
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>We are in the midst of a time of great change in genetics that may dramatically impact human biology and medicine. The completion of the human genome project,1,2 the development of low cost, high-throughput parallel sequencing technology, and large-scale studies of genetic variation3 have provided a rich set of techniques and data for the study of genetic disease risk, treatment response, population diversity, and human evolution. Newly-developed sequencing instruments now generate hundreds of millions to billions of short sequences per run, allowing for rapid complete sequencing of human genomes. These technological advances have facilitated a precipitous drop (Figure 1) in the cost per base pair of DNA sequenced. To capitalize on the potential of these technologies for research and clinical applications, translational scientists and clinicians must become familiar with a continuously evolving field. In this review we will provide a historical perspective on human genome sequencing, summarize current and future sequencing technologies, highlight issues related to data management and interpretation, and finally consider research and clinical applications of high-throughput sequencing, with specific emphasis on cardiovascular disease. Open in a separate window Figure 1 Sequencing milestones, costs, and output since completion of the human genome project. Note logarithmic scale for sequencing costs and bases produced per sequence run.
Quality Control, Genotype, Genome, Human, Genetic Variation, High-Throughput Nucleotide Sequencing, Humans, Sequence Analysis, DNA, Polymorphism, Single Nucleotide
Quality Control, Genotype, Genome, Human, Genetic Variation, High-Throughput Nucleotide Sequencing, Humans, Sequence Analysis, DNA, Polymorphism, Single Nucleotide
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 73 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
