Ribocentre-switch: a database of riboswitches.

Riboswitches are regulatory elements found in the untranslated regions (UTRs) of certain mRNA molecules. They typically comprise two distinct domains: an aptamer domain that can bind to specific small molecules, and an expression platform that controls gene expression. Riboswitches work by undergoing a conformational change upon binding to their specific ligand, thus activating or repressing the genes downstream. This mechanism allows gene expression regulation in response to metabolites or small molecules. To systematically summarise riboswitch structures and their related ligand binding functions, we present Ribocentre-switch, a comprehensive database of riboswitches, including the information as follows: sequences, structures, functions, ligand binding pockets and biological applications. It encompasses 56 riboswitches and 26 orphan riboswitches from over 430 references, with a total of 89 591 sequences. It serves as a good resource for comparing different riboswitches and facilitating the identification of potential riboswitch candidates. Therefore, it may facilitate the understanding of RNA structural conformational changes in response to ligand signaling. The database is publicly available at https://riboswitch.ribocentre.org.

Decoding human fetal liver haematopoiesis.

Definitive haematopoiesis in the fetal liver supports self-renewal and differentiation of haematopoietic stem cells and multipotent progenitors (HSC/MPPs) but remains poorly defined in humans. Here, using single-cell transcriptome profiling of approximately 140,000 liver and 74,000 skin, kidney and yolk sac cells, we identify the repertoire of human blood and immune cells during development. We infer differentiation trajectories from HSC/MPPs and evaluate the influence of the tissue microenvironment on blood and immune cell development. We reveal physiological erythropoiesis in fetal skin and the presence of mast cells, natural killer and innate lymphoid cell precursors in the yolk sac. We demonstrate a shift in the haemopoietic composition of fetal liver during gestation away from being predominantly erythroid, accompanied by a parallel change in differentiation potential of HSC/MPPs, which we functionally validate. Our integrated map of fetal liver haematopoiesis provides a blueprint for the study of paediatric blood and immune disorders, and a reference for harnessing the therapeutic potential of HSC/MPPs.

Ribocentre: a database of ribozymes.

Ribozymes are excellent systems in which to study 'sequence - structure - function' relationships in RNA molecules. Understanding these relationships may greatly help structural modeling and design of functional RNA structures and some functional structural modules could be repurposed in molecular design. At present, there is no comprehensive database summarising all the natural ribozyme families. We have therefore created Ribocentre, a database that collects together sequence, structure and mechanistic data on 21 ribozyme families. This includes available information on timelines, sequence families, secondary and tertiary structures, catalytic mechanisms, applications of the ribozymes together with key publications. The database is publicly available at https://www.ribocentre.org.

Clinical genomics expands the link between erroneous cell division, primary microcephaly and intellectual disability.

Primary microcephaly is a rare neurogenic and genetically heterogeneous disorder characterized by significant brain size reduction that results in numerous neurodevelopmental disorders (NDD) problems, including mild to severe intellectual disability (ID), global developmental delay (GDD), seizures and other congenital malformations. This disorder can arise from a mutation in genes involved in various biological pathways, including those within the brain. We characterized a recessive neurological disorder observed in nine young adults from five independent consanguineous Pakistani families. The disorder is characterized by microcephaly, ID, developmental delay (DD), early-onset epilepsy, recurrent infection, hearing loss, growth retardation, skeletal and limb defects. Through exome sequencing, we identified novel homozygous variants in five genes that were previously associated with brain diseases, namely CENPJ (NM_018451.5: c.1856A > G; p.Lys619Arg), STIL (NM_001048166.1: c.1235C > A; p.(Pro412Gln), CDK5RAP2 (NM_018249.6 c.3935 T > G; p.Leu1312Trp), RBBP8 (NM_203291.2 c.1843C > T; p.Gln615*) and CEP135 (NM_025009.5 c.1469A > G; p.Glu490Gly). These variants were validated by Sanger sequencing across all family members, and in silico structural analysis. Protein 3D homology modeling of wild-type and mutated proteins revealed substantial changes in the structure, suggesting a potential impact on function. Importantly, all identified genes play crucial roles in maintaining genomic integrity during cell division, with CENPJ, STIL, CDK5RAP2, and CEP135 being involved in centrosomal function. Collectively, our findings underscore the link between erroneous cell division, particularly centrosomal function, primary microcephaly and ID.

Evaluation of the stereochemical quality of predicted RNA 3D models in the RNA-Puzzles submissions.

In silico prediction is a well-established approach to derive a general shape of an RNA molecule based on its sequence or secondary structure. This paper reports an analysis of the stereochemical quality of the RNA three-dimensional models predicted using dedicated computer programs. The stereochemistry of 1052 RNA 3D structures, including 1030 models predicted by fully automated and human-guided approaches within 22 RNA-Puzzles challenges and reference structures, is analyzed. The evaluation is based on standards of RNA stereochemistry that the Protein Data Bank requires from deposited experimental structures. Deviations from standard bond lengths and angles, planarity, or chirality are quantified. A reduction in the number of such deviations should help in the improvement of RNA 3D structure modeling approaches.

Exome sequencing identifies homozygous variants in MBOAT7 associated with neurodevelopmental disorder.

Intellectual disability (ID) is a large group of neurodevelopmental disorders characterized by a congenital limitation in intellectual functioning (reasoning, learning, and problem solving), adaptive behavior (conceptual, social, and practical skills), originated at birth and manifested before the age of 18. By whole exome sequencing of five consanguineous Pakistani families presenting hallmark features of ID, global developmental delay, aggressive and self-injurious behaviors, microcephaly, febrile seizures and facial dysmorphic features, we identified three novel homozygous missense variants (NM_024298.5: c.588G > T; p.Trp196Cys, c.736 T > C; p.Tyr246His and c.524A > C; p. Asp175Ala) and one rare homozygous in-frame deletion variant (c.758_778del;p.Glu253_Ala259del) in membrane-bound O-acyltransferase family member 7 (MBOAT7) gene previously associated with autosomal recessive neurodevelopmental disorder. The segregation of the variants was validated by Sanger sequencing in all family members. In silico homology modeling of wild-type and mutated proteins revealed substantial changes in the structure of both proteins, indicating a possible effect on function. The identification and validation of new pathogenic MBOAT7 variants in five cases of autosomal recessive ID further highlight the importance of this genes in proper brain function and development.

Nr4a1 marks a distinctive ILC2 activation subset in the mouse inflammatory lung.

BACKGROUND: Group 2 innate lymphoid cells (ILC2s) are critical sources of type 2 cytokines and represent one of the major tissue-resident lymphoid cells in the mouse lung. However, the molecular mechanisms underlying ILC2 activation under challenges are not fully understood. RESULTS: Here, using single-cell transcriptomics, genetic reporters, and gene knockouts, we identify four ILC2 subsets, including two non-activation subsets and two activation subsets, in the mouse acute inflammatory lung. Of note, a distinct activation subset, marked by the transcription factor Nr4a1, paradoxically expresses both tissue-resident memory T cell (Trm), and effector/central memory T cell (Tem/Tcm) signature genes, as well as higher scores of proliferation, activation, and wound healing, all driven by its particular regulons. Furthermore, we demonstrate that the Nr4a1+ILC2s are restrained from activating by the programmed cell death protein-1 (PD-1), which negatively modulates their activation-related regulons. PD-1 deficiency places the non-activation ILC2s in a state that is prone to activation, resulting in Nr4a1+ILC2 differentiation through different activation trajectories. Loss of PD-1 also leads to the expansion of Nr4a1+ILC2s by the increase of their proliferation ability. CONCLUSIONS: The findings show that activated ILC2s are a heterogenous population encompassing distinct subsets that have different propensities, and therefore provide an opportunity to explore PD-1's role in modulating the activity of ILC2s for disease prevention and therapy.

Assessment of three-dimensional RNA structure prediction in CASP15.

The prediction of RNA three-dimensional structures remains an unsolved problem. Here, we report assessments of RNA structure predictions in CASP15, the first CASP exercise that involved RNA structure modeling. Forty-two predictor groups submitted models for at least one of twelve RNA-containing targets. These models were evaluated by the RNA-Puzzles organizers and, separately, by a CASP-recruited team using metrics (GDT, lDDT) and approaches (Z-score rankings) initially developed for assessment of proteins and generalized here for RNA assessment. The two assessments independently ranked the same predictor groups as first (AIchemy_RNA2), second (Chen), and third (RNAPolis and GeneSilico, tied); predictions from deep learning approaches were significantly worse than these top ranked groups, which did not use deep learning. Further analyses based on direct comparison of predicted models to cryogenic electron microscopy (cryo-EM) maps and x-ray diffraction data support these rankings. With the exception of two RNA-protein complexes, models submitted by CASP15 groups correctly predicted the global fold of the RNA targets. Comparisons of CASP15 submissions to designed RNA nanostructures as well as molecular replacement trials highlight the potential utility of current RNA modeling approaches for RNA nanotechnology and structural biology, respectively. Nevertheless, challenges remain in modeling fine details such as noncanonical pairs, in ranking among submitted models, and in prediction of multiple structures resolved by cryo-EM or crystallography.

Putative cell type discovery from single-cell gene expression data.

We present the Single-Cell Clustering Assessment Framework, a method for the automated identification of putative cell types from single-cell RNA sequencing (scRNA-seq) data. By iteratively applying a machine learning approach to a given set of cells, we simultaneously identify distinct cell groups and a weighted list of feature genes for each group. The differentially expressed feature genes discriminate the given cell group from other cells. Each such group of cells corresponds to a putative cell type or state, characterized by the feature genes as markers. Benchmarking using expert-annotated scRNA-seq datasets shows that our method automatically identifies the 'ground truth' cell assignments with high accuracy.

Sterile 20-like kinase 3 promotes tick-borne encephalitis virus assembly by interacting with NS2A and prM and enhancing the NS2A-NS4A association.

Tick-borne encephalitis virus (TBEV) is the causative agent of a potentially fatal neurological infection in humans. Investigating virus-host interaction is important for understanding the pathogenesis of TBEV and developing effective antiviral drugs against this virus. Here, we report that mammalian ste20-like kinase 3 (MST3) is involved in the regulation of TBEV infection. The knockdown or knockout of MST3, but not other mammalian ste20-like kinase family members, inhibited TBEV replication. The knockdown of MST3 also significantly reduced TBEV replication in mouse primary astrocytes. Life cycle analysis indicated that MST3 remarkably impaired virion assembly efficiency and specific infectivity by respectively 59% and 95% in MST3-knockout cells. We further found that MST3 interacts with the viral proteins NS2A and prM; and MST3 enhances the interaction of NS2A-NS4A. Thus, MST3-NS2A complex plays a major role in recruiting prM-E heterodimers and NS4A and mediates the virion assembly. Additionally, we found that MST3 was biotinylated and combined with other proteins (e.g., ATG5, Sec24A, and SNX4) that are associated with the cellular membrane required for TBEV infection. Overall, our study revealed a novel function for MST3 in TBEV infection and identified as a novel host factor supporting TBEV assembly.

Regulatory circular RNAs in viral diseases: applications in diagnosis and therapy.

Circular RNA (circRNA) forms closed loops via back-splicing in precursor mRNA, resisting exonuclease degradation. In higher eukaryotes, protein-coding genes create circRNAs through exon back-splicing. Unlike mRNAs, circRNAs possess unique production and structural traits, bestowing distinct cellular functions and biomedical potential. In this review, we explore the pivotal roles of viral circRNAs and associated RNA in various biological processes. Analysing the interactions between viral circRNA and host cellular machinery yields fresh insights into antiviral immunity, catalysing the development of potential therapeutics. Furthermore, circRNAs serve as enduring biomarkers in viral diseases due to their stable translation within specific tissues. Additionally, a deeper understanding of translational circRNA could expedite the establishment of circRNA-based expression platforms, meeting the rising demand for broad-spectrum viral vaccines. We also highlight the applications of circular RNA in biomarker studies as well as circRNA-based therapeutics. Prospectively, we expect a technological revolution in combating viral infections using circRNA.

A test metric for assessing single-cell RNA-seq batch correction.

Single-cell transcriptomics is a versatile tool for exploring heterogeneous cell populations, but as with all genomics experiments, batch effects can hamper data integration and interpretation. The success of batch-effect correction is often evaluated by visual inspection of low-dimensional embeddings, which are inherently imprecise. Here we present a user-friendly, robust and sensitive k-nearest-neighbor batch-effect test (kBET; https://github.com/theislab/kBET ) for quantification of batch effects. We used kBET to assess commonly used batch-regression and normalization approaches, and to quantify the extent to which they remove batch effects while preserving biological variability. We also demonstrate the application of kBET to data from peripheral blood mononuclear cells (PBMCs) from healthy donors to distinguish cell-type-specific inter-individual variability from changes in relative proportions of cell populations. This has important implications for future data-integration efforts, central to projects such as the Human Cell Atlas.

RNA-Puzzles Round IV: 3D structure predictions of four ribozymes and two aptamers.

RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA 3D structure prediction. With agreement from crystallographers, the RNA structures are predicted by various groups before the publication of the crystal structures. We now report the prediction of 3D structures for six RNA sequences: four nucleolytic ribozymes and two riboswitches. Systematic protocols for comparing models and crystal structures are described and analyzed. In these six puzzles, we discuss (i) the comparison between the automated web servers and human experts; (ii) the prediction of coaxial stacking; (iii) the prediction of structural details and ligand binding; (iv) the development of novel prediction methods; and (v) the potential improvements to be made. We show that correct prediction of coaxial stacking and tertiary contacts is essential for the prediction of RNA architecture, while ligand binding modes can only be predicted with low resolution and simultaneous prediction of RNA structure with accurate ligand binding still remains out of reach. All the predicted models are available for the future development of force field parameters and the improvement of comparison and assessment tools.

RNA-Puzzles toolkit: a computational resource of RNA 3D structure benchmark datasets, structure manipulation, and evaluation tools.

Significant improvements have been made in the efficiency and accuracy of RNA 3D structure prediction methods during the succeeding challenges of RNA-Puzzles, a community-wide effort on the assessment of blind prediction of RNA tertiary structures. The RNA-Puzzles contest has shown, among others, that the development and validation of computational methods for RNA fold prediction strongly depend on the benchmark datasets and the structure comparison algorithms. Yet, there has been no systematic benchmark set or decoy structures available for the 3D structure prediction of RNA, hindering the standardization of comparative tests in the modeling of RNA structure. Furthermore, there has not been a unified set of tools that allows deep and complete RNA structure analysis, and at the same time, that is easy to use. Here, we present RNA-Puzzles toolkit, a computational resource including (i) decoy sets generated by different RNA 3D structure prediction methods (raw, for-evaluation and standardized datasets), (ii) 3D structure normalization, analysis, manipulation, visualization tools (RNA_format, RNA_normalizer, rna-tools) and (iii) 3D structure comparison metric tools (RNAQUA, MCQ4Structures). This resource provides a full list of computational tools as well as a standard RNA 3D structure prediction assessment protocol for the community.

Computational Pipeline for Reference-Free Comparative Analysis of RNA 3D Structures Applied to SARS-CoV-2 UTR Models.

RNA is a unique biomolecule that is involved in a variety of fundamental biological functions, all of which depend solely on its structure and dynamics. Since the experimental determination of crystal RNA structures is laborious, computational 3D structure prediction methods are experiencing an ongoing and thriving development. Such methods can lead to many models; thus, it is necessary to build comparisons and extract common structural motifs for further medical or biological studies. Here, we introduce a computational pipeline dedicated to reference-free high-throughput comparative analysis of 3D RNA structures. We show its application in the RNA-Puzzles challenge, in which five participating groups attempted to predict the three-dimensional structures of 5'- and 3'-untranslated regions (UTRs) of the SARS-CoV-2 genome. We report the results of this puzzle and discuss the structural motifs obtained from the analysis. All simulated models and tools incorporated into the pipeline are open to scientific and academic use.

BBKNN: fast batch alignment of single cell transcriptomes.

MOTIVATION: Increasing numbers of large scale single cell RNA-Seq projects are leading to a data explosion, which can only be fully exploited through data integration. A number of methods have been developed to combine diverse datasets by removing technical batch effects, but most are computationally intensive. To overcome the challenge of enormous datasets, we have developed BBKNN, an extremely fast graph-based data integration algorithm. We illustrate the power of BBKNN on large scale mouse atlasing data, and favourably benchmark its run time against a number of competing methods. AVAILABILITY AND IMPLEMENTATION: BBKNN is available at https://github.com/Teichlab/bbknn, along with documentation and multiple example notebooks, and can be installed from pip. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Secondary structure of the SARS-CoV-2 5'-UTR.

The SARS-CoV-2, a positive-sense single-stranded RNA Coronavirus, is a global threat to human health. Thus, understanding its life cycle mechanistically would be important to facilitate the design of antiviral drugs. A key aspect of viral progression is the synthesis of viral proteins by the ribosome of the human host. In Coronaviruses, this process is regulated by the viral 5' and 3' untranslated regions (UTRs), but the precise regulatory mechanism has not yet been well understood. In particular, the 5'-UTR of the viral genome is most likely involved in translation initiation of viral proteins. Here, we performed inline probing and RNase V1 probing to establish a model of the secondary structure of SARS-CoV-2 5'-UTR. We found that the 5'-UTR contains stable structures including a very stable four-way junction close to the AUG start codon. Sequence alignment analysis of SARS-CoV-2 variants 5'-UTRs revealed a highly conserved structure with few co-variations that confirmed our secondary structure model based on probing experiments.

Integrated Analysis of Long Non-Coding RNA and mRNA Expression Profile in Myelodysplastic Syndromes.

BACKGROUND: Myelodysplastic syndromes (MDS) are a heterogeneous group of myeloid malignancies. The incidence of MDS is gradually increasing, but the pathogenesis is still not very clear. Studies have shown that long non-coding RNAs (lncRNAs) play a critical role in both oncogenic and tumor-suppressive pathways. However, the function of lncRNAs in MDS is still unknown. The purpose of this study was to investigate the expression profiles and biological function of the aberrantly expressed lncRNAs and mRNAs in MDS. METHODS: We downloaded two data sets (GSE4619 and GSE19429) from the Gene Expression Omnibus database and obtained differentially expressed (DE) lncRNAs and DE-mRNAs between MDS cases and healthy controls. Then we performed systematic bioinformatics analysis to know the biological function of DE-lncRNAs and DE-mRNAs in MDS. RESULTS: We identified 40 DE-lncRNAs and 643 DE-mRNAs between MDS cases and healthy controls. Gene Ontology (GO) and pathway analysis revealed that DE-lncRNAs and DE-mRNAs were mainly involved in necroptosis, apoptosis, immunodeficiency, p53 and FoxO signaling pathways. LncRNA-mRNA co-expression and lncRNA functional similarity network showed that twelve down-regulated lncRNAs co-regulated the same target gene and they were similar in function. CONCLUSIONS: The comprehensive analysis of lncRNA and mRNA is helpful in understanding the pathogenesis of MDS, and the synergistically down-regulated lncRNAs may contribute to the development of new diagnostic and therapeutic strategies.

First-Principles Study of Nitrogen Adsorption and Dissociation on PuH2 (111) Surface.

Plutonium mononitride is one of the main fuels for Generation IV reactors and can be prepared from nitrogenation of plutonium hydride. We investigated the adsorption and dissociation of nitrogen on PuH2 (111) surface to elaborate the initial stage of nitrogenation. The adsorption energies varied greatly with respect to the adsorption sites and orientations of the adsorbed molecule. The nitrogen exhibited preferential adsorption above the ccp site, where the molecular nitrogen was nearly parallel to the PuH2 surface and pointed to the nearest Pu atom. The orbital hybridization and the electrostatic attraction between the Pu and N weakened the N-N bond in the adsorbed molecule. The mechanism of the dissociation process was investigated within transition state theory, and the analysis of the activation barrier indicated that dissociation of nitrogen is not the rate-determining step of nitrogenation. These findings can contribute to a better understanding of the nuclear fuel cycle.