Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA257423 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We generated RRBS data to analyse the DNA methylation profiling among WT-AG-haESCs, DKO-AG-haESCs and round spermatids, we found deletion of H19 and Gtl2 DMRs do not change the methylation patterns in AG-haESCs base on all detected CpG sites.
2015-06-29 | GSE60075 | GEO
Project description:We generated RRBS data to analyse the DNA methylation profiling among WT-AG-haESCs, DKO-AG-haESCs and round spermatids, we found deletion of H19 and Gtl2 DMRs do not change the methylation patterns in AG-haESCs base on all detected CpG sites. We used round spermatids as control and analysed the DNA methylation profiles of all the cell lines were by RRBS.
2015-06-29 | E-GEOD-60075 | biostudies-arrayexpress
Project description:DNA methylation profiling in WT-AG-haESCs, DKO-AG-haESCs and round spermatids
| PRJNA257422 | ENA
Project description:RNA seq result shows that WT-AG-haESCs and DKO-AG-haESCs samples are clustered together using hierarchical cluster both in the all expression genes and imprinting genes. This suggests that DKO of DMRs of H19 and Gtl2 do not change the overall gene expression patterns in AG-haESCs. We used round spermatids as control. Using RNA-seq, profile of all the expression genes and imprinting genes beteween different samples were analysed.
2015-06-29 | E-GEOD-60072 | biostudies-arrayexpress
Project description:RNA seq result shows that WT-AG-haESCs and DKO-AG-haESCs samples are clustered together using hierarchical cluster both in the all expression genes and imprinting genes. This suggests that DKO of DMRs of H19 and Gtl2 do not change the overall gene expression patterns in AG-haESCs.
2015-06-29 | GSE60072 | GEO
Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and dKO round spermatids Transcriptomes
| PRJNA254123 | ENA
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived WT and dKO round spermatids transcriptome profiling (RNA-seq) Methods: Adult WT and dKO round spermatids mRNA profiles mice were generated by deep sequencing, in dulplicate. 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. qRT–PCR validation was performed using TaqMan and SYBR Green assays 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 retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and dKO round spermatids, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions: Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-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 a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Adult wild type (WT) and dKO mouse round spermatids were generated by deep sequencing, in dulplicate, using Illumina GAIIx.
2014-07-03 | E-GEOD-59017 | biostudies-arrayexpress
Project description:Our lab first derived mouse androgenetic haploid embryonic stem cells (AG-haESCs) and demonstrated that AG-haESCs can be used as an “artificial spermatids” to generate gene-edited semi-cloned (SC) mice through intracytoplasmic injection (ICAHCI) into mature oocyte, even though the birth efficiency is very low. Further we proved that H19-DMR and IG-DMR were the main barrier to generate viable mice through androgenetic and parthenogenetic haESCs. More importantly, AG-haESCs mediated SC technology combined with CRISPR-Cas9 is a powerful tool to generate gene-modified mouse models and carry out genetic screening at organismal level. However, it is still not clear how the H19-DMR and IG-DMR coordinately regulate SC embryo development. Here, we found that the H19-DMR and IG-DMR regulate the development of SC embryos in spatio-temporal scales. Firstly, we found that the H19-DMR and IG-DMR are not indispensable for the development of preimplantation of SC embryos. Secondly, H19-DMR is essential for the development of SC embryos in mid-gestation and IG-DMR takes effect in late-gestation. Further, the maintenance of paternal H19-DMR methylation status and deletion of paternal H19 transcription unit play a key role in the structures and transport functions of SC embryo placenta. Importantly, AG-haESCs carrying triple deletions, including H19, H19-DMR and IG-DMR, can further improve the efficiency in generation of viable, normal-size, and fertile mice.
2019-09-17 | GSE132254 | GEO