Identification and expression analysis of miRNA in hybrid snakehead by deep sequencing approach and their targets prediction

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Original Article

Identification and expression analysis of miRNA in hybrid snakehead by deep sequencing approach and their targets prediction ⁎

Wangbao Gonga, Yong Huangb, , Jun Xiea, Guangjun Wanga, Deguang Yua, Xihong Sunb, Kai Zhanga, Zhifei Lia, Ermeng Yua, Jingjing Tiana, Yun Zhua a

Key Laboratory of Tropical&Subtropical Fishery Resource Application & Cultivation, Ministry of Agriculture, Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510380, China b College of Animal Science and Technology, Henan University of Science and Technology, Luoyang, 471003, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Hybrid snakehead miRNA Expression Deep sequencing Targets

MicroRNAs (miRNAs) play important regulatory roles in numerous biological processes, but there is no report on miRNAs of hybrid snakehead. In this study, four independent small RNA libraries were constructed from the spleen, liver kidney and muscle of hybrid snakehead. These libraries were sequenced using deep sequencing technology, as result, a total of 1,067,172, 1,152,002, 1,653,941 and 970,866 clean reads from these four libraries were obtained. 252 known miRNAs and 63 putative novel miRNAs in these small RNA dataset were identified. The stem-loop RT-qPCR analysis indicated that eight known miRNAs and two novel miRNAs show different expression in eight different kinds of tissues. For better understanding the functions of miRNAs, 95,947 predicated target genes were analyzed by GO and their pathways, the results indicated that these targets of the identified miRNAs are involved in a broad range of physiological functions.

1. Introduction MicroRNAs (miRNAs) are a family of extensively endogenous noncoding small RNA molecules, approximately 20–24 nt in length, which can directly control post transcriptional regulation by binding to target mRNA and stopping their expression via translational repression or degradation [1,2]. Mature miRNAs are typically generated via a twostep processing pathway. Firstly, pri-miRNA is transcribed by RNA polymerase II from the genome, and then pri-miRNA is converted into pre-miRNA by the nuclear RNase type III enzyme, Drosha [3]. Later, the pre-miRNA is exported from the nucleus by Exportin 5 with RanGTPase activity and cleaved by Dicer in the cytoplasm to form a duplex small RNA of ~22 nts or designated 5p and 3p [4]. Finally, the mature miRNAs couple with the RISC and guide RISC to complementary miRNA target genes [5]. An increasing number of studies have demonstrated that miRNAs play important regulatory roles in numerous biological processes, including organ development, cell differentiation, proliferation, apoptosis, homeostasis, metabolism, tumorigenesis, bacterial and viral infections, immunological regulation and so on in organisms, and even viruses [6–9]. Channa argus and Channa maculata, commonly called snakehead fish, belong to the family Channidae, and are carnivorous, air-breathers

⁎

being cultured widely in China, and in most southern and south-eastern Asian countries, such as Vietnam, Cambodia and Thailand [10]. In recent years, the hybrid snakehead, C. maculata♀ × C. argus♂has become the most popular breed to culture in the family in China. It is regarded as valuable fish in China because of its high protein content, significant anti-hypoxia capacity, rapid growth and even curative function in traditional Chinese medicine [11,12]. The total snakehead production of China in 2013 was over 500,000 tons ranking ninth in the production of all freshwater fish species in China (Fisheries Bureau of Ministry of Agriculture 2014) [13]. In recent years, large numbers of miRNAs have been identified from animal species including various model and non-model fish [14,15], but there are no reports on miRNAs in hybrid snakehead. In this study, we first constructed four small RNA libraries from the four different tissues (spleen liver, kidney, and muscle) of hybrid snakehead, respectively. Through deep sequencing of the small RNA libraries and subsequent bioinformatic analysis, miRNAs in four libraries of hybrid snakehead were identified and the differentially expressed miRNAs were analyzed. Thus, the discovery of miRNA information from this study will significantly advance our knowledge of the miRNA population and contribute to a better understanding of the different miRNAs roles playing in regulating the growth biological processes in hybrid snakehead and

Corresponding author. E-mail address: [email protected] (Y. Huang).

https://doi.org/10.1016/j.ygeno.2018.08.012 Received 12 June 2018; Received in revised form 4 August 2018; Accepted 15 August 2018 0888-7543/ © 2018 Elsevier Inc. All rights reserved.

Please cite this article as: Gong, W., Genomics, https://doi.org/10.1016/j.ygeno.2018.08.012

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Fig. 1. Small RNA reads from spleen, liver, kidney and muscle were blasted against the Rfam database non-coding RNA to annotate rRNA, tRNA, snoRNA, snRNA and others RNAs.

(Table 1). The results indicate that the deep sequencing data were highly enriched for small RNA sequences. Furthermore, the length distribution analysis of these small RNA sequences reads showed that they exhibit similar pattern of distribution in length in all libraries (Fig. 2). The length of the small RNAs in all libraries varied from 18 nt to 26 nt and the majority of reads are 21 to 23 nt in length, followed by 18, 19, and 20 nts, which are consistent with the typical sizes of Dicer cleaved products. Our results are also consistent with the typical small RNA distribution of fishes, such as Ctenopharyngodon idella [16], Monopterus albus [17], Misgurnus anguillicaudatus [18] and Paralichthys olivaceus [19]. The raw reads of the four libraries were uploaded to NCBI and accession numbers were obtained, which are SRP145515, SRP146087, SRP145586 and SRP145591.

also provide insights into their target genes of miRNAs function in future. 2. Results and discussion 2.1. Deep sequencing of small RNAs of hybrid snakehead Up to now, there is little information available regarding miRNA in hybrid snakehead, especially the information about miRNAs in different tissues. To identify miRNAs in hybrid snakehead, four small RNA libraries from spleen, liver, kidney and muscle were constructed and sequenced using deep sequencing technology, respectively. A total number of 12,535,289, 11,515,096, 14,422,196 and 11,322,193 raw reads were obtained. After removing the reads with 3ADT&length filter, junk reads, RFam (rRNA, tRNA, snRNA, snoRNA, and other Rfam RNAs) (Fig. 1) and Rbepbase sequences, result in a total of 1,067,172, 1,152,002, 1,653,941 and 970,866 clean reads representing 293,695, 317,923, 368,262 and 387,507 unique sequences (mappable reads)

2.2. miRNAs in hybrid snakehead To identify miRNAs in hybrid snakehead, all mapped sequences were compared with known animal miRNAs and miRNA precursor 2

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Table 1 Analysis of small RNA sequences from the four tissues of hybird snakehead fish. Type

Raw reads 3ADT& length filter Junk reads Rfam Repeats mappable reads

Spleen tissue

Liver tissue

Kidney tissue

Muscle tissue

Total

%

unique

%

Total

%

unique

%

Total

%

unique

%

Total

%

unique

%

12,535,289 4,890,410

100 39.01

1,067,172 762,922

100 71.49

11,515,096 7,711,499

100 66.97

1,152,002 825,912

100 71.69

14,422,196 5,447,998

100 37.78

1,653,941 1,273,428

100 76.99

11,322,193 4,162,845

100 36.77

970,866 572,566

100 58.97

4,137 368,939 102,542 7,267,200

0.03 2.94 0.82 57.97

1,881 8,568 544 293,695

0.18 0.80 0.05 27.52

2,421 629,463 244,751 3,170,428

0.02 5.47 2.13 27.53

1,229 6,870 435 317,923

0.11 0.60 0.04 27.60

4,987 414,200 157,993 8,551,275

0.03 2.87 1.10 59.29

2,095 10.036 904 368,262

0.13 0.61 0.05 22.27

8,149 521,436 57,285 6,619,204

0.07 4.61 0.51 58.46

2,503 8,096 790 387,507

0.26 0.83 0.08 39.91

Fig. 2. Size distribution of small RNAs found in four tissues from hybird snakehead fish.

snakehead. The lengths of pre-miRNA sequences ranged from 52 to 149 nt with an average length of 79 nt and mature miRNAs are distributed in the range of 18 nt to 25 nt. The MFE of these predicted premiRNAs ranged from −15.4 kcal/mol to −75.4 kcal/mol. The MFEI ranged from 0.84 to 2.1, with an average of 1.24, which is consistent with the characteristics of miRNA. As demonstrated by previous studies, known miRNAs are often the high abundantly expressed miRNAs, while most novel miRNAs are among the least abundant [26]. In present study, most of novel miRNAs were expressed at low reads and is consistent with previous studies.

sequences in miRBase database. As a result, a total of 252 known miRNAs were identified in hybrid snakehead (Table S1). The read numbers of these known miRNAs ranged from 1 to 4,550,356, indicating that there are not only highly expressed miRNAs, but also low expressed miRNAs. These identified miRNAs cover 97 miRNA families and most abundant are let-7 (15 members), miR-17 (12 members) and miR-30 (9 members) (Table S2). Let-7 is a big miRNA family which is also highly conserved in metazoans from worm to humans [20]. Previous studies suggest that that let-7 family miRNAs are important regulators of fundamental biological processes [21]. High conservation of the miRNA families suggested an evolutionary conserved function. Some studies reveal that miR-17 family members have played essential roles during normal development of the heart, lungs and immune system [22–24]. In addition, they could promote cell proliferation and suppress cancer cell apoptosis. For example, miR-17-5p regulates breast cancer cell proliferation by inhibiting translation of AIB1 mRNA [25]. The important advantage of deep sequencing technology has given rise to the discovery that a great number of the low-abundance or novel miRNAs. To predict novel miRNAs in hybrid snakehead, all the mapped small RNAs that did not match any of the known animal miRNAs were further analyzed by blasting to the zebra genome sequence using Mireap software, these small RNAs were classified as novel miRNAs. We annotated the newly discovered 5p/3p sequences as “p3/p5”. A total of 63 novel miRNAs were identified from the four libraries altogether, 6 of which are only found in all four libraries (Table S3). It was noteworthy that PC-5p-32_122915 and PC-3p-2308_443 showed the highest reads in all sequenced tissues compared to others novel miRNAs reads, suggesting two novel miRNAs might be the functional role in hybrid

2.3. Tissue-specific expression of miRNA in hybrid snakehead In these miRNAs identified by deep sequencing, 175 miRNAs showed co-expressed in all 4 tissues (Fig. 3). The six miRNAs are uniquely expressed in the spleen compared to only seven hybrid snakehead miRNAs identified in liver. In addition, there are also 13 and 41 miRNAs which have specific expressed in kidney and muscle, respectively. The specific tissue expression implies that these miRNAs may be required for the regulation of tissue differentiation or the maintenance of tissue identity. While most miRNAs are shared among tissues, the kidney displayed the largest number of unique miRNAs. 244 miRNAs are expressed in spleen, 211 are expressed in liver, 256 are expressed in kidney, and 241 are expressed in muscle tissue. Highly expressed miRNAs often reflect the different roles in a particular tissue or development stage as well as corresponding to biological mechanisms [27]. The top 10 abundant miRNAs are listed in Table 2, suggesting that they may play some important roles in the development or physiology of 3

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value of log2ratio fold-change > 2 between two libraries were identified by deep sequencing. Results showed that there are some differentially expressed miRNAs in two libraries (Fig. 4). We found 62 miRNAs, 48 miRNAs, 93 miRNAs, 58 miRNAs, 102 miRNAs, and 92 miRNAs expressed differentially in spleen versus liver, spleen versus kidney, spleen versus muscle, liver versus kidney, liver versus muscle and kidney versus muscle (Table S4). Ssa-miR-122-3p_R-1_2ss12TC19TA and fru-miR-122_R-1 were significantly down regulated (> 10-fold change) in spleen compared to liver. Dre-miR-34b_L-1R + 1_1ss11TC was significantly down-regulated (> 6-fold change) in spleen compared to kidney, while dre-miR-2187-3p_L+1R-1_1ss21AG and dre-miR2187-5p_R-1 were significantly up regulated (> 6-fold change). OlamiR-206_R+1 and pol-miR-133-3p were identified to be significantly down-regulated (> 14-fold change) in spleen than in muscle, and ccrmiR-722_L-2R + 3 was significantly up-regulated (> 7-fold change). Interestingly, down-regulated miRNA, pol-miR-133-3p also showed > 12-fold higher expression in muscle than that in kidney, and up-regulated miRNA ola-miR-144_L-1R+2 showed 6-fold higher expression. Ola-miR-223_R+2 showed down-regulated at least 6-fold change only in liver than in kidney, while ssa-miR-122-5p_R-1 showed up-regulated and > 9-fold higher expression. In contrast, aca-miR-133a_L-1R+1, the most down-regulated miRNAs, showed > 11-fold higher expression in liver than that in muscle, while ccr-miR-722_L-2R+3 exhibited 9-fold increase. This suggests that these different miRNAs may play major roles in the regulation of fundamental biological processes in organ development of hybrid snakehead. Previously study showed that a muscle-specific miRNA, miR-133 regulated insulin-like growth factor-1 receptor during skeletal myogenesis [33]. miR-122 is a liver-abundant miRNA. Studies indicated that miR-122 accounts for over 70% of total miRNAs in hepatocytes and is also expressed at low level in the heart [34]. Others research suggested that miR-122 plays critical roles in liver homeostasis and metabolism. Silencing of miR-122 has been associated with steatohepatitis, fibrosis and HCC [35,36].

Fig. 3. Venn diagram showing the distribution of miRNAs expressed in the spleen, liver, kidney and muscle in hybird snakehead fish.

tissue. Highly expressed miRNAs in the muscle, such as ssa-let-7a-5p and aca-miR-133a_L-1R+1 exhibited the most abundant expression of > 1 million reads (1,608,258 and 1,029,174 reads in muscle, respectively). In the others three libraries of hybrid snakehead, the abundance of expression of hhi-miR-26_R+1(319,160 reads), fru-miR122_R-1 (900,610 reads) and ssa-miR-21b-5p_R-1(242,336 reads) reached their highest levels in spleen, liver and kidney respectively in the present study. Interestingly, ssa-let-7a-5p has also highly expression in spleen, liver, kidney and muscle indicating ssa-let-7a-5p may execute important psychological function in these tissues. As described for other fish species, let-7 has also highly expressed in some tissues including in Megalobrama amblycephala liver, in Lates calcarifer muscle, liver, intestine, heart, kidney and spleen [28,29], suggesting let-7 might play an important role in the regulation of constitutive processes in diverse tissues. Moreover, we have found that a novel miRNA named PC-5p32_122915 is highly expressed with 330,947 reads in liver and 177,121 reads in muscle respectively, indicating this novel miRNA might has a tissue-specific expression which provided clues about their physiological functions [30]. Previously studies showed that miR-133 is involved in myoblast proliferation and regulates fish skeletal muscle growth by mediating Hedgehog and Insulin-like growth factor signaling pathways [31,32].

2.5. Validation of the identified miRNAs by stem-loop RT-qPCR Validating and quantifying the differentially expressed miRNAs in the different tissues is an important initial step to further investigate the fundamental functions of these miRNAs in organism. In our study, ten differentially expressed miRNAs including eight known miRNAs (dremiR-22a-3p, tni-miR-25, hhi-miR-26_R+1, ola-miR-125b, ccr-miR-1263p_L-1R+1, fru-miR-217_R+1, aca-miR-499-5p_R-1 and ssa-miR-21885p) and two novel miRNAs (PC-3p-3596_263 and PC-5p-9879_90) randomly selected to confirm their expression using stem-loop qRT-PCR in eight different tissues (spleen, liver, muscle, kidney, gill, testis, intestine and heart) (Fig. 5). Their relative expression is represented along with the average threshold cycle (CT) values. All the 10 differentially expressed miRNAs are expressed in all examined tissues, which are consistent with the deep sequencing data, although expression of known miRNAs was significantly higher than that of the novel miRNAs. These data provide evidence that deep sequencing is a more sensitive

2.4. Differential expression analysis of the identified miRNAs Differentially expressed miRNAs between libraries give a clue to molecular events related to the growth and development of the fish in various tissues. To adjudge differentially expressed miRNAs, the differentially expressed miRNAs with P-value < .001 and the absolute

Table 2 Highly expressed miRNAs in spleen, liver, kidney and muscle of hybird snakehead fish. miRNA

Spleen

miRNA

Liver

miRNA

Kidney

miRNA

Muscle

hhi-miR-26_R+1 ssa-let-7a-5p ola-miR-143_R+2 ola-miR-100_R+3 ssa-miR-21b-5p_R-1 ccr-miR-126-3p_L-1R+1 fru-miR-10c aca-miR-30c-5p_R+3 ola-miR-125b ssa-miR-146a-5p

319,160 240,998 148,469 143,668 137,217 89,177 68,629 54,869 53,695 48,253

fru-miR-122_R-1 PC-5p-32_122915 hhi-miR-26_R+1 ssa-let-7a-5p ola-miR-100_R+3 ola-miR-199a-3p_R-1 aca-miR-30c-5p_R+3 dre-miR-22a-3p ssa-miR-21b-5p_R-1 ssa-miR-146a-5p

900,610 330,947 327,974 258,343 115,797 69,977 68,793 66,081 60,099 59,678

ssa-miR-21b-5p_R-1 hhi-miR-26_R+1 ssa-let-7a-5p ssa-miR-2188-5p ola-miR-100_R+3 aca-miR-30c-5p_R+3 ola-miR-125b ccr-miR-126-3p_L-1R+1 aca-let-7e-5p ssa-miR-92a-3p

242,336 222,445 199,835 98,031 70,875 68,774 34,563 34,065 33,812 31,763

ssa-let-7a-5p aca-miR-133a_L-1R+1 ola-miR-100_R+3 ola-miR-125b aca-miR-1a-3p ola-miR-199a-3p_R-1 ola-miR-206_R+1 PC-5p-32_122915 dre-miR-22a-3p aca-miR-214-3p

1,608,258 1,029,174 670,467 557,475 413,029 297,779 179,048 177,121 134,156 114,978

4

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Fig. 4. miRNA expression numbers of hybird snakehead in four tissues. Red dots show the miRNAs up-regulated, green dots show the miRNAs down-regulated and blue dots show the miRNAs expressed equally between the samples. The fold-change value > 2 and p value less than < 0.001. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

highly expression in liver, and which was weakly expressed in others 7 tissues. Intriguingly, two novel miRNAs (PC-3p-3596_263 and PC-5p9879_90) exhibited relative low expression in all tissues, especially in gill. Previously studied imply that novel miRNAs are usually weakly expressed while known RNAs are highly expressed [38,39]. Overall, these results indicated that the expression pattern of these miRNAs varies dramatically in different tissues, some miRNAs exhibited preferentially expression in certain tissues, whereas a few miRNAs are highly expressed in multiple tissues, suggesting that miRNAs may play a regulatory role in growth and development of hybrid snakehead.

and reliable method for identifying differentially expressed miRNAs in hybrid snakehead. Among the known miRNAs, the expression of dremiR-22a-3p, ola-miR-125b, ccr-miR-126-3p_L-1R + 1 and aca-miR499-5p_R-1 were maximal in muscle while they showed abundant expression in the gill, testis, intestine and heart, indicating that these four miRNAs may play important regulation roles in muscle of animal. TnimiR-25 was more abundantly expressed in kidney and moderate in spleen and liver and least expression in the others five tissues. Expression of hhi-miR-26_R+1 was abundant in liver, followed by kidney, spleen and heart and it was weak in muscle, gill, testis and intestine. Ssa-miR-2188-5p was expressed predominantly in the spleen which belong to the key tissue for fish immunity and hematopoiesis [37], indicating that this miRNAs may play crucial roles for gene regulation in physiological activity of immunity. Fru-miR-217_R+1 exhibited

2.6. Target prediction of miRNAs and enrichment analysis The ultimate goal of the present study is to understand the 5

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Fig. 5. Relative expression of 10 miRNAs in eight tissues from hybird snakehead fish by stem-loop qRT-PCR. The analysis was done for three biological samples with technical replicates. Error bars represent standard deviation from the mean (P < .05).

6

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molecular function and. A total of 50 significantly enriched GO terms were generated (Fig. 6 and Table S6). Based on the biological process, the genes are classified into 25 subcategories, of which large numbers of targets are categorized as “transcription, DNA-templated” and “regulation of transcription, DNA-templated”. In the case of cellular component, the genes are classified into 15 subcategories, and > 60% of all predicated target genes are clustered into the nucleus, integral component of membrane, and cytosol, whereas cytoskeleton and mitochondrial inner membrane” comprised the smallest proportion. For the molecular function subcategory, the majority of targets are classified under ATP binding, zinc ion binding and protein binding, indicating that most of the predicted targets encoded transcription factors, confirming the widely held view that most animal miRNA targets encode transcription factors. Furthermore, to universally summarize the orchestrating roles of miRNAs in hybrid snakehead, enriched KEGG analysis of target genes of identified miRNAs was performed. KEGG analysis revealed that a total of 249 pathway networks are found to be annotated, of which the top 20 enriched pathways are discovered to be involved in 8135 target genes (Fig. 7 and Table S7). Intriguingly, Huntington's disease is the most significantly enriched with respect to the rich factor and gene number (327 genes), followed by Alzheimer's disease (277 genes), Lysosome (235 genes), Parkinson's disease (168 genes) and Oxidative phosphorylation (139 genes). These results indicated that those potential targets might be related with function of disease resistance, organ growth and development in hybrid snakehead. In addition, some potential pathways that might be associated with immunity included Toll-like receptor signaling pathway (KO04620), Vibrio cholerae infection (KO05110), Jak-STAT signaling pathway (KO04630), Intestinal immune network for IgA production (KO04672), MAPK signaling pathway (KO04010), RIG-I-like receptor signaling pathway (KO04622)

physiological functions of miRNAs and their target genes for elucidating the miRNA regulatory network. However, little information about hybrid snakehead genomics is available. In this study, transcript sequences of hybrid snakehead from our laboratory (no published data) were used as a reference set. Target gene prediction was performed using TargetScan and miRanda software. A total of 95,947 potential putative genes were found as targets for these identified hybrid snakehead miRNAs (Table S5). The number of target genes for each miRNAs ranged from two to > 400. Not surprisingly, one miRNA can regulates multi-genes, and similarly multiple miRNAs can regulate one gene, indicating that the miRNA gene regulation network might be extremely complicated [40]. The let-7 and miR-101 family members were found to regulate maximum number of target genes in the hybrid snakehead. The targets for the novel miRNAs were found to be 15,695 genes. Many experimental and/or computational approaches demonstrated that miRNAs target many transcription factors [41,42]. Our study results showed that most of predicted targets are transcription factors, for instance, those encoding the zinc finger, F-box protein, Tbox, ring finger protein, insulin-like growth factor, interferon regulatory factor 2-binding protein, tumor protein p53 binding protein, nuclear receptor, eukaryotic translation initiation factor, inhibitor of growth protein and so on. These potential predicted targets can give valuable insight into specific biological processes being regulated in growth and development of hybrid snakehead. Therefore, more experimental evidence is needed to validate the relationships between miRNAs and the putative targets. To further understand the physiological role of predicated targets of the known and novel miRNAs identified, these targets were subjected to GO analysis for evaluating their potential functions. Results revealed 42,819, 31,298 and 34,868 genes classified into three category including 3474 biological process, 700 cellular component and 1833

Fig. 6. Functional classification of miRNA target genes according to GO category. 7

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Fig. 7. KEGG pathways enriched analysis for target genes of miRNAs.

collected and frozen in liquid nitrogen and stored at −80 °C prior to use. All experimental procedures were approved by the Ethics Committee of Laboratory Animal of Henan University of Science and Technology.

and T cell receptor signaling pathway (KO04660) suggesting that putative target genes play important role in cell proliferation, differentiation, and immunity which are regulated by these miRNAs. Further identification of the target genes of these miRNAs could shed new light on their regulatory roles of miRNAs in hybrid snakehead.

4.2. Construction of small RNA libraries and deep sequencing 3. Conclusions Total RNA was isolated using Trizol reagent (Takara, China) according to manufacturer instructions. The total RNA quantity and purity were analyzed with Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, USA) with RIN value > 8.0. Approximately 1 μg of total RNA were used to prepare small RNA library according to protocol of TruSeq Small RNA Sample Prep Kits (Illumina, USA). The small RNAs fraction were isolated by polyacrylamide gel electrophoresis and ligated with proprietary adaptors (Illumina, USA). Short RNAs were then reverse-transcribed into cDNA by RT-PCR. The four small RNA libraries from spleen, liver, kidney and muscle hybrid snakehead were constructed and then sent to LC-Sciences (Hangzhou, China) for deep sequencing using an Illumina Hiseq 3000 platform.

By deep sequencing, four small RNA libraries from spleen, liver, kidney and muscle of hybrid snakehead were successfully constructed, respectively. A total of 252 known and 63 novel miRNAs were identified. The expression profiles of known and novel miRNAs between two tissues also was analyzed. The present study is the first systemic to character these identified miRNAs. The 10 miRNAs were validated by stem-loop qPCR technology and found that different miRNAs might have important function in the physiology of specific tissues. Further target genes were predicted and analyzed by bioinformatics methods.Subsequently GO and KEGG pathway enrichment analyses indicated relevant biological processes. Our data provide important and valuable information resources for miRNA transcriptome of different tissues of hybrid snakehead. Future detailed studies are need to uncover the miRNAs and its targets functional regulation mechanism.

4.3. Small RNA bioinformatic analysis The raw reads were subjected to the Illumina pipeline filter, and then the dataset was further processed with an in-house program, ACGT101-miR (LC Sciences, USA) to remove adapter dimers, junk and low complexity, the remaining 18 to 26 nt reads were regarded as clean reads and were used for further analysis. The clean reads were analyzed by Blast against the zebrafish genome. The matched sequences were blasted against the Rfam (ftp.sanger.ac.uk/pub/databases/Rfam) and Repbase (http://www.girinst.org/) to discard mRNA, rRNA, tRNA,

4. Materials and methods 4.1. Fish and sample preparation The hybrid snakehead used in this study was purchased from a fish farm (Guangzhou, Guangdong, China) with an average weight of approximately 700-800 g. The tissue samples of hybrid snakehead were 8

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by both softwares and calculated the overlaps were combined. The GO terms and KEGG pathway of these targets were annotated and analyzed with the DAVID Bioinformatics Resources Database [46].

snRNA, snoRNA, other noncoding RNAs and repeat sequences. The reads were then mapped to miRBase 21.0 by Blast search to identify known animal miRNAs. At the same time, sequencing reads that do not match any of the known miRNA were further analyzed to discover novel miRNAs. Novel candidate miRNAs were identified by prediction of the secondary structures with Mfold program (http://mfold.rna albany.edu/). The naming system of miRNAs identified in this study is as follows: the miRNA name is composed of the first known miR name in a cluster, an underscore, and a matching annotation: L-n means the miRNA_seq (detected) is n base less than known rep_miRSeq in the left side; R-n means the miRNA_seq (detected) is n base less than known rep_miRSeq in the right side; L+n means the miRNA_seq (detected) is n base more than known rep_miRSeq in the left side; R+n means the miRNA_seq (detected) is n base more than known rep_miRSeq in the right side; 2ss5TC13TA means 2 substitut in (ss), which are T to C at position 5 and T to A at position 13. If there is no matching annotation, the miRNA_seq (detected) is exactly the same as known rep_miRSEq. Newly discovered 5′/3′ sequences are annotated as p5/p3 to distinguish from the reported 5′/3′ sequences.

Acknowledgements This study was supported by grants from the National Natural Science Foundation of China (31302201), Pearl River S&T Nova Program of Guangzhou (2014J2200088) and National key Technology R & D Program of China (2012BAD25B04). Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ygeno.2018.08.012. References [1] L. He, G.J. Hannon, MicroRNAs: small RNAs with a big role in gene regulation, Nat. Rev. Genet. 5 (2004) 522–531. [2] D.P. Bartel, MicroRNAs: genomics, biogenesis, mechanism, and function, Cell 116 (2004) 281–297. [3] G. Hutvagner, P.D. Zamore, A microRNA in a multiple-turnover RNAi enzyme complex, Science 297 (2002) 2056–2060. [4] Y. Lee, K. Jeon, J.T. Lee, S. Kim, V.N. Kim, MicroRNA maturation: stepwise processing and subcellular localization, EMBO J. 21 (2002) 4663–4670. [5] T.P. Chendrimada, K.J. Finn, X. Ji, D. Baillat, R.I. Gregory, S.A. Liebhaber, A.E. Pasquinelli, R. Shiekhattar, MicroRNA silencing through RISC recruitment of eIF6, Nature 447 (2007) 823–828. [6] K. Sun, E.C. Lai, Adult-specific functions of animal microRNAs, Nat. Rev. Genet. 14 (2013) 535–548. [7] W.P. Kloosterman, R.H. Plasterk, The diverse functions of microRNAs in animal development and disease, Dev. Cell 11 (2006) 441–450. [8] Y. Huang, X.J. Shen, Q. Zou, S.P. Wang, S.M. Tang, G.Z. Zhang, Biological functions of microRNAs: a review, J. Physiol. Biochem. 67 (2011) 129–139. [9] S. Callegari, S. Gastaldello, O.R. Faridani, M.G. Masucci, Epstein-Barr virus encoded microRNAs target SUMO-regulated cellular functions, FEBS J. 281 (2014) 4935–4950. [10] E.A. Adamson, D.A. Hurwood, P.B. Mather, A reappraisal of the evolution of Asian snakehead fishes (Pisces, Channidae) using molecular data from multiple genes and fossil calibration, Mol. Phylogenet. Evol. 56 (2010) 707–717. [11] A. Zhou, S. Xie, Z. Wang, M. Junaid, L. Fan, C. Wang, Q. Ye, Y. Chen, D.S. Pei, J. Zou, Molecular cloning, characterization and expression analysis of heat shock protein 90 in albino northern snakehead Channa argus, Gene 626( (2017) 173–181. [12] S.R. Zhu, J.L. Li, N. Xie, L.M. Zhu, Q. Wang, G.H. Yue, Genetic diversity based on SSR analysis of the cultured snakehead fish, Channa argus, (Channidae) in China, Genet. Mol. Res. 13 (2014) 8046–8054. [13] M. Ou, C. Yang, Q. Luo, R. Huang, A.D. Zhang, L.J. Liao, Y.M. Li, L.B. He, Z.Y. Zhu, K.C. Chen, Y.P. Wang, An NGS-based approach for the identification of sex-specific markers in snakehead, Channa argus, Oncotarget 8 (2017) 98733–98744. [14] T.T. Bizuayehu, I. Babiak, MicroRNA in teleost fish, Genome Biol Evol 6 (2014) 1911–1937. [15] L. Yang, Z. Zhang, S. He, Bichir microRNA repertoire suggests a ray-finned fish affinity of Polypteriforme, Gene 566 (2015) 242–247. [16] W. Gong, Y. Huang, J. Xie, G. Wang, D. Yu, X. Sun, Genome-wide identification and characterization of conserved and novel microRNAs in grass carp (Ctenopharyngodon idella) by deep sequencing, Comput. Biol. Chem. 68( (2017) 92–100. [17] Y. Gao, W. Guo, Q. Hu, M. Zou, R. Tang, W. Chi, D. Li, Characterization and differential expression patterns of conserved microRNAs and mRNAs in three genders of the rice field eel (Monopterus albus), Sex. Dev. 8 (2014) 387–398. [18] S. Huang, X. Cao, X. Tian, W. Wang, High-Throughput Sequencing Identifies MicroRNAs from Posterior Intestine of Loach (Misgurnus anguillicaudatus) and their Response to Intestinal Air-Breathing Inhibition, PLoS One 11 (2016) e0149123. [19] Y. Fu, Z. Shi, M. Wu, J. Zhang, L. Jia, X. Chen, Identification and differential expression of microRNAs during metamorphosis of the Japanese flounder (Paralichthys olivaceus), PLoS One 6 (2011) e22957. [20] S. Roush, F.J. Slack, The let-7 family of microRNAs, Trends Cell Biol. 18 (2008) 505–516. [21] J.T. Powers, K.M. Tsanov, D.S. Pearson, F. Roels, C.S. Spina, R. Ebright, M. Seligson, Y. de Soysa, P. Cahan, J. Theissen, H.C. Tu, A. Han, K.C. Kurek, G.S. Lapier, J.K. Osborne, S.J. Ross, M. Cesana, J.J. Collins, F. Berthold, G.Q. Daley, Multiple mechanisms disrupt the let-7 microRNA family in neuroblastoma, Nature 535(2016) 246–251. [22] H. Zhang, Y. Fu, Z. Shi, Y. Su, J. Zhang, miR-17 is involved in Japanese Flounder (Paralichthys olivaceus) development by targeting the Cdc42 mRNA, Comp. Biochem. Physiol. B Biochem. Mol. Biol. 191( (2016) 163–170. [23] M. Lai, A. Gonzalez-Martin, A.B. Cooper, H. Oda, H.Y. Jin, J. Shepherd, L. He, J. Zhu, D. Nemazee, C. Xiao, Regulation of B-cell development and tolerance by

4.4. Analysis of differential expressed miRNAs To investigate the differentially expressed miRNAs among spleen, liver, kidney and muscle, firstly, each identified miRNAs read count was normalized to the total number of miRNA reads in each given sample and multiplied by a million. Subsequently, the fold-change log2 (sample1/sample2) and P-value were calculated from the normalized expression, and significantly difference of a given miRNA was determined by the P < .001 and fold-change > 2 in two samples, a specific miRNA was considered to be expressed significantly different. P-value formula: y£ymin

(x + y)! N p(x | y) = ⎛ 2 ⎞ (x + y + 1) N ⎝ 1 ⎠ x!y! 1 + N2 N ⎜

C(y£ymin x) =

(

1

)

∑

p(y|x)

y=0

⎟

¥

D(y£ymax x) =

∑

p(y|x)

y£ymax

The N1 and x represent the total count of clean reads and normalized expression, respectively, for a given miRNA in the peak lactation small RNA library. The N2 and y represent the total count of clean reads and normalized expression respectively, for a given miRNA in the late lactation small RNA library. 4.5. Validation of miRNA expression by stem-loop RT-qPCR To validate the presence and expression of the identified miRNAs, eight known miRNAs and two novel miRNAs with different expression patterns are selected for stem-loop RT-qPCR. Total RNA from sample tissues were extracted as described above and then transcribed into cDNA using miRNA specific stem-loop RT primers according to criteria described previously [43–45]. The resulting cDNA was diluted ten times with sterile water. Real time qPCR was performed by MyiQ2 Two Color qPCR Detection System (Bio-Rad, USA). The conditions used for qPCR were: one cycle at 94 °C for 2 min followed by 45 cycles at 95 °C for 10 s, 56 °C for 30s; and a final 70 cycles at 60 °C for 30 s. All reactions were run in triplicate for each sample. Relative expression levels of the miRNAs were measured in terms of threshold Ct and were normalized to 5S rRNA using the equation 2−ΔΔCt, in which ΔCt = Ct miRNA–Ct 5S. All primers for stem-loop RT-qPCR are listed in Table S8. 4.6. Target gene prediction and functional analysis Predicted targets of miRNAs in present study were performed by LC Sciences Service, and then we analyzed the GO terms and KEGG Pathway of these miRNAs. First, miRanda and TargetScan softwares were applied to identify miRNA binding sites. Then the data predicted 9

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