Comparison of Single Genome and Allele Frequency Data Reveals Discordant Demographic Histories

Inference of demographic history from genetic data is a primary goal of population genetics of KEYWORDS model and nonmodel organisms. Whole genome-based approaches such as the pairwise/multiple pairwise sequentially Markovian coalescent methods use genomic data from one to four individuals to infer the sequentially demographic history of an entire population, while site frequency spectrum (SFS)-based methods use the Markovian distribution of allele frequencies in a sample to reconstruct the same historical events. Although both coalescent methods are extensively used in empirical studies and perform well on data simulated under simple models, site frequency there have been only limited comparisons of them in more complex and realistic settings. Here we use spectrum published demographic models based on data from three human populations (Yoruba, descendants of population northwest-Europeans, and Han Chinese) as an empirical test case to study the behavior of both inference genetics procedures. We find that several of the demographic histories inferred by the whole genome-based demographic methods do not predict the genome-wide distribution of heterozygosity, nor do they predict the empirical inference SFS. However, using simulated data, we also find that the whole genome methods can reconstruct the nonmodel complex demographic models inferred by SFS-based methods, suggesting that the discordant patterns of organisms genetic variation are not attributable to a lack of statistical power, but may reflect unmodeled complexities in the underlying demography. More generally, our findings indicate that demographic inference from a small number of genomes, routine in genomic studies of nonmodel organisms, should be interpreted cautiously, as these models cannot recapitulate other summaries of the data.