Simulating autosomes and X-chromosomes (at the same time)

[Yazzi McDonough]

Hey everyone,

I'm trying to run a simple WF model, but where (sexual) diploids have both an autosome and an X-chromosome where mutations can arise/fix. Hopefully someone can help me understand how to model such a scenario?

I have given a (verbal) possible solution, but I'm brand new to SLiM, so it would be good to know whether this model does what I think it does before I spend the next eternity coding, debugging, and running tests...

----Further context----

Specifically, the idea is that every generation, a mutation may arise on either the autosome or X-chromosome, altering the fitness. It then carries out like any other SLiM simulation; over the generations this mutation segregates and eventually leads to substitution (or loss). This will go on for many generations, potentially leading to many fixations. At the end of the simulation, I want to count how many mutations substituted on the autosome, and how many on the X-chromosome.

----The issue----

It's very clear how to model either an autosome or X-chromosome (using the initilizeSex function), but less clear on how to model them both at the same time.

----My solution----

I understand that having multiple autosomes is not currently supported, other than the work around in section 6.1.4 of the manual (i.e., creating genomic regions separated by a small, highly recombining region).

I also see that modelling X and Y chromosomes with a psuedo autosomal region is done by initializing sex to autosome and suppressing recombination in a genomic region when the individual is male (section 14.5).

My thinking is, perhaps we can model this problem similar to the manual's section 14.5 and 6.1.4:

1. InitiliseSex to autosome
2. Create two genomic regions (g1 and g2) with high recombination separating them (i.e., acting as two chromosomes)
3. Set one genomic region to free recombination to represent the autosome (g1), and one region with conditional recombination (specifically, no recombination in males) to represent the X (g2)
4. On the first time-step, add a 'marker' mutation on all Males in the X-chromosome region to denote a male (as in 14.5). Since this section never recombines with anything, I believe this creates a Y chromosome.
   

We now have a scenario where one region freely recombines in either sex (i.e., autosomes), and one region that only recombines when the 'male-marker' is absent (i.e., the X-chromsome), which is great. There's also a Y-chromosomal region that's created as a byproduct (but more on that below).

----My question(s)----

So I have two questions:

• Does this model make sense? Or is there an easier way that I'm completely missing?
  

• I don't actually want any mutations to arise on the Y-chromosome region (or if they must, I don't want them to affect fitness or be tallied as a substitution), as I'm interested in only X and autosomal substitutions/fitness effects. So... is there a way to suppress mutations from arising in this region (say, if they occur in the region with the male marker). Since in the model I described X-chromosomes and Y-chromosomes are of the same genomic element (say, 'g2'), I believe that mutations will end up arising in this Y-chromosomal region, but perhaps I can create a statement that removes them from the population when they arise (I don't recall seeing something like this in the manual or workshops)?

------------

Any help would be greatly appreciated!

(This is my first time posting, so sorry if I've missed any formalities!)

[Ben Haller]

Hi Yazzi!  Your approach sounds good, and you found the relevant sections – 14.5, in particular.

Note that initializeRecombinationRate() has an optional sex parameter, so you can make the male vs. female recombination behaviors using SLiM's built-in facilities.

There is no easier way at present, although I hope that in future there will be.

You'll need to remove mutations in the Y yourself, yes.  See section 14.9 on modeling haploids; you'd use a similar approach, both for removing unwanted Y mutations, and also perhaps for removing fixed X mutations (which SLiM wouldn't automatically remove because it wouldn't understand that they're fixed).

Good luck!  A fairly advanced model for a brand-new SLiM user, but it sounds like you've got the right end of the stick.  If you get a working solution, it'd be great if you posted it here.  Happy modeling!

Cheers,
-B.

Benjamin C. Haller
Messer Lab
Cornell University


Yazzi McDonough wrote on 7/4/24 11:10 AM:

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SLiM forward genetic simulation: http://messerlab.org/slim/
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