Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

RNAseq analysis of Chrnb4-cre driven Dicer conditional knockout (Dicer CKO) whole retinas

ABSTRACT: We have shown that Chrnb4-cre; Dicerflox/flox retinas (Dicer CKO) display a cone dystrophy by postnatal day P21, independent of rod degeneration. To elucidate which gene pathways were affected by Dicer loss, RNA sequencing was performed in whole neural retinas of P21 control and Dicer CKO mice. This experiment aims to identify which genes were differentially expressed between Dicer conditional knockout and control mice.

INSTRUMENT(S): Illumina HiSeq 4000

ORGANISM(S): Mus musculus

SUBMITTER: Jane Sowden

PROVIDER: E-MTAB-6133 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Shared Molecules

Only show the datasets with similarity scores above: 0.5

Threshold

0.5

Similar Datasets

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.