RNA-binding proteins (RBPs) play key roles in post-transcriptional regulation. Accurate identification of RBP binding sites in multiple cell lines and tissue types from diverse species is a fundamental endeavor towards understanding the regulatory mechanisms of RBPs under both physiological and pathological conditions. Our POSTAR annotation processes make use of publicly available large-scale CLIP-seq datasets and external functional genomic annotations to generate a comprehensive map of RBP binding sites and their association with other regulatory events as well as functional variants. Here, we present POSTAR3, an updated database with improvements in data collection, annotation infrastructure, and analysis that support the annotation of post-transcriptional regulation in multiple species including: we made a comprehensive update on the CLIP-seq and Ribo-seq datasets which cover more biological conditions, technologies, and species; we added RNA secondary structure profiling for RBP binding sites; we provided miRNA-mediated degradation events validated by degradome-seq; we included RBP binding sites at circRNA junction regions; we expanded the annotation of RBP binding sites, particularly using updated genomic variants and mutations associated with diseases. POSTAR3 is freely available at http://postar.ncrnalab.org.
Rationale: Long extracellular RNAs (exRNAs) in plasma can be profiled by new sequencing technologies, even with low abundance. However, cancer-related exRNAs and their variations remain understudied. Methods: We investigated different variations (i.e. differential expression, alternative splicing, alternative polyadenylation, and differential editing) in diverse long exRNA species (e.g. long noncoding RNAs and circular RNAs) using 79 plasma exosomal RNA-seq (exoRNA-seq) datasets of multiple cancer types. We then integrated 53 exoRNA-seq datasets and 65 self-profiled cell-free RNA-seq (cfRNA-seq) datasets to identify recurrent variations in liver cancer patients. We further combined TCGA tissue RNA-seq datasets and validated biomarker candidates by RT-qPCR in an individual cohort of more than 100 plasma samples. Finally, we used machine learning models to identify a signature of 3 noncoding RNAs for the detection of liver cancer. Results: We found that different types of RNA variations identified from exoRNA-seq data were enriched in pathways related to tumorigenesis and metastasis, immune, and metabolism, suggesting that cancer signals can be detected from long exRNAs. Subsequently, we identified more than 100 recurrent variations in plasma from liver cancer patients by integrating exoRNA-seq and cfRNA-seq datasets. From these datasets, 5 significantly up-regulated long exRNAs were confirmed by TCGA data and validated by RT-qPCR in an independent cohort. When using machine learning models to combine two of these validated circular and structured RNAs ( SNORD3B-1, circ-0080695 ) with a miRNA ( miR-122 ) as a panel to classify liver cancer patients from healthy donors, the average AUROC of the cross-validation was 89.4%. The selected 3-RNA panel successfully detected 79.2% AFP-negative samples and 77.1% early-stage liver cancer samples in the testing and validation sets. Conclusions: Our study revealed that different types of RNA variations related to cancer can be detected in plasma and identified a 3-RNA detection panel for liver cancer, especially for AFP-negative and early-stage patients.
Background Dominant deafness-onychodystrophy (DDOD) syndrome is a rare disorder mainly characterized by severe deafness, onychodystrophy and brachydactyly. We previously identified c.1516C > T (p.Arg506X) in ATP6V1B2 as cause of DDOD syndrome, accounting for all cases of this genetic disorder. Clinical follow-up of DDOD syndrome patients with cochlear implantation revealed the language rehabilitation was unsatisfactory although the implanted cochlea worked well, which indicates there might be learning and memory problems in DDOD syndrome patients. However, the underlying mechanisms were unknown. Methods atp6v1b2 knockdown zebrafish and Atp6v1b2 c.1516C > T knockin mice were constructed to explore the phenotypes and related mechanism. In mutant mice, auditory brainstem response test and cochlear morphology analysis were performed to evaluate the auditory function. Behavioral tests were used to investigate various behavioral and cognitive domains. Resting-state functional magnetic resonance imaging was used to evaluate functional connectivity in the mouse brain. Immunofluorescence, Western blot, and co-immunoprecipitation were performed to examine the expression and interactions between the subunits of V-ATPases. Findings atp6v1b2 knockdown zebrafish showed developmental defects in multiple organs and systems. However, Atp6v1b2 c.1516C > T knockin mice displayed obvious cognitive defects but normal hearing and cochlear morphology. Impaired hippocampal CA1 region and weaker interaction between the V1E and B2 subunits in Atp6v1b2 Arg506X//Arg506X mice were observed. Interpretation Our study extends the phenotypic range of DDOD syndrome. The impaired hippocampal CA1 region may be the pathological basis of the behavioral defects in mutant mice. The molecular mechanism underlying V-ATPases dysfunction involves a weak interaction between subunits, although the assembly of V-ATPases can still take place.
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