VIRTUS: a pipeline for comprehensive virus analysis from conventional RNA-seq data

Yasumizu, Yoshiaki; Hara, Atsushi; Sakaguchi, Shimon; Ohkura, Naganari

doi:10.1101/2020.05.08.085308

Cited by 4 publications

(4 citation statements)

References 16 publications

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“…The comprehensive viral quantification of RNA-seq was performed by a bioinformatics pipeline; VIRTUS 62 (v1.2.1), which was composed of fastp, STAR, and Salmon. First, we created indices using createindex.cwl with references downloaded from Gencode v33.…”

Section: Methodsmentioning

confidence: 99%

Myasthenia gravis-specific aberrant neuromuscular gene expression by medullary thymic epithelial cells in thymoma

Yasumizu

Ohkura

Murata

et al. 2021

Preprint

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Myasthenia gravis (MG) is a neurological disease caused by autoantibodies against neuromuscular-associated proteins. While MG is frequently developed in thymoma patients, the etiologic factors for MG are not well understood. Here, by constructing a comprehensive atlas of thymoma using bulk and single-cell RNA-seq, we identified ectopic expression of neuromuscular molecules in MG-associated thymoma (MG-thymoma). These molecules were originated from a distinct subpopulation of medullary thymic epithelial cells (mTECs), which we named neuromuscular mTECs (nmTECs). MG-thymoma also exhibited microenvironments dedicated to autoantibody production, including ectopic germinal center formation, T follicular helper cell accumulation, and type 2 conventional dendritic cell migration. Cell-cell interaction analysis also predicted the interaction between nmTECs and T/B cells via CXCL12-CXCR4. The enrichment of nmTECs presenting neuromuscular molecules within MG-thymoma was further confirmed by immunohistochemically and by cellular composition estimation from MG-thymoma transcriptome. Altogether, this study suggests that nmTECs play a significant role in MG pathogenesis via ectopic expression of neuromuscular molecules.

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Section: Methodsmentioning

confidence: 99%

Myasthenia gravis-specific aberrant neuromuscular gene expression by medullary thymic epithelial cells in thymoma

Yasumizu

Ohkura

Murata

et al. 2021

Preprint

Self Cite

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“…VIRTUS is applied to identify the cells sheltering activated viruses and not the copy number of the virus, the composition of multiple viruses in a cell, and the expression differences between infected and uninfected cells. 87…”

Section: Virtusmentioning

confidence: 99%

“…A sensor named VIRTUS (Viral Transcript Usage Sensor) was developed for detecting and quantifying mRNA transcripts in the data of traditional human RNA‐seq data. VIRTUS is applied to identify the cells sheltering activated viruses and not the copy number of the virus, the composition of multiple viruses in a cell, and the expression differences between infected and uninfected cells 87 …”

Section: Detectionmentioning

confidence: 99%

COVID‐19: A systematic review and update on prevention, diagnosis, and treatment

Aliabadi

Eivazzadeh‐Keihan

Parikhani

et al. 2022

MedComm

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Since the rapid onset of the COVID‐19 or SARS‐CoV‐2 pandemic in the world in 2019, extensive studies have been conducted to unveil the behavior and emission pattern of the virus in order to determine the best ways to diagnosis of virus and thereof formulate effective drugs or vaccines to combat the disease. The emergence of novel diagnostic and therapeutic techniques considering the multiplicity of reports from one side and contradictions in assessments from the other side necessitates instantaneous updates on the progress of clinical investigations. There is also growing public anxiety from time to time mutation of COVID‐19, as reflected in considerable mortality and transmission, respectively, from delta and Omicron variants. We comprehensively review and summarize different aspects of prevention, diagnosis, and treatment of COVID‐19. First, biological characteristics of COVID‐19 were explained from diagnosis standpoint. Thereafter, the preclinical animal models of COVID‐19 were discussed to frame the symptoms and clinical effects of COVID‐19 from patient to patient with treatment strategies and in‐silico/computational biology. Finally, the opportunities and challenges of nanoscience/nanotechnology in identification, diagnosis, and treatment of COVID‐19 were discussed. This review covers almost all SARS‐CoV‐2‐related topics extensively to deepen the understanding of the latest achievements (last updated on January 11, 2022).

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“…Transcriptome from a host tissue may contain mRNAs from microorganisms that have not been fully investigated. Several tools have been developed to detect the microbiomes in the RNAseq data, such as Kraken2 [6], VIRTUS [7], and IDseq [8]. However, there is no convenient tool that can analyze both host and microbiome transcriptome in the same set of data within a single workflow of analyses, which poses a challenge to researchers, especially those without bioinformatics expertise, who are interested in examining microbiome in host tissues and its relation to the endogenous expression of host genes at the both bulk tissue and single-cell level.…”

Section: Introductionmentioning

confidence: 99%

MTD: a unique pipeline for host and meta-transcriptome joint and integrative analyses of RNA-seq data

Liu

Ling

2021

Preprint

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RNA-seq data contains not only host transcriptomes but also non-host information that comprises transcripts from active microbiota in the host cells. Therefore, joint and integrative analyses of both host and meta-transcriptome can reveal gene expression of microbial community in a given sample as well as the correlative and interactive dynamics of host response to the microbiome. However, there are no convenient tools that can systemically analyze host-microbiota interactions by simultaneously quantifying host and meta-transcriptome in the same sample at the tissue and the single-cell level, which poses a challenge for interested researchers with a limited expertise in bioinformatics. Here, we developed a software pipeline that can comprehensively and synergistically analyze and correlate the host and meta-transcriptome in a single sample using bulk and single-cell RNA-seq data. This pipeline, named MTD, can extensively identify and quantify microbiome, including viruses, bacteria, protozoa, fungi, plasmids, and vectors in the host cells and correlate the microbiome with the host transcriptome. MTD is easy to install and run, involving only a few lines of simple commands. It empowers researchers with unique genomics insights into host immune responses to microorganisms.

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VIRTUS: a pipeline for comprehensive virus analysis from conventional RNA-seq data

Cited by 4 publications

References 16 publications

Myasthenia gravis-specific aberrant neuromuscular gene expression by medullary thymic epithelial cells in thymoma

Myasthenia gravis-specific aberrant neuromuscular gene expression by medullary thymic epithelial cells in thymoma

COVID‐19: A systematic review and update on prevention, diagnosis, and treatment

MTD: a unique pipeline for host and meta-transcriptome joint and integrative analyses of RNA-seq data

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