MicroRNAs (miRNAs) are small non-coding RNAs (typically consisting of 18–25 nucleotides) that negatively control expression of target genes at the post-transcriptional level. Owing to the biological significance of miRNAs, miRTarBase was developed to provide comprehensive information on experimentally validated miRNA–target interactions (MTIs). To date, the database has accumulated >13,404 validated MTIs from 11,021 articles from manual curations. In this update, a text-mining system was incorporated to enhance the recognition of MTI-related articles by adopting a scoring system. In addition, a variety of biological databases were integrated to provide information on the regulatory network of miRNAs and its expression in blood. Not only targets of miRNAs but also regulators of miRNAs are provided to users for investigating the up- and downstream regulations of miRNAs. Moreover, the number of MTIs with high-throughput experimental evidence increased remarkably (validated by CLIP-seq technology). In conclusion, these improvements promote the miRTarBase as one of the most comprehensively annotated and experimentally validated miRNA–target interaction databases. The updated version of miRTarBase is now available at http://miRTarBase.cuhk.edu.cn/.

MicroRNAs (miRNAs) are noncoding RNAs with 18–26 nucleotides; they pair with target mRNAs to regulate gene expression and produce significant changes in various physiological and pathological processes. In recent years, the interaction between miRNAs and their target genes has become one of the mainstream directions for drug development. As a large-scale biological database that mainly provides miRNA–target interactions (MTIs) verified by biological experiments, miRTarBase has undergone five revisions and enhancements. The database has accumulated >2 200 449 verified MTIs from 13 389 manually curated articles and CLIP-seq data. An optimized scoring system is adopted to enhance this update’s critical recognition of MTI-related articles and corresponding disease information. In addition, single-nucleotide polymorphisms and disease-related variants related to the binding efficiency of miRNA and target were characterized in miRNAs and gene 3′ untranslated regions. miRNA expression profiles across extracellular vesicles, blood and different tissues, including exosomal miRNAs and tissue-specific miRNAs, were integrated to explore miRNA functions and biomarkers. For the user interface, we have classified attributes, including RNA expression, specific interaction, protein expression and biological function, for various validation experiments related to the role of miRNA. We also used seed sequence information to evaluate the binding sites of miRNA. In summary, these enhancements render miRTarBase as one of the most research-amicable MTI databases that contain comprehensive and experimentally verified annotations. The newly updated version of miRTarBase is now available at https://miRTarBase.cuhk.edu.cn/.

Protein post-translational modifications (PTMs) play an important role in different cellular processes. In view of the importance of PTMs in cellular functions and the massive data accumulated by the rapid development of mass spectrometry (MS)-based proteomics, this paper presents an update of dbPTM with over 2 777 000 PTM substrate sites obtained from existing databases and manual curation of literature, of which more than 2 235 000 entries are experimentally verified. This update has manually curated over 42 new modification types that were not included in the previous version. Due to the increasing number of studies on the mechanism of PTMs in the past few years, a great deal of upstream regulatory proteins of PTM substrate sites have been revealed. The updated dbPTM thus collates regulatory information from databases and literature, and merges them into a protein-protein interaction network. To enhance the understanding of the association between PTMs and molecular functions/cellular processes, the functional annotations of PTMs are curated and integrated into the database. In addition, the existing PTM-related resources, including annotation databases and prediction tools are also renewed. Overall, in this update, we would like to provide users with the most abundant data and comprehensive annotations on PTMs of proteins. The updated dbPTM is now freely accessible at https://awi.cuhk.edu.cn/dbPTM/.

Circular RNAs (circRNAs), which are single-stranded RNA molecules that have individually formed into a covalently closed continuous loop, act as sponges of microRNAs to regulate transcription and translation. CircRNAs are important molecules in the field of cancer diagnosis, as growing evidence suggests that they are closely related to pathological cancer features. Therefore, they have high potential for clinical use as novel cancer biomarkers. In this article, we present our updates to CircNet (version 2.0), into which circRNAs from circAtlas and MiOncoCirc, and novel circRNAs from The Cancer Genome Atlas database have been integrated. In total, 2732 samples from 37 types of cancers were integrated into CircNet 2.0 and analyzed using several of the most reliable circRNA detection algorithms. Furthermore, target miRNAs were predicted from the full-length circRNA sequence using three reliable tools (PITA, miRanda and TargetScan). Additionally, 384 897 experimentally verified miRNA–target interactions from miRTarBase were integrated into our database to facilitate the construction of high-quality circRNA–miRNA–gene regulatory networks. These improvements, along with the user-friendly interactive web interface for data presentation, search, and visualization, showcase the updated CircNet database as a powerful, experimentally validated resource, for providing strong data support in the biomedical fields. CircNet 2.0 is currently accessible at https://awi.cuhk.edu.cn/∼CircNet.

Preeclampsia is a life-threating pregnancy disorder, especially preterm preeclampsia and early-onset preeclampsia, the heterogeneity and complexity of preeclampsia make it difficult to predict risk and develop treatments. Plasma cell-free RNA carries unique information from human tissue and may be useful for noninvasive monitoring of maternal, placental, and fetal dynamics during pregnancy. This study aimed to investigate various RNA biotypes associated with preeclampsia in plasma and develop classifiers to predict preterm preeclampsia and early-onset preeclampsia before diagnosis. We performed a novel cell-free RNA sequencing method named PALM-Seq to investigate the cell-free RNA characteristics of 715 healthy and 202 preeclampsia pregnancies before symptom onset. We explored changes in the abundance of different RNA biotypes in plasma between healthy and preeclampsia samples and built preterm preeclampsia and early-onset preeclampsia prediction classifiers using machine learning methods. Furthermore, we validated the performance of the classifiers using the external and internal validation cohorts and assessed the area under the curve and positive predictive value. We detected 77 differentially expressed genes including mRNA (44%) and miRNA (26%) between healthy and preterm preeclampsia mothers before symptom onset, which could separate preterm preeclampsia from healthy samples and play critical functional roles in preeclampsia physiology. We developed two classifiers for predicting preterm preeclampsia and early-onset preeclampsia before diagnosis based on 13 cell-free RNA signatures and two clinical features (IVF and MAP), respectively. Notably, both classifiers showed enhanced performance compared to the existing methods: the preterm preeclampsia prediction model achieved 81% area under the curve and 68% positive predictive value in an independent validation cohort (preterm PE, n=46; control, n=151); the early-onset preeclampsia prediction model had an area under the curve of 88% and a positive predictive value of 73% in an external validation cohort (early-onset PE, n=28; control, n=234). Furthermore, we demonstrated downregulation of miRNAs may play vital roles in preeclampsia through the upregulation of preeclampsia-relevant target genes. Our cohort study presented the first comprehensive transcriptomic landscape of different RNA biotypes in preeclampsia and developed two advanced classifiers with significant clinical importance for preterm preeclampsia and early-onset preeclampsia prediction before symptom onset. We demonstrated for the first time that messenger RNA, microRNA, and long noncoding RNA can simultaneously serve as potential biomarkers of preeclampsia, holding the promise of prevention of preeclampsia in advance. Abnormal cell-free messenger RNA, microRNA and long noncoding RNA molecular changes help to elucidate the pathogenic determinants of preeclampsia, and open new therapeutic windows to effectively reduce pregnancy complications and fetal morbidity.

BMI1 plays critical roles in maintaining the self-renewal of hematopoietic, neural, intestinal stem cells, and cancer stem cells (CSCs) for a variety of cancer types. BMI1 promotes cell proliferative life span and epithelial to mesenchymal transition (EMT). Upregulation of BMI1 occurs in multiple cancer types and is associated with poor prognosis. Mechanistically, BMI1 is a subunit of the Polycomb repressive complex 1 (PRC1), and binds the catalytic RING2/RING1b subunit to form a functional E3 ubiquitin ligase. Through mono-ubiquitination of histone H2A at lysine 119 (H2A-K119Ub), BMI1 represses multiple gene loci; among these, the INK4A/ARF locus has been most thoroughly investigated. The locus encodes the p16INK4A and p14/p19ARF tumor suppressors that function in the pRb and p53 pathways, respectively. Its repression contributes to BMI1-derived tumorigenesis. BMI1 also possesses other oncogenic functions, specifically its regulative role in DNA damage response (DDR). In this process, BMI1 ubiquitinates histone H2A and γH2AX, thereby facilitating the repair of double-stranded DNA breaks (DSBs) through stimulating homologous recombination and non-homologous end joining. Additionally, BMI1 compromises DSB-induced checkpoint activation independent of its-associated E3 ubiquitin ligase activity. We review the emerging role of BMI1 in DDR regulation and discuss its impact on BMI1-derived tumorigenesis.