Natural selection and recombination

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Razib has a nice discussion of an interesting observation just published in PLoS Genetics– that there is a negative correlation between recombination rate in the human genome and population differentiation. This observation, along with the complementary observations of correlations between nucleotide diversity and recombination and between nucleotide diversity and density of functional elements, form part of a growing body of literature establishing that the signatures of natural selection–positive and negative–have influenced overall patterns of genetic diversity in humans.

It’s important to emphasize again that these observations are influenced by both positive selection (the removal of genetic diversity at sites linked to advantageous alleles) and background selection (the removal of genetic diversity at sites linked to deleterious alleles). One important question is the relative role of these two forces in generating these overall patterns (the implications for human evolution of extensive positive selection are somewhat different than the implications of extensive negative selection); there are a couple ways forward on addressing this discussed by the authors here.

The authors here also raise the intriguing possibility of leveraging populations which have diverged at different times to examine differences in the efficiency of natural selection over time; they don’t quite have the data to do this yet, but they certainly will in the next couple years. They do make the observation, using admittedly suboptimally ascertained data, that there does appear to be the same qualitative relationship–perhaps even stronger– between recombination rate and differentiation even between very closely related populations like the Chinese and the Japanese; though only suggestive, this raises the possibility that the signatures of selection (again, both positive and negative) are detectable even on a quite short timeframe. Overall, this is an exciting direction for the use of resequencing datasets that will be coming out soon.

Finally, since John Hawks doesn’t have comments, I’ll make a comment on his post on this paper. In particular, based on the observation above (about the relationship between differentiation between closely-related populations and recombination), he writes:

There are a lot more genes that are geographically circumscribed and low in frequency affecting FST at a more localized level, and fewer affecting major allele frequencies between continental regions.

Though this may be true, the correlation between FST and differentiation between closely-related populations observed here is almost certainly not due to any effect of this sort. The data used in the Chinese-Japanese comparison (for example) is from the Affymetrix and Illumina genotyping chips (ie. HapMap 3), which contain mostly common variation and no (or very few) low-frequency SNPs specific to the Japanese (or Chinese). This effect is likely due to small differences in allele frequency between the Chinese and the Japanese at relatively *common, non-geographically circumscribed* SNPs. That is, imagine two SNPs, one at 55% frequency in Japan and 50% frequency in the rest of the world, and one at 50% frequency everywhere. Their observation (I think) is that SNPs of the former type are more common in low recombination rate areas of the genome, not that they find a bunch of new alleles that have arisen in the last few thousand years since those populations split. One could double-check this, but based on the chips they used, I’m pretty confident this is the case.

8 Comments

  1. If one allele is considered to be “advantageous”, all alternate alleles are thus “deleterious” since their opportunity cost is the advantageous allele. Similarly, if an allele is considered “deleterious”, other alternatives to it must be “advantageous” in comparison. So every kind of positive selection entails negative selection and vice versa. A distinction we might make is the a new mutation may be better or (more likely) worse than the “wild” type, in the former case we expect “positive” selection and in the latter “negative”.

  2. Of course they’re not finding new selected alleles; they’re seeing the effect of linkage with selected alleles which probably have not been identified.

    It may help you to try running some numbers. Your example — 55% in Japan, 50% in China — leads to an Fst of 0.002, which is of course quite a bit less than the mean Fst we see between Japan and China. To get a substantial increase over the mean Fst (which is around 0.02-0.04 within continents), you would need allele frequencies that differ like more than 0.5 and 0.7 or so.

    Keeping those numbers in mind, you can see that it actually takes a fairly substantial shift in frequencies in a low-recombination block to make two nearby populations look more divergent for that particular genomic region compared to the mean.

    The most plausible way to get that kind of shift in low-frequency regions is hitchhiking.

    It’s a little unfortunate that they don’t report the genic/nongenic comparison for the HapMap comparisons, but that will be easy enough to check.

  3. >Of course they’re not finding new selected alleles; they’re seeing the effect of linkage with selected alleles which probably have not been identified.

    Right. So we agree, it has nothing to do with low frequency, geographically restricted alleles :)

    mean Fst between china and japan in the hapmap is ~0.005, fwiw.

  4. >A distinction we might make is the a new mutation may be better or (more likely) worse than the “wild” type, in the former case we expect “positive” selection and in the latter “negative”.

    Yep, that’s what I mean.

  5. >mean Fst between china and japan in the hapmap is ~0.005, fwiw.

    So in light of that, let me give a different example (I admit I sort of randomly pulled those initial numbers out of the air without much thought):

    Allele 1: 60% in Japan, 50% in China
    Allele 2: 55% in Japan, 50% in China

    The observation (again, I think) in this paper is that the former are more common in regions of low recombination compared to the latter.

  6. The observation (again, I think) in this paper is that the former are more common in regions of low recombination compared to the latter.

    Which is exactly what you’d expect if there were a lot of new selected alleles at frequencies less than 20 percent that had pulled common variants along with them, over a longer region in areas of lower recombination.

    This is key to the literature on “draft”. The usual observation is that variation is correlated with recombination rate, because of the effect of hitchhiking on common linked neutral alleles.

  7. ok, i see the argument. yes, that’s plausible. It’s also consistent with background selection on new deleterious alleles, and positive selection on standing variation. probably a weighted average of all these effects, and the weights are unclear.

  8. probably a weighted average of all these effects, and the weights are unclear.

    I agree, although background selection in particular is very weak given human recombination rates and gene density, so that would take a lot more selection (across deleterious variants), while hitchhiking would take relatively few instances of positive selection.

    Selection on standing variants may be a factor, although (a) they are rare relative to to new mutations, because the human population formerly was very small, and (b) if they’re old enough, they shouldn’t be tightly linked to particular allelic variants, even where recombination is low.

    I’ll do updated numbers on both these factors and post them, because it’s important to get those weights.

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