Gpuccio: Functional Information Methodology

As I pointed out, under some circumstances your method will grossly overestimate FI as you have defined it. You would at least have an argument if you redefined FI to be the information needed to keep a particular gene (say) functional.

Even if you adopt a more restricted (and intuitive) definition of FI, however, your procedure still can’t tell you about increases in FI in a lineage. All you’re doing is looking at sequence conservation of various species with respect to human, right? You observe that conservation is almost always lower as you look across longer branches. But conservation is only a lower bound on the FI of the sequence; a changing lower bound tells you precisely nothing about changes to the quantity itself. It’s not mathematically possible to draw that kind of conclusion.

In fact, we would expect to see conservation decreasing with increasing branch length even if the function and the FI of a gene haven’t changed at all. Functional sequence can change without changing function, but it does so more slowly (sometimes much more slowly) than nonfunctional sequence changes, since the mutational avenues that preserve function are much more restricted (and may only become accessible with a different genetic background or in a different environment).

I’ll offer the same example I gave in the other thread: the human immune system. Your body contains DNA with more than 500 bits of FI, coding for hundreds of specific antibodies that are highly functional, each precisely tuned to a protein on a particular pathogen or pathogen strain. You were not born with DNA that had that information in it; it was generated by a process of random mutation and selection.

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