Genetic traces of ancient demography

Abstract

Patterns of gene differences among humans contain information about the demographic history of our species. Haploid loci like mitochondrial DNA and the nonrecombining part of the Y chromosome show a pattern indicating expansion from a population of only several thousand during the late middle or early upper Pleistocene. Nuclear short tandem repeat loci also show evidence of this expansion. Both mitochondrial DNA and the Y chromosome coalesce within the last several hundred thousand years, and they cannot provide information about the population before their coalescence. Several nuclear loci are informative about our ancestral population size during nearly the whole Pleistocene. They indicate a small effective size, on the order of 10,000 breeding individuals, throughout this time period. This genetic evidence denies any version of the multiregional model of modern human origins. It implies instead that our ancestors were effectively a separate species for most of the Pleistocene.

Figure 1

Schematic history of a nuclear locus in humans and chimps.

Figure 2

Simulated gene trees from a pair of populations of constant size that exchange an average of one-half a gene every generation. These are four simulated loci from the same populations with the vertical axes drawn to the same time scale.

Figure 3

Simulated gene trees from a pair of populations that expanded by a factor of 1,000. The populations exchange an average of one-half a gene every generation.

Figure 4

Simulated gene trees from a pair of populations that have contracted by a factor of 100. The populations exchange an average of one-half a gene every generation. Because the vertical axes are drawn to the same scale, the trees in the left two panels are so shallow that they are invisible.

Figure 5

Gene tree (Top), frequency spectrum (Middle) and mismatch distribution (Bottom) from a population that has undergone a population expansion. The circles on tree represent mutations. The simulation parameters match approximately those estimated from human mtDNA.

Figure 6

Gene tree (Top), frequency spectrum (Middle) and mismatch distribution (Bottom) from a population that has always been constant in size.

Figure 7

Frequency spectrum and mismatch distribution from a world sample of 636 mtDNA sequences at 411 positions of the first hypervariable segment (HVS-I). Compare this with Fig. 5. The diamonds show the expected number of segregating sites in each frequency interval expected in a constant size population.

Figure 8

Frequency spectrum and mismatch distribution from a world sample of 718 Y chromosome sequences. There are 20 segregating sites ascertained at approximately 20,000 positions. Ascertainment was done in two samples, one with 21 chromosomes and one with 53. If a site has population frequency x, then the probability that it will be detected in a sample of size n, the ascertainment function, is 1 − (xⁿ + (1 − x)ⁿ). Diamonds show the expected number of sites in each frequency class under the hypothesis of constant population size, computed by multiplying the ascertainment function by the distribution in Eq. 1. The excess of low frequency sites is consistent with a Pleistocene population expansion. Because the whole nonrecombining portion of the Y chromosome is a single locus, these sites are not independent, and there is no simple statistical test of the constant size hypothesis.

Figure 9

Frequency spectrum of 23 Alu insertions in humans. The diamonds show the expected numbers of loci under constant population size as specified by the long-neck model. Circles show expected numbers of loci under the hourglass model of a population contraction. The hourglass hypothesis can be rejected by a statistical test, whereas the long-neck model cannot. Each of these was ascertained in a diploid. The probability of detecting at least one copy of an insertion in a diploid whose population frequency is x is x² + 2x(1 − x), the ascertainment function for this system. Expected values for the long-neck model were computed by multiplying the distribution in Eq. 2 by this function. Expected values for the hourglass model were computed by multiplying the ascertainment function by the uniform distribution because the distribution of the number of copies of a mutation in the top interval of the tree is uniform.