nhaliday + mutation   67

Theory of Self-Reproducing Automata - John von Neumann
Fourth Lecture: THE ROLE OF HIGH AND OF EXTREMELY HIGH COMPLICATION

Comparisons between computing machines and the nervous systems. Estimates of size for computing machines, present and near future.

Estimates for size for the human central nervous system. Excursus about the “mixed” character of living organisms. Analog and digital elements. Observations about the “mixed” character of all componentry, artificial as well as natural. Interpretation of the position to be taken with respect to these.

Evaluation of the discrepancy in size between artificial and natural automata. Interpretation of this discrepancy in terms of physical factors. Nature of the materials used.

The probability of the presence of other intellectual factors. The role of complication and the theoretical penetration that it requires.

Questions of reliability and errors reconsidered. Probability of individual errors and length of procedure. Typical lengths of procedure for computing machines and for living organisms--that is, for artificial and for natural automata. Upper limits on acceptable probability of error in individual operations. Compensation by checking and self-correcting features.

Differences of principle in the way in which errors are dealt with in artificial and in natural automata. The “single error” principle in artificial automata. Crudeness of our approach in this case, due to the lack of adequate theory. More sophisticated treatment of this problem in natural automata: The role of the autonomy of parts. Connections between this autonomy and evolution.

- 10^10 neurons in brain, 10^4 vacuum tubes in largest computer at time
- machines faster: 5 ms from neuron potential to neuron potential, 10^-3 ms for vacuum tubes

https://en.wikipedia.org/wiki/John_von_Neumann#Computing
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april 2018 by nhaliday
The Hanson-Yudkowsky AI-Foom Debate - Machine Intelligence Research Institute
How Deviant Recent AI Progress Lumpiness?: http://www.overcomingbias.com/2018/03/how-deviant-recent-ai-progress-lumpiness.html
I seem to disagree with most people working on artificial intelligence (AI) risk. While with them I expect rapid change once AI is powerful enough to replace most all human workers, I expect this change to be spread across the world, not concentrated in one main localized AI system. The efforts of AI risk folks to design AI systems whose values won’t drift might stop global AI value drift if there is just one main AI system. But doing so in a world of many AI systems at similar abilities levels requires strong global governance of AI systems, which is a tall order anytime soon. Their continued focus on preventing single system drift suggests that they expect a single main AI system.

The main reason that I understand to expect relatively local AI progress is if AI progress is unusually lumpy, i.e., arriving in unusually fewer larger packages rather than in the usual many smaller packages. If one AI team finds a big lump, it might jump way ahead of the other teams.

However, we have a vast literature on the lumpiness of research and innovation more generally, which clearly says that usually most of the value in innovation is found in many small innovations. We have also so far seen this in computer science (CS) and AI. Even if there have been historical examples where much value was found in particular big innovations, such as nuclear weapons or the origin of humans.

Apparently many people associated with AI risk, including the star machine learning (ML) researchers that they often idolize, find it intuitively plausible that AI and ML progress is exceptionally lumpy. Such researchers often say, “My project is ‘huge’, and will soon do it all!” A decade ago my ex-co-blogger Eliezer Yudkowsky and I argued here on this blog about our differing estimates of AI progress lumpiness. He recently offered Alpha Go Zero as evidence of AI lumpiness:

...

In this post, let me give another example (beyond two big lumps in a row) of what could change my mind. I offer a clear observable indicator, for which data should have available now: deviant citation lumpiness in recent ML research. One standard measure of research impact is citations; bigger lumpier developments gain more citations that smaller ones. And it turns out that the lumpiness of citations is remarkably constant across research fields! See this March 3 paper in Science:

I Still Don’t Get Foom: http://www.overcomingbias.com/2014/07/30855.html
All of which makes it look like I’m the one with the problem; everyone else gets it. Even so, I’m gonna try to explain my problem again, in the hope that someone can explain where I’m going wrong. Here goes.

“Intelligence” just means an ability to do mental/calculation tasks, averaged over many tasks. I’ve always found it plausible that machines will continue to do more kinds of mental tasks better, and eventually be better at pretty much all of them. But what I’ve found it hard to accept is a “local explosion.” This is where a single machine, built by a single project using only a tiny fraction of world resources, goes in a short time (e.g., weeks) from being so weak that it is usually beat by a single human with the usual tools, to so powerful that it easily takes over the entire world. Yes, smarter machines may greatly increase overall economic growth rates, and yes such growth may be uneven. But this degree of unevenness seems implausibly extreme. Let me explain.

If we count by economic value, humans now do most of the mental tasks worth doing. Evolution has given us a brain chock-full of useful well-honed modules. And the fact that most mental tasks require the use of many modules is enough to explain why some of us are smarter than others. (There’d be a common “g” factor in task performance even with independent module variation.) Our modules aren’t that different from those of other primates, but because ours are different enough to allow lots of cultural transmission of innovation, we’ve out-competed other primates handily.

We’ve had computers for over seventy years, and have slowly build up libraries of software modules for them. Like brains, computers do mental tasks by combining modules. An important mental task is software innovation: improving these modules, adding new ones, and finding new ways to combine them. Ideas for new modules are sometimes inspired by the modules we see in our brains. When an innovation team finds an improvement, they usually sell access to it, which gives them resources for new projects, and lets others take advantage of their innovation.

...

In Bostrom’s graph above the line for an initially small project and system has a much higher slope, which means that it becomes in a short time vastly better at software innovation. Better than the entire rest of the world put together. And my key question is: how could it plausibly do that? Since the rest of the world is already trying the best it can to usefully innovate, and to abstract to promote such innovation, what exactly gives one small project such a huge advantage to let it innovate so much faster?

...

In fact, most software innovation seems to be driven by hardware advances, instead of innovator creativity. Apparently, good ideas are available but must usually wait until hardware is cheap enough to support them.

Yes, sometimes architectural choices have wider impacts. But I was an artificial intelligence researcher for nine years, ending twenty years ago, and I never saw an architecture choice make a huge difference, relative to other reasonable architecture choices. For most big systems, overall architecture matters a lot less than getting lots of detail right. Researchers have long wandered the space of architectures, mostly rediscovering variations on what others found before.

Some hope that a small project could be much better at innovation because it specializes in that topic, and much better understands new theoretical insights into the basic nature of innovation or intelligence. But I don’t think those are actually topics where one can usefully specialize much, or where we’ll find much useful new theory. To be much better at learning, the project would instead have to be much better at hundreds of specific kinds of learning. Which is very hard to do in a small project.

What does Bostrom say? Alas, not much. He distinguishes several advantages of digital over human minds, but all software shares those advantages. Bostrom also distinguishes five paths: better software, brain emulation (i.e., ems), biological enhancement of humans, brain-computer interfaces, and better human organizations. He doesn’t think interfaces would work, and sees organizations and better biology as only playing supporting roles.

...

Similarly, while you might imagine someday standing in awe in front of a super intelligence that embodies all the power of a new age, superintelligence just isn’t the sort of thing that one project could invent. As “intelligence” is just the name we give to being better at many mental tasks by using many good mental modules, there’s no one place to improve it. So I can’t see a plausible way one project could increase its intelligence vastly faster than could the rest of the world.

Takeoff speeds: https://sideways-view.com/2018/02/24/takeoff-speeds/
Futurists have argued for years about whether the development of AGI will look more like a breakthrough within a small group (“fast takeoff”), or a continuous acceleration distributed across the broader economy or a large firm (“slow takeoff”).

I currently think a slow takeoff is significantly more likely. This post explains some of my reasoning and why I think it matters. Mostly the post lists arguments I often hear for a fast takeoff and explains why I don’t find them compelling.

(Note: this is not a post about whether an intelligence explosion will occur. That seems very likely to me. Quantitatively I expect it to go along these lines. So e.g. while I disagree with many of the claims and assumptions in Intelligence Explosion Microeconomics, I don’t disagree with the central thesis or with most of the arguments.)
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april 2018 by nhaliday
Antinomia Imediata – experiments in a reaction from the left
https://antinomiaimediata.wordpress.com/lrx/
So, what is the Left Reaction? First of all, it’s reaction: opposition to the modern rationalist establishment, the Cathedral. It opposes the universalist Jacobin program of global government, favoring a fractured geopolitics organized through long-evolved complex systems. It’s profoundly anti-socialist and anti-communist, favoring market economy and individualism. It abhors tribalism and seeks a realistic plan for dismantling it (primarily informed by HBD and HBE). It looks at modernity as a degenerative ratchet, whose only way out is intensification (hence clinging to crypto-marxist market-driven acceleration).

How come can any of this still be in the *Left*? It defends equality of power, i.e. freedom. This radical understanding of liberty is deeply rooted in leftist tradition and has been consistently abhored by the Right. LRx is not democrat, is not socialist, is not progressist and is not even liberal (in its current, American use). But it defends equality of power. It’s utopia is individual sovereignty. It’s method is paleo-agorism. The anti-hierarchy of hunter-gatherer nomads is its understanding of the only realistic objective of equality.

...

In more cosmic terms, it seeks only to fulfill the Revolution’s side in the left-right intelligence pump: mutation or creation of paths. Proudhon’s antinomy is essentially about this: the collective force of the socius, evinced in moral standards and social organization vs the creative force of the individuals, that constantly revolutionize and disrupt the social body. The interplay of these forces create reality (it’s a metaphysics indeed): the Absolute (socius) builds so that the (individualistic) Revolution can destroy so that the Absolute may adapt, and then repeat. The good old formula of ‘solve et coagula’.

Ultimately, if the Neoreaction promises eternal hell, the LRx sneers “but Satan is with us”.

https://antinomiaimediata.wordpress.com/2016/12/16/a-statement-of-principles/
Liberty is to be understood as the ability and right of all sentient beings to dispose of their persons and the fruits of their labor, and nothing else, as they see fit. This stems from their self-awareness and their ability to control and choose the content of their actions.

...

Equality is to be understood as the state of no imbalance of power, that is, of no subjection to another sentient being. This stems from their universal ability for empathy, and from their equal ability for reason.

...

It is important to notice that, contrary to usual statements of these two principles, my standpoint is that Liberty and Equality here are not merely compatible, meaning they could coexist in some possible universe, but rather they are two sides of the same coin, complementary and interdependent. There can be NO Liberty where there is no Equality, for the imbalance of power, the state of subjection, will render sentient beings unable to dispose of their persons and the fruits of their labor[1], and it will limit their ability to choose over their rightful jurisdiction. Likewise, there can be NO Equality without Liberty, for restraining sentient beings’ ability to choose and dispose of their persons and fruits of labor will render some more powerful than the rest, and establish a state of subjection.

https://antinomiaimediata.wordpress.com/2017/04/18/flatness/
equality is the founding principle (and ultimately indistinguishable from) freedom. of course, it’s only in one specific sense of “equality” that this sentence is true.

to try and eliminate the bullshit, let’s turn to networks again:

any nodes’ degrees of freedom is the number of nodes they are connected to in a network. freedom is maximum when the network is symmetrically connected, i. e., when all nodes are connected to each other and thus there is no topographical hierarchy (middlemen) – in other words, flatness.

in this understanding, the maximization of freedom is the maximization of entropy production, that is, of intelligence. As Land puts it:

https://antinomiaimediata.wordpress.com/category/philosophy/mutualism/
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march 2018 by nhaliday
Why Sex? And why only in Pairs? - Marginal REVOLUTION
The core conclusion is that mutations continue to rise with the number of sex-participating partners, but in simple Red Queen models the limiting features of the genotypes is the same whether there are two, three, or more partners.

Men Are Animals: http://www.overcomingbias.com/2018/06/men-are-animals.html
I agree with all the comments citing motility/sessility.
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january 2018 by nhaliday
What Does a “Normal” Human Genome Look Like? | Science
So, what have our first glimpses of variation in the genomes of generally healthy people taught us? First, balancing selection, the evolutionary process that favors genetic diversification rather than the fixation of a single “best” variant, appears to play a minor role outside the immune system. Local adaptation, which accounts for variation in traits such as pigmentation, dietary specialization, and susceptibility to particular pathogens is also a second-tier player. What is on the top tier? Increasingly, the answer appears to be mutations that are “deleterious” by biochemical or standard evolutionary criteria. These mutations, as has long been appreciated, overwhelmingly make up the most abundant form of nonneutral variation in all genomes. A model for human genetic individuality is emerging in which there actually is a “wild-type” human genome—one in which most genes exist in an evolutionarily optimized form. There just are no “wild-type” humans: We each fall short of this Platonic ideal in our own distinctive ways.
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november 2017 by nhaliday
trees are harlequins, words are harlequins — bayes: a kinda-sorta masterpost
lol, gwern: https://www.reddit.com/r/slatestarcodex/comments/6ghsxf/biweekly_rational_feed/diqr0rq/
> What sort of person thinks “oh yeah, my beliefs about these coefficients correspond to a Gaussian with variance 2.5″? And what if I do cross-validation, like I always do, and find that variance 200 works better for the problem? Was the other person wrong? But how could they have known?
> ...Even ignoring the mode vs. mean issue, I have never met anyone who could tell whether their beliefs were normally distributed vs. Laplace distributed. Have you?
I must have spent too much time in Bayesland because both those strike me as very easy and I often think them! My beliefs usually are Laplace distributed when it comes to things like genetics (it makes me very sad to see GWASes with flat priors), and my Gaussian coefficients are actually a variance of 0.70 (assuming standardized variables w.l.o.g.) as is consistent with field-wide meta-analyses indicating that d>1 is pretty rare.
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august 2017 by nhaliday
Man's Future Birthright: Essays on Science and Humanity by H. J. Muller. - Reviewed by Theodosius Dobzhansky
Hermann J. Muller (1890-1967) was not only a great geneticist but a visionary full of messianic zeal, profoundly concerned about directing the evolutionary course of mankind toward what he believed a better future.
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july 2017 by nhaliday
The Genomic Health Of Ancient Hominins | bioRxiv
On a broad scale, hereditary disease risks are similar for ancient hominins and modern-day humans, and the GRS percentiles of ancient individuals span the full range of what is observed in present day individuals. In addition, there is evidence that ancient pastoralists may have had healthier genomes than hunter-gatherers and agriculturalists. We also observed a temporal trend whereby genomes from the recent past are more likely to be healthier than genomes from the deep past.

Gwern has interesting take (abstract is misleading): https://twitter.com/gwern/status/871061144152178688

here it is in conclusion (and cf Figure 3A):
The genomic health of ancient individuals appears to have improved over time (Figure 3B). This calls into question the idea that genetic load has been increasing in human populations (Lynch 2016). However, there exists a perplexing pattern: ancient individuals who lived within the last few thousand years have healthier genomes, on average, than present day humans.

http://www.pnas.org/content/early/2017/08/08/1703856114
After controlling for age, BMI, and other variables, knee OA prevalence was 2.1-fold higher (95% confidence interval, 1.5–3.1) in the postindustrial sample than in the early industrial sample. Our results indicate that increases in longevity and BMI are insufficient to explain the approximate doubling of knee OA prevalence that has occurred in the United States since the mid-20th century. Knee OA is thus more preventable than is commonly assumed, but prevention will require research on additional independent risk factors that either arose or have become amplified in the postindustrial era.
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june 2017 by nhaliday
Genomic analysis of family data reveals additional genetic effects on intelligence and personality | bioRxiv
methodology:
Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits: http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1003520
Pedigree- and SNP-Associated Genetics and Recent Environment are the Major Contributors to Anthropometric and Cardiometabolic Trait Variation: http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005804

Missing Heritability – found?: https://westhunt.wordpress.com/2017/02/09/missing-heritability-found/
There is an interesting new paper out on genetics and IQ. The claim is that they have found the missing heritability – in rare variants, generally different in each family.

Some of the variants, the ones we find with GWAS, are fairly common and fitness-neutral: the variant that slightly increases IQ confers the same fitness (or very close to the same) as the one that slightly decreases IQ – presumably because of other effects it has. If this weren’t the case, it would be impossible for both of the variants to remain common.

The rare variants that affect IQ will generally decrease IQ – and since pleiotropy is the norm, usually they’ll be deleterious in other ways as well. Genetic load.

Happy families are all alike; every unhappy family is unhappy in its own way.: https://westhunt.wordpress.com/2017/06/06/happy-families-are-all-alike-every-unhappy-family-is-unhappy-in-its-own-way/
It now looks as if the majority of the genetic variance in IQ is the product of mutational load, and the same may be true for many psychological traits. To the extent this is the case, a lot of human psychological variation must be non-adaptive. Maybe some personality variation fulfills an evolutionary function, but a lot does not. Being a dumb asshole may be a bug, rather than a feature. More generally, this kind of analysis could show us whether particular low-fitness syndromes, like autism, were ever strategies – I suspect not.

It’s bad new news for medicine and psychiatry, though. It would suggest that what we call a given type of mental illness, like schizophrenia, is really a grab-bag of many different syndromes. The ultimate causes are extremely varied: at best, there may be shared intermediate causal factors. Not good news for drug development: individualized medicine is a threat, not a promise.

see also comment at: https://pinboard.in/u:nhaliday/b:a6ab4034b0d0

https://www.reddit.com/r/slatestarcodex/comments/5sldfa/genomic_analysis_of_family_data_reveals/
So the big implication here is that it's better than I had dared hope - like Yang/Visscher/Hsu have argued, the old GCTA estimate of ~0.3 is indeed a rather loose lower bound on additive genetic variants, and the rest of the missing heritability is just the relatively uncommon additive variants (ie <1% frequency), and so, like Yang demonstrated with height, using much more comprehensive imputation of SNP scores or using whole-genomes will be able to explain almost all of the genetic contribution. In other words, with better imputation panels, we can go back and squeeze out better polygenic scores from old GWASes, new GWASes will be able to reach and break the 0.3 upper bound, and eventually we can feasibly predict 0.5-0.8. Between the expanding sample sizes from biobanks, the still-falling price of whole genomes, the gradual development of better regression methods (informative priors, biological annotation information, networks, genetic correlations), and better imputation, the future of GWAS polygenic scores is bright. Which obviously will be extremely helpful for embryo selection/genome synthesis.

The argument that this supports mutation-selection balance is weaker but plausible. I hope that it's true, because if that's why there is so much genetic variation in intelligence, then that strongly encourages genetic engineering - there is no good reason or Chesterton fence for intelligence variants being non-fixed, it's just that evolution is too slow to purge the constantly-accumulating bad variants. And we can do better.
https://rubenarslan.github.io/generation_scotland_pedigree_gcta/

The surprising implications of familial association in disease risk: https://arxiv.org/abs/1707.00014
https://spottedtoad.wordpress.com/2017/06/09/personalized-medicine-wont-work-but-race-based-medicine-probably-will/
As Greg Cochran has pointed out, this probably isn’t going to work. There are a few genes like BRCA1 (which makes you more likely to get breast and ovarian cancer) that we can detect and might affect treatment, but an awful lot of disease turns out to be just the result of random chance and deleterious mutation. This means that you can’t easily tailor disease treatment to people’s genes, because everybody is fucked up in their own special way. If Johnny is schizophrenic because of 100 random errors in the genes that code for his neurons, and Jack is schizophrenic because of 100 other random errors, there’s very little way to test a drug to work for either of them- they’re the only one in the world, most likely, with that specific pattern of errors. This is, presumably why the incidence of schizophrenia and autism rises in populations when dads get older- more random errors in sperm formation mean more random errors in the baby’s genes, and more things that go wrong down the line.

The looming crisis in human genetics: http://www.economist.com/node/14742737
Some awkward news ahead
- Geoffrey Miller

Human geneticists have reached a private crisis of conscience, and it will become public knowledge in 2010. The crisis has depressing health implications and alarming political ones. In a nutshell: the new genetics will reveal much less than hoped about how to cure disease, and much more than feared about human evolution and inequality, including genetic differences between classes, ethnicities and races.

2009!
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june 2017 by nhaliday
Germline selection | West Hunter
Here’s what seems to be happening: you have cells in the testes that reproduce, producing one daughter cell like the parent and one that develops into a sperm cell. That’s the way it’s supposed to be. But carrying certain very specific mutations of FGFR2 or FGFR3 seem to cause occasional divisions that result in two daughter cells – so the pre-sperm cells that carry such mutations gradually become more and more common in the testes and produce a growing fraction of sperm with those mutations. It’s rather like cancer. You get clumps of cells producing the bad sperm.

Same things is happening with MEN2B (RET gene), which is also more common than it should be, although not as much so as achondroplasia.

Without this unusual mutational mechanism, there would be a shortage of dwarfs.
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may 2017 by nhaliday
Interview: Mostly Sealing Wax | West Hunter
https://soundcloud.com/user-519115521/greg-cochran-part-2
https://medium.com/@houstoneuler/annotating-part-2-of-the-greg-cochran-interview-with-james-miller-678ba33f74fc

- conformity and Google, defense and spying (China knows prob almost all our "secrets")
- in the past you could just find new things faster than people could reverse-engineer. part of the problem is that innovation is slowing down today (part of the reason for convergence by China/developing world).
- introgression from archaics of various kinds
- mutational load and IQ, wrath of khan neanderthal
- trade and antiquity (not that useful besides ideas tbh), Roman empire, disease, smallpox
- spices needed to be grown elsewhere, but besides that...
- analogy: caste system in India (why no Brahmin car repairmen?), slavery in Greco-Roman times, more water mills in medieval times (rivers better in north, but still could have done it), new elite not liking getting hands dirty, low status of engineers, rise of finance
- crookery in finance, hedge fund edge might be substantially insider trading
- long-term wisdom of moving all manufacturing to China...?
- economic myopia: British financialization before WW1 vis-a-vis Germany. North vs. South and cotton/industry, camels in Middle East vs. wagons in Europe
- Western medicine easier to convert to science than Eastern, pseudoscience and wrong theories better than bag of recipes
- Greeks definitely knew some things that were lost (eg, line in Pliny makes reference to combinatorics calculation rediscovered by German dude much later. think he's referring to Catalan numbers?), Lucio Russo book
- Indo-Europeans, Western Europe, Amerindians, India, British Isles, gender, disease, and conquest
- no farming (Dark Age), then why were people still farming on Shetland Islands north of Scotland?
- "symbolic" walls, bodies with arrows
- family stuff, children learning, talking dog, memory and aging
- Chinese/Japanese writing difficulty and children learning to read
- Hatfield-McCoy feud: the McCoy family was actually a case study in a neurological journal. they had anger management issues because of cancers of their adrenal gland (!!).

the Chinese know...: https://macropolo.org/casting-off-real-beijings-cryptic-warnings-finance-taking-economy/
Over the last couple of years, a cryptic idiom has crept into the way China’s top leaders talk about risks in the country’s financial system: tuo shi xiang xu (脱实向虚), which loosely translates as “casting off the real for the empty.” Premier Li Keqiang warned against it at his press conference at the end of the 2016 National People’s Congress (NPC). At this year’s NPC, Li inserted this very expression into his annual work report. And in April, while on an inspection tour of Guangxi, President Xi Jinping used the term, saying that China must “unceasingly promote industrial modernization, raise the level of manufacturing, and not allow the real to be cast off for the empty.”

Such an odd turn of phrase is easy to overlook, but it belies concerns about a significant shift in the way that China’s economy works. What Xi and Li were warning against is typically called financialization in developed economies. It’s when “real” companies—industrial firms, manufacturers, utility companies, property developers, and anyone else that produces a tangible product or service—take their money and, rather than put it back into their businesses, invest it in “empty”, or speculative, assets. It occurs when the returns on financial investments outstrip those in the real economy, leading to a disproportionate amount of money being routed into the financial system.
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may 2017 by nhaliday
Estimating the number of unseen variants in the human genome
To find all common variants (frequency at least 1%) the number of individuals that need to be sequenced is small (∼350) and does not differ much among the different populations; our data show that, subject to sequence accuracy, the 1000 Genomes Project is likely to find most of these common variants and a high proportion of the rarer ones (frequency between 0.1 and 1%). The data reveal a rule of diminishing returns: a small number of individuals (∼150) is sufficient to identify 80% of variants with a frequency of at least 0.1%, while a much larger number (> 3,000 individuals) is necessary to find all of those variants.

A map of human genome variation from population-scale sequencing: http://www.internationalgenome.org/sites/1000genomes.org/files/docs/nature09534.pdf

Scientists using data from the 1000 Genomes Project, which sequenced one thousand individuals from 26 human populations, found that "a typical [individual] genome differs from the reference human genome at 4.1 million to 5.0 million sites … affecting 20 million bases of sequence."[11] Nearly all (>99.9%) of these sites are small differences, either single nucleotide polymorphisms or brief insertion-deletions in the genetic sequence, but structural variations account for a greater number of base-pairs than the SNPs and indels.[11]

Human genetic variation: https://en.wikipedia.org/wiki/Human_genetic_variation

Singleton Variants Dominate the Genetic Architecture of Human Gene Expression: https://www.biorxiv.org/content/early/2017/12/15/219238
study  sapiens  genetics  genomics  population-genetics  bioinformatics  data  prediction  cost-benefit  scale  scaling-up  org:nat  QTL  methodology  multi  pdf  curvature  convexity-curvature  nonlinearity  measurement  magnitude  🌞  distribution  missing-heritability  pop-structure  genetic-load  mutation  wiki  reference  article  structure  bio  preprint  biodet  variance-components  nibble  chart 
may 2017 by nhaliday
Polymorphisms and Load | West Hunter
Anyhow, we now have some estimates of the relative influence of common variants on various traits (from recent Visscher-type papers) . The fraction of genetic variation that can be explained by common variants is about half for height and IQ, one-third for schizophrenia, one-quarter for BMI, and about one-fifth for personality, as measured by standard personality measures, which I don’t have much faith in. If I had to guess, and at this point I do, the more that trait variation is a deviation from the selective optimum, rather than being orthogonal to fitness, the more it is influenced by load.
west-hunter  scitariat  discussion  biodet  behavioral-gen  genetics  QTL  population-genetics  genetic-load  data  iq  embodied  psychiatry  personality  stylized-facts  prediction  variance-components  correlation  evolution  sapiens  mutation  distribution  🌞  disease  health  fitness  psychology  cog-psych  spearhead  perturbation 
may 2017 by nhaliday
Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network
Towards explaining non-shared-environment effects on intelligence, psychiatric disorders, and other cognitive traits - developmental noise such as post-conception mutations in individual cells or groups of cells
pdf  study  psychology  cog-psych  neuro  neuro-nitgrit  brain-scan  biodet  genetics  genomics  GWAS  🌞  psychiatry  behavioral-gen  mutation  environmental-effects  roots  org:nat  gwern  random  autism  proposal  signal-noise  developmental  composition-decomposition 
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.

https://westhunt.wordpress.com/2012/10/17/more-to-go-wrong/

https://westhunt.wordpress.com/2012/07/13/sanctuary/
interesting, suggestive comment on Africa:
https://westhunt.wordpress.com/2012/07/13/sanctuary/#comment-3671
https://westhunt.wordpress.com/2012/07/14/too-darn-hot/
http://infoproc.blogspot.com/2012/07/rare-variants-and-human-genetic.html
https://westhunt.wordpress.com/2012/07/18/changes-in-attitudes/
https://westhunt.wordpress.com/2012/08/24/men-and-macaques/
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.
https://westhunt.wordpress.com/2016/04/10/bugs-versus-drift/
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.
west-hunter  scitariat  discussion  bio  sapiens  biodet  evolution  mutation  genetics  genetic-load  population-genetics  nibble  stylized-facts  methodology  models  equilibrium  iq  neuro  neuro-nitgrit  epidemiology  selection  malthus  temperature  enhancement  CRISPR  genomics  behavioral-gen  multi  poast  africa  roots  pop-diff  ideas  gedanken  paternal-age  🌞  environment  speculation  gene-drift  longevity  immune  disease  parasites-microbiome  scifi-fantasy  europe  asia  race  migration  hsu  study  summary  commentary  shift  the-great-west-whale  nordic  intelligence  eden  long-short-run  debate  hmm  idk  explanans  comparison  structure  occident  mediterranean  geography  within-group  correlation  direction  volo-avolo  demographics  age-generation  measurement  data  applicability-prereqs  aging 
may 2017 by nhaliday
The Issue that Time Forgot | West Hunter
Human population genetics in the 1960s was obsessed with the question of genetic load. Much of the motivation was concern about health consequences of radiation and nuclear weapons. We now know that radiation does bad things to organisms but that the mutation rate in mammals is nearly insensitive to the effects of ionizing radiation. No one knew that then. Popular concern about the issue was also pumped up by monster movies, which were everywhere on late night television. Does anyone remember Godzilla?

...

The key paper about load was published in 19582. Morton, Crow, and Muller showed that, under some simplifying assumptions, the regression of mortality (and on other traits like IQ) on the inbreeding coefficient could reveal the nature of our burden of mutations. In particular the negative logarithm of the rate, for example the infant mortality rate, should be linear in the inbreeding coefficient:

-ln(q) = A + Bf

where q is the mortality rate and f the inbreeding coefficient. Their important insight was the if our load is mostly deleterious recessives then the rate should increase rapidly with inbreeding. If, on the other hand, our load reflects a lot of balanced polymorphisms then the load should not increase very much with inbreeding. In particular the load ratio, B/A, ought to be something like 10 if there are a lot of deleterious recessives while something like 2 if there are a lot of balanced polymorphisms. A clear explanation of the the theory and the results availabe by the early 1970s can be found in the classic Cavalli and Bodmer text3.

The bottom line was that load ratios from human populations did not give a clear signal either way. A typical B/A ratio was something like 4. The interest in and optimism about load theory in 1960 had fizzled by 1970.

Today all those issues are back on the table in a big way. What is our burden of mutation? How many of our aches and pains and premature deaths are costs of balanced polymorphism? Unfortunately the whole toolkit of 50 years ago has been mostly forgotten by the current generation of human population geneticists. A shame.

- Harpending
west-hunter  scitariat  discussion  history  mostly-modern  electromag  bio  sapiens  genetics  population-genetics  genetic-load  mutation  kinship  reflection  stylized-facts  methodology  🌞 
april 2017 by nhaliday
Evolution of Virulence | West Hunter
Once upon a time, I thought a lot about evolution and pathogens. I still do, on occasion.

It used to be the case [and still is] that many biologists thought that natural selection would inevitably tend towards a situation in which pathogens did infinitesimal harm to their host. This despite the epidemics all around them. I remember reading a book on parasitology in which the gormless author mentioned a certain species of parasitic copepod that routinely blinded the fish they attached to. He said that many a naive grad student would think that that these parasitic copepods were bad for the fish, but sophisticated evolutionists like himself knew (and would explain to the newbies) that of course the fish didn’t suffer any reduction in fitness by going blind – theory said so ! Clearly, that man had a Ph.D.

If a pathogen can gain increased reproduction by tapping host resources, or by doing any damn thing that helps itself and hurts the host, that tactic may pay, and be selected for. It depends on the balance between the advantages and costs – almost entirely those to the pathogen, since the pathogen evolves much more rapidly than the host. In some cases, as much as a million times faster – because of generations that may be 20 minutes long rather than 20 years, because pathogens often have very large populations, which favors Fisherian acceleration, and in many cases, a relatively high mutation rate. Pathogen evolution is, at least some cases, so rapid that you see significant evolutionary change within a single host. Along the same lines, we have seen very significant evolutionary changes in antibiotic resistance among pathogenic bacteria over the past few decades, but I’m pretty sure that there hasn’t been much evolutionary change in mankind since I was a kid.

So when analyzing virulence, people mostly consider evolutionary pressures on the pathogens, rather than the host. Something like the Born-Oppenheimer approximation.
west-hunter  bio  disease  parasites-microbiome  red-queen  thinking  incentives  evolution  🌞  deep-materialism  discussion  mutation  selection  time  immune  scitariat  maxim-gun  cooperate-defect  ideas  anthropic  is-ought  gender  gender-diff  scale  magnitude  stylized-facts  approximation  analogy  comparison  pro-rata 
april 2017 by nhaliday
Evolution Runs Faster on Short Timescales | Quanta Magazine
But if more splashes of paint appear on a wall, they will gradually conceal some of the original color beneath new layers. Similarly, evolution and natural selection write over the initial mutations that appear over short timescales. Over millions of years, an A in the DNA may become a T, but in the intervening time it may be a C or a G for a while. Ho believes that this mutational saturation is a major cause of what he calls the time-dependent rate phenomenon.

“Think of it like the stock market,” he said. Look at the hourly or daily fluctuations of Standard & Poor’s 500 index, and it will appear wildly unstable, swinging this way and that. Zoom out, however, and the market appears much more stable as the daily shifts start to average out. In the same way, the forces of natural selection weed out the less advantageous and more deleterious mutations over time.
news  org:mag  org:sci  evolution  bio  nature  mutation  selection  time  methodology  stylized-facts  genetics  population-genetics  genomics  speed  pigeonhole-markov  bits  nibble  org:inst 
march 2017 by nhaliday
De novo mutations in regulatory elements cause neurodevelopmental disorders | bioRxiv
De novo mutations in hundreds of different genes collectively cause 25-42% of severe developmental disorders (DD). The cause in the remaining cases is largely unknown. The role of de novo mutations in regulatory elements affecting known DD-associated genes or other genes is essentially unexplored. We identified de novo mutations in three classes of putative regulatory elements in almost 8,000 DD patients. Here we show that de novo mutations in highly conserved fetal-brain active elements are significantly and specifically enriched in neurodevelopmental disorders. We identified a significant two-fold enrichment of recurrently mutated elements. We estimate that, genome-wide, de novo mutations in fetal-brain active elements are likely to be causal for 1-3% of patients without a diagnostic coding variant and that only a small fraction (<2%) of de novo mutations in these elements are pathogenic. Our findings represent a robust estimate of the contribution of de novo mutations in regulatory elements to this genetically heterogeneous set of disorders, and emphasise the importance of combining functional and evolutionary evidence to delineate regulatory causes of genetic disorders.
study  preprint  bio  sapiens  biodet  genetics  genomics  genetic-load  mutation  developmental  neuro  psychiatry  QTL  🌞  epidemiology  behavioral-gen 
march 2017 by nhaliday
Sustainability | West Hunter
There have been societies that functioned for a long time, thousands of years. They had sustainable demographic patterns. That means that they had enough children to replace themselves – not necessarily in every generation, but over the long haul. But sustainability requires more than that. Long-lived civilizations [ones with cities, literacy, governments, and all that] had a pattern of natural selection that didn’t drastically decrease intelligence – in some cases, one that favored it, at least in some subgroups. There was also ongoing selection against mutational accumulation – which meant that individuals with more genetic load than than average were significantly less likely to survive and reproduce. Basically, this happened through high child mortality, and in some cases by lower fitness in lower socioeconomic classes [starvation]. There was nothing fun about it.

Modern industrialized societies are failing on all three counts. Every population that can make a decent cuckoo clock has below-replacement fertility. The demographic pattern also selects against intelligence, something like one IQ point a generation. And, even if people at every level of intelligence had the same number of children, so that there was no selection against IQ, we would still be getting more and messed up, because there’s not enough selection going on to counter ongoing mutations.

It is possible that some country, or countries, will change in a way that avoids civilizational collapse. I doubt if this will happen by voluntary action. Some sort of technological solution might also arise – but it has to be soon.

Bruce Charlton, Victorian IQ, Episcopalians, military officers:
https://westhunt.wordpress.com/2013/05/09/sustainability/#comment-13188
https://westhunt.wordpress.com/2013/05/09/sustainability/#comment-13207
Again, I don’t believe a word of it. As for the declining rate of innovation, you have to have a really wide-ranging understanding of modern science and technology to have any feeling for what the underlying causes are. I come closer than most, and I probably don’t know enough. You don’t know enough. Let me tell you one thing: if genetic potential IQ for IQ had dropped 1 std, we’d see the end of progress in higher mathematics, and that has not happened at all.

Moreover, the selective trends disfavoring IQ all involve higher education among women and apparently nothing else – a trend which didn’t really get started until much more recently.

Not long enough, nor is dysgenic selection strong enough.

ranting on libertarians:
https://westhunt.wordpress.com/2013/05/09/sustainability/#comment-13348
About 40% of those Americans with credit cards keep a balance on their credit cards and pay ridiculous high interest. But that must be the right decision!
https://westhunt.wordpress.com/2013/05/09/sustainability/#comment-13499
” then that is their decision” – that’s fucking obvious. The question is whether they tend to make decisions that work very well – saying ‘that is their decision” is exactly the kind of crap I was referring to. As for “they probably have it coming” – if I’m smarter than you, which I surely am, using those smarts to rook you in every possible way must be just peachy. In fact, I’ll bet I could manage it even after warning you in advance.

On average, families in this country have paid between 10% and 14% of their income in debt service over the past few decades. That fraction averages considerably higher in low-income families – more like 18%. A quarter of those low income families are putting over 40% of their income into debt service. That’s mostly stuff other than credit-card debt.

Is this Straussian?

hmm:
Examining Arguments Made by Interest Rate Cap Advocates: https://www.mercatus.org/system/files/peirce_reframing_ch13.pdf

https://twitter.com/tcjfs/status/964972690435133440
https://archive.is/r34J8
Interest rate caps on $1,000 installment loans, by US state, today and in 1935
west-hunter  civilization  dysgenics  fertility  legacy  risk  mutation  genetic-load  discussion  rant  iq  demographics  gnon  sapiens  trends  malthus  leviathan  long-short-run  science-anxiety  error  biodet  duty  s:*  malaise  big-picture  debt  randy-ayndy  recent-selection  demographic-transition  order-disorder  deep-materialism  🌞  age-generation  scitariat  rhythm  allodium  behavioral-gen  nihil  zeitgeist  rot  the-bones  prudence  darwinian  flux-stasis  counter-revolution  modernity  microfoundations  multi  poast  civil-liberty  is-ought  track-record  time-preference  temperance  patience  antidemos  money  compensation  class  coming-apart  pro-rata  behavioral-econ  blowhards  history  early-modern  britain  religion  christianity  protestant-catholic  gender  science  innovation  frontier  the-trenches  speedometer  military  elite  optimate  data  intervention  aphorism  alt-inst  ethics  morality  straussian  intelligence  class-warfare  authoritarianism  hari-seldon  interests  crooked  twitter  social  back 
march 2017 by nhaliday
A Resolution of the Mutation Load Paradox in Humans
It has been argued that the mutation load, the proportional reduction in population mean fitness relative to the fitness of an idealized mutation-free individual, allows a theoretical prediction of the proportion of individuals in the population that fail to reproduce as a consequence of these harmful mutations. Application of this theory to humans implies that at least 88% of individuals should fail to reproduce and that each female would need to have more than 16 offspring to maintain population size. This prediction is clearly at odds with the low reproductive excess of human populations. Here, we derive expressions for the fraction of individuals that fail to reproduce as a consequence of recurrent deleterious mutation (φ) for a model in which selection occurs via differences in relative fitness, such as would occur through competition between individuals. We show that φ is much smaller than the value predicted by comparing fitness to that of a mutation-free genotype. Under the relative fitness model, we show that φ depends jointly on U and the selective effects of new deleterious mutations and that a species could tolerate 10’s or even 100’s of new deleterious mutations per genome each generation.

Mutation load under additive fitness effects: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4957254/
pdf  study  org:nat  bio  sapiens  evolution  genetics  population-genetics  selection  mutation  genetic-load  🌞  models  EEA  distribution  deep-materialism  science-anxiety  multi 
march 2017 by nhaliday
Social Epistasis Amplifies the Fitness Costs of Deleterious Mutations, Engendering Rapid Fitness Decline Among Modernized Populations | SpringerLink
- Michael A. Woodley

We argue that in social species, interorganismal gene-gene interactions, which in previous literatures have been termed social epistasis, allow genomes carrying deleterious mutations to reduce via group-level pleiotropy the fitness of others, including noncarriers. This fitness reduction occurs by way of degradation of group-level processes that optimize the reproductive ecology of a population for intergroup competition through, among other mechanisms, suppression of free-riding.

--

Fitness indicators theory (Houle 2000; Miller 2000) predicts that the behavioral and physiological condition of prospective partners strongly influences female mate choice in particular, as these constitute honest indicators of underlying genetic quality. Furthermore, as deleterious mutations are pleiotropic (i.e., they can influence the development of multiple traits simultaneously), they are a source of genetic correlation among diverse behavioral and physiological domains, yielding a latent general fitness factor( f ). This optimizes the efficiency of sexual selection, as selection for quality with respect to one domain will increase the probability of selection for quality “across the board” (Houle 2000; Miller 2000). If purifying selection is primarily cryptic—working by virtue of those lower in f simply being less successful in competition for mates and therefore producing fewer offspring relative to those higher in the factor—then considerably less reproductive failure is needed to solve the mutation load paradox (19% instead of 88% based on simulations in Leseque et al. 2012).

...

Theoretical work involving humans suggests a loss of intrinsic fitness of around 1% per generation in the populations of modernized countries (Lynch 2016; Muller 1950). Thus, these might yet be undergoing mutational meltdown, albeit very gradually (i.e., over the course of centuries)

...

An interesting observation is that the fitness of the populations of modernized nations does appear to be rapidly decreasing—although not in a manner consonant with the direct action of deleterious mutations on the fitness of individuals (as per the mutation load paradox).

...

Increased education has furthermore encouraged individuals to trade fertility against opportunities to enhance their social status and earning power, with the largest fitness losses occurring among those with high status who potentially carry fewer deleterious mutations (i.e., by virtue of possessing higher levels of traits that exhibit some sensitivity to mutation load, such as general intelligence; Spain et al. 2015; Woodley of Menie et al. 2016a). Hitherto not considered is the possibility that the demographic transition represents a potential change in the fitness characteristics of the group-level extended phenotype of modernized populations, indicating that there might exist pathways through which deleterious mutations that accumulate due to ecological mildness could pathologically alter fertility tradeoffs in ways that might account for the maladaptive aspects of the fertility transition (e.g., subreplacement fertility; Basten, Lutz and Scherbov, 2013).

...

Cooperation, though offering significant fitness benefits to individual organisms and groups, involves some costs for cooperators in order to realize mutual gains for all parties. Free riders are individuals that benefit from cooperation without suffering any of the costs needed to sustain it. Hence, free riders enjoy a fitness advantage relative to cooperators via the former’s parasitism on the latter.

...

The balance of selection can alternate between the different levels depending on the sorts of selective challenges that a population encounters. For example, group selection may operate on human populations during times of intergroup conflict (i.e., warfare), whereas during times of peace, selection may tend to favor the fitness of individuals instead (Woodley and Figueredo 2013; Wilson 2002). A major factor that seems to permit group-level selection to be viable under certain ecological regimes is the existence of free-rider controls, i.e., features of the group’s social ecology that curb the reproductive fitness of the carriers of “selfish” genetic variants (MacDonald 1994; Wilson 2002).

...

High-status individuals participate in the generation and vertical cultural transmission of free-rider controls—these take the form of religious and ideological systems which make a virtue out of behaviors that overtly benefit the group, and a vice out of those that only favor individual-level fitness, via the promotion of ethnocentrism, martyrdom, and displays of commitment (MacDonald 1994, 2009, 2010; Wilson 2002). Humans are furthermore equipped with specialized mental adaptations for coordinating as part of a group, such as effortful control—the ability to override implicit behavioral drives via the use of explicit processing systems, which allow them to regulate their behavior based on what is optimal for the group (MacDonald 2008). The interaction between individuals of different degrees of status, i.e., those that generate and maintain cultural norms and those who are merely subject to them, therefore constitutes a form of social epistasis, as the complex patterns of interactions among genomes that characterize human culture have the effect of regulating both individual- and group-level (via the curbing of free-riding) fitness (MacDonald 2009, 2010).

Mutations that push the behavior of high-status individuals away from the promotion of group-selected norms may promote a breakdown of or otherwise alter these social epistatic interactions, causing dysregulation of the group’s reproductive ecology. Behavioral changes are furthermore a highly likely consequence of mutation accumulation, as “behavior” (construed broadly) is a large potential target for new mutations (Miller 2000; Lynch 2016) 1 owing to the fact that approximately 84% of all genes in the human genome are involved in some aspect of brain development and/or maintenance (Hawrylycz et al. 2012).

Consistent with the theorized role of group-level (cultural) regulatory processes in the maintenance of fitness optima, positive correlations exist between religiosity (a major freerider control; MacDonald 1994; Wilson 2002) and fertility, both at the individual differences and cross-cultural levels (Meisenberg 2011). Religiosity has declined in modernized nations—a process that has gone hand-in-hand with the rise of a values system called postmaterialism (Inglehart 1977), which is characterized by the proliferation of individualistic, secular, and antihierarchical values (Welzel 2013). The holding of these values is negatively associated with fertility, both at the individual level (when measured as political liberalism; Goldstone et al. 2011) and across time and cultures (Inglehart and Appel 1989). The rise of postmaterialist values is also associated with increasingly delayed onset of reproduction (Klien 1990) which directly increases the (population) mutation load.

Pathological Altruism

Some of the values embodied in postmaterialism have been linked to the pathological altruism phenomenon, i.e., forms of altruism that damage the intended recipients or givers of largesse (Oakley et al. 2012; Oakley 2013). Virtues associated with altruism such as kindness, fidelity, magnanimity, and heroism, along with quasi-moral traits associated with personality and mental health, may be under sexual selection and might therefore be sensitive, through the f factor, to the deleterious effects of accumulating mutations (Miller 2007).

...

Another form of pathologically altruistic behavior that Oakley (2013) documents is self-righteousness, which may be increasing, consistent with secular trend data indicating elevated levels of self-regarding behavior among Western populations (sometimes called the narcissism epidemic; Twenge and Campbell 2009). This sort of behavior constitutes a key component of the clever silly phenomenon in which the embrace of counterfactual beliefs is used to leverage social status via virtue signaling (e.g., the conflation of moral equality among individuals, sexes, and populations with biological equality) (Dutton and van der Linden 2015; Charlton 2009; Woodley 2010). There may be a greater number of influential persons inclined to disseminate such beliefs, in that the prevalence of phenotypes disposed toward egoistic behaviors may have increased in Western populations (per Twenge and coworkers’ research), and because egoists, specifically Machiavellians and narcissists, appear advantaged in the acquisition of elite societal stations (Spurk et al. 2015).

[Do Bad Guys Get Ahead or Fall Behind? Relationships of the Dark Triad of Personality With Objective and Subjective Career Success: http://sci-hub.tw/http://journals.sagepub.com/doi/abs/10.1177/1948550615609735

After controlling for other relevant variables (i.e., gender, age, job tenure, organization size, education, and work hours), narcissism was positively related to salary, Machiavellianism was positively related to leadership position and career satisfaction, and psychopathy was negatively related to all analyzed outcomes.]

...

By altering cultural norms, elite egoists may encourage the efflorescence of selfish behaviors against which some older and once highly influential cultural systems acted. For example, Christianity in various forms strongly promoted personal sacrifice for the good of groups and proscribed egoistic behaviors (Rubin 2015), but has declined significantly in terms of cultural power following modernization (Inglehart 1977). Thus, it is possible that a feedback loop exists wherein deleterious mutation accumulation raises population levels of egoism, either directly or indirectly, via the breakdown of developmental constraints on personality canalization; the resultantly greater number of egoists are then able to exploit relevant personality traits to attain positions of sociocultural influence; and through these … [more]
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march 2017 by nhaliday
Neurodiversity | West Hunter
Having an accurate evaluation of a syndrome as a generally bad thing isn’t equivalent to attacking those with that syndrome. Being a leper is a bad thing, not just another wonderful flavor of humanity [insert hot tub joke] , but that doesn’t mean that we have to spend our spare time playing practical jokes on lepers, tempting though that is.. Leper hockey. We can cure leprosy, and we are right to do so. Preventing deafness through rubella vaccination was the right thing too – deafness sucks. And so on. As we get better at treating and preventing, humans are going to get more uniform – and that’s a good thing. Back to normalcy!

focus: https://westhunt.wordpress.com/2017/02/22/neurodiversity/#comment-88691
interesting discussion of mutational load: https://westhunt.wordpress.com/2017/02/22/neurodiversity/#comment-88793

https://westhunt.wordpress.com/2013/04/30/blurry/
I was thinking again about the consequences of having more small-effect deleterious mutations than average. I don’t think that they would push hard in a particular direction in phenotype space – I don’t believe they would make you look weird, but by definition they would be bad for you, reduce fitness. I remembered a passage in a book by Steve Stirling, in which our heroine felt as if her brain ‘was moving like a mechanism of jewels and steel precisely formed.’ It strikes me that a person with an extra dollop of this kind of genetic load wouldn’t feel like that. And of course that heroine did have low genetic load, being the product of millennia of selective breeding, not to mention an extra boost from the Invisible Crown.

https://westhunt.wordpress.com/2013/04/30/blurry/#comment-12769
Well, what does the distribution of fitness burden by frequency look like for deleterious mutations of a given fitness penalty?
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It’s proportional to the mutation rate for that class. There is reason to believe that there are more ways to moderately or slightly screw up a protein than to really ruin it, which indicates that mild mutations make up most load in protein-coding sequences. More of the genome is made up of conserved regulatory sequences, but mutations there probably have even milder effects, since few mutations in non-coding sequences cause a serious Mendelian disease.

https://westhunt.wordpress.com/2013/04/30/blurry/#comment-12803
I have wondered if there was some sort of evolutionary tradeoff between muscles and brains over the past hundred thousand years through dystrophin’s dual role. There is some evidence of recent positive selection among proteins that interact with dystrophin, such as DTNBP1 and DTNA.

Any novel environment where higher intelligence can accrue more caloric energy than brute strength alone (see: the invention of the bow) should relax the selection pressure for muscularity. The Neanderthals didn’t fare so well with the brute strength strategy.
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Sure: that’s what you might call an inevitable tradeoff, a consequence of the laws of physics. Just as big guys need more food. But because of the way our biochemistry is wired, there can be tradeoffs that exist but are not inevitable consequences of the laws of physics – particularly likely when a gene has two fairly different functions, as they often do.
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february 2017 by nhaliday
Evolution of Resistance Against CRISPR/Cas9 Gene Drive | Genetics
CRISPR/Cas9 gene drive (CGD) promises to be a highly adaptable approach for spreading genetically engineered alleles throughout a species, even if those alleles impair reproductive success. CGD has been shown to be effective in laboratory crosses of insects, yet it remains unclear to what extent potential resistance mechanisms will affect the dynamics of this process in large natural populations. Here we develop a comprehensive population genetic framework for modeling CGD dynamics, which incorporates potential resistance mechanisms as well as random genetic drift. Using this framework, we calculate the probability that resistance against CGD evolves from standing genetic variation, de novo mutation of wild-type alleles, or cleavage repair by nonhomologous end joining (NHEJ)—a likely by-product of CGD itself. We show that resistance to standard CGD approaches should evolve almost inevitably in most natural populations, unless repair of CGD-induced cleavage via NHEJ can be effectively suppressed, or resistance costs are on par with those of the driver. The key factor determining the probability that resistance evolves is the overall rate at which resistance alleles arise at the population level by mutation or NHEJ. By contrast, the conversion efficiency of the driver, its fitness cost, and its introduction frequency have only minor impact. Our results shed light on strategies that could facilitate the engineering of drivers with lower resistance potential, and motivate the possibility to embrace resistance as a possible mechanism for controlling a CGD approach. This study highlights the need for careful modeling of the population dynamics of CGD prior to the actual release of a driver construct into the wild.
study  org:nat  bio  genetics  evolution  population-genetics  models  CRISPR  unintended-consequences  geoengineering  mutation  risk  parasites-microbiome  threat-modeling  selfish-gene  cooperate-defect  red-queen 
february 2017 by nhaliday
Information Processing: Epistasis vs additivity
On epistasis: why it is unimportant in polygenic directional selection: http://rstb.royalsocietypublishing.org/content/365/1544/1241.short
- James F. Crow

The Evolution of Multilocus Systems Under Weak Selection: http://www.genetics.org/content/genetics/134/2/627.full.pdf
- Thomas Nagylaki

Data and Theory Point to Mainly Additive Genetic Variance for Complex Traits: http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1000008
The relative proportion of additive and non-additive variation for complex traits is important in evolutionary biology, medicine, and agriculture. We address a long-standing controversy and paradox about the contribution of non-additive genetic variation, namely that knowledge about biological pathways and gene networks imply that epistasis is important. Yet empirical data across a range of traits and species imply that most genetic variance is additive. We evaluate the evidence from empirical studies of genetic variance components and find that additive variance typically accounts for over half, and often close to 100%, of the total genetic variance. We present new theoretical results, based upon the distribution of allele frequencies under neutral and other population genetic models, that show why this is the case even if there are non-additive effects at the level of gene action. We conclude that interactions at the level of genes are not likely to generate much interaction at the level of variance.
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february 2017 by nhaliday
Information Processing: Recent evolution in humans
"There is a good theoretical argument for why evolution may speed up due to population growth. Given a particular probability distribution for producing beneficial mutations, a large population implies a faster rate of incidence of such mutations. Because reproductive dynamics leads to exponential solutions (i.e., a slight increase in expected number of offspring compounds rapidly), the time required for an advantageous allele to sweep through a population only grows logarithmically with the population, while the rate of incidence grows linearly."

To elaborate on the last point, consider the set of mutations that are sufficiently advantageous that they would sweep through a population of N humans (i.e. reach fixation) in some specified period of time, such as 5000 years. If the probability of such a mutation is p, the rate of occurrence in the population is proportional to pN. Now imagine the population of the group increases to 100N. The rate of mutations is then much higher -- 100pN -- but the time necessary for fixation has only increased by the logarithm of 100 since selective advantage works exponentially: the population fraction with the mutant gene grows as exp( r t ), where r is the reproductive advantage and t is time. This rather obvious point -- that linear beats log -- suggests that the rate of evolution will speed up as population size increases. (A possible loophole is if the probability of mutations as a function of relative advantage is itself an exponential function, and falls off rapidly with increasing advantage.) If the Hawks et al. results are any guide, as many as 7% of all genes have been under intense selection in the last 10-50,000 years. (See here for another summary of the research with a nice illustration of how linkage disequilibrium arises due to favorable mutations.) Importantly, the variants that reached fixation over this period are different in different geographical regions.

Thus civilization, with its consequently larger populations supported by agriculture, enhanced rather than suppressed the rate of human evolution.

A related question is whether selection pressure remained strong after the development of civilization. Perhaps reproductive success became largely decoupled from genetic influences once humans became civilized? Not only is this implausible, but it seems to be directly contradicted by evidence. The graph below, based on English inheritance records, shows that the rich gradually out-reproduced the poor: the wealthy had more than twice as many surviving children as the poor. (Note the range of inheritances in the graph covers the middle class to moderately wealthy; the poor and very rich are not shown.) Thus, in this period of history wealth was a good proxy for reproductive success. Genes which were beneficial for the accrual of wealth (e.g., for intelligence, self-discipline, delayal of gratification, etc.) would have become more prevalent over time. In a simple population model, any lineage that remained consistently poor over a few hundred year period would contribute almost zero to today's population of Britons.

...

See also my review of Clark's A Farewell to Alms, and this video of a talk by Clark. When Clark wrote the book he wasn't sure whether it was genetic change or cultural change that led to the industrial revolution in England. In the video lecture he comments that he has since become convinced it was largely genetic. That doesn't jibe with the back of the envelope calculation I give below -- even in the optimistic case (largest effect) it would seem to take a thousand years to have a big shift in overall population characteristics.

Here's a very crude back of the envelope calculation: if, in a brutal Malthusian setting, the top 10% in wealth were to out-reproduce the average by 20% per generation, then after only 10 generations or so (say 2-300 years), essentially everyone in the population would trace their heritage in some way to this group. In our population the average IQ of the high income group is about +.5 SD relative to the average. If the heritability of IQ is .5, then in an ideal case we could see a selection-driven increase of +.25 SD every 2-300 years, or +1 SD per millenium. This is highly speculative, of course, and oversimplified, but it shows that there is (plausibly) no shortage of selection pressure to drive noticeable, even dramatic, change. If the estimate is too high by an order of magnitude (the rich group doesn't directly replace the others; there is inevitably a lot of intermarriage between descendants of the rich and non-rich), a change of +1 SD per 10,000 years would still be possible. There's clearly no shortage in genetic variation affecting intelligence: we see 1 SD variations not just within populations but commonly in individual families!
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january 2017 by nhaliday
Sir Ronald Aylmer Fisher | West Hunter
In 1930 he published The Genetical Theory of Natural Selection, which completed the fusion of Darwinian natural selection with Mendelian inheritance. James Crow said that it was ‘arguably the deepest and most influential book on evolution since Darwin’. In it, Fisher analyzed sexual selection, mimicry, and sex ratios, where he made some of the first arguments using game theory. The book touches on many other topics. As was the case with his other works, The Genetical Theory is a dense book, not easy for most people to understand. Fisher’s tendency to leave out mathematical steps that he deemed obvious (a leftover from his early training in mental mathematics) frustrates many readers.

The Genetical Theory is of particular interest to us because Fisher there lays out his ideas on how population size can speed up evolution. As we explain elsewhere, more individuals mean there will be more mutations, including favorable mutations, and so Fisher expected more rapid evolution in larger populations. This idea was originally suggested, in a nonmathematical way, in Darwin’s Origin of Species.

Although Fisher was fiercely loyal to friends and could be very charming, he had a quick temper and was a fine hater. The same uncompromising spirit that fostered his originality led to constant conflict with authority. He had a long conflict with Karl Pearson, who had also played an important part in the development of mathematical statistics. In this case, Pearson was more at fault, resisting the advent of a more talented competitor, as well as being an eminently hateable person in general. Over time Fisher also became increasing angry at Sewall Wright (another one of the founders of population genetics) due to scientific disagreements – and this was just wrong, because Wright was a sweetheart.

Fisher’s personality decreased his potential influence. He was not a school-builder, and was impatient with administrators. He expected to find some form of war-work in the Second World War, but his characteristics had alienated too many people, and thus his team dispersed to other jobs during the war. He returned to Rothamsted for the duration. This was a difficult time for him: his marriage disintegrated and his oldest son, an RAF pilot, was killed in the war.

...

Fisher’s ideas in genetics have taken an odd path. The Genetical Theory was not widely read, sold few copies, and has never been translated. Only gradually did its ideas find an audience. Of course, that audience included people like Bill Hamilton, the greatest mathematical biologist of the last half of the 20th century, who was strongly influenced by Fisher’s work. Hamilton said “By the time of my ultimate graduation,will I have understood all that is true in this book and will I get a First? I doubt it. In some ways some of us have overtaken Fisher; in many, however, this brilliant, daring man is still far in front.“

In fact, over the past generation, much of Fisher’s work has been neglected – in the sense that interest in population genetics has decreased (particularly interest in selection) and fewer students are exposed to his work in genetics in any way. Ernst Mayr didn’t even mention Fisher in his 1991 book One Long Argument: Charles Darwin and the Genesis of Modern Evolutionary Thought, while Stephen Jay Gould, in The Structure of Evolutionary Theory, gave Fisher 6 pages out of 1433. Of course Mayr and Gould were both complete chuckleheads.

Fisher’s work affords continuing insight, including important implications concerning human evolution that have emerged more than 50 years after his death. We strongly discourage other professionals from learning anything about his ideas.
west-hunter  history  bio  evolution  genetics  population-genetics  profile  giants  people  mostly-modern  the-trenches  innovation  novelty  britain  fisher  mental-math  narrative  scitariat  old-anglo  world-war  pre-ww2  scale  population  pop-structure  books  classic  speed  correlation  mutation  personality 
january 2017 by nhaliday
Europeans mutate differently - The Unz Review
But there’s a final element to be explored. Why is there in enrichment in the first place? It turns out that this sort of mutation is very common in melanomas. In particular of interest to me: “Folate deficiency is known to cause DNA damage including uracil misincorporation and double-strand breaks, leading in some cases to birth defects and reduced male fertility.” Folate deficiency can occur when light skinned individuals are exposed to sunlight. It strikes me that the higher mutational load for these particular transitions in Southern Europeans as opposed to Northern Europeans could simply be a function of the fact that they are in sunnier climates.
gnxp  scitariat  study  summary  evolution  sapiens  genetics  hmm  idk  europe  recent-selection  mutation  genomics  pop-structure  pop-diff 
january 2017 by nhaliday
Fitness landscape - Wikipedia
Fitness landscapes are often conceived of as ranges of mountains. There exist local peaks (points from which all paths are downhill, i.e. to lower fitness) and valleys (regions from which many paths lead uphill). A fitness landscape with many local peaks surrounded by deep valleys is called rugged. If all genotypes have the same replication rate, on the other hand, a fitness landscape is said to be flat. An evolving population typically climbs uphill in the fitness landscape, by a series of small genetic changes, until a local optimum is reached.
concept  genetics  population-genetics  evolution  bio  wiki  reference  visual-understanding  exploration-exploitation  models  mutation  local-global 
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
hsu  scitariat  genetics  embodied  recent-selection  study  summary  europe  mediterranean  street-fighting  GWAS  spearhead  pop-structure  biodet  QTL  mutation  evolution  pop-diff  shift  gene-drift 
december 2016 by nhaliday
Edge.org: 2016 : WHAT DO YOU CONSIDER THE MOST INTERESTING RECENT [SCIENTIFIC] NEWS? WHAT MAKES IT IMPORTANT?
highlights:
- quantum supremacy [Scott Aaronson]
- gene drive
- gene editing/CRISPR
- carcinogen may be entropy
- differentiable programming
- quantitative biology
soft:
- antisocial punishment of pro-social cooperators
- "strongest prejudice" (politics) [Haidt]
- Europeans' origins [Cochran]
- "Anthropic Capitalism And The New Gimmick Economy" [Eric Weinstein]

https://twitter.com/toad_spotted/status/986253381344907265
https://archive.is/gNGDJ
There's an underdiscussed contradiction between the idea that our society would make almost all knowledge available freely and instantaneously to almost everyone and that almost everyone would find gainful employment as knowledge workers. Value is in scarcity not abundance.
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You’d need to turn reputational-based systems into an income stream
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november 2016 by nhaliday
Neutral theory of molecular evolution - 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.
wiki  reference  genetics  evolution  genomics  bio  concept  thinking  mutation 
november 2016 by nhaliday
Talkin’ ’bout their generations | West Hunter
According to the Decode results, mothers contribute 15 mutations, regardless of age, while men contribute 25 + 2*(g-20) mutations, when g is the average paternal age. As I pointed out earlier, if g is the same in both sexes, the average number of mutations is just 2g, which makes for 2 mutations per calendar year. I’ve been checking out average maternal age: it doesn’t vary much. The lowest I’ve seen was 26, the highest 30, so 28 is a reasonable number. So far, in the data we’ve gathered, the population with the highest paternal age was in Gambia, with an average paternal age of 47. If we assume that the average maternal age is 28 (which look about right from the graph: I haven’t digitized it yet) then the average kid would receive 94 new mutations (15 maternal, 79 paternal). With an average generation length of 37.5 years (the average of 28 and 47), that makes for 2.5 mutations per calendar year: about 15% higher than you would see in most populations, where the gap between average maternal and paternal age is not nearly as large.

A Gambia-sized gap would result in a noticeably higher rate of neutral genetic divergence. If it had existed long enough you might be able to notice it, but I think there’s a better chance of seeing this effect in Australian Aborigines, who had high average paternal age and might have had it for a long time. Other than the Australians, I would guess that all the old-dad societies are relatively recent.

The higher mutational load is not just a consequence of the higher per-year mutation rate in these old-dad societies – since generations are longer, there is less selection per calendar year (considering that most selection acts early in life). The number of mutations per generation is probably the most important number. I found some numbers for Polar Eskimos, hunter-gatherers (they gather snow) in a tough environment: average maternal age was 27, average paternal age was 32, for an average generation length of 29.5. They’d have 64 mutations a generation: the per-generation rate in Gambia is 47% higher.

There are also qualitative differences in selection: selection is weaker in childhood and stronger in midlife in an old-dad society, as Henry pointed out. So that situation should select for longer life, except that’s hard to manage in the presence of higher-than-usual genetic load.

https://westhunt.wordpress.com/2012/10/19/base-substitutions-and-deletions/
According to Jim Crow”s 2006 article, base substitutions are mostly (overwhelmingly) from males and increase with paternal age, but small deletions are contributed about equally by males and females, with no noticeable age effect. Probably the deletions happen during meiosis.

So, with a huge gene like those involved in Duchenne’s muscular dystrophy or neurofibromatosis I, which have many exons (79 for dystrophin), many of the mutations are caused by deletions. The paternal age effect is weaker for those syndromes (since less than half of the causal mutations are base substitutions)

https://westhunt.wordpress.com/2012/08/26/gerontocratic-polygyny/
https://westhunt.wordpress.com/2012/09/05/obvious-yessss-it-was-obvious/
https://westhunt.wordpress.com/2012/08/22/paternal-age/
https://westhunt.wordpress.com/2012/09/17/gambia/
https://westhunt.wordpress.com/2012/09/16/paternal-age-and-the-force-of-mortality/
No surprises here save one. While selection for survival should extend male lifespans by 10 to 20 years in the case of old fathers, selection for survival before the age of reproduction is much weaker in the the case of older fathers. A prediction is that adolescent and young male death rates should be higher in old father societies because selection is weaker. I never realized that.

Hamilton’s theory does not describe human life history very well, as Rogers shows in his Figure 16.1 and discusses in the text. Human female fertility ceases long before the theory predicts that it should and humans live much longer. The reconciliation certainly has to do with kin selection or indirect selection. For example Kris Hawkes pushes the “grandmother hypothesis” according to which females cease reproduction and instead work for their daughters’ children. If she is right this grandmother effect selected for the prolonged human lifespan, and the long lifespan of males is a side-effect of selection for long life in females.
west-hunter  objektbuch  genetics  genetic-load  developmental  paternal-age  epidemiology  science-anxiety  scitariat  multi  social-structure  life-history  mutation  🌞  effect-size  data  ideas  speculation  methodology  gender  gender-diff  sex  africa  recent-selection  pop-diff  kinship  selection  population-genetics  electromag  longevity  aging  iq  intelligence  neuro  eden  explanans  age-generation 
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
http://onlinelibrary.wiley.com/doi/10.1111/j.0014-3820.2000.tb00693.x/abstract

COMPENSATING FOR OUR LOAD OF MUTATIONS: FREEZING THE MELTDOWN OF SMALL POPULATIONS

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.
west-hunter  sapiens  genetics  genetic-load  archaics  speculation  methodology  competition  population-genetics  gene-flow  europe  critique  evolution  mutation  pop-structure  multi  study  links  commentary  discussion  context  dimensionality  scitariat  stylized-facts  poast  gene-drift  population  magnitude  street-fighting  nibble  aphorism  pop-diff  africa  antiquity  comparison  troll  lol  stereotypes  alien-character  speaking 
november 2016 by nhaliday
Faster than Fisher | West Hunter
There’s a simple model of the spread of an advantageous allele:  You take σ, the typical  distance people move in one generation, and s,  the selective advantage: the advantageous allele spreads as a nonlinear wave at speed  σ * √(2s).  The problem is, that’s slow.   Suppose that s = 0.10 (a large advantage), σ = 10 kilometers, and a generation time of 30 years: the allele would take almost 7,000 years to expand out 1000 kilometers.

...

This big expansion didn’t just happen from peasants marrying the girl next door: it required migrations and conquests. This one looks as if it rode with the Indo-European expansion: I’ll bet it started out in a group that had domesticated only horses.

The same processes, migration and conquest, must explain the wide distribution of many geographically widespread selective sweeps and partial sweeps. They were adaptive, all right, but expanded much faster than possible from purely local diffusion. We already have reason to think that SLC24A5 was carried to Europe by Middle Eastern farmers; the same is probably true for the haplotype that carries the high-activity ergothioniene transporter and the 35delG connexin-26/GJB2 deafness mutation. The Indo-Europeans probably introduced the T-13910 LCT mutation and the delta-F508 cystic fibrosis mutation, so we should see delta-F508 in northwest India and Pakistan – and we do !

https://westhunt.wordpress.com/2014/11/22/faster-than-fisher/#comment-63067
To entertain a (possibly mistaken) physical analogy, it sounds like you’re suggested a sort genetic convection through space, as opposed to conduction. I.e. Entire masses of folks, carrying a new selected variant, are displacing others – as opposed to the slow gene flow process of “girl-next-door.” Is that about right? (Hopefully I haven’t revealed my ignorance of basic thermodynamics here…)

Has there been any attempt to estimate sigma from these time periods?

Genetic Convection: https://westhunt.wordpress.com/2015/02/22/genetic-convection/
People are sometimes interested in estimating the point of origin of a sweeping allele: this is probably effectively impossible even if diffusion were the only spread mechanism, since the selective advantage might well vary in both time and space. But that’s ok, since population movements – genetic convection – are real and very important. This means that the difficulties in estimating the origin of a Fisher wave are totally insignificant, compared to the difficulties of estimating the effects of past colonizations, conquests and Völkerwanderungs. So when Yuval Itan and Mark Thomas estimated that 13,910 T LCT allele originated in central Europe, in the early Neolithic, they didn’t just go wrong because of failing to notice that the same allele is fairly common in northern India: no, their whole notion was unsound in the first place. We’re talking turbulence on steroids. Hari Seldon couldn’t figure this one out from the existing geographic distribution.
west-hunter  genetics  population-genetics  street-fighting  levers  evolution  gavisti  🌞  selection  giants  nibble  fisher  speed  gene-flow  scitariat  stylized-facts  methodology  archaeology  waves  frontier  agri-mindset  analogy  visual-understanding  physics  thermo  interdisciplinary  spreading  spatial  geography  poast  multi  volo-avolo  accuracy  estimate  order-disorder  time  homo-hetero  branches  trees  distribution  data  hari-seldon  aphorism  cliometrics  aDNA  mutation  lexical 
november 2016 by nhaliday
The Day Before Forever | West Hunter
Yesterday, I was discussing the possibilities concerning slowing, or reversing aging – why it’s obviously possible, although likely a hard engineering problem. Why partial successes would be valuable, why making use of the evolutionary theory of senescence should help, why we should look at whales and porcupines as well as Jeanne Calment, etc., etc. I talked a long time – it’s a subject that has interested me for many years.

But there’s one big question: why are the powers that be utterly uninterested ?

https://www.facebook.com/ISIInc/videos/vb.267919097102/641005449680861/?type=2&theater
The Intercollegiate Studies Institute and the Abagail Adams Institute host a debate between Peter Thiel and William Hurlbut. Resolved: Technology Should Treat Death as an Enemy

https://westhunt.wordpress.com/2017/07/03/the-best-things-in-life-are-cheap-today/
What if you could buy an extra year of youth for a million bucks (real cost). Clearly this country ( or any country) can’t afford that for everyone. Some people could: and I think it would stick in many people’s craw. Even worse if they do it by harvesting the pineal glands of children and using them to manufacture a waxy nodule that forfends age.

This is something like the days of old, pre-industrial times. Back then, the expensive, effective life-extender was food in a famine year.

https://westhunt.wordpress.com/2017/04/11/the-big-picture/
Once upon a time, I wrote a long spiel on life extension – before it was cool, apparently. I sent it off to an interested friend [a science fiction editor] who was at that time collaborating on a book with a certain politician. That politician – Speaker of the House, but that could be anyone of thousands of guys, right? – ran into my spiel and read it. His immediate reaction was that greatly extending the healthy human life span would be horrible – it would bankrupt Social Security ! Nice to know that guys running the show always have the big picture in mind.

Reminds me of a sf story [Trouble with Lichens] in which something of that sort is invented and denounced by the British trade unions, as a plot to keep them working forever & never retire.

https://westhunt.wordpress.com/2015/04/16/he-still-has-that-hair/
He’s got the argument backward: sure, natural selection has not favored perfect repair, so says the evolutionary theory of of senescence. If it had, then we could perhaps conclude that perfect repair was very hard to achieve, since we don’t see it, at least not in complex animals.* But since it was not favored, since natural selection never even tried, it may not be that difficult.

Any cost-free longevity gene that made you live to be 120 would have had a small payoff, since various hazards were fairly likely to get you by then anyway… And even if it would have been favored, a similar gene that cost a nickel would not have been. Yet we can afford a nickel.

There are useful natural examples: we don’t have to start from scratch. Bowhead whales live over 200 years: I’m not too proud to learn from them.

Lastly , this would take a lot of work. So what?

*Although we can invent things that evolution can’t – we don’t insist that all the intermediate stages be viable.

https://westhunt.wordpress.com/2013/12/09/aging/
https://westhunt.wordpress.com/2014/09/22/suspicious-minds/

doesn't think much of Aubrey de Gray: https://westhunt.wordpress.com/2013/07/21/of-mice-and-men/#comment-15832
I wouldn’t rely on Aubrey de Gray.

It might be easier to fix if we invested more than a millionth of a percent of GNP on longevity research. It’s doable, but hardly anyone is interested. I doubt if most people, including most MDs and biologists, even know that it’s theoretically possible.

I suppose I should do something about it. Some of our recent work ( Henry and me) suggests that people of sub-Saharan African descent might offer some clues – their funny pattern of high paternal age probably causes the late-life mortality crossover, it couldn’t hurt to know the mechanisms involved.

Make Room! Make Room!: https://westhunt.wordpress.com/2015/06/24/make-room-make-room/
There is a recent article in Phys Rev Letters (“Programed Death is Favored by Natural Selection in Spatial Systems”) arguing that aging is an adaptation – natural selection has favored mechanisms that get rid of useless old farts. I can think of other people that have argued for this – some pretty smart cookies (August Weismann, for example, although he later abandoned the idea) and at the other end of the spectrum utter loons like Martin Blaser.

...

There might could be mutations that significantly extended lifespan but had consequences that were bad for fitness, at least in past environments – but that isn’t too likely if mutational accumulation and antagonistic pleiotropy are the key drivers of senescence in humans. As I said, we’ve never seen any.

more on Martin Blaser:
https://westhunt.wordpress.com/2013/01/22/nasty-brutish-but-not-that-short/#comment-7514
This is off topic, but I just read Germs Are Us and was struck by the quote from Martin Blaser ““[causing nothing but harm] isn’t how evolution works” […] “H. pylori is an ancestral component of humanity.”
That seems to be the assumption that the inevitable trend is toward symbiosis that I recall from Ewald’s “Plague Time”. My recollection is that it’s false if the pathogen can easily jump to another host. The bulk of the New Yorker article reminded me of Seth Roberts.

I have corresponded at length with Blaser. He’s a damn fool, not just on this. Speaking of, would there be general interest in listing all the damn fools in public life? Of course making the short list would be easier.

https://westhunt.wordpress.com/2013/01/18/dirty-old-men/#comment-64117
I have corresponded at length with Blaser. He’s a damn fool, not just on this. Speaking of, would there be general interest in listing all the damn fools in public life? Of course making the short list would be easier.
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november 2016 by nhaliday
Why Information Grows – Paul Romer
thinking like a physicist:

The key element in thinking like a physicist is being willing to push simultaneously to extreme levels of abstraction and specificity. This sounds paradoxical until you see it in action. Then it seems obvious. Abstraction means that you strip away inessential detail. Specificity means that you take very seriously the things that remain.

Abstraction vs. Radical Specificity: https://paulromer.net/abstraction-vs-radical-specificity/
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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

https://westhunt.wordpress.com/2016/05/08/you-dont-need-a-weatherman/#comment-78939
Chinese, Koreans, Japanese and Ashkenazi Jews all have high levels of myopia. Australian Aborigines have almost none, I think.

https://westhunt.wordpress.com/2016/05/08/you-dont-need-a-weatherman/#comment-79094
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.
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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.
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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

bundles : abstractpatterns

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