Pluto Bioinformatics

GSE114939: RNA-seq distinguished dominant inflammatory profile in placenta from a preterm labor mouse model and control

Bulk RNA sequencing

Purpose: No gene expression profiles for the placenta in LPS-induced preterm labor mouse model have been published. The goal of this study was to obtain a comprehensive catalog of differentially expressed genes (DEGs) in the placenta using RNA-seq.; Methods: Preterm labor mouse model (P) and control pregnancy group (C) were gained using a protocol from R. Migale, et al., BMC MED 14 (2016):86. Briefly, on day 15.5 of gestation, an abdominal minilaparotomy was performed. The upper right uterine horn between the first and second sacs received injections of saline (C) or 20 mg E. coli LPS serotype O55:B5 (Sigma-Aldrich, Gillingham, UK) (P) to model preterm labor. Six hours after injections of LPS, the mice were sacrificed and placentas were excised and immediately snap-frozen in liquid nitrogen before being stored at 80C for subsequent analysis. Placental mRNA profiles were generated by deep sequencing using Illumina seq 2500. The sequence reads that passed quality filters were analyzed at the transcript isoform level with TopHat followed by Cufflinks. qRTPCR validation was performed using TaqMan and SYBR Green assays.; Results: We mapped about 44 million sequence reads per sample to the mouse genome (build mm8) and 25307 transcripts with TopHat workflow. 155 differentially expressed genes (DEGs) in placenta were identified between the preterm group and control group, with a fold change 1.5 and p value <0.05. 61 inflammation-related genes occupied the dominant role. 7 of these were validated with qRTPCR.; Conclusions: Our study represents the first detailed analysis of transcriptomes in placenta in LPS-induced preterm labor mouse model by RNA-seq technology. Dominant inflammatory profile in this model was gained, which gives us a better understanding of the exact molecular processes involved in the development of preterm labor after infection. SOURCE: Yi Xiaochun (329098686@qq.com) - Sun Yat-sen Memorial Hospital of the Sun Yat-sen University