NCBI Logo
GEO Logo
   NCBI > GEO > Accession DisplayHelp Not logged in | LoginHelp
GEO help: Mouse over screen elements for information.
          Go
Series GSE83794 Query DataSets for GSE83794
Status Public on Jan 10, 2018
Title Next-generation Sequencing (NGS) identified genome-wide profiles of piwi-interacting RNAs (piRNAs) in human Epithelial Ovarian Cancers (EOCa)
Organism Homo sapiens
Experiment type Non-coding RNA profiling by high throughput sequencing
Summary Purpose: The aim of this study is to identify known and novel small RNAs (Piwi-interacting RNAs and microRNAs) in normal ovary and epithelial ovarian malignancies by adopting high-throughput RNA sequencing (RNA-Seq) and unveil their possible functions in neoplastic pathways of the two most frequently observed and highly lethal subtypes of epithelial ovarian cancers, endometrioid ovarian cancer (ENOCa) and serous ovarian cancer (SOCa). The study has been performed in normal ovarian tissues as well as malignant tissues of these cancer subtypes.
Methods: 1 µg of total RNA was used as the starting material for library preparation as prescribed by Illumina Truseq small RNA library protocol. Small RNA sequencing was carried out by Genotypic Technology, Bangalore, India on Illumina Next-Seq 500 platform. Library preparation was done by performing 3' and 5' adapter ligation followed by reverse transcription of cDNA and amplification of the library. The construct of the library was fractionated to select 16-40 nucleotide insert of small RNAs using PAGE. The quality check of the library was done in Agilent Technologies 2100 Bioanalyzer using a DNA-specific chip, such as High Sensitivity DNA. The sequence reads that passed through Quality Check by FastQC and aligned to the human genome (hg19) were further analysed using in-house pipelines and set of known and novel piRNAs and miRNAs were identified. The sets of known piRNAs and miRNAs identified were assessed for their involvement in neoplastic processes of ovarian cancer subtypes by performing target analysis and GO enrichment studies.
Results: Using an in-house prediction pipeline, we mapped about 10-15 million sequence reads per sample to the human genome (hg19) and detected 256, 234 and 219 annotated piRNAs in ENOCa, SOCa, and normal ovary respectively; whereas the average number of known miRNAs present in each sample was estimated to be 480. The annotated piRNAs obtained from each sample exhibited varied length distribution between 26-32 nts.
Conclusions: For the first time, our study reported the presence of piRNAs in ENOCa, SOCa and normal ovarian tissue from the next-gen sequencing of small RNAs of 16-40 nts length. The extensive catalogue of human EOCa small RNAs (both piRNAs and miRNAs) detected in this study provides a useful resource to dissect complex neoplastic events that are possibly mediated by these ncRNAs, especially by piRNAs. Moreover, these piRNAs could be used as probable small RNA biomarkers for the EOCa.
 
Overall design Small RNA profile of human epithelial ovarian cancer and normal epithelial ovarian tissue was generated by deep sequencing using Illumina Next-Seq 500
 
Contributor(s) Singh G, Mallick B
Citation(s) 29320577
Submission date Jun 28, 2016
Last update date May 15, 2019
Contact name Dr. Bibekanand Mallick
E-mail(s) vivek.iitian@gmail.com
Organization name National Institute of Technology
Department Department of Life Science
Lab RNAi & Functional Genomics Lab.
Street address NIT Rourkela
City Rourkela
State/province Odisha
ZIP/Postal code 769008
Country India
 
Platforms (1)
GPL18573 Illumina NextSeq 500 (Homo sapiens)
Samples (3)
GSM2218896 NO
GSM2218897 ENOCa
GSM2218898 SOCa
Relations
BioProject PRJNA327030
SRA SRP077450

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE83794_RAW.tar 20.0 Kb (http)(custom) TAR (of TXT)
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

| NLM | NIH | GEO Help | Disclaimer | Accessibility |
NCBI Home NCBI Search NCBI SiteMap