PLoS ONE · 2013 · 86 citations · 34 references
Life SciencesGeneticsMolecular BiologyGene ExpressionGenomicsTranscriptomicsMicrorna BiologyRna Sequencing AnalysisCdna Library ConstructionComputational Prediction ModelsDe Novo AssemblyMicrorna Target PredictionRna SequencingTranscriptome AnalysisTranscriptome SequencingWhole Transcriptome Analysis
BACKGROUND: De novo transcriptome sequencing is a robust method of predicting miRNA target genes, especially samples without reference genomes. Differentially expressed miRNAs have been previously identified in hemocytes collected from healthy skin and from skin affected by skin ulceration syndrome (SUS) in Apostichopusjaponicus. Target identification for these differentially expressed miRNAs is a major challenge for this non-model organism. METHODOLOGY/PRINCIPAL FINDINGS: To thoroughly understand the function of miRNAs, a normalized cDNA library was sequenced with the Illumina Hiseq2000 technology. A total of 91,098,474 clean reads corresponding to 251,148 unigenes, each with an average length of 494bp, were obtained. Blastx analysis against a nonredundant (nr) NCBI protein database revealed that in this set, 52,680 unigenes coded for 3,893 annotated proteins. Two digital gene expression (DGE) libraries from healthy and SUS samples showed that 4,858 of the unigenes were expressed at significantly different levels; 2,163 were significantly up-regulated, while 2,695 were significantly down-regulated. The computational prediction of miRNA targets from these differentially expressed genes identified 732 unigenes as the targets of 57 conserved and 8 putative novel miRNA families, including spu-miRNA-31 and spu-miRNA-2008. CONCLUSION: This study demonstrates the feasibility of identifying miRNA targets by transcriptome analysis. The DGE assembly data represent a substantial increase in the genomic resources available for this species and will provide insights into the gene expression profile analysis and the miRNAs function annotations of further studies.
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