Discovery of Porcine MicroRNA by Solexa Sequencing Figure 2. Count number distribution of different RNA class. A, Counted the Reads number; B. Counted the unique Tag number. doi:10.1371/journal.pone.0016235.g002 of unique sequence tags (84.72%) was attributed to unknown RNAs (Figure 2, A). This indicated that the annotated miRNAs might be the most abundant class of small ncRNAs in different porcine tissues. There was a less abundant but much more diverse class of small RNAs that could represent other classes of small ncRNAs. This is consistent with the results of Glazov et al. (2008) who reported the identification of chicken embryo miRNAs using a Solexa deep sequencing approach [36]. Identification of conserved and novel miRNA candidates by miRDeep After removing the sequence reads with recognizable adapters, unique sequence reads of size $15 nt were analyzed using the miRDeep software to detect conserved and novel porcine miRNAs (method 1). This program uses a probabilistic model of miRNA biogenesis to score the compatibility of the position and frequency of sequenced RNA with the secondary structure of the miRNA precursor [37]. Through this method, 195 porcine miRNAs with high sequence identity (.95%) to known animal miRNAs (miRBase 16.0) were identified by miRDeep program (Table S1). The results also showed that 36 porcine miRNAs that had already been deposited in miRBase were also present in our deep sequencing data, including ssc-let-7c, ssc-miR-103, and ssc-miR- 106a. Some miRNA-star sequences (miRNA*, the other arm of the stem) identified by miRDeep were present in high abundance in the pig. One example is ssc-miR-140*. This miRNA* sequence read number was 8483, which is much higher than that of ssc- miR-140 (the read number of miR-140 was only 4), indicating that miRNA* might be the functional form in pigs (Table S1). Candidate novel miRNAs were simultaneously identified from deep sequencing data by miRNA precursor prediction using miRDeep. To determine whether these miRNA sequences are conserved in mammals, they were searched against the NCBI ‘‘non-redundant’’ database. Sequences that are parts of repetitive elements or annotated function RNAs were excluded. None of these miRNA sequences could find identity sequences in other species, indicating that these may be potential novel pig specific- miRNAs. Typically, miRNAs are 18–26 nt long, and 67 of these new miRNAs were identified and termed the ‘‘ssc-miR-new plus number’’ (Table S2). In addition, a class of miRNAs named ‘‘ssc- miR-large plus number,’’ which ranged in size from 27–30 nt, was also predicted by miRDeep (Table S2). The Vienna package and Randfold application were applied to the miRDeep package to confirm whether these new miRNAs could form typical secondary structures. Another tool, the mfold software, was also used [38]. The mfold results showed that some of the new miRNAs identified by miRDeep could not form typical secondary structures, and these were therefore discarded. The secondary structures of the remaining miRNAs are shown in Table S3. The folding free energy (DG) of each structure was given by mfold; the results indicated that their DG value was lower than -17 kcal/mol. The genomic locations of the novel candidate miRNAs on the WGS sequence from the NCBI database were generated by miRDeep and are listed in Table S4. Subsequently, the chromosome location on the pig draft genomic sequence from the Sanger database was determined using the BLASTN software (Table S9). As an example, ssc-mir-new2, ssc-mir-new5, and ssc-mir-new35 were found on chromosome X. Identification of conserved miRNA candidates by the BLASTN method To determine whether known miRNAs from other species are also present in our porcine deep sequencing data, BLAST matching of known animal mature miRNA sequences (miR- Base16.0) to our sequence tags was performed using the command-line blastall program [13], with the expect value set at 1 (to be stringent when matching the short lengths of known miRNA sequences) and using the BLASTN nucleotide program (method 2). The results showed that 473 unique sequence tags had perfect matches to known animal miRNAs (Table S5), and 343 had sequence variations to known animal miRNAs (Table S6). When comparing miRNAs across different species, we found minor differences in the nucleotide composition of the miRNAs of some species. Therefore, the number of conserved candidate porcine miRNAs is listed in the table more than once. For example, mature miRNA let-7b from Pan troglodytes and Xenopus tropicalis differed by 2 nucleotides. We found 2 unique porcine tag sequences that exactly matched these. The read number of the sequence that matched ptr-let-7b was 88,532. However, there were 4 other sequences that matched xtr-let-7b (Table S5). Consequently, it was difficult to determine whether one sequence belonged to the true let-7b miRNA in pig or whether they were different isomiRs, or could be due to sequencing error. To simplify the dataset, Sequences which under the same miRNA name was classified as one miRNA species. As a result, 416 porcine miRNAs were found by using BLASTn method. Implementation of the miRDeep program to search for conserved mature miRNAs from porcine genomic sequences To determine whether other reported animal miRNAs could be sequenced and captured by Solexa sequencing in our study, miRDeep software was re-adopted to predicate porcine miRNAs (method 3). This approach is similar to method 1, but using known animal mature miRNAs (miRBase 16.0) instead of porcine Solexa sequences. To test the ability of miRDeep detect known miRNAs, all known porcine mature miRNA sequences that had already been deposited in the miRBase database were used. As a result, PLoS ONE | www.plosone.org 3 January 2011 | Volume 6 | Issue 1 | e16235