Dataset Information

Systematic Identification and Characterization of Long Non-coding RNAs in Mouse Mature Sperm

ABSTRACT: Increasingly, studies have shown that mature spermatozoa contain many transcripts including mRNAs and miRNAs. However, the expression profile of long noncoding RNAs (lncRNAs) in mammalian sperm has not been systematically investigated. Here, we used highly purified RNA to investigate lncRNA expression profiles in mouse mature sperm by stranded-specific RNA-seq. We identified 20907 known and 4088 novel lncRNAs transcripts, and the existence of intact lncRNAs was confirmed by RT-PCR and fluorescence in situ hybridization on two representative lncRNAs. Compared with testes, 2873 upregulated and 6629 downregulated lncRNAs and 1237 upregulated and 2513 downregulated mRNAs were identified in sperm. Based on the “Cis and Trans” RNA-RNA interaction principle, we found 1793 targeted coding genes of differently expressed lncRNAs. In terms of GO analysis, differentially expressed lncRNAs targeted genes mainly related to nucleic acid metabolic, protein modification, chromatin and histone modification, sperm function, and spermatogenesis. In contrast, differentially expressed transcripts of mRNAs were highly enriched for nucleic acid metabolic, spermatogenesis, sperm function, and chromatin organization. Furthermore, KEGG pathway analysis showed that the differentially expressed lncRNAs were involved in mRNA surveillance and AMPK signaling pathways. Besides these two pathways, RNA transport splicesome was another pathway incorporated with the differentially expressed mRNA. In summary, this study provides a preliminary database valuable for identifying lncRNAs critical in the late stage of spermatogenesis or important for sperm function regulation.

ORGANISM(S): Mus musculus

PROVIDER: GSE88732 | GEO | 2017/02/04

SECONDARY ACCESSION(S): PRJNA348417

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Objective: Seek the differentially expressed mRNAs and long non-coding RNAs (LncRNAs) to construct the modulated network and seek for the hub LncRNAs during the process of human immunodeficiency virus (HIV) transcription. Method: Blood samples from HIV-infections were collected. They were divided into transcription active group and relatively inactive group based on the quantitative detection results of total HIV DNA and cell-association RNA (CA-RNA) from peripheral blood mononuclear cells (PBMCs). Individuals within each group were matched by age and genders. Microarray chips detection technology were utilized to detect and find the differentially expressed LncRNAs and mRNAs by statistical method of paired T test, then underwent some bioinformatics analysis. Result: 1240 differentially expressed genes (include 689 LncRNAs and 551 mRNAs) were found. Gene ontology analysis showed the differentially expressed mRNAs mainly enriched in positive or negative gene expression, immune cell formation or epigenetic regulation in the biological process; nucleosome, nucleolus, cytoplasm, nuclear chromatin in the cell component; RNA polymerase II regulatory region sequence-specific DNA binding, DNA, histone, and nucleic acid binding, transcription factor activity in molecular function. Pathway analysis showed the differentially expressed mRNAs enriched in the biological pathways such as systemic lupus erythematosus, alcoholism, cytokine-cytokine receptor interaction, RNA transport, mRNA surveillance pathway, Pathways in cancer, etc. Cis and trans analysis to the differentially expressed LncRNAs searching its targeted genes and then made intersection for the differentially expressed mRNAs, then constructed the modulated network between LncRNAs and mRNAs. Based on this modulated network, four hub transcripts were excavated and validated by quantitative real-time PCR to confirm the veracity of microarray analysis findings. Two hub transcripts of lnc-CCNYL1-1:2 and ZNF793 were found directly interacted in the modulated network and their level of expression transformed parallelly. Conclusion: Quantitative detection results of cellular levels of total HIV DNA and RNA can distinguish whether HIV is in the state of active transcription. During process of HIV transcription, the differentially expressed LncRNAs involve the biological process of gene expression regulation, the hub genes excavated form the modulated network may become the potential candidate targets for HIV antiviral treatment.

Dataset Information

Systematic Identification and Characterization of Long Non-coding RNAs in Mouse Mature Sperm

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets