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MicroRNA profiling of human pancreas development.

ABSTRACT: MicroRNAs (miRNAs) are non-coding RNAs that play a fundamental role in regulation of gene expression affecting differentiation and development. In particular, miRNAs have been described to regulate genes important for pancreatic development and islet function. The aim of this study was to determine the miRNA expression signature during human pancreas development. We identified 212 miRNAs that were expressed throughout different gestational ages. From those, 4 miRNAs increased (group I), 35 miRNAs decreased (group II), during pancreatic development. The expression of the remaining 173 miRNAs was relatively constant throughout all assessed gestational ages. The determination of the specific group of miRNAs expressed in the human developing pancreas may further the understanding of gene expression regulation during this important process.

ORGANISM(S): Homo sapiens

PROVIDER: GSE22026 | GEO | 2010/09/06

SECONDARY ACCESSION(S): PRJNA127451

REPOSITORIES: GEO

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Project description:Purpose: Next-generation sequencing technologies allow miRNA detection at an unprecedented sensitivity.Early- to mid-gestational fetal mammalian skin wounds heal rapidly and without scarring. The goals of this study are to obtain the differently expressed miRNAs between late- and mid-gestational fetal Keratinocytes for further studies. Methods: Keratinocytes were obtained from six fetal skin samples dividied into two groups: a mid-gestation group and a late-gestation group. RNA extracted from Keratinocytes was used to prepare a small RNA library for next-generation sequencing (NGS) using an Illumina Genome Analyzer IIx. To uncover potentially novel microRNA (miRNAs), the mirTools 2.0 web server was used to identify candidate novel human miRNAs from the NGS data.UCSC Genome Browser and the Vienna RNAfold web server were used to further validate the novel miRNA candidates. The repeatability of the expression levels detected by NGS was confirmed by real-time quantitative RT-PCR. Results: Using an optimized data analysis workflow, we detected a total of 99,354,224 raw reads from the six samples, 85,252,341 (85.81%) were high-quality reads (≥ 18nt). After alignment to the human genome (GRCH38), the number of genome-aligned reads was 74,678,115 (87.60% of the high-quality reads). The number of sequence reads that correspond to known miRNAs was 61,587,749 (82.47% of the genome-matching reads), as was determined by perfect sequence matching to the database of known miRNAs (miRBase release 18). After removing the matched non-coding RNAs (Release 10), 8,755,258 reads remained for identification of novel miRNA candidates by mirTools 2.0. The results revealed the existence of 202 novel miRNA candidates and 29 known miRNAs that were not listed in miRBase release 18. Of the 202 potential novel miRNAs, 106 candidates were detected by at least 10 counts, by NGS, indicating that they have a higher probability of being novel human miRNAs. Using Student's t-test, 173 known miRNAs and 23 novel miRNA candidates were found to be statistically significant (P values < 0.05). The expression of 22 novel miRNA candidates and 88 known miRNAs was changed by more than 2.0-fold (known: 15 up-regulated and 73 down-regulated; novel: two up-regulated and 20 down-regulated). Conclusions: Our study represents the first detailed analysis of human miRNAs in fetal Keratinocytes. Using mirTools 2.0 web server, we have revealed the existence of 202 novel miRNA candidates. Of the 202 potential novel miRNAs, 106 candidates were detected by at least 10 counts, by NGS, indicating that they have a higher probability of being novel human miRNAs. Taken together, our results provide compelling evidence that dynamic expression of miRNAs in fetal Keratinocytes at different gestational ages. MiRNAs presenting altered expression at different gestational ages in fetal Keratinocytes may contribute to scarless wound healing in early- to mid-gestational fetal Keratinocytes, and thus may be new targets for potential scar prevention and reduction therapies.

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MicroRNA profiling of human pancreas development.

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