Dataset Information

Hybridization-based reconstruction of small non-coding RNA transcripts from deep sequencing data.

ABSTRACT: Recent advances in RNA sequencing technology (RNA-Seq) enables comprehensive profiling of RNAs by producing millions of short sequence reads from size-fractionated RNA libraries. Although conventional tools for detecting and distinguishing non-coding RNAs (ncRNAs) from reference-genome data can be applied to sequence data, ncRNA detection can be improved by harnessing the full information content provided by this new technology. Here we present NorahDesk, the first unbiased and universally applicable method for small ncRNAs detection from RNA-Seq data. NorahDesk utilizes the coverage-distribution of small RNA sequence data as well as thermodynamic assessments of secondary structure to reliably predict and annotate ncRNA classes. Using publicly available mouse sequence data from brain, skeletal muscle, testis and ovary, we evaluated our method with an emphasis on the performance for microRNAs (miRNAs) and piwi-interacting small RNA (piRNA). We compared our method with Dario and mirDeep2 and found that NorahDesk produces longer transcripts with higher read coverage. This feature makes it the first method particularly suitable for the prediction of both known and novel piRNAs.

SUBMITTER: Ragan C

PROVIDER: S-EPMC3439898 | biostudies-other | 2012 Sep

REPOSITORIES: biostudies-other

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Publications

Hybridization-based reconstruction of small non-coding RNA transcripts from deep sequencing data.

Ragan Chikako C Mowry Bryan J BJ Bauer Denis C DC Bauer Denis C DC

Nucleic acids research 20120616 16

Recent advances in RNA sequencing technology (RNA-Seq) enables comprehensive profiling of RNAs by producing millions of short sequence reads from size-fractionated RNA libraries. Although conventional tools for detecting and distinguishing non-coding RNAs (ncRNAs) from reference-genome data can be applied to sequence data, ncRNA detection can be improved by harnessing the full information content provided by this new technology. Here we present NorahDesk, the first unbiased and universally appli ...[more]

PMID: 22705792

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Project description:PIWI-interacting RNAs (piRNAs) are a novel class of small ncRNAs initially isolated from germ line cells; although recent studies report that they are expressed also in somatic cells. To elucidate the role of piRNAs in somatic cells, in particular from breast cancer, we performed the first extensive next generation sequencing expression analysis of small RNA transcriptomes of hormone responsive breast cancer cell lines in different culture conditions. In addition, to understand the behavior of piRNAs with respect to miRNAs in breast tumor tissues, small RNA sequence data set available in Gene Expression Omnibus (GSE39162) database was used. Results led to the identification of ~100 and ~150 human piRNAs in the breast cancerous cell lines and tumors respectively, several of which differentially expressed in cell lines under different experimental conditions tested or in response to ERβ and in tumor tissues. Western blotting and Q-PCR analysis also revealed the presence in breast cell lines of PIWIL (PIWI Like) subfamily members proteins encoded in the human genome (PIWIL2/HILI and PIWIL4/HIWI2) and of other components of the piRNA biogenesis pathways, suggesting that this might indeed be functional in somatic cells. These results show that piRNAs are expressed in human somatic cells, in particular in cancer, where their expression is influenced by neoplastic transformation, growth conditions and estrogen receptor beta. More important, we demonstrate for the first time a distinct pattern of piRNAs expression in cancerous vs normal breast tissues, which suggests a potential role of these epigenetic modulators in mammary carcinogenesis and maintenance of the cancer cell phenotype. In addition, to understand the behavior of piRNAs with respect to miRNAs in breast tumor tissues, small RNA sequence data set available in Gene Expression Omnibus (GEO; GSM957192 TAX577740T ,GSM957194 TAX577740N, GSM957195 TAX577453T, GSM957197 TAX577453N, GSM957198 TAX577745T, GSM957200 TAX577745N, GSM957201 TAX577579T, GSM957203 TAX577579N) was used.

Dataset Information

Hybridization-based reconstruction of small non-coding RNA transcripts from deep sequencing data.

Publications

Hybridization-based reconstruction of small non-coding RNA transcripts from deep sequencing data.

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