The question is a bit vague (not that that is all bad) so my answer will be as well. There are (infinitely) many ways to define sequences and matrices of numbers and polynomials. Some of the simpler ones lead to sequences with special names. Simple transformations will send some of these nice ones to others. A sequence of polynomials gives an array of coefficients . Diagonals can give something else. For example the binomial coefficients have their recurrence $\binom{n}{k}=\binom{n-1}{k-1}+\binom{n-1}{k}$. If we change it to $B(n,k)=s\,B(n-1,k-1)+B(n-1,k)$ (with appropriate initial conditions) then we just have $B(n,k)=\binom{n}{k}s^k$ and each row can be viewed as a polynomial $(1+s)^n$. It is well known that the Fibonacci numbers can be viewed as sums of certain diagonals of Pascals triangle. If we use instead the B(n,k) then we get the Fibonacci polynomials which start your question. $1,1,s+1,2s+1,s^2+3s+1,3s^2+4s+1\dots$ Splitting these into even and odd terms gives us $1,s+1,s^2+3s+1,\dots$ and also $1,2s+1,3s^2+4s+1,\dots$ either is a basis of the space of polynomials as is $1,s,s^2,\dots$ sending any one of these to an integer sequence (starting with 1) sends the others to another. See what the linear transformations in your examples do to $1,s,s^2,s^3,\dots$
Here is another example (which I was happy to discover) My personal favorite recurrence is that for convergents to $\sqrt2$, $1/1,3/2,7/5,17/12,41/29,\dots$ The numerators $1,3,7,17,41,\dots$ and the denominators 1,2,5,12,29,... both satisfy the recurrence $a_n=2a_{n-1}+a_{n-2}$ just with different initial conditions. They could be called the Pell and Pell-Lucas numbers. If we say $A_n=2A_{n-1}+sA_{n-2}$ then we get a sequence $1,1,s+2,3s+4,s^2+8s+8,5s^2+20s+16,\dots$ These are closely related to Chebyshev polynomials of the first kind.(replace s by -s^2 and multiply every other one by s). Avoiding many digressions, Consider the two sequences
$$1,s+2,s^2+8s+8,s^3+18s^2+48s+32,\dots$$ $$1,3s+4,5s^2+20s+16,7s^3+56s^2+112s+64,\dots$$
If the first is mapped to 1,0,0,0,0...then the last is mapped to 1, 2/3, -8/15, 32/21, -128/15, 2560/33, -1415168/1365, 57344/3, -118521856/255 which is intriguingly close to the negatives of the cosecant numbers 1, -1/3, 7/15, -31/21, 127/15, -2555/33, 1414477/1365, -57337/3, 118518239/255
If the last one is mapped to 1,0,0,0,0 then the first is mapped to -2,16,-272,7936,... which are the tangent numbers (but with alternating signs).
later: The OEIS and associated Journal of Integer Sequences are full of sequences and transformations taking one to another. The example above was an illustration (the only one I tried) of what I am sure would generate many examples (probably some nicer than the one I gave). Start with an integer recurrence of the form $a_0=0$ $a_1=1$ and $a_m=u(m)a_{m-1}+v(m)a_{m-2}$. Replace this with $A_0=1$ $A_1=1$ and $A_m=u(m)a_{m-1}+sv(m)a_{m-2}$. Then (in general) $A_{2t}$ and $A_{2t+1}$ are both polynomials of degree $t$ so one has two bases for the additive vector-space of polynomials. Take the linear transformation which sends one to $1,0,0,0,\dots$ and see what it does to the other (or some other basis of that space). Look up the associated sequence (perhaps the numerators and denominators if it is a rational sequence) in the OEIS and see what you got. Examples (which I have not investigated) include powers of 2 ($a_n=a_{n-1}+2a_{n-2}$) and factorials ($a_n=(n-1)a_{n-1}+(n-1) a_{n-2}$). Those two are shifted, it would be nicer to start with $a_0=1$ and $a_1=1$ making appropriate adjustments. Starting the second example with $a_0=1$ and $a_1=0$ gives derangements. One could consider other initial conditions $A_0=c_0$ and $A_1=c_1$
There are many sequences of orthogonal polynomials like the Chebshev polynomials I mentioned above, (Legendre, Laguerre, Hermite, Jacobi,etc.) which are alternately even and odd. Dividing the odd ones by $x$ and then replacing $x$ with $\sqrt{x}$ (maybe taking absolute value of coefficients) gives more examples. Exponential generating functions might be more appropriate in some cases.
All that we are using of the polynomial structure is the (additive) book-keeping for the coordinates of a vector-space. Of course for famous sequences of polynomials that is still interesting. In general we could instead look at infinite lower triangular matrices. Then I think that your linear transformations correspond to the first column of the inverse matrix and the image on the companion sequence is simply the first column of a certain matrix product. Other columns might be of interest as well.