The Effects of Migration and Assortative Mating on Admixture Linkage Disequilibrium

Zaitlen, Noah; Huntsman, Scott; Hu, Donglei; Spear, Melissa L.; Eng, Celeste; Oh, Sam S.; White, Marquitta J.; Mak, Angel C. Y.; Davis, Adam; Meade, Kelly; Brigino-Buenaventura, Emerita; LeNoir, Michael A.; Bibbins‐Domingo, Kirsten; Burchard, Esteban G.; Halperin, Eran

doi:10.1101/056168

Cited by 13 publications

(33 citation statements)

References 19 publications

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“…The variance-inflating effect of positive assortative mating on the admixture level is similar to that described by Z AITLEN et al . (2017) for the magnitude of ancestry linkage disequilibrium.…”

Section: Discussionsupporting

confidence: 87%

“…Empirical examples of the correlation in ancestry between members of mating pairs in admixed populations motivated Z AITLEN et al . (2017) to model mating preferences as a fixed correlation in admixture fraction between mates in the admixed population.…”

Section: Discussionmentioning

confidence: 99%

“…(2017) to model mating preferences as a fixed correlation in admixture fraction between mates in the admixed population. Extending a Wright-Fisher model, Z AITLEN et al . (2017) found a similar inflation of the variance of admixture under positive assortative mating and a decrease in the variance of admixture with negative assortment.…”

Section: Discussionmentioning

confidence: 99%

“…Mechanistic models describing the dynamics of admixture among two or more populations have proven informative for understanding the processes that underlie patterns of admixture in admixed populations. Such models have examined a variety of phenomena, including sex-biased admixture (G OLDBERG et al ., 2014; G OLDBERG and R OSENBERG , 2015), the interaction of admixture with migration and population size (L ONG , 1991; P OOL and N IELSEN , 2009), the consequences of spatial structure for ancestry patterns (W ANG et al ., 2011; S EDGHIFAR et al ., 2015), hybrid incompatibilities and epistasis (L INDTKE and B UERKLE , 2015; S CHUMER et al ., 2015; S CHUMER and B RANDVAIN , 2016; S EDGHIFAR et al ., 2016), and the effect of admixture on linkage disequilibrium (C HAKRABORTY and W EISS , 1988; P FAFF et al ., 2001; G RAVEL , 2012; L OH et al ., 2013; L IANG and N IELSEN , 2014; N I et al ., 2016; Z AITLEN et al ., 2017).…”

Section: Introductionmentioning

confidence: 99%

“…One phenomenon of recent interest in the study of admixed populations is assortative mating, in which admixture levels of individuals in a population system that includes an admixed population and its source populations influence the formation of mating pairs. Empirical analyses of mating pairs in admixed populations have documented nonrandom pairings with respect to admixture levels (R ISCH et al ., 2009; S EBRO et al ., 2010; Z AITLEN et al ., 2017). In particular, Z OU et al .…”

Section: Introductionmentioning

confidence: 99%

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Assortative mating by population of origin in a mechanistic model of admixture

Goldberg

Rastogi

Rosenberg

2019

Preprint

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AbstractPopulations whose mating pairs have levels of similarity in phenotypes or genotypes that differ systematically from the level expected under random mating are described as experiencing assortative mating. Excess similarity in mating pairs is termed positive assortative mating, and excess dissimilarity is negative assortative mating. In humans, empirical studies suggest that mating pairs from various admixed populations—whose ancestry derives from two or more source populations—possess correlated ancestry components that indicate the occurrence of positive assortative mating on the basis of ancestry. Generalizing a two-sex mechanistic admixture model, we devise a model of one form of ancestry-assortative mating that occurs through preferential mating based on source population. Under the model, we study the moments of the admixture fraction distribution for different assumptions about mating preferences, including both positive and negative assortative mating by population. We consider the special cases of assortative mating by population that involve a single admixture event and that consider a model of constant contributions to the admixed population over time. We demonstrate that whereas the mean admixture under assortative mating is equivalent to that of a corresponding randomly mating population, the variance of admixture depends on the level and direction of assortative mating. In contrast to standard settings in which positive assortment increases variation within a population, certain assortative mating scenarios allow the variance of admixture to decrease relative to a corresponding randomly mating population: with the three populations we consider, the variance-increasing effect of positive assortative mating within a population might be overwhelmed by a variance-decreasing effect emerging from mating preferences involving other pairs of populations. The effect of assortative mating is smaller on the X chromosome than the autosomes because inheritance of the X in males depends only on the mother’s ancestry, not on the mating pair. Because the variance of admixture is informative about the timing of admixture and possibly about sex-biased admixture contributions, the effects of assortative mating are important to consider in inferring features of population history from distributions of admixture values. Our model provides a framework to quantitatively study assortative mating under flexible scenarios of admixture over time.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Assortative mating by population of origin in a mechanistic model of admixture

Goldberg

Rastogi

Rosenberg

2019

Preprint

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Glioma risk associated with extent of estimated European genetic ancestry in African Americans and Hispanics

Ostrom

Egan

Nabors

et al. 2019

Intl Journal of Cancer

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Glioma incidence is highest in non‐Hispanic Whites, and to date, glioma genome‐wide association studies (GWAS) to date have only included European ancestry (EA) populations. African Americans and Hispanics in the US have varying proportions of EA, African (AA) and Native American ancestries (NAA). It is unknown if identified GWAS loci or increased EA is associated with increased glioma risk. We assessed whether EA was associated with glioma in African Americans and Hispanics. Data were obtained for 832 cases and 675 controls from the Glioma International Case–Control Study and GliomaSE Case–Control Study previously estimated to have <80% EA, or self‐identify as non‐White. We estimated global and local ancestry using fastStructure and RFMix, respectively, using 1,000 genomes project reference populations. Within groups with ≥40% AA (AFR≥0.4), and ≥15% NAA (AMR≥0.15), genome‐wide association between local EA and glioma was evaluated using logistic regression conditioned on global EA for all gliomas. We identified two regions (7q21.11, p = 6.36 × 10−4; 11p11.12, p = 7.0 × 10−4) associated with increased EA, and one associated with decreased EA (20p12.13, p = 0.0026) in AFR≥0.4. In addition, we identified a peak at rs1620291 (p = 4.36 × 10−6) in 7q21.3. Among AMR≥0.15, we found an association between increased EA in one region (12q24.21, p = 8.38 × 10−4), and decreased EA in two regions (8q24.21, p = 0. 0010; 20q13.33, p = 6.36 × 10−4). No other significant associations were identified. This analysis identified an association between glioma and two regions previously identified in EA populations (8q24.21, 20q13.33) and four novel regions (7q21.11, 11p11.12, 12q24.21 and 20p12.13). The identifications of novel association with EA suggest regions to target for future genetic association studies.

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Genome-wide Significance Thresholds for Admixture Mapping Studies

Grinde

Brown

Reiner

et al. 2019

The American Journal of Human Genetics

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Admixture mapping studies have become more common in recent years, due in part to technological advances and growing international efforts to increase the diversity of genetic studies. However, many open questions remain about appropriate implementation of admixture mapping studies, including how best to control for multiple testing, particularly in the presence of population structure. In this study, we develop a theoretical framework to characterize the correlation of local ancestry and admixture mapping test statistics in admixed populations with contributions from any number of ancestral populations and arbitrary population structure. Based on this framework, we develop an analytical approach for obtaining genome-wide significance thresholds for admixture mapping studies. We validate our approach via analysis of simulated traits with real genotype data for 8,064 unrelated African American and 3,425 Hispanic/ Latina women from the Women's Health Initiative SNP Health Association Resource (WHI SHARe). In an application to these WHI SHARe data, our approach yields genome-wide significant p value thresholds of 2.1 3 10 À5 and 4.5 3 10 À6 for admixture mapping studies in the African American and Hispanic/Latina cohorts, respectively. Compared to other commonly used multiple testing correction procedures, our method is fast, easy to implement (using our publicly available R package), and controls the family-wise error rate even in structured populations. Importantly, we note that the appropriate admixture mapping significance threshold depends on the number of ancestral populations, generations since admixture, and population structure of the sample; as a result, significance thresholds are not, in general, transferable across studies.

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The Effects of Migration and Assortative Mating on Admixture Linkage Disequilibrium

Cited by 13 publications

References 19 publications

Assortative mating by population of origin in a mechanistic model of admixture

Assortative mating by population of origin in a mechanistic model of admixture

Glioma risk associated with extent of estimated European genetic ancestry in African Americans and Hispanics

Genome-wide Significance Thresholds for Admixture Mapping Studies

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