Quantitative measures of within-host viral genetic diversity

Fuhrmann, Lara; Jablonski, Kim Philipp; Beerenwinkel, Niko

doi:10.1016/j.coviro.2021.06.002

Cited by 12 publications

(5 citation statements)

References 43 publications

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“…This pattern of intrahost evolution results in the formation of mutant spectra that constitute reservoirs of genetic and phenotypic virus variants in the infected host ( 11 , 12 ). Studies with several RNA viruses have shown that viral intramutant spectrum complexity, estimated by the average number of mutations per genome, expressed by a series of diversity indices (Shannon entropy, maximum mutation frequency, Gini Simpson, nucleotide diversity, number of polymorphic sites, and number of haplotypes [ 13 , 14 ]), may have an impact on viral tropism, viral persistence, disease progression, and response to antiviral interventions (several cases have been described or reviewed in references 11 and 15 – 22 ). Evidence of quasispecies dynamics has been reported for SARS-CoV-2 ( 23 – 29 ), as well as for other coronaviruses ( 30 – 34 ).…”

Section: Introductionmentioning

confidence: 99%

SARS-CoV-2 Point Mutation and Deletion Spectra and Their Association with Different Disease Outcomes

et al. 2022

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The study shows that mutant spectra of SARS-CoV-2 from diagnostic samples differ in point mutation abundance and complexity and that significantly larger values were observed in virus from patients who developed mild COVID-19 symptoms. Mutant spectrum complexity is not a uniform trait among isolates. The nature and location of low-frequency amino acid substitutions present in mutant spectra anticipate great potential for phenotypic diversification of SARS-CoV-2.

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Section: Introductionmentioning

confidence: 99%

SARS-CoV-2 Point Mutation and Deletion Spectra and Their Association with Different Disease Outcomes

et al. 2022

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“…To demonstrate the ease with which new software components and scrips can be introduced we added two methods for viral diversity estimation: first, PredictHaplo [29] a well-performing global haplotype reconstruction method, and second, a script for the computation of within-sample diversity indices [42], like Shannon Entropy or population nucleotide diversity. The indices are often applied to compare diversity between samples and have been used for the estimation of time since infection [43].…”

Section: Adaptabilitymentioning

confidence: 99%

V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation

Fuhrmann,

Jablonski,

Topolsky

et al. 2023

Preprint

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The large amount and diversity of viral genomic datasets generated by next-generation sequencing technologies poses a set of challenges for computational data analysis workflows, including rigorous quality control, adaptation to higher sample coverage, and tailored steps for specific applications. Here, we present V-pipe 3.0, a computational pipeline designed for analyzing next-generation sequencing data of short viral genomes. It is developed to enable reproducible, scalable, adaptable, and transparent inference of genetic diversity of viral samples. By presenting two large-scale data analysis projects, we demonstrate the effectiveness of V-pipe 3.0 in supporting sustainable viral genomic data science.

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“…Population heterogeneity extends to RNA viruses (and some DNA viruses) replicating in their natural habitats, as well as in cell culture, where designed experiments have permitted quantification of relevant parameters (mutation rates and frequencies, population size effects on viral fitness, etc.) (as representative articles and reviews, see [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31]).…”

Section: Introductionmentioning

confidence: 99%

SARS-CoV-2 Mutant Spectra at Different Depth Levels Reveal an Overwhelming Abundance of Low Frequency Mutations

et al. 2022

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Populations of RNA viruses are composed of complex and dynamic mixtures of variant genomes that are termed mutant spectra or mutant clouds. This applies also to SARS-CoV-2, and mutations that are detected at low frequency in an infected individual can be dominant (represented in the consensus sequence) in subsequent variants of interest or variants of concern. Here we briefly review the main conclusions of our work on mutant spectrum characterization of hepatitis C virus (HCV) and SARS-CoV-2 at the nucleotide and amino acid levels and address the following two new questions derived from previous results: (i) how is the SARS-CoV-2 mutant and deletion spectrum composition in diagnostic samples, when examined at progressively lower cut-off mutant frequency values in ultra-deep sequencing; (ii) how the frequency distribution of minority amino acid substitutions in SARS-CoV-2 compares with that of HCV sampled also from infected patients. The main conclusions are the following: (i) the number of different mutations found at low frequency in SARS-CoV-2 mutant spectra increases dramatically (50- to 100-fold) as the cut-off frequency for mutation detection is lowered from 0.5% to 0.1%, and (ii) that, contrary to HCV, SARS-CoV-2 mutant spectra exhibit a deficit of intermediate frequency amino acid substitutions. The possible origin and implications of mutant spectrum differences among RNA viruses are discussed.

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Quantitative measures of within-host viral genetic diversity

Cited by 12 publications

References 43 publications

SARS-CoV-2 Point Mutation and Deletion Spectra and Their Association with Different Disease Outcomes

SARS-CoV-2 Point Mutation and Deletion Spectra and Their Association with Different Disease Outcomes

V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation

SARS-CoV-2 Mutant Spectra at Different Depth Levels Reveal an Overwhelming Abundance of Low Frequency Mutations

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