Distribution of ancestral chromosomal segments in admixed genomes and its implications for inferring population history and admixture mapping

Abstract

The ancestral chromosomal segments in admixed genomes are of significant importance for both population history inference and admixture mapping, because they essentially provide the basic information for tracking genetic events. However, the distributions of the lengths of ancestral chromosomal segments (LACS) under some admixture models remain poorly understood. Here we introduced a theoretical framework on the distribution of LACS in two representative admixture models, that is, hybrid isolation (HI) model and gradual admixture (GA) model. Although the distribution of LACS in the GA model differs from that in the HI model, we demonstrated that the mean LACS in the HI model is approximately half of that in the GA model if both admixture proportion and admixture time in the two models are identical. We showed that the theoretical framework greatly facilitated the inference and understanding of population admixture history by analyzing African-American and Mexican empirical data. In addition, we found the peak of association signatures in the HI model was much narrower and sharper than that in the GA model, indicating that the identification of putative causal allele in the HI model is more efficient than that in the GA model. Thus admixture mapping with case-only data would be a reasonable and economical choice in the HI model due to the weak background noise. However, according to our previous studies, many populations are likely to be gradually admixed and have pretty high background linkage disequilibrium. Therefore, we suggest using a case-control approach rather than a case-only approach to conduct admixture mapping to retain the statistics power in recently admixed populations.

Models, methods and tools for ancestry inference and admixture analysis

“…Jin et al further explored admixture dynamics by comparing the empirical and simulated distributions of ancestral tracks under three typical two-way admixtures models, i.e., the HI model, the GA model, and the CGF model [23]. Jin et al later deduced the theoretical distributions of ancestral tracks under the HI and GA models [22]. Gravel extended these studies to multiple ancestral populations and discrete migrations, and developed a method called Tracks to infer admixture history [25].…”

“…where T is the admixture time and x is a variable representing the length of the ACT [22,25,78]. Because the length distribution of the ACT is varies for different demographic admixture models, the ACT length can be collected to find the best-fit model for the admixture history [21][22][23]25,26,78,79].…”

“…Because the length distribution of the ACT is varies for different demographic admixture models, the ACT length can be collected to find the best-fit model for the admixture history [21][22][23]25,26,78,79]. Pool and Nielsen first used the length of ancestral tracks to infer population history [26].…”

“…One of the applications of these models is to understand the admixture history of the target population [18][19][20][22][23][24][25]50,53,[73][74][75]. One of the major benefits of genotyping technology is that high quality genetic data from hundreds of populations are available for studying global patterns of population migrations and population admixture [76,77].…”

“…Recently, the availability of genome-wide high-density single nucleotide polymorphisms (SNPs) data has facilitated the study of detailed genetic structures in admixed populations [12][13][14][15][16][17]. Population history in admixed populations can be recovered by utilizing the information in genomes, such as break points of recombination [16], admixture linkage disequilibrium (ALD) [18][19][20], and the length of ancestral tracks [21][22][23][24][25][26] because admixed genomes can be explained as the mosaics of segments from different ancestries. To date, there have been many methods and corresponding computational tools developed for analyzing population admixture.…”