Reconstructing viral haplotypes using long reads

Cai, Dehan; Sun, Yanni

doi:10.1093/bioinformatics/btac089

Cited by 9 publications

(14 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many attempts have been made to reconstruct viral haplotypes using NGS reads. However, the short length of NGS reads cannot cover distant single-nucleotide variants, making it difficult to reconstruct complete or near-complete haplotypes ( Cai and Sun, 2022 ). Long-read ONT data can be used to study sample-specific genomic details, including structural variation (SV) and haplotypes.…”

Section: Summary and Future Prospectivementioning

confidence: 99%

Nanopore sequencing technology and its application in plant virus diagnostics

Sun

Liu

Zhou³

et al. 2022

Front. Microbiol.

View full text Add to dashboard Cite

Plant viruses threaten crop yield and quality; thus, efficient and accurate pathogen diagnostics are critical for crop disease management and control. Recent advances in sequencing technology have revolutionized plant virus research. Metagenomics sequencing technology, represented by next-generation sequencing (NGS), has greatly enhanced the development of virus diagnostics research because of its high sensitivity, high throughput and non-sequence dependence. However, NGS-based virus identification protocols are limited by their high cost, labor intensiveness, and bulky equipment. In recent years, Oxford Nanopore Technologies and advances in third-generation sequencing technology have enabled direct, real-time sequencing of long DNA or RNA reads. Oxford Nanopore Technologies exhibit versatility in plant virus detection through their portable sequencers and flexible data analyses, thus are wildly used in plant virus surveillance, identification of new viruses, viral genome assembly, and evolution research. In this review, we discuss the applications of nanopore sequencing in plant virus diagnostics, as well as their limitations.

show abstract

Section: Summary and Future Prospectivementioning

confidence: 99%

Nanopore sequencing technology and its application in plant virus diagnostics

Sun

Liu

Zhou³

et al. 2022

Front. Microbiol.

View full text Add to dashboard Cite

show abstract

“…Because SNVs indicate the differences between haplotypes, focusing on SNVs helps distinguish reads from different haplotypes. There are different methods for SNV detection ( Cai and Sun, 2022 ; Feng et al , 2021 ). Users can select an SNV detection tool to generate SNV sites as input to HaploDMF.…”

Section: Methodsmentioning

confidence: 99%

“…Users can select an SNV detection tool to generate SNV sites as input to HaploDMF. Here, we use our own method (RVHaplo) based on binomial tests for SNV detection ( Cai and Sun, 2022 ). It outputs a set of SNV sites given the alignment between reads and a reference genome.…”

Section: Methodsmentioning

confidence: 99%

“…Long-read assembly programs can be applied to haplotype reconstruction, but many of them ( Kolmogorov et al , 2020 ; Koren et al , 2017 ; Li, 2016 ; Ruan and Li, 2020 ) are not designed for viral populations with highly similar haplotypes. They tend to output contigs from the most dominant one ( Cai and Sun, 2022 ; Luo et al , 2022 ). Thus, haplotype reconstruction requires a different set of efforts from the generic assembly.…”

Section: Introductionmentioning

confidence: 99%

“…Three recently published tools use long reads to reconstruct haplotypes. RVHaplo ( Cai and Sun, 2022 ) and iGDA ( Feng et al , 2021 ) are two reference-based tools. They first detect sites containing SNVs from the alignment between reads and a reference genome.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

HaploDMF: viral haplotype reconstruction from long reads via deep matrix factorization

2022

Self Cite

View full text Add to dashboard Cite

Motivation Lacking strict proofreading mechanisms, many RNA viruses can generate progeny with slightly changed genomes. Being able to characterize highly similar genomes (i.e. haplotypes) in one virus population helps study the viruses’ evolution and their interactions with the host/other microbes. High-throughput sequencing data has become the major source for characterizing viral populations. However, the inherent limitation on read length by next-generation sequencing (NGS) makes complete haplotype reconstruction difficult. Results In this work, we present a new tool named HaploDMF that can construct complete haplotypes using third-generation sequencing (TGS) data. HaploDMF utilizes a deep matrix factorization model with an adapted loss function to learn latent features from aligned reads automatically. The latent features are then used to cluster reads of the same haplotype. Unlike existing tools whose performance can be affected by the overlap size between reads, HaploDMF is able to achieve highly robust performance on data with different coverage, haplotype number, and error rates. In particular, it can generate more complete haplotypes even when the sequencing coverage drops in the middle. We benchmark HaploDMF against the state-of-the-art tools on simulated and real sequencing TGS data on different viruses. The results show that HaploDMF competes favorably against all others. Availability The source code and the documentation of HaploDMF are available at https://github.com/dhcai21/HaploDMF. Supplementary information Supplementary data are available at Bioinformatics online.

show abstract

Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks

Mohebbi,

Zelikovsky,

Mangul

et al. 2024

Nat Commun

View full text Add to dashboard Cite

The emergence of viral variants with altered phenotypes is a public health challenge underscoring the need for advanced evolutionary forecasting methods. Given extensive epistatic interactions within viral genomes and known viral evolutionary history, efficient genomic surveillance necessitates early detection of emerging viral haplotypes rather than commonly targeted single mutations. Haplotype inference, however, is a significantly more challenging problem precluding the use of traditional approaches. Here, using SARS-CoV-2 evolutionary dynamics as a case study, we show that emerging haplotypes with altered transmissibility can be linked to dense communities in coordinated substitution networks, which become discernible significantly earlier than the haplotypes become prevalent. From these insights, we develop a computational framework for inference of viral variants and validate it by successful early detection of known SARS-CoV-2 strains. Our methodology offers greater scalability than phylogenetic lineage tracing and can be applied to any rapidly evolving pathogen with adequate genomic surveillance data.

show abstract

Reconstructing viral haplotypes using long reads

Cited by 9 publications

References 31 publications

Nanopore sequencing technology and its application in plant virus diagnostics

Nanopore sequencing technology and its application in plant virus diagnostics

HaploDMF: viral haplotype reconstruction from long reads via deep matrix factorization

Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks

Contact Info

Product

Resources

About