Animal Science and Technology College, Henan University of Science and Technology, Luoyang City, Henan Province, 471003 PR China Received October 2, 2014; in final form March 5, 2015

MicroRNAs (miRNAs) are a group of endogenous, short non-coding RNAs with the length of about 22 nt, which mediate gene expression at the post-transcriptional level through mRNA degradation or translational repression. Among them, some are highly evolutionally conserved in the animal kingdom; this provides a powerful strategy for identifying miRNAs in new species. The Chinese soft-shelled turtle (Pelodiscus sinensis) is one of the most important freshwater aquaculture reptilian species in China, but related miRNAs have not been identified up to now. In the present study, a total of 10 Pelodiscus sinensis miRNAs were identified according to Pelodiscus sinensis ESTs and GSSs information in NCBI database by bioinformatics approaches. The RT-PCR-based assays were performed and found that 10 Pelodiscus sinensis miRNAs were expressed. Using these miRNAs, 22 target genes were identified. These genes encode 22 proteins involved in metabolism, signal transduction, transcriptional regulation, and development. These miRNAs and their targets will serve as useful resources for their functional analyses in miRNA-regulated processes in Pelodiscus sinensis breeding and genetic research.

Keywords: microRNA, Pelodiscus sinensis, bioinformatics prediction, target gene.

DOI: 10.7868/S0132342315040144


The Chinese soft-shelled turtle Pelodiscus sinensis are among the most primitive of reptiles, diverging from other reptilian stock in the Paleozoic era. The Pelodiscus sinensis is an economically important species in freshwater aquaculture in Asia including China, Japan, and Korea [1—3]. In China, it is considered to not only be a rich delicious high-protein food source, but also of medicinal value due to being rich in collagen and unsaturated fatty acids [4]. In recent years, Pelodiscus sinensis production has grown rapidly and becomes one of big industries in Chinese reptile was roughly estimated that this species culture yields 300000 tons in 2011 (Ministry of Agriculture and Fisheries Bureau of China, 2012).

MicroRNAs (miRNAs) are genome-encoded; they represent an extensive class of single-stranded approximately 22 nt-long small RNA molecules, which playe very important roles in regulating gene expression at the post-transcriptional level by degradation of target mRNAs or by repression of target gene translation in organisms as diverse as viruses, unicellular algae, plants, worms, flies, fish, and mammals [5—9]. Biogenesis of miRNAs, in general, starts from nuclear tran-

# Corresponding author (fax: +86379 64563979; e-mail: huangyong1979111@126.com).

scription of primary miRNAs (pri-miRNA) by RNA polymerase II. Subsequently, pri-miRNAs are transported to the cytoplasm by exportin 5, where they are further processed by the Dicer endonuclease into short double-stranded RNA duplexes. Finally, mature miRNAs incorporated in an RNA-induced silencing complex (RISC) direct the RISC complex to regulate the translation of target mRNA by two mechanisms— translation silencing and/or transcript cleavage of target mRNA [10—13]. Recently, more and more evidences appear suggesting that miRNAs have diverse biological functions, such as embryo formation, organogenesis, cell death, cell proliferation, lipid metabolism, hematopoiesis, immune development, and interaction between host and pathogen [14—19].

Currently, three methods are used for identification of miRNAs: direct cloning, deep sequencing, and bioinformatics (computational) approaches [20—27]. Although direct cloning and deep sequencing have been widely used to characterize miRNA profiles and discover novel miRNAs in a variety of organisms, they are time consuming and expensive. Since large number of known mature miRNAs are evolutionary conserved in different animal species, bioinformatics approach is widely used for discovering conserved miRNAs, especially in species whose genomes are yet to be completely sequenced [28—32]. Meanwhile, this method

has been proved to be faster, affordable, and more effective [33-37].

To date, more than 28000 miRNAs found in animals and plants have been identified and deposited in the miRNA registry database (miRBase Release 21.0, June 2014) (http://www.mirbase.org/), but not the Pelodiscus sinensis miRNA. In our present study, bio-informatics approach was used to identify miRNA homologs by searching the publicly available expressed sequence tag (EST) and genomic survey sequence (GSS) datasets in NCBI against the known miRNAs that have been identified in animal species. This effort resulted in identification of eight novel miRNAs in Pelodiscus sinensis, in addition to two previously identified miRNAs. These miRNAs belong to 8 miRNA families. Further, their targets were also identified by target prediction software. The findings will lay foundation for further research on the roles of miRNAs in Pelodiscus sinensis and also will provide a phylogenet-ically important dataset for reptilian miRNA evolution studies.


Sequence Database and Reference miRNA Dataset

To search for potential conserved miRNAs in Pelodiscus sinensis species, the sequences of all previously identified miRNAs and their pre-miRNAs in animals were obtained from the miRNA registry database (Release 21.0). To avoid overlap of miRNAs, repeated sequences of miRNAs within the above species were removed and the remaining 11538 unique miRNAs were defined as the reference dataset. Pelodiscus sinensis ESTs and GSSs were obtained from NCBI, a total number of 214 EST and 77164 GSSs are deposited in GenBank.

Computational Prediction of Pelodiscus sinensis miRNAs

The BLAST version 2.2.27 alignment tool downloaded from the NCBI website was used to identify potentially conserved miRNAs. To improve the search efficiency, the BLASTN parameters were the same as those described in previous papers [38]. The procedure of the search for potential miRNAs in Pelodiscus sinensis is shown in Fig. 1. Potential miRNAs were identified based on the following criteria: (1) the pre-miRNA could fold into a perfect stem-loop hairpin secondary structure that contained ~22-nt mature miRNA sequence within one arm of the hairpin; (2) predicted mature miRNAs were allowed to have only 0-4 nucleotide mismatches in sequence with all previously known animal mature miRNAs; (3) the predicted secondary structures had negative minimal free energy (MFE) and had higher minimal folding free energy index (MFEI), which could distinguish miRNA from other different types of non-coding RNA by RNA-fold prediction; (4) pre-miRNAs had

30-70% contents of A+U by support vector machine (SVM ) since the unstable structures of pre-miRNAs are needed to produce mature single-stranded miRNAs [39]. Finally, some possible false sequences of pre-miRNAs were checked by manual inspection.

Conservation Studies and Phylogenetic Analysis

Alignments of known animal miRNAs were conducted using the DNAMAN software package (Lyn-non Corporation, Quebec, Canada J7V9M5). The precursor sequences of the predicted Pelodiscus sinen-sis miRNAs were selected for phylogenetic analyses using MEGA.5.0 to investigate their evolutionary relationships with other members of the same family [40]. Evolutionary distances were calculated by neighbor-joining (NJ) method following 1000 bootstrapped replicates [41].

RT-PCR Assay

To verify computational predictions, all ten predicted miRNAs from Pelodiscus sinensis were selected to confirm by the stem-loop RT-PCR experiment. Small RNAs from the Pelodiscus sinensis mixed tissues (skin, muscle, brain, liver, and spleen) was extracted using an RNeasy Mini Kit (Qiagen), according to the supplier's protocol. The cDNAs were synthesized from small RNAs using miRNA specific stem-loop RT primers according to the criteria described previously [42-44]. The stem-loop RT primers and gene specific primers are listed in Table 1. cDNA (100 ng) was used as template for PCR. PCR was programmed as follows: initial denaturation at 95 °C for 3 min followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 60°C for 30 s, and extension at 72°C for 25 s and final elongation step at 72° C for 7 min. The PCR products were separated in 2.5% (w/v) agarose gel. The DNA fragments were directly subcloned into PMD18-T vector (Takara) and sequenced.

Prediction of miRNA Potential Targets in Pelodiscus sinensis

The Pelodiscus sinensis mRNA database were downloaded from NCBI and then RNA hybrid online program was used to screen potential target genes to predict the possible function of identified potential miRNAs [45]. The Pelodiscus sinensis candidate target gene were described as follows: (1) the maximum number of mismatched nucleotides between the mature miRNA and its potential target genes was four; (2) the maximum number of mismatched nucleotides at positions 1-9 was one; (3) no mismatches were allowed at positions 10-11; and (4) more than two continuous mismatches at any position were not allowed. Subsequently, miRNA-target duplexes were checked manually.


Obtained potential candidates whose sequence has <4 mismatches against known miRNAs

Extracted precursor sequence of 100-nt upstream and downstream

Predict secondary RNA structure by RNA fold

Hairpin candidates

Identification of real and pseudo miRNA precursors by SVM

New miRNA genes

Fig. 1. Procedure of potential Pelodiscus sinensis miRNA gene search by identifying homologs ofpreviously known miRNA genes.


Identification and Characteristics of Predicted miRNAs in Pelodiscus sinensis

Most mature miRNAs are evolutionarily conserved from species to species with

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