Hsu links a review paper70305-4/fulltext “‘Reliability of genomic predictions for North American Holstein bulls’, VanRaden et al 2009”) on the topic which discusses the usefulness of genetic prediction using cheap small SNP chips and how well it fits the highly-polygenic non-fixed model (which would imply that there’s still a very long way to go before gains from breeding disappear):
Marker effects for most other traits were evenly distributed across all chromosomes with only a few regions having larger effects, which may explain why the infinitesimal model and standard quantitative genetic theories have worked well. The distribution of marker effects indicates primarily polygenic rather than simple inheritance and suggests that the favorable alleles will not become homozygous quickly, and genetic variation will remain even after intense selection. Thus, dairy cattle breeders may expect genetic progress to continue for many generations.
Nonlinear and linear predictions were correlated by >0.99 for most traits. The nonlinear genomic model had little advantage in R2 over the linear model except for fat and protein percentages with increases of 8 and 7%, respectively (Table 2). Gains in R2 averaged 3% with simulated data (VanRaden, 2008) but generally were smaller with real data, which indicated that most traits are influenced by more loci than the 100 QTL used in simulation. The R2 improved when the prior assumption was that all markers have some effect rather than that most have no effect.
If I understand correctly, the inheritability of a trait often increases with a decrease of environmental variability.
In this study they are comparing cattle raised in modern times in a developed country (the Netherlands, I think), hence the environment was likely about optimal, and unsurprising most of the observed phenotypic variation had a genetic origin. Ethiopian subsistence farmers probably don’t have access to cheap soy and corn and have their cows graze on marginal lands, therefore nutrient availability is likely the limiting factor in their milk production. Similar patterns can be found in traits like human stature and IQ, which are more inheritable in developed countries rather than in third-world countries, and are subject to quick bursts when a country becomes more developed.
Also, in the modern dairy industry, cows are slaughtered around the age four and sold for beef, while in subsistence farming they are likely to be kept for many years past peak milk production, resulting in lower lifetime averages.
As for the specific of the inheritability of a continuous trait, I’m not an expert of genetics, but it seems to me that a polygenic model makes intuitive sense, as was quantitatively confirmed by this study. They found that a non-linear model predicts the data better than a linear model, which is however quite good, and again I don’t find this particularly surprising since linear approximations often perform well on sufficiently smooth functions, especially in the neighbourhood of a stationary point (where you can expect the genotypes of a relatively stable population to be, approximately).
My problem with Hsu line of argument is that he extrapolates predictions of these kinds of linear models way past observed phenotypes, which is something that has no theoretical basis, especially given that non-linear effects (logarithmic and logistic responses, square-cube effects, etc.) are ubiquitous in biology.
If I understand correctly, the inheritability of a trait often increases with a decrease of environmental variability.
Yes. (More relevantly, I’d say that as the environment gets better, the heritability will increase.)
Overall, your points about the Ethiopian cows are correct but I don’t think they would account for more than a relatively small chunk of the difference between the best American milk cows and regular Ethiopian milk cows. It really does look to me like humanity has pushed milk capacity dozens of standard deviations past where it would have been even centuries ago.
They found that a non-linear model predicts the data better than a linear model, which is however quite good, and again I don’t find this particularly surprising since linear approximations often perform well on sufficiently smooth functions, especially in the neighbourhood of a stationary point (where you can expect the genotypes of a relatively stable population to be, approximately).
Not surprising no, but people have seriously argued to me that things like embryo selection will not work well or at all because it’s possible important stuff will be due to nonlinear genetic interactions (most recently on Google+, but I’ve seen it elsewhere). So it’s something that apparently needs to be established.
My problem with Hsu line of argument is that he extrapolates predictions of these kinds of linear models way past observed phenotypes, which is something that has no theoretical basis, especially given that non-linear effects
I’m not sure how seriously Hsu takes the 30SD part as translating to underlying intelligence; the issue of SDs/normal ordinal distribution of intelligence in the population vs a hypothetical underlying cardinal scale of intelligence (http://lesswrong.com/lw/kcs/what_resources_have_increasing_marginal_utility/b0qb) is not really easy to come down to a hard conclusion except to note that in some areas AI progress curves spend a while in the human range but often go steadily beyond (eg computer chess), which suggests to me that large difference in human intelligence rankings do translate to fairly meaningful (albeit not huge) absolute intelligence differences, in which case the 30SDs might translate to a lot of real intelligence and not some trivial-but-statistically-measurable improvements in how fast they can do crosswords or something.
I think probably the best response here is to take it as saying that the lower limit will be extremely high and equivalent to the top observed phenotype, like a von Neumann. Since right now estimates of IVF sperm donor usage in the USA suggest something like 30-60k kids a year are born that way*, if the fertility doctors dropped in an iterated embryo selection procedure before implantation. I think 30-60k geniuses would make a major difference to society**, and if they happened to be even smarter than the previous top observed phenotypes...?
* I use this figure because looking into the matter, I don’t think many women who could bear kids normally would willing sign up for IVF just to get the benefits of embryo selection. It’s much too painful, inconvenient, and signals the wrong values. But women who have to do IVF if they ever want to have a kid would be much more likely to make use of it.
** to put 30-60k in perspective, the USA has around 4m babies a year, so ignoring demographics, the top 1% (roughly MENSA level, below-average for LW, well below average for cutting-edge research) of babies represents 40k. If all the IVFers used embryo selection and it boosted the IVF babies to an average of just 130, well below genius, it’d practically single-handedly double the 1%ers.
Hsu links a review paper70305-4/fulltext “‘Reliability of genomic predictions for North American Holstein bulls’, VanRaden et al 2009”) on the topic which discusses the usefulness of genetic prediction using cheap small SNP chips and how well it fits the highly-polygenic non-fixed model (which would imply that there’s still a very long way to go before gains from breeding disappear):
Thanks for the link.
If I understand correctly, the inheritability of a trait often increases with a decrease of environmental variability.
In this study they are comparing cattle raised in modern times in a developed country (the Netherlands, I think), hence the environment was likely about optimal, and unsurprising most of the observed phenotypic variation had a genetic origin.
Ethiopian subsistence farmers probably don’t have access to cheap soy and corn and have their cows graze on marginal lands, therefore nutrient availability is likely the limiting factor in their milk production.
Similar patterns can be found in traits like human stature and IQ, which are more inheritable in developed countries rather than in third-world countries, and are subject to quick bursts when a country becomes more developed.
Also, in the modern dairy industry, cows are slaughtered around the age four and sold for beef, while in subsistence farming they are likely to be kept for many years past peak milk production, resulting in lower lifetime averages.
As for the specific of the inheritability of a continuous trait, I’m not an expert of genetics, but it seems to me that a polygenic model makes intuitive sense, as was quantitatively confirmed by this study.
They found that a non-linear model predicts the data better than a linear model, which is however quite good, and again I don’t find this particularly surprising since linear approximations often perform well on sufficiently smooth functions, especially in the neighbourhood of a stationary point (where you can expect the genotypes of a relatively stable population to be, approximately).
My problem with Hsu line of argument is that he extrapolates predictions of these kinds of linear models way past observed phenotypes, which is something that has no theoretical basis, especially given that non-linear effects (logarithmic and logistic responses, square-cube effects, etc.) are ubiquitous in biology.
Yes. (More relevantly, I’d say that as the environment gets better, the heritability will increase.)
Overall, your points about the Ethiopian cows are correct but I don’t think they would account for more than a relatively small chunk of the difference between the best American milk cows and regular Ethiopian milk cows. It really does look to me like humanity has pushed milk capacity dozens of standard deviations past where it would have been even centuries ago.
Not surprising no, but people have seriously argued to me that things like embryo selection will not work well or at all because it’s possible important stuff will be due to nonlinear genetic interactions (most recently on Google+, but I’ve seen it elsewhere). So it’s something that apparently needs to be established.
I’m not sure how seriously Hsu takes the 30SD part as translating to underlying intelligence; the issue of SDs/normal ordinal distribution of intelligence in the population vs a hypothetical underlying cardinal scale of intelligence (http://lesswrong.com/lw/kcs/what_resources_have_increasing_marginal_utility/b0qb) is not really easy to come down to a hard conclusion except to note that in some areas AI progress curves spend a while in the human range but often go steadily beyond (eg computer chess), which suggests to me that large difference in human intelligence rankings do translate to fairly meaningful (albeit not huge) absolute intelligence differences, in which case the 30SDs might translate to a lot of real intelligence and not some trivial-but-statistically-measurable improvements in how fast they can do crosswords or something.
I think probably the best response here is to take it as saying that the lower limit will be extremely high and equivalent to the top observed phenotype, like a von Neumann. Since right now estimates of IVF sperm donor usage in the USA suggest something like 30-60k kids a year are born that way*, if the fertility doctors dropped in an iterated embryo selection procedure before implantation. I think 30-60k geniuses would make a major difference to society**, and if they happened to be even smarter than the previous top observed phenotypes...?
* I use this figure because looking into the matter, I don’t think many women who could bear kids normally would willing sign up for IVF just to get the benefits of embryo selection. It’s much too painful, inconvenient, and signals the wrong values. But women who have to do IVF if they ever want to have a kid would be much more likely to make use of it.
** to put 30-60k in perspective, the USA has around 4m babies a year, so ignoring demographics, the top 1% (roughly MENSA level, below-average for LW, well below average for cutting-edge research) of babies represents 40k. If all the IVFers used embryo selection and it boosted the IVF babies to an average of just 130, well below genius, it’d practically single-handedly double the 1%ers.