In the years following the completion of the first human genome, references were already being made to the potential impact of the “$1000 genome”. Even before extensive data was available to support the hypothesis, the idea that personal genome sequencing could be used to improve medical care had already taken root. With the subsequent development of next generation DNA sequencing (NGS) machines, a conceivable path to this sort of holy grail for biomedical science had been opened, while the constant and exponential reduction in sequencing costs further fostered this objective.
Fast forward to 2021, and there are now multiple private companies offering whole genome sequencing for far less than $1000 and a competitive market pushing these prices towards $100. All signs indicate that we have reached — and even passed — the era of the $100 genome, but does this reflect reality? A 2020 study by Schwarze et al. looking at the comprehensive cost of clinical sequencing, including clinical data analysis, demonstrates that real cost is far more than commonly quoted. Using real world data from a National Health Service (NHS) laboratory in the United Kingdom, their work shows that the full cost is closer to $5,700/cancer genome and ~$3,900/genome for rare disease trios. These values are similar to earlier published studies (although somewhat lower) and interestingly, while the sequencing reagents account for the large majority of cost (79-76%), the clinical bioinformatics is the second main cost. This represents 11% of the cost for cancer samples and 7.3% for rare diseases. This means that all other associated costs including samples processing, library construction and QC, data reporting and data archiving make up the remaining cost.
This study, which was based on standardized sequencing of hundreds of patient genomes, clearly demonstrates that even today, the actual comprehensive costs for genome sequencing are well about the $1000 genome target. Moreover, while the cost of sequencing reagents will continue to decrease, the analysis of personal cancer genomes likely will not, due to the virtually infinite combinations of mutations may drive a cancer to develop. In this scenario, as the bioinformatics-related percentage of the total cost continues to increase over time, more attention will certainly be drawn to the development of new methods and resources to deal with the complex biological reality of understating cancer genetics.