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2014.01.074.
3.4. Validation of miRNAs Conflict of interest To validate conserved predicted miRNAs, qRT-PCR was performed on 16 randomly selected miRNAs in C3 and V3 libraries. Fig. 6 shows that 3 (miR-181b, miR-181d and miR-301) were significantly downregulated, and 4 (miR-29b, miR-125b, miR-320a and miR-140) upregulated including 3 (miR-29b, miR-125b and miR-320a) significantly. It seems likely that these 7 miRNAs have some function in MEV infection. The majority (12 of 16) of the randomly selected miRNA expression profiles by qRT-PCR were consistent with those obtained by deep sequencing. 3.5. Absence of MEV derived miRNA From the V3 library, 20 small unique RNAs were mapped to the MEV genome; however, no miRNA was identified using miReap software prediction. These results indicate that MEV does not encode miRNA. A possible reason is that, as a very small DNA virus with a genome of only about 5 kb, MEV must make highly efficient use of its available coding capacity. A functional non-coding RNA would not be an effective use of such a genome. 4. Conclusions Using Illumina's ultrahigh throughput approach we have identified 196 known mammalian miRNA orthologs belonging to 152 miRNA
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