So we will get underway. So I'm supposed to talk about weather and climate extremes, attribution and risk. There's an example here of one that was in the news just recently about wildfires in Fort McMurray in Alberta. And they're probably still going on. And so we're often asked by the media, is this particular event, is this global warming, or is it natural variability, black and white? No shades of gray in those kinds of questions. And so my comment is that these are not the right questions because it's always a combination of both nowadays. Oh, do we have a pointer here somewhere? Don't see one. All right. And so this is just a brief overview of the fact that, as Jim said, that climate change is happening. Thanks. It is due to humans, 97% of the scientists agree. There's a few who, for one reason or another, ideological reasons, religious reasons or other, seem not to agree. And the data are certainly of mixed quality. Does this pointer work? Nope. Try this one. Ah, there we are. The data of mixed quality and length. So you can all end this lots of variability. There's lots of weather going on. So you can always point to things that don't seem to agree. But together, they actually tell a very compelling story. And this is what we do as scientists is to put them all together. And they leave no doubt whatsoever about the human role in climate change. But what we do about this problem depends not on scientists. Our role is to advise you as to what we think will happen, what the consequences will be so that you can make informed decisions. But it's up to the public at large and, in particular, politicians. Unfortunately, politicians, some of the ones in Washington, as to what we actually do about this. And it relates to value systems. And you can have lots of discussions about that kind of thing. So here's my quick summary of the overall problem. The planet is running a fever. So if it went to the doctor, the symptoms are the temperature and the composition of the atmosphere is changing. Carbon dioxide is increasing in the atmosphere. The diagnosis is that these two things are actually related to one another. And the human activities are causal. So that's an attribution statement. And then prognosis is for more warming at rates that can be disruptive will cause strife. The treatment, then, is for mitigation to reduce the emissions, to cut down on the problem. So these have special meanings, these terms, mitigation and adaptation, as I mentioned before, which is really planning for the consequences. And we're not doing enough of either. And so the alternative, of course, is that you suffer the consequences. And too much of that is happening already. So here's a very brief background on the overall view. This is the global mean temperature from NOAA, starting off in 1880 or thereabouts. And you can see there's a certain raggedness to it, certain up and down nature to it. And I've also got the pre-industrial level indicated on here. And so we're already well over one degree Celsius above that. His degree Fahrenheit, multiplied by 9 over 5 to get from one to the other. And then this is the annual values of carbon dioxide. After 1957 and 1958, records were begun in Mauna Loa. And that's the Mauna Loa record with the annual cycle taken out and added up to the results from bubbles of air that have been trapped in ice cores in Antarctica and Greenland to take this back in time. And so the pre-industrial level is down here, around 280 parts per million by volume. And you can see this overall increase. And I put these two curves together to indicate that they're related to one another. Because one of the things that we can show here at NCAR, this is the attribution aspect, is that these two things are related to one another. But obviously, there's a lot of wiggles up and down which are not related to this. And this is the sort of things that denies of climate change can easily point to. So the last value on here was the calendar year 2015. It was 0.9 degrees Celsius above the 20th century record. And then this is the value for, actually it was at the time I did this, the last 12 months. We could update that now by another month. And it's about the same value. It's a wonderful degree C above the 20th century. So the last 12 months are the warmest 12 months on record by quite a substantial amount, in fact. So this is a jump of about 0.2 degrees Celsius that's occurred in the past year or so. And a key part of this is related to the El Nino phenomenon. But also it's related to the global warming that's going on.  We can run climate models with and without human influences and see what the difference is. And so an example down the bottom right is the result from the IPCC 2013 where a whole host of models were used. And there are two different versions of these, some older versions called CMAP3 and some newer ones called CMAP5. And then the observations are on here, which have a lot more raggedness to them. And then we can run these experiments with so-called natural force, which includes volcanoes and changes in the sun. And so this is what we get then. And here's what the results from the model suggest. These shock downward decreases in the temperature are related to volcanoes. And so they're present down below here, maybe not quite as evident. And you can see that it's after about the 1960s, after about 1970, that these are clearly separated from one another. And so this is the global warming signal. This is the result of the changes in the composition of the atmosphere. In particular, the increases in greenhouse gases, the heat trapping gases such as carbon dioxide and others, methane, nitrous oxide, and so on. Jerry Meale is going to talk to you a bit more about this a little bit later. And so I'm not going to dwell on this particular aspect. This deals with the average climate. And what we're going to deal with here is a lot more about the consequences of this with regard to extremes. And so here's some things about extremes. The extremes may or may not be rare, depending on how you define them. But they often break records. There are values outside of previous experience. And they may not, therefore, be planned for. And so things break. Thresholds are crossed. Often, there are high impact events. And they have high costs. There may be loss of life and limb. And some examples are given here about things that we'll talk about a little bit later. And so one of the ways in which climate change enters into this, it's not that we don't have these kind of events from weather and from natural variability and from El Nino. There are always droughts and floods and extremes around the world that occur naturally. But climate change is typically making a lot of these things worse. We cross some of these thresholds. We break records and things break. Some of the more complicated ones, people say, all right, global warming, it's an increase in temperature. Maybe it's associated with heat waves. What they do not understand adequately is how it affects storms and rainfall and floods and droughts. So I want to say a little bit about this. If we've got extra heat, where does that heat go? Well, in the human body, we sweat. Water plays a role. If you go up in the mountains here, not today, but maybe yesterday or the day before, without a water bottle, you can end up, perhaps, with heat stroke if you don't keep adequate water going in. Out here in the West, we can use evaporative coolers, swamp coolers, to moisten the atmosphere and take up the heat instead of increasing the temperature. And this works quite well for the planet Earth because 70% of the planet Earth is the ocean. And so the increasing heat actually goes into evaporation of surface moisture. Of course, that has consequences because it gets into the atmosphere and then it has to rain somewhere. So that's what we're actually talking about here. Another example, what happens if there's been some showers that's been raining outside, as it will later today? And the sun comes out. The first thing that happens is that the puddles dry up. And then the temperature goes up. The temperature doesn't immediately go up because all of this water lying around. And one of the ways in which you can keep cooler at home is spraying water around on the roof and so on. And so water plays a key role. It's the air conditioner of the planet. This is one thing you might remember. If it's the only thing you remember out of this talk, is that warmer air can hold more moisture. And the rate is about 4% per degree Fahrenheit, 7% per degree Celsius. So this has consequences. This is actually why we have weather systems. It relates to the fact that if you have a parcel of air, it's got some moisture in it, and for some reason that air parcel rises, it moves into lower pressure and therefore it expands and therefore it cools. If it cools, it can no longer hold all of the moisture and so it rains. This is very fundamental to why it rains. And of course, the air rises for various reasons. It might be because of a cold front or a warm front or a storm system of some sort or the other or because the wind blows up against the mountains. But this is one of the reasons. This is why it rains. And so with global warming, there's a bit more heat. Firstly, there's more drying. There's more evaporation. There's more moisture that goes into the atmosphere. And that has consequences. Firstly, in places where it's raining, there's more rain. But if it happens not to be raining, that extra heat means there's more drying. And so there's more potential for drought. So here's a particular thunderstorm. A key thing about rainfall events is that I don't know whether you've ever thought about this kind of thing. But the moisture that falls out is much, much greater. The rate at which it falls out is much greater than the rate at which it can evaporate. And so the way in which you can get heavy rainfalls is not because it's evaporating like crazy and all of the moisture is going right up into the cloud. Instead, that rate is typically about a factor of 10 or much larger. It can be a factor of 40 larger for the rainfall rate versus the evaporation rate. And so the only way we can get heavy rains is by having a weather system that reaches out and brings all of the moisture from around the area into the storm. And then it dumps it down in the form of heavy rains. And of course, this is why it cannot rain everywhere at once. And so in the summertime, often, if you're out on the golf course or something, you can experience some gusty winds. Oh, what's going on? There's nothing around here. But then you look over in the distance and you can see, oh, there's a thunderstorm over there. This is a thunderstorm reaching out. And it can reach out quite substantial distances as a part of the circulation of the storm to gather the moisture and bring it into the storm and dump it down. And so one of the consequences of this is that if there's more moisture in the environment, it rains harder. And there's a greater risk of flooding. So now, turning to the attribution science, the traditional now hypothesis and approach for dealing with this is that there is no human influence on climate. And we have to prove that there is. And we've done this many times for certain kinds of things. But for some variables like precipitation, it's much trickier to do this. So is it sufficient to say, well, we know there's a human influence on climate from temperature. I showed you that before. We can show that with our climate models. But what about precipitation? Well, as I've just shown you, there are effects on precipitation. But they're fairly complicated. So scientists make two kinds of errors when they're dealing with this kind of thing. The little diagram on the bottom right here is that they can make a statement that turns out to be true, and they can make a statement that there's no human influence. And that may also be true. In other words, the false, false category. But scientists lean over backwards to not make false, positive statements, the type one errors, wrongly concluding that there is a human influence where there isn't. And typically, we use this 95% confidence limit. And as a result, many scientists make what is called a type two error, which is down in this box here. In other words, there's a false negative, and they wrongly conclude that there is no human influence when there really is. In other words, the scientific community has been very, very conservative with regard to statements that say that there's a human influence on climate. I think it's very unfortunate, but I think it's beginning to change. Here's an example here. So here's a so-called bell-shaped curve.  This is the mean value, 50 degrees Fahrenheit. And then I've warmed it up artificially here to be where it's been warmed up by 10 degrees Fahrenheit. And I've just kept the distribution around the mean the same in this case. And so those of you who know about this, the standard deviation or the spread about this is the same in both of these sets of curves. So here's what is called the 95th percentile over here, or the 5th percent significance level. And the way in which scientists have worked to say, if the climate, if stuff is happening out here, then we regard it as being significant at this 5% significance level or the 95% confidence level. Now in this case, you can see what would happen is that in B, all of the stuff that's out here, I don't know what it is, 10% or 15% of the time, you would conclude that, yes indeed, there is a climate change. But all of the place where you're in here with B, even though there really is a climate change, you would say, oh no, we cannot prove, we cannot say clearly that there's been a climate change because this is, this still could have happened, it's still within the previous realm of variability. And so we make type two errors most of the time.  The only way you can avoid this is to have a climate change so large that these two distributions are completely separate from one another. So what are the expectations with regard to climate events, these extremes that we're dealing with? Well, the changes in atmospheric circulation with climate change turn out to be relatively small. We can show that with our models here at NCAR. And they vary quite a bit from one run to another. And you have to average over a large ensemble to really identify the changes in the atmospheric circulation. And in any event, also, there is individual character. There, every event is unique. Think about that, I mean there's an infinite variety of weather events outside. It's actually remarkable. There are some events that you can look at and say, oh, that looks a little bit like what happened three years ago. But you don't have to go very far, you go 10 miles away and something quite different is happening. And then the subsequent evolution is quite different. And so, as a result, it's statistical forecasting of the weather has not proven useful. That's why we need to use dynamical models for numerical weather prediction. So studies that have tried to attribute events have nearly always concluded that natural variability dominates, and they should. But they're really asking the wrong questions, in my view. And so what we have suggested is that it's essential to distinguish between the small, noisy, chaotic, and unpredictable dynamics in the atmosphere from the thermodynamic effects. And I'll explain a little bit more by what I mean by that in just a minute. And it's more useful to regard the extreme circulation regime or the weather event as being largely unaffected by climate change because the effects of climate change are usually relatively small. And then we ask the question of whether the impact of the event was affected by the known changes in the environment in which this particular event was forming. And as I've mentioned to you before, in general, it's warmer and it's moisture in the environment. And this affects all of the storms that we're dealing with. And we've got a lot more confidence relating to climate change in these thermodynamic aspects. And so dynamical aspects deal with the phenomena. The individual cloud or weather system, its movement, the development, it tends to be chaotic and unpredictable. And chaotic has a special mathematical meaning nowadays. And so you can look that up. I don't have time to go into that. And every event is unique. But the environment in which the phenomena is occurring deals with the overall temperature, the water vape, how much moisture is available, perhaps the sea level if we're over the ocean. And these aspects tend to be very robust and predictable. And so the key thing is that the environment for all storms has changed. It's warmer by, this is a very conservative number now. It's closer to one degree Celsius, perhaps the air is typically moisture by five to 10%, closer to 10% probably now. The ocean heat content is much higher. The memory for the system in terms of climate change is in the ocean. The oceans are warmer. The sea temperatures are higher. The ocean heat content is higher. As a result, sea level is higher now by about 19 or 20 centimeters by eight inches. And this is the sea level record here. This one here is the two meter temperature record since 1979. This is the water vapor record. This is global values of the total column water vapor in the atmosphere, showing that these are relentlessly going up. And the main support comes from the oceans and the thermal inertia in the oceans. So there have been problems with many of the current practices. There's often been, I think, misleading and erroneous statements. Some of these have been published in the literature and some of them which have been very visible, I've mentioned here. Many misleading statements in the literature and I think the result has actually been disastrous for public understanding because there's a lot of events that have occurred. In fact, all events that occur nowadays have a component of climate change in them. And the question is exactly what level is it? And maybe you can guess from the things I've just said is that it's at least the 10% level and it could easily be double that. But it's not 100%. So we've suggested that there are more useful ways to approach this. And this is called a conditional approach. And so we suggest that we can ask these kinds of questions. Given the weather pattern, how were the temperatures, the precipitation and the associated impacts influenced by climate change? Or given the drought, the drought itself, let's assume the drought was caused simply by natural variability, but given the drought, how was the drying, the evapotranspiration, enhanced by climate change? And how did that influence the moisture deficits and the dryness and thus the wildfire risk which typically goes along with drought? Did it lead to more intense and perhaps longer lasting drought as likely? Given a flood, where did all the moisture come from? There's not enough studies of this kind of thing. Was it enhanced by the changes in ocean temperatures that may have had a climate change component? Given a heat wave, how was that influenced by the drought that often exists, the dry conditions around, which means all of the heat goes into raising temperature instead of into evaporation, as I mentioned before? So those kind of factors come into play. Given extreme snow, I'm gonna talk a little bit about snow, where did the moisture come from? Was it related to higher than normal sea surface temperatures off the coast or farther afield? Or more generally, given an extreme storm, how was it influenced by the anomalous sea surface temperatures in the ocean heat content? The anomalous moisture transports into a storm and the associated rainfall and then the heating that goes on with that in the atmosphere that can help to invigorate the storm. And was the storm surge worse because of higher sea levels? So we can talk about those kind of examples and I'm gonna give you a quick run through of a few of these. The National Academy of Sciences weighed in on the attribution of extreme climate events earlier this year. I think this was March, yeah, March this year. And from their website, they say that, well, scientists have cautioned in the past that individual events couldn't be attributed to climate change. But now, with advances in understanding the climate science behind extreme events and the science of extreme event attribution, such blanket statements may not be accurate. Very understated, what they're really saying is using the approach that we have identified here, in fact, we can often make very clear statements that there is an influence, a human influence on climate, on individual events. And so the strongly conditioned approach, the thing given that we've got a storm, what was the impacts, is becoming much more acceptable and this seems to be catching on with a number of scientists. So the first example, it's not John Travolta. Superstorm Sandy, my family was very much involved in this, my daughter and her family live in Hoboken, New Jersey. My wife was visiting them at the time and they were all evacuated, but I gave them six days notice and they were well prepared, they had all of the things they needed, they cleaned out all the drains and everything, but the whole area was evacuated and they lost power for 10 days or something like that. So here's this big storm, it started off as a hurricane, it came up and the outstanding thing was this, was not so much the real intensity or the depth of the storm itself, but how big it became, it became a hybrid storm and so this is a picture of it. And there were over $70 billion in damages and over 110 lives lost in that. And so here's a few things about it. I mean, it caused tremendous damage when it made landfall on the New Jersey coast in the New York area. It began, it got up to a category three hurricane, but it became this hybrid storm and some of the worst damage was on the Jersey shore. But there was heavy precipitation farther inland that was also a major problem. And so that's the sort of quick summary and the thing about it was that the European Center for Medium Range Weather Forecasts made accurate forecasts of this about six days in advance. National Weather Service didn't quite catch up until about four days in advance. And what they have done subsequently was they re-ran all of their forecasts for this and they made about over 50 forecasts using an ensemble of forecasts. So they run it all over again and they test it to assumptions about the data and the uncertainties in the data. And they changed, in this case, the observed sea surface temperatures off the coast for the climatological values that were typically one to 1.5 degrees C cooler and a swath about 1,000 miles off the coast or something like that. But only very small changes occurred in the track of the storm. In other words, the weather situation, the synoptic situation, where the highs and low pressure systems were pretty well locked in place and they weren't affected by this, but the storm itself was. And what happened is that the observed sea surface temperatures led to a much bigger, more intense storm with stronger winds and greater precipitation. So here's the result of this. In the background here, you can see the observed sea surface temperatures. That's the colors and you can see the 26 degrees Celsius isotherm. This is the Gulf Stream up here. So the Gulf Stream is coming up through here. And then this is the climatology. You can see it's much more smooth. The 26 degree isotherm is much further to the south. And this is the storm that was forecast under these conditions and this is the storm that was forecast under those conditions. And so you can see the impact. It was substantially weaker and it was smaller. This is the change in the winds that occurred. So the winds, these are actually in meters per second. And there was overall a 3.6 meter per second increase in going from here to here, 3.6 meters per second. You can roughly double that about seven miles per hour or something like that. But if you have 21 versus 19, so that's only two meters per second difference, it turns out that's a 35% increase in damage because the damage actually goes up about the cube of the wind speed. And so very small differences convert to quite large differences in the damage. And so this is what I showed you before. And then the average depth of the storm was increased by about 7.6 hectopascals, millibars. The wind speeds increased by 3.6 meters per second. The precipitation in the storm increased by 35%. And the sea levels also of course along the coast were higher because of global warming. And so climate change was not responsible for all of these changes. It was probably responsible for perhaps a third of this. And they could have done another experiment just looking at the climate change aspects. But I think it's very likely, one of the biggest sources of damage was the fact that the subway tunnels in New York City were flooded and also the tunnels between Manhattan and New Jersey, which is Hoboken, which is where my daughter lives, and also to Brooklyn, probably would not have flooded without climate change. And so the flooding occurs because of the highest sea level plus the high tides, the big storm plus the storm surge. And that damage alone was probably worth $40 billion that you can attribute to climate change. Then in June of 2013, there was some major flooding just north of here in the Northern Rockies in Calgary, Alberta. This is, this runs right up, this is the Rockies here, this is the edge of Alberta here, and this is where all of the flooding occurred. And where did all the moisture come from to produce this kind of thing? This is the overall picture for the month in which it occurred, June of 2013, showing the overall temperatures average for that. And so it was relatively warm up through here, but in particular off the coast, this sort of reflects the sea surface temperatures. It was very warm out here in this region here and maybe slightly above normal in the Gulf, but that's probably not the most vital place. This is a bit of a funny projection as looking down from more of the polar region. And so here's where all the rains were occurring. The green here is the rains. And so it was raining out here and raining in here. And there was a high pressure system here and a high pressure system, low pressure system here. And so because of the juxtaposition of this high pressure system and this high pressure system, there was a flow right up into here of moisture coming out of this region here. This is the actual moisture. This is the water vapor channel that's on one of the satellites showing the moisture distribution. So very high levels of moisture down in here in the green and the blue in general. So you can see the moisture flowing right up into this region here. And so there's sort of the pattern of where the moisture was coming from. Some of it was coming out of the Gulf, but a lot of it was coming out of the tropical Atlantic and out here the sea surface temperatures were substantially above normal. And so there's probably a climate change related to this aspect related to this plus the fact that the temperatures over the land are warmer by a couple of degrees and therefore the atmosphere can hold more moisture and that's a very important factor because it means the moisture didn't rain out here or here instead it carried all the way up into this region here. And then in September of 2013, shortly after this, we had a major flooding event in Boulder and since you're in Boulder, I thought I would have to include this. How am I doing on time? I've got plenty of time at the moment. And so these are some of the statistics. You know, we had a record daily amount. What was it? A factor of two more than the previous record on any day and the monthly record for September was smashed by a factor of three and the previous record for any month was only 9.6 and so there were all kinds of records broken with this. There were eight fatalities and certainly over $2 billion in damages. This is some of the damage that occurred around here close to downtown Boulder. And this is what it looked like not too far away from here up in some of the mountains, some of the erosion that occurred was incredible. This is the biggest setting for it and now we're looking again at this water vapor channel and with some enhancements in this case, looking at the basically, you know, half of the northern hemisphere. And so if you sort of step back and look at this, you can say, well, this is where all the action is. This is where all of the heavy rains are occurring down in this region here and now here's this river of moisture going right up into Colorado and it's emanating from down in here and there was some moisture that came up into Colorado out of the Gulf at lower levels but in particular this was very special down in here. So what was going on down in this region down here? You know, so if we look at this little box down in here this is the sea surface temperature distribution. It turns out this was quite warm and this is the sea temperatures in that particular box and you can see there's lots of ups and downs here. The main ups and downs tend to relate to El Nino events where it's not just warm here but it's warm all over the eastern Pacific. The exception was in 2013, it was only warm in this region here. It turned out that was the warmest spot in the western hemisphere. And as a result, that's where all of the low level flow tended to go towards this warm spot. That's why we saw all of that activity in the previous slide. But you can also see when you look at this, oh look, yeah, we can see evidence of climate change. There's certainly a lot of spikiness in this but there's very clear evidence of general warming that's been going on in that particular region. And so this is the Water Vapor Channel showing this picture and this river of moisture coming right up into Colorado at that time. So it was an unusual weather setup. It was probably unique, well, it was unique. The models have generally not been able to replicate that kind of thing. But the amount of moisture that was in the atmosphere down here was an incredible amount. It was as high as 75 millimeters, about three inches of moisture in the form of water vapor in that region. The normal is about one inch of water vapor in the atmosphere. And so after that river shut off, the storms in Colorado ceased, there were two tropical storms formed, Manoel and Ingrid on both sides of Mexico. And it, whoops, and it doesn't say on here. I thought I had some details but there were hundreds of lives lost in Mexico and there was hundreds of millions of dollars of damage that occurred in Mexico. We didn't get any of that in the news here because we were so focused on what was going on in Colorado but it was not disconnected at all. And recently the DOE has run some experiments where they used the approach that we suggested. So given the storm, let's use a model that can simulate things like this as a forecast model and they use the WRF model, the Worf model and they ran it under what they considered to be pre-industrial conditions and then they ran it under current day conditions and they got this distribution of rainfall, seven day rainfall over the Colorado region, northeast Colorado region and in general you can see the overall increase was about 30%. And so they conclude that the anthropogenic drivers which was the biggest factor was the fact that the atmosphere was moisture and the atmosphere was warmer and it can hold more moisture and therefore it rained about 30% of the rains in Colorado was probably due to the anthropogenic climate change. So this is just a quick summary of what I've already told you in this regard. Let me not dwell on it. And so the warmer conditions allowed the air to hold more moisture. Or here's the notes on Mexico down here that subsequently there were hundreds of deaths in Mexico and over 10,000 were evacuated with billions of damage. So turning quickly to drought, the other side of the coin, weather or when there is a dry spell is largely caused by natural variability and it tends to be dominated by ENSO which is El Niño Southern Oscillation or La Niña. La Niña causes droughts in certain parts of the world and in completely different parts of the world occur in El Niño events. So in El Niño events it's over Australia, Southeast Asia, Northeast part of Brazil and so forth. But given a drought, global warming tends to make it worse. There's increased drying. Where does the heat go? We've got increased heat from the increased trapping of energy by greenhouse gases. And one of the things it does is it increases the drying, it increases the heating and the heat waves and it increases the wildfire risk. And so one example is the wildfires at Fulton McMurray which caused tremendous horrendous damage. These are just some pictures of that and some of this generated its own weather in fact. These were all the wildfires around there at that particular time and we can look at that from satellite and see this. And one of the troubles is that some of the ground there has a lot of peat in it and so the flames get into this peat and it just keeps simmering away, burning away and that's what's keeping these things going and it's very, very difficult to put out. This is the 30 day accumulator.  I found this slide which went a little bit into Canada and so we can actually look up here and we can see that over this period it was actually very dry all through this period here and it was from rains down here and it was also very warm all throughout the west at that particular time. But this is what it looked like in the Calgary region in Alberta for the previous year and so this is sort of more normal kinds of rainfall and for five months they had had very depressed rainfall amounts, about 20% of normal and so very little rainfall, very little soil moisture, very little evaporative cooling so all of the heat goes into drying, raising temperature, increasing wildfire risk. That's what set the stage for this kind of transition here and that's generally true in the west. There's longer wildfire seasons. In this case the El Nino was probably partly responsible for the fact that it was dry in that region and tends to be what happens but it makes for tender dry conditions and so I put together the slide with a whole bunch of microwave ovens and the idea here is that you have one microwave oven, these are small microwave ovens and they go in every square foot, one every square foot. So currently the energy imbalance, this is the net energy imbalance with all the feedbacks included is about one watt per square meter. This is what causes global warming. This is the increased trapping that we've got. Now it's a very tiny amount. It's like having a Christmas tree bulb in every square meter or something like that. In a drought water's playing no role and so over one month the extra accumulated energy is equivalent to running a microwave oven at full power, small microwave oven which is about 720 watts over every square foot. So there's 10 square foot in every square meter so if you wanna do it for every one microwave oven every square meter multiply this by 10 so that would be 60 minutes. Every six minutes for six minutes, no wonder things catch on fire. That's the extra accumulated energy from global warming. So that's what happens in drought. So what about snow? This is a picture here, we had a meeting here actually and we went outside and took this picture when there was snow dealing with attribution and this was the storm called Jonas by the Weather Channel and so on. It was an east coast storm off the east coast and it was in exactly the right position to produce tremendous amounts of snow in Washington DC you may recall. And so there were pictures of the panda having fun in the Washington Zoo. These are some pictures of what was going on weather wise and these two pictures are in Hoboken and this is my grandchild in Hoboken, New Jersey having fun in the snow. So this is what it looked like in that situation. The sea temperatures off the coast, this is where the Gulf Stream lies. There were pockets of water that were as much as seven degrees Celsius above normal but there were also little cold pools but in general it was two to three degrees if not more warmer than normal all the way off the coast. In other words, there was substantially more. Think of the number, seven percent per degree Celsius times three, 20 percent more moisture lurking off the coast waiting for any storm to come along to pick up and then dump it down in the form of, will it be rain or snow? All right, there's plenty of cold air over the land at this time of year and so that what happens. This is the bigger picture. It was very warm down here. There's an El Nino down here and this is the overall smooth version of this if you like and this is relative to 1981 to 2010 so it's already got quite a bit of global warming built into the background that this is subtracted from and so this is what two degrees C in that region up here above there and so it's closer to three degrees C over a lot of this region above normal in that region but it was within 1,000 miles of the coast. It's not unlike Superstorm Sandy in that regard and then this is the water vapor channel. Your eye tends to be drawn to the yellow here but you should be looking at the storm itself. This is all of the heavy rainfall that was occurring and the water vapor that was occurring and flowing into this particular storm coming off of these very high sea surface temperatures off the coast so that's sort of the flow of moisture and the flow of moisture, the typical rule of thumb for just about all weather systems is that the flow of moisture occurs about four times the distance of the radius of the rainfall. So if you've got an individual thunderstorm and it's raining over one mile say the moisture is flowing in from at least four miles away. If you've got a big extra tropical storm where it's raining over 500 miles then the moisture to supply that storm is coming from 2,000 miles away. In other words, the moisture that's going in here is coming out of the Gulf of Mexico and out of the tropical Atlantic typically to get into that storm in order to account for all of the moisture that's occurring. And so there's a Goldilocks effect with regard to these storms. If it's too cold, the air gets freeze dried because of this 4% per degree Fahrenheit. If it's too hot, it's rain. If the conditions are just right, Goldilocks effect, that's when you get the biggest snowfalls and so the highest snow actually occurs when the temperatures are about 28 to 32 degrees Fahrenheit. Now in winter in the US, in Colorado, it gets cold but it's a bit warmer than it used to be. What does that mean? It means there's more moisture in the atmosphere. In the middle of winter, we actually expect and we actually observe that there's more snow in the middle of winter now than there used to be and sometimes we even get a bit of rain in December and January. We never used to get rain in December and January here. So this is the relationship, the 4% per degree Fahrenheit, the one degree increase in temperature increases the water vapor by 7%. The sea surface temperatures are at least one degree Fahrenheit higher and therefore there's more percent. Okay, I got to speed up a little here and so this is what has happened on the Northern Hemisphere basis is that in the middle of winter, in October, November, December and January and probably February if you updated it with recent statistics, there is more snowpack around the Northern Hemisphere. Most people don't know this but in the middle of summer from March on there's a lot less snowpack. That's because more of the snow falls as rain and it melts a lot faster because of global warming and the biggest changes have occurred in the eastern parts of the United States in particular and so one of the consequences of global warming is more snow in the middle of winter but a shorter snow season. All right, so this is, we can wrap up at this point. I'll tell you what I've got and I'll go through it extremely quickly and you can ask questions about it but this is the sort of thing that a general conclusion, while we cannot say that these events were due to global warming because that's a poorly closed question, it's highly likely that they wouldn't have had such extreme impacts without global warming. All right, so what I've got here and I don't have time to go through this is a whole bunch of things on sort of what's happened around the world in the last year or so and so there's the big typhoon that went through or cyclone that went through Vanuatu. There was the flooding a year ago in Texas and Oklahoma which had an El Nino connection. There's the widespread heat waves that occurred last summer all around the world and the wildfires galore throughout the west including Alaska and Western Canada last year and probably more again this year. They're already underway and these kind of statistics. There were record breaking typhoons and hurricanes in the Pacific, the largest number of category four and five storms ever. We had this nice picture where we had three of them all together and Kilo, Kilo started off as a hurricane and then it went across the dateline which is very, very rare and so transitioned from being a hurricane to a typhoon. That's just the terminology, west of the dateline they call them typhoons but it was exactly the same thing. There was major flooding in South Carolina, October three to five that was very much related to an atmospheric river coming off of the coast and there was a tropical storm at Yokun out there somewhere and major flooding in India, the drought in Indonesia, this was very much El Nino. These are all wildfires, those aren't clouds, those are wildfires in Borneo and major drought in South Africa, the driest ever terrible conditions and that's again partly close by El Nino as to where the drought occurs but again it's made worse by global warming and then November, December last year record breaking flooding in Missouri. Previously the values have been running along about five inches, previous records 10 and this year time 15 and at the same time the Southern Hemisphere record breaking flooding in Paraguay. So the strongest hurricane ever in the Southern Hemisphere hit the Fijian Islands in 2016. We've had a number of episodes of Houston flooding in April and May and even more recently and again you can see this kind of characteristic of these atmospheric rivers that come in and the atmosphere just holding more moisture. So here's the summary, all right? Let you read this. And the Paris Agreement is designed to address this and this is our paper dealing with this. You can access this at my website so I'll go back and leave it at this and thanks very much.


What's wrong with you? Oh, sorry, no. I ain't a boss. How you been, man? I ain't seen you in a long time, man. Man, I've been in town for almost a year and you ain't come out to see me. Okay, but I called you a week and a half ago and you ain't called me. Can we go to the next 70, please? You played how long? I played for eight years. I started with the Houston Oilers slash Titans. Got drafted in 1995 to 67 pick. When Floyd Reeves and Jeff Fisher selected me, it was one of those things that I'll never forget. I never thought you'd be coaching football. I thought you'd be like a track guy coaching. First of all, that form is terrible. It's not like this. You know, I didn't think I would coach either, but I love coaching the technique of being a wide receiver. I love coaching the position, but it's more than in coaching the position. It's positioning those guys for life. There it is, there it is. But that's two points then. So what you do on your free time, man? I fish. You don't know how to fish? I have a doctor's degree in fishology. You still, man, you still don't even know how to bait the hook. I fish. Three on there, one inside. I just make it look easy. I quit. You know, I was here a couple of months ago with Eddie George and Stephen there got their jersey retired. It's surreal. It just makes me feel good to come home and see the former players just being on the field with my brothers. And that's what I really, really miss and I really, really love. I'm still ahead. No, you ain't. We're tired. No, they're dead again. Have a good day. I miss, I love you, man. You're a great man. I love you. You too, my friend.


So it really is indeed a pleasure to be here. I was here, I think, five years ago last time. And my message has stayed hopefully, maybe not hopefully, but has stayed very much consistent. As Jim alluded to, our lab has been focused on what some people have called the darkest matter of the human genome, which specifically interested in regions that change very, very rapidly, specifically within the human species, areas of the genome that have been proven to be dynamic, both in terms of structure, their organization, and in terms of their evolution. As he mentioned, specifically we're focused as one aspect of that study on regions of the genome that are highly duplicated. And so these come in two different flavors. These are duplicated sequences that are either duplicated within a chromosome known as intra-chromosomal duplications, or duplicated between non-homologous chromosomes known as interchromosomal duplications. The reasons we're interested in this are really two-fold. One, these are dynamic by dint of the fact that they have sequence identity at very high levels to non-homologous recombination, promoting additional rearrangement events at the specific sites. The second reason is that if you believe the work of Susuma Ono and others, duplication is the primary force by which new genes and gene families evolve. So we're interested in these regions really from the perspective of dynamic mutation, de novo mutation associated with disease, and second from the perspective of the evolution, potentially of new genes and gene families within human. And both of those topics I want to discuss today. So I just summarize the work that came from really analyzing the whole genome, really the finished human genome. This is the pattern of the largest and most identical duplications within our genome. The blue lines representing these large blocks greater than 95%, greater than 20 kb in size of intra-chromosomal duplications. And you'll notice from this that a lot of our duplications are essentially interspersed. So if you look at chromosome 7, you find a lot of the pairwise, large ones separated by megabases of sequence. If you add the intra-chromosomal pattern, you get something like this. So this is the pattern of the human genome, and it's been relatively constant through the new assemblies. And most of this data I should point out came from back-based sequencing. This is the sequencing of large insert clones. If you go back and look at some of the first published whole genome shotgun assembly versions of the human genome, these varies the genome are completely missing. The important point is about 60% of the large duplications within our genome are interspersed. As I say, they're separated by at least a megabase from their nearest neighbor, or they map to another chromosome. If you contrast this with some recent data that we've done with Deanna Church and looking at kind of the comparable finished version of the mouse genome, this is the pattern that you see for the most identical and the largest duplications within mouse. So in this, the total amount of duplicated sequence in the mouse genome now turns out to be very similar to what we saw initially with human, roughly 5% of the genome. But you'll notice two things. The actual locations of these are fewer in number, so they're about half the number of sites in the mouse genome that are highly duplicated. And the second thing you'll notice is that essentially most of the lines, the blue lines here, which indicate intra-chromosomal duplications are right on top of one another. Suggesting that most of the duplications in mouse, about 82% of them are tandem. That is to say, clustered in orientation. So this difference between man and mouse in terms of finished back-based sequence assembly has important ramifications both in terms of evolution, the fact that you can juxtapose different pieces of DNA, creating complex configurations that you don't see in closer-rated species, and also in terms of disease. So its importance in terms of disease comes from really this, some of the seminal work from Jim Lapsky and others in the early 1990s. And the idea is very straightforward. If you have duplicated sequences within a genome, you can trick the recombination machinery during meiosis to recombine where it shouldn't. So here's showing two of the four chromosomes aligning during meiosis, the duplicated sequence showing in green, and a non-elique homologous recombination, also known as an equal crossing over event occurring, leading to gametes that have accumulated an additional copy of that duplicated sequence or have lost a copy of that duplicated sequence. So the really important part is that if these are essentially interspersed, imagine intracromosomal duplications now with unique sequences encoding genes A, B, and C, genes A, B, and C get taken along for the ride. So in addition to producing gametes that have additional copies of that duplicated sequence, we now have gametes that have additional copies of genes A, B, and C, and we have gametes that have lost copies of A, B, and C. If those genes are triple sensitive, A is sufficient or imprinted, the result is disease. And so there are, at this point, about 30 different syndromes in the human population that are caused precisely by this mechanism. It is not really a genetic disease because it doesn't have to be transmitted. There's something that goes on in all of us as we sit in this room and we produce gametes, either egg or sperm. And an architecture that has a lot of these interspersed configurations is obviously going to be proposed, be predisposed to these types of events that have a lot of frequency. So these are some of the diseases. I'm sure many of you have heard of some of them. Velocardiophageal to George, Williams syndrome, Prada-Willi, and so on. There are two interesting aspects about these diseases if you look at them. So shown here is the actual size of the duplication, which is mediating the rearrangement. And the important point here is that most of the events are large. The duplicated sequences have to be greater than 10 kb, often greater than 100 kb in size The second point is that the degree of sequence identity is also very high. So typically most of the diseases are caused by duplications that are greater than 95%, and the vast majority are greater than 98%. And the third component of these diseases, which you can kind of see here, is that the vast majority of diseases that have been described thus far involve some type of neurologic component, either peripheral nervous system or central nervous and cognitive deficit with these kids. So the hypothesis was very straightforward. If we had a beautiful duplication map of the genome, which was born on the sweat of a lot of wonderful people working on this project over the last 10 years, could we use that as essentially a morbidity map to predict the sites of disease associated with these specific regions? And specifically could we focus on children with mental retardation to find new diseases previously unknown? So this is this duplication map I showed you again. So it was not just a quality control exercise for the human genome project, but we actually viewed it as a disease map. And so here's our roadmap. All the gold bars represent blocks of sequence where the architecture is such that you would believe to be a high frequency of de novo mutation based on very large, very identical sequences at these positions. So there are roughly 130 regions at that time of the genome. 23 at that time, which are the gold bars with letters behind them, were ones already associated with disease, that the remaining, at least some subset of those remaining regions would be associated with de novo disease in the human population. So the way we did this is kind of old technology now, but we began this work about two and a half years ago. We targeted all of our regions that had at least 50 kb of unique sequence, less than 5 megabases, that were flanked by duplications greater than 95 percent identity and greater than 10 kb in size. We took backs from these regions and we built a specialized microarray that contained about 2,000 backs from these roughly 130 regions of the human genome. We spotted them on a microarray and we simply would test the given normal DNA sample labeled with one fluorochrome against a diseased individual labeled with another fluorochrome and looked for signal intensity differences based on hybridization to this chip as evidence or gain of loss of that specific region. So in terms of a study populations, we used a normal control group, which people have argued maybe isn't the best control group, but it was what we had available at that time, which included all the hat map samples, as well as an additional diversity panel of roughly 45 individuals. So we used these normal individuals to establish the normal pattern of variation within individuals without disease or at least without disease associated with mental retardation. So I'm not going to go over those details other than to say that we found a lots of copy number variation. So harkening back to something that Claire mentioned, the human genome has riddled with differences in gains and losses of sequences in different individuals. We then focused on a collection of kids that essentially the clinical community or at least diagnostic community had given up on. There were roughly 500 children children which had been tested for fragile X had been come back negative children tested for subtylomeric rearrangements and children whose carrier type was normal for testing using this platform. So some of the results. So after screening the normal collection then following up with studies of these three roughly initially the first 291 children from Oxford. We found regions of the genome that look like this. So what you're looking at here is a log 2 relative hybridization intensely plot for four different individuals. These are all children with mental retardation and we're looking for things that deviate from the log 2 ratio of zero which would be no difference. And you'll probably notice that there's a lot of noise over these regions. This is because about a third of our probes were actually selected and really isn't 2N but it's actually more than that so this actually creates some background. But clearly there's something different about these four kids. They have essentially about five backs that are apparently showing evidence of micro deletion in a region that we never saw once in a normal control group of study. These are validated by fish. I think the most probably interesting aspect is we could actually go back now and do a more high density oligonucleotide customized microarray so instead of using five backs in the region we designed now 11,000 oligos over that specific region and really confirm to see whether the break points were identical. So showing here those four children once again this is the log 2 relative hybridization intensity depression shown here in terms of log 2 indicated by significance in terms of when you see the red signal. And what you can see here is a couple of things. First off, if we compare the affected child with that of the parents so this is one of the children compared to mom and dad in the parent area but they essentially have a deletion the child has a deletion roughly 450 kb precisely at that site. You also notice here this is the segmental duplications these are very large highly identical duplications which share about a 99% identity over 100 kb in size. So the duplications are demarcating the boundaries or the break points roughly which you'll also notice when you look at the regions contained underneath this is the deletion as well. The important point here was that we had essentially an identical critical region in four children identified from the study of mental retardation all of them had hapline sufficiency at least as that's our model and in fact all of them that we've been able to test so far were de novo events. In other words parents did not have this lesion this was seen specifically in the kids. On top here are some of the genes and there's five genes mapping into that region but obviously there's some great candidates. One of the most interesting is map T also known as tau it's a gene in which point mutations have been associated with Parkinson's, Alzheimer's and frontal temporal dementia. So we're screening now patients which have essentially phenocopy in terms of disease and looking for point mutations. I'd like to just emphasize or make this note that even though we screen only 300 kids this was roughly of the idiopathic collection that we looked at was roughly the total in terms of disease. These are what the kids look like so we now in collaboration with our former competitors Bert De Vries in Holland we've had the opportunity to look at roughly now 21 children all of them which have the micro deletion 19 of them we've been able to look at parenterals and show the de novo events and if you look at these kids you can see there's some similarities in phenotype. One of the most pronounced believe it or not is this very bulbous nose you can see a pronounced philtrum sometimes protruding tongue as well as a fairly happy disposition which has actually been noted in many of the clinical records. The children have a better outlook than most of us in terms of life and in fact we've now been able to go back and identify from de novo collections being able to show clinicians the data they've been able to identify additional kids using this approach. So one of the interesting parts of this particular we think is a new deletion syndrome the exact same region that we identified as being deleted in the human population was a region that was described a year and a half earlier by Kari Stephenson from Decode as being a site of a common inversion polymorphism in humans and shown here is the region once again this is actually looking at the SEF diversity panel and the black indicating the frequency of that inversion that inversion is essentially restricted largely to Caucasian populations both European and Mediterranean populations have this inversion most common. You'll see once you get into Africa and Asia and Amerindia see very low frequencies of this inversion. Their data suggested this inversion for completely different reasons was associated with increased fecundity and associated with increased combination in these populations that was based on genealogical data from the Icelandic population. So we went back and we looked at our kids to see if they came from haplotypes or if they carried the inversion and to date 19 out of 19 cases all come from this inversion haplotype. So I want to make it clear that we don't know necessarily whether it's the inversion that's predisposing to this micro deletion event or it's something else on that haplotypic background which may be predisposing but the data are overwhelming that this inversion polymorphism which is ethnically stratified is essentially predisposing or the inversion haplotype is one of the ramifications would be that this is largely a Caucasian-specific idiopathic mental retardation syndrome and our screening so far of African Americans has shown no cases of screening of 500 kids of this particular deletion. That wasn't the only one we found so here's another region on 15 Q2 4.1 to 4.2 4 megabases in size these are the children these are their actual genotypes on array CGH over oligos rate points in three of the four cases occur precisely at regions of high sequence identity in these three cases we know that each of these events is de novo these kids are fairly high functioning they have IQs around 65 to 70 they have been described as autistic spectrum disorder but they have extra features such as growth deficiency here's yet a third example this is distal to the Prada-Wooley region on 15 Q1 3.3 our initial screening we skipped over this region and that was because of our criteria this index patient here had a break point between break point 3 and break point 5 actually was not a de novo event so we looked at the parents the mother actually had this very large deletion over this region however it turned out that the mother also had mild mental retardation as well as epilepsy we got two additional cases that came in both of these cases were smaller they were between break point 4 and break point 5 these particular cases were both de novo and in both of these cases there's also mild mental retardation or developmental delay and epilepsy we don't know for sure if this is a genomic disorder but we're betting it is what's particularly interesting is that there is one gene located here, Cherna 7 which is a gated ion channel gene which has been implicated I don't think ever proven to be associated with myoclonic epilepsy so we believe that haplitis efficiency of this region also causes disease and once again the break points are mapping to these very large highly identical duplications the last example that I'll show you is example of recurrent deletion not associated with mental retardation so we've now moved outside of kids with mental retardation started screening kids with other types of pediatric disease and so this is analysis of some of those children this is a collection of roughly 80 pediatric patients with renal disease that have been screened what we found in this particular case was once again a de novo deletion should point out that all of these cases are de novo with respect to break points embedded right within the segmental duplications what's particularly remarkable about this disease is that at least in terms of the studies that we've looked at or the samples that we've looked at this is largely with Christine Belen-Chantelot it accounts for about 20% of pediatric patients with renal disease that they have in their collection so it's a very common what we think is a common micro deletion interestingly enough it's never been observed once in a control group of 927 individuals and interestingly on top of that is essentially that about 36% of children with maturity onset diabetes of the young type 5 also have the same micro deletion there is a gene in this region TCF2 transcription factor in which point mutations have been shown to be associated with both renal disease and modi-5 diabetes so in summary we've actually looked at now a large number of kids particularly from the IMR study these numbers are based largely on the initial 300 set from Oxford and in these patients we identified what we think are roughly 16 sites of novel structural variation I wouldn't claim that the majority of those are causative but I do feel comfortable saying that we do have at least three novel genomic disorders in which we have de novo events recurrence and we have phenotypic similarities that actually allow us to assign this as a new disorder we have one example of a micro deletion event associated with diabetes and renal disease and I'd be willing to hazard a bet that if we screen more children with more forms of pediatric disease we'll actually find additional genomic disorders associated with a wide range of phenotypes I'll just leave this one slide here as an example of why I think this is so important we just finished screening using the Lumina platform with Debbie Nickerson and Greg Cooper in my group a large number of normal individuals these are individuals that came in essentially for lipid testing as part of a study known as the park study and shown here is essentially hotspot regions that were found deleted or duplicated within this normal control group so shown here are the duplications in pink and the deletions shown here in blue these are the number of chromosomes from this collection of roughly 1920 chromosomes that were shown at various frequencies so here is the absolute number, here's the 1% frequency cutoff and here are a bunch of events that are roughly 0.1 and 0.2% frequency so coming back to the point that Richard made two issues that I want you to think about roughly in this group we have 6% to 12% of normal individuals having big deletions precisely over regions that are non-allelic homologous recombination predisposed we have an excess which we don't understand why in terms of deletions versus duplications but we have an absence of things that are around the 1% to 2% to 3% frequency I would bet that these are being fed by these mutations at a high frequency in the more normal pool and the question remains open what is the impact of these in terms of disease or susceptibility so one of the things you might ask yourself is why if you think about the mouse genome architecture and human why do we have all these large blocks of inter-chromosomal and inter-chromosomal duplications if they predispose 10% of our genome to micro-delete and micro-duplicate at a high frequency so we have tried to address this question over the years and maybe I'll kind of go over these fairly quickly but the idea one of the important things to realize about the duplication architecture in these regions it's not just one piece of sequence it's essentially heterogeneous made up of many different parts that have different evolutionary histories and trajectories so this is one of roughly the 400 regions in our human genome and each of the colored and gray are all duplicated so basically this full 790KB stretch of DNA is entirely duplicated when you actually reconstruct the evolutionary history of this region what you find is that everything in color we've been able to show comes from a different area of the genome so we have essentially this hodgepodge mosaic over these specific regions made up of all of these pairwise alignments from all over the genome to complicate matters these regions then duplicate blocks and can share large blocks of homology in common with another and these are the types of events the secondary events that actually predispose to micro deletions and micro duplications associated with disease so we have this architecture can we systematically reconstruct the evolutionary history of these regions and so working with Pavel Pebsner we came up with an approach to look at all the individual pairwise alignments within the human genome then make up these duplication blocks in evolutionary shared segments so we could break all these pairwise alignments into individual subunits and then using data largely from work from UCSC basically compare these regions of the human genome all the duplicated positions to see if we can identify the ancestral segment from where the duplication began therefore provide directionality in terms of the duplications and here the logic is pretty straightforward and primate specific so if we look at outgroup species such as rat, dog and mouse that should not have these regions duplicated we should see a single hit moreover because the human copy that's ancestral moves by this multiple step procedure in terms of duplication we should see more orthologous anchors between the human and a million outgroup sequence so using this approach we define the ancestral origin for 67% of the duplications within the human genome validated by fish to see if we really could identify these ancestral origins so we take an outgroup species we take a probe that comes from the derivative locus and we hybridize to see if it goes back to the right spot that we predicted that confirmed in this case a relatively small number of experiments not out of 12 times we then also compared our experimental maps which we had generated over the years before with our unsilical prediction with Pavel and you can see that there's pretty good correspondence between the duplicons that we identified so what do we learn from this analysis? so here's the part that we learned if we start looking at these intracromosomal duplication blocks that cause disease what we find in almost all cases with one or two exceptions is that shown here is a map of the duplication blocks so these are all the duplication blocks that have emerged in the last 25 million years on chromosome 15 about a third of these cause disease one of the things that we find is that located almost precisely in the center of these blocks is a common sequence in about 90% of the cases at least for this specific chromosome this is what we call a core duplicon it has a number of interesting properties it's the most abundant and most ancient as you might expect in terms of duplications even though these have all heterogeneous histories it is common to the vast majority seems to be the focal point for intracromosomal duplication formation cores are frequently duplicated as solo elements in the genome but rarely are the flanking duplicons so the flanking duplicons are almost always exist in association with a core and when you look at the cores they are enriched four to five fold for both genes, at least annotated genes per base pair as well as ESTs so these seem to be the most transcriptionally active most dynamic areas of the genome when we compare those cores and we find them on about a half a dozen human chromosomes that have experienced this burst of intracromosomal duplication what we find is that these cores are often associated with great ape and human specific gene families that have been described in the literature over the last five or six years we describe one of the first called the nuclear pore interacting protein which evolves about 50 times faster than most normal genes based on DNDS ratios there's a number of other genes that have been described the common features of these genes is they do not have orthologs in mouse they have multiple copies in human and chimp they show dramatic changes in their expression profile compared to at least out group species such as baboon or macaque and at least three of the four examples here show signatures of positive selection and in two cases very dramatic examples of positive selection so I'll just finish off by actually sharing with you some of the work we've been able to do with Eric and NIST particularly in this regard because these regions are so complicated we really can't get a handle on their architecture from looking at whole genome shock and sequence assemblies of chimpanzee gorilla, macaque and so on so working with Eric we've been able to actually target these regions and re-sequence them systematically in a number of primate species so shown here is another core region just to give you an idea these are all the locations of these cores and this is I should say these duplication blocks so this is about 250 kb in size and there's this core of roughly 20 kb which is an 18 of the or the 14 of the 16 blocks that are shown on this chromosome this is a core which is particularly interesting as it has a very rapidly evolving gene family embedded within it this is the nuclear pore interacting protein such that if you look at the actual degree of sequence identity in sliding windows across this region of the genome this is actually comparing any two of these copies you will find troughs and peaks in terms of the sequence identity and what's most remarkable is that these troughs correspond precisely to the position of exons this is this 8 exon gene which with no known function and the other thing I'll just point out is that 98% of these changes are resultant amino acid changes between the copies this is an extreme example of positive selection so working with Eric we drilled down and looked at a lot of other copies in other primates particularly focusing on gorilla, chimpanzee, orangutan, and baboon we sequence annotated all of the sequences that we got back both experimentally and computationally then we constructed a phylogeny of these segments so I hope you don't go blind but this is the actual phylogeny shown here this is based on a neighbor joint analysis of 2KB of non-coding sequence for the core and shown here is the structure that you see with HSA representing human, PTR representing chimp, GGO representing gorilla, and so on so what we get from this bewildering complexity over this part of the genome are really a couple things number one, all of this architecture that we now see which we now know causes disease is about 10 million years young so all the events have occurred in the common ancestor of chimp, human, and gorilla or immediately after the separation of those species the second thing which I think is really interesting is that when we look at orangutan we find none of the core we see the core once again present but we see completely different flanking duplicons which are unique in human and all the other great ape species so orangutan has done the exact same thing that our genome did 7 million years ago and has been doing the same core but has actually picked up completely different flanking sequences which are unique in chimpanzee unique in gorilla and unique in human so this tells us that this core is actively transducing we think segments of the genome around and just to give you a perspective back now 25 million years ago these are all the pieces that in human look like this sorry so this is the architecture that we see in human each one of these blocks of sequence are essentially unique in baboon they're unique in macaque so we think these all began as unique copy sequences with the core beginning to jump probably about 20 million years ago pick up flanks and continue to grow such that it now occupies LCR 16a and its associated duplicons about 10% of the U chromatin of human chromosome 16 in this case 16p with large insert sequences we also map the locations in orangutan and so this is the orangutan picture this is human 16 very limited activity on human 16 but here you see on chromosome 13 the core has essentially jumped jumped to a new chromosome and begun to do its dance again on these particular chromosomes creating a very complex architecture once again on chromosome 13 interspersed duplications distributed across in this case chromosome 13 so here I think the important point is the cores are mobile they can jump to new chromosomes and they can actually transduce flanking sequences as part of its trajectory I don't have time to go into all this data to summarize what we know about this particular core we know that it began as a single copy sequence about 25 million years ago and data that I don't have time to show you indicates that it was actually testis specific is expressed only in the testis and it showed no evidence of selection of any of the normal tests looking at KAKS so this is a little bit heretical I think because most people would teach you that all genes are born from other genes our data suggests that this thing was born from a transcript that was probably neutral in terms of evolution then about 25 million years to 12 million years ago and a common ancestor of orangutan, gorilla and chimpanzee and human it began to move, began to duplicate some copies on this lineage duplicating specifically heavily on chromosome 16 and here duplicating on chromosome 13 at this point when it began to duplicate based on expression analysis in orangutan chimpanzee and human we see ubiquitous pattern of expression it's expressed in every tissue in orangutan and in human that we've ever analyzed to date so we've looked at about a dozen in orangutan and about 32 different tissues in human between 7 and 12 million years ago not on this lineage but in the African great ape human lineage we see extreme positive selection KAKS values on the order of like 10 compared to the old a world monkey sequence suggesting that at that point some mutation must have occurred to lead to an open reading frame that was essentially selective and then became fixed at a very high frequency in the population so the 98% amino acid changes that I mentioned are occurring right here at this branch so we believe that the movement of this core led to the emergence of a novel gene family about 7 million years ago the youngest and most rapidly evolving genes in the human species so in summary, I've talked about the architecture of the human genome with respect to these large blocks of duplication talked about how complex they were and specifically showed you some examples of how these complex architecture can predispose to de novo large deletions probably a huge significant effect or selective effect within the population our targeted approach has uncovered four new micro deletion syndromes that have been shown that they were current de novo and I think the question remains unanswered what is the importance of this mechanism toward complex disease because if you think about it none of these events can be tagged using a tag snip because they're de novo, they're occurring on different in some cases on different haplotypes then I talked about the evolutionary significance of these regions particularly the core architecture that we think has emerged through account and particularly leave you with this kind of final thought maybe the negative selection of these micro deletion and micro duplication events that exist in our species that may be partially offset by the positive effect of having newly minted genes many copies of them at new locations and if you think about it there's a huge challenge ahead even though there are few in number is to work out what are the functions of these types of genes that don't exist in out group species STS and SNP mappers fear to tread and we hope to continue hopefully, I think my students say it's going to be on my epitaph that he found these genes but never actually showed the function of a single one maybe five years from now I can come back and share with you some evidence that they're actually functional so acknowledge these folks Andy Sharp, Heather Mefford they did most of the postdocs that worked on the human disease angle Matt Johnson and Zouxi Jiang they're both students who did all the work of these core regions good colleagues in sequencing centers Baylor Washu and specifically at NISC who rose to the challenge of sequencing some of these very difficult clones I think I have a reputation probably rightly deserved that these are some of the nastiest clones for sequencing centers to sequence thank the patients of people like Bashali Mascari Bob Lakesley and really Jeff Jerry Bouchard who really took these on to completion at least within the primates and a lot of great colleagues clinical colleagues particularly overseas that have been very forthcoming in providing samples and working on collaborations thank you any questions from the floor I'll ask one Richard's got one Richard you got one Evan what about wild mice have you got any duplication data there or they got the same low level of these events nothing on wild mice so no information on wild yet we have a lot of information from the inbreds over the duplicated regions and they show as much variation as humans do the only difference is that variation is restricted to the duplications which are tandem and doesn't influence these unique stretches between the interspersed duplications I want to ask a question we're trying to get a PowerPoint loaded so I'll also install a little Evan so the screen that you did of the pediatric patients the pediatric disease you'd likely find more of these copy number changes but there's no reason to think if you screened unusual adult onset diseases you might find similar we've toyed with the idea and we're thinking about doing a more adult oriented disease I guess I kind of have this fundamental belief that if we can show it at a pediatric level there'll be a stronger genetic component so I'm more interested in screening more kids with disease in which we don't have a good explanation of diseases where environmental play will play a bigger role and genetics might play less


So we have come back to fight supposedly one of the hardest bosses in the game. I got a checkpoint, I had to do other things. Come back. I'm taking this Udan 1v1. Even though it's not 1v1, I know it's got a couple more adds within, but I just can't see from the videos I've seen him standing in the way of my comments there. Even though it's basically the only bit of magic on my build besides the 60 Intellectility to use the commenters there and my staff, which is I think a level 4 or 5. That is it. So I'm going to spawn me wolves in.  Wolves! Go! Wolves! Oh my daisies aren't going well already. He's going to bat me. Hey there you are. Okay, so yeah, I could do up to so many more magic buffs I can do on my build. I just haven't done yet. I started off as a summer. I need to respect to be honest. I need to respect. What was it? Just getting him? Getting him? Ah, I like the way. Do you know I got to a level 130 before I realized I could lock onto enemies? Oh, he's almost dead.   Come at me boy. Come at me. You're done for now. Oh, I can't stand the way of the commenters there. A veteran's prosthesis. Nice. Well, that's it guys. He wasn't too hard whatsoever. Whatsoever craziness. Let's discover that. Nice. So if you guys want to actually know what's on this build, I'll show you now. Almost ended the video there guys. Not going to lie. Okay, so obviously my wolves, which were level seven, these things get to work. I love them. You know what it is? It's aggro. Let's take the aggro away on many bosses. I mean, I can't sponge too much damage, especially upon his higher end bosses, but the aggro is pretty cool. So what I'm using is my baby, my bloodhands fang, but I didn't even fire that or use that in his fight. I'm using the Lucet's Cleanson staff. It's a plus five, which is a decent staff. It actually reels as you get as well. There's so many guys on these guys. And the arm I'm using is just, well, basically tank a bit more damage because I was getting bombed. And that's it really. I'm using the Krimsen Amber Medallion for more HP. I've still got my gold scourbun, just for them more wounds, you know what I'm saying? And I've got this one here. And they carry in the filigree crest, which lowers HP consumed by skills. Also, actually, also it's my flask. I forgot to say that, which is why I get the increased 10 seconds of null HP consumption with this. It's because of my flask. And this just gets to work, guys. This is amazing. Amazing. Like I said, don't mind my build at the minute. It's all over the place, my stats are all over the place. Because like I said, I started as a, I started as basically a samurai.  I'm going to respect though. I'm definitely going to respect and make it a lot stronger because you can do that. But the flask I am using, here we go. I've got this Rulian Hidden Tia, which eliminates all HP consumption in the mix physical. Let's see the 10 seconds of free HP consumption. And then we got temporary boost magic attacks in mixed physical, which is pretty cool as well. So yeah, them two combined. And that's all I've used, guys. And I mean, it destroyed, I am quite high level though. I think my level 169 at the minute. But yeah, but that's what I use, guys. That's what I use. It could be way better. No, you don't have to keep telling me, I know, I know, man. But yeah, guys, it really was no match to be honest. I thought it was going to be a lot harder, but hey, them slower moving bosses with this comment is so easier to target. It's unbelievable. But there we have it, guys. And that's how I beat Commander Nioh. Is it not all Nioh? Is it Commander Nioh? All Nioh is a different one. A different one. But yeah, there we have it, guys. If you enjoyed the video, leave a like. It really helps out. If you like what you see and want to see more, be sure to subscribe. And hopefully, people, I will see you on that next one.