Expression profiling dataset of competing endogenous RNA in pre-eclampsia

Area of Science:

• Genomics
• Biomolecular research
• Reproductive medicine

Background:

• Pre-eclampsia (PE) is a serious pregnancy complication.
• Understanding the molecular mechanisms of PE is crucial for early detection and management.
• Competing endogenous RNA (ceRNA) networks play a role in gene regulation.

Purpose of the Study:

• To provide raw and analyzed data on ceRNA expression profiles in severe pre-eclampsia (SPE) placentas.
• To support further research into the pathogenesis of pre-eclampsia.
• To identify potential novel biomarkers for early pre-eclampsia detection.

Main Methods:

• Microarray analysis was used to investigate ceRNA expression profiles.
• Differential expression analysis was performed on placentas from women with SPE and normal pregnancies.
• Data were submitted to the Gene Expression Omnibus (GEO) repository (accession number GSE102897).

Main Results:

• Identified differentially expressed circular RNAs (circRNAs), long noncoding RNAs (lncRNAs), and messenger RNAs (mRNAs) between normal and SPE placentas.
• The dataset includes comprehensive expression profiles of these RNA transcripts.
• The data descriptor serves as an extended version of methodologies described in a related publication.

Conclusions:

• The disseminated data can facilitate further investigation into the molecular mechanisms underlying pre-eclampsia.
• The identified differentially expressed RNAs hold potential as biomarkers for early pre-eclampsia prediction.
• This data descriptor enhances the accessibility of valuable research findings for the scientific community.