Giving Compass' Take:

· Despite making advances in gene sequencing allowing scientist to monitor the COVID-19 pandemic, lack of data sharing leaves gaps in our understanding of the virus.

· How can scientists effectively share their research with others? Why is data sharing important in advancing testing and treatment options? 

· Here are a few suggestions and recommendations for donors looking to help during the Coronavirus pandemic.

When the new coronavirus (formally known as SARS-CoV-2) was identified in China in January, scientists around the world were ready to respond. The virus’s entire genetic makeup, or genome, was published online within days. By comparison, during the SARS coronavirus outbreak in 2003, this took almost three months, after the disease was originally blamed on chlamydia.

Advances in the technology have brought down the cost of gene sequencing significantly and the machines are now small enough to fit in the palm of your hand. This has made it easier for a large number of samples to be sequenced around the world.

‘You can see from the sequences how the virus spreads, the speed at which it's spreading and estimate the number of people that are infected. As we get more and more sequences, the more and more accurate the numbers are,’ said Professor Anne-Mieke Vandamme from KU Leuven, Belgium.

Next-generation sequencing, or NGS, can generate enormous amounts of data, and the challenge becomes finding ways to analyse it properly.

In 2015, Prof. Vandamme led a project called VIROGENESIS to develop new tools to help analyse and interpret the data that comes from sequencing, particularly for laboratories that were not used to dealing with sophisticated genetic analysis.

‘When we were doing the project, there were only mainly research labs that had NGS. Now everyone has NGS,’ she said.

One of the tools developed, called Genome Detective, can take the raw data from the sequencing machine, filter out results from non-viruses, piece together the genome and use that to identify the virus. It does not rely on any prior guesses or hypotheses, so it can even identify viruses that have not been seen before. This was used to confirm the first case of COVID-19 in Belgium, identifying it as a SARS-related coronavirus.

Read the full article about data and COVID-19 at The Naked Scientist.