Dataset Information

Characterizing Transcriptional Regulatory Sequences in Coronaviruses and Their Role in Recombination.

ABSTRACT: Novel coronaviruses, including SARS-CoV-2, SARS, and MERS, often originate from recombination events. The mechanism of recombination in RNA viruses is template switching. Coronavirus transcription also involves template switching at specific regions, called transcriptional regulatory sequences (TRS). It is hypothesized but not yet verified that TRS sites are prone to recombination events. Here, we developed a tool called SuPER to systematically identify TRS in coronavirus genomes and then investigated whether recombination is more common at TRS. We ran SuPER on 506 coronavirus genomes and identified 465 TRS-L and 3,509 TRS-B. We found that the TRS-L core sequence (CS) and the secondary structure of the leader sequence are generally conserved within coronavirus genera but different between genera. By examining the location of recombination breakpoints with respect to TRS-B CS, we observed that recombination hotspots are more frequently colocated with TRS-B sites than expected.

SUBMITTER: Yang Y

PROVIDER: S-EPMC7665640 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characterizing Transcriptional Regulatory Sequences in Coronaviruses and Their Role in Recombination.

Yang Yiyan Y Yan Wei W Hall A Brantley AB Jiang Xiaofang X

Molecular biology and evolution 20210401 4

Novel coronaviruses, including SARS-CoV-2, SARS, and MERS, often originate from recombination events. The mechanism of recombination in RNA viruses is template switching. Coronavirus transcription also involves template switching at specific regions, called transcriptional regulatory sequences (TRS). It is hypothesized but not yet verified that TRS sites are prone to recombination events. Here, we developed a tool called SuPER to systematically identify TRS in coronavirus genomes and then invest ...[more]

PMID: 33146390

Similar Datasets

Project description:Recombination is a significant factor driving the evolution of RNA viruses. The prevalence and variation of porcine reproductive and respiratory syndrome virus (PRRSV) in China have been increasing in complexity due to extensive interlineage recombination. When this recombination phenomenon occurs in live vaccine strains, it becomes increasingly difficult to prevent and control PRRSV. Reverse genetic manipulation to engineer a different transcriptional regulatory sequence (TRS) circuit introduces genetic traps into the viral genome that are lethal to recombinant RNA progeny viruses. In this study, major interlineage recombination patterns were identified between lineage 1 (L1) PRRSVs and lineage 8 (L8) PRRSVs in China, from 2019 to 2023. The recombinant mutant virus, vA-TRSall, was constructed and successfully rescued by rewiring the entire TRS circuit without changing the amino acid-coding sequence in the genome of the PRRSV live vaccine strain vHuN4-F112. The vA-TRSall, with a brand new TRS circuit, provided effective immune protection against the highly pathogenic L8 PRRSV (vHuN4) and epidemic NADC30-like L1 PRRSV (vZJqz21). Recombination analysis in vitro and in vivo showed that, compared with the vHuN4-F112 and vZJqz21 co-infection groups, the incidence rates of mutation breakpoints and template-switching recombination in the vA-TRSall and vZJqz21 co-infected groups were effectively reduced. The results have enriched our understanding of the critical role of TRS circuits in PRRSV recombination mechanisms and indicate a successful redesign that can endow PRRSV live vaccines with recombination-resistant capabilities.ImportancePorcine reproductive and respiratory syndrome viruses (PRRSVs) are genetically diverse, and this is due in part to their extensive recombination. Live vaccines are widely used to prevent and control PRRS in China. However, owing to the wide variety of live vaccines, non-standard use, and the wild viruses prevalent on pig farms, new strains, generated via RNA recombination, are continuously emerging. Vaccine strains are also involved in PRRSV recombination, which leads to the emergence of new variants and alterations in virulence and pathogenesis. A recombination-resistant genome was engineered by rewiring the entire transcriptional regulatory sequence (TRS) circuit of the live PRRSV vaccine strain. Theoretically, after clinical application, once the virus recombines with the genome of the epidemic strain, the base pairing between the two sets of TRS circuits should be disrupted, resulting in a fatal genetic trap for the generation of an RNA recombinant progeny virus. Therefore, the remodeled PRRSV TRS mutant generated in this study can serve as a recombination-resistant platform for the rational design of safe PRRS vaccines in the future.

Project description:BackgroundHigh throughput gene expression experiments yield large amounts of data that can augment our understanding of disease processes, in addition to classifying samples. Here we present new paradigms of data Separation based on construction of transcriptional regulatory networks for normal and abnormal cells using sequence predictions, literature based data and gene expression studies. We analyzed expression datasets from a number of diseased and normal cells, including different types of acute leukemia, and breast cancer with variable clinical outcome.ResultsWe constructed sample-specific regulatory networks to identify links between transcription factors (TFs) and regulated genes that differentiate between healthy and diseased states. This approach carries the advantage of identifying key transcription factor-gene pairs with differential activity between healthy and diseased states rather than merely using gene expression profiles, thus alluding to processes that may be involved in gene deregulation. We then generalized this approach by studying simultaneous changes in functionality of multiple regulatory links pointing to a regulated gene or emanating from one TF (or changes in gene centrality defined by its in-degree or out-degree measures, respectively). We found that samples can often be separated based on these measures of gene centrality more robustly than using individual links. We examined distributions of distances (the number of links needed to traverse the path between each pair of genes) in the transcriptional networks for gene subsets whose collective expression profiles could best separate each dataset into predefined groups. We found that genes that optimally classify samples are concentrated in neighborhoods in the gene regulatory networks. This suggests that genes that are deregulated in diseased states exhibit a remarkable degree of connectivity.ConclusionTranscription factor-regulated gene links and centrality of genes on transcriptional networks can be used to differentiate between cell types. Transcriptional network blueprints can be used as a basis for further research into gene deregulation in diseased states.

Dataset Information

Characterizing Transcriptional Regulatory Sequences in Coronaviruses and Their Role in Recombination.

Publications

Characterizing Transcriptional Regulatory Sequences in Coronaviruses and Their Role in Recombination.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets