Dataset Information

Study on SARS-CoV-2 strains in Iran reveals potential contribution of co-infection with and recombination between different strains to the emergence of new strains.

ABSTRACT: We aimed to describe SARS-CoV-2 strains in Iranians from nine distributed cities infected during two months expanding late 2020 and early 2021 by genotyping known informative single nucleotide in five PCR amplicons. Two variants associated with haplotype H1 (clade G) and nine additional variants associated with other haplotypes were genotyped, respectively, in RNA isolates of 244 and 85 individuals. The variants associated with the H1a (GR) and H1b (GH) haplotypes were most prevalent, indicating a significant change in infection pattern with passage of time. The most important findings were that recombinant genomes and co-infection, respectively, were surmised in 44.7% and 12.9% of the samples extensively genotyped. Partners of many of the recombinations were relatively common strains. Co-existing viruses were among those currently circulating in Iran. In addition to random mutations, co-infection with different existing strains and recombination between their genomes may significantly contribute to the emergence of new SARS-CoV-2 strains.

SUBMITTER: Taghizadeh P

PROVIDER: S-EPMC8214199 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Study on SARS-CoV-2 strains in Iran reveals potential contribution of co-infection with and recombination between different strains to the emergence of new strains.

Taghizadeh Peyman P Salehi Sadegh S Heshmati Ali A Houshmand Seyed Massoud SM InanlooRahatloo Kolsoum K Mahjoubi Forouzandeh F Sanati Mohammad Hossein MH Yari Hadi H Alavi Afagh A Jamehdar Saeid Amel SA Dabiri Soroosh S Galehdari Hamid H Haghshenas Mohammad Reza MR Hashemian Amir Masoud AM Heidarzadeh Abtin A Jahanzad Issa I Kheyrani Elham E Piroozmand Ahmad A Mojtahedi Ali A Nikoo Hadi Razavi HR Rahimi Bidgoli Mohammad Masoud MM Rezvani Nayebali N Sepehrnejad Mehdi M Shakibzadeh Arash A Shariati Gholamreza G Seyyedi Noorossadat N MohammadSaleh Zahraei Seyed S Safari Iman I Elahi Elahe E

Virology 20210619

We aimed to describe SARS-CoV-2 strains in Iranians from nine distributed cities infected during two months expanding late 2020 and early 2021 by genotyping known informative single nucleotide in five PCR amplicons. Two variants associated with haplotype H1 (clade G) and nine additional variants associated with other haplotypes were genotyped, respectively, in RNA isolates of 244 and 85 individuals. The variants associated with the H1a (GR) and H1b (GH) haplotypes were most prevalent, indicating ...[more]

PMID: 34265628

Similar Datasets

Project description:BackgroundThe emergence of SARS-CoV-2 underscores the need to better understand the evolutionary processes that drive the emergence and adaptation of zoonotic viruses in humans. In the betacoronavirus genus, which also includes SARS-CoV and MERS-CoV, recombination frequently encompasses the receptor binding domain (RBD) of the Spike protein, which is responsible for viral binding to host cell receptors. In this work, we reconstruct the evolutionary events that have accompanied the emergence of SARS-CoV-2, with a special emphasis on the RBD and its adaptation for binding to its receptor, human ACE2.MethodsBy means of phylogenetic and recombination analyses, we found evidence of a recombination event in the RBD involving ancestral linages to both SARS-CoV and SARS-CoV-2. We then assessed the effect of this recombination at protein level by reconstructing the RBD of the closest ancestors to SARS-CoV-2, SARS-CoV, and other Sarbecoviruses, including the most recent common ancestor of the recombining clade. The resulting information was used to measure and compare, in silico, their ACE2-binding affinities using the physics-based trRosetta algorithm.ResultsWe show that, through an ancestral recombination event, SARS-CoV and SARS-CoV-2 share an RBD sequence that includes two insertions (positions 432-436 and 460-472), as well as the variants 427N and 436Y. Both 427N and 436Y belong to a helix that interacts directly with the human ACE2 (hACE2) receptor. Reconstruction of ancestral states, combined with protein-binding affinity analyses, suggests that the recombination event involving ancestral strains of SARS-CoV and SARS-CoV-2 led to an increased affinity for hACE2 binding and that alleles 427N and 436Y significantly enhanced affinity as well.ConclusionsWe report an ancestral recombination event affecting the RBD of both SARS-CoV and SARS-CoV-2 that was associated with an increased binding affinity to hACE2. Structural modeling indicates that ancestors of SARS-CoV-2 may have acquired the ability to infect humans decades ago. The binding affinity with the human receptor would have been subsequently boosted in SARS-CoV and SARS-CoV-2 through further mutations in RBD.

Project description:Effective systems for the analysis of molecular data are fundamental for monitoring the spread of infectious diseases and studying pathogen evolution. The rapid identification of emerging viral strains, and/or genetic variants potentially associated with novel phenotypic features is one of the most important objectives of genomic surveillance of human pathogens and represents one of the first lines of defense for the control of their spread. During the COVID 19 pandemic, several taxonomic frameworks have been proposed for the classification of SARS-Cov-2 isolates. These systems, which are typically based on phylogenetic approaches, represent essential tools for epidemiological studies as well as contributing to the study of the origin of the outbreak. Here, we propose an alternative, reproducible, and transparent phenetic method to study changes in SARS-CoV-2 genomic diversity over time. We suggest that our approach can complement other systems and facilitate the identification of biologically relevant variants in the viral genome. To demonstrate the validity of our approach, we present comparative genomic analyses of more than 175,000 genomes. Our method delineates 22 distinct SARS-CoV-2 haplogroups, which, based on the distribution of high-frequency genetic variants, fall into four major macrohaplogroups. We highlight biased spatiotemporal distributions of SARS-CoV-2 genetic profiles and show that seven of the 22 haplogroups (and of all of the four haplogroup clusters) showed a broad geographic distribution within China by the time the outbreak was widely recognized-suggesting early emergence and widespread cryptic circulation of the virus well before its isolation in January 2020. General patterns of genomic variability are remarkably similar within all major SARS-CoV-2 haplogroups, with UTRs consistently exhibiting the greatest variability, with s2m, a conserved secondary structure element of unknown function in the 3'-UTR of the viral genome showing evidence of a functional shift. Although several polymorphic sites that are specific to one or more haplogroups were predicted to be under positive or negative selection, overall our analyses suggest that the emergence of novel types is unlikely to be driven by convergent evolution and independent fixation of advantageous substitutions, or by selection of recombined strains. In the absence of extensive clinical metadata for most available genome sequences, and in the context of extensive geographic and temporal biases in the sampling, many questions regarding the evolution and clinical characteristics of SARS-CoV-2 isolates remain open. However, our data indicate that the approach outlined here can be usefully employed in the identification of candidate SARS-CoV-2 genetic variants of clinical and epidemiological importance.

Dataset Information

Study on SARS-CoV-2 strains in Iran reveals potential contribution of co-infection with and recombination between different strains to the emergence of new strains.

Publications

Study on SARS-CoV-2 strains in Iran reveals potential contribution of co-infection with and recombination between different strains to the emergence of new strains.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets