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Next Generation Sequencing Facilitates Quantitative Analysis of mRNA expression prolifes in placentas from wild Type,early-onset and later-onset PE mouse models

GSE168702 Mus musculus Expression profiling by high throughput sequencing 10 samples 2024/03/11 GPL21273
Summary
Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare transcriptome profiling (RNA-seq) of E17.5 placentas from control, early-onset (EO) and later-onset (LO) preeclampsia (PE) mice. Methods: E17.5 placental mRNA profiles of offspring from control, EO and LO PE mice were generated by deep sequencing, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the E17.5 placentas from control EO and LO PE mice with BWA workflow and 34,115 transcripts with TopHat workflow. R Conclusions: Our study represents the first detailed analysis of E17.5 placentas transcriptomes, with biologic replicates, generated by mRNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within tissue. We conclude that mRNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
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