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Next Generation Genome Sequencing Key to Strong UK Bioscience Research Base
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Next Generation Genome Sequencing Key to Strong UK Bioscience Research Base

Next Generation Genome Sequencing Key to Strong UK Bioscience Research Base
News

Next Generation Genome Sequencing Key to Strong UK Bioscience Research Base

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A strong and well-coordinated community of researchers with skills and training in mathematics and computing will be crucial. And a concerted effort to develop software for data analysis is also vital to ensure that the best possible value is drawn from this capability in the UK.

New fast machines for sequencing genomes have made it possible to reduce the time required to complete a sequence by several orders of magnitude. The first human genome sequence took years to complete, whereas it is now possible to sequence an entire human genome in under a week.

BBSRC's review of the potential impacts that these technologies can have on research in biosciences shows that genome sequencing has become an efficient and commonly-used tool, which is increasingly affordable.  

There are new areas of research opening up as a result. For example, it is possible to look at genomes on a population level - we can sequence and compare the genomes of many individuals from the same species, which is a powerful way of identifying any genetic basis for useful or desirable traits as well as potential vulnerabilities and weaknesses. This will be particularly important in crop improvement research in the coming years as we face the need to grow more food in the context of a changing environment.  

Professor Ottoline Leyser, University of Cambridge, who chaired the review said "We have reached the stage where, in many cases, genome sequencing can be viewed as a tool rather than as a project in itself. It is useful right across biology, and has huge potential to contribute to global issues that require solutions based on excellent bioscience research, such as food security, biofuels and healthy ageing.  

"At present, supply and demand for next generation sequencing access are balanced but we must monitor this very carefully to ensure that this remains the case. The review suggests that having a small number of centralised resources, such as The Genome Analysis Centre, enables us to meet demand with a great degree of flexibility - we can expand only as much as we need to at any one time in response to the needs of the whole community. But some smaller, specialized local provision is also likely to be important."  

Data storage and availability in the UK is developing well - for example, via the ELIXIR data infrastructure project, where BBSRC leads the funding strategy. And again, this must be monitored closely as volumes of data increase.  

There is also a need for software development such that researchers are able to use the data more easily.  

"To derive maximum value from current and future investments in genome research, we need to ensure coordination across the UK community. This will facilitate knowledge exchange; help to establish best practice; and ensure efficient use of technological and other resources. And BBSRC and TGAC are in a good position to facilitate this," added Professor Leyser. "It is also clear that training researchers in mathematics and computing so that they are able to work easily with large datasets from day one of their careers is becoming an essential part of maintaining the UK's capability in bioscience research," she said.  

Professor Douglas Kell, Chief Executive, BBSRC said "This review is very useful for BBSRC. It offers us the opportunity to ensure that there is effective uptake of this technology across our community. We can also see areas where more work and investment may be required. These may include training and skills development for researchers and also the development of new bioinformatics tools to deal with the huge volumes of data that is being produced; we often talk about the risk of 'data deluge' and this is a real life example where we can make a difference to ensure value is extracted from large data sets."

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