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Once upon a time, sequencing the human genome took tens of millions of dollars and a warehouse full of DNA sequencing machines that analyzed samples throughout the day, and year after year. Now, less than a decade later, the same human genome sequence — the order of nucleotides or “letters” — can be generated using a single machine that analyzes samples for a few days, and for about 100-fold lower cost. The ability to sequence DNA faster and more cheaply comes from recent technological advancements, representing the most significant technological metamorphosis in the history of modern genetics.

Deriving the sequence of a genome is only the first step in understanding what it does. Once you know the sequence, the challenge is to identify the meaning therein by finding the genes and determining their functions. In a sense, sequencing a genome is writing down the words in which the book of life is written, and identifying the genes is learning the meanings of those words. Of course, we still need to how the genome controls the biology of the organism. To do this, scientists work to identify all the genes, their variant forms and changing levels of activity. The process is known as genome annotation and has traditionally been done by heavily computational means.

Advances in DNA sequencing technology have driven the decoding of genomes, and now scientists can also use the technology to directly study the genes themselves. As Chad Nusbaum, co-director of the ӳ����ý’s Genome Sequencing and Analysis Program, explained at the recent Beyond the Genome conference in Boston, scientists are now able to use RNA sequence ‘evidence’ to precisely and comprehensively identify genes. This is done by taking the RNA made from active genes, converting it to DNA for sequencing, sequencing a lot of it, and then laying the reads back on the genome to show where the genes are.

He said, “These technologies are putting us in the position to talk about the content of the genome. We can use these technologies to identify genes.” However, Chad said that the ӳ����ý is going to continue to improve these applications by devising ways to confront the remaining challenges, such as the need to analyze lots of samples, including those that are low-quality. “Going forward, the ӳ����ý wants to do a ton of things,” he said. “So, we’re scaling up.” In other words, keep your eyes peeled for new DNA sequencing applications and a better understanding of a genome’s content.

Stay tuned for more of our coverage from the recent in Boston.