 Okay. So we're going to pick up with a few themes, more extended outlook from the program, right? So we've talked to our R01 collaborators this morning. Now we're going to hear a little bit about the future. We're going to hear a little bit more about data integration. We're going to hear a little bit more about some stuff we don't do, which is big data, lots of genomes, lots of genotypes, gene interaction type stuff. So Carolyn's going to talk about strategic planning and thoughts and ideas of genome. Hi, everybody. For those of you who don't know me, I am the division director for the Division of Genome Sciences at the National Human Genome Research Institute. I'm going to talk to you guys kind of quickly through just an update on where we are at NHGRI in terms of our current strategic planning, which we hope to publish in 2020, which is why we call it our 2020 vision for genomics. One of my colleagues doesn't like this as our imagery because she says it makes us look like we're the National Eye Institute, but we stuck with it anyways because we like a good pun. But I'm certainly happy when we get into some of the discussion talk to talk about things a little bit more broadly than maybe just NHGRI, and I'll discuss a little bit about what I mean by that distinction as part of this overview. So the National Human Genome Research Institute is one of the 27 institutes and centers at NIH, and our broad vision is to improve the health of all humans through advances in genomic research. We really see genomics transforming our understanding of human health and disease. I certainly don't need to sort of share that this much with this audience, but we really sort of see the way to think about empowering and expanding on the field of genomics, thinking about the resources, the methods, the research from a generalizable perspective needed to do basic research in genomics and also transfer that to clinical settings. Just a little bit of internal structure. Some of this I think is just, this is just my sort of outreach advertising to remind you all that in addition to COMP, you can come apply for grants to NHGRI at any time and to help orient you a little bit in terms of how you do that. We have three primary divisions. Colin and I are both in the Division of Genome Sciences, which is really focused on those foundational resources, tech dev, experimental approaches, et cetera, to think about basic research and facilitate research on the function of the genome and human health and disease. Christine is actually a member of our Division of Genomic Medicine, which is really looking at how do we move genomic technologies to impact clinical applications for care and how do we think about the research needed to support, identify and advance approaches of the use of genomic data in the role of diagnosis, treatment and prevention. And finally, we actually have a congressional mandate to spend five percent of our extramural budget on ethical, legal and social implications or LC research. And that's housed in our Division of Genomes and Society, which really does research on societal issues relevant to genomics research. This is just a website to just remind people about research funding opportunities. I apologize, I started eating a piece of candy, which I shouldn't have done before talking. To talk about research, just to remind people about coming in to apply for it. I didn't pull up these two announcements. I probably should have two things that I want to make this group aware of, and you can find out more about this by going, you know, googling research funding opportunities in HDRI or talking to Colin, Christine or myself. One is we have a program for early stage and new investigators, people who have not yet received an R01, who have been actively involved in consortia, COMP would count. So if you have junior members in your group who have really been contributing in consortium activities and are ready to sort of have an independent R01 level approach, it's called our Genomic Innovator Award. It's an R35, it's a slightly different mechanism, but the idea and what we're trying to target is a recognition that sometimes people who do their sort of training post-doc time, junior time in a consortium work have trouble competing for a traditional R01 because they don't have those first author publications, et cetera, but we really see them as a key contributors to genomics. So they can be funded through our Genomic Innovator Award. We also have a program announcement out for variation, function and disease. Really looking at how can we understand the functional impact of genomic variation tying that to disease. It's just for, it's traditional R01s, R21s that get reviewed at CSR like everything else, but it's just highlighting NHGRI's interest in that area. I think some COMP investigators got some funding through that so you could talk to us about it or you have a successful grantee through that program who could also give you some tips. We have lots of other things we fund, lots of other areas to go to, but I just always want to sort of encourage people to think about NHGRI as a place for funding. So stepping away from that and coming back a little bit more to what are we doing with strategic planning. NHGRI has a long culture and history of being involved in strategic planning, going back to our origins coming out of the Human Genome Project. And so these papers here are really the strategic plans for the Human Genome Project itself, which from the period of 1991 to 2003 was pretty much synonymous with the activities that were happening at NHGRI originally as a center and then as an institute. Coming into the more recent years in, we published a strategic plan in 2003, the vision for the future of genomics research and then in 2011, charting a course for genomic medicine from base pairs to bed sides, which has really been where we lay out and define first once the Human Genome Project is done, where do we see ourselves going as an institute. And then in the 2011 plan, we really talked about this idea of how do we move to genomic medicine? How do we move from a research focused on understanding the structures of genomes through the biology of genomes, the biology of disease, and ultimately into advancing the science of medicine and inspire improving the effectiveness of health care? And that's the strategic plan we've been operating under since 2011. And so recognizing that that's now eight years old, we really sort of realized it's time to take another step and look at where should we be going, what should we be doing in genomics? As we think about our current role in genomics, I'm going to show a couple of different slides around this, but I think they're both important because they're really shaping some of how do we think about what should we be doing as genome in the context of where the field of genomics has gone. And so two relevant numbers, I'm going to show some other slides around this, but I think it's important to note is NHGRI is what Eric Green, my boss likes to call it as a small institute. I actually think we're a small, medium-sized institute, whether we're a large small institute or a small medium-sized can be up for debate, but we're not the Cancer Institute or Heart, Lung, and Blood or NIGMS. We only have 1.5% of the total NIH budget. That's still a very healthy budget. I don't want to say we don't have a healthy budget. But from that perspective, we're doing a small amount of it, and we actually only currently fund 15% of the awards coming out of NIH that are coded as human genomics. So even though we're the Genome Institute, we're not the primary funder of research in human genomics coming out of NIH. One of the ways that we sort of are looking at that as we think about this is looking at that as a trend over time. So at the time that the human genome era, as we call it, sort of the 1990 to 2003, we actually were funding greater than 95% of the human genome research from NHGRI. But as you look over the time period of our various strategic plans going forward, it's been a pretty steady decline. And so the fact that we're projecting at the time that our plan comes out in 2020 that we're probably going to be funding about 10% of the total genomics. But you can flip that around and put a more positive spin on it and say that what this really demonstrates is the dissemination of genomics into all sorts of areas and fields across relevant to the categorical, which is what we sometimes call the disease-specific ICs, relevant to even some of the, you know, Nibbib and some of the other ICs that aren't disease-focused. There's really just been an uptake of genomics. Our budget has stayed steady over time. So as this increase happens, that means that there's more and more funding going broadly into human genomics across all of NIH. And coming along with that is a lot of interest in genomics across NIH. One of the things relevant to this room is that's part of why we feel pretty confident that there's interest across NIH in activities related to COMP in this current climate. No promises, but definitely interest is there. So we have to sort of think about how do we as an institute play our role when we're in this world, this 10% of funding versus the 95% of funding. So as we come into our strategic plan, we sort of say, okay, how can we think about being the driving force for genomics at NIH and around the world? How do we keep a leadership role in this new environment? How do we think about coming up with a plan that really gives us this clear 2020 vision to advance thinking about the role of genomics in advancing human health, think about our priorities, shape our research portfolio, and again, given the changing landscape, really focus on where are the places we should be leading, where are the places we should be fostering partnerships, who are our stakeholders? It's an increasing number of groups that are our stakeholders into what we're doing at NHGRI. Not only other researchers, but even into healthcare, education, policy, general public communities, et cetera. But through all of that, what we really see is we're not the primary funders, but we still think we have a very important role at the forefront of genomics. So that's our new tagline, NHGRI, the forefront of genomics, really seeing ourselves as saying, what is it that are the key investments and key activities we can put energy into that's going to advance the entire field, push the field forward, and also continue to support the field through foundational activities that we traditionally have done. A little process-y dive into what have we done for strategic planning. Many of you may have heard some of these, seen some of these slides before. We've been really trying to get out to the community through workshops, town halls, gathering at existing meetings like today. We have a webpage, social media tools, hashtag genomics 2020, if anyone here is actively tweeting. And then we also have been engaging various advisory groups, and all of this is going to lead to a finale meeting that's been scheduled for next April to really talk about this. We started this process in 2018. It's actually going to be, when all told, over a two-year-long process. And it's because we've really been doing that outreach, trying to get community input and make sure that we're hearing from our constituents, our stakeholders, other groups in terms of what we're doing, what we should be doing, and where we're going. But we're pretty far along in the process. So I'll be able to share with you a little bit of what we've been, where we are in our thinking, but I'm also going to have some time at the end and purposely leading to get feedback from all of you. But our idea is to have a meeting in April, get this manuscript done, and really have our finale published on October 2020. Eric Green, who's our Institute Director, likes milestone moments, and that actually lines up with the 30th anniversary of the launch of the Human Genome Project. So that's where we're sort of coming in a milestone area. In thinking about this, we've been collecting information sort of driven internally, and there's lots of overlap between these areas, but we had to organize in some way. So from a staff perspective, we sort of came up with five focus areas, basic genomics and genomic technologies, genomics of human health and disease, genomics in medicine and health, really that sort of clinical genomic medicine focus, genomics of data science, or genomics and data science, and then society, education and engagement. For each of these, we've come up with already, based on the feedback we've gotten, some synthesis on areas that we see we should be focusing on. For the interest of time, I'm just going to focus with you guys on stuff from the first two groups. We can talk about the others if you want, but my going through all, you guys might even find my going through two of these, there's a lot of words on slides, but I'm happy to talk about the others as well, and just sort of show you where we are and what we've been thinking, and then get some feedback from you guys on things we've been missing, things we might be thinking about or any questions you might have. So in the context of basic genomics and genomic technologies, we really see ourselves having this foundational role in continuing to enable the generation characterization and interpretation of whole genome sequences, epigenomes and transcriptomes. Sometimes when we talk about this, we pull the interpretation part into a separate bullet, but you can combine them or bring them together. But really, what is in the genome and what does it do? And we focus mostly on whole genomes, epigenomes and transcriptomes in that. We also have been responding to, and we actually had a concept, even advance of the strategic plan at our last council, to really talk about moving some of the technology also into the generation and use of synthetic nucleic acids. It's having a lot of impact around the space, and we really see, although there's been some work in that, a need for some more concerted effort to really move that forward for all of the things that we currently know it enables and all of the science we probably don't even know about yet that that type of activity will enable. We really want to be thinking about what are the roles of genes, regulatory elements and variation within genes and regulatory elements in pathways, networks and phenotypes. This is certainly a bullet that comp falls under and would be certainly playing a large role in and continuing to advance space in that area, particularly some of the more path work and network level activity than has been done so far. We see an important role for evolutionary and comparative genomic data to markedly advance understanding of genome function, and this is called out because we do have as a member of NIH a huge focus on human health, but we certainly recognize that evolutionary and comparative genomics is essential to that understanding. And then finally, a higher level priority, which I could have maybe, which I didn't sort of come across here, is we really see a huge need at NHGRI to prioritize the increased use of diversity in genomics as a field. We haven't done good in that in the first sort of 10 years of the field. We do a lot of research in European populations and don't really take into account the diversity of the world. And so as we think about that as an overarching theme, from a basic genomics and genomic technologies perspective, we really need to think about how do we better understand population structure and admixture, and how do we actually leverage that information to improve our understanding of human health and disease? So I'm going to pause for a minute. I'll go on to the genomics of human health and disease in a second, but just to see if anyone has any sort of... I know I just said a lot. Anyone has any sort of questions or responses or thoughts about these sort of thematic areas, things that resonate with you, things we seem to have missed, questions, et cetera. Maybe just one thing. First of all, thanks so much for coming and speaking to us. So kind of the way I look at it and it fits in with your presentation is, we moved from structure decades ago through sequencing, which is completed, thank goodness, and now we're into really functioning as outlined here. And of course, our role is to really drive that part of it to determine function, focusing specifically on protein coding genome, but there's the whole rest of the genome going on. So I'm just wondering where do you think our kind of perspective or role comes into this perspective in terms of functional annotation of the human genome from, I guess, a comparative aspect from the mouse aspect. Yeah. No, I think, I mean, like I said, I really think both the... Actually, the first third and fourth bullet, I think really do all sort of have roles where sort of what is happening in the mouse comes into play. So the idea if we're gonna interpret whole genomes, we have to be able to interpret the genes. We recognize that as a perspective. We actually have a lot of internal debate about sort of variation-based approaches to genomics or a genome-centric approach to genomics, and are we balancing those correctly? Are they really different? Are they the same? But I think one of the things that we are really seeing the role from a... And this isn't an NIH-wide perspective. I think from an NIH-wide perspective, there's a lot of question and value about really thinking about genes and related to disease outcomes. For NHGRI, I think the question is, how do we really get the... How can we get mouse models? I'm gonna just focus on that because of the audience. In ways that can be really robust in helping us to get a better understanding of the genome. So we actually sometimes, from an NHGRI perspective, are going backwards a little bit, and I don't mean that in a negative way, but if you think about that variation to function to disease, or genetics to function to disease, I think a lot of the other ICs are really in that function to disease space, and we're really interested in trying to get a better handle about how to connect to variation and genetic and gene, individual genes, gene products, or variation within genes to functional outcomes in ways that can help us have a better generalized understanding of the genome and how to use it as a tool. So I think there's a lot of room for the types of things you guys are doing and expanding and building on it to help that. So some of the stuff, for example, yesterday, unfortunately, with my schedule, wasn't able to make the whole meeting, but some of the discussion in the OMIX group, as you think about tying the OMIX to the phenotype, and how do we think about parallel work happening in humans and connecting not just the underlying gene, but functional understanding across different layers between species, I think, is an area that's of interest to us. I don't know if that got at your question, or, okay. I think it might be under point number one, but I don't see it quite spelled out quite so clearly. One of the big things is higher order chromatin structure, understanding how that affects gene regulation, and so maybe that's under epigenomes, but. Yeah, I have to admit that one, I squeezed two things together, so it is under one where we sort of talk about that generation, it's that characterization part when we really start characterizing that it's a high, we sort of, I just used epigenomes as shortcut for a lot of other aspects. Okay. So also as we think about this, this is sort of moving a little bit too, is how do we think about using genomics into the understanding of human health and disease, and so this one we always get a lot of pushback on, but establishing the functional consequence of any genomic variant affecting human health and disease. That's a grand challenge in a way that we sometimes, when you put it in a sentence, are overstating, and we recognize that, but we still haven't figured out a way to convey it in a sentence without going better, but what we're really trying to do in that case is say, and you could say functional consequence of genes and genomic variants in relationship to human health and disease, is to really try to move the field, any part is the idea of moving the field from rather than doing things on a one-off basis, how can we start to have robust directions that people can take, that people can say, here's a way to do this. Comp is an example of this. If you wanna understand the impact of a knockout gene, let's do a systematic approach. What are other systematic approaches, what are other systematic technologies, large-scale methods, generalizable methods that we should be applying to make it a better understanding of variants and or genes impact and function, rather than, and I don't mean this in a negative way, but rather than just diving into things on a one-off basis. So we see that as important. Determining the genomic architecture of human diseases and traits, and so buried into that sentence is gene-gene interactions, gene-environment interactions, getting beyond having an understanding of what types of diseases have strong alleles, what types of things, how do you bring in polygenic risk models, all of those types of things to really inform genomic architecture of human disease and traits. Thinking about how do we really move the analysis and methods to use non-sequence genomic data, and by non-sequence genomic data, I mean not just saying, oh, this variant, getting into epigenomics, getting into chromatin structure, getting into other aspects of genomics and how they relate to human health and disease. Right now we have a whole field that does a really good job of sequencing or genotyping and looking at underlying variation in relationship to disease, but there's so much more to the genome than that, that also relates to disease and how do we, and that's, there's active in that area, but how do we move that forward more? This is a little more human focused than mouse, but one of the things we've really noticed is we really need to think about how are we assembling the sample sets we use in human genomic studies. As we move into an era of bio-banking, as we move into an era where more people are getting genomic data in the clinic, people are using direct to consumer activities, things are happening internationally in lots of different ways. The approach we use to get sample sets and to get data needs to transform and we need to think as an institute about how do we take a leadership role in making sure that the field figures out how to really capitalize on the data that's there and also make sure that, again, we have, and as we do this, a commitment to systematic inclusion of ancestral diversity. How do we transform this in ways that we are recognizing the diversity of the human population, ancestral socioeconomic, et cetera. So we're not also doing a thing that we're all sometimes worried about, which is like promoting health disparities by creating a field of genomics that only applies to a subset of the world. And then also thinking about somatic variation in human health and disease. I have a background in cancer. We've studied somatic variation in cancer. That's all, not all, but NCI's got that under control. But there's a huge role of somatic variation in lots of other diseases that is emerging, but really hasn't had, again, a really good systematic high level approach to. And we see thinking about, we're not gonna study all of that, but again, what are things that we can do in terms of technologies, resources, methods to really move research in that area. So again, I'll just pause here. Yeah, I still have like two minutes and I'll let us use them to see if you guys have any thoughts or comments on this. Can you use a microphone, please? I'm having trouble hearing you, so. So when you go through this planning process internally and you present it to us, it sounds great. It's all this foundational stuff that we will need, but you talked to the other institutes about this, do they know that? Are they doing their planning based on this? Do they want to duplicate this or that they are planning to take advantage of this and they know about it? Yeah. How much do you talk to each other? So we talked to each other in different ways. So we have had a town hall that was actually really well attended within NIH. And so we did do outreach in that standpoint of sort of bringing things out. But part of one of the ways that we talk to each other and work with each other is through trans-NIH committees, trans-NIH activities, but more importantly, I think it really comes, I'm looking at Oleg and Colin and Christine, through the relationships that we build with people at other ICs. So we will have situations where we see a clear need for an area and we go into a partnership with another IC and we work with them. So we've been, we're known as a leader in large scale gene sequencing, right? So when Alzheimer's, when the AGEAN Institute started the Alzheimer's sequencing project, they worked with us directly, program directors who were involved in ours were on, you know, actively working with them. Same with when NHLBI started their top med program. So we have ways that we sort of talk to each other. Do we talk to each other as well as we could? Is the 27 IC structure of NIH ideal? No, you know, but part of what we are thinking about as we do this is that question of how do we present our leadership role in ways that people want to work with us? And again, we have to actively, as we go to implement this, really buy into our partnership role, both at NIH and internationally, nationally and internationally to be able to do that. But really, we do do our best to communicate with other ICs and ICs try to communicate with us. We do develop partnerships in these areas, but it's, we could do, we can always do better. Did that answer your question or was that just too much? We are trying. Yes. And the other thing that I will say too that sometimes I'm gonna put on you guys as well is if you find sometimes like you're like, I'm working on this project over here and I wish these people at the other IC would do this, you guys can help make those connections sometimes. Like you can call up Colin and say, hey, my PD, my program director on this grant over here could really use some like, it would be great if you guys could talk to each other. Part of our job is to talk with you and part of our job is to talk with each other. And so you guys, if you see a connection you wanna have made, communicate it to us. And that can sometimes help us as well. Colin's gonna love me for that suggestion, but I'm just gonna reiterate what I always say is our job as program directors is to serve the community where the stewards of the taxpayer funds. And if you feel like we're not doing the right job in talking to each other, we should let us know that so we can try to continue to make those improvements. Thank you for the overview. So you know we build infrastructure? Yes. And we build infrastructure in lots of different contexts, this one and for other ICs. So I'm wondering how much of what you're presenting here today is informed by something that looks like bringing some of those infrastructure pieces together and how you think that ecosystem might look as we go forward for your 2020 vision. And I think it really plays to the previous comment about the other ICs as well. Because it's not a single IC piece. Yes. So there's two parts to that. I'm gonna not run over my time. I am gonna just pull up super quick that we have a whole discussion in genomic data sharing. And I don't mean this in an oh, we thought of that. But one of the things that's really in here is, it's under three, is this facilitating, storing, sharing and computing on large scale genomic data. And then there's a huge recognition across NIH that we're not doing that well right now. And to give you an idea of the commitment that's happening is tomorrow is the leadership forum of all the IC directors. And they're using a whole like, I think two or two and a half hours of their day talking about how do we improve the data science ecosystem at NIH. They're not gonna solve it in that chunk of time, but just recognizing they get one day a year that they all come together and do this leadership forum and they're giving a quarter of the time for this issue is, I'm saying it shows that they really is a recognition that we need to be doing a better job. I think the challenges that we have in doing that is twofold and I'll be honest with you all, even though I am being WebExed. One is it's that, again, this 27 ICs and 27 different ways to do it and we're going out there and building these siloed things and then retrofitting them as opposed to planning them from the start. So I think one of the things that we're trying to do, the Common Fund is also trying to do this is really start to have an idea of let's not build something new without thinking about it in the context of the broader ecosystem, but we're gonna have trouble with that with the 27 competing priorities. But we are, that's one of the things that we haven't done well. And the other is, to be completely honest, we don't have the expertise at NIH to really be doing data science as well as we can. When I was recruiting for a data science person, it was so hard and the first thing you do when you're recruiting at NIH is you say, oh, I'm gonna go find another IC who has a really good person and take them. Call in those, I just did that on another project of his. But I couldn't even, and the people who were there, their ICs were like, oh no, you don't get to take this person and held onto them really tight. And so part of what I hope to say by bringing this up is to encourage people to think about if you know some people who have that expertise and might wanna do a government service type of job to come to us and we would hire them in an instant. We're also doing some programs right now to bring in a like scholars program to sort of inject us with some people who really understand these problems. Because sometimes, and I'm sure you've experienced this, I think we don't have the expertise to actually solve the problem. And so we come up with solutions that make it slightly worse. So to follow up on two of those points, lots of people in my group have asked to have their job titles changed to data scientists. And you know some of them are here, so I'm sure they'd be happy to talk to you. And the other piece I think is that from my point of view, moving the data around, not particularly problematic. It's kind of functional, it's important. Building reasonable visualizations and getting the data to a high enough quality state. And I think that's really something that this program has really focused on quality and the interoperability of the data and the visualization of it. So those are the really hard things. And if we go to things like commercial cloud-based platforms, that stuff won't be easy to move. And so thinking about how the visualizations work across ICs and within ICs is a piece that I personally would really like to focus on. Yeah, no, I appreciate that. So if I could just tack on to that question about having appropriate people to do this. I think either training programs or programs that, I mean, one of the things about data science people, it's very hard to recruit them away from people who can pay them real money. And academia is not at the top of the food chain there. So I think that there have to be some programs. And I think GRI would be perfectly well positioned as sort of to lead in this area, right? In helping people or providing mechanisms for support that would help to even out the salaries and everything else. I mean, you put a data scientist on an R01 and then it's gone. So it's like, I think there just needs to be more mechanisms for that. And maybe that's something that GRI can conceive of in the career path building aspect. No, that's a great suggestion as well. Okay, well, I've gone, I started a little late, but I did go over my allotted time. So apologies to Colin for that. I am here for the rest of the afternoon. I know a lot of you are gonna have to rush out, but if the break or at the end, if you wanna catch me or send anything else or Caroline Hutter, if you Google, I'm the first thing that pops up. You can also send me an email at any time. Thank you.