ArticleNature communications2021
Jumper enables discontinuous transcript assembly in coronaviruses.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Cross-genus analysis reveals architecturally programmed sgRNA synthesis patterns in coronaviruses.Molecular systems biology · 2026Article
- VirDiG: aBioinformatics advances · 2025Article
- Minimum flow decomposition in graphs with cycles using integer linear programming.Journal of global optimization : an international journal dealing with theoretical and computational aspects of seeking global optima and their applications in science, management and engineering · 2025Article
- Cov-trans: an efficient algorithm for discontinuous transcript assembly in coronaviruses.BMC genomics · 2024Article
- A safety framework for flow decomposition problems via integer linear programming.Bioinformatics (Oxford, England) · 2023Article
- Efficient Minimum Flow Decomposition via Integer Linear Programming.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
- Accurate Identification of Transcription Regulatory Sequences and Genes in Coronaviruses.Molecular biology and evolution · 2022Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Genes 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.