I’m going through a bunch of comparative transcriptomics & genomics papers purporting to find genes associated with aging by looking at either which genes are overexpressed in young vs old animals, or highly mutated between long-lived vs short-lived species.
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Maybe the problem with the transcriptomics is study design? N=16 biopsies, list all genes with p<0.05 difference between old & young transcript levels, is pretty typical, and maybe that’s just too much noise?
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Ok, not “maybe”, it is too much noise. I’ll add sample sizes, p-values, and relative fold changes to my notes; will write up results in a blog post.
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How expensive?
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A mouse lifespan study with 100 mice is about $200k, $400k with thermoneutral housing. This doesn’t count the cost of genetic modification.
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Is it viable to do that with daphnia?
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Tentatively, yes. There’s one lab that’s demonstrated CRISPR knockouts and another that’s demonstrated siRNA knockdowns.
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I wonder if group testing (knock out N genes in the mouse - if nothing happens eliminate all of them, if something happens narrow it down to which of those N genes matters) is a viable approach to speed up the process? Or is there too much intergene interaction for that?
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I’d worry that too many of those would just be immediately fatal.
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