About: High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next generation sequencing

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About: High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next generation sequencing Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next generation sequencing
Creator	Gupta, Rakesh Sekhar, Chandra Gupta, Vivek Kumar, Sanjeev Scaria, Vinod Das, Jayashankar Jain, Abhinav Arumugam, Prabhakar Bhandari, Sudhir Bhoyar, Rahul Chattopadhyay, Sabyasachi Faruq, Mohammed Gandotra, Sheetal Imran, Mohamed Jha, Diksha Jha, Rakesh Jolly, Bani Jose, Blessy Kumar Divakar, Mohit Kumar, Vipin Kumar, Anshul Kumari, Anupama Lakshmi, Juturu Mahajan, Shelly Mahajan, Vidur Masih, Shet Mathur, Sandeep Mohanty, Jatindra Nandy, Ananya Naushin, Salwa Nayak, Ananya Pandhare, Kavita Poojary, Mukta Pradhan, Shalini Raghavendran, P Ranjan, Gyan Rao, Vivek Reshma, Betsy Rojarani, Pallavali Rophina, Mercy Roy, Shuvra Sahlot, Rahul Sahoo, Maheswata Sahoo, Swayamprabha Sehgal, Paras Sengupta, Antara Sharma, Disha Sharma, Sumit Singh, Anjali Singh, Pawan Singhal, Khushboo Sivasubbu, Sridhar Siwach, Sanjay Surekha, Araveti Tyagi, Nishu Varma, Narendra Wadhwa, Saruchi
Source	BioRxiv
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 for 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 detection of SARS-CoV-2, with an additional advantage of enabling genetic epidemiology of SARS-CoV-2.
has issue date	2020-08-10(xsd:dateTime)
bibo:doi	10.1101/2020.08.10.242677
has license	biorxiv
sha1sum (hex)	4ae2f596199dc5eadf7f7d8cb8c2a1796c24bdb9
schema:url	https://doi.org/10.1101/2020.08.10.242677
resource representing a document's title	High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next generation sequencing
schema:publication	bioRxiv
resource representing a document's body	covid:4ae2f596199dc5eadf7f7d8cb8c2a1796c24bdb9#body_text
is schema:about of	named entity 'PAN' named entity 'DETECT' named entity 'USED' named entity 'CONCORDANCE' named entity 'COULD BE' named entity 'SENSITIVE' named entity 'high-throughput' named entity 'SARS-CoV-2' named entity 'global pandemic' named entity 'PCR' named entity 'clades' named entity 'SARS-CoV-2' named entity 'genetic epidemiology' named entity 'evolution' named entity 'SARS-CoV-2' named entity 'phylogenetic network' named entity 'France' named entity 'Global Outbreak' named entity 'genome' named entity 'medical support' named entity 'CSIR' named entity 'genomes' named entity 'quality assessment' named entity 'genomes' named entity 'SARS-CoV-2' named entity 'epidemic' named entity 'genome sequence' named entity 'exonic'

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