what does mother nature say about GCs?

why is there not a bigger emphasis on minimizing GCs?

I know that higher puzzle levels generally reduce the allowed GCs slightly, but I feel especially virtuous when I have energy solutions with minimal GCs, yet there is no bonus for this.

What I’m asking is whether Mother Nature really awards a bonus of some kind for minimizing GCs, and if so whether the EteRNA model is somehow missing it?

Or conversely, if Mother Nature *likes* a moderate number of GCs, maybe the EteRNA model should further emphasize that!?!?!

The best answer I have for you is that we don’t really know how nature feels about G-Cs except that we know for sure it pisses her off when you use too many.

:smiley:

In humans, 40-55% see the human genome paper.
http://www.nature.com/nature/journal/…

similar among other mammals as well.
http://genome.cshlp.org/content/20/8/…

It can be as low as 20% in the malaria parasite, all the way to 70% in some bacteria or viruses, but those are real outliers.

So the short answer is learning to super-minimize the GC content is more of an exercise in learning EXACTLY how much each type of shape costs to make.

It’s like boot camp for your energy budget - once you learn not to spend all your grocery money on cake and ice-cream, there are no budget constraints when you graduate to submitting lab designs (so far!).

ok, those are good factoids! but I guess it leads to another question, about whether when we leave mother nature and go to the lab, do we have reasons why even there we want to stick to these ratios of GCs?

@JRStern If we use a very large number of GC bonds, the RNA doesn’t even sequence properly let alone fold properly. My profile has in the first bullet point a link to 6 past GC-heavy designs that simply outright failed in the lab. Other than that I don’t think we have any reasons.

So, too many GCs just plain doesn’t work. Is something like this also true of the minimal number of GCs, that it just lacks cohesion and just doesn’t work - or is the matter still open on the low end? Thanks.

:smiley: Almost everything is open.

well it’s interesting, isn’t it? I mean, we expect nature to find minimal solutions, when the real achievement seems to be finding *any* solution, and you always have to ask, “solution for what?” which is going to depend on characteristics of the environment, so just what *does* dictate how much GC (for example) nature wants to use? apparently it’s not minimal, and not maximal. I guess if it needs to fold to a certain shape, then optimal is the most GCs that let it fold to that shape, which will depend on all sorts of things. just thinking out loud here. that would have to include the full 3D configuration, of the RNA, and of whatever non-RNA things it needs to bind to. probably impossible to judge ahead of time.

In the papers linked above, high GC content is usually associated with mRNAs which code for proteins. These don’t have any well-defined shape, they are just dumb information carriers, and it doesn’t matter so much what their melting temperature is because there ARE little chemically powered robots that take them apart and read them out (the polymerases and the ribosome).

Just wanted to mention that because you are right, the selection criteria for free-standing RNA shapes will be different. You can see that in the difference between introns (often where non-coding RNA hides out) and exons (code for proteins) in the human genome paper.

huh. well, we have some mRNA puzzles, don’t we? but you do say, “usually”. which can mean either than the mRNA don’t, or the regular RNA, do. but (just stream of consciousness here), if mRNA have different rules, should they be scored differently in this game?