Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR26345792.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 1 of 1 |
Similar Datasets
Project description:Using small RNA-Seq(sRNA-Seq) to get small RNA profiling of dcl2/3/4, dcl1/2/3/4 and WT
2016-03-17 | GSE70913 | GEO
Project description:Using small RNA-Seq(sRNA-Seq) to get miRNA profiling of WT, snrk2.2/3/6, and hyl1-2 mutant
2017-04-12 | GSE93243 | GEO
Project description:1, Using mRNA-Seq to get expression profiling of rrp6l1-2 mutant and Col-0 wild-type (WT); 2,Using MethylC-Seq to provide single-base resolution of DNA methylation status in rrp6l1-2 mutant; 3, Using small RNA-Seq(sRNA-Seq) to get small RNA profiling of rrp6l1-2 and WT mRNA-Seq: 2 samples examined, WT and rrp6l1-2 mutant; MethylC-Seq: 1 sample examined, rrp6l1-2 mutant; small RNA-Seq: 2 samples examined, WT and rrp6l1-2 mutant
2014-04-16 | E-GEOD-50486 | biostudies-arrayexpress
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare small non-coding RNA profiling (snRNA-seq) in WT oocyte, sperm and 2PN stage embryos to those sperm and 2PN stage embryos derived from WT, Dicer cKO and Drosha cKO. We further study the roles of sperm-borne small RNA on fertilization and pre-implantation embryonic development. Methods: Small RNA profiles of adult wild-type (WT) oocytes, adult WT sperm, 2PN stage embryos, adult Dicer cKO/Drosha cKO sperm, 2PN stage embryos were generated by deep sequencing in duplicate, using Ion Torrent Proton. The sequence reads that passed quality filters were analyzed at the small RNA 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 small RNA (miRNA and endo-siRNA) in the oocyte, sperm and 2PN stage of WT and Dicer cKO/Drosha cKO mice with BWA workflow and 34,115 transcripts with TopHat workflow. Approximately 47% of the miRNAs showed differential expression between the WT and Dicer cKO sperm, ~52% of miRNAs were shown dysregulated in Drosha cKO sperm compared to those in WT sperm with a fold change ≥2.0 and p value <0.05. 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 small non-coding RNAs (miRNAs) in sperm and demonstrated that sperm-borne small RNAs are important for fertilization and early embrynic develoment, with biologic duplicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of small RNAs profiles in mouse sperm, oocytes and 2PN stage of embryos. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of small RNA contents within sperm or oocytes/embryos. We conclude that RNA-seq based small RNAs characterization in gametes would expedite genetic network analyses and permit the dissection of complex biologic functions during fertilization and embryonic development.
2015-10-08 | GSE73824 | GEO
Project description:1, Using mRNA-Seq to get expression profiling of rrp6l1-2 mutant and Col-0 wild-type (WT); 2,Using MethylC-Seq to provide single-base resolution of DNA methylation status in rrp6l1-2 mutant; 3, Using small RNA-Seq(sRNA-Seq) to get small RNA profiling of rrp6l1-2 and WT
2014-04-16 | GSE50486 | GEO
Project description:The goal of small RNA-seq is to identify the differentially expressed small RNAs (microRNA, 22G RNA, piRNA, snoRNA) in the wild-type (WT) and hrde-1 mutant of C.elegans at the normoxia reared and hypoxia treatment conditions at P0 generation, and those small RNAs maintained dysregulation in F1, F2 and F3 generation.
2022-12-13 | GSE188270 | GEO
Project description:The first GSSM of V. vinifera was reconstructed (MODEL2408120001). Tissue-specific models for stem, leaf, and berry of the Cabernet Sauvignon cultivar were generated from the original model, through the integration of RNA-Seq data. These models have been merged into diel multi-tissue models to study the interactions between tissues at light and dark phases.
2024-09-02 | MODEL2408160001 | BioModels