Massive Parallel Sequencing of Small RNAs from Newborn Mouse Ovaries Identifies Novel miRNAs Preferentially Expressed in the Ovaries.
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».