SARS-CoV-2 RNA stabilizes host mRNAs to elicit immunopathogenesis.

SARS-CoV-2 RNA interacts with host factors to suppress interferon responses and simultaneously induces cytokine release to drive the development of severe coronavirus disease 2019 (COVID-19). However, how SARS-CoV-2 hijacks host RNAs to elicit such imbalanced immune responses remains elusive. Here, we analyzed SARS-CoV-2 RNA in situ structures and interactions in infected cells and patient lung samples using RIC-seq. We discovered that SARS-CoV-2 RNA forms 2,095 potential duplexes with the 3' UTRs of 205 host mRNAs to increase their stability by recruiting RNA-binding protein YBX3 in A549 cells. Disrupting the SARS-CoV-2-to-host RNA duplex or knocking down YBX3 decreased host mRNA stability and reduced viral replication. Among SARS-CoV-2-stabilized host targets, NFKBIZ was crucial for promoting cytokine production and reducing interferon responses, probably contributing to cytokine storm induction. Our study uncovers the crucial roles of RNA-RNA interactions in the immunopathogenesis of RNA viruses such as SARS-CoV-2 and provides valuable host targets for drug development.

Capture RIC-seq reveals positional rules of PTBP1-associated RNA loops in splicing regulation.

RNA-binding proteins (RBPs) bind at different positions of the pre-mRNA molecules to promote or reduce the usage of a particular exon. Seeking to understand the working principle of these positional effects, we develop a capture RIC-seq (CRIC-seq) method to enrich specific RBP-associated in situ proximal RNA-RNA fragments for deep sequencing. We determine hnRNPA1-, SRSF1-, and PTBP1-associated proximal RNA-RNA contacts and regulatory mechanisms in HeLa cells. Unexpectedly, the 3D RNA map analysis shows that PTBP1-associated loops in individual introns preferentially promote cassette exon splicing by accelerating asymmetric intron removal, whereas the loops spanning across cassette exon primarily repress splicing. These "positional rules" can faithfully predict PTBP1-regulated splicing outcomes. We further demonstrate that cancer-related splicing quantitative trait loci can disrupt RNA loops by reducing PTBP1 binding on pre-mRNAs to cause aberrant splicing in tumors. Our study presents a powerful method for exploring the functions of RBP-associated RNA-RNA proximal contacts in gene regulation and disease.

Complementary Alu sequences mediate enhancer-promoter selectivity.

Enhancers determine spatiotemporal gene expression programs by engaging with long-range promoters1-4. However, it remains unknown how enhancers find their cognate promoters. We recently developed a RNA in situ conformation sequencing technology to identify enhancer-promoter connectivity using pairwise interacting enhancer RNAs and promoter-derived noncoding RNAs5,6. Here we apply this technology to generate high-confidence enhancer-promoter RNA interaction maps in six additional cell lines. Using these maps, we discover that 37.9% of the enhancer-promoter RNA interaction sites are overlapped with Alu sequences. These pairwise interacting Alu and non-Alu RNA sequences tend to be complementary and potentially form duplexes. Knockout of Alu elements compromises enhancer-promoter looping, whereas Alu insertion or CRISPR-dCasRx-mediated Alu tethering to unregulated promoter RNAs can create new loops to homologous enhancers. Mapping 535,404 noncoding risk variants back to the enhancer-promoter RNA interaction maps enabled us to construct variant-to-function maps for interpreting their molecular functions, including 15,318 deletions or insertions in 11,677 Alu elements that affect 6,497 protein-coding genes. We further demonstrate that polymorphic Alu insertion at the PTK2 enhancer can promote tumorigenesis. Our study uncovers a principle for determining enhancer-promoter pairing specificity and provides a framework to link noncoding risk variants to their molecular functions.

RIC-seq for global in situ profiling of RNA-RNA spatial interactions.

Highly structured RNA molecules usually interact with each other, and associate with various RNA-binding proteins, to regulate critical biological processes. However, RNA structures and interactions in intact cells remain largely unknown. Here, by coupling proximity ligation mediated by RNA-binding proteins with deep sequencing, we report an RNA in situ conformation sequencing (RIC-seq) technology for the global profiling of intra- and intermolecular RNA-RNA interactions. This technique not only recapitulates known RNA secondary structures and tertiary interactions, but also facilitates the generation of three-dimensional (3D) interaction maps of RNA in human cells. Using these maps, we identify noncoding RNA targets globally, and discern RNA topological domains and trans-interacting hubs. We reveal that the functional connectivity of enhancers and promoters can be assigned using their pairwise-interacting RNAs. Furthermore, we show that CCAT1-5L-a super-enhancer hub RNA-interacts with the RNA-binding protein hnRNPK, as well as RNA derived from the MYC promoter and enhancer, to boost MYC transcription by modulating chromatin looping. Our study demonstrates the power and applicability of RIC-seq in discovering the 3D structures, interactions and regulatory roles of RNA.

RNA in situ conformation sequencing reveals novel long-range RNA structures with impact on splicing.

Over recent years, long-range RNA structure has emerged as a factor that is fundamental to alternative splicing regulation. An increasing number of human disorders are now being associated with splicing defects; hence it is essential to develop methods that assess long-range RNA structure experimentally. RNA in situ conformation sequencing (RIC-seq) is a method that recapitulates RNA structure within physiological RNA-protein complexes. In this work, we juxtapose pairs of conserved complementary regions (PCCRs) that were predicted in silico with the results of RIC-seq experiments conducted in seven human cell lines. We show statistically that RIC-seq support of PCCRs correlates with their properties, such as equilibrium free energy, presence of compensatory substitutions, and occurrence of A-to-I RNA editing sites and forked eCLIP peaks. Exons enclosed in PCCRs that are supported by RIC-seq tend to have weaker splice sites and lower inclusion rates, which is indicative of post-transcriptional splicing regulation mediated by RNA structure. Based on these findings, we prioritize PCCRs according to their RIC-seq support and show, using antisense nucleotides and minigene mutagenesis, that PCCRs in two disease-associated human genes, PHF20L1 and CASK, and also PCCRs in their murine orthologs, impact alternative splicing. In sum, we demonstrate how RIC-seq experiments can be used to discover functional long-range RNA structures, and particularly those that regulate alternative splicing.

NOVA1 prevents overactivation of the unfolded protein response and facilitates chromatin access during human white adipogenesis.

The molecular mechanism underlying white adipogenesis in humans has not been fully elucidated beyond the transcriptional level. Here, we found that the RNA-binding protein NOVA1 is required for the adipogenic differentiation of human mesenchymal stem cells. By thoroughly exploring the interactions between NOVA1 and its binding RNA, we proved that NOVA1 deficiency resulted in the aberrant splicing of DNAJC10 with an in-frame premature stop codon, reduced DNAJC10 expression at the protein level and hyperactivation of the unfolded protein response (UPR). Moreover, NOVA1 knockdown abrogated the down-regulation of NCOR2 during adipogenesis and up-regulated the 47b+ splicing isoform, which led to decreased chromatin accessibility at the loci of lipid metabolism genes. Interestingly, these effects on human adipogenesis could not be recapitulated in mice. Further analysis of multispecies genomes and transcriptomes indicated that NOVA1-targeted RNA splicing is evolutionarily regulated. Our findings provide evidence for human-specific roles of NOVA1 in coordinating splicing and cell organelle functions during white adipogenesis.

Research Progress of H2S Donors Conjugate Drugs Based on ADTOH.

H2S is an endogenous gas signaling molecule and its multiple biological effects have been demonstrated. The abnormal level of H2S is closely related to the occurrence and development of many diseases, and H2S donors has important pharmacological implications. In recent years, H2S donors represented by ADTOH (5-(4-hydroxyphenyl)-3H-1,2-dithiole-3-thione) are often used to synthesize new 'conjugate' compounds that can release H2S and parent drugs. These hybrids retain the pharmacological activity of the parent drugs and H2S and have a synergistic effect. ADTOH and parent drug hybrids have become one of the important strategies for the development of H2S donor conjugate drugs. This review summarizes molecular hybrids between ADTOH and clinical drugs to provide new ideas for the study of H2S donor drug design.

An accurate clone-based haplotyping method by overlapping pool sequencing.

Chromosome-long haplotyping of human genomes is important to identify genetic variants with differing gene expression, in human evolution studies, clinical diagnosis, and other biological and medical fields. Although several methods have realized haplotyping based on sequencing technologies or population statistics, accuracy and cost are factors that prohibit their wide use. Borrowing ideas from group testing theories, we proposed a clone-based haplotyping method by overlapping pool sequencing. The clones from a single individual were pooled combinatorially and then sequenced. According to the distinct pooling pattern for each clone in the overlapping pool sequencing, alleles for the recovered variants could be assigned to their original clones precisely. Subsequently, the clone sequences could be reconstructed by linking these alleles accordingly and assembling them into haplotypes with high accuracy. To verify the utility of our method, we constructed 130 110 clones in silico for the individual NA12878 and simulated the pooling and sequencing process. Ultimately, 99.9% of variants on chromosome 1 that were covered by clones from both parental chromosomes were recovered correctly, and 112 haplotype contigs were assembled with an N50 length of 3.4 Mb and no switch errors. A comparison with current clone-based haplotyping methods indicated our method was more accurate.

Efficient identification of SNPs in pooled DNA samples using a dual mononucleotide addition-based sequencing method.

Identifying single nucleotide polymorphism (SNPs) from pooled samples is critical for many studies and applications. SNPs determined by next-generation sequencing results may suffer from errors in both base calling and read mapping. Taking advantage of dual mononucleotide addition-based pyrosequencing, we present Epds, a method to efficiently identify SNPs from pooled DNA samples. On the basis of only five patterns of non-synchronistic extensions between the wild and mutant sequences using dual mononucleotide addition-based pyrosequencing, we employed an enumerative algorithm to infer the mutant locus and estimate the proportion of mutant sequence. According to the profiles resulting from three runs with distinct dual mononucleotide additions, Epds could recover the mutant bases. Results showed that our method had a false-positive rate of less than 3%. Series of simulations revealed that Epds outperformed the current method (PSM) in many situations. Finally, experiments based on profiles produced by real sequencing proved that our method could be successfully applied for the identification of mutants from pooled samples. The software for implementing this method and the experimental data are available at http://bioinfo.seu.edu.cn/Epds .

Predicting and Interpreting the Structure of Type IV Pilus of Electricigens by Molecular Dynamics Simulations.

Nanowires that transfer electrons to extracellular acceptors are important in organic matter degradation and nutrient cycling in the environment. Geobacter pili of the group of Type IV pilus are regarded as nanowire-like biological structures. However, determination of the structure of pili remains challenging due to the insolubility of monomers, presence of surface appendages, heterogeneity of the assembly, and low-resolution of electron microscopy techniques. Our previous study provided a method to predict structures for Type IV pili. In this work, we improved on our previous method using molecular dynamics simulations to optimize structures of Neisseria gonorrhoeae (GC), Neisseria meningitidis and Geobacter uraniireducens pilus. Comparison between the predicted structures for GC and Neisseria meningitidis pilus and their native structures revealed that proposed method could predict Type IV pilus successfully. According to the predicted structures, the structural basis for conductivity in G.uraniireducens pili was attributed to the three N-terminal aromatic amino acids. The aromatics were interspersed within the regions of charged amino acids, which may influence the configuration of the aromatic contacts and the rate of electron transfer. These results will supplement experimental research into the mechanism of long-rang electron transport along pili of electricigens.

Accurate estimation of haplotype frequency from pooled sequencing data and cost-effective identification of rare haplotype carriers by overlapping pool sequencing.

MOTIVATION: A variety of hypotheses have been proposed for finding the missing heritability of complex diseases in genome-wide association studies. Studies have focused on the value of haplotype to improve the power of detecting associations with disease. To facilitate haplotype-based association analysis, it is necessary to accurately estimate haplotype frequencies of pooled samples. RESULTS: Taking advantage of databases that contain prior haplotypes, we present Ehapp based on the algorithm for solving the system of linear equations to estimate the frequencies of haplotypes from pooled sequencing data. Effects of various factors in sequencing on the performance are evaluated using simulated data. Our method could estimate the frequencies of haplotypes with only about 3% average relative difference for pooled sequencing of the mixture of 10 haplotypes with total coverage of 50×. When unknown haplotypes exist, our method maintains excellent performance for haplotypes with actual frequencies >0.05. Comparisons with present method on simulated data in conjunction with publicly available Illumina sequencing data indicate that our method is state of the art for many sequencing study designs. We also demonstrate the feasibility of applying overlapping pool sequencing to identify rare haplotype carriers cost-effectively. AVAILABILITY AND IMPLEMENTATION: Ehapp (in Perl) for the Linux platforms is available online (http://bioinfo.seu.edu.cn/Ehapp/). CONTACT: xsun@seu.edu.cn SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DectICO: an alignment-free supervised metagenomic classification method based on feature extraction and dynamic selection.

BACKGROUND: Continual progress in next-generation sequencing allows for generating increasingly large metagenomes which are over time or space. Comparing and classifying the metagenomes with different microbial communities is critical. Alignment-free supervised classification is important for discriminating between the multifarious components of metagenomic samples, because it can be accomplished independently of known microbial genomes. RESULTS: We propose an alignment-free supervised metagenomic classification method called DectICO. The intrinsic correlation of oligonucleotides provides the feature set, which is selected dynamically using a kernel partial least squares algorithm, and the feature matrices extracted with this set are sequentially employed to train classifiers by support vector machine (SVM). We evaluated the classification performance of DectICO on three actual metagenomic sequencing datasets, two containing deep sequencing metagenomes and one of low coverage. Validation results show that DectICO is powerful, performs well based on long oligonucleotides (i.e., 6-mer to 8-mer), and is more stable and generalized than a sequence-composition-based method. The classifiers trained by our method are more accurate than non-dynamic feature selection methods and a recently published recursive-SVM-based classification approach. CONCLUSIONS: The alignment-free supervised classification method DectICO can accurately classify metagenomic samples without dependence on known microbial genomes. Selecting the ICO dynamically offers better stability and generality compared with sequence-composition-based classification algorithms. Our proposed method provides new insights in metagenomic sample classification.

Quantitative group testing-based overlapping pool sequencing to identify rare variant carriers.

BACKGROUND: Genome-wide association studies have revealed that rare variants are responsible for a large portion of the heritability of some complex human diseases. This highlights the increasing importance of detecting and screening for rare variants. Although the massively parallel sequencing technologies have greatly reduced the cost of DNA sequencing, the identification of rare variant carriers by large-scale re-sequencing remains prohibitively expensive because of the huge challenge of constructing libraries for thousands of samples. Recently, several studies have reported that techniques from group testing theory and compressed sensing could help identify rare variant carriers in large-scale samples with few pooled sequencing experiments and a dramatically reduced cost. RESULTS: Based on quantitative group testing, we propose an efficient overlapping pool sequencing strategy that allows the efficient recovery of variant carriers in numerous individuals with much lower costs than conventional methods. We used random k-set pool designs to mix samples, and optimized the design parameters according to an indicative probability. Based on a mathematical model of sequencing depth distribution, an optimal threshold was selected to declare a pool positive or negative. Then, using the quantitative information contained in the sequencing results, we designed a heuristic Bayesian probability decoding algorithm to identify variant carriers. Finally, we conducted in silico experiments to find variant carriers among 200 simulated Escherichia coli strains. With the simulated pools and publicly available Illumina sequencing data, our method correctly identified the variant carriers for 91.5-97.9% variants with the variant frequency ranging from 0.5 to 1.5%. CONCLUSIONS: Using the number of reads, variant carriers could be identified precisely even though samples were randomly selected and pooled. Our method performed better than the published DNA Sudoku design and compressed sequencing, especially in reducing the required data throughput and cost.

Identifying rare variants with optimal depth of coverage and cost-effective overlapping pool sequencing.

Genome-wide association studies have identified hundreds of genetic variants associated with complex diseases although most variants identified so far explain only a small proportion of heritability, suggesting that rare variants are responsible for missing heritability. Identification of rare variants through large-scale resequencing becomes increasing important but still prohibitively expensive despite the rapid decline in the sequencing costs. Nevertheless, group testing based overlapping pool sequencing in which pooled rather than individual samples are sequenced will greatly reduces the efforts of sample preparation as well as the costs to screen for rare variants. Here, we proposed an overlapping pool sequencing to screen rare variants with optimal sequencing depth and a corresponding cost model. We formulated a model to compute the optimal depth for sufficient observations of variants in pooled sequencing. Utilizing shifted transversal design algorithm, appropriate parameters for overlapping pool sequencing could be selected to minimize cost and guarantee accuracy. Due to the mixing constraint and high depth for pooled sequencing, results showed that it was more cost-effective to divide a large population into smaller blocks which were tested using optimized strategies independently. Finally, we conducted an experiment to screen variant carriers with frequency equaled 1%. With simulated pools and publicly available human exome sequencing data, the experiment achieved 99.93% accuracy. Utilizing overlapping pool sequencing, the cost for screening variant carriers with frequency equaled 1% in 200 diploid individuals dropped to at least 66% at which target sequencing region was set to 30 Mb.

Intrinsic correlation of oligonucleotides: a novel genomic signature for metagenome analysis.

Because a vast majority (99%) of microbes in a given community is likely to be non-cultivable, metagenomics has gradually entered the mainstream of microbial research methods. With the development of high-throughput sequencing techniques, an increasing number of sequencing read data sets of metagenomes from various microbial communities have become available. For these data sets, metagenomic analysis based on mapping reads to microbial genomes has been hampered by the limited number of microbial genomes that are available. Further, this type of analysis is computationally intensive. Thus alignment-free methods, which characterize the sequencing reads with a genomic signature instead of with genomic alignments, can be applied. However, the main requirement of these alignment-free methods is a stable genomic signature that performs reliably. Here, we propose a novel genomic signature of microbial genomes called the intrinsic correlation of oligonucleotides (ICOs). This signature represents the quantification of an intrinsic relationship between any two oligonucleotides. We analyzed microbial genomes at different taxonomic levels using ICO profiles and confirmed the wide availability of useful ICOs. We used intra-genomic and inter-genomic distances and relational grades to evaluate the performance of ICOs as a genomic signature. The results of these experiments showed that ICOs can characterize microbial genomes well, and ICOs were better at distinguishing species than tetranucleotide composition, not only in terms of whole genomes but also in terms of sequence fragments. In addition, we evaluated the performance of a hybrid feature that combined ICOs and tetranucleotide composition. The experimental results showed that the hybrid feature performed better than ICOs or tetranucleotide composition alone. ICOs can characterize microbial genomes successfully and are capable of distinguishing organisms at different taxonomic levels. ICOs perform better than tetranucleotide composition in characterizing microbial genomes. The hybrid feature that used a combination of the two kinds of sequence features had advantages over a single sequence feature.

Long-range RNA structures in the human transcriptome beyond evolutionarily conserved regions.

RNA structure has been increasingly recognized as a critical player in the biogenesis and turnover of many transcripts classes. In eukaryotes, the prediction of RNA structure by thermodynamic modeling meets fundamental limitations due to the large sizes and complex, discontinuous organization of eukaryotic genes. Signatures of functional RNA structures can be found by detecting compensatory substitutions in homologous sequences, but a comparative approach is applicable only within conserved sequence blocks. Here, we developed a computational pipeline called PHRIC, which is not limited to conserved regions and relies on RNA contacts derived from RNA in situ conformation sequencing (RIC-seq) experiments. It extracts pairs of short RNA fragments surrounded by nested clusters of RNA contacts and predicts long, nearly perfect complementary base pairings formed between these fragments. In application to a panel of RIC-seq experiments in seven human cell lines, PHRIC predicted ~12,000 stable long-range RNA structures with equilibrium free energy below -15 kcal/mol, the vast majority of which fall outside of regions annotated as conserved among vertebrates. These structures, nevertheless, show some level of sequence conservation and remarkable compensatory substitution patterns in other clades. Furthermore, we found that introns have a higher propensity to form stable long-range RNA structures between each other, and moreover that RNA structures tend to concentrate within the same intron rather than connect adjacent introns. These results for the first time extend the application of proximity ligation assays to RNA structure prediction beyond conserved regions.

Research advances on interferon (IFN) response during BVDV infection.

Bovine viral diarrhea virus (BVDV) is an important pathogen responsible for significant economic loss to cattle. BVDV infection in pregnant cattle leads to fetal infection and reproductive losses, including early embryonic death, abortion, and stillbirth. Importantly, vaccinated heifers could not provide fetal protection against BVDV. It can be divided into two genotypes (BVDV-1 and BVDV-2) and two biotypes (cytopathic (CP) and non-cytopathic (NCP)). Infection with NCP-BVDV during gestation, the fetus becomes persistently infected (PI) and sheds BVDV throughout life, serving as the main source of infection for other cattle. BVDV potentially induces immunosuppression and aggravates bovine respiratory disease (BRD). Accordingly, BVDV infection results in a heterogeneous range of clinical signs and immune responses. Interferon (IFN) plays a vital role by mediating the innate immune response against antiviral infection through the Janus Kinase (JAK)-signal transducer and activator of transcription (STAT) pathway. BVDV infection can reportedly exert variable degrees of influence on IFN response. Interestingly, reports have suggested that IFN can exert a significant inhibitory effect on various viruses. Human IFN-α was used to restrain BVDV in vitro. In this article, we summarized the latest researches on IFN response during BVDV infection.

Recent advances in RNA structurome.

RNA structures are essential to support RNA functions and regulation in various biological processes. Recently, a range of novel technologies have been developed to decode genome-wide RNA structures and novel modes of functionality across a wide range of species. In this review, we summarize key strategies for probing the RNA structurome and discuss the pros and cons of representative technologies. In particular, these new technologies have been applied to dissect the structural landscape of the SARS-CoV-2 RNA genome. We also summarize the functionalities of RNA structures discovered in different regulatory layers-including RNA processing, transport, localization, and mRNA translation-across viruses, bacteria, animals, and plants. We review many versatile RNA structural elements in the context of different physiological and pathological processes (e.g., cell differentiation, stress response, and viral replication). Finally, we discuss future prospects for RNA structural studies to map the RNA structurome at higher resolution and at the single-molecule and single-cell level, and to decipher novel modes of RNA structures and functions for innovative applications.

APAF1-Binding Long Noncoding RNA Promotes Tumor Growth and Multidrug Resistance in Gastric Cancer by Blocking Apoptosome Assembly.

Chemotherapeutics remain the first choice for advanced gastric cancers (GCs). However, drug resistance and unavoidable severe toxicity lead to chemotherapy failure and poor prognosis. Long noncoding RNAs (lncRNAs) play critical roles in tumor progression in many cancers, including GC. Here, through RNA screening, an apoptotic protease-activating factor 1 (APAF1)-binding lncRNA (ABL) that is significantly elevated in cancerous GC tissues and an independent prognostic factor for GC patients is identified. Moreover, ABL overexpression inhibits GC cell apoptosis and promotes GC cell survival and multidrug resistance in GC xenograft and organoid models. Mechanistically, ABL directly binds to the RNA-binding protein IGF2BP1 via its KH1/2 domain, and then IGF2BP1 further recognizes the METTL3-mediated m6A modification on ABL, which maintains ABL stability. In addition, ABL can bind to the WD1/WD2 domain of APAF1, which competitively prevent cytochrome c from interacting with APAF1, blocking apoptosome assembly and caspase-9/3 activation; these events lead to resistance to cell death in GC cells. Intriguingly, targeting ABL using encapsulated liposomal siRNA can significantly enhance the sensitivity of GC cells to chemotherapy. Collectively, the results suggest that ABL can be a potential prognostic biomarker and therapeutic target in GC.