Raw text dump of youtube transcript of Sanford talk

welcome to sense for Sophia's Distinguished Lecture series this morning it is indeed an honor to have the NIH community dr. Sanford is a retired professor Cornell University he received his MS and PhD from the University of Wisconsin in the field of plant genetics as a Cornell University professor he conducted genetic research for over 40 years resulting in more than 100 scientific publications and several dozen patents he he presently presently president of feed my sheep Foundation which focuses on supporting science and technology research initiatives in the area of life sciences dr. Sanford's most significant scientific contributions have been the biolistic process colloquially known as the gene gun of which a prototype is now part of the collection of the Smithsonian National Museum of American history and of which principles have enabled agriculture to grow crops and feed billions in the third world he is co-inventor of the pathogen derived resistance process and co-inventor of the genetic vaccination process he is the formulator and author of the treatise genetic entropy and the developer of Mendel's Accountant a comprehensive numerical simulation of the mutation selection process dr. Sanford was the lead organizer editor of the Cornell symposium and it subsequently published proceedings entitled biological information new perspectives and most recently he is co-author of contested bones a review of paleoanthropology and its current status let us welcome dr. Sanford this morning as he presents an address entitled net genetic loss in humans and bacteria and enviros dr. Sanford would you please accept the podium so I'd like to thank Peter Leeds and the science and philosophy group for inviting me and I'd like to just say that NIH I hold in the highest possible esteem and so it's a great privilege for me to share with you my research from that I've been doing for about the last two decades and that research represents the second half of my career first half of my career involved crop improvement and genetic engineering technologies and for the last eighteen years I've been studying what I would call genetic theory and so I've shortened my title I I was a little too ambitious in what I wanted to cover in a single talk and so the title is human genetic degeneration question mark it's not really a question mark because most of the people in the field of population genetics know that the human race is now has a growing genetic load because of the accumulation of deleterious mutations and so but we need to understand that and so I'd like to share information for you is it's relevant to this very important topic I'd like to distinguish the main concern and the secondary concern I originally got involved in this research because I was interested in the question what can mutation plus selection do and what can it do and so that involved evolutionary theory and problems with evolutionary theory but as I've gotten deeper into the topic more and more I've realised genetic degeneration is a very serious concern for the human race mutations are catastrophic and so I'd like to put the addressing the the concern of human genetic degeneration and what we might do to slow it down as the primary concern so human mutation is catastrophic and so arguably it's one of the primary causes of death and suffering so we know that nearly all non neutral mutations are deleterious and we inherit a multitude mutations from our ancestors and our parents and then from the very first division of our zygote we begin to add new mutations to that genetic load and so we accumulate mutations at the rate of approximately three new mutations every cell division throughout our lifetime and so that growing genetic load is what causes aging and limits the upper life limit of our race we die due to primarily due to a mutation accumulation and tragically that's not the end of it because we pass on the mutations we inherited and the new mutations that we've generated to our children and so children should be more mutant than their parents consistently which is why genetic load tends to accumulate continuously over time so just to put that in perspective it's now widely understood that the human mutation rate is approximately 100 mutations per person per generation and so our children have about 100 more mutations than we have and our grandchildren will have about 100 more mutations than they have so that's very disturbing it's even more disturbing in the population level if there are a hundred mutations per person and there's seven billion people on the planet than there are 700 billion new mutations entering the human population in this generation and so the question becomes what type of selection could eliminate so many mutations that are pouring into the human population so my colleagues and I have been studying this for 18 years it's resulted in about 20 scientific papers and three books and so I can't summarize all that in this short talk but if you go to FMS org that site there's clickable links to all of the relevant papers that I've written on this topic just before we continue I just like to clarify a little bit of vocabulary some people are saying that I'm misusing the word entropy and I just like to clarify that because I believe I'm using the word appropriately so the term entropy is used by physicists in a very specific sense and in a somewhat different sense engineers use that term and people who involved in information theory also use that term and it's not quite the same very similar mathematical formulation but different concepts and so people say well you have to use that terminology but actually I'm using entropy in the generic sense or in the common sense of the word and I'm using it correctly so for example in the merriam-webster dictionary it says broadly the degree of disorder or uncertainty in the system they also say it can mean degradation of matter and energy in the universe to an ultimate state of inert uniformity or the general trend of the universe toward death and disorder or a process of degradation or running down or a trend of disorder normally the form the tech most technical definition of entropy is it's a measure of disorder but more broadly used it's a process where disorder always increases other dictionaries have similar definitions the tendency of a system is left to itself to descend into chaos entropy increases as matter and energy in the universe degrade and the second law of thermodynamics states the entropy must increase in all processes so that's the sense I'm using the term so if I talk about genetic entropy or if I talk about entropic decay of the genome that's what I'm talking about okay so on what basis should we be concerned about genetic degeneration there are four fundamental problems that we should be concerned about and these problems are not widely understood the first one is there are limits to what advantageous mutations do and so advantageous mutations might counteract the effect of the flood of deleterious mutations that are entering the human population but what we'll see is that actually beneficial mutations are rare and seldom can make the type of compensation that's needed to stop the net loss of information secondly natural selection is severely constrained by something I call selection interference and it's because selecting for one trait interferes with selecting for another trait and when you have billions of traits segregating in the population then the selection process starts to work against itself and you are end up only being able to select the best or worst mutations the third problem is that the deleterious mutations are pouring into our population much faster than they can be selectively removed and then lastly most mutations are not neutral although that's the common conception most mutations are nearly neutral and that totally changes the implication okay so let's start by talking about the limits of beneficial mutations so Darwin believed that Fitness would increase continuously through natural selection but he didn't know what natural selection was acting on he didn't know about genetics or Mendel or mutations and so his book really is largely philosophical and conceptual it's not really subject to testing because really there was no way to know what was being transmitted but with the coming of Ronald Fisher decades later Fisher brought mathematical rigor to the understanding of selection and he is really the father of population genetics holding and right also contributed that he was really the one who got it started and it started with his book genetical theory of natural selection and his thesis he proves in his book that what he calls the fundamental theorem of natural selection and the essence of what he proved claimed that Fitness would always increase universally and automatically most biologists know that's not true but it's been held up as a mathematical proof that the things are going better not worse and that and that that's like a mathematical certainty he stated that very strongly he said this is like a natural law and actually the law he likened it to us entropy or the second law of thermodynamics this famous person and his famous theorem probably the most famous theorem in biology was accepted uncritically for about 90 years and so last year a mathematician and I critically assess his formulation and found that there had a major problems with it it wasn't a complete and it had someone at one of the most foundational premises for his mathematics was the assumption that mutations had a net neutral effect and so we now know that's clearly wrong so it requires a reformulation of his theorem we have to include mutations in the equation and that's what we published on in mathematical biology last year so here's how he envisioned he envisioned mutations to be arising with their mutational effect ranging from very bad to very good with neutrals being centered so they pictured a balance of good and bad mutations so that he could just ignore the impact of mutations because they were having that neutral effect the problem is we now know beyond any doubt that beneficial mutations are very rare and that non neutral mutations are consistently deleterious as you'd expect from typographical changes in a text so here's a very strong quote which i think is right on by Kitely and Lynch they say the vast majority of mutations are deleterious and this is one of the most well established principles of evolutionary genetics supported by both molecular and quantitative genetic data and so that's a very strong statement it's the most one of the most well established principles and I show two other papers that have similar conclusions the first one has a subtitle wither beneficial mutations and in that paper the author argues that benefices are so rare we can't measure how rare they are garish and Lenski actually look at biological data they have the long term evolutionary experiment with bacteria and they actually monitored the sequence changes over time in bacterial populations and found that the beneficial mutations were indeed exceedingly rare they estimated one in a million mutations is beneficial so that just puts it in perspective so Fisher's formula is I'm not going to I'm not a mathematician and I'm not going to talk much about math but basically Fisher's formula was very simple he said that the increase in fitness over time was due to only one thing and that was the amount of genetic variability in the population and so he doesn't have a factor of mutations because as we said he looked at in the mutations cancel each other out and so the mutational effects don't matter so since we know that's wrong based nurs formula my my collaborators formula says that fitness over change depends upon the pre-existing variation in the population plus the effect of mutations which are and the net effect of the mutations is always very skewed toward a deleterious effect so basically variation in the population allows you do to do selection that tends to increase fitness the mutations that pour into the population are overwhelmingly deleterious they tend to decrease Fitness so Fitness gain is not at all certain in fact when we actually plug in realistic biological parameters increasing Fitness is very very problematic and so basically our research has flipped his theorem the Fisher's theorem has gone from proving that Fitness is always increasing to indicating that Fitness is actually it's very difficult you need very extraordinary parameter settings to actually get and that gain and fitness so I organized the symposium at Cornell a while back on the topic of biological information new perspectives and the proceedings are available I have a synopsis for people who are interested you don't want to read the whole proceedings but the synopsis is useful so let see me afterwards it's that if that interests you but that symposium addressed the question what is biological information secondly where does it come from how does it arise and thirdly can it be sustained or is biological information inherently subject to entropic decay and so one of the things we found and published in that Proceedings was that most beneficial mutations are too subtle to be selected they're invisible to natural selection and so I just going to take a few seconds to explain this this figure from the paper these are Fitness effects and so total neutrality would be here so here art would be neutral over here would be extremely beneficial things things that would increase here would be where a single mutation can increase fitness by 10% and so you have a continuum of fitness effects one means that that a given Fitness effect is accumulating just as if there's no selection and what we see is that the vast majority of beneficial mutations don't get selected until we get into the really high impact beneficials and this is a visually a little bit deceptive because this is a log scale so the vast majority of mutations are too subtle to be selected and only the best mutations get amplified so not only as our beneficial is very rare but they are overwhelmingly nearly neutral unselectable but take a minute to explain this because it's critical to understanding the issues that we're dealing with if this is a distribution of fitness effects with zero being neutral mutations okay what we have is three things to observe first of all the mutations under this curve are vastly more abundant than the rare mutations that are to the right of zero number two the curves are very steeply crowded towards zero so that most mutations are nearly neutral and the exact shape of the curve doesn't change what happens just any curve like this that are where you have mostly have low impact alleles means that there's a problem the third point is that there is a no selection zone where natural selection can't see those mutational effects and so there's a significant zone exactly how wide it is depends upon numerous variables but there is a no selection zone so in this area basically mutations accumulate as if there's no selection there are things over here that can be selected away but those are that depends on numerous variables and there are very rare beneficials where you can get a really significant impact and these can actually increase net fitness but they are very isolated and so there's a limit to what they can do so we've done thousands of numerical simulations with different parameters what we see is that using realistic parameters we always seen that loss of information that loss of fitness but we can get if we have enough beneficials and if there are enough high-impact beneficials we can create a situation where our numerical scores within a simulation do - just a few extremely beneficial mutations can more than compensate for large numbers of low-impact deleterious mutations you can go okay well that's interesting is but that's just a few good mutations trying to balance out thousands of bad mutations is there a problem with that the problem is this leads to increasing fitness only in a narrow artificial sense in a broader sense the whole genome is still big good degenerating because while a few nucleotide sites are being improved huge numbers are being degraded this type of trade-off is not sustainable as it results in a shrinking functional genome basically you're throwing out lots of information from lots of nucleotide sites and you're trying to replace all that information with a single desirable point mutation so that's that's something that we've been researching in depth realistically there are a few extremely beneficial mutations mostly they're reductive for example sickle cell anemia is an example of a beneficial mutation it has a very significant impact but it's actually reductive that is it's a broken gene broken protein broken cell and it's in the long run not taking things forward it's actually degrading so one more point I'd like to make in terms of beneficial mutations is that when you're trying to increase information or compensate for loss of information usually single point mutations acting here there and everywhere in the genome don't add up to the type of information that's being degraded a single point mutation can kill a gene but it's really hard to improve a gene unless you can change strings of nucleotides it's a little bit like this it random letters in the alphabet don't have information but if you put them into words you can start to build information so we need words really to enhance or compensate a genome so my colleagues and I have published a paper a few years ago the waiting time problem in a model home Ihnen population so taking into consideration a pre human population with the population size of about 10,000 how long does it take to take two nucleotides in that genome and switch them to two other nucleotides at the same location that's that that's the waiting time does it might be what you think thousands maybe millions of years to wait for that well takes a lot longer than that so turns out that here we have a graph where this is the string length a string of two would be a dinucleotide where you're gonna change two letters three up to eight so really small genetic words so to speak and on this scale we have time and you'll notice it's being measured in billions of years well what's with that so let's just go walk through this and we'll try to understand why the waiting time is so long first of all if you're just waiting for a single mutation for a single nucleotide change and you're waiting for that change to actually catch hold in the population and be selected to fixation it's surprisingly long just to make a single specific nucleotide change about 1.5 million years so the ape to man timeline is about 6 million years so this is only changing one letter so if you're waiting for a string of 2 it takes 84 million years if you're waiting for a string of 3 which would be let's say as create a new codon change an amino acid 376 million years and it goes up from there for a string of eight it takes which would be a short genetic word you need more time than the universe has had this sounds crazy right this paper is rock solid and has been read by 10,000 people and there's been no serious critique so it's it's it I'd be happy to if you read the paper and you'll see it's really solid so there's a huge waiting time in terms of even creating small amounts of information that's more than simple letter changes single letter changes so the conclusion for beneficial mutations is for many reasons rare beneficial mutations cannot sufficiently compensate for the relentless influx of deleterious mutations that's the bottom line and there's it's just really strong second so selection is limited by selection interference Holliday's dilemma Aldens dilemma is a famous problem that was recognized by Halden who was the second most important founder of neo-darwinian theory so first Fisher gave us neo-darwinian theory and then Halden expanded upon it but well into his career he realized there was a major problem and so let me just read to you about he he said his paper and 57 titled the cost of natural selection how much does it cost to select away the unfit that's the question there's a cause the cost of selection is individuals in a population have to prematurely die and so you can only do selection to the extent you have a surplus population and once you've used up that surplus population selecting for certain things you can't select anymore so if you're selecting for trying to select for too many things at once you have to eliminate too many individuals in the population the population will start to shrink and we'll go to extinction so here's the way he describes it natural selection cannot occur with great intensity for a number of characters at once he says if two species differ at a thousand different locations or if you have basically to get a thousand mutations substituted the mean rate of generation substitution as has been suggested is one for 300 generations it takes a least 300,000 generation which is six million years to get a thousand mutations fixed a thousand beneficials fixed he says even the geological time scale is too short for such processes to go on and respect to thousands of Llosa I am convinced that the quantitative Garga montz in this kind put forward here should play a part in all future discussions of evolution that's how profound he thought this problem was it should be the center of discussion and the issue is how much selection can you do effectively because selection involves elimination of individuals Holden's dilemma was actually the reason that Kimura developed a neutral theory of evolution so chimera realized Holliday knows right he's at Aldens well-known estimate a new allele may be substitute in a population every 300 generations and at the rate of one substitution of every two years he says the substitutional load becomes so large substitutional load means how many individuals have to be selected away within a population that's the cost the substitutional load becomes so large that the mammalian species could not tolerate it he ends up by saying compared to how all Dane the firm for all dance forms of the cost is larger he's saying Halden underestimated the problem and then he gives an example of how much you know to see the amount of polymorphisms we see in the human population we would need each parent to have three million offspring so you can select away all the two that's this that's the problem and so he said that doesn't work mathematically there are no species that makes certainly not people where you can have an average of 3 million progeny per female and so he said most of the genetic change most of the polymorphisms we see in the human genome must be due to neutral mutations therefore most of the genome must be junk but it's based upon this idea of the cost of substitution mueller expanded upon this so mueller is the only population geneticist to get a new nobel prize he got a Nobel Prize for showing that radiation increases mutation rates and he was very concerned with human genetic degeneration and so one of the things he realized as he considering the problem of human degeneration is that if you have linkage groups you know the human genome was made up of linkage groups and so there's a typical linkage group is 30,000 letters long so mutations in that linkage group are linked forever basically and so if you have lots of bad mutations entering that linkage group and basically the linkage group is reducing and fitness continuously if you throw in one or two beneficials they just get neutralized by the large of deleterious so linkage is a killer it means every linkage block needs to degenerate and so he originally formulated it this is a problem for asexual species because you can't break apart the good and the bad genes so you can't get selection to work but it doesn't just apply to asexual species it applies to every linkage block in the human genome that problem is Mueller's ratchet because the ratchet is that a linkage group can only get worse it can never get better okay solo is the scientist who took that an issue and analyzed it in terms of just human mitochondrial DNA so infinitesimally small part of the human genome and he concluded that a surprisingly large range of biologically realistic parameter combination should have led to an extinction of the evolutionary line leading to him as within 20 million years well 20 million years is so long you know we're not most of us too worried about how much we're going to degenerate in the next 20 million years but the problem is he's only looking at a tiny tiny fraction of the genome so if you consider all the linkage blocks in the genome not just this one the problem is becomes very significant and then even in the near term the bottom line of this issue is that the near neutral box gets bigger meaning the part of the genome that's unselectable gets broader depending upon different types of noise like environmental noise and other issues but the biggest interfering factor for selection is the other mutations if you have too many mutations good and bad everything cancels out and you have a huge no selection zone conclusion in terms of this problem is that as mutations accumulate selection interference gets worse and worse and so selection efficiency progressively breaks down such that only the best and the worst mutations are selectable thirdly is the issue of the flood of deleterious mutations pouring in to the human population so if mutation rate is too high natural selection cannot remove the mutations as fast as they arise so again coming back to Mueller the Nobel laureate so he in 1950 wrote the paper are a load of mutations and here's what he says it's a straw it's surprising what he says actually his whole paper is surprising but here's what he says about the the the critical mutation rate he was very very concerned that we were near the tipping point and where mutations if the mutation rate goes to high human race must degenerate and if it continues all the way to extinction so he was extremely concerned about this a major concern at that time was nations were using nuclear testing and open in the open air so there was radiation floating throughout the atmosphere of the world he's saying we may be destroying the human race in the long run by doing that so he wanted to know the shipping point he says the upper mutation rate that beyond which equilibrium is impossible must be much lower than 0.5 that means half a mutation per person per generation is too high and he goes on to say it might even be as low as 0.1 one mutation in ten individuals of regeneration even he says if selection were to be given full scope so he was a eugenicist he would have said let the unfits perish don't let them reproduce but he's he's assuming intense selection by the way our numerical simulations we always assume our default parameter setting is half of the population has removed every generation so we're doing very intense selection in our numerical simulations much more than Muller would have said would be reasonable so let's look at the numbers behind Mueller's estimates so a lot of population geneticists have looked at this issue and they've come up with an equation Nachman and Crowell will publish the equation but apparently Kimura was already doing making similar calculations and it's apparent that Muller was doing similar calculations but so here's a formula that tells us how much of a population must be selectively eliminated depending on you he is a constant U is the number of deleterious mutations for person for generation so you it can tell us how much elimination is needed or a different formulation it tells us how many offspring per female are required to stay ahead of the bad mutation so you can select away the bad mutations as they accumulate for a mutation rate of 0.1 which was Mueller's estimate that requires 10% selective elimination now when I say 10% selective elimination I'm not talking about normal juvenile deaths like due to car accidents or Wars or pestilence I'm talking about where people are dying because they are distinctly inferior to the people around them so selective elimination doesn't include all that accidental death it has to do with Fitness based death so this is actually a very this is kind of an upper limit a lot of Genesis would say yeah 10% of the population being select their way is a realistic number so that's manageable but if the mutation rate goes to 1 it actually becomes problematic you have to get rid of 63 percent of the population and that means minimally even after the accidental deaths 5 point 4 offspring per female so the to certain can survive mutation rate of 2 it goes up to 14 children per female and for mutation rate of 3 you need 40 offspring per female not including the accidental deaths so this is the Nachman and crawl paper basically they were measuring 175 new mutations per generation there they're off a little bit but doesn't matter the genetic load associated with such a high you would be intolerable they go on to say for you equals 3 deleterious mutation rate of 3 per person per generation each fail would need to produce 40 offspring as our calculations show and this assumes all mortalities due to selection so basically there's a series of papers that say that here's one that says it is difficult to explain how human populations could have survived a high rate of deleterious mutation where it's they consider a high rate of mutation anything over 1 is a paradoxical to a species with a low reproductive rate and they're going to say deleterious mutation rates appear to be so hi in humans and our close relatives it's doubtful that such species could survive so the interesting thing is they're assuming that the actual mutation rate is down around one or two mutations per generation all of the people I'm going to describe assume that 90 to 99 percent of the genome is junk DNA so that's now very much in doubt it's widely recognized that there's more than three mutations per person per generation they're deleterious so here's another author the implications of mutations of this magnitude for population genetics and evolutionary theory are profound the question of how our species accommodate such mutation rates is central to evolutionary thought so they're saying this is a big deal this isn't some side issue how just looking at the mitochondrial DNA just looking at an infant s in my tiny part of the genome they say we should increase our attention to the broader question of how or whether organisms can tolerate in the sense of evolution a genetic system with such a high mutation burden he's just talking about mitochondrial mutations here's a most recent publication on this issue a book written by Alex Condor Schaaf who was here for a h for a long time now is teaching at Michigan he just wrote a book called crumbling genome and here's a few interesting things coming from his book number one he says in the average human genotype over a hundred genes are dysfunctional or missing and he adds and over a thousand genes are substantially impaired doesn't that make you feel healthy and vigorous knowing that you have carries that much genetic load it's very very concerning he's goes on to say a newborn human carries about a hundred new de novo mutations originated in the germline and he says about 10% of those are substantially deleterious that's a huge thing to say to say that 10% of the genome is functional means that you need 10 mutations per person for generation which goes way over the top in terms of what a population can sustain so we use this quote this this.e formula earlier and basically with ten mutations per person per generation you need 44,000 offspring per female that's not exactly reasonable now den growler has has chided and code the encode project at NIH for considering that perhaps a large fraction of the genome might be functional let's say even eighty percent in which case there would be eighty new mutations per person per generation and he correctly realizes that you need something like ten to the 35th power offspring per female and he calls that Bunker's and i say that dr. growler is totally right that is bonkers but ten to the eleventh is bonkers and forty four thousand children per female is bonkers so all these assumptions assume that their genetic degeneration is not happening and it's clear that all those cognitions are Bunker's mutations are happening at somewhere between ten and eighty percent or some significant part of the genome is functional and that's why people are upset about encode is because if there are a significant part of the genome that's there that's functional then we are experiencing rapid genetic degeneration and so there are many lines of evidence that show this all these paradoxes go away if we simply accept the genome is degenerating which is painfully obvious okay so do people argue against this they do but it's kind of like straw man that they're they're dealing with of course the idea that if it's if it's almost all junk then the mutation rate isn't nearly so high if we could get mutation down to one or two or three mutations well three is over the top isn't it so you need to get down to one or two percent of the genome as functional or genetic degeneration is certain some people have formulated a kind of far-fetched and hypothesis called the mutation I call it the mutation count mechanism where they say well as mutations accumulate mother nature somehow counts the number of mutations per person and then selection is again the people who have high mutation people who have accumulated more mutations are selected away we've done simulations of that and we basically have disproven it you can look it up as under the link I gave you you can read that paper but it's really clear that that hypothesis is not real biologically realistic doesn't work the second explanation is they something called synergistic epistasis mechanism and again we've proven that it doesn't work the idea is if you have lots of mutations that are deleterious as they accumulate they amplify each other's deleterious effect the intensity of degeneration is so great that somehow it improves selection it's just the opposite the way it works and that somehow that that helps all of our simulations show that if we introduce synergistic epistasis it goes to degenerates much faster which is what logic would demand and populations goes extinct quickly all three of these really have been falsified so conclusion in terms of the large number of mutations pouring into the population even if we could solve the other three problems that I described a deleterious mutation rate of three or more ensures continuous jak degeneration the propose of escape mechanisms are not credible they've been falsified so number four the new nutria problem the new nutria problem is a longer term concern but this is the most significant problem and so I want to explain it to you the new nutria problem was first recognized by again Muller who has had such a huge impact and in his Mueller's ratchet paper he didn't use that term that was coined later but in his paper about this intersection interference and the accumulation of more bad Newton's in linkage groups than good mutations he says there comes a level of advantage however that is too small to be effectively seized upon by selection its voice being lost in the noise so to speak well whether you're talking about beneficials or deleterious the idea is most think of it this way you have a genome of 3 billion letters ok and you take out one letter or you change one letter randomly okay is that going to have a huge Fitness effect it's going to have a tiny Fitness effect and in fact it's real it's like it's like rust on a car you can't see each rust event but it is continuous and destructive so the person who studied this most was dr. Tomoko Ulta and she is one of the few female population Genesis she was mentored by dr. Kimura the author of the neutral theory of evolution and he was saying most of the genome is junk and it's just and so it doesn't have any deleterious effect mutations in those parts of the genome she said no most mutations are nearly neutral they're there they're low enough impact they can't be influenced by selection but there's still a problem because they accumulate and so she actually persuaded her mentor and eventually Kim were accepted yeah they're mostly nearly neutral not neutral this is huge because you're all taught that most of the genome is junk in that it's mostly neutral but it's not so here's a recent paper that that clarifies this Walker and Kitely they're talking about the distribution of fitness effects of new mutations and they say it seems unlikely that any mutation is truly neutral in the sense that it has no effect on Fitness all mutations must have some effect even if that effect is vanishingly small so that statement which is which is correct is a game-changer for how we understand what's happening in the genome so here's dr. Crowe one of the most distinguished geneticists of the last century and he's writing at PNAS and he's talking about the mutation rate and is it a health risk and he says the typical mutation is very mild it usually has no overt effect but shows up as a small decrease in viability or fertility he goes on to say for the past few centuries harmful mutations have been accumulating the decrease in viability from mutation accumulation is something like 1 to 2 percent per generation he's saying the human race is degenerating and has been G's generating for a long time at the rate of 1% per generation that's pretty astounding and so it doesn't sound too bad in one generation but if you start with the fitness of one and just have it reduced by one percent for three hundred generations you see a radical decline in fitness and that we see that in our simulations and we see that you know in biological systems as well when this very distinguished nurse is saying we have a problem and that we're degenerating anyone who cares about long-term human health and welfare should take note okay so Kandra Schaaf who used to work here he wrote a paper and the subtitle is why aren't we dead a hundred times over okay and so he says I interpret the results in terms of the whole genome and show an agreement with Takeda that V s DM s very slight deleterious mutations can cause too high a mutational load accumulation of V s DM s in a lineage acts like a time bomb the existence of vertebrate lineages should be limited to like a million generations okay so he's saying this is a huge long term problem but you have to understand he believes that the mutation rate is like one or two mutations well this was earlier he published this earlier what he was thinking the mutation rate was much lower than it really is so it's worse than he says but it is a long term issue so Michael Lynch is one of the people whose most who studied this in the greatest depth and so I just like to quote a few of his papers here is a paper early on that he wrote we find that the accumulation of new mildly deleterious mutations fundamentally alters the scaling of extinction time causing the extinction of populations that would be deemed safe on the basis of demography alone in his 2010 paper more recent paper in PNAS he says he predicts it in the next few centuries we will see one to 5% fitness decline for generations so he's actually more pessimistic than crow and so that's a 5% would be disastrous and he concludes we will see getting capacitation at the morphological physiological and neurobiological levels so he's very concerned he's and again 2016 he published most recently in the United States the incidence of the variety of afflictions including autism male infertility asthma immune system disorders diabetes already exhibit increases exceeding the expected rate and he goes on to say the long-term consequence of such effects is an expected genetic degeneration in the baseline human condition so our own research confirms and further elucidates the things i've been studying so this is one of the papers that we published can purifying natural selection preserve biological information from the same symposium and I just want to show you three very illuminating plots that Mendel's Accountant our numerical simulation consistently reveal the first one is mutation accumulation so we have 5,000 generations here and we have the mutation count per person over time and if you have a mutation rate of 50 which is kind of halfway between 100 and 150 percent functionality in the human genome is not unreasonable in my point of view notice that it goes up like clockwork the upward increase is always a straight line in other words it's very systematic accumulation is incredibly systematic and so basically this the way this is structured is that if there was no selection and we had 50 mutations per person per generation this line would be straight but it would end up right here so during 5000 generations we we read eliminated less than 10% of the bad mutations the rest of the mutations are accumulating as if there's no selection that's a huge problem by the way there are beneficial mutations in that but they don't show up because they're so far down this they're basically bouncing along rate along the bottom of the they're so beneficial happened that there's no way they can counterbalance the deleterious this is the deleterious mutation plot with a log scale we're plotting how much of the mutations that these different levels of fitness effect accumulate so the mutations over here are accumulating just as if there's no selection going on over here we have perfect elimination the high impact deleterious mutations are selected way very effectively we have using codominance with this but the low impact mutations Jesco they it's like rust on the car they just continuously accumulate there's a transition zone where things are accumulating but not as fast at this point right in the middle we're at 0.5 is what we call the throat selection threshold okay so there is a selection threshold the size of the new nutri box is large and so the lastly if we look at the beneficials again we see that and using the same the same experiment is that beneficial is that pretty much not amplified until we get into the high impact and they're there but they they don't even show up in our plots in our mutation count plots so we do end up seeing a crow type decline in a 5,000 generation period we see a radical decline in fitness so that's the near note your problem is a long term process but it's really interesting to know that you know I don't think that this near neutral problem is stoppable it's unstoppable basically so it has implications so in conclusion even if the deleterious mutation rates were less than 1 the nurture problem should very gradually cause the human genome to rust out and degenerate so final conclusions our research over the last almost two decades has validated and elucidated further elicited all of the problems that were already well-known within the field of population genetics just to review the four points in summary benefices cannot keep up with deleterious mutations selection interference profound limits selection efficiency high mutation rates anything above - should cause rapid and degeneration and near neutral should be virtually unstoppable that's the summation of the last 18 years of my research and it's consistent with the history of population genic starting from the founders of neo Darwinian theory all the population geneticists who have carefully examined it have been troubled how can we stop mutation accumulation so what are the implications their humanitarian implications their evolutionary implications there are philosophical implications in terms of human welfare are we seeing degeneration now Alzheimer's and dementia we now consider normal but you know as you just read from the past it wasn't normal for for people as they got old to lose their minds it was normal for the old to be wise and a source of wise counsel so I believe there is a pandemic for those diseases autism it's clear the rates are going up it's clear there's a genetic component aust ISM I believe certain cancers are increasing I believe autoimmune disorders are increasing and that allergy problems other all immunological problems are increasing Lynch was saying maybe this is genic degeneration personally I don't think that mutation rate is increasing so I can't imagine that all that would happen in one generation unless it's epigenetic mutation the whole issue of there's a whole nother layer of information there's entropic degeneration at all levels and so even as there's entropic degeneration of the genome there's also intrapreneur degeneration of the epigenome and so what about epigenetic mutations should we be trying to reduce the rate of epigenetic mutation is it open question it's not my field but I really think we should strive toward reducing mutation rates Lynch suggests in his papers that we just need more death so if we had lots of juvenile death that would mean more selection that's not true most juvenile is due to just bad circumstances and so he suggested well let's go to the third world where there's a high mortality rate and those people will be filtering out the bad mutations that's not correct we can increase selection intensity with our numerical simulations it doesn't stop the problem we can go to eugenics not eugenics won't solve it there's many reasons why gene editing well you could fix one or two mutations that way in a few people but it's not a solution for the human population it doesn't can't be applied to millions of mutations and same thing with zygotic selection so doctor Condor chef talked about these two things as a kind of a hopeful way to go I don't think so because you can't you only for rich people so basically reducing mutation rate would help and we should I believe do everything we can to reduce the somatic mutation rate and to reduce the epigenetic mutation rate my host is the science and philosophy group and it's all been science and now I just feel I have license to share my personal perspective on this even as Lynch encounter chef they've expressed their point of view my personal view is a Christian view and we are dying people in a dying world we all know we're dying people and we're dying by genetic m for entropy it's it's accumulation of mutations which is why everybody in this room is more mutant you were today than you were yesterday our hope is not in this body our hope is not mother earth our hope is in heaven that's a additional biblical perspective I think it matches the data disturbingly well I do not take genetic entropy lightly because I know that it causes so much suffering and so much death but I see it as a reality and so that's why I've been pursuing this research so thank you so much for listening I'm happy to oh one other thing is I said I was going to talk about our virus work and so during question and answer if people on staff happy to discuss that there was a typographical error in the announcement it says that 100% of the influenza virus mutated that's typographical error but 10% of the h1n1 human version of the influenza virus mutated during a 90 year period and yes h1n1 human version did go extinct in 2009 what's circulating now is primarily swine flu versions of h1n1 so I'll end it at that thank you so much yes hello dr. Sanford first of all I just want to thank you for having your talk I'm involved in a fairly significant group and your work comes up quite often my question is a bit of a two-parter first you say did that there was 700 billion new mutations per generation correct at a genome size of 3 billion when we for simplicity sake sticking with point mutations have flipped every single mutation possible multiple times over yes yes basically every possible mutation that could happen in the genome has happened during our lifetime great and then you stated that most mutations are in the non-selection range wouldn't at some point you reach an equilibrium where the deleterious mutations flip and become returned to the previous state so flipping flipping of back mutations are really rare so you'd have either your weight basically the new mutations are flooding in back mutations are exceedingly rare events and so it'd be just as if there was no back there is back mutation but it wouldn't stem the tide thank you I got that right you arguing that the baby differs from both parents by 100 nucleotides yeah 5050 from each parent what is actually the experimental evidence for that we do next-generation sequencing and things of one could test up today is there evidence for that yes so so I think most of the data is coming from parent-child trios and so they're actually doing sequencing of parent and child and so they actually can count the mutations there are parts of the genome where they're not countable like in tandem repeats and things so they make some adjustment for that but the 100 mutations per person per generation now is widely being circulated as the actual mutation rate what fraction is on neutral is debatable yes so have you ever considered situation with some invertebrate species like horseshoe crabs that have been around for you know a long time into the geological record how does the species like that can continue to exist it's really a great question Condor chef actually talks about that he said these these lineages have all should have a lifespan limit and so one one author I didn't include was dr. Fred Hoyle a famous physicist he actually was so interested in this it's been a few years of his life looking at the mathematics of evolution and he concluded DNA is degrading and he said any given piece of DNA has a limited shelf life basically and so he envisioned aliens coming and receiving the planet periodically to make up for how they degenerated genome so so really it's hard to imagine deep time lineages surviving unchanged like the horseshoe crab it's really a conceptual hurdle and and this I think should be acknowledged widely that how if if current oh so one really interesting thing jumping to the virus issue is you know we watched the h1n1 virus go from a red hot pandemic to to a whimper to an extinction event in 90 years there's a paper recently published that say that all RNA viruses of all different families appear to be evolutionarily young meaning tens of thousands of years old whereas you'd think that viruses would date back to millions or billions of years ago and so it's really interesting the time element is I something I don't want to deal with I just want to deal with the present I'm wondering what your starting point is because you're talking about genetic degeneration in humans what what is the point where you're starting from like what's the point where I'm just curious because you have a continuity of humans coming from some ancestor that we wouldn't consider human what is the point that you're starting from that's a good question basically if we start with a population with zero mutations there is a burn in time where it has to reach equilibrium where the it takes time for enough genetic diversity to build up in a zero population popular zero mutation population and so there is a time where it's unrealistic rate is unrealistically high and so we we acknowledge that but we could start anywhere so we could start let's suppose that all the human beings in the world disappeared except the people in this room we could start and say okay the average fitness in this room is one and then we're going to monitor fitness not as reproduction because that's a circular argument we've mounted our Fitness by function you know like IQ or physical strength or things like or longevity those things are a better way to measure it but it's a great question and it is a part of the formulation we do start with mutations with zero mute we start our populations with zero and so that's a factor but we can restart a population once you've reached equilibrium a burn endpoint and we still see the climb thank you for a fascinating talk I was just wondering the mutational load is as you say is very high but there's a lot of redundancy in the function of the human genome and I'm just wondering if anybody has looked at it from that perspective that there are similar functions so maybe a particular mutation may take out a key one key gene but there are redundant systems that can actually take over that function yes so like that gets in a little bit into the philosophy element because it looks to me and a lot of people like the genome is designed to be stabilized by things like diploid e or things like gene family backups or other types of redundancy so redundancy does in in in modern design engineering design we look at redundancy is a really good thing and it is a good thing for our genome and it's interesting because how do you evolve processes that only have long term effects normally selection can only act upon things are short beneficial mutations have a normally a short-term vision of where they're going so to speak so kind of two-part question the first thing is about formulations from Fisher right and the early on population geneticist so those are incredibly useful informal but they're also streaming simplistic and they assume as you're assuming still like 100 years later that Fitness is just one dimensional feature and that the function of selection is to increase Fitness when it's it's probably this multi-dimensional feature and that the function would be of selection would be to maintain the ability to adapt and not increase Fitness that's not that's just the construct that was used mathematically to formalize this and this will be to the second part which is the question should be as was mentioned for other species correct so for bacteria for instance and this has been studied so this could be looked at it if if your predictions are right this should be observed in back to your population they should collapse after a little bit of like measurable amount of time in the lab because they go through a lot of generations and you can measure more accurately the distribution of mutations and the number of generations and even sequence everything and and see the predictions but that doesn't seem to happen okay those are all really good points let's see if I can remember what they were the first one was oftentimes it's not about gain and fitness but adaptation right I totally agree adaptive mutations are are real we can document them they they have value but they don't necessarily increase net net information so I look at adaptation mutations mostly as fine-tuning systems and so in the sense adaptations let a species remain the species because the species can accommodate changing environments the second issue you brought up was multi-dimensional I totally agree that the typical population genetics formulas are crazily oversimplified the reason we went to numerical simulation is we we we do recall our numerical simulations comprehensive because we try to consider all the variables and rather than just like a lot of in the past numerical simulations only simulate some part of evolutionary process or like let's say the rate of drift or the rate of some and they often have simplifying assumptions like truncation selection or no environmental variance things like that so to do good numerical simulations and you have to consider like 30 parameters and they're all adjustable but you can you can so you can look at a wide range of possibilities but you realize you can't reduce this to a formula and so I agree with that your last point was yeah exactly that point if you can reduce it to a formula you can't model realistic systems and then when you look at systems like bacteria oh where this is not happening for so I was talking to bacteria so the bacteria is also a good question so I recently read a paper about reductive evolution in bacteria and the long term Ecola experiment also reflects this is bacteria rapidly adapt to a new medium or a new environment and that's really interesting its adaptation they're not gaining any new function all those experiments usually actually involve reductive evolution for example all of the beneficial mutations in the long term Lensky experiment were loss of function genes were deleted genes were silenced or gene land scenes were downregulated so in one case a promoter which is normally regulated became an unregulated promoter but all that is adaptive fine-tuning there was no new information being created and in fact technically as the bacteria jettisons unnecessary genes for that environment they are actually painting themselves into a corner they won't be able to survive in any other environment so they become handicapped in a sense so there's a 1 another paper on reductive evolution in bacteria where they say they were looking at specific bacteria they said one third of all random deletions increased Fitness has to do with getting rid of any genes that aren't necessary for the moment it's very short term you know the bacteria it works for them short term but if then when they need those genes that they've jettisoned they can't they don't have them so it's a it's a doubt that's even that in my opinion that type of adaptation is entropic thank you yeah thank you for such a provocative talk where you giveth us the thesis that according to current biological paradigms we don't exist but my question is is so much of that thesis hinges on a simple piece of evidence that we don't have a normal distribution of D latias and beneficial mutations and my question really is how can we empirically test this when we can only look to the past and present and we actually don't know the future of mutations a number of geneticists have tried to quantitate the actual distribution of mutations it's actually hard to quantify the new neutrals because they're so neutral that you can't see the effect and so there is a certain amount of assumption there the let's see lost my train of thought your question was how can we know the distribution of mutations sure and so Lansky's experiment is really interesting because they because they were periodically sequencing the population has it changed they could actually determine exactly and and they could determine when mutations are OHS they could see which mutations were beneficial only a tiny fraction were beneficial and they were all reductive so there's that's a quantitative thing also we we did a research on the influenza virus so Rob Carter and I turns out that over the last 70 years or so medical people have been freezing influenza samples and then all those samples for through history were sequenced so we have this historical sequence kind of like the linguistic Linsky situation but with influenza and what we see is that actually let me just show a slide here this is our numerical simulation mutation goes up perfectly linearly and Fitness goes down you know with a fitness decline curve and this is the influenza study that we did Rob gathered sequence data going back to the 30s and what he sees is a strict linear accumulations just from the same way so basically it's clock like 10% of the influenced h1n1 influenza virus mutated and so this is this is Jack entropy at work if it's supported by other people who have been following h1n1 virulence and they show that the decline over since since again records were being kept or actually since the 1918 influenza is that the various declined in the same type of way that that we see in our simulations to the point where in 2009 that human version of h1n1 there's still H 1 N 1 circulating that swine flu but h1n1 went extinct in 2009 so that's clearly indicating that this is not neutral or adaptive this is genetic entropy at work in a biological system where we can measure what's going on there were mutations by the way there are some adaptation there were some beneficial mutations happening but it wasn't enough to stop extinction and these two other curves were two other influenza outbreaks and they similarly underwent entropic decay I didn't go extinct yet but they're clearly headed that way so we do have some biological data ok it's it's think it's true that it's largely theoretical but there's now growing biological data thank you yeah so I really appreciate you showing up and I know I've taken too much time I have a few books that I'm happy to share with you one genetic entropy and one on contested bones if you think you're going to read it you're welcome to a copy the BI NP biological information new perspectives that proceedings is in the NIH library and you can but you don't want to read that proceedings or take you a few months it's 25 really long papers very technical on all the different dimensions to biological information but there's like a synopsis you can read in a few hours which is freely available at bi and P dot work it stands for biological information new perspectives org and there you can download the synopsis for free so if that interests you that's available but thank you so much for your patience [Applause]