Haplotype determination of the Bombyx mori nucleopolyhedrovirus by Nanopore sequencing and linkage of single nucleotide variants.

IF 3.6 4区 医学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Jörg T Wennmann, Fang-Shiang Lim, Sergei Senger, Mudasir Gani, Johannes A Jehle, Jens Keilwagen
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引用次数: 0

Abstract

Naturally occurring isolates of baculoviruses, such as the Bombyx mori nucleopolyhedrovirus (BmNPV), usually consist of numerous genetically different haplotypes. Deciphering the different haplotypes of such isolates is hampered by the large size of the dsDNA genome, as well as the short read length of next generation sequencing (NGS) techniques that are widely applied for baculovirus isolate characterization. In this study, we addressed this challenge by combining the accuracy of NGS to determine single nucleotide variants (SNVs) as genetic markers with the long read length of Nanopore sequencing technique. This hybrid approach allowed the comprehensive analysis of genetically homogeneous and heterogeneous isolates of BmNPV. Specifically, this allowed the identification of two putative major haplotypes in the heterogeneous isolate BmNPV-Ja by SNV position linkage. SNV positions, which were determined based on NGS data, were linked by the long Nanopore reads in a Position Weight Matrix. Using a modified Expectation-Maximization algorithm, the Nanopore reads were assigned according to the occurrence of variable SNV positions by machine learning. The cohorts of reads were de novo assembled, which led to the identification of BmNPV haplotypes. The method demonstrated the strength of the combined approach of short- and long-read sequencing techniques to decipher the genetic diversity of baculovirus isolates.

通过纳米孔测序和单核苷酸变异的连接确定蚕核多角体病毒的单倍型。
天然存在的杆状病毒分离物(如蚕核多角体病毒(BmNPV))通常由许多基因不同的单倍型组成。由于dsDNA基因组体积庞大,而广泛应用于杆状病毒分离鉴定的新一代测序(NGS)技术读长较短,因此破译这些分离株的不同单倍型受到了阻碍。在本研究中,我们将 NGS 测定单核苷酸变异(SNV)作为遗传标记的准确性与 Nanopore 测序技术的长读长相结合,从而解决了这一难题。这种混合方法可对 BmNPV 的基因同质性和异质性分离物进行全面分析。具体来说,这种方法可以通过 SNV 位置联接在异源分离物 BmNPV-Ja 中鉴定出两种推定的主要单倍型。根据 NGS 数据确定的 SNV 位置通过位置权重矩阵中的 Nanopore 长读数连接起来。利用改进的期望最大化算法,通过机器学习根据可变 SNV 位置的出现情况分配 Nanopore 读数。对读数队列进行了从头组装,从而确定了 BmNPV 单倍型。该方法证明了长短线程测序技术相结合的方法在破译杆状病毒分离株遗传多样性方面的优势。
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来源期刊
Journal of General Virology
Journal of General Virology 医学-病毒学
CiteScore
7.70
自引率
2.60%
发文量
91
审稿时长
3 months
期刊介绍: JOURNAL OF GENERAL VIROLOGY (JGV), a journal of the Society for General Microbiology (SGM), publishes high-calibre research papers with high production standards, giving the journal a worldwide reputation for excellence and attracting an eminent audience.
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