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High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7888613/ https://www.ncbi.nlm.nih.gov/pubmed/33596239 http://dx.doi.org/10.1371/journal.pone.0247115 |
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author | Bhoyar, Rahul C. Jain, Abhinav Sehgal, Paras Divakar, Mohit Kumar Sharma, Disha Imran, Mohamed Jolly, Bani Ranjan, Gyan Rophina, Mercy Sharma, Sumit Siwach, Sanjay Pandhare, Kavita Sahoo, Swayamprabha Sahoo, Maheswata Nayak, Ananya Mohanty, Jatindra Nath Das, Jayashankar Bhandari, Sudhir Mathur, Sandeep K. Kumar, Anshul Sahlot, Rahul Rojarani, Pallavali Lakshmi, Juturu Vijaya Surekha, Avileli Sekhar, Pulala Chandra Mahajan, Shelly Masih, Shet Singh, Pawan Kumar, Vipin Jose, Blessy Mahajan, Vidur Gupta, Vivek Gupta, Rakesh Arumugam, Prabhakar Singh, Anjali Nandy, Ananya P. V., Ragavendran Jha, Rakesh Mohan Kumari, Anupama Gandotra, Sheetal Rao, Vivek Faruq, Mohammed Kumar, Sanjeev Reshma G., Betsy Varma G., Narendra Roy, Shuvra Shekhar Sengupta, Antara Chattopadhyay, Sabyasachi Singhal, Khushboo Pradhan, Shalini Jha, Diksha Naushin, Salwa Wadhwa, Saruchi Tyagi, Nishu Poojary, Mukta Scaria, Vinod Sivasubbu, Sridhar |
author_facet | Bhoyar, Rahul C. Jain, Abhinav Sehgal, Paras Divakar, Mohit Kumar Sharma, Disha Imran, Mohamed Jolly, Bani Ranjan, Gyan Rophina, Mercy Sharma, Sumit Siwach, Sanjay Pandhare, Kavita Sahoo, Swayamprabha Sahoo, Maheswata Nayak, Ananya Mohanty, Jatindra Nath Das, Jayashankar Bhandari, Sudhir Mathur, Sandeep K. Kumar, Anshul Sahlot, Rahul Rojarani, Pallavali Lakshmi, Juturu Vijaya Surekha, Avileli Sekhar, Pulala Chandra Mahajan, Shelly Masih, Shet Singh, Pawan Kumar, Vipin Jose, Blessy Mahajan, Vidur Gupta, Vivek Gupta, Rakesh Arumugam, Prabhakar Singh, Anjali Nandy, Ananya P. V., Ragavendran Jha, Rakesh Mohan Kumari, Anupama Gandotra, Sheetal Rao, Vivek Faruq, Mohammed Kumar, Sanjeev Reshma G., Betsy Varma G., Narendra Roy, Shuvra Shekhar Sengupta, Antara Chattopadhyay, Sabyasachi Singhal, Khushboo Pradhan, Shalini Jha, Diksha Naushin, Salwa Wadhwa, Saruchi Tyagi, Nishu Poojary, Mukta Scaria, Vinod Sivasubbu, Sridhar |
author_sort | Bhoyar, Rahul C. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7888613 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-78886132021-02-23 High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing Bhoyar, Rahul C. Jain, Abhinav Sehgal, Paras Divakar, Mohit Kumar Sharma, Disha Imran, Mohamed Jolly, Bani Ranjan, Gyan Rophina, Mercy Sharma, Sumit Siwach, Sanjay Pandhare, Kavita Sahoo, Swayamprabha Sahoo, Maheswata Nayak, Ananya Mohanty, Jatindra Nath Das, Jayashankar Bhandari, Sudhir Mathur, Sandeep K. Kumar, Anshul Sahlot, Rahul Rojarani, Pallavali Lakshmi, Juturu Vijaya Surekha, Avileli Sekhar, Pulala Chandra Mahajan, Shelly Masih, Shet Singh, Pawan Kumar, Vipin Jose, Blessy Mahajan, Vidur Gupta, Vivek Gupta, Rakesh Arumugam, Prabhakar Singh, Anjali Nandy, Ananya P. V., Ragavendran Jha, Rakesh Mohan Kumari, Anupama Gandotra, Sheetal Rao, Vivek Faruq, Mohammed Kumar, Sanjeev Reshma G., Betsy Varma G., Narendra Roy, Shuvra Shekhar Sengupta, Antara Chattopadhyay, Sabyasachi Singhal, Khushboo Pradhan, Shalini Jha, Diksha Naushin, Salwa Wadhwa, Saruchi Tyagi, Nishu Poojary, Mukta Scaria, Vinod Sivasubbu, Sridhar PLoS One Research Article 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. Public Library of Science 2021-02-17 /pmc/articles/PMC7888613/ /pubmed/33596239 http://dx.doi.org/10.1371/journal.pone.0247115 Text en © 2021 Bhoyar et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Bhoyar, Rahul C. Jain, Abhinav Sehgal, Paras Divakar, Mohit Kumar Sharma, Disha Imran, Mohamed Jolly, Bani Ranjan, Gyan Rophina, Mercy Sharma, Sumit Siwach, Sanjay Pandhare, Kavita Sahoo, Swayamprabha Sahoo, Maheswata Nayak, Ananya Mohanty, Jatindra Nath Das, Jayashankar Bhandari, Sudhir Mathur, Sandeep K. Kumar, Anshul Sahlot, Rahul Rojarani, Pallavali Lakshmi, Juturu Vijaya Surekha, Avileli Sekhar, Pulala Chandra Mahajan, Shelly Masih, Shet Singh, Pawan Kumar, Vipin Jose, Blessy Mahajan, Vidur Gupta, Vivek Gupta, Rakesh Arumugam, Prabhakar Singh, Anjali Nandy, Ananya P. V., Ragavendran Jha, Rakesh Mohan Kumari, Anupama Gandotra, Sheetal Rao, Vivek Faruq, Mohammed Kumar, Sanjeev Reshma G., Betsy Varma G., Narendra Roy, Shuvra Shekhar Sengupta, Antara Chattopadhyay, Sabyasachi Singhal, Khushboo Pradhan, Shalini Jha, Diksha Naushin, Salwa Wadhwa, Saruchi Tyagi, Nishu Poojary, Mukta Scaria, Vinod Sivasubbu, Sridhar High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing |
title | High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing |
title_full | High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing |
title_fullStr | High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing |
title_full_unstemmed | High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing |
title_short | High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing |
title_sort | high throughput detection and genetic epidemiology of sars-cov-2 using covidseq next-generation sequencing |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7888613/ https://www.ncbi.nlm.nih.gov/pubmed/33596239 http://dx.doi.org/10.1371/journal.pone.0247115 |
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