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> The number of subjects absolutely does matter. Selecting mice for intelligence is all nice and well, but you have to breed thousands, and "discard" most of them. Both in traditional breeding as well as with genetic engineering, you have to have sufficient number of trials to conclude anything. The number of 'subjects' is elastic. If applied to IVF, that's everyone who uses IVF. In embryo selection, you are selecting out of available embryos, eg 1 out of 5. With other techniques like ovarian biopsy or gametogenesis, you are potentially selecting 1 out of 100+. Hence, plenty of subjects. > You can reliably quantify the intelligence of a mouse at a few weeks of age and breed it soon thereafter (though you would probably use that "IQ" to score its parents). You can't reliably quantify health and intelligence of a Human within years, especially if you are aiming for "multiple standard deviations" above average. At the very least the practical generational span is 20 years, and usually much longer if the subjects have any say in the matter. All irrelevant, since no one is suggesting phenotyping. That's the point of the polygenic scores. > The mutations they screen for are virtually never causal, but merely markers associated with actually causal sequences. Also irrelevant. When you are doing prediction for selection, all you need to do is predict the one with the highest scores. There is zero need to identify even a single causal variant. GWASes are so predictive because the SNPs are in LD with the causal variants, and the LD does not change abruptly in a single selection step. However, since you think that none have been identified, you should go read the appendix to Lee et al 2018, among other IQ GWASes, where they do estimates, and turn up scores of SNPs which have causal probabilities >90%. |