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| Status |
Public on Mar 11, 2024 |
| Title |
Next Generation Sequencing Facilitates Quantitative Analysis of mRNA expression prolifes in placentas from wild Type,early-onset and later-onset PE mouse models |
| Organism |
Mus musculus |
| Experiment type |
Expression profiling by high throughput sequencing
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| 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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| Overall design |
E17.5 placental mRNA profiles from Control (Con), EO and LO PE mice were generated by deep sequencing, in quadruplication, using Illumina GAIIx
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| Contributor(s) |
Liu X, Zhao W |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
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| Submission date |
Mar 11, 2021 |
| Last update date |
Mar 11, 2024 |
| Contact name |
Wen-Long Zhao |
| E-mail(s) |
zbyzwl1919@sina.com
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| Organization name |
The International Peace Maternity and Child Health Hospital
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| Street address |
Guangyuan road 145#
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| City |
Shanghai |
| ZIP/Postal code |
200030 |
| Country |
China |
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| Platforms (1) |
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| Samples (10)
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| Relations |
| BioProject |
PRJNA713561 |
| SRA |
SRP310236 |
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