 Genome project actually started. I was a postdoctoral fellow in the laboratory of Dr. Maynard Olson. I was actually doing that postdoctoral fellowship as part of a residency in clinical pathology, and that was the time that this new field of genomics was named and first was being discussed, and the thing that was catapulting that discussion forward was this audacious idea of should we sequence the human genome. And next thing you know, they got funded to be one of the first genome centers in the United States participating in the Human Genome Project, and Maynard turned to me and said, you're going to run this project. My role, when the gun went off in the Human Genome Project, was to be responsible for mapping one of the 24 human chromosomes. In retrospect, it was a bizarre way to organize the effort, but it's a way that made sense that the time, when you sort of reflect back on a quarter century since the launch of the Human Genome Project, it's easy to remember the scientific accomplishments of the genome project because we see them every day. You can open up a browser and look at the human genome sequence, and you can't deny that somebody historically had to go back and figure out what the order of those three billion letters were, just like we could marvel at a world map and say somebody figure this out for the first time. What sometimes doesn't get said enough is that beyond these immediate scientific products of the Human Genome Project have been some incredibly important lessons. And I think those lessons are an key part of the legacy of the Human Genome Project. And Francis Collins and Jim Watson agree with me. When the genome project was being contemplated in the 1980s, part of the resistance, actually a lot of the resistance to it, was that it was clear it was going to be big science. It was going to be consortium science. It was going to be a lot of partnerships. And it was going to be international. And that ran against the typical culture of the way biomedical research was done. I think if we fast forward to 25 years later, where we are now, and we think about the idea of big science, it's sort of very comfortable, I think. In the issue of nature, that our common appears just by coincidence, actually, appears a couple of papers that are sort of the final major papers of the 1000 Genomes Project, which is an excellent example of consortium-based science that followed the Human Genome Project. 1000 Genomes Project aims to catalog and make available to the scientific community an important resource, that resource being, basically, information about where our genome sequence differs among different people. So looking at genomic variants, where the spelling is different at particular locations. So when I say that the Genome Project made some major cultural changes in science, I think high on that list, which is one of the lessons we speak about, and I think frequently gets mentioned, is in the whole arena of data sharing. Purpose of the Genome Project was to create a resource that people could capitalize on to advance knowledge of human biology and eventually better understanding of human health and disease. That data needed to get out quickly. And so that had to break the cultural norm of generate data, publish on it, release the data. Data sharing, being a key part of what the Genome Project did, wasn't going to end when the Genome Project ended 12 years ago. Rather, it was very clear this just sort of set the stage for new cultural norms. And now most recently, the NIH put into place a new policy that's now being implemented over the next year or so that speaks to all genomic data being generated across the NIH, all institutes, and embracing much more sharing orientation to genomic data. And we won't stop there. So let's move beyond genomics. There's lots of discussion about data sharing in other arenas as well at NIH in terms of NIH-funded research. I repeatedly joke about the fact that when the Genome Project began, fundamentally those of us working on it didn't really know what we were doing. We had some general ideas, but we didn't have a long range view of exactly what was going to be needed. And an example of that is data analysis. So the lesson learned in that case was you actually have to think about data analysis early in the project. You tend to think about data generation because that's the exciting stuff. Let's generate the data and you tend to say, oh, eventually we'll analyze it. I think a lot of the big projects that have been started in recent years and are even being planned now, the lesson learned is you've got to be planning for data analysis at the very beginning, the same time you're thinking about data generation. There are probably multiple examples that you can immediately point to. I would say the most recent one would be the Precision Medicine Initiative where it's very clear that is going to be a very data intensive effort involving very different types of data, everything from electronic health record data to genomic data to physiological data collected by sensors that people might wear, mobile sensors. And so even as the project is being mapped out, even thinking about how it's going to be organized and strategically put together, thinking about how exactly is that data going to be organized and analyzed so that when we actually have the data we'll be much better poised to take advantage of it. So when you trace the successes in the Human Genome Project, almost every one of them are tied to technological advances that took place. It happened early on. We were just mapping the human genome and figuring out how to just get it ready for sequencing. And through a series of technical innovations, one on top of the next, on top of the next, on top of the next, before you know it, it was sort of a revolutionary advance in our ability to sequence DNA, even though it was still the same fundamental method that was being used. And when we realized that, it was very clear it was time to sequence the human genome, and we did. But the point was, from the beginning, there was this constant investment in technology development, technology refinement, and that was absolutely key and was one of the important lessons learned. A good recent example that's actually not genomics in nature is the Brain Initiative that NIH launched a few years ago, where the major focus initially actually is on technology development and to really get better and better methods that can be eventually scaled up to do the kind of very complicated work they want to do to attain the goals of the Brain Project and figure out how the human brain actually works. So one of the other novel aspects of the Human Genome Project was the idea that, in addition to doing the science and thinking about the scientific advances, is that in parallel, consider what the societal implications of that work are going to be. Jim Watson deserves the credit of declaring early on, actually very early on in the Human Genome Project, that we should be studying the ethical, legal, and social implications of the genomic advances that will take place during the project. It was sort of branded LC, ELSI, ethical, legal, and social implications. So the LC research program was launched within our institute, but also similar studies were launched by other funding agencies, including funding agencies in other countries that were participating in the Human Genome Project. And I think that was very different than anything that had ever been done before. It ended up being probably like the largest block of bioethics research ever created. It actually eventually led to the U.S. Congress requesting that our institute, in perpetuity in essence, should dedicate about five percent of its research dollars for studying LC-type issues, which we do. And again, another one of these lessons many issues around the right protections to put into place so that individuals participating in research are properly protected. There's a guiding framework for this in the United States, something called the Common Rule, which has been in place for a number of years. And now there are revisions to the Common Rule being contemplated, in part because we realize that science has changed, and societal attitudes have changed, and our approach to protection of research participants might need to change. And so we're now in a deliberative process of considering changes to the Common Rule. So when the Genome Project was being actively discussed even before it was launched, I think a lot of its critics would say, you got to be kidding. First of all, you probably can't do this. It's not feasible. It's going to be too expensive. And you really don't know what you're doing. And I've seen that play out on multiple projects since then, and even today in contemplating projects like the Precision Medicine Initiative here in the United States, where the goal just seems so incredibly big and audacious. And there's so many details that we can't even articulate. And yet, if you wait until you have the perfect plan, you're probably waiting too long. And so I think one of the, another lesson of the Human Genome Project is to be audacious. But at the same time, you've got to be flexible. And you also just have to immediately acknowledge that you have the great plan to get something out of the gates, but that plan, within a matter of days or weeks or months, needs to be revised. And I think that willingness to make revisions to your audacious plan is a key component to being successful. When I got involved in genomics as a resident in clinical pathology, now 27 years ago, and I then got involved in the Genome Project on day one now 25 years ago, it made some logical sense. To me, I don't pretend for a minute to have some grand vision as a young resident in clinical pathology. But I did sort of see connections between diagnostic medicine, which is what clinical pathologists do, and thinking about how fundamental knowledge of the human blueprint might improve our ability to better diagnose disease and help people monitor their health. That there was fundamental connections I could make at a conceptual level. But I would never have believed 25 years ago that within my career, maybe not even in my life, I would see true changes to the practice of medicine. And now 25 years later, I'm seeing them. I'm seeing direct connections between the fruits of the Human Genome Project and the incredible progress that's been made in genomics in the last 12 years, since the end of the Genome Project, and actually changing how we practice medicine. That doesn't mean medicine's being turned upside down. We just have really vivid examples so far in cancer and microbiology and prenatal testing and rare diseases. But I do think that some of the things that we immediately see on the near horizon will absolutely happen. And I do believe that there'll be some major surprises, because there certainly have been over the past quarter century some remarkable surprises.