The BBC ran an article a few weeks ago on the possibility of performance enhancing genetics: think Team BMC Genomics! The piece has an interview with Dr Philippe Moullier from INSERM in Nantes, he was part of a group that published a paper describing "Neo-organ" gene therapy treatment of neuromuscular diseases by the introduction of the erythropoietin gene into mice.
For those of you that easily forget: EPO has a rather bad rap in cycling, just ask the UCI or Lance Armstrong!
|Adding EPO to you, and detection with qPCR|
Dr Moullier is part of another team that published a real-time PCR method to detect the EPO-transgene in the presence of endogenous sequences: Longevity of rAAV vector and plasmid DNA in blood after intramuscular injection in nonhuman primates: implications for gene doping. Unfortunately any cycling team with the millions of dollars needed to start a GM program can probably design their way around such tests. In the same paper they showed that intramuscular (IM) injection of an EPO plasmid led to detectable levels of DNA in the blood and a "significant, but not life-threatening, increase in haematocrit". The DNA was rapidly eliminated, but the plasmid genomes can persist for several months in WBCs. RO Snyder at the University of Florida, who led the work, has uploaded some slides from the 2013 Gene and Cell Doping Symposium in Beijing. So all this looks possible.
What's this got to do with RNA-seq: why aim to detect a single gene product when athletes can find ways around the tests. Lance Armstrong was not overly sophisticated in his approach, and athletes have more to gain personally than the testing organisations so are probably quite motivated put some effort into their doping.
Instead of the single gene or metabolite test why not try an experiment comparing groups of doping vs non-doping athletes and monitor their blood-based gene expression levels over time. The aim would be to find a gene expression signature for doping in general, or at least for a specific class of doping; EPO vs Steroids for instance.