Dataset Information

Epidemiological associations with genomic variation in SARS-CoV-2.

ABSTRACT: SARS-CoV-2 (CoV) is the etiological agent of the COVID-19 pandemic and evolves to evade both host immune systems and intervention strategies. We divided the CoV genome into 29 constituent regions and applied novel analytical approaches to identify associations between CoV genomic features and epidemiological metadata. Our results show that nonstructural protein 3 (nsp3) and Spike protein (S) have the highest variation and greatest correlation with the viral whole-genome variation. S protein variation is correlated with nsp3, nsp6, and 3'-to-5' exonuclease variation. Country of origin and time since the start of the pandemic were the most influential metadata associated with genomic variation, while host sex and age were the least influential. We define a novel statistic-coherence-and show its utility in identifying geographic regions (populations) with unusually high (many new variants) or low (isolated) viral phylogenetic diversity. Interestingly, at both global and regional scales, we identify geographic locations with high coherence neighboring regions of low coherence; this emphasizes the utility of this metric to inform public health measures for disease spread. Our results provide a direction to prioritize genes associated with outcome predictors (e.g., health, therapeutic, and vaccine outcomes) and to improve DNA tests for predicting disease status.

SUBMITTER: Rahnavard A

PROVIDER: S-EPMC8626494 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Epidemiological associations with genomic variation in SARS-CoV-2.

Rahnavard Ali A Dawson Tyson T Clement Rebecca R Stearrett Nathaniel N Pérez-Losada Marcos M Crandall Keith A KA

Scientific reports 20211126 1

SARS-CoV-2 (CoV) is the etiological agent of the COVID-19 pandemic and evolves to evade both host immune systems and intervention strategies. We divided the CoV genome into 29 constituent regions and applied novel analytical approaches to identify associations between CoV genomic features and epidemiological metadata. Our results show that nonstructural protein 3 (nsp3) and Spike protein (S) have the highest variation and greatest correlation with the viral whole-genome variation. S protein vari ...[more]

PMID: 34837008

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Project description:A detailed understanding of how and when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission occurs is crucial for designing effective prevention measures. Other than contact tracing, genome sequencing provides information to help infer who infected whom. However, the effectiveness of the genomic approach in this context depends on both (high enough) mutation and (low enough) transmission rates. Today, the level of resolution that we can obtain when describing SARS-CoV-2 outbreaks using just genomic information alone remains unclear. In order to answer this question, we sequenced forty-nine SARS-CoV-2 patient samples from ten local clusters in NW Spain for which partial epidemiological information was available and inferred transmission history using genomic variants. Importantly, we obtained high-quality genomic data, sequencing each sample twice and using unique barcodes to exclude cross-sample contamination. Phylogenetic and cluster analyses showed that consensus genomes were generally sufficient to discriminate among independent transmission clusters. However, levels of intrahost variation were low, which prevented in most cases the unambiguous identification of direct transmission events. After filtering out recurrent variants across clusters, the genomic data were generally compatible with the epidemiological information but did not support specific transmission events over possible alternatives. We estimated the effective transmission bottleneck size to be one to two viral particles for sample pairs whose donor-recipient relationship was likely. Our analyses suggest that intrahost genomic variation in SARS-CoV-2 might be generally limited and that homoplasy and recurrent errors complicate identifying shared intrahost variants. Reliable reconstruction of direct SARS-CoV-2 transmission based solely on genomic data seems hindered by a slow mutation rate, potential convergent events, and technical artifacts. Detailed contact tracing seems essential in most cases to study SARS-CoV-2 transmission at high resolution.

Project description:The emergence of new SARS-CoV-2 variants in Palestine highlights the need for continuous genetic surveillance and accurate screening strategies. This case series study aimed to investigate the geographic distribution and genetic variation of the SARS-CoV-2 Delta Variant in Palestine in August 2021. Samples were collected at random in August 2021 (n = 571) from eight districts in the West Bank, Palestine. All samples were confirmed as positive for COVID-19 by RT-PCR. The samples passed the quality control test and were successfully sequenced using the ARTIC protocol. The Delta Variant was revealed to have four dominant lineages: B.1.617 (19%), AY.122 (18%), AY.106 (17%), and AY.121 (13%). The study revealed eight significant purely spatial clusters (p < 0.005) distributed in the northern and southern parts of Palestine. Phylogenetic analysis of SARS-CoV-2 genomes (n = 552) showed no geographically specific clades. The haplotype network revealed three haplogroups without any geographic distribution. Chronologically, the Delta Variant peak in Palestine was shortly preceded by the one in the neighboring Israeli community and shortly followed by the peak in Jordan. In addition, the study revealed an extremely intense transmission network of the Delta Variant circulating between the Palestinian districts as hubs (SHR ≈ 0.5), with Al-Khalil, the district with the highest prevalence of COVID-19, witnessing the highest frequency of transitions. Genetic diversity analysis indicated closely related haplogroups, as haplotype diversity (Hd) is high but has low nucleotide diversity (π). However, nucleotide diversity (π) in Palestine is still higher than the global figures. Neutrality tests were significantly (p < 0.05) low, including Tajima's D, Fu-Li's F, and Fu-Li's D, suggesting one or more of the following: population expansion, selective sweep, and natural negative selection. Wright's F-statistic (Fst) showed genetic differentiation (Fst > 0.25) with low to medium gene flow (Nm). Recombination events were minimal between clusters (Rm) and between adjacent sites (Rs). The study confirms the utility of the whole genome sequence as a surveillance system to track the emergence of new SARS-CoV-2 variants for any possible geographical association and the use of genetic variation analysis and haplotype networking to delineate any minimal change or slight deviation in the viral genome from a reference strain.

Dataset Information

Epidemiological associations with genomic variation in SARS-CoV-2.

Publications

Epidemiological associations with genomic variation in SARS-CoV-2.

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