Very important paper in PLOS BIOLOGY just out, Natural Selection Constrains Neutral Diversity across A Wide Range of Species. Important enough that the journal commissioned this article: Lewontin’s Paradox Resolved? In Larger Populations, Stronger Selection Erases More Diversity. The paradox is pretty straightforward. Assuming the neutral theory of molecular evolution you’d expect that you’d have more genetic diversity in species with larger population sizes, because the larger the population size the longer it would take for mutations to transition from novelty to fixation. More formally the time until fixation of a neutral polymorphism is ~4Ne, with Ne being the effective population size. In small populations mutations will emerge and fix rather quickly due to the generation to generation volatility of drift being so powerful, and therefore keeping down the total diversity. In large populations mutations will take a long time to traverse the frequency range from 0 to 100% because of the weakness of inter-generational random drift. The paradox was a big deal because for the past 30 years or so the neutral (or nearly neutral) has been the implicit null model, and I’d argue broadly supported as such, albeit with strong dissents.
The “controversies” that occurred from the 1970s onward about the role of selection and and its enemies are somewhat notorious. Some of the figures are well known to the public. Richard Dawkins and Stephen Jay Gould both had cameos because of their differing views about the pervasiveness of adaptation in evolutionary process more generally. But the geneticists at the heart of the major disagreements are more obscure to the general public, though in the early 1990s the Sacramento Bee reported on the beef between John Gillespie and Motoo Kimura (Gillespie was based out of UC Davis, near Sacramento). From what I can tell, and who I know, it strikes me that genomics has now somewhat mitigated the role of rhetoric in the debate, and at the same time fostered an abating of the extremism of some of the anti-selectionists. Leibniz’s stance of “let us calculate” has now become more important than a turn of the phrase or evocative metaphor. With data there is less of a role for posturing. Additionally, the fact is that many researchers did not follow mathematical theoretical proofs very closely or with genuine comprehension, so empirical results are really what is changing the terms of the debate. The Drosophila world has long been a redoubt for selectionism, but now you see papers such as Genome-wide signals of positive selection in human evolution, which argue for the importance of that population genetic parameter even for small effective population size organisms such as humans.
What the authors did in the above paper was leverage the fact that with genome-wide data they could test the theoretical propositions empirically. In particular, they looked at regions with reduced recombination,* and therefore should be subject more strongly to selection (whether selective sweeps, which allow for the hitchhiking of regions around the target of selection and generate long haplotypes, or background selection, which constrains genomic variation due to negative pressures against mutation). As the figure above shows there is a correlation between the power of selection on the genome and inferred effective population size. I say inferred because they had to use species range and size as proxies. Obviously this isn’t perfect, but I suspect that the utilization of these proxy variables only diminishes the correlation. The authors admit that there is a lot of work to be done, but this is just the first step. Perhaps the results will change somewhat with a different selection of organisms (N = 40), but I’m moderately skeptical. Probably the most important line in the paper is “it seems clear that, in most cases, BGS [background selection] is a more appropriate null model for tests of natural selection than strict neutrality.”
* Recombination shuffles the association of variants across the genome, and so separates their destiny, whether good (positive selection) or bad (negative selection).