» Articles » PMID: 24253859

Distribution of Ancestral Chromosomal Segments in Admixed Genomes and Its Implications for Inferring Population History and Admixture Mapping

Overview
Journal Eur J Hum Genet
Specialty Genetics
Date 2013 Nov 21
PMID 24253859
Citations 16
Authors
Affiliations
Soon will be listed here.
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.

Citing Articles

Reconstructing complex admixture history using a hierarchical model.

Zhang S, Zhang R, Yuan K, Yang L, Liu C, Liu Y Brief Bioinform. 2024; 25(2).

PMID: 38261339 PMC: 10805183. DOI: 10.1093/bib/bbad540.


Genome-wide admixture and association analysis identifies African ancestry-specific risk loci of eosinophilic esophagitis in African Americans.

Gautam Y, Caldwell J, Kottyan L, Chehade M, Dellon E, Rothenberg M J Allergy Clin Immunol. 2022; 151(5):1337-1350.

PMID: 36400179 PMC: 10164699. DOI: 10.1016/j.jaci.2022.09.040.


Hybridization underlies localized trait evolution in cavefish.

Moran R, Jaggard J, Roback E, Kenzior A, Rohner N, Kowalko J iScience. 2022; 25(2):103778.

PMID: 35146393 PMC: 8819016. DOI: 10.1016/j.isci.2022.103778.


Genetic Ancestry Inference and Its Application for the Genetic Mapping of Human Diseases.

Suarez-Pajes E, Diaz-de Usera A, Marcelino-Rodriguez I, Guillen-Guio B, Flores C Int J Mol Sci. 2021; 22(13).

PMID: 34203440 PMC: 8269095. DOI: 10.3390/ijms22136962.


AdmixSim: A Forward-Time Simulator for Various Complex Scenarios of Population Admixture.

Yang X, Yuan K, Ni X, Zhou Y, Guo W, Xu S Front Genet. 2020; 11:601439.

PMID: 33343638 PMC: 7744625. DOI: 10.3389/fgene.2020.601439.


References
1.
Tian C, Hinds D, Shigeta R, Adler S, Lee A, Pahl M . A genomewide single-nucleotide-polymorphism panel for Mexican American admixture mapping. Am J Hum Genet. 2007; 80(6):1014-23. PMC: 1867091. DOI: 10.1086/513522. View

2.
Ewens W, Spielman R . The transmission/disequilibrium test: history, subdivision, and admixture. Am J Hum Genet. 1995; 57(2):455-64. PMC: 1801556. View

3.
Tian C, Hinds D, Shigeta R, Kittles R, Ballinger D, Seldin M . A genomewide single-nucleotide-polymorphism panel with high ancestry information for African American admixture mapping. Am J Hum Genet. 2006; 79(4):640-9. PMC: 1592561. DOI: 10.1086/507954. View

4.
Zhu X, Luke A, Cooper R, Quertermous T, Hanis C, Mosley T . Admixture mapping for hypertension loci with genome-scan markers. Nat Genet. 2005; 37(2):177-81. DOI: 10.1038/ng1510. View

5.
Kidd J, Gravel S, Byrnes J, Moreno-Estrada A, Musharoff S, Bryc K . Population genetic inference from personal genome data: impact of ancestry and admixture on human genomic variation. Am J Hum Genet. 2012; 91(4):660-71. PMC: 3484644. DOI: 10.1016/j.ajhg.2012.08.025. View