Project description:Purpose: Cadmium (Cd) is detrimental to environment and human health, but the specific mechanism of the regulatory network is still remained unclear. Caenorhabditis elegans (C. elegans) is selected as the ideal model organism to investigate the effect of Cd exposure. Methods: We employed the phosphoproteomic technologies, high-throughput sequencing method and bioinformatic tools (RNAhybrid, Risearch2 and Targetscan) to investigate the phosphorylated change and the regulatory networks of circRNA, lncRNA, microRNA (miRNA) and mRNA after Cd exposure in C. elegans. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) were also employed. The relationship between transcriptional factors (TFs) and kinases, and the kinase-substrate were predicted using Jaspar database and iGPS, respectively. Results:26 differentially expressed circRNAs (DEcircRNAs), 143 lncRNAs (DElncRNAs), 69 miRNAs (DEmiRNAs) and 6209 mRNAs (DEmRNAs) were identified. According to qRCR, four DEcircRNAs and three DElncRNAs were found and confirmed the different expression levels between the treated and control group. 23 miRNAs and six miRNAs were the potential targets of the confirmed circRNAs and lncRNAs respectively using the predictive tools of RNAhybrid, RIsearch and Targetscan. Similarly, the target mRNAs of miRNAs were identified. Next, the regulatory network of lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA were established. Furthermore, five protein-coding genes might be regulated by DElnRNAs through cis-acting and 114 by trans-acting. The GO and KEGG analysis were performing on the parents’ genes of the mRNAs. GSEA was performed on all protein-coding genes, and the correlation between these genes and validated lncRNAs were used for pre-ranking. For the phosphopromotics, 42 differentially regulative phosphopeptides were identified. In this work, four novel pairs of TFs-kinases-substrate which might be influenced by Cd exposure were firstly constructed. Conclusions: Cd might mainly influence the reproductive function and aging of C. elegans through regulating the circRNAs and lncRNAs. Also, it might inhibit the expression of TFs to reduce the phosphorylated level of corresponding protein.

Project description:In platelets, splicing and translation occur in the absence of a nucleus. However, the integrity and stability of mRNAs derived from megakaryocyte progenitor cells remain poorly quantified on a transcriptome-wide level. As circular RNAs (circRNAs) are resistant to degradation by exonucleases, their abundance relative to linear RNAs can be used as a surrogate marker for mRNA stability in the absence of transcription. Here we show that circRNAs are enriched in human platelets 17-188 fold relative to nucleated tissues, and 14-26 fold relative to samples digested with RNAseR to selectively remove linear RNA. We compare RNAseq read depths inside and outside circRNAs to provide in silico evidence of transcript circularity, show that exons within circRNAs are enriched ~13X in platelets relative to nucleated tissues, and identify 3162 genes significantly enriched for circRNAs including some where all RNAs appear to be derived from circular molecules. We also confirm that this is a feature of other anucleate cells through transcriptome sequencing of mature erythrocytes, demonstrate that circRNAs are not enriched in megakaryocytes, and that linear RNAs decay more rapidly than circRNAs in platelet preparations. Collectively, these results suggest that circulating platelets have lost on aveage over 90% of their progenitor mRNAs, and that translation in platelets occurrs against the backdrop of a highly degraded transcriptome. Finally, we find that transcripts classified as products of reverse transcriptase template switching are both enriched in platelets and resistant to decay, countering the recent suggestion that up to 50% of rearranged RNAs are artefacts. A single rRNA depleted total RNA sample was sequenced. This together with 25 publicly available rRNA depleted total RNA samples (including 3 from platelets) were analysed using PTESFinder v 1 (http://sourceforge.net/projects/ptesfinder-v1/) to identify back-splice junctions, characteristic of circRNA transcripts. The contribution of circRNA producing exons was analysed on a gene by gene basis as follows: All circRNA transcripts identified in any sample were first pooled to define exons which can contribute to circRNA generation using custom scripts (available on request). For each sample, expression estimates (RPKMI) across all circRNA producing exons were computed for each locus using the total size of exons (in bp) and the read counts mapping to them. Similarly, total size and exonic read counts for exons for which no circRNA were detected in any sample were used to compute expression estimates (RPKME) for non-circRNA producing exons for each locus. Abundance ratios (RPKMI/RPKME and RPKMI/RPKMI+RPKME) were calculated and compared between Platelets and human tissues using Wilcoxon signed-rank test. Please note that the '25sample_info_accn_no.txt' contains the accession numbers and tissue/cell type information for 25 samples analyzed together.

Dataset Information

LncRNA and circRNA expression profiles of Aβ25-35-induced AD mice hippocampus treated with Tripterygium Glycoside

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets