Correction: HENMT1 and piRNA Stability Are Required for Adult Male Germ Cell Transposon Repression and to Define the Spermatogenic Program in the Mouse

Integrated Metabolomic and Transcriptomic Analysis of Modified Nucleosides for Biomarker Discovery in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for ~75% of kidney cancers. The biallelic inactivation of the von Hippel-Lindau tumor suppressor gene (VHL) is the truncal driver mutation of most cases of ccRCC. Cancer cells are metabolically reprogrammed and excrete modified nucleosides in larger amounts due to their increased RNA turnover. Modified nucleosides occur in RNAs and cannot be recycled by salvage pathways. Their potential as biomarkers has been demonstrated for breast or pancreatic cancer. To assess their suitability as biomarkers in ccRCC, we used an established murine ccRCC model, harboring Vhl, Trp53 and Rb1 (VPR) knockouts. Cell culture media of this ccRCC model and primary murine proximal tubular epithelial cells (PECs) were investigated by HPLC coupled to triple-quadrupole mass spectrometry using multiple-reaction monitoring. VPR cell lines were significantly distinguishable from PEC cell lines and excreted higher amounts of modified nucleosides such as pseudouridine, 5-methylcytidine or 2'-O-methylcytidine. The method's reliability was confirmed in serum-starved VPR cells. RNA-sequencing revealed the upregulation of specific enzymes responsible for the formation of those modified nucleosides in the ccRCC model. These enzymes included Nsun2, Nsun5, Pus1, Pus7, Naf1 and Fbl. In this study, we identified potential biomarkers for ccRCC for validation in clinical trials.

Exploring Potential Regulatory Anesthetic Drugs Based on RNA Binding Protein and Constructing CESC Prognosis Model: A Study Based on TCGA Database

Objective

To investigate the differential expression of RBPs in cervical squamous cell carcinoma (CESC), analyze the regulatory effect of narcotic drugs on RBPs, and establish the prognostic risk model of CESC patients.

Methods

RNA-SEQ data and clinical case data of cancer and normal samples from CESC patients were obtained from the Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) database. Differentially expressed RBPs were screened by R language and enriched. The CMAP database is used to predict the anesthetic drugs that regulate the differential expression of RBPs. The prognostic risk score model was constructed by COX regression analysis. Risk score of each CESC patient was calculated and divided into high-risk group and low-risk group according to the median risk score. The prediction efficiency of prognostic risk model was evaluated by Kaplan-Meier (KM) analysis and receiver operating characteristic (ROC) curve, and the correlation between prognostic risk model and clinical characteristics was analyzed. Immunohistochemistry was used to detect the expression of RNASEH2A and HENMT1 in tissues.

Results

There were 65 differentially expressed RBPs in CESC. Five anesthetics, including benzocaine, procaine, pentoxyverine, and tetracaine were obtained to regulate RBPs. Survival analysis showed that seven genes were related to the prognosis of patients, and the CESC risk score model was constructed by COX regression. The risk score can be used as an independent prognostic factor. RNASEH2A and HENMT1 are up-regulated in tumors, which can effectively distinguish normal tissues from tumor tissues.

Conclusion

It is found that different anesthetic drugs have different regulatory effects on the differential expression of RBPs. Based on the differentially expressed RBPs, the prognostic risk score model of CESC patients was constructed. To provide ideas for the formulation of individualized precise anesthesia scheme and cancer pain analgesia scheme, which is helpful to improve the perioperative survival rate of cancer patients.

3'-Terminal 2'-O-methylation of lung cancer miR-21-5p enhances its stability and association with Argonaute 2

Methylation of miRNAs at the 2′-hydroxyl group on the ribose at 3′-end (2′-O-methylation, 2′Ome) is critical for miRNA function in plants and Drosophila. Whether this methylation phenomenon exists for mammalian miRNA remains unknown. Through LC–MS/MS analysis, we discover that majority of miR-21-5p isolated from human non-small cell lung cancer (NSCLC) tissue possesses 3′-terminal 2′Ome. Predominant 3′-terminal 2′Ome of miR-21-5p in cancer tissue is confirmed by qRT-PCR and northern blot after oxidation/β-elimination procedure. Cancerous and the paired non-cancerous lung tissue miRNAs display different pattern of 3′-terminal 2′Ome. We further identify HENMT1 as the methyltransferase responsible for 3′-terminal 2′Ome of mammalian miRNAs. Compared to non-methylated miR-21-5p, methylated miR-21-5p is more resistant to digestion by 3′→5′ exoribonuclease polyribonucleotide nucleotidyltransferase 1 (PNPT1) and has higher affinity to Argonaute-2, which may contribute to its higher stability and stronger inhibition on programmed cell death protein 4 (PDCD4) translation, respectively. Our findings reveal HENMT1-mediated 3′-terminal 2′Ome of mammalian miRNAs and highlight its role in enhancing miRNA’s stability and function.

The Importance of Small Non-Coding RNAs in Human Reproduction: A Review Article

Background

MicroRNAs (miRNA) play a key role in the regulation of gene expression through the translational suppression and control of post-transcriptional modifications.

Aim

Previous studies demonstrated that miRNAs conduct the pathways involved in human reproduction including maintenance of primordial germ cells (PGCs), spermatogenesis, oocyte maturation, folliculogenesis and corpus luteum function. The association of miRNA expression with infertility, polycystic ovary syndrome (PCOS), premature ovarian failure (POF), and repeated implantation failure (RIF) was previously revealed. Furthermore, there are evidences of the importance of miRNAs in embryonic development and implantation. Piwi-interacting RNAs (piRNAs) and miRNAs play an important role in the post-transcriptional regulatory processes of germ cells. Indeed, the investigation of small RNAs including miRNAs and piRNAs increase our understanding of the mechanisms involved in fertility. In this review, the current knowledge of microRNAs in embryogenesis and fertility is discussed.

Conclusion

Further research is necessary to provide new insights into the application of small RNAs in the diagnosis and therapeutic approaches to infertility.

IsopiRBank: a research resource for tracking piRNA isoforms

PIWI-interacting RNAs (piRNAs) are essential for transcriptional and post-transcriptional regulation of transposons and coding genes in germline. With the development of sequencing technologies, length variations of piRNAs have been identified in several species. However, the extent to which, piRNA isoforms exist, and whether these isoforms are functionally distinct from canonical piRNAs remain uncharacterized. Through data mining from 2154 datasets of small RNA sequencing data from four species (Homo sapiens, Mus musculus, Danio rerio and Drosophila melanogaster), we have identified 8 749 139 piRNA isoforms from 175 454 canonical piRNAs, and classified them on the basis of variations on 5′ or 3′ end via the alignment of isoforms with canonical sequence. We thus established a database named IsopiRBank. Each isoforms has detailed annotation as follows: normalized expression data, classification, spatiotemporal expression data and genome origin. Users can also select interested isoforms for further analysis, including target prediction and Enrichment analysis. Taken together, IsopiRBank is an interactive database that aims to present the first integrated resource of piRNA isoforms, and broaden the research of piRNA biology. IsopiRBank can be accessed at http://mcg.ustc.edu.cn/bsc/isopir/index.html without any registration or log in requirement.

Database URL: http://mcg.ustc.edu.cn/bsc/isopir/index.html