Uncommon Ground


Genetic structure and clonal diversity in Leymus chinensis

There’s a small chance you’ll remember that about six months ago I posted about a pre-print on which I am co-author. I’m pleased to report that the paper was published in the December issue of the American Journal of Botany. If you follow me on Twitter, you may have seen me retweet a couple of times about this already, but I thought I’d make a post here. It’s been a long time since I posted anything, and I hope to get back into the habit of writing something every week or two. Here’s the abstract and link in case you’re interested.



The distribution of genetic diversity on the landscape has critical ecological and evolutionary implications. This may be especially the case on a local scale for foundation plant species because they create and define ecological communities, contributing disproportionately to ecosystem function.


We examined the distribution of genetic diversity and clones, which we defined first as unique multilocus genotypes (MLG), and then by grouping similar MLGs into multilocus lineages. We used 186 markers from inter-simple sequence repeats (ISSR) across 358 ramets from 13 patches of the foundation grass Leymus chinensis. We examined the relationship between genetic and clonal diversities, their variation with patch size, and the effect of the number of markers used to evaluate genetic diversity and structure in this species.


Every ramet had a unique MLG. Almost all patches consisted of individuals belonging to a single multilocus lineages. We confirmed this with a clustering algorithm to group related genotypes. The predominance of a single lineage within each patch could be the result of the accumulation of somatic mutations, limited dispersal, some sexual reproduction with partners mainly restricted to the same patch, or a combination of all three.


We found strong genetic structure among patches of L. chinensis. Consistent with previous work on the species, the clustering of similar genotypes within patches suggests that clonal reproduction combined with somatic mutation, limited dispersal, and some degree of sexual reproduction among neighbors causes individuals within a patch to be more closely related than among patches.

doi: https://doi.org/10.1002/ajb2.1771

Sharing a new version of my genetic drift simulation

You may be aware that I wrote a series of applications in RShiny several years ago to illustrate some principles of population genetics. I just finished revising the genetic drift application. If you’ve used it in the past, you’ll know that it would get hung up when you tried to simulate a long time series or a lot of populations. After some digging around, I realized that the problem isn’t with running the simulation or with collecting the results. It’s with converting the results to a form that allows the simulation to unfold over time.

As a result, this version allows you to turn the animation off. Now you can run long time series with lots of populations (where “lots” equals “up to 10”). You won’t see the results played as a movie, but you’ll see them displayed very quickly. As you’ll see from the first link above, all of the source code is available on Github. If you find any of these applications useful, you’ll want to take a look at the Google Doc that Katie Lotterhos put together and announced on Twitter last January. It includes screenshots and links to applications written by CJ Battey, Graham Coop, and Chris Muir.