Massive Parallel Sequencing of Small RNAs from Newborn Mouse Ovaries Identifies Novel miRNAs Preferentially Expressed in the Ovaries.

Small RNAs including miRNAs, piRNAs, and snoRNAs are emerging factors in gene regulation in many organisms. Among them, miRNAs are ubiquitously expressed, conserved 19-25 nucleotides which either repress or block translation mechanism by base-paring with the target mRNA, usually in the 3' untranslated region. miRNAs are involved in diverse biological processes including development and cell differentiation. We have previously shown by microarray analysis that numerous miRNAs are expressed in the newborn ovary. However, the role of miRNAs in the developing ovary is not well understood. To identify small RNAs expressed in the newborn ovary, small RNA was extracted from mouse newborn ovary tissues and subjected to massive parallel sequencing using Solexa sequencing technology (Genome Analyzer, Illumina). Solexa sequencing produced 4,655,992 reads of 33 bp each representing a total of 154 Mbp of sequence data. The Pash alignment algorithm was used to map the reads onto the mouse genome assembly (NCBI Build 37, mm9) and the optimal Pash run mapped 50.13% of the Solexa reads to the genome. Sequence reads were clustered based on overlapping mapping coordinates and intersected with known miRNAs, snoRNAs, piRNA clusters, and repeats. Sequenced small RNA reads were mapped to the mouse genome. 25.24% of the reads were mapped to miRNAs, 25.54% to genomic repeats, 3.5% to piRNAs, and 0.18% to snoRNAs. Interestingly, Solexa reads preferentially mapped to the X chromosome. Putative novel miRNAs were identified by screening read clusters not intersecting with known RNAs and consisting of at least 100 reads, and conserved across human, rat, and mouse. Novel miRNAs were also identified by finding distinct small RNA sequences lacking annotations that shared partially overlapping genomic positions on the same strand (termed 'hotspots') and small hot-spots were folded with RNALfold software and novel miRNAs were identified using the machine learning approach implemented in MiPred. We synthesized primers corresponding to novel miRNA sequences and performed semi-quantitative RT-PCR on small RNA cDNAs derived from 11 different mouse tissues. Using this approach, we identified 3 known miRNA sequences (mmu-mir-202, mmu-mir-503, and mmu-mir-672) and 7 novel miRNA sequences which were preferentially expressed in the newborn ovary. These miRNAs may play important roles in ovarian development, folliculogenesis, and female fertility. (poster)

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