One of the interesting things about genetics, and population genetics even more specifically, is how the theory and analysis outran the biophysical mechanism of the phenomenon. By this, I mean that the Mendelian laws inferred from transmission of physical characteristics predate any understanding about how genes were embedded within chromosomes, let alone the structural nature of DNA.
Population genetics, which fused the quantitative evolutionary thinking of the biometrical school with Mendelism, arguably outran the data by decades. Until the molecular evolution revolution of the 1960s controversies such as the role of selection and drift in shaping variation were rhetoric rich and data poor. Though the allozyme era was clarifying, I do think people who were shaped by that era get a bit fixated on being a particular camp. In contrast, with the genomics revolution many researchers seem to be more willing to let the data speak, because the data is so copious. A model that is relevant in one part of the tree of life may not be as predictive in another portion of it.
The rise of data makes old questions live again. With that, I present a paper in PNAS where the first author is Jonathan Wakely, a pioneer of coalescent theory, Effects of the population pedigree on genetic signatures of historical demographic events:
Genetic variation among loci in the genomes of diploid biparental organisms is the result of mutation and genetic transmission through the genealogy, or population pedigree, of the species. We explore the consequences of this for patterns of variation at unlinked loci for two kinds of demographic events: the occurrence of a very large family or a strong selective sweep that occurred in the recent past. The results indicate that only rather extreme versions of such events can be expected to structure population pedigrees in such a way that unlinked loci will show deviations from the standard predictions of population genetics, which average over population pedigrees. The results also suggest that large samples of individuals and loci increase the chance of picking up signatures of these events, and that very large families may have a unique signature in terms of sample distributions of mutant alleles.
The paper is open access, so read the whole thing. The major math is tucked away in the extended material. Many of the formalisms in the text are those you’d regularly encounter in population genetics. The issue they’re addressing here is the fact that real populations exhibit pedigree structure, and even unlinked loci, which we treat as independent evolutionary histories, share a pedigree history.
If you read the text though it is notable how robust standard population genetic inferences are to the fact that in a literal sense they’re based on false assumptions. Massive demographic expansion (e.g., Genghis Khan haplotype) and unrealistic selection coefficients don’t seem to disturb the lineages enough so that the assumption of independent assortment starts to become misleading.
This shouldn’t be entirely surprising. I would argue that genomics has not really revolutionized evolution or population biology. The big frameworks are vindicated because nature is one, and the glimmers of reality you see in sparse data nevertheless sample from a comprehensible underlying distribution. As we get more data we’re getting more clarity, but the overall picture is not shocking or surprising.
Citation: John Wakeley, Léandra King, and Peter R. Wilton, Effects of the population pedigree on genetic signatures of historical demographic events