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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
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
Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders : Nature Genetics : Nature Research
Autism spectrum disorder (ASD) risk is influenced by common polygenic and de novo variation. We aimed to clarify the influence of polygenic risk for ASD and to identify subgroups of ASD cases, including those with strongly acting de novo variants, in which polygenic risk is relevant. Using a novel approach called the polygenic transmission disequilibrium test and data from 6,454 families with a child with ASD, we show that polygenic risk for ASD, schizophrenia, and greater educational attainment is over-transmitted to children with ASD. These findings hold independent of proband IQ. We find that polygenic variation contributes additively to risk in ASD cases who carry a strongly acting de novo variant. Lastly, we show that elements of polygenic risk are independent and differ in their relationship with phenotype. These results confirm that the genetic influences on ASD are additive and suggest that they create risk through at least partially distinct etiologic pathways.
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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):

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.
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
Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits:
Pedigree- and SNP-Associated Genetics and Recent Environment are the Major Contributors to Anthropometric and Cardiometabolic Trait Variation:

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.:
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:
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.

The surprising implications of familial association in disease risk:
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:
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.

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june 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:

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:

Singleton Variants Dominate the Genetic Architecture of Human Gene Expression:
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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.
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may 2017 by nhaliday
Soft sweeps are the dominant mode of adaptation in the human genome | bioRxiv
Detection of 2000 instances of recent human selection, half of which are specific to individual human populations, and many of which affect the central nervous system. Note this doesn’t cover polygenic selection, so it’s a very loose lower bound on how much recent human evolution there has been.

How Sweeps Get Soft:
A puzzling finding from the search for selection in humans is the large number of apparently selected variants versus the apparent absence of high frequency selected regions and regions that have become fixed in our species.

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

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


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

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

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


What is the most likely cause of such variations in the mutation rate? Right now, I’d say differences in average paternal age. We know that modest differences (~5 years) in average paternal age can easily generate ~20% differences in the mutation rate. Such between-population differences in mutation rates seem quite plausible, particularly since the Neolithic.
more recent:
Probably not, but the question is complex: depends on the shape of the deleterious mutational spectrum [which we don’t know], ancient and recent demography, paternal age, and the extent of truncation selection in the population.
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may 2017 by nhaliday
The 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
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april 2017 by nhaliday
Genome-Wide Association Study Reveals Multiple Loci Influencing Normal Human Facial Morphology
Domestic dogs exhibit tremendous phenotypic diversity, including a greater variation in body size than any other terrestrial mammal. Here, we generate a high density map of canine genetic variation by genotyping 915 dogs from 80 domestic dog breeds, 83 wild canids, and 10 outbred African shelter dogs across 60,968 single-nucleotide polymorphisms (SNPs). Coupling this genomic resource with external measurements from breed standards and individuals as well as skeletal measurements from museum specimens, we identify 51 regions of the dog genome associated with phenotypic variation among breeds in 57 traits. The complex traits include average breed body size and external body dimensions and cranial, dental, and long bone shape and size with and without allometric scaling. In contrast to the results from association mapping of quantitative traits in humans and domesticated plants, we find that across dog breeds, a small number of quantitative trait loci (≤3) explain the majority of phenotypic variation for most of the traits we studied. In addition, many genomic regions show signatures of recent selection, with most of the highly differentiated regions being associated with breed-defining traits such as body size, coat characteristics, and ear floppiness. Our results demonstrate the efficacy of mapping multiple traits in the domestic dog using a database of genotyped individuals and highlight the important role human-directed selection has played in altering the genetic architecture of key traits in this important species.
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april 2017 by nhaliday

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