bioRxivGenomicsPreprint
HiDRA-seq: High-Throughput SARS-CoV-2 Detection by RNA Barcoding and Amplicon Sequencing
Emilio YángüeziD, Griffin W White, Susanne KreutzeriD, Lennart OpitziD, Lucy PovedaiD, Timothy SykesiD, Maria Domenica Moccia, Catharine AquinoiD, Ralph SchlapbachiD
Abstract
The recent outbreak of a new coronavirus that causes a Severe Acute Respiratory Syndrome in humans (SARS-CoV-2) has developed into a global pandemic with over 6 million reported cases and more than 375,000 deaths worldwide. Many countries have faced a shortage of diagnostic kits as well as a lack of infrastructure to perform necessary testing. Due to these limiting factors, only patients showing symptoms indicating infection were subjected to testing, whilst asymptomatic individuals, who are widely believed to be responsible for the fast dispersion of the virus, were largely omitted from the testing regimes. The inability to implement high throughput diagnostic and contact tracing strategies has forced many countries to institute lockdowns with severe economic and social consequences. The World Health Organization (WHO) has encouraged affected countries to increase testing capabilities to identify new cases, allow for a well-controlled lifting of lockdown measures, and prepare for future outbreaks. Here, we propose HiDRA-seq, a rapidly implementable, high throughput, and scalable solution that uses NGS lab infrastructure and reagents for population-scale SARS-CoV-2 testing. This method is based on the use of indexed oligo-dT primers to generate barcoded cDNA from a large number of patient samples. From this, highly multiplexed NGS libraries are prepared targeting SARS-CoV-2 specific regions and sequenced. The low amount of sequencing data required for diagnosis allows the combination of thousands of samples in a sequencing run, while reducing the cost to approximately 2 CHF/EUR/USD per RNA sample. Here, we describe in detail the first version of the protocol, which can be further improved in the future to increase its sensitivity and to identify other respiratory viruses or analyze individual genetic features associated with disease progression.
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