vsRNAfinder: a novel method for identifying high-confidence viral small RNAs from small RNA-Seq data.

Virus-encoded small RNAs (vsRNA) have been reported to play an important role in viral infection. Unfortunately, there is still a lack of an effective method for vsRNA identification. Herein, we presented vsRNAfinder, a de novo method for identifying high-confidence vsRNAs from small RNA-Seq (sRNA-Seq) data based on peak calling and Poisson distribution and is publicly available at https://github.com/ZenaCai/vsRNAfinder. vsRNAfinder outperformed two widely used methods namely miRDeep2 and ShortStack in identifying viral miRNAs with a significantly improved sensitivity. It can also be used to identify sRNAs in animals and plants with similar performance to miRDeep2 and ShortStack. vsRNAfinder would greatly facilitate effective identification of vsRNAs from sRNA-Seq data.

VirusCircBase: a database of virus circular RNAs.

Circular RNAs (circRNAs) are covalently closed long noncoding RNAs critical in diverse cellular activities and multiple human diseases. Several cancer-related viral circRNAs have been identified in double-stranded DNA viruses (dsDNA), yet no systematic study about the viral circRNAs has been reported. Herein, we have performed a systematic survey of 11 924 circRNAs from 23 viral species by computational prediction of viral circRNAs from viral-infection-related RNA sequencing data. Besides the dsDNA viruses, our study has also revealed lots of circRNAs in single-stranded RNA viruses and retro-transcribing viruses, such as the Zika virus, the Influenza A virus, the Zaire ebolavirus, and the Human immunodeficiency virus 1. Most viral circRNAs had reverse complementary sequences or repeated sequences at the flanking sequences of the back-splice sites. Most viral circRNAs only expressed in a specific cell line or tissue in a specific species. Functional enrichment analysis indicated that the viral circRNAs from dsDNA viruses were involved in KEGG pathways associated with cancer. All viral circRNAs presented in the current study were stored and organized in VirusCircBase, which is freely available at http://www.computationalbiology.cn/ViruscircBase/home.html and is the first virus circRNA database. VirusCircBase forms the fundamental atlas for the further exploration and investigation of viral circRNAs in the context of public health.

Identification and characterization of circRNAs encoded by MERS-CoV, SARS-CoV-1 and SARS-CoV-2.

The life-threatening coronaviruses MERS-CoV, SARS-CoV-1 and SARS-CoV-2 (SARS-CoV-1/2) have caused and will continue to cause enormous morbidity and mortality to humans. Virus-encoded noncoding RNAs are poorly understood in coronaviruses. Data mining of viral-infection-related RNA-sequencing data has resulted in the identification of 28 754, 720 and 3437 circRNAs encoded by MERS-CoV, SARS-CoV-1 and SARS-CoV-2, respectively. MERS-CoV exhibits much more prominent ability to encode circRNAs in all genomic regions than those of SARS-CoV-1/2. Viral circRNAs typically exhibit low expression levels. Moreover, majority of the viral circRNAs exhibit expressions only in the late stage of viral infection. Analysis of the competitive interactions of viral circRNAs, human miRNAs and mRNAs in MERS-CoV infections reveals that viral circRNAs up-regulated genes related to mRNA splicing and processing in the early stage of viral infection, and regulated genes involved in diverse functions including cancer, metabolism, autophagy, viral infection in the late stage of viral infection. Similar analysis in SARS-CoV-2 infections reveals that its viral circRNAs down-regulated genes associated with metabolic processes of cholesterol, alcohol, fatty acid and up-regulated genes associated with cellular responses to oxidative stress in the late stage of viral infection. A few genes regulated by viral circRNAs from both MERS-CoV and SARS-CoV-2 were enriched in several biological processes such as response to reactive oxygen and centrosome localization. This study provides the first glimpse into viral circRNAs in three deadly coronaviruses and would serve as a valuable resource for further studies of circRNAs in coronaviruses.

Systematic identification and characterization of viral small RNAs from small RNA-Seq data.

Virus-encoded small RNAs (vsRNAs) have been reported to play an important role in viral infections. Unfortunately, there is still a lack of a systematic characterization and resource of vsRNAs. Herein, we identified a total of 19 734 high-confidence vsRNAs including 2746 microRNAs (miRNAs) in 64 viral species from more than 800 samples of public small RNA-Seq data. The number of vsRNAs identified in viruses varied from 1 to 2489 with a median of 170. The length distribution of vsRNAs peaked at 21 and 22 nt. Plant viruses were found to express larger number and higher levels of vsRNAs than those of animal viruses. Besides, the number of vsRNAs identified increased as the viral infection persisted. Interestingly, the vsRNA showed strong expression specificity as little overlap was observed among vsRNAs identified in different strains of a virus, or in different hosts, cells, or tissues infected by the same virus. Little conservation was observed among vsRNAs of different viruses. The viral miRNAs were found to interact with host genes involved in multiple biological processes related to organization, development, action potential, polarity establishment, methylation, immune response, gene regulation, localization, and so on. To facilitate the usage of vsRNAs, a database named vsRNAdb was built for organizing and storing vsRNAs which is available at http://www.computationalbiology.cn/vsRNAdb/#/vsRNAdb/#/. Overall, the study deepens our understanding about the diversity and complexity of vsRNAs and provides a rich resource for further studies of vsRNAs.

Systematic identification and characterization of repeat sequences in African swine fever virus genomes.

African swine fever virus (ASFV) is a large DNA virus that infects domestic pigs with high morbidity and mortality rates. Repeat sequences, which are DNA sequence elements that are repeated more than twice in the genome, play an important role in the ASFV genome. The majority of repeat sequences, however, have not been identified and characterized in a systematic manner. In this study, three types of repeat sequences, including microsatellites, minisatellites and short interspersed nuclear elements (SINEs), were identified in the ASFV genome, and their distribution, structure, function, and evolutionary history were investigated. Most repeat sequences were observed in noncoding regions and at the 5' end of the genome. Noncoding repeat sequences tended to form enhancers, whereas coding repeat sequences had a lower ratio of alpha-helix and beta-sheet and a higher ratio of loop structure and surface amino acids than nonrepeat sequences. In addition, the repeat sequences tended to encode penetrating and antimicrobial peptides. Further analysis of the evolution of repeat sequences revealed that the pan-repeat sequences presented an open state, showing the diversity of repeat sequences. Finally, CpG islands were observed to be negatively correlated with repeat sequence occurrences, suggesting that they may affect the generation of repeat sequences. Overall, this study emphasizes the importance of repeat sequences in ASFVs, and these results can aid in understanding the virus's function and evolution.

Prokaryotic virus host predictor: a Gaussian model for host prediction of prokaryotic viruses in metagenomics.

BACKGROUND: Viruses are ubiquitous biological entities, estimated to be the largest reservoirs of unexplored genetic diversity on Earth. Full functional characterization and annotation of newly discovered viruses requires tools to enable taxonomic assignment, the range of hosts, and biological properties of the virus. Here we focus on prokaryotic viruses, which include phages and archaeal viruses, and for which identifying the viral host is an essential step in characterizing the virus, as the virus relies on the host for survival. Currently, the method for determining the viral host is either to culture the virus, which is low-throughput, time-consuming, and expensive, or to computationally predict the viral hosts, which needs improvements at both accuracy and usability. Here we develop a Gaussian model to predict hosts for prokaryotic viruses with better performances than previous computational methods. RESULTS: We present here Prokaryotic virus Host Predictor (PHP), a software tool using a Gaussian model, to predict hosts for prokaryotic viruses using the differences of k-mer frequencies between viral and host genomic sequences as features. PHP gave a host prediction accuracy of 34% (genus level) on the VirHostMatcher benchmark dataset and a host prediction accuracy of 35% (genus level) on a new dataset containing 671 viruses and 60,105 prokaryotic genomes. The prediction accuracy exceeded that of two alignment-free methods (VirHostMatcher and WIsH, 28-34%, genus level). PHP also outperformed these two alignment-free methods much (24-38% vs 18-20%, genus level) when predicting hosts for prokaryotic viruses which cannot be predicted by the BLAST-based or the CRISPR-spacer-based methods alone. Requiring a minimal score for making predictions (thresholding) and taking the consensus of the top 30 predictions further improved the host prediction accuracy of PHP. CONCLUSIONS: The Prokaryotic virus Host Predictor software tool provides an intuitive and user-friendly API for the Gaussian model described herein. This work will facilitate the rapid identification of hosts for newly identified prokaryotic viruses in metagenomic studies.

FluPhenotype-a one-stop platform for early warnings of the influenza A virus.

MOTIVATION: Newly emerging influenza viruses keep challenging global public health. To evaluate the potential risk of the viruses, it is critical to rapidly determine the phenotypes of the viruses, including the antigenicity, host, virulence and drug resistance. RESULTS: Here, we built FluPhenotype, a one-stop platform to rapidly determinate the phenotypes of the influenza A viruses. The input of FluPhenotype is the complete or partial genomic/protein sequences of the influenza A viruses. The output presents five types of information about the viruses: (i) sequence annotation including the gene and protein names as well as the open reading frames, (ii) potential hosts and human-adaptation-associated amino acid markers, (iii) antigenic and genetic relationships with the vaccine strains of different HA subtypes, (iv) mammalian virulence-related amino acid markers and (v) drug resistance-related amino acid markers. FluPhenotype will be a useful bioinformatic tool for surveillance and early warnings of the newly emerging influenza A viruses. AVAILABILITY AND IMPLEMENTATION: It is publicly available from: http://www.computationalbiology.cn : 18888/IVEW. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Cell membrane proteins with high N-glycosylation, high expression and multiple interaction partners are preferred by mammalian viruses as receptors.

MOTIVATION: Receptor mediated entry is the first step for viral infection. However, the question of how viruses select receptors remains unanswered. RESULTS: Here, by manually curating a high-quality database of 268 pairs of mammalian virus-host receptor interaction, which included 128 unique viral species or sub-species and 119 virus receptors, we found the viral receptors are structurally and functionally diverse, yet they had several common features when compared to other cell membrane proteins: more protein domains, higher level of N-glycosylation, higher ratio of self-interaction and more interaction partners, and higher expression in most tissues of the host. This study could deepen our understanding of virus-receptor interaction. AVAILABILITY AND IMPLEMENTATION: The database of mammalian virus-host receptor interaction is available at http://www.computationalbiology.cn: 5000/viralReceptor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An updated database of virus circular RNAs provides new insights into the biogenesis mechanism of the molecule.

Virus circular RNAs (circRNA) have been reported to be extensively expressed and play important roles in viral infections. Previously we build the first database of virus circRNAs named VirusCircBase which has been widely used in the field. This study significantly improved the database on both the data quantity and database functionality: the number of virus circRNAs, virus species, host organisms was increased from 46440, 23, 9 to 60859, 43, 22, respectively, and 1902 full-length virus circRNAs were newly added; new functions were added such as visualization of the expression level of virus circRNAs and visualization of virus circRNAs in the Genome Browser. Analysis of the expression of virus circRNAs showed that they had low expression levels in most cells or tissues and showed strong expression heterogeneity. Analysis of the splicing of virus circRNAs showed that they used a much higher proportion of non-canonical back-splicing signals compared to those in animals and plants, and mainly used the A5SS (alternative 5' splice site) in alternative-splicing. Most virus circRNAs have no more than two isoforms. Finally, human genes associated with the virus circRNA production were investigated and more than 1000 human genes exhibited moderate correlations with the expression of virus circRNAs. Most of them showed negative correlations including 42 genes encoding RNA-binding proteins. They were significantly enriched in biological processes related to cell cycle and RNA processing. Overall, the study provides a valuable resource for further studies of virus circRNAs and also provides new insights into the biogenesis mechanisms of virus circRNAs.

EVIHVR: A platform for analysis of expression, variation and identification of human virus receptors.

Motivation: Virus receptors are presented on the cell surfaces of a host and are key for viral infection of host cells. However, no unified resource for the study of viral receptors is currently available. Results: To address this problem, we built EVIHVR, a platform for analyzing the expression and variation, and for the identification of human virus receptors. EVIHVR provides three functions: (1) Receptor expression function for browsing and analyzing the expression of human virus receptors in various human tissues/cells; (2) Receptor gene polymorphism function for analyzing the genetic polymorphism of human virus receptors in different human populations and human tissues; and (3) Predict receptor function for identifying potential virus receptors based on differential expression analysis. EVIHVR can become a useful tool for the analysis and identification of human virus receptors. Availability and implementation: EVIHVR is publicly available at http://www.computationalbiology.cn/EVIHVR/#/.

Rapid identification of human-infecting viruses.

Viruses have caused much mortality and morbidity to humans and pose a serious threat to global public health. The virome with the potential of human infection is still far from complete. Novel viruses have been discovered at an unprecedented pace as the rapid development of viral metagenomics. However, there is still a lack of methodology for rapidly identifying novel viruses with the potential of human infection. This study built several machine learning models to discriminate human-infecting viruses from other viruses based on the frequency of k-mers in the viral genomic sequences. The k-nearest neighbor (KNN) model can predict the human-infecting viruses with an accuracy of over 90%. The performance of this KNN model built on the short contigs (≥1 kb) is comparable to those built on the viral genomes. We used a reported human blood virome to further validate this KNN model with an accuracy of over 80% based on very short raw reads (150 bp). Our work demonstrates a conceptual and generic protocol for the discovery of novel human-infecting viruses in viral metagenomics studies.

RAEdb: a database of enhancers identified by high-throughput reporter assays.

High-throughput reporter assays have been recently developed to directly and quantitatively assess enhancer activity for thousands of regulatory elements. However, there is still no database to collect these enhancers. We developed RAEdb, the first database to collect enhancers identified by high-throughput reporter assays. RAEdb includes 538 320 enhancers derived from eight studies, most of which were from six human cell lines. An activity score was assigned to each enhancer based on reporter assays. Based on these enhancers, 7658 epromoters (promoters with enhancer activity) were identified and stored in the database. RAEdb provides two ways of searches: the first is to search studies by species and cell line; the other is to search enhancers or epromoters by position, activity score, sequence and gene. RAEdb also provides a genome browser to query, visualize and compare enhancers. All data in RAEdb is freely available for download.

Homologous recombination shapes the genetic diversity of African swine fever viruses.

The African swine fever virus (ASFV) has severely influenced the swine industry of the world. Currently, there is no effective vaccine or drugs against the ASFV. How to effectively control the virus is challenging. In this study, we have analyzed all the publicly available ASFV genomes and demonstrated that there was a large genetic diversity of ASFV genomes. Interestingly, the genetic diversity was mainly caused by extensive genomic insertions and/or deletions (indels) instead of the point mutations. Further analyses showed that the indels may be attributed much to the homologous recombination, as supported by significant associations between the occurrence of extensive recombination events and the indels in the ASFV genomes. Besides, the homologous recombination also led to changes of gene content of ASFVs. Finally, repeated elements of dozens of nucleotides in length were observed to widely distribute and cluster in the adjacent positions of ASFV genomes, which may facilitate the occurrence of homologous recombination. This work highlighted the importance of homologous recombination in shaping the genetic diversity of the ASFVs, and could help understand the evolution of the virus.

Directional Selection from Host Plants Is a Major Force Driving Host Specificity in Magnaporthe Species.

One major threat to global food security that requires immediate attention, is the increasing incidence of host shift and host expansion in growing number of pathogenic fungi and emergence of new pathogens. The threat is more alarming because, yield quality and quantity improvement efforts are encouraging the cultivation of uniform plants with low genetic diversity that are increasingly susceptible to emerging pathogens. However, the influence of host genome differentiation on pathogen genome differentiation and its contribution to emergence and adaptability is still obscure. Here, we compared genome sequence of 6 isolates of Magnaporthe species obtained from three different host plants. We demonstrated the evolutionary relationship between Magnaporthe species and the influence of host differentiation on pathogens. Phylogenetic analysis showed that evolution of pathogen directly corresponds with host divergence, suggesting that host-pathogen interaction has led to co-evolution. Furthermore, we identified an asymmetric selection pressure on Magnaporthe species. Oryza sativa-infecting isolates showed higher directional selection from host and subsequently tends to lower the genetic diversity in its genome. We concluded that, frequent gene loss or gain, new transposon acquisition and sequence divergence are host adaptability mechanisms for Magnaporthe species, and this coevolution processes is greatly driven by directional selection from host plants.