scholarly journals Jumper enables discontinuous transcript assembly in coronaviruses

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Palash Sashittal ◽  
Chuanyi Zhang ◽  
Jian Peng ◽  
Mohammed El-Kebir
Keyword(s):  
Alternative Splicing ◽  
Maximum Likelihood ◽  
Rna Polymerase ◽  
Drug Response ◽  
Transcript Level ◽  
Rna Dependent Rna Polymerase ◽  
Short Read ◽  
Likelihood Model ◽  
Discontinuous Transcription ◽  
Transcript Assembly

AbstractGenes in SARS-CoV-2 and other viruses in the order of Nidovirales are expressed by a process of discontinuous transcription which is distinct from alternative splicing in eukaryotes and is mediated by the viral RNA-dependent RNA polymerase. Here, we introduce the DISCONTINUOUS TRANSCRIPT ASSEMBLYproblem of finding transcripts and their abundances given an alignment of paired-end short reads under a maximum likelihood model that accounts for varying transcript lengths. We show, using simulations, that our method, JUMPER, outperforms existing methods for classical transcript assembly. On short-read data of SARS-CoV-1, SARS-CoV-2 and MERS-CoV samples, we find that JUMPER not only identifies canonical transcripts that are part of the reference transcriptome, but also predicts expression of non-canonical transcripts that are supported by subsequent orthogonal analyses. Moreover, application of JUMPER on samples with and without treatment reveals viral drug response at the transcript level. As such, JUMPER enables detailed analyses of Nidovirales transcriptomes under varying conditions.

scholarly journals JUMPER Enables Discontinuous Transcript Assembly in Coronaviruses

2021 ◽  
Author(s):  
Palash Sashittal ◽  
Chuanyi Zhang ◽  
Jian Peng ◽  
Mohammed El-Kebir
Keyword(s):  
Alternative Splicing ◽  
Hamiltonian Path ◽  
Transcript Level ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Splice Graph ◽  
Long Read ◽  
Likelihood Model ◽  
Characterization Of Solutions ◽  
Transcript Assembly

Abstract Genes in SARS-CoV-2 and other viruses in the order of Nidovirales are expressed by a process of discontinuous transcription mediated by the viral RNA-dependent RNA polymerase. This process is distinct from alternative splicing in eukaryotes and produces subgenomic RNAs that express different viral genes. Here, we introduce the DISCONTINUOUS TRANSCRIPT ASSEMBLY problem of finding transcripts T and their abundances c given an alignment R of paired end short reads under a maximum likelihood model that accounts for varying transcript lengths. Underpinning our approach is the concept of a segment graph, a directed acyclic graph that, distinct from the splice graph used to characterize alternative splicing, has a unique Hamiltonian path. We provide a compact characterization of solutions as subsets of non-overlapping edges in this graph, enabling the formulation of an efficient progressive heuristic that uses mixed integer linear program. We show using simulations that our method, JUMPER, drastically outperforms existing methods for classical transcript assembly. On short-read data of SARS-CoV-1, SARS-CoV-2 and MERS-CoV samples, we find that JUMPER not only identifies canonical transcripts that are part of the reference transcriptome, but also predicts expression of non-canonical transcripts that are well supported by direct evidence from long-read data, presence in multiple, independent samples or a conserved core sequence. Moreover, application of JUMPER on samples with and without treatment reveals viral drug response at the transcript level. As such, JUMPER enables detailed analyses of Nidovirales transcriptomes under varying conditions.

scholarly journals Jumper Enables Discontinuous Transcript Assembly in Coronaviruses

2021 ◽  
Author(s):  
Palash Sashittal ◽  
Chuanyi Zhang ◽  
Jian Peng ◽  
Mohammed El-Kebir
Keyword(s):  
Alternative Splicing ◽  
Hamiltonian Path ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Splice Graph ◽  
Long Read ◽  
Likelihood Model ◽  
Characterization Of Solutions ◽  
Conserved Core ◽  
Transcript Assembly

AbstractGenes in SARS-CoV-2 and, more generally, in viruses in the order of Nidovirales are expressed by a process of discontinuous transcription mediated by the viral RNA-dependent RNA polymerase. This process is distinct from alternative splicing in eukaryotes, rendering current transcript assembly methods unsuitable to Nidovirales sequencing samples. Here, we introduce the Discontinuous Transcript Assembly problem of finding transcripts and their abundances c given an alignment under a maximum likelihood model that accounts for varying transcript lengths. Underpinning our approach is the concept of a segment graph, a directed acyclic graph that, distinct from the splice graph used to characterize alternative splicing, has a unique Hamiltonian path. We provide a compact characterization of solutions as subsets of non-overlapping edges in this graph, enabling the formulation of an efficient mixed integer linear program. We show using simulations that our method, Jumper, drastically outperforms existing methods for classical transcript assembly. On short-read data of SARS-CoV-1 and SARS-CoV-2 samples, we find that Jumper not only identifies canonical transcripts that are part of the reference transcriptome, but also predicts expression of non-canonical transcripts that are well supported by direct evidence from long-read data, presence in multiple, independent samples or a conserved core sequence. Jumper enables detailed analyses of Nidovirales transcriptomes.Code availabilitySoftware is available at https://github.com/elkebir-group/Jumper

Recent Advances towards Drug Design Targeting the Protease of 2019 novel coronavirus (2019-nCoV)

2020 ◽  
Vol 27 ◽  
Author(s):  
Sehrish Bano ◽  
Abdul Hameed ◽  
Mariya Al-Rashida ◽  
Shafia Iftikhar ◽  
Jamshed Iqbal
Keyword(s):  
Drug Design ◽  
Rna Polymerase ◽  
Drug Targets ◽  
Antiviral Agents ◽  
Structural Features ◽  
Antiviral Drugs ◽  
Rna Dependent Rna Polymerase ◽  
Mortality And Morbidity ◽  
Functional Relationships ◽  
Novel Coronavirus

Background: The 2019 novel coronavirus (2019-nCoV), also known as coronavirus 2 (SARS-CoV-2) acute respiratory syndrome has recently emerged and continued to spread rapidly with high level of mortality and morbidity rates. Currently, no efficacious therapy is available to relieve coronavirus infections. As new drug design and development takes much time, there is a possibility to find an effective treatment from existing antiviral agents. Objective: In this case, there is a need to find out the relationship between possible drug targets and mechanism of action of antiviral drugs. This review discusses about the efforts to develop drug from known or new molecules. Methods: Viruses usually have two structural integrities, proteins and nucleic acids, both of which can be possible drug targets. Herein, we systemically discuss the structural-functional relationships of the spike, 3-chymotrypsin-like protease (3CLpro), papain like protease (PLpro) and RNA-dependent RNA polymerase (RdRp), as these are prominent structural features of corona virus. Certain antiviral drugs such as Remdesivir are RNA dependent RNA polymerase inhibitor. It has the ability to terminate RNA replication by inhibiting ATP. Results: It is reported that ATP is involved in synthesis of coronavirus non-structural proteins from 3CLpro and PLpro. Similarly, mechanisms of action of many other antiviral agents has been discussed in this review. It will provide new insights into the mechanism of inhibition, and let us develop new therapeutic antiviral approaches against novel SARS-CoV-2 coronavirus. Conclusion: In conclusion, this review summarizes recent progress in developing protease inhibitors for SARS-CoV-2.

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