scholarly journals Hantaviridae: Current Classification and Future Perspectives

Viruses ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 788 ◽  
Author(s):  
Lies Laenen ◽  
Valentijn Vergote ◽  
Charles H. Calisher ◽  
Boris Klempa ◽  
Jonas Klingström ◽  
...  
Keyword(s):  
Hierarchical Clustering ◽  
Rna Virus ◽  
New Order ◽  
Genomic Sequencing ◽  
Future Perspectives ◽  
Sequencing Data ◽  
Diversity Partitioning ◽  
Classification Schemes ◽  
Current Classification ◽  
Negative Sense

In recent years, negative-sense RNA virus classification and taxon nomenclature have undergone considerable transformation. In 2016, the new order Bunyavirales was established, elevating the previous genus Hantavirus to family rank, thereby creating Hantaviridae. Here we summarize affirmed taxonomic modifications of this family from 2016 to 2019. Changes involve the admission of >30 new hantavirid species and the establishment of subfamilies and novel genera based on DivErsity pArtitioning by hieRarchical Clustering (DEmARC) analysis of genomic sequencing data. We outline an objective framework that can be used in future classification schemes when more hantavirids sequences will be available. Finally, we summarize current taxonomic proposals and problems in hantavirid taxonomy that will have to be addressed shortly.

scholarly journals Commonalities across computational workflows for uncovering explanatory variants in undiagnosed cases

2021 ◽  
Author(s):  
Shilpa Nadimpalli Kobren ◽  
◽  
Dustin Baldridge ◽  
Matt Velinder ◽  
Joel B. Krier ◽  
...  
Keyword(s):  
Online Survey ◽  
Variant Calling ◽  
Theoretical Method ◽  
The United States ◽  
Genomic Sequencing ◽  
Biomedical Data ◽  
Sequencing Data ◽  
Multimodal Data ◽  
Undiagnosed Diseases ◽  
Undiagnosed Diseases Network

Abstract Purpose Genomic sequencing has become an increasingly powerful and relevant tool to be leveraged for the discovery of genetic aberrations underlying rare, Mendelian conditions. Although the computational tools incorporated into diagnostic workflows for this task are continually evolving and improving, we nevertheless sought to investigate commonalities across sequencing processing workflows to reveal consensus and standard practice tools and highlight exploratory analyses where technical and theoretical method improvements would be most impactful. Methods We collected details regarding the computational approaches used by a genetic testing laboratory and 11 clinical research sites in the United States participating in the Undiagnosed Diseases Network via meetings with bioinformaticians, online survey forms, and analyses of internal protocols. Results We found that tools for processing genomic sequencing data can be grouped into four distinct categories. Whereas well-established practices exist for initial variant calling and quality control steps, there is substantial divergence across sites in later stages for variant prioritization and multimodal data integration, demonstrating a diversity of approaches for solving the most mysterious undiagnosed cases. Conclusion The largest differences across diagnostic workflows suggest that advances in structural variant detection, noncoding variant interpretation, and integration of additional biomedical data may be especially promising for solving chronically undiagnosed cases.

scholarly journals Virome composition in marine fish revealed by meta-transcriptomics

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Jemma L Geoghegan ◽  
Francesca Di Giallonardo ◽  
Michelle Wille ◽  
Ayda Susana Ortiz-Baez ◽  
Vincenzo A Costa ◽  
...  
Keyword(s):  
Marine Fish ◽  
Rna Virus ◽  
Community Diversity ◽  
Fish Diet ◽  
Biological Factors ◽  
Evolutionary Context ◽  
Ideal Model System ◽  
Abundance And Diversity ◽  
Fish Hosts ◽  
Negative Sense

Abstract Revealing the determinants of virome composition is central to placing disease emergence in a broader evolutionary context. Fish are the most species-rich group of vertebrates and so provide an ideal model system to study the factors that shape virome compositions and their evolution. We characterized the viromes of nineteen wild-caught species of marine fish using total RNA sequencing (meta-transcriptomics) combined with analyses of sequence and protein structural homology to identify divergent viruses that often evade characterization. From this, we identified twenty-five new vertebrate-associated viruses and a further twenty-two viruses likely associated with fish diet or their microbiomes. The vertebrate-associated viruses identified here included the first fish virus in the Matonaviridae (single-strand, negative-sense RNA virus). Other viruses fell within the Astroviridae, Picornaviridae, Arenaviridae, Reoviridae, Hepadnaviridae, Paramyxoviridae, Rhabdoviridae, Hantaviridae, Filoviridae, and Flaviviridae, and were sometimes phylogenetically distinct from known fish viruses. We also show how key metrics of virome composition—viral richness, abundance, and diversity—can be analysed along with host ecological and biological factors as a means to understand virus ecology. Accordingly, these data suggest that that the vertebrate-associated viromes of the fish sampled here are predominantly shaped by the phylogenetic history (i.e. taxonomic order) of their hosts, along with several biological factors including water temperature, habitat depth, community diversity and swimming behaviour. No such correlations were found for viruses associated with porifera, molluscs, arthropods, fungi, and algae, that are unlikely to replicate in fish hosts. Overall, these data indicate that fish harbour particularly large and complex viromes and the vast majority of fish viromes are undescribed.

scholarly journals GenomeDiver: A platform for phenotype-guided medical genomic diagnosis

2020 ◽  
Author(s):  
Nathaniel Pearson ◽  
Christian Stolte ◽  
Kevin Shi ◽  
Faygel Beren ◽  
Noura S. Abul-Husn ◽  
...  
Keyword(s):  
Diagnostic Testing ◽  
Diagnostic Process ◽  
Genomic Sequencing ◽  
Sequencing Data ◽  
Clinical Diagnostic Laboratory ◽  
Diagnostic Laboratory ◽  
Phenotypic Data ◽  
Human Phenotype ◽  
Phenotype Data

ABSTRACTPurposeMaking a diagnosis from clinical genomic sequencing requires well-structured phenotypic data to guide genotype interpretation. A patient’s phenotypic features can be documented using the Human Phenotype Ontology (HPO), generating terms used to prioritize genes potentially causing the patient’s disease. We have developed GenomeDiver to provide a user interface for clinicians that allows more effective collaboration with the clinical diagnostic laboratory, with the goal of improving the success of the diagnostic process.MethodsGenomeDiver is designed to prompt reverse phenotyping of patients undergoing genetic testing, enriching the amount and quality of structured phenotype data for the diagnostic laboratory, and helping clinicians to explore and flag diseases potentially causing their patient’s presentation.ResultsWe show how GenomeDiver communicates the clinician’s informed insights to the diagnostic lab in the form of HPO terms for interpretation of genomic sequencing data. We describe our user-driven design process, the engineering of the software for efficiency, security and portability, and an example of the performance of GenomeDiver using simulated genomic testing data.ConclusionsGenomeDiver is a first step in a new approach to genomic diagnostics that enhances laboratory-clinician interactions, with the goal of directly engaging clinicians to improve the outcome of genomic diagnostic testing.

scholarly journals Genome organization and molecular characterization of the three Formica exsecta viruses—FeV1, FeV2 and FeV4

PeerJ ◽  
2019 ◽  
Vol 6 ◽  
pp. e6216 ◽  
Author(s):  
Kishor Dhaygude ◽  
Helena Johansson ◽  
Jonna Kulmuni ◽  
Liselotte Sundström
Keyword(s):  
Molecular Characterization ◽  
Genome Organization ◽  
Rna Virus ◽  
Open Reading Frames ◽  
Link Type ◽  
Infection Pathways ◽  
Comparative Genomics Analysis ◽  
First Time ◽  
Negative Sense

We present the genome organization and molecular characterization of the three Formica exsecta viruses, along with ORF predictions, and functional annotation of genes. The Formica exsecta virus-4 (FeV4; GenBank ID: MF287670) is a newly discovered negative-sense single-stranded RNA virus representing the first identified member of order Mononegavirales in ants, whereas the Formica exsecta virus-1 (FeV1; GenBank ID: KF500001), and the Formica exsecta virus-2 (FeV2; GenBank ID: KF500002) are positive single-stranded RNA viruses initially identified (but not characterized) in our earlier study. The new virus FeV4 was found by re-analyzing data from a study published earlier. The Formica exsecta virus-4 genome is 9,866 bp in size, with an overall G + C content of 44.92%, and containing five predicted open reading frames (ORFs). Our bioinformatics analysis indicates that gaps are absent and the ORFs are complete, which based on our comparative genomics analysis suggests that the genomes are complete. Following the characterization, we validate virus infection for FeV1, FeV2 and FeV4 for the first time in field-collected worker ants. Some colonies were infected by multiple viruses, and the viruses were observed to infect all castes, and multiple life stages of workers and queens. Finally, highly similar viruses were expressed in adult workers and queens of six other Formica species: F. fusca, F. pressilabris, F. pratensis, F. aquilonia, F. truncorum and F. cinerea. This research indicates that viruses can be shared between ant species, but further studies on viral transmission are needed to understand viral infection pathways.

scholarly journals Comprehensive analysis of RNA-seq and whole genome sequencing data reveals no evidence for SARS-CoV-2 integrating into host genome

2021 ◽  
Author(s):  
Yu-Sheng Chen ◽  
Shuaiyao Lu ◽  
Bing Zhang ◽  
Tingfu Du ◽  
Wen-Jie Li ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Rna Virus ◽  
Comprehensive Analysis ◽  
Host Genome ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Rna Seq ◽  
Sequencing Data ◽  
Infected Cells

SARS-CoV-2, as the causation of severe epidemic of COVID-19, is one kind of positive single-stranded RNA virus with high transmissibility. However, whether or not SARS-CoV-2 can integrate into host genome needs thorough investigation. Here, we performed both RNA sequencing (RNA-seq) and whole genome sequencing on SARS-CoV-2 infected human and monkey cells, and investigated the presence of host-virus chimeric events. Through RNA-seq, we did detect the chimeric host-virus reads in the infected cells. But further analysis using mixed libraries of infected cells and uninfected zebrafish embryos demonstrated that these reads are falsely generated during library construction. In support, whole genome sequencing also didn't identify the existence of chimeric reads in their corresponding regions. Therefore, the evidence for SARS-CoV-2's integration into host genome is lacking.

scholarly journals A discovery 70 years in the making: characterization of the Rose rosette virus

2011 ◽  
Vol 92 (7) ◽  
pp. 1727-1732 ◽  
Author(s):  
Alma G. Laney ◽  
Karen E. Keller ◽  
Robert R. Martin ◽  
Ioannis E. Tzanetakis
Keyword(s):  
Rna Virus ◽  
Causal Agent ◽  
Low Diversity ◽  
The Usa ◽  
Rose Rosette ◽  
Diversity Studies ◽  
The Rose ◽  
Negative Sense ◽  
Eastern Half

Rose rosette was first described in the early 1940s and it has emerged as one of the most devastating diseases of roses. Although it has been 70 years since the disease description, the rosette agent is yet to be characterized. In this communication, we identify and characterize the putative causal agent of the disease, a negative-sense RNA virus and new member of the genus Emaravirus. The virus was detected in 84/84 rose rosette-affected plants collected from the eastern half of the USA, but not in any of 30 symptomless plants tested. The strong correlation between virus and disease is a good indication that the virus, provisionally named Rose rosette virus, is the causal agent of the disease. Diversity studies using two virus proteins, p3 and p4, demonstrated that the virus has low diversity between isolates as they share nucleotide identities ranging from 97 to 99%.

scholarly journals The Segment Matters: Probable Reassortment of Tilapia Lake Virus (TiLV) Complicates Phylogenetic Analysis and Inference of Geographical Origin of New Isolate from Bangladesh

Viruses ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 258 ◽  
Author(s):  
Dominique L. Chaput ◽  
David Bass ◽  
Md. Mehedi Alam ◽  
Neaz Al Hasan ◽  
Grant D. Stentiford ◽  
...  
Keyword(s):  
Phylogenetic Analysis ◽  
Geographical Origin ◽  
Rna Virus ◽  
Geographic Origin ◽  
South American ◽  
Reassortment Event ◽  
Coding Regions ◽  
Whole Genomes ◽  
History Of ◽  
Negative Sense

Tilapia lake virus (TiLV), a negative sense RNA virus with a 10 segment genome, is an emerging threat to tilapia aquaculture worldwide, with outbreaks causing over 90% mortality reported on several continents since 2014. Following a severe tilapia mortality event in July 2017, we confirmed the presence of TiLV in Bangladesh and obtained the near-complete genome of this isolate, BD-2017. Phylogenetic analysis of the concatenated 10 segment coding regions placed BD-2017 in a clade with the two isolates from Thailand, separate from the Israeli and South American isolates. However, phylogenetic analysis of individual segments gave conflicting results, sometimes clustering BD-2017 with one of the Israeli isolates, and splitting pairs of isolates from the same region. By comparing patterns of topological difference among segments of quartets of isolates, we showed that TiLV likely has a history of reassortment. Segments 5 and 6, in particular, appear to have undergone a relatively recent reassortment event involving Ecuador isolate EC-2012 and Israel isolate Til-4-2011. The phylogeny of TiLV isolates therefore depends on the segment sequenced. Our findings illustrate the need to exercise caution when using phylogenetic analysis to infer geographic origin and track the movement of TiLV, and we recommend using whole genomes wherever possible.

scholarly journals Clonal reconstruction from time course genomic sequencing data

BMC Genomics ◽  
2019 ◽  
Vol 20 (S12) ◽  
Author(s):  
Wazim Mohammed Ismail ◽  
Haixu Tang
Keyword(s):  
Maximum Likelihood ◽  
Time Course ◽  
Bacterial Population ◽  
Heuristic Algorithms ◽  
Long Term Evolution ◽  
Genomic Sequencing ◽  
Multiple Time ◽  
Sequencing Data ◽  
Term Evolution

Abstract Background Bacterial cells during many replication cycles accumulate spontaneous mutations, which result in the birth of novel clones. As a result of this clonal expansion, an evolving bacterial population has different clonal composition over time, as revealed in the long-term evolution experiments (LTEEs). Accurately inferring the haplotypes of novel clones as well as the clonal frequencies and the clonal evolutionary history in a bacterial population is useful for the characterization of the evolutionary pressure on multiple correlated mutations instead of that on individual mutations. Results In this paper, we study the computational problem of reconstructing the haplotypes of bacterial clones from the variant allele frequencies observed from an evolving bacterial population at multiple time points. We formalize the problem using a maximum likelihood function, which is defined under the assumption that mutations occur spontaneously, and thus the likelihood of a mutation occurring in a specific clone is proportional to the frequency of the clone in the population when the mutation occurs. We develop a series of heuristic algorithms to address the maximum likelihood inference, and show through simulation experiments that the algorithms are fast and achieve near optimal accuracy that is practically plausible under the maximum likelihood framework. We also validate our method using experimental data obtained from a recent study on long-term evolution of Escherichia coli. Conclusion We developed efficient algorithms to reconstruct the clonal evolution history from time course genomic sequencing data. Our algorithm can also incorporate clonal sequencing data to improve the reconstruction results when they are available. Based on the evaluation on both simulated and experimental sequencing data, our algorithms can achieve satisfactory results on the genome sequencing data from long-term evolution experiments. Availability The program (ClonalTREE) is available as open-source software on GitHub at https://github.com/COL-IU/ClonalTREE.

Topic and Cluster Evolution Over Noisy Document Streams

2011 ◽  
pp. 220-239 ◽  
Author(s):  
Sascha Schulz ◽  
Myra Spiliopoulou ◽  
Rene Schult
Keyword(s):  
Strategic Management ◽  
Hierarchical Clustering ◽  
Relevant Literature ◽  
Information Filtering ◽  
Feature Space ◽  
Classification Schemes ◽  
Topic Evolution ◽  
Cluster Evolution ◽  
Time Periods ◽  
Emerging Topics

We study the issue of discovering and tracing thematic topics in a stream of documents. This issue, often studied under the label “topic evolution” is of interest in many applications where thematic trends should be identified and monitored, including environmental modelling for marketing and strategic management applications, information filtering over streams of news and enrichment of classification schemes with emerging new classes. We concentrate on the latter area and depict an example application from the automotive industry – the discovery of emerging topics in repair & maintenance reports. We first discuss relevant literature on (a) the discovery and monitoring of topics over document streams and (b) the monitoring of evolving clusters over arbitrary data streams. Then, we propose our own method for topic evolution over a stream of small noisy documents: We combine hierarchical clustering, performed at different time periods, with cluster comparison over adjacent time periods, taking into account that the feature space itself may change from one period to the next. We elaborate on the behaviour of this method and show how human experts can be assisted in identifying class candidates among the topics thus identified.

scholarly journals Old World hantaviruses do not produce detectable amounts of dsRNA in infected cells and the 5′ termini of their genomic RNAs are monophosphorylated

2011 ◽  
Vol 92 (5) ◽  
pp. 1199-1204 ◽  
Author(s):  
Hao Wang ◽  
Antti Vaheri ◽  
Friedemann Weber ◽  
Alexander Plyusnin
Keyword(s):  
Rna Virus ◽  
Innate Immune ◽  
Hantaan Virus ◽  
Signalling Pathways ◽  
Genomic Rna ◽  
Genomic Rnas ◽  
Old World ◽  
Interferon Induction ◽  
Infected Cells ◽  
Negative Sense

dsRNA and 5′-triphosphate RNA are considered critical activators of the innate immune response because of their interaction with pattern recognition receptors. It has been reported that no dsRNA is detected in negative-sense RNA virus-infected cells and that Hantaan virus (HTNV) genomic RNA bears a 5′ monophosphate group. In this paper we examine the 5′ termini of genomic RNAs of and dsRNA production by two major groups of Old World hantaviruses. No detectable amounts of dsRNA were found in infected cells. Also, the genomic RNAs of these hantaviruses bear a 5′ monophosphate group and therefore are unable to trigger interferon induction. Taken together with the earlier data on HTNV, these results suggest that in addition to the dsRNA and genomic RNA, which may be only minimally involved in the induction of innate immunity, other cellular signalling pathways may also be involved and that these await further investigation.

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