Maximum Data with Minimum Costs
The research community has obviously benefited from the competitive environment among the NGS vendors as they’ve driven down the cost of sequencing. Fierce competition continues to push the current high-throughput platforms to generate more data for less money.
For example, Illumina’s HiSeq® machine can generate 600 Gb—that’s enough data to sequence six whole human genomes, 60 human exomes, or 200+ RNA samples in a single run.
Lowering the “per Gb cost” while keeping error rates to under 1% are the key metrics that have been driving this industry. The most competitive instruments today have lowered the cost per Gb by becoming massively parallel, with as many as three billion sequences generated concurrently.
Output has also improved by increasing the read lengths of each run. While Sanger sequencing can generate reads of 1 kb or more, the high-throughput instruments of the past started out with reads as short as 25 bases. High-throughput NGS machines have steadily improved over the past few years, with read lengths reaching 150 bases.
While extremely successful, achieving the goals of “more data for less money” has not come without sacrifices. High-throughput sequencing machines are expensive and require long run times. Instruments with the highest output (and the lowest cost per Gb) are priced in the range of $600K to $700K.
While the cost per Gb is quite competitive, the minimum run cost for these machines is still several thousand dollars. And the longer read lengths have come at the expense of substantially longer run times, which now generally range from 6 to 11 days.
For researchers with large projects and big budgets, long runtimes and high minimum run costs aren’t such an issue. They’ve got enough samples to “feed the machine.” Projects with flexible timelines could possibly spare the additional time required to pool samples with other researchers to create a complete run, but researchers with smaller budgets may not have the capital to purchase an instrument of their own.
For those with time-sensitive projects, a quick turnaround is high priority. For example, researchers testing the quality of a library or new preparation methods with multiple iterations need results quickly. Clinicians dealing with patient samples (where sequencing results may be necessary for diagnoses or choosing treatment options) require results even faster.