Since 2006, there has been an explosion of new methods, techniques, and protocols for the examination of virtually any question in basic genetics or clinical research involving nucleic acid. Although now almost a decade old, the term next-generation sequencing remains the popular way to describe very-high-throughput sequencing methods that allow millions to trillions of observations to be made in parallel during a single instrument run. In 2006, second- and third-generation sequencing techniques began to emerge that permitted an unbiased means to examine billions of templates of DNA and RNA. Between 20, microarrays offered the first genome-scale parallel analysis of DNA and RNA. In the mid-to-late 1990s, microarrays were developed as highly parallel assays to measure RNA and DNA ( 91, 107). The progression from the discovery of the structure of DNA to the ability to sequence it as a routine assay has had several inflection points. DNA sequence has even been proposed as a highly efficient storage mechanism for large-scale data ( 22). Dozens of next-generation sequencing companies and technologies have been created, and the corresponding field of bioinformatics has exploded as a major scientific and training discipline. Since then, genomics has evolved at an amazing pace. The development of the polymerase chain reaction ( 103, 104), the widespread availability of high-quality nucleic acid–modifying enzymes, and the development of fluorescent automated DNA sequencing enabled the Human Genome Project to deliver the first draft of the human genome sequence in 2001 ( 64, 123) and the first completed draft three years later ( 54). As with many technologies, advances across multiple fields were brought together to achieve routine sequencing at the genome scale. Since the fundamental discovery of the structure of DNA ( 128) and the pioneering development of methods to detect the sequence of DNA bases by foundational approaches such as Maxam & Gilbert's technique ( 76) and Sanger sequencing ( 106), the field of DNA sequencing has rapidly evolved in capacity, capability, and applications.
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