As a side note, here’s the succinct algorithm I thought of the “clean up” the human genome.
For each allele:
Sample across the population, find the prevalence of different versions of the allele
Expected : most alleles are going to be either [99% version A][1% or slightly mutated A]
Take version A, the other versions are incorrect
Some Alleles will be in the form of [40% version A][50% version B] [10% mutated versions of A or B]
In this case, look at the data and try to see if A or B is statistically correlated with a desirable trait. If you can’t determine, choose the version the parents of this designer baby have.
And that’s it. You don’t need to know what most of the genes do. Statistically speaking you are going to almost always be right with this algorithm, the resulting baby will not be uber but will not have as many problems as baseline humanity, because by simple probability, most mutations are neutral or deleterious, and a significantly beneficial mutation will have a prevalence greater than 1%.
You’re right that most de novo mutations are harmful, but I don’t think this strategy is necessarily optimal. There’s no guarantee that rare alleles are harmful.
In this case, look at the data and try to see if A or B is statistically correlated with a desirable trait
This is more or less what I think the correct approach is, but you’re glossing over a lot of detail. There are big questions around HOW to do this, to what degree desirable traits are heritable, as well as tradeoffs inherent in the human genome where the answer as to which variant is the “better” cannot be given an unqualified answer.
I am not saying the algorithm is optimal. But it’s safe. Suppose you find a rare allele that your protein folding model predicts improves function. Why didn’t nature pick it? There may be a long term problem you can’t model, while picking the majority allele is a less risky choice.
Basically, nature only cares about what works over a reproductive lifetime. But nature has information you won’t have in any feasible computer model as it is sampling from actual lives.
It may be safe from an individual perspective, but if you always pick the more common allele, you are converging towards the modal genome, which would be a world where everyone is a clone of everyone else.
Genetic diversity is valuable both as a hedge against disease and because it lends itself to specialization, which is an important part of the modern economy.
As a side note, here’s the succinct algorithm I thought of the “clean up” the human genome.
For each allele:
Sample across the population, find the prevalence of different versions of the allele
Expected : most alleles are going to be either [99% version A][1% or slightly mutated A]
Take version A, the other versions are incorrect
Some Alleles will be in the form of [40% version A][50% version B] [10% mutated versions of A or B]
In this case, look at the data and try to see if A or B is statistically correlated with a desirable trait. If you can’t determine, choose the version the parents of this designer baby have.
And that’s it. You don’t need to know what most of the genes do. Statistically speaking you are going to almost always be right with this algorithm, the resulting baby will not be uber but will not have as many problems as baseline humanity, because by simple probability, most mutations are neutral or deleterious, and a significantly beneficial mutation will have a prevalence greater than 1%.
You’re right that most de novo mutations are harmful, but I don’t think this strategy is necessarily optimal. There’s no guarantee that rare alleles are harmful.
This is more or less what I think the correct approach is, but you’re glossing over a lot of detail. There are big questions around HOW to do this, to what degree desirable traits are heritable, as well as tradeoffs inherent in the human genome where the answer as to which variant is the “better” cannot be given an unqualified answer.
I am not saying the algorithm is optimal. But it’s safe. Suppose you find a rare allele that your protein folding model predicts improves function. Why didn’t nature pick it? There may be a long term problem you can’t model, while picking the majority allele is a less risky choice.
Basically, nature only cares about what works over a reproductive lifetime. But nature has information you won’t have in any feasible computer model as it is sampling from actual lives.
It may be safe from an individual perspective, but if you always pick the more common allele, you are converging towards the modal genome, which would be a world where everyone is a clone of everyone else.
Genetic diversity is valuable both as a hedge against disease and because it lends itself to specialization, which is an important part of the modern economy.