Dataset Information

Identification and characterization of miRNAs expressed in the bovine ovary.

ABSTRACT:

Background

MicroRNAs are the major class of gene-regulating molecules playing diverse roles through sequence complementarity to target mRNAs at post-transcriptional level. Tightly regulated expression and interaction of a multitude of genes for ovarian folliculogenesis could be regulated by these miRNAs. Identification of them is the first step towards understanding miRNA-guided gene regulation in different biological functions. Despite increasing efforts in miRNAs identification across various species and diverse tissue types, little is known about bovine ovarian miRNAs. Here, we report the identification and characterization of miRNAs expressed in the bovine ovary through cloning, expression analysis and target prediction.

Results

The miRNA library (5'-independent ligation cloning method), which was constructed from bovine ovary in this study, revealed cloning of 50 known and 24 novel miRNAs. Among all identified miRNAs, 38 were found to be new for bovine and were derived from 43 distinct loci showing characteristic secondary structure. While 22 miRNAs precursor loci were found to be well conserved in more than one species, 16 were found to be bovine specific. Most of the miRNAs were cloned multiple times, in which let-7a, let-7b, let-7c, miR-21, miR-23b, miR-24, miR-27a, miR-126 and miR-143 were cloned 10, 28, 13, 4, 11, 7, 6, 4 and 11 times, respectively. Expression analysis of all new and some annotated miRNAs in different intra-ovarian structures and in other multiple tissues showed that some were present ubiquitously while others were differentially expressed among different tissue types. Bta-miR-29a was localized in the follicular cells at different developmental stages in the cyclic ovary. Bio-informatics prediction, screening and Gene Ontology analysis of miRNAs targets identified several biological processes and pathways underlying the ovarian function.

Conclusion

Results of this study suggest the presence of miRNAs in the bovine ovary, thereby elucidate their potential role in regulating diverse molecular and physiological pathways underlying the ovarian functionality. This information will give insights into bovine ovarian miRNAs, which can be further characterized for their role in follicular development and female fertility as well.

SUBMITTER: Hossain MM

PROVIDER: S-EPMC2762473 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

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Publications

Identification and characterization of miRNAs expressed in the bovine ovary.

Hossain Md Munir MM Ghanem Nasser N Hoelker Michael M Rings Franca F Phatsara Chirawath C Tholen Ernst E Schellander Karl K Tesfaye Dawit D

BMC genomics 20090918

<h4>Background</h4>MicroRNAs are the major class of gene-regulating molecules playing diverse roles through sequence complementarity to target mRNAs at post-transcriptional level. Tightly regulated expression and interaction of a multitude of genes for ovarian folliculogenesis could be regulated by these miRNAs. Identification of them is the first step towards understanding miRNA-guided gene regulation in different biological functions. Despite increasing efforts in miRNAs identification across ...[more]

PMID: 19765282

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Project description:BackgroundMicroRNAs (miRNAs) are a family of approximately 22 nucleotide small RNA molecules which regulate gene expression by fully or partially binding to their complementary sequences in mRNAs or promoters. A large number of miRNAs and their expression patterns have been reported in human, mouse and rat. However, miRNAs and their expression patterns in live stock species such as beef cattle are not well studied.ResultsWe constructed and sequenced small-RNA libraries to yield a total of 13,541 small-RNA sequences from 11 bovine tissues including brain, subcutaneous fat, muscle, liver, kidney, spleen and thymus. In total, 228 miRNAs including 29 novel miRNA candidates were identified. Of the 199 miRNAs, 101 have been previously reported as bovine miRNAs and the other 98 are bovine orthologs of known miRNAs that have been identified in at least one other mammalian species. Of the 29 novel miRNA candidates, 17 appeared at this point in time to be bovine specific, while the remaining 12 had evidence of evolutionary conservation in other mammalian species. Five miRNAs (miR-23a, -23b, -99a, -125b and -126-5p) were very abundant across the 11 tissues, accounting for 44.3% of all small RNA sequences. The expression analysis of selected miRNAs using qRT-PCR also showed that miR-26a and -99a were highly expressed in all tissues, while miR-122 and miR-133a were predominantly expressed in liver and muscle, respectively.ConclusionThe miRNA expression patterns among 11 tissues from beef cattle revealed that most miRNAs were ubiquitously expressed in all tissues, while only a few miRNAs were tissue specific. Only 60% miRNAs in this study were found to display strand bias, suggesting that there are some key factors for mature miRNA selection other than internal stability. Most bovine miRNAs are highly conserved in other three mammalian species, indicating that these miRNAs may have a role in different species that are potential molecular markers for evolution.

Project description:BACKGROUND: The miRNAs, a class of short approximately 22-nucleotide non-coding RNAs, often act post-transcriptionally to inhibit mRNA expression. In effect, they control gene expression by targeting mRNA. They also help in carrying out normal functioning of a cell as they play an important role in various cellular processes. However, dysregulation of miRNAs is found to be a major cause of a disease. It has been demonstrated that miRNA expression is altered in many human cancers, suggesting that they may play an important role as disease biomarkers. Multiple reports have also noted the utility of miRNAs for the diagnosis of cancer. Among the large number of miRNAs present in a microarray data, a modest number might be sufficient to classify human cancers. Hence, the identification of differentially expressed miRNAs is an important problem particularly for the data sets with large number of miRNAs and small number of samples. RESULTS: In this regard, a new miRNA selection algorithm, called ?HEM, is presented based on rough hypercuboid approach. It selects a set of miRNAs from a microarray data by maximizing both relevance and significance of the selected miRNAs. The degree of dependency of sample categories on miRNAs is defined, based on the concept of hypercuboid equivalence partition matrix, to measure both relevance and significance of miRNAs. The effectiveness of the new approach is demonstrated on six publicly available miRNA expression data sets using support vector machine. The.632+ bootstrap error estimate is used to minimize the variability and biasedness of the derived results. CONCLUSIONS: An important finding is that the ?HEM algorithm achieves lowest B.632+ error rate of support vector machine with a reduced set of differentially expressed miRNAs on four expression data sets compare to some existing machine learning and statistical methods, while for other two data sets, the error rate of the ?HEM algorithm is comparable with the existing techniques. The results on several microarray data sets demonstrate that the proposed method can bring a remarkable improvement on miRNA selection problem. The method is a potentially useful tool for exploration of miRNA expression data and identification of differentially expressed miRNAs worth further investigation.

Dataset Information

Identification and characterization of miRNAs expressed in the bovine ovary.

Background

Results

Conclusion

Publications

Identification and characterization of miRNAs expressed in the bovine ovary.

Similar Datasets

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