High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing
0301 basic medicine
Genotyping
Genotype
Epidemiology
Science
India
Genome, Viral
Coronavirus Disease 2019 Research
FOS: Health sciences
Diagnostic Methods for COVID-19 Detection
Sensitivity and Specificity
Gene
Computational biology
03 medical and health sciences
Virology
Health Sciences
Concordance
Genetics
Humans
DNA sequencing
Pandemics
Biology
Internal medicine
Phylogeny
Multiplex
Molecular Epidemiology
SARS-CoV-2
Q
R
COVID-19
High-Throughput Nucleotide Sequencing
Gastrointestinal Viral Infections and Vaccines Development
3. Good health
Infectious Diseases
FOS: Biological sciences
Molecular epidemiology
RNA, Viral
Medicine
Multiplex Polymerase Chain Reaction
Research Article
DOI:
10.1371/journal.pone.0247115
Publication Date:
2021-02-17T19:50:37Z
AUTHORS (57)
ABSTRACT
The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance, and determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding, and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for the detection of SARS-CoV-2, with an additional advantage of enabling the genetic epidemiology of SARS-CoV-2.
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