nhaliday + gene-drift   16

Use and Interpretation of LD Score Regression
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies: https://sci-hub.bz/10.1038/ng.3211
- Po-Ru Loh, Nick Patterson, et al.


Both polygenicity (i.e. many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield inflated distributions of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from bias and true signal from polygenicity. We have developed an approach that quantifies the contributions of each by examining the relationship between test statistics and linkage disequilibrium (LD). We term this approach LD Score regression. LD Score regression provides an upper bound on the contribution of confounding bias to the observed inflation in test statistics and can be used to estimate a more powerful correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of test statistic inflation in many GWAS of large sample size.

Supplementary Note: https://images.nature.com/original/nature-assets/ng/journal/v47/n3/extref/ng.3211-S1.pdf

An atlas of genetic correlations across human diseases
and traits: https://sci-hub.bz/10.1038/ng.3406


Supplementary Note: https://images.nature.com/original/nature-assets/ng/journal/v47/n11/extref/ng.3406-S1.pdf

ldsc is a command line tool for estimating heritability and genetic correlation from GWAS summary statistics. ldsc also computes LD Scores.
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november 2017 by nhaliday
Effective population size for advantageous mutations | West Hunter
So, with beneficial mutations, the effective population size is very different. Instead of being dominated by bottlenecks, it is more influenced by eras of large population size – more and more so as the selective advantage of the mutation increases. In the limit, if we imagine  mutations so advantageous that they spread  very rapidly, the effective population size approaches the population mean.
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august 2017 by nhaliday
The variance of among-group variance is substantial and does not depend on the number of loci contributing to variance in the character. It is just as large for polygenic characters as for single loci with the same additive variance. This implies that one polygenic character contains exactly as much information about population relationships as one single-locus marker.

same is true of expectation apparently (so drift has same impact on polygenic and single-locus traits)
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may 2017 by nhaliday
Soft sweeps are the dominant mode of adaptation in the human genome | bioRxiv
Detection of 2000 instances of recent human selection, half of which are specific to individual human populations, and many of which affect the central nervous system. Note this doesn’t cover polygenic selection, so it’s a very loose lower bound on how much recent human evolution there has been.

How Sweeps Get Soft: https://westhunt.wordpress.com/2011/09/29/how-sweeps-get-soft/
A puzzling finding from the search for selection in humans is the large number of apparently selected variants versus the apparent absence of high frequency selected regions and regions that have become fixed in our species.

Cochran, John Hawks, and I were involved in some of this work, and we all thought immediately without any discussion that the intermediate frequency sweeps must reflect heterozygote advantage.
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may 2017 by nhaliday
Typos | West Hunter
In a simple model, a given mutant has an equilibrium frequency μ/s, when μ is the mutation rate from good to bad alleles and s is the size of the selective disadvantage. To estimate the total impact of mutation at that locus, you multiply the frequency by the expected harm, s: which means that the fitness decrease (from effects at that locus) is just μ, the mutation rate. If we assume that these fitness effects are multiplicative, the total fitness decrease (also called ‘mutational load’) is approximately 1 – exp(-U), when U is where U=Σ2μ, the total number of new harmful mutations per diploid individual.


interesting, suggestive comment on Africa:
I have reason to believe that few people understand genetic load very well, probably for self-referential reasons, but better explanations are possible.

One key point is that the amount of neutral variation is determined by the long-term mutational rate and population history, while the amount of deleterious variation [genetic load] is set by the selective pressures and the prevailing mutation rate over a much shorter time scale. For example, if you consider the class of mutations that reduce fitness by 1%, what matters is the past few thousand years, not the past few tens or hundreds of of thousands of years.


So, assuming that African populations have more neutral variation than non-African populations (which is well-established), what do we expect to see when we compare the levels of probably-damaging mutations in those two populations? If the Africans and non-Africans had experienced essentially similar mutation rates and selective pressures over the past few thousand years, we would expect to see the same levels of probably-damaging mutations. Bottlenecks that happened at the last glacial maximum or in the expansion out of Africa are irrelevant – too long ago to matter.

But we don’t. The amount of rare synonymous stuff is about 22% higher in Africans. The amount of rare nonsynonymous stuff (usually at least slightly deleterious) is 20.6% higher. The number of rare variants predicted to be more deleterious is ~21.6% higher. The amount of stuff predicted to be even more deleterious is ~27% higher. The number of harmful looking loss-of-function mutations (yet more deleterious) is 25% higher.

It looks as if the excess grows as the severity of the mutations increases. There is a scenario in which this is possible: the mutation rate in Africa has increased recently. Not yesterday, but, say, over the past few thousand years.


What is the most likely cause of such variations in the mutation rate? Right now, I’d say differences in average paternal age. We know that modest differences (~5 years) in average paternal age can easily generate ~20% differences in the mutation rate. Such between-population differences in mutation rates seem quite plausible, particularly since the Neolithic.
more recent: https://westhunt.wordpress.com/2017/06/06/happy-families-are-all-alike-every-unhappy-family-is-unhappy-in-its-own-way/#comment-92491
Probably not, but the question is complex: depends on the shape of the deleterious mutational spectrum [which we don’t know], ancient and recent demography, paternal age, and the extent of truncation selection in the population.
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may 2017 by nhaliday
The deleterious mutation load is insensitive to recent population history : Nature Genetics : Nature Research
Distance from sub-Saharan Africa predicts mutational load in diverse human genomes: http://www.pnas.org/content/113/4/E440.abstract
“Out Of Africa” Bottleneck Is What Really Matters For Mutations: https://www.gnxp.com/WordPress/2017/04/26/out-of-africa-bottleneck-is-what-really-matters-for-mutations/
But there is also a lot of archaeological and some ancient genetic DNA now that indicates that the vast majority of non-African ancestry began to expand rapidly around 50-60,000 years ago. This is tens of thousands of years after the lowest value given above. Therefore, again we have to make recourse to a long period of separation before the expansion. This is not implausible on the face of it, but we could do something else: just assume there’s an artifact with their methods and the inferred date of divergence is too old. That would solve many of the issues.

I really don’t know if the above quibbles have any ramification for the site frequency spectrum of deleterious mutations. My own hunch is that no, it doesn’t impact the qualitative results at all.

Figure 3 clearly shows that Europeans are enriched for weak and moderately deleterious mutations (the last category produces weird results, and I wish they’d talked about this more, but they observe that strong deleterious mutations have issues getting detected). Ne is just the effective population size and s is the selection coefficient (bigger number, stronger selection).

Too Much Diversity: https://westhunt.wordpress.com/2012/11/30/too-much-diversity/
There’s a new paper out in Nature, by Wenqing Fu and many other people, about the recent origin of most variants in protein-coding genes. They conclude that most are less than 5-10,000 year old – younger in Europeans than in Africans. This is a natural consequence of the shape of human demographic history – there was a huge population increase with the advent of agriculture, and more people meant more mutations. That agricultural expansion happened somewhat earlier in the Middle East and Europe than in Africa.


A very few mutations are beneficial, some are neutral and many are deleterious, although the degree of harm inflicted varies widely. So the population expansion also increased the number of bad mutations – but unless selection also relaxed, it would not have changed the per-capita number of deleterious mutations, or the distribution of their effects (what fraction had large, medium, or small effects on fitness). It increased the diversity of deleterious mutations – they are more motley, not more common. The article never talks about that per-capita number, or, if it did , I was unable to winkle it out. It talks about ages and numbers of mutations – but not the mean number, in either of the two populations studied (European Americans and African Americans) . I think it would been a lot clearer, confused fewer reporters, if it had made that distinction. On the other hand, depending on the facts on the ground, talking about mutational load might be a grant-killer. There was a paper earlier this year (with many of the same authors) that used about half of the same data and did mention per-capita numbers. I’ve discussed it.


The paper says that there may be an excess of weakly deleterious mutations in Europeans due to bottlenecks back in the Ice Age. The idea works like this: selection is less efficient in small populations. Deleterious mutations with an effect s < 1/Ne drift freely and are not efficiently removed by selection. This effect takes on the order of Ne generations – so a population reduced to an effective size of of 10,000 for 10,000 generations ( ~250,000 years) would accumulate a large-than-usual number of deleterious mutations of effect size ~10-4. Lohmueller et al wrote about this back in 2008: the scenario they used had a European ancestral bottleneck 200,000 years long, which is A. what you need to make this scenario work and B. impossible, since it’s way before anatomically modern humans left Africa. Back to the drawing board.

disease alleles:
Ascertainment bias can create the illusion of genetic health disparities: https://www.biorxiv.org/content/early/2017/09/28/195768
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january 2017 by nhaliday
Information Processing: Recent human evolution: European height
By studying height, a classic polygenic trait, we demonstrate the first human signature of widespread selection on standing variation. We show that frequencies of alleles associated with increased height, both at known loci and genome wide, are systematically elevated in Northern Europeans compared with Southern Europeans (P < 4.3 × 10^−4). This pattern mirrors intra-European height differences and is not confounded by ancestry or other ascertainment biases. The systematic frequency differences are consistent with the presence of widespread weak selection (selection coefficients ~10^−3–10^−5 per allele) rather than genetic drift alone (P < 10^−15).

good comment (Bates):
The paper doesn't really highlight the fact, but drift looks like a real patsy hypothesis for complex traits: In the "no selection, just drift" neutral world, 1,400+ SNPs all have to have happened to "drift" synchonously from North to South... Hence the p value of 0.0000000000000001 against :-) = No drift ever for complex traits
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december 2016 by nhaliday
Standards Drift | West Hunter
We now know that the fraction of Neanderthal ancestry in coding regions has been gradually decreasing with time since the origin admixture, and is now something half as large as it was originally. There were some useful Neanderthal alleles that were favored by selection, and others that deleterious enough to have disappeared completely, but we’re talking about the general trend.


I’m thinking of it as standards drift. In a populations, alleles are always being selected for compatibility, for working correctly, conferring high fitness, on a particular average genetic background. Each allele has a spec it needs to meet. That spec doesn’t necessarily stay the same over time: obviously changes in environment will make a difference. Drift should matter too: if a given allele becomes more common, even by chance, the specs will change for other alleles that interact with it. But there’s always a spec.

When two populations split, their specs start to drift apart. There’s no genetic equivalent of that iridium meter bar. Function at the organismal level doesn’t change so much, but there are many slightly different ways of achieving that function.


While we’re at it, if there are Pygmies whose genomes are majority ancient Pygmy, their Bantu component is probably slightly incompatible: if left to themselves for a hundred thousand years, they’d probably lose a fair amount of it. Of course they will all be eaten long before that happens.

We don’t see people today with Neanderthal Y chromosomes or mtDNA. I keep hearing people argue that this means that mating between Neanderthal males and AMH females must have produced sterile males, or that matings between AMH men and Neanderthal women were all sterile, or whatever.

That is not necessarily the case. A slight disadvantage is all that would be required to totally eliminate Neanderthal Y-chromosomes or mtDNA.

Imagine that a Neanderthal Y-chromosome reduces the bearer’s fitness by 1%, and that the original frequency of Neanderthal Y chromosomes (after admixture) was 2%.

It’s been something like 1500 generations. The expected frequency is 5.67 x 10-9. In real life it would probably have fluctuated to zero, and of course stayed there.

Understand and remember.

The first problem is that there may not have been enough Neanderthals. Selection is not very effective in removing deleterious alleles when their selective disadvantage is < 1/N. For Neanderthals, some analyses indicate the effective population size was around 1000 (others think it was a large but deeply subdivided population), but the effective pop for mtDNA (haploid and only transmitted by females ) was 1/4th that – so, N ~250. Not very big.

The other, general, problem with mtDNA is lack of recombination. In an asexual lineage, mutations accumulate. Muller's ratchet. The only fix is back-mutation, which is very rare, unless the species population size is huge. Sex, on the other hand, reshuffles: a kid can have fewer deleterious mutations than either parent.

So you don’t expect hominid mtDNA to be in great shape, nearly perfectly optimized. That’s closer to true for nuclear genes. Since hominid mtDNA is not too close to optimal, it’s not a huge surprise if population A has noticeably more effective mitochondria than population B.

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november 2016 by nhaliday
Degenerate Neanderthals | West Hunter
Both papers talk about the likely genetic burden that Eurasians picked up from that Neanderthal admixture. Since East Asians have a somewhat higher level of Neanderthal admixture than people in Europe or the Middle East (~20% more) then they must have even more toxic Neanderthal genes, and Africans the least. This echoes earlier papers that have argued that population history (out-of-Africa bottleneck, Neanderthal admixture, etc) must have increased genetic load in Eurasians.
Evidently extra genetic load has anti-intuitive effects.

interesting: https://westhunt.wordpress.com/2015/11/03/degenerate-neanderthals/#comment-73074


The model allows us to investigate compensatory mutations, which restore fitness losses incurred by other mutations, in a context-dependent manner. We have conducted a moment analysis of the model, supplemented by the numerical results of computer simulations. The mean reduction of fitness (i.e., expected load) scaled to one is approximately n/(n + 2Ne), where Ne is the effective population size. The reciprocal relationship between the load and Ne implies that the fixation of deleterious mutations is unlikely to cause extinction when there is a broad scope for compensatory mutations, except in very small populations. Furthermore, the dependence of load on n implies that pleiotropy plays a large role in determining the extinction risk of small populations.
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november 2016 by nhaliday
The 10,000 Year Explosion - Parting of the Ways
There are plenty of other challenges that humans of that era (~100,000 years ago) never met: for example they never colonized the high Arctic, the Americas, or Australia/New Guinea. Even though Neanderthals and Africans had brains that were as large as or larger than those of modern humans, even though humans in Africa were reasonably modern-looking, modern behavioral capacities did not yet exist. They didn't yet have the spark. Come to think of it, most people today still don't. We'll have more to say on that in a moment.


The Neanderthals had big brains (averaging about 1500 cubic centimeters, noticeably larger than those of modern people) and a technology like that of their anatomically modern contemporaries in Africa, but were quite different in a number of ways: different physically, but also socially and ecologically. Neanderthals were cold-adapted, with relatively short arms and legs in order to reduce heat loss - something like Arctic peoples today, only much more so. Considering that the climate the Neanderthals experienced was considerably milder than the high Arctic (more like Wisconsin), their pronounced cold adaptation suggest that they may have relied more on physical than cultural changes. Of course they spent at least six times as many generations in the cold as any modern human population has, and that may have had something to do with it as well.


Like other early humans, Neanderthals were relatively uncreative; their tools changed very slowly and they show no signs of art, symbolism, or trade. Their brains were large and had grown larger over time, in parallel with humans in Africa, but we really have no idea what they did with them. Since brains are metabolically expensive, natural selection wouldn't have favored an increase in brain size unless it increased fitness, but we don't know what function that those big brains served. Usually people explain that those big brains are not as impressive as they seem, since the brain-to-body weight ratio is what’s really important, and Neanderthals were heavier than modern humans of the same height.

You may wonder why we normalize brain size by body weight. We wonder as well.

Among less intelligent creatures, such as amphibians and reptiles, most of the brain is busy dealing with a flood of sensory data. You’d expect that brain size would have to increase with body size in some way in order to keep up. If you assume that the key is how much surface the animal has, in order to monitor what’s causing that nagging itch and control all the muscles needed for movement, brain size should scale as the 2/3rds power of weight. If an animal has a brain that’s bigger than predicted by that 2/3rds power scaling law, then maybe it’s smarter than average. That argument works reasonable well for a wide range of species, but it can’t make sense for animals with big brains. In particular it can’t make sense for primates, since in that case we know that most of the brain is used for purposes other than muscle control and immediate reaction to sensation. Look at this way - if dividing brain volume by weight is a valid approach, Nero Wolfe must be really, really stupid.

We think that Neanderthal brains really were large, definitely larger than those of people today. This doesn’t necessarily mean that they were smarter, at least not as a culture. The archaeological record certainly indicates that they were not, since their material culture was definitely simpler than that of their successors. In fact, they may have been relatively unintelligent, even with their big brains. Although brain size certainly is correlated with intelligence in modern humans, it is not the only factor that affects intelligence. By the way, you may have read somewhere (The Mismeasure of Man) that brain volume has no relationship to intelligence, but that’s just a lie.

One paradoxical possibility is that Neanderthals lacked complex language and so had to be smart as individuals in order to learn their culture and technology, while that same lack severely limited their societal achievements. Complex language of the type we see in modern humans makes learning a lot easier: without it, learning to create even Mousterian tools may have been difficult. In that case, individuals would have to repeatedly re-invent the wheel (so to speak) while there would have been little societal progress.

It could also be that Neanderthal brains were less powerful than you’d expect because there just weren’t enough Neanderthals. That may sound obscure, but bear with us. The problem is that evolution is less efficient in small populations, in the same way that any statistical survey – polls, for example -becomes less accurate with fewer samples.


Our favorite hypothesis is that Neanderthals and other archaic humans had a fundamentally different kind of learning than moderns. One of the enduring puzzles is the near-stasis of tool kits in early humans - as we have said before, the Acheulean hand-axe tradition last for almost a million years and extended from the Cape of Good Hope to Germany, while the Mousterian lasted for a quarter of a million years. Somehow these early humans were capable of transmitting a simple material culture for hundreds of thousands of years with little change. More information was transmitted to the next generation than in chimpanzees, but not as much as in modern humans. At the same time, that information was transmitted with surprisingly high accuracy. This must be the case, since random errors in transmission would have caused changes in those tool traditions, resulting in noticeable variation over space and time – which we do not see.

It looks to us as if toolmaking in those populations was, to some extent, innate: genetically determined. Just as song birds are born with a rough genetic template that constrains what songs are learned, early humans may have been born with genetically determined behavioral tendencies that resulted in certain kinds of tools. Genetic transmission of that information has the characteristics required to explain this pattern of simple, near-static technology, since only a limited amount of information can be acquired through natural selection, while the information that is acquired is transmitted with very high accuracy.


Starting 70,000 or 80,000 years ago, we begin to see some signs of increased cultural complexity in Africa. There is evidence of long-distance transport of tool materials (obsidian) in Ethiopia, which could be the first signs of trade. A set of pierced snail shells (~75,000 years old) in Blombos Cave in South Africa seem, judging from wear, to be the remains of a necklace, although there is no evidence that tools were used to pierce the shells. In that same site, researchers found pieces of ochre with a crosshatched pattern inscribed. We have found manufactured ostrich-egg beads in Kenya that are about 50,000 years old, the first clear examples of artificial decorative or symbolic (that is to say, useless) objects. We see a new kind of small stone points that must have been used on darts that were considerably smaller than previous spears. Although it would seem likely that such darts would have been propelled by atlatls, no atlatls have yet been found that date anywhere near that far back. There are reports of 90,000 year-old bone fish spears from central Africa which, if correct, would be evidence of a significant advance in tool complexity. However, since no other similar tools found in Africa are older than 30,000 years, those fish spears are roughly as anomalous as a Neanderthal-era thumb drive, and we have our doubts about that date. On the whole, the African archeological data of this period furnishes examples of new technology and simple symbolic objects, but the evidence is patchy, and it seems that some innovations appeared and then faded away for reasons that we don’t understand.

A note on behavioral modernity: the consensus seems to be that any clear evidence of a population making symbolic or decorative objects establishes their behavioral modernity, defined as cultural creativity and reliance on abstract thought. For some reason, anthropologists treat behavioral modernity as a qualitative character: an ancient population either had it or not, just as women are pregnant or not, never a ‘little bit pregnant’. It’s treated as a Boolean variable. Like so many basic notions in anthropology, this makes no sense. The components of ‘behavioral modernity’ had to be evolved traits with heritable variation, subject to natural selection – how else would they have come into existence at all? Surely ancient individuals and populations varied in their capacity for abstract thought and cultural innovation – behavioral modernity must be more like height than pregnancy.


The fact the ability to learn complex new ideas and transmit them to the next generation is universal in modern humans suggests that natural selection favored that kind of receptivity. On the other hand, the rarity of individual creativity suggests that the trait itself was not favored by selection in the past, but is instead a rare side effect.

We think that the archaeological record in Africa before the expansion of modern humans shows a gradual but slow increase in such abilities, which is the usual pattern for a trait favored by selection. On the other hand, the rate of change in the European Upper Paleolithic seems faster, almost discontinuous – but there is a well-understood biological pattern that may explain that as well.

The most dramatic evidence of some kind of significant change is the fact that anatomically modern humans expanded out of Africa about 50,000 years ago.
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september 2016 by nhaliday
Information Processing: Evidence for (very) recent natural selection in humans
height (+), infant head circumference (+), some biomolecular stuff, female hip size (+), male BMI (-), age of menarche (+, !!), and birth weight (+)

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.

The 2,000 year selection of the British: http://www.unz.com/gnxp/the-2000-year-selection-of-the-british/

Detection of human adaptation during the past 2,000 years: http://www.biorxiv.org/content/early/2016/05/07/052084

The key idea is that recent selection distorts the ancestral genealogy of sampled haplotypes at a selected site. In particular, the terminal (tip) branches of the genealogy tend to be shorter for the favored allele than for the disfavored allele, and hence, haplotypes carrying the favored allele will tend to carry fewer singleton mutations (Fig. 1A-C and SOM).

To capture this effect, we use the sum of distances to the nearest singleton in each direction from a test SNP as a summary statistic (Fig. 1D).

Figure 1. Illustration of the SDS method.

Figure 2. Properties of SDS.

Based on a recent model of European demography [25], we estimate that the mean tip length for a neutral sample of 3,000 individuals is 75 generations, or roughly 2,000 years (Fig. 2A). Since SDS aims to measure changes in tip lengths of the genealogy, we conjectured that it would be most likely to detect selection approximately within this timeframe.

Indeed, in simulated sweep models with samples of 3,000 individuals (Fig. 2B,C and fig. S2), we find that SDS focuses specifically on very recent time scales, and has equal power for hard and soft sweeps within this timeframe. At individual loci, SDS is powered to detect ~2% selection over 100 generations. Moreover, SDS has essentially no power to detect older selection events that stopped >100 generations before the present. In contrast, a commonly-used test for hard sweeps, iHS [12], integrates signal over much longer timescales (>1,000 generations), has no specificity to the more recent history, and has essentially no power for the soft sweep scenarios.

Catching evolution in the act with the Singleton Density Score: http://www.molecularecologist.com/2016/05/catching-evolution-in-the-act-with-the-singleton-density-score/
The Singleton Density Score (SDS) is a measure based on the idea that changes in allele frequencies induced by recent selection can be observed in a sample’s genealogy as differences in the branch length distribution.

You don’t need a weatherman: https://westhunt.wordpress.com/2016/05/08/you-dont-need-a-weatherman/
You can do a million cool things with this method. Since the effective time scale goes inversely with sample size, you could look at evolution in England over the past 1000 years or the past 500. Differencing, over the period 1-1000 AD. Since you can look at polygenic traits, you can see whether the alleles favoring higher IQs have increased or decreased in frequency over various stretches of time. You can see if Greg Clark’s proposed mechanism really happened. You can (soon) tell if creeping Pinkerization is genetic, or partly genetic.

You could probably find out if the Middle Easterners really have gotten slower, and when it happened.

Looking at IQ alleles, you could not only show whether the Ashkenazi Jews really are biologically smarter but if so, when it happened, which would give you strong hints as to how it happened.

We know that IQ-favoring alleles are going down (slowly) right now (not counting immigration, which of course drastically speeds it up). Soon we will know if this was true while Russia was under the Mongol yoke – we’ll know how smart Periclean Athenians were and when that boost occurred. And so on. And on!


“The pace has been so rapid that humans have changed significantly in body and mind over recorded history."

bicameral mind: https://westhunt.wordpress.com/2016/05/08/you-dont-need-a-weatherman/#comment-78934

Chinese, Koreans, Japanese and Ashkenazi Jews all have high levels of myopia. Australian Aborigines have almost none, I think.

I expect that the fall of all great empires is based on long term dysgenic trends. There is no logical reason why so many empires and civilizations throughout history could grow so big and then not simply keep growing, except for dysgenics.
I can think of about twenty other possible explanations off the top of my head, but dysgenics is a possible cause.
I agree with DataExplorer. The largest factor in the decay of civilizations is dysgenics. The discussion by R. A. Fisher 1930 p. 193 is very cogent on this matter. Soon we will know for sure.
Sometimes it can be rapid. Assume that the upper classes are mostly urban, and somewhat sharper than average. Then the Mongols arrive.
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august 2016 by nhaliday

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