Information Processing

 

Human Accelerated Regions (HARs) are regions of DNA that were conserved throughout prior (e.g., vertebrate) evolution but are significantly different in the human genome.

Allen Institute: ... of the known 3,171 human accelerated regions, 99 percent of these human-specific mutations fall into "non-coding" regions of DNA, or regions of DNA that don't contain instructions for making a protein. Many of them are in stretches of our genome known as enhancers, regions which regulate nearby genes, and about half of those are nestled in enhancers that are active in the developing human brain.

Our analysis of DNA regions used in predictors for common diseases and complex human traits found that large portions of phenotype variance reside in non-coding regions. This has important consequences for pleiotropy and for our understanding of genetic architecture. 

Over the weekend The Guardian and The Times (UK) both ran articles on embryo selection. 

Greg Clark (UC Davis and London School of Economics) deserves enormous credit for producing a large multi-generational dataset which is relevant to some of the most fundamental issues in social science: inequality, economic development, social policy, wealth formation, meritocracy, and recent human evolution. If you have even a casual interest in the dynamics of human society you should study these results carefully... Correction: Height, Educational Attainment (EA), and cognitive ability predictors are controlled by many thousands of genetic loci, not hundreds! For out of sample validation of the Educational Attainment (EA) polygenic score, see Game Over: Genomic Prediction of Social Mobility.

 

Some time ago I posted about The Grisly Folk by H.G. Wells, an essay on Neanderthals and their encounters with modern humans. See also The Neanderthal Problem, about the potential resurrection of early hominids via genomic technology, and the associated ethical problems. 

The Grisly Folk: ... Many and obstinate were the duels and battles these two sorts of men fought for this world in that bleak age of the windy steppes, thirty or forty thousand years ago. The two races were intolerable to each other. They both wanted the eaves and the banks by the rivers where the big flints were got. They fought over the dead mammoths that had been bogged in the marshes, and over the reindeer stags that had been killed in the rutting season. When a human tribe found signs of the grisly folk near their cave and squatting place, they had perforce to track them down and kill them; their own safety and the safety of their little ones was only to be secured by that killing. The Neandertalers thought the little children of men fair game and pleasant eating. ...

William Golding was inspired by Wells to write The Inheritors (his second book, after Lord of the Flies), which is rendered mostly (until the end, at which point the perspective is reversed) from the Neanderthal point of view. Both Wells and Golding assume that Neanderthals were not as cognitively capable as modern humans, but Golding's primitives are peaceful quasi-vegetarians, quite unlike the Grisly Folk of Wells.

The Inheritors 

Golding considered this his finest novel and it is a beautifully realised tale about the last days of the Neanderthal people and our fear of the ‘other’ and the unfamiliar. The action is revealed through the eyes of the Neanderthals whose peaceful world is threatened by the emergence of Homo sapiens. 

The struggle between the simple Neanderthals and the malevolent modern humans ends in helpless despair ... 

From the book jacket: "When the spring came the people - what was left of them - moved back by the old paths from the sea. But this year strange things were happening, terrifying things that had never happened before. Inexplicable sounds and smells; new, unimaginable creatures half glimpsed through the leaves. What the people didn't, and perhaps never would, know, was that the day of their people was already over."

See this episode of the podcast Backlisted for an excellent discussion of the book. 

I am particularly interested in how Golding captures the perspective of pre-humans with limited cognitive abilities. He conveys the strangeness and incomprehensibility of modern humans as perceived by Neanderthals. In this sense, the book is a type of Science Fiction: it describes a first encounter with Aliens of superior capability.

We are approaching the day when modern humans will encounter a new and quasi-alien intelligence: it may be AI, or it may be genetically enhanced versions of ourselves.

On a scientific note, can someone provide an update to this 2013 work: "... high quality genome sequence obtained from the toe of a female Neanderthal who lived in the Altai mountains in Siberia. Interestingly, copy number variation at 16p11.2 is one of the structural variants identified in a recent deCODE study as related to IQ depression"? Here is an interesting follow up paper: Nature 2016 Aug 11; 536(7615): 205–209.

Show Page    YouTube Channel

John Hawks on Human Evolution, Ancient DNA, and Big Labs Devouring Fossils – Episode #6

Hawks is the Vilas-Borghesi Distinguished Achievement Professor of Anthropology at the University of Wisconsin – Madison. He is an anthropologist and studies the bones and genes of ancient humans. He’s worked on almost every part of our evolutionary story, from the very origin of our lineage among the apes, to the last 10,000 years of our history.

Links:

John Hawks Weblog

Ghosts and Hybrids: How ancient DNA and new fossils are changing human origins (Research Presentation)

Transcript

man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

I have written previously about James Crow and R.A. Fisher. Now to Mootoo Kimura.

Wikipedia: Motoo Kimura (木村 資生 Kimura Motō) (November 13, 1924 – November 13, 1994) was a Japanese biologist best known for introducing the neutral theory of molecular evolution in 1968.[2][3] He became one of the most influential theoretical population geneticists. He is remembered in genetics for his innovative use of diffusion equations to calculate the probability of fixation of beneficial, deleterious, or neutral alleles.[4] Combining theoretical population genetics with molecular evolution data, he also developed the neutral theory of molecular evolution in which genetic drift is the main force changing allele frequencies.[5] James F. Crow, himself a renowned population geneticist, considered Kimura to be one of the two greatest evolutionary geneticists, along with Gustave Malécot, after the great trio of the modern synthesis, Ronald Fisher, J. B. S. Haldane and Sewall Wright.[6]

What is the fate of the neutral theory? I suppose the fundamental question is what fraction of molecular changes (mutations) have significant phenotypic effects (i.e., effects on fitness). If the fraction is very small then one could, at the molecular level, adopt the neutral theory as a first approximation. (At the level of phenotypes, I can't see drift dominating unless the effective population size is very small.) Still unsettled?

Wikipedia: ... According to Kimura, the theory applies only for evolution at the molecular level, and phenotypic evolution is controlled by natural selection, as postulated by Charles Darwin. The proposal of the neutral theory was followed by an extensive "neutralist-selectionist" controversy over the interpretation of patterns of molecular divergence and polymorphism, peaking in the 1970s and 1980s. Since then, much evidence has been found for selection at molecular level.

The article Kimura & Crow: Infinite alleles, appeared in Genes to Genomes, the blog of the Genetics Society of America. (See also here ;-)

... Kimura was originally trained as a plant cytologist; he had been fascinated by plants since boyhood, and cytogenetics had been the hot field in Japan at the time. But his interest in chromosomes waned as he began yearning to “do something in genetics like what the theoretical physicists were doing in physics.” This ambition was buoyed by Kimura’s regular, hunger-fueled excursions to the house of his cousin-in-law Matsuhei Tamura, a mathematical physicist. Kimura visited almost every Sunday, partly because he was intensely interested in the quantum physicist’s stories, and partly because he needed to fill his belly during the post-war food shortages.

Kimura joined the lab of Japan’s most famous cytogeneticist, Hitoshi Kihara, who recognized the quiet young man’s talent for theory and left him mostly to his own devices. So, while his friends picked apart the chromosomes of wheat and watermelon, Kimura indulged in the more abstract pleasures of population genetics. He would travel the full-day’s train journey to Tokyo to copy out by hand the papers of Sewall Wright, one of the founders of the field. Determined to understand Wright’s papers, Kimura haunted the math department, attending classes, asking questions, learning from books, until he gradually gained the sophistication to follow Wright’s arguments, and eventually, critique and extend them.

But this new intellectual world was isolating. Kimura’s lab mates took a dim view of his absorption in mathematics and the situation only worsened when he took a job at the newly founded National Institute of Genetics. The facility was housed in the makeshift and uncomfortable office of a wartime aircraft factory. There was no library, no access to foreign journals, and no colleague who could understand his work. The only geneticist there who saw its value was zoologist Taku Komai, who had studied in the fly lab of genetics superstar T. H. Morgan in the United States. Komai recommended Kimura extend his training overseas and introduced him to an American scientist working for the Atomic Bomb Casualty Commission. Before long Kimura had a scholarship, a Fulbright travel award, and a ticket to Seattle.

Once they met, Crow immediately took Kimura under his wing. He invited Kimura over for dinner to meet his idol Sewall Wright. Crow probed Kimura about the paper he had just written on the Pacific voyage and was impressed that it neatly reduced a formidably complex equation down to a simple relationship used by physicists to describe heat conduction. He encouraged Kimura to submit the paper to GENETICS, where Crow was an editor (the paper was later effusively and uncharacteristically praised by its reviewer, Wright).

Always an Eccentric? A Brief Biography of Mootoo Kimura:

This paper suggests that some genetic variants which increase risk of coronary artery disease (CAD) have been maintained in the population because of their positive effects in other areas of fitness, such as reproduction.

Genetic loci associated with coronary artery disease harbor evidence of selection and antagonistic pleiotropy
https://doi.org/10.1371/journal.pgen.1006328

Abstract

Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits. While selection on quantitative traits is much more common, very few signals have been detected because of their polygenic nature. We searched for positive selection signals underlying coronary artery disease (CAD) in worldwide populations, using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk. We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk. These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness. We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductive success is antagonistic. This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans. Lastly, we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines, which further highlights the unique biological significance of candidate adaptive loci underlying CAD. Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD.

Author summary

How genetic variation contributes to disease is complex, especially for those such as coronary artery disease (CAD) that develop over the lifetime of individuals. One of the fundamental questions about CAD––whose progression begins in young adults with arterial plaque accumulation leading to life-threatening outcomes later in life––is why natural selection has not removed or reduced this costly disease. It is the leading cause of death worldwide and has been present in human populations for thousands of years, implying considerable pressures that natural selection should have operated on. Our study provides new evidence that genes underlying CAD have recently been modified by natural selection and that these same genes uniquely and extensively contribute to human reproduction, which suggests that natural selection may have maintained genetic variation contributing to CAD because of its beneficial effects on fitness. This study provides novel evidence that CAD has been maintained in modern humans as a by-product of the fitness advantages those genes provide early in human lifecycles.

From the paper:

... research in quantitative genetics has shown that rapid adaptation can often occur on complex traits that are highly polygenic [29, 30]. Under the ‘infinitesimal (polygenic) model’, such traits are likely to respond quickly to changing selective pressures through smaller allele frequency shifts in many polymorphisms already present in the population [13, 31].

To test for selection signals for variants directly linked with CAD, we utilized SNP summary statistics from 56 genome-wide significant CAD loci in Nikpay et al. [40], the most recent and largest CAD case-control GWAS meta-analysis to date, to identify 76 candidate genes for CAD (see Methods). Nikpay used 60,801 CAD cases and 123,504 controls ...

For a subset of CAD loci, we found significant quantitative associations between disease risk and selection signals and for each of these the direction of this association was often consistent between populations ...

In the comparison across populations, directionality of significant selection-risk associations tended to be most consistent for populations within the same ancestral group (Fig 1B). For example, in PHACTR1, negative associations were present within all European populations (CEU, TSI, FIN), and in NT5C2 strong positive associations were present in all East Asian populations (CHB, CHD, JPT). Other negative associations that were consistent across all populations within an ancestry group included five genes in Europeans (COG5, ABO, ANKS1A, KSR2, FLT1) and four genes (LDLR, PEMT, KIAA1462, PDGFD) in East Asians. ...

... By comparing positive selection variation with genetic risk variation at known loci underlying CAD, we were able to identify and prioritize genes that have been the most likely targets of selection related to this disease across diverse human populations. That selection signals and the direction of selection-risk relationships varied among some populations suggests that CAD-driven selection has operated differently in these populations and thus that these populations might respond differently to similar heart disease prevention strategies. The pleiotropic effects that genes associated with CAD have on traits associated with reproduction that are expressed early in life strongly suggests some of the evolutionary reasons for the existence of human vulnerability to CAD.

Bonus: ~300 variants control about 20% of total variance in genetic CAD risk. This means polygenic risk predictors will eventually have a strong correlation (e.g., at least ~0.4 or 0.5) with actual risk. Good enough for identification of outliers.

Association analyses based on false discovery rate implicate new loci for coronary artery disease
Nature Genetics (2017) doi:10.1038/ng.3913

Genome-wide association studies (GWAS) in coronary artery disease (CAD) had identified 66 loci at 'genome-wide significance' (P < 5 × 10−8) at the time of this analysis, but a much larger number of putative loci at a false discovery rate (FDR) of 5% (refs. 1,2,3,4). Here we leverage an interim release of UK Biobank (UKBB) data to evaluate the validity of the FDR approach. We tested a CAD phenotype inclusive of angina (SOFT; ncases = 10,801) as well as a stricter definition without angina (HARD; ncases = 6,482) and selected cases with the former phenotype to conduct a meta-analysis using the two most recent CAD GWAS2, 3. This approach identified 13 new loci at genome-wide significance, 12 of which were on our previous list of loci meeting the 5% FDR threshold2, thus providing strong support that the remaining loci identified by FDR represent genuine signals. The 304 independent variants associated at 5% FDR in this study explain 21.2% of CAD heritability and identify 243 loci that implicate pathways in blood vessel morphogenesis as well as lipid metabolism, nitric oxide signaling and inflammation.

This is a recent review article (2016):

Genetics of Coronary Artery Disease ...Overall, recent studies have led to a broader understanding of the genetic architecture of CAD and demonstrate that it largely derives from the cumulative effect of multiple common risk alleles individually of small effect size rather than rare variants with large effects on CAD risk. Despite this success, there has been limited progress in understanding the function of the novel loci; the majority of which are in noncoding regions of the genome.

Note Added in response to 2020 Twitter mob attack which attempts to misrepresent my views:

This is not my research. The authors are affiliated with Columbia University and the New York Genome Center.

I do not work on evolutionary history or signals of recent natural selection, but I defend the freedom of other researchers to investigate it.

One has to make a big conceptual leap to claim this research implies group differences. The fact that a certain set of genetic variants has been under selection does not necessarily imply anything about overall differences in phenotype between populations. Nevertheless the work is interesting and sheds some light on natural selection in deep human history.

Racist inferences based on the results of the paper are the fault of the reader, not the authors of the paper or of this blog.




A new paper (94 pages!) investigates signals of recent selection on traits such as height and educational attainment (proxy for cognitive ability). Here's what I wrote about height a few years ago in Genetic group differences in height and recent human evolution:

These recent Nature Genetics papers offer more evidence that group differences in a complex polygenic trait (height), governed by thousands of causal variants, can arise over a relatively short time (~ 10k years) as a result of natural selection (differential response to varying local conditions). One can reach this conclusion well before most of the causal variants have been accounted for, because the frequency differences are found across many variants (natural selection affects all of them). Note the first sentence above contradicts many silly things (drift over selection, genetic uniformity of all human subpopulations due to insufficient time for selection, etc.) asserted by supposed experts on evolution, genetics, human biology, etc. over the last 50+ years. The science of human evolution has progressed remarkably in just the last 5 years, thanks mainly to advances in genomic technology.

Cognitive ability is similar to height in many respects, so this type of analysis should be possible in the near future. ...

The paper below conducts an allele frequency analysis on admixture graphs, which contain information about branching population histories. Thanks to recent studies, they now have enough data to run the analysis on educational attainment as well as height. Among their results: a clear signal that modern East Asians experienced positive selection (~10kya?) for + alleles linked to educational attainment (see left panel of figure above; CHB = Chinese, CEU = Northern Europeans). These variants have also been linked to neural development.

Detecting polygenic adaptation in admixture graphs

Fernando Racimo∗1, Jeremy J. Berg2 and Joseph K. Pickrell1,2 1New York Genome Center, New York, NY 10013, USA 2Department of Biological Sciences, Columbia University, New York, NY 10027, USA June 4, 2017

Abstract
An open question in human evolution is the importance of polygenic adaptation: adaptive changes in the mean of a multifactorial trait due to shifts in allele frequencies across many loci. In recent years, several methods have been developed to detect polygenic adaptation using loci identified in genome-wide association studies (GWAS). Though powerful, these methods suffer from limited interpretability: they can detect which sets of populations have evidence for polygenic adaptation, but are unable to reveal where in the history of multiple populations these processes occurred. To address this, we created a method to detect polygenic adaptation in an admixture graph, which is a representation of the historical divergences and admixture events relating different populations through time. We developed a Markov chain Monte Carlo (MCMC) algorithm to infer branch-specific parameters reflecting the strength of selection in each branch of a graph. Additionally, we developed a set of summary statistics that are fast to compute and can indicate which branches are most likely to have experienced polygenic adaptation. We show via simulations that this method - which we call PhenoGraph - has good power to detect polygenic adaptation, and applied it to human population genomic data from around the world. We also provide evidence that variants associated with several traits, including height, educational attainment, and self-reported unibrow, have been influenced by polygenic adaptation in different human populations.

https://doi.org/10.1101/146043

From the paper:

We find evidence for polygenic adaptation in East Asian populations at variants that have been associated with educational attainment in European GWAS. This result is robust to the choice of data we used (1000 Genomes or Lazaridis et al. (2014) panels). Our modeling framework suggests that selection operated before or early in the process of divergence among East Asian populations - whose earliest separation dates at least as far back as approximately 10 thousand years ago [42, 43, 44, 45] - because the signal is common to different East Asian populations (Han Chinese, Dai Chinese, Japanese, Koreans, etc.). The signal is also robust to GWAS ascertainment (Figure 6), and to our modeling assumptions, as we found a significant difference between East Asian and non- East-Asian populations even when performing a simple binomial sign test (Tables S4, S9, S19 and S24).

James Miller interviews Greg Cochran on a variety of topics.

Some comments on the early part of the interview (you might need to listen to it to make sense of what I write below):

1. The prediction I've made about the consequences of additive genetic variance in intelligence is not that we'll be able to realize +30 SDs of cognitive ability. That would only be true if we could ignore pleiotropy, nonlinear corrections to the additive approximation, etc. What I claim is that because there are +30 SDs up for grabs in the first order approximation, it seems likely that at least a chunk of this will be realizable, leading to geniuses beyond those that have existed so far in human history (this is the actual claim). To doubt this conclusion one would have to argue that even, say, +8 or +10 SDs out of 30 are unrealizable, which is hard to believe since we have examples of healthy and robust individuals who are in the +6 or +7 range. (These numbers are poorly defined since the normal distribution fails to apply in the tails.)

### I could make further, more technical, arguments that originate from the fact that the genomic space is very high dimensional. These suggest that, given healthy/robust examples at +X, it is very unlikely that there is NO path in the high dimensional space to a phenotype value greater than X while holding "robustness" relatively fixed. ###

2. Greg comments on whether super smart people can have "normal" personalities. This is obviously not necessary for them to be viable contributors to civilization (and even less of an issue in a future civilization where everyone is quite a bit smarter on average). He posits that von Neumann might have been radically strange, but able to emulate an ordinary person when necessary. (The joke is that he was actually a Martian pretending to be human.) My impression from reading Ulam's autobiography, Adventures of a Mathematician (see also here), is that von Neumann was actually not that strange by the standards of mathematicians -- he was sociable, had a good sense of humor, enjoyed interactions with others and with his family. He and Ulam were close and spent a lot of time together. I suspect Ulam's portrait of vN is reasonably accurate.

3. The University of Chicago conference on genetics and behavior Greg mentions, which was hosted in James Heckman's institute, is described here, here, and here (videos).


### A masochist in the comments asked for the actual argument, so here it is: ###

Here's a simple example which I think conveys the basic idea.

Suppose you have 10k variants and that individuals with 5.5k or more + variants are at the limit of cognitive ability yet seen in history (i.e., at the one in a million or billion or whatever level). Now suppose that each of the 10k + variants comes with some deleterious effect on some other trait(s) like general health, mental stability, etc. (This is actually too pessimistic -- some will actually come with positive effects!) These deleterious effects are not uniform over the 10k variants -- for some fixed number of + variants (i.e., 5.5k) there are many different individuals with different levels of overall health/robustness.

Let the number of distinct genotypes that lead to (nearly) "maximal historical" cognitive ability be n = (number of ways to distribute 5.5k +'s over 10k variants); this is a huge number. Now, we know of many actual examples of historical geniuses who were relatively healthy and robust. The probability that these specific individuals achieved the *minimum* level of negative or deleterious effects over all n possibilities is vanishingly small. But that means that there are genotypes with *more* than 5.5k + variants at the same level of general robustness. These correspond to individuals who are healthy/robust but have greater cognitive ability than any historical genius.

You can make this argument fully realistic by dropping the assumption that + effect sizes on cognitive ability are uniform, that effects on different traits are completely additive, etc. The point is that there are so many genotypes that realize [cognitive ability ~ historical max], that the ones produced so far are unlikely to maximize overall health/robustness given that constraint. But that means there are other genotypes (off the surface of constraint) with even higher cognitive ability, yet still healthy and robust.

All beings so far have created something beyond themselves; and do you want to be the ebb of this great flood and even go back to the beasts rather than overcome man? What is the ape to man? A laughingstock or a painful embarrassment. And man shall be just that for the superman: a laughingstock or a painful embarrassment. You have made your way from worm to man, and much in you is still worm. Once you were apes, and even now, too, man is more ape than any ape. What is great in man is that he is a bridge and not an end. -- Thus Spoke Zarathustra

The kind of thoughts one has while overlooking Lake Como from a grand villa  :-)

The New Atlantis: Friedrich Nietzsche gets a bad rap, for celebrating the will to power and leaving good morals by the wayside; in growing numbers, Americans are beginning to feel the same uneasy skepticism toward the Silicon Valley moguls who have come to thoroughly dominate our economy and imagination. For critics on the left as well as the right, today’s tech titans are uncomfortably squishy, or indifferent, when it comes to partisan, ideological matters. ...

... As Nietzsche knew, a democratic society like ours is supremely unlikely to produce any bona fide supermen. But supernerds? They’re multiplying like rabbits, and they’ve got an open field. Nothing can stop them; certainly not the rest of us.

According to Peter Thiel, however, that scary conclusion is false, for an even scarier reason. In interviews, speeches, and his new book of adapted college lectures, Zero to One, Thiel — the most political and theoretical of the supernerds — raises the prospect of a remarkably comprehensive failure among our best and brightest.

... Thiel’s critique, it turns out, has much in common with Nietzsche’s: Nietzsche worries that Darwinian competition breeds mediocre humans, while Thiel complains that commercial competition breeds mediocre companies. The principle of incremental success produces no true success at all; instead, it suppresses creative genius.

Zero to One is mainly “about how to build companies that create new things,” as Thiel writes in the preface. ...

Thiel begins by distinguishing between two kinds of technological progress: horizontal progress, which means “copying things that work — going from 1 to n,” and vertical progress, which means “doing new things — going from 0 to 1.” The modern world, says Thiel, “experienced relentless [vertical] technological progress from the advent of the steam engine in the 1760s all the way up to about 1970.”

... “Making small changes to things that already exist might lead you to a local maximum,” he writes, “but it won’t help you find the global maximum.” And with limited resources in a global economy, nothing less than the world is at stake. To find the global maximum, entrepreneurs must “transcend the daily brute struggle for survival” by building “creative monopolies” — creating markets where none exist, rather than dumping their energies into wringing the last marginal dollar of value from markets choked with belligerent competitors. For example, Google, as Thiel points out, has basically held a monopoly over Internet search since the early 2000s. For Thiel, the benefits of creative monopolies extend far beyond the companies themselves. While we typically think of monopolies as exploitative and domineering, “creative monopolists give customers more choices by adding entirely new categories of abundance to the world.”

Creative monopolies require what Thiel calls “definite optimism,” which involves making bold, specific plans for the future, and taking risks to fulfill them. ...

... Overtly, we’re increasingly at the mercy of our technological overlords. Covertly, our social life has become crippled by something so powerful that it can render even the most promising supernerd all but powerless, to say nothing of you and me. Our kryptonite is a cosmic idea, one with which Nietzsche was all too familiar: “the people have won — or ‘the slaves’ or ‘the mob’ or ‘the herd’ or whatever you like to call them,” Nietzsche said about the self-styled democratic free spirits. “‘The masters’ have been disposed of; the morality of the common man has won.” Nietzsche despised this mob-ification of morals. ...

As Francis Fukuyama put it in Our Posthuman Future (2002) ... a division between the metaphorical 1 and 99 percent might come about through a biotechnological revolution — something about which even the most assertive of our supernerds at Google are still cagey. ...

“We live in a world,” Thiel told the Dinner for Western Civilization, “in which courage is in far shorter supply than genius.” As he puts it in Zero to One: “Brilliant thinking is rare, but courage is in even shorter supply.” ...

This new paper describes a technique for detecting recent (i.e., last 2k years) selection on both Mendelian and polygenic traits. The authors find evidence for selection on a number of phenotypes, ranging from hair and eye color, to height and head size (the data set they applied their method to was UK10K whole genomes, so results are specific to the British). This is a remarkable result, which confirms the hypothesis that humans have been subject to strong selection in the recent past -- i.e., during periods documented by historical record.

See this 2008 post Recent natural selection in humans, in which I estimate that significant selection on millennial (1000 year) timescales is plausible. Evidence for selection on height in Europe over the last 10k years or less has been accumulating for some time: see, e.g., Genetic group differences in height and recent human evolution.

How does the new method work?

Strong selection in the recent past can cause allele frequencies to change significantly. Consider two different SNPs, which today have equal minor allele frequency (for simplicity, let this be equal to one half). Assume that one SNP was subject to strong recent selection, and another (neutral) has had approximately zero effect on fitness.  The advantageous version of the first SNP was less common in the far past, and rose in frequency recently (e.g., over the last 2k years). In contrast, the two versions of the neutral SNP have been present in roughly the same proportion (up to fluctuations) for a long time. Consequently, in the total past breeding population (i.e., going back tens of thousands of years) there have been many more copies of the neutral alleles (and the chunks of DNA surrounding them) than of the positively selected allele. Each of the chunks of DNA around the SNPs we are considering is subject to a roughly constant rate of mutation.

Looking at the current population, one would then expect a larger variety of mutations in the DNA region surrounding the neutral allele (both versions) than near the favored selected allele (which was rarer in the population until very recently, and whose surrounding region had fewer chances to accumulate mutations). By comparing the difference in local mutational diversity between the two versions of the neutral allele (should be zero modulo fluctuations, for the case MAF = 0.5), and between the (+) and (-) versions of the selected allele (nonzero, due to relative change in frequency), one obtains a sensitive signal for recent selection. See figure at bottom for more detail. In the paper what I call mutational diversity is measured by looking at distance distribution of singletons, which are rare variants found in only one individual in the sample under study.

Some numbers: For a unique lineage, ~100 de novo mutations per generation, over ~100 generations = 1 de novo per ~300kb, similar to singleton interval length scale. Note singletons defined in a sample of 10k individuals in the current population; distribution would vary with sample size.

Detection of human adaptation during the past 2,000 years
bioRxiv: doi: http://dx.doi.org/10.1101/052084

Detection of recent natural selection is a challenging problem in population genetics, as standard methods generally integrate over long timescales. Here we introduce the Singleton Density Score (SDS), a powerful measure to infer very recent changes in allele frequencies from contemporary genome sequences. When applied to data from the UK10K Project, SDS reflects allele frequency changes in the ancestors of modern Britons during the past 2,000 years. We see strong signals of selection at lactase and HLA, and in favor of blond hair and blue eyes. Turning to signals of polygenic adaptation we find, remarkably, that recent selection for increased height has driven allele frequency shifts across most of the genome. Moreover, we report suggestive new evidence for polygenic shifts affecting many other complex traits. Our results suggest that polygenic adaptation has played a pervasive role in shaping genotypic and phenotypic variation in modern humans.

Jamie Metzl writes in TechCrunch.

Homo Sapiens 2.0? We need a species-wide conversation about the future of human genetic enhancement:

After 4 billion years of evolution by one set of rules, our species is about to begin evolving by another.

Overlapping and mutually reinforcing revolutions in genetics, information technology, artificial intelligence, big data analytics, and other fields are providing the tools that will make it possible to genetically alter our future offspring should we choose to do so. For some very good reasons, we will.

Nearly everybody wants to have cancers cured and terrible diseases eliminated. Most of us want to live longer, healthier and more robust lives. Genetic technologies will make that possible. But the very tools we will use to achieve these goals will also open the door to the selection for and ultimately manipulation of non-disease-related genetic traits — and with them a new set of evolutionary possibilities.

As the genetic revolution plays out, it will raise fundamental questions about what it means to be human, unleash deep divisions within and between groups, and could even lead to destabilizing international conflict.

And the revolution has already begun. ...

See also this panel discussion with Metzl, Steve Pinker, Dalton Conley, and me.

Starting @15:20 you can watch the 2016 Vice documentary Unnatural Selection. Among the topics covered: CRISPR, PGD (Preimplantation Genetic Diagnosis), biobanks, etc. If you've never seen individual sperm and eggs manipulated by a lab tech, this is your chance :-)

And the angel said unto them, Fear not: for, behold, I bring you good tidings of great joy, which shall be to all people.

Mary was born in the twenties, when the tests were new and still primitive. Her mother had frozen a dozen eggs, from which came Mary and her sister Elizabeth. Mary had her father's long frame, brown eyes, and friendly demeanor. She was clever, but Elizabeth was the really brainy one. Both were healthy and strong and free from inherited disease. All this her parents knew from the tests -- performed on DNA taken from a few cells of each embryo. The reports came via email, from GP Inc., by way of the fertility doctor. Dad used to joke that Mary and Elizabeth were the pick of the litter, but never mentioned what happened to the other fertilized eggs.

Now Mary and Joe were ready for their first child. The choices were dizzying. Fortunately, Elizabeth had been through the same process just the year before, and referred them to her genetic engineer, a friend from Harvard. Joe was a bit reluctant about bleeding edge edits, but Mary had a feeling the GP engineer was right -- their son had the potential to be truly special, with just the right tweaks ...

See also [1], [2], and [3].

These recent Nature Genetics papers offer more evidence that group differences in a complex polygenic trait (height), governed by thousands of causal variants, can arise over a relatively short time (~ 10k years) as a result of natural selection (differential response to varying local conditions). One can reach this conclusion well before most of the causal variants have been accounted for, because the frequency differences are found across many variants (natural selection affects all of them). Note the first sentence above contradicts many silly things (drift over selection, genetic uniformity of all human subpopulations due to insufficient time for selection, etc.) asserted by supposed experts on evolution, genetics, human biology, etc. over the last 50+ years. The science of human evolution has progressed remarkably in just the last 5 years, thanks mainly to advances in genomic technology.

Cognitive ability is similar to height in many respects, so this type of analysis should be possible in the near future.

See discussion in earlier posts:
Height, breeding values and selection
Recent human evolution: European height
Eight thousand years of natural selection in Europe
No genomic dark matter

Population genetic differentiation of height and body mass index across Europe

Nature Genetics 47, 1357–1362 (2015) doi:10.1038/ng.3401

Across-nation differences in the mean values for complex traits are common1, 2, 3, 4, 5, 6, 7, 8, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 × 10−8; BMI, P < 5.95 × 10−4), and we find an among-population genetic correlation for tall and slender individuals (r = −0.80, 95% CI = −0.95, −0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58).

Height-reducing variants and selection for short stature in Sardinia

Nature Genetics 47, 1352–1356 (2015) doi:10.1038/ng.3403 

We report sequencing-based whole-genome association analyses to evaluate the impact of rare and founder variants on stature in 6,307 individuals on the island of Sardinia. We identify two variants with large effects. One variant, which introduces a stop codon in the GHR gene, is relatively frequent in Sardinia (0.87% versus <0.01% elsewhere) and in the homozygous state causes Laron syndrome involving short stature. We find that this variant reduces height in heterozygotes by an average of 4.2 cm (−0.64 s.d.). The other variant, in the imprinted KCNQ1 gene (minor allele frequency (MAF) = 7.7% in Sardinia versus <1% elsewhere) reduces height by an average of 1.83 cm (−0.31 s.d.) when maternally inherited. Additionally, polygenic scores indicate that known height-decreasing alleles are at systematically higher frequencies in Sardinians than would be expected by genetic drift. The findings are consistent with selection for shorter stature in Sardinia and a suggestive human example of the proposed 'island effect' reducing the size of large mammals.

I hope you enjoy my essay in the new issue of the science magazine Nautilus (theme: the year 2050), which discusses the co-evolution of humans and machines as we advance in both AI and genetic technologies. My Nautilus article from 2014: Super-Intelligent Humans Are Coming.

Nautilus: ... AI can be thought of as a search problem over an effectively infinite, high-dimensional landscape of possible programs. Nature solved this search problem by brute force, effectively performing a huge computation involving trillions of evolving agents of varying information processing capability in a complex environment (the Earth). It took billions of years to go from the first tiny DNA replicators to Homo Sapiens. What evolution accomplished required tremendous resources. While silicon-based technologies are increasingly capable of simulating a mammalian or even human brain, we have little idea of how to find the tiny subset of all possible programs running on this hardware that would exhibit intelligent behavior.

But there is hope. By 2050, there will be another rapidly evolving and advancing intelligence besides that of machines: our own. The cost to sequence a human genome has fallen below $1,000, and powerful methods have been developed to unravel the genetic architecture of complex traits such as human cognitive ability. Technologies already exist which allow genomic selection of embryos during in vitro fertilization—an embryo’s DNA can be sequenced from a single extracted cell. Recent advances such as CRISPR allow highly targeted editing of genomes, and will eventually find their uses in human reproduction.

... These two threads—smarter people and smarter machines—will inevitably intersect. Just as machines will be much smarter in 2050, we can expect that the humans who design, build, and program them will also be smarter. Naively, one would expect the rate of advance of machine intelligence to outstrip that of biological intelligence. Tinkering with a machine seems easier than modifying a living species, one generation at a time. But advances in genomics—both in our ability to relate complex traits to the underlying genetic codes, and the ability to make direct edits to genomes—will allow rapid advances in biologically-based cognition. Also, once machines reach human levels of intelligence, our ability to tinker starts to be limited by ethical considerations. Rebooting an operating system is one thing, but what about a sentient being with memories and a sense of free will?

... AI research also pushes even very bright humans to their limits. The frontier machine intelligence architecture of the moment uses deep neural nets: multilayered networks of simulated neurons inspired by their biological counterparts. Silicon brains of this kind, running on huge clusters of GPUs (graphical processor units made cheap by research and development and economies of scale in the video game industry), have recently surpassed human performance on a number of narrowly defined tasks, such as image or character recognition. We are learning how to tune deep neural nets using large samples of training data, but the resulting structures are mysterious to us. The theoretical basis for this work is still primitive, and it remains largely an empirical black art. The neural networks researcher and physicist Michael Nielsen puts it this way:

... in neural networks there are large numbers of parameters and hyper-parameters, and extremely complex interactions between them. In such extraordinarily complex systems it’s exceedingly difficult to establish reliable general statements. Understanding neural networks in their full generality is a problem that, like quantum foundations, tests the limits of the human mind.

... It may seem incredible, or even disturbing, to predict that ordinary humans will lose touch with the most consequential developments on planet Earth, developments that determine the ultimate fate of our civilization and species. Yet consider the early 20th-century development of quantum mechanics. The first physicists studying quantum mechanics in Berlin—men like Albert Einstein and Max Planck—worried that human minds might not be capable of understanding the physics of the atomic realm. Today, no more than a fraction of a percent of the population has a good understanding of quantum physics, although it underlies many of our most important technologies: Some have estimated that 10-30 percent of modern gross domestic product is based on quantum mechanics. In the same way, ordinary humans of the future will come to accept machine intelligence as everyday technological magic, like the flat screen TV or smartphone, but with no deeper understanding of how it is possible.

New gods will arise, as mysterious and familiar as the old.

H.G. Wells on the first encounters between modern humans and Neanderthals. See also The Neanderthal problem and Neanderthals dumb?

The Grisly Folk: ... But one may doubt if the first human group to come into the grisly land was clever enough to solve the problems of the new warfare. Maybe they turned southward again to the gentler regions from which they had come, and were killed by or mingled with their own brethren again. Maybe they perished altogether in that new land of the grisly folk into which they had intruded. Yet the truth may be that they even held their own and increased. If they died there were others of their kind to follow them and achieve a better fate.

That was the beginning of a nightmare age for the little children of the human tribe. They knew they were watched.

Their steps were dogged. The legends of ogres and man-eating giants that haunt the childhood of the world may descend to us from those ancient days of fear. And for the Neandertalers it was the beginning of an incessant war that could end only in extermination.

The Neandertalers, albeit not so erect and tall as men, were the heavier, stronger creatures, but they were stupid, and they went alone or in twos and threes; the menfolk were swifter, quicker-witted, and more social — when they fought they fought in combination. They lined out and surrounded and pestered and pelted their antagonists from every side. They fought the men of that grisly race as dogs might fight a bear. They shouted to one another what each should do, and the Neandertaler had no speech; he did not understand. They moved too quickly for him and fought too cunningly.

Many and obstinate were the duels and battles these two sorts of men fought for this world in that bleak age of the windy steppes, thirty or forty thousand years ago. The two races were intolerable to each other. They both wanted the eaves and the banks by the rivers where the big flints were got. They fought over the dead mammoths that had been bogged in the marshes, and over the reindeer stags that had been killed in the rutting season. When a human tribe found signs of the grisly folk near their cave and squatting place, they had perforce to track them down and kill them; their own safety and the safety of their little ones was only to be secured by that killing. The Neandertalers thought the little children of men fair game and pleasant eating. ...

Razib Khan discusses other examples from this genre.

The latest from the Reich lab at Harvard. The availability of ancient DNA allows for direct comparisons between ancestral and descendant populations. These methods will only become more powerful as technology and access to samples improve.

Note the evidence for polygenic selection on height, over timescales of less than 10k years. (Fig. 3 from paper displayed above.) See also Recent human evolution: European height.

Eight thousand years of natural selection in Europe
http://dx.doi.org/10.1101/016477

The arrival of farming in Europe beginning around 8,500 years ago required adaptation to new environments, pathogens, diets, and social organizations. While evidence of natural selection can be revealed by studying patterns of genetic variation in present-day people, these pattern are only indirect echoes of past events, and provide little information about where and when selection occurred. Ancient DNA makes it possible to examine populations as they were before, during and after adaptation events, and thus to reveal the tempo and mode of selection. Here we report the first genome-wide scan for selection using ancient DNA, based on 83 human samples from Holocene Europe analyzed at over 300,000 positions. We find five genome-wide signals of selection, at loci associated with diet and pigmentation. Surprisingly in light of suggestions of selection on immune traits associated with the advent of agriculture and denser living conditions, we find no strong sweeps associated with immunological phenotypes. We also report a scan for selection for complex traits, and find two signals of selection on height: for short stature in Iberia after the arrival of agriculture, and for tall stature on the Pontic-Caspian steppe earlier than 5,000 years ago. A surprise is that in Scandinavian hunter-gatherers living around 8,000 years ago, there is a high frequency of the derived allele at the EDAR gene that is the strongest known signal of selection in East Asians and that is thought to have arisen in East Asia. These results document the power of ancient DNA to reveal features of past adaptation that could not be understood from analyses of present-day people.

From the paper:

... We also tested for selection on complex traits, which are controlled by many genetic variants, each with a weak effect. Under the pressure of natural selection, these variants are expected to experience small but correlated directional shifts, rather than any single variant changing dramatically in frequency, and recent studies have argued that this may be a predominant mode of natural selection in humans40. The best documented example of this process in humans is height, which has been shown to have been under recent selection in Europe41. At alleles known from GWAS to affect height, northern Europeans have, on average, a significantly higher probability of carrying the height-increasing allele than southern Europeans, which could either reflect selection for increased height in the ancestry of northern Europeans or decreased height in the ancestry of southern Europeans. To test for this signal in our data, we used a statistic that tests whether trait-affecting alleles are more differentiated than randomly sampled alleles, in a way that is coordinated across all alleles consistent with directional selection42. We applied the test to all populations together, as well as to pairs of populations in order to localize the signal (Figure 3, Extended Data Figure 5, Methods).

We detect a significant signal of directional selection on height in Europe (p=0.002), and our ancient DNA data allows us to determine when this occurred and also to determine the direction of selection. Both the Iberian Early Neolithic and Middle Neolithic samples show evidence of selection for decreased height relative to present-day European Americans (Figure 3A; p=0.002 and p < 0.0001, respectively). Comparing populations that existed at the same time (Figure 3B), there is a significant signal of selection between central European and Iberian populations in each of the Early Neolithic, Middle Neolithic and present-day periods (p=0.011, 0.012 and 0.004, respectively). Therefore, the selective gradient in height in Europe has existed for the past 8,000 years. This gradient was established in the Early Neolithic, increased into the Middle Neolithic and decreased at some point thereafter. Since we detect no significant evidence of selection or change in genetic height among Northern European populations, our results further suggest that selection operated mainly on Southern rather than Northern European populations. There is another possible signal in the Yamnaya, related to people who migrated into central Europe beginning at least 4,800 years ago and who contributed about half the ancestry of northern Europeans today9 . The Yamnaya have the greatest predicted genetic height of any population, and the difference between Yamnaya and the Iberian Middle Neolithic is the greatest observed in our data. ...

If the analysis leading to the figure below is correct, shifts on the order of 1 SD are possible over timescales less than 10k years, due to natural selection in human populations. Say it with me again: Selection, Not Drift.  (Click for larger version.)