Subcellular RNA distribution and its change during human embryonic stem cell differentiation.

The spatial localization of RNA within cells is closely related to its function and also involved in cell fate determination. However, the atlas of RNA distribution within cells and dynamic changes during the developmental process are largely unknown. In this study, five subcellular components, including cytoplasmic extract, membrane extract, soluble nuclear extract, chromatin-bound nuclear extract, and cytoskeletal extract, were isolated and the rules of subcellular RNA distribution in human embryonic stem cells (hESCs) and its change during hESC differentiation are summarized for the first time. The overall distribution patterns of coding and non-coding RNAs are revealed. Interestingly, some developmental genes are found to be transcribed but confined to the chromatin in undifferentiated hESC. Unexpectedly, alternative splicing and polyadenylation endow spatial heterogeneity among different isoforms of the same gene. Finally, the dynamic pattern of RNA distribution during hESC differentiation is characterized, which provides new clues for a comprehensive understanding hESC pluripotency and differentiation.

LncReader: identification of dual functional long noncoding RNAs using a multi-head self-attention mechanism.

Long noncoding ribonucleic acids (RNAs; LncRNAs) endowed with both protein-coding and noncoding functions are referred to as 'dual functional lncRNAs'. Recently, dual functional lncRNAs have been intensively studied and identified as involved in various fundamental cellular processes. However, apart from time-consuming and cell-type-specific experiments, there is virtually no in silico method for predicting the identity of dual functional lncRNAs. Here, we developed a deep-learning model with a multi-head self-attention mechanism, LncReader, to identify dual functional lncRNAs. Our data demonstrated that LncReader showed multiple advantages compared to various classical machine learning methods using benchmark datasets from our previously reported cncRNAdb project. Moreover, to obtain independent in-house datasets for robust testing, mass spectrometry proteomics combined with RNA-seq and Ribo-seq were applied in four leukaemia cell lines, which further confirmed that LncReader achieved the best performance compared to other tools. Therefore, LncReader provides an accurate and practical tool that enables fast dual functional lncRNA identification.

Single-cell architecture and functional requirement of alternative splicing during hematopoietic stem cell formation.

Single-cell transcriptional profiling has rapidly advanced our understanding of the embryonic hematopoiesis; however, whether and what role RNA alternative splicing (AS) plays remains an enigma. This is important for understanding the mechanisms underlying splicing-associated hematopoietic diseases and for the derivation of therapeutic stem cells. Here, we used single-cell full-length transcriptome data to construct an isoform-based transcriptional atlas of the murine endothelial-to-hematopoietic stem cell (HSC) transition, which enables the identification of hemogenic signature isoforms and stage-specific AS events. We showed that the inclusion of these hemogenic-specific AS events was essential for hemogenic function in vitro. Expression data and knockout mouse studies highlighted the critical role of Srsf2: Early Srsf2 deficiency from endothelial cells affected the splicing pattern of several master hematopoietic regulators and significantly impaired HSC generation. These results redefine our understanding of the dynamic HSC developmental transcriptome and demonstrate that elaborately controlled RNA splicing governs cell fate in HSC formation.

RNAInter v4.0: RNA interactome repository with redefined confidence scoring system and improved accessibility.

Establishing an RNA-associated interaction repository facilitates the system-level understanding of RNA functions. However, as these interactions are distributed throughout various resources, an essential prerequisite for effectively applying these data requires that they are deposited together and annotated with confidence scores. Hence, we have updated the RNA-associated interaction database RNAInter (RNA Interactome Database) to version 4.0, which is freely accessible at http://www.rnainter.org or http://www.rna-society.org/rnainter/. Compared with previous versions, the current RNAInter not only contains an enlarged data set, but also an updated confidence scoring system. The merits of this 4.0 version can be summarized in the following points: (i) a redefined confidence scoring system as achieved by integrating the trust of experimental evidence, the trust of the scientific community and the types of tissues/cells, (ii) a redesigned fully functional database that enables for a more rapid retrieval and browsing of interactions via an upgraded user-friendly interface and (iii) an update of entries to >47 million by manually mining the literature and integrating six database resources with evidence from experimental and computational sources. Overall, RNAInter will provide a more comprehensive and readily accessible RNA interactome platform to investigate the regulatory landscape of cellular RNAs.

RNALocate v2.0: an updated resource for RNA subcellular localization with increased coverage and annotation.

Resolving the spatial distribution of the transcriptome at a subcellular level can increase our understanding of biology and diseases. To facilitate studies of biological functions and molecular mechanisms in the transcriptome, we updated RNALocate, a resource for RNA subcellular localization analysis that is freely accessible at http://www.rnalocate.org/ or http://www.rna-society.org/rnalocate/. Compared to RNALocate v1.0, the new features in version 2.0 include (i) expansion of the data sources and the coverage of species; (ii) incorporation and integration of RNA-seq datasets containing information about subcellular localization; (iii) addition and reorganization of RNA information (RNA subcellular localization conditions and descriptive figures for method, RNA homology information, RNA interaction and ncRNA disease information) and (iv) three additional prediction tools: DM3Loc, iLoc-lncRNA and iLoc-mRNA. Overall, RNALocate v2.0 provides a comprehensive RNA subcellular localization resource for researchers to deconvolute the highly complex architecture of the cell.

CellCall: integrating paired ligand-receptor and transcription factor activities for cell-cell communication.

With the dramatic development of single-cell RNA sequencing (scRNA-seq) technologies, the systematic decoding of cell-cell communication has received great research interest. To date, several in-silico methods have been developed, but most of them lack the ability to predict the communication pathways connecting the insides and outsides of cells. Here, we developed CellCall, a toolkit to infer inter- and intracellular communication pathways by integrating paired ligand-receptor and transcription factor (TF) activity. Moreover, CellCall uses an embedded pathway activity analysis method to identify the significantly activated pathways involved in intercellular crosstalk between certain cell types. Additionally, CellCall offers a rich suite of visualization options (Circos plot, Sankey plot, bubble plot, ridge plot, etc.) to present the analysis results. Case studies on scRNA-seq datasets of human testicular cells and the tumor immune microenvironment demonstrated the reliable and unique functionality of CellCall in intercellular communication analysis and internal TF activity exploration, which were further validated experimentally. Comparative analysis of CellCall and other tools indicated that CellCall was more accurate and offered more functions. In summary, CellCall provides a sophisticated and practical tool allowing researchers to decipher intercellular communication and related internal regulatory signals based on scRNA-seq data. CellCall is freely available at https://github.com/ShellyCoder/cellcall.

Hematopoietic Stem Cell Heterogeneity Is Linked to the Initiation and Therapeutic Response of Myeloproliferative Neoplasms.

The implications of stem cell heterogeneity for disease pathogenesis and therapy are poorly defined. JAK2V617F+ myeloproliferative neoplasms (MPNs), harboring the same mutation in hematopoietic stem cells (HSCs), display diverse phenotypes, including polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). These chronic malignant disorders are ideal models to analyze the pathological consequences of stem cell heterogeneity. Single-cell gene expression profiling with parallel mutation detection demonstrated that the megakaryocyte (Mk)-primed HSC subpopulation expanded significantly with enhanced potential in untreated individuals with JAK2V617F+ ET, driven primarily by the JAK2 mutation and elevated interferon signaling. During treatment, mutant HSCs were targeted preferentially in the Mk-primed HSC subpopulation. Interestingly, homozygous mutant HSCs were forced to re-enter quiescence, whereas their heterozygous counterparts underwent apoptosis. This study provides important evidence for the association of stem cell heterogeneity with the pathogenesis and therapeutic response of a malignant disease.

hnRNPLL controls pluripotency exit of embryonic stem cells by modulating alternative splicing of Tbx3 and Bptf.

The regulatory circuitry underlying embryonic stem (ES) cell self-renewal is well defined, but how this circuitry is disintegrated to enable lineage specification is unclear. RNA-binding proteins (RBPs) have essential roles in RNA-mediated gene regulation, and preliminary data suggest that they might regulate ES cell fate. By combining bioinformatic analyses with functional screening, we identified seven RBPs played important roles for the exit from pluripotency of ES cells. We characterized hnRNPLL, which mainly functions as a global regulator of alternative splicing in ES cells. Specifically, hnRNPLL promotes multiple ES cell-preferred exon skipping events during the onset of ES cell differentiation. hnRNPLL depletion thus leads to sustained expression of ES cell-preferred isoforms, resulting in a differentiation deficiency that causes developmental defects and growth impairment in hnRNPLL-KO mice. In particular, hnRNPLL-mediated alternative splicing of two transcription factors, Bptf and Tbx3, is important for pluripotency exit. These data uncover the critical role of RBPs in pluripotency exit and suggest the application of targeting RBPs in controlling ES cell fate.

RNAInter in 2020: RNA interactome repository with increased coverage and annotation.

Research on RNA-associated interactions has exploded in recent years, and increasing numbers of studies are not limited to RNA-RNA and RNA-protein interactions but also include RNA-DNA/compound interactions. To facilitate the development of the interactome and promote understanding of the biological functions and molecular mechanisms of RNA, we updated RAID v2.0 to RNAInter (RNA Interactome Database), a repository for RNA-associated interactions that is freely accessible at http://www.rna-society.org/rnainter/ or http://www.rna-society.org/raid/. Compared to RAID v2.0, new features in RNAInter include (i) 8-fold more interaction data and 94 additional species; (ii) more definite annotations organized, including RNA editing/localization/modification/structure and homology interaction; (iii) advanced functions including fuzzy/batch search, interaction network and RNA dynamic expression and (iv) four embedded RNA interactome tools: RIscoper, IntaRNA, PRIdictor and DeepBind. Consequently, RNAInter contains >41 million RNA-associated interaction entries, involving more than 450 thousand unique molecules, including RNA, protein, DNA and compound. Overall, RNAInter provides a comprehensive RNA interactome resource for researchers and paves the way to investigate the regulatory landscape of cellular RNAs.

Dissecting dynamic expression of autophagy-related genes during human fetal digestive tract development via single-cell RNA sequencing.

Macroautophagy/autophagy has been demonstrated to play an essential role in embryonic development. However, the role of autophagy during human fetal digestive tract development has not been investigated. Here, by using over 5,000 human embryonic digestive tract cells ranging from 6 weeks to 25 weeks, we explored the dynamic expression of autophagy-related genes at single-cell resolution, and found that the transcriptional activity of autophagy-related genes boosted remarkably and specifically in the early (between 6 and 9 weeks) stages. Interestingly, the small intestine cells at 9 weeks showed the most significant enrichment of autophagy-related genes than any other stages. In summary, our results for the first time revealed that autophagy may play an essential role in the development of the digestive tract, especially for the small intestine, in early human embryos. Abbreviations: GI: gastrointestinal; S-Intes: small intestine; t-SNE: t-distributed stochastic neighbor embedding.

Transcriptomic insights into temporal expression pattern of autophagy genes during monocytic and granulocytic differentiation.

Macroautophagy/autophagy plays an essential role in hematopoietic stem cell (HSC) differentiation. However, the role of autophagy during monocytic and granulocytic differentiation remains poorly understood. Hence, we first represented global transcriptomic analysis for temporal expression of autophagy genes during monocytic and granulocytic differentiation by combining RNA-Seq data with monocytic and granulocytic induction in CD34+ hematopoietic stem and progenitor cells. According to a self-organizing map (SOM) algorithm, our results show temporal expression patterns of autophagy genes during monocytic and granulocytic differentiation. More importantly, 22 autophagy genes present significantly divergent roles during monocytic and granulocytic differentiation, indicating these autophagy genes could be important factors involved in the differentiation of myeloid progenitors into monocytes and granulocytes.

MNDR v2.0: an updated resource of ncRNA-disease associations in mammals.

Accumulating evidence suggests that diverse non-coding RNAs (ncRNAs) are involved in the progression of a wide variety of diseases. In recent years, abundant ncRNA-disease associations have been found and predicted according to experiments and prediction algorithms. Diverse ncRNA-disease associations are scattered over many resources and mammals, whereas a global view of diverse ncRNA-disease associations is not available for any mammals. Hence, we have updated the MNDR v2.0 database (www.rna-society.org/mndr/) by integrating experimental and prediction associations from manual literature curation and other resources under one common framework. The new developments in MNDR v2.0 include (i) an over 220-fold increase in ncRNA-disease associations enhancement compared with the previous version (including lncRNA, miRNA, piRNA, snoRNA and more than 1400 diseases); (ii) integrating experimental and prediction evidence from 14 resources and prediction algorithms for each ncRNA-disease association; (iii) mapping disease names to the Disease Ontology and Medical Subject Headings (MeSH); (iv) providing a confidence score for each ncRNA-disease association and (v) an increase of species coverage to six mammals. Finally, MNDR v2.0 intends to provide the scientific community with a resource for efficient browsing and extraction of the associations between diverse ncRNAs and diseases, including >260 000 ncRNA-disease associations.

KSRP specifies monocytic and granulocytic differentiation through regulating miR-129 biogenesis and RUNX1 expression.

RNA-binding proteins (RBPs) integrate the processing of RNAs into post-transcriptional gene regulation, but the direct contribution of them to myeloid cell specification is poorly understood. Here, we report the first global RBP transcriptomic analysis of myeloid differentiation by combining RNA-seq analysis with myeloid induction in CD34+ hematopoietic progenitor cells. The downregulated expression of the KH-Type Splicing Regulatory Protein (KSRP) during monocytopoiesis and up-regulated expression during granulopoiesis suggests that KSRP has divergent roles during monocytic and granulocytic differentiation. A further comparative analysis of miRNA transcripts reveals that KSRP promotes the biogenesis of miR-129, and the expression patterns and roles of miR-129 in myeloid differentiation are equivalent to those of KSRP. Finally, miR-129 directly blocks the expression of Runt Related Transcription Factor 1 (RUNX1), which evokes transcriptional modulation by RUNX1. Based on our findings, KSRP, miR-129, and RUNX1 participate in a regulatory axis to control the outcome of myeloid differentiation.

RAID v2.0: an updated resource of RNA-associated interactions across organisms.

With the development of biotechnologies and computational prediction algorithms, the number of experimental and computational prediction RNA-associated interactions has grown rapidly in recent years. However, diverse RNA-associated interactions are scattered over a wide variety of resources and organisms, whereas a fully comprehensive view of diverse RNA-associated interactions is still not available for any species. Hence, we have updated the RAID database to version 2.0 (RAID v2.0, www.rna-society.org/raid/) by integrating experimental and computational prediction interactions from manually reading literature and other database resources under one common framework. The new developments in RAID v2.0 include (i) over 850-fold RNA-associated interactions, an enhancement compared to the previous version; (ii) numerous resources integrated with experimental or computational prediction evidence for each RNA-associated interaction; (iii) a reliability assessment for each RNA-associated interaction based on an integrative confidence score; and (iv) an increase of species coverage to 60. Consequently, RAID v2.0 recruits more than 5.27 million RNA-associated interactions, including more than 4 million RNA-RNA interactions and more than 1.2 million RNA-protein interactions, referring to nearly 130 000 RNA/protein symbols across 60 species.

RNALocate: a resource for RNA subcellular localizations.

Increasing evidence has revealed that RNA subcellular localization is a very important feature for deeply understanding RNA's biological functions after being transported into intra- or extra-cellular regions. RNALocate is a web-accessible database that aims to provide a high-quality RNA subcellular localization resource and facilitate future researches on RNA function or structure. The current version of RNALocate documents more than 37 700 manually curated RNA subcellular localization entries with experimental evidence, involving more than 21 800 RNAs with 42 subcellular localizations in 65 species, mainly including Homo sapiens, Mus musculus and Saccharomyces cerevisiae etc. Besides, RNA homology, sequence and interaction data have also been integrated into RNALocate. Users can access these data through online search, browse, blast and visualization tools. In conclusion, RNALocate will be of help in elucidating the entirety of RNA subcellular localization, and developing new prediction methods. The database is available at http://www.rna-society.org/rnalocate/.

ncRDeathDB: A comprehensive bioinformatics resource for deciphering network organization of the ncRNA-mediated cell death system.

Programmed cell death (PCD) is a critical biological process involved in many important processes, and defects in PCD have been linked with numerous human diseases. In recent years, the protein architecture in different PCD subroutines has been explored, but our understanding of the global network organization of the noncoding RNA (ncRNA)-mediated cell death system is limited and ambiguous. Hence, we developed the comprehensive bioinformatics resource (ncRDeathDB, www.rna-society.org/ncrdeathdb ) to archive ncRNA-associated cell death interactions. The current version of ncRDeathDB documents a total of more than 4600 ncRNA-mediated PCD entries in 12 species. ncRDeathDB provides a user-friendly interface to query, browse and manipulate these ncRNA-associated cell death interactions. Furthermore, this resource will help to visualize and navigate current knowledge of the noncoding RNA component of cell death and autophagy, to uncover the generic organizing principles of ncRNA-associated cell death systems, and to generate valuable biological hypotheses.

SynBioLGDB: a resource for experimentally validated logic gates in synthetic biology.

Synthetic biologists have developed DNA/molecular modules that perform genetic logic operations in living cells to track key moments in a cell's life or change the fate of a cell. Increasing evidence has also revealed that diverse genetic logic gates capable of generating a Boolean function play critically important roles in synthetic biology. Basic genetic logic gates have been designed to combine biological science with digital logic. SynBioLGDB (http://bioinformatics.ac.cn/synbiolgdb/) aims to provide the synthetic biology community with a useful resource for efficient browsing and visualization of genetic logic gates. The current version of SynBioLGDB documents more than 189 genetic logic gates with experimental evidence involving 80 AND gates and 16 NOR gates, etc. in three species (Human, Escherichia coli and Bacillus clausii). SynBioLGDB provides a user-friendly interface through which conveniently to query and browse detailed information about these genetic logic gates. SynBioLGDB will enable more comprehensive understanding of the connection of genetic logic gates to execute complex cellular functions in living cells.

RAID: a comprehensive resource for human RNA-associated (RNA-RNA/RNA-protein) interaction.

Transcriptomic analyses have revealed an unexpected complexity in the eukaryote transcriptome, which includes not only protein-coding transcripts but also an expanding catalog of noncoding RNAs (ncRNAs). Diverse coding and noncoding RNAs (ncRNAs) perform functions through interaction with each other in various cellular processes. In this project, we have developed RAID (http://www.rna-society.org/raid), an RNA-associated (RNA-RNA/RNA-protein) interaction database. RAID intends to provide the scientific community with all-in-one resources for efficient browsing and extraction of the RNA-associated interactions in human. This version of RAID contains more than 6100 RNA-associated interactions obtained by manually reviewing more than 2100 published papers, including 4493 RNA-RNA interactions and 1619 RNA-protein interactions. Each entry contains detailed information on an RNA-associated interaction, including RAID ID, RNA/protein symbol, RNA/protein categories, validated method, expressing tissue, literature references (Pubmed IDs), and detailed functional description. Users can query, browse, analyze, and manipulate RNA-associated (RNA-RNA/RNA-protein) interaction. RAID provides a comprehensive resource of human RNA-associated (RNA-RNA/RNA-protein) interaction network. Furthermore, this resource will help in uncovering the generic organizing principles of cellular function network.