tRNA-derived small RNA (tsRNA), a novel type of regulatory small noncoding RNA, plays an important role in physiological and pathological processes. However, the understanding of the functional mechanism of tsRNAs in cells and their role in the occurrence and development of diseases is limited. Here, we integrated multiomics data such as transcriptome, epitranscriptome, and targetome data, and developed novel computer tools to establish tsRFun, a comprehensive platform to facilitate tsRNA research (http://rna.sysu.edu.cn/tsRFun/ or http://biomed.nscc-gz.cn/DB/tsRFun/). tsRFun evaluated tsRNA expression profiles and the prognostic value of tsRNAs across 32 types of cancers, identified tsRNA target molecules utilizing high-throughput CLASH/CLEAR or CLIP sequencing data, and constructed the interaction networks among tsRNAs, microRNAs, and mRNAs. In addition to its data presentation capabilities, tsRFun offers multiple real-time online tools for tsRNA identification, target prediction, and functional enrichment analysis. In summary, tsRFun provides a valuable data resource and multiple analysis tools for tsRNA investigation.
The unfolded protein response (UPR) plays important roles in various cells that have a high demand for protein folding, which are involved in the process of cell differentiation and development. Here, we separately knocked down the three sensors of the UPR in myoblasts and found that PERK knockdown led to a marked transformation in myoblasts from a fusiform to a rounded morphology, which suggests that PERK is required for early myoblast differentiation. Interestingly, knocking down PERK induced reprogramming of C2C12 myoblasts into stem-like cells by altering the miRNA networks associated with differentiation and stemness maintenance, and the PERK-ATF4 signaling pathway transactivated muscle differentiation-associated miRNAs in the early stage of myoblast differentiation. Furthermore, we identified Ppp1cc as a direct target gene of miR-128 regulated by the PERK signaling pathway and showed that its repression is critical for a feedback loop that regulates the activity of UPR-associated signaling pathways, leading to cell migration, cell fusion, endoplasmic reticulum expansion, and myotube formation during myoblast differentiation. Subsequently, we found that the RNA-binding protein ARPP21, encoded by the host gene of miR-128-2, antagonized miR-128 activity by competing with it to bind to the 3′ untranslated region (UTR) of Ppp1cc to maintain the balance of the differentiation state. Together, these results reveal the crucial role of PERK signaling in myoblast maintenance and differentiation and identify the mechanism underlying the role of UPR signaling as a major regulator of miRNA networks during early differentiation of myoblasts.
RNA viruses are diverse components of global ecosystems. The metagenomic identification of RNA viruses is currently limited to those with sequence similarity to known viruses, such that highly divergent viruses that comprise the "dark matter" of the virosphere remain challenging to detect. We developed a deep learning algorithm – LucaProt – to search for highly divergent RNA-dependent RNA polymerase (RdRP) sequences in 10,487 global meta-transcriptomes. LucaProt integrates both sequence and structural information to accurately and efficiently detect RdRP sequences. With this approach we identified 180,571 RNA viral species and 180 superclades (viral phyla/classes). This is the broadest diversity of RNA viruses described to date, including many viruses undetectable using BLAST or HMM approaches. The newly identified RNA viruses were present in diverse ecological niches, including the air, hot springs and hydrothermal vents, and both virus diversity and abundance varied substantially among ecological types. We also identified the longest RNA virus genome (nido-like) observed so far, at 47,250 nucleotides, and expanded the diversity of RNA bacteriophage to more than ten phyla/classes. This study marks the beginning of a new era of virus discovery, with the potential to redefine our understanding of the global virosphere and reshape our understanding of virus evolutionary history.
tRNA molecules contain dense, abundant modifications that affect tRNA structure, stability, mRNA decoding and tsRNA formation. tRNA modifications and related enzymes are responsive to environmental cues and are associated with a range of physiological and pathological processes. However, there is a lack of resources that can be used to mine and analyse these dynamically changing tRNA modifications. In this study, we established tModBase (https://www.tmodbase.com/) for deciphering the landscape of tRNA modification profiles from epitranscriptome data. We analysed 103 datasets generated with second- and third-generation sequencing technologies and illustrated the misincorporation and termination signals of tRNA modification sites in ten species. We thus systematically demonstrate the modification profiles across different tissues/cell lines and summarize the characteristics of tRNA-associated human diseases. By integrating transcriptome data from 32 cancers, we developed novel tools for analysing the relationships between tRNA modifications and RNA modification enzymes, the expression of 1442 tRNA-derived small RNAs (tsRNAs), and 654 DNA variations. Our database will provide new insights into the features of tRNA modifications and the biological pathways in which they participate.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has caused a pandemic of coronavirus disease 2019 (COVID-19) and is threatening global health. SARS-CoV-2 spreads by air with a transmission rate of up to 15%, but the probability of its maternal–fetal transmission through the placenta is reported to be low at around 3.28%. However, it is still unclear that which tissues and developmental periods hold higher risks and what the underlying molecular mechanisms are. We conducted an integrated analysis of large-scale transcriptome and single-cell sequencing data to investigate the key factors that affect SARS-CoV-2 maternal–fetal transmission as well as the characteristics and effects of them. Our results showed that the abundance of cytomegalovirus (CMV) and Zika virus (ZIKV) infection-associated factors in the placenta were higher than their primarily infected tissues, while the expression levels of SARS-CoV-2 binding receptor angiotensin-converting enzyme II (ACE2) were similar between lung and placenta. By contrast, an important SARS-CoV-2 infection-associated factor, type II transmembrane serine protease (TMPRSS2), was poorly expressed in placenta. Further scRNA-Seq analysis revealed that ACE2 and TMPRSS2 were co-expressed in very few trophoblastic cells. Interestingly, during the embryonic development stages, the abundance of ACE2 and TMPRSS2 was much higher in multiple embryonic tissues than in the placenta. Based on our present analysis, the intestine in 20th week of embryonic development was at a high risk of SARS-CoV-2 infection. Additionally, we found that during the fetal development, ACE2 and TMPRSS2 were enriched in pathogen infection-associated pathways and may involve in the biological processes related to T-cell activation. In conclusion, our present study suggests that though the placenta provides a good physical barrier against SARS-CoV-2 infection for healthy fetal development, multiple embryonic tissues are under risks of the virus infection, which may be adversely affected once infected prenatally. Therefore, it is necessary to enhance maternal care to prevent the potential impact and harm of SARS-CoV-2 maternal–fetal transmission.
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