Sequencing Technologies – cheaper, faster and better
Meeting Room 2, CMS
Obtaining the sequence of the three-billion letters human genome has been one of the biggest enterprises in the history of science. It involved a remarkable organization of scientists, policy-makers and funding agencies from across the globe but it also marked the beginning of a new era in molecular biology characterized by a revolution in data generation. As in other areas of science technological advances combined with the availability of high-performance computers have made possible to collect, process and analyse biological data at a rate that have revolutionised the life sciences. One example is the advent of the next generation sequencing technologies that has completely transformed the landscape of genomics. These technologies introduced massive parallel platforms that supported by advanced software systems generate in the order of billions of nucleotides per run of the instruments. Today, any laboratory equipped with the latest technologies can produce in few days as much sequence data as the Human Genome Project did and at a fraction of the cost. More excitingly these new technologies have opened up the possibilities for novel applications that traditionally were outside the scope of sequencing. One example is the study of environmental samples such as microbiomes and soil; or the use of deep sequencing for the analysis of expression data. As sequencing becomes cheaper and more accurate we will soon be able to explore genetic information at a single-cell level. The so-called third generation technologies will implement single-molecule sequencing directly reducing the operation time and potentially increasing the accuracy of the instruments output. Another important legacy from the Human Genome Project is the recognition that sharing and making the data available prior to publication can speed science and promote collaborations (Toronto Statement). The prospects of a sustained increase in sequencing capacity combined with a well-established model for data sharing places genomics at the forefront of the data-driven science revolution. In this tutorial we will review the progress of the sequencing technologies since the early days of the Human Genome Project with a critical view on the challenges ahead.