A brief note on the resemblance between relatives in the presence of population stratification

Sebro, Ronnie; Risch, Neil

doi:10.1038/hdy.2011.124

Cited by 16 publications

(18 citation statements)

References 10 publications

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“…For a locus with alleles A and a, the formula for F is given by: where N AA , N aa and N Aa are the individual counts of genotypes AA, aa and Aa, respectively [8]. …”

Section: Methodsmentioning

confidence: 99%

“…The genetic structure of a population refers to the distribution of alleles and genotypes in the population. Characterizing the genetic structure of a study population is important because ignoring it can lead to undetected biases, including false positive findings in genetic association studies [4, 5, 6] and inaccurate estimation of kinship and heritability [7, 8]. …”

Section: Introductionmentioning

confidence: 99%

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Structured mating: Patterns and implications

et al. 2017

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Genetic similarity of spouses can reflect factors influencing mate choice, such as physical/behavioral characteristics, and patterns of social endogamy. Spouse correlations for both genetic ancestry and measured traits may impact genotype distributions (Hardy Weinberg and linkage equilibrium), and therefore genetic association studies. Here we evaluate white spouse-pairs from the Framingham Heart Study (FHS) original and offspring cohorts (N = 124 and 755, respectively) to explore spousal genetic similarity and its consequences. Two principal components (PCs) of the genome-wide association (GWA) data were identified, with the first (PC1) delineating clines of Northern/Western to Southern European ancestry and the second (PC2) delineating clines of Ashkenazi Jewish ancestry. In the original (older) cohort, there was a striking positive correlation between the spouses in PC1 (r = 0.73, P = 3x10-22) and also for PC2 (r = 0.80, P = 7x10-29). In the offspring cohort, the spouse correlations were lower but still highly significant for PC1 (r = 0.38, P = 7x10-28) and for PC2 (r = 0.45, P = 2x10-39). We observed significant Hardy-Weinberg disequilibrium for single nucleotide polymorphisms (SNPs) loading heavily on PC1 and PC2 across 3 generations, and also significant linkage disequilibrium between unlinked SNPs; both decreased with time, consistent with reduced ancestral endogamy over generations and congruent with theoretical calculations. Ignoring ancestry, estimates of spouse kinship have a mean significantly greater than 0, and more so in the earlier generations. Adjusting kinship estimates for genetic ancestry through the use of PCs led to a mean spouse kinship not different from 0, demonstrating that spouse genetic similarity could be fully attributed to ancestral assortative mating. These findings also have significance for studies of heritability that are based on distantly related individuals (kinship less than 0.05), as we also demonstrate the poor correlation of kinship estimates in that range when ancestry is or is not taken into account.

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“…For a locus with alleles A and a, the formula for F is given by: where N AA , N aa and N Aa are the individual counts of genotypes AA, aa and Aa, respectively [8]. …”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Structured mating: Patterns and implications

et al. 2017

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“…‘population stratification’, [9], [10]). However, genetic clusters are not necessarily spatially clumped, since individuals belonging to the same genetic cluster may be spatially randomly distributed, and clusters may be highly intermingled.…”

Section: Introductionmentioning

confidence: 99%

Within-Population Genetic Structure in Beech (Fagus sylvatica L.) Stands Characterized by Different Disturbance Histories: Does Forest Management Simplify Population Substructure?

Piotti

Leonardi

Heuertz³

et al. 2013

PLoS ONE

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The fine-scale assessment of both spatially and non-spatially distributed genetic variation is crucial to preserve forest genetic resources through appropriate forest management. Cryptic within-population genetic structure may be more common than previously thought in forest tree populations, which has strong implications for the potential of forests to adapt to environmental change. The present study was aimed at comparing within-population genetic structure in European beech (Fagus sylvatica L.) plots experiencing different disturbance levels. Five plot pairs made up by disturbed and undisturbed plots having the same biogeographic history were sampled throughout Europe. Overall, 1298 individuals were analyzed using four highly polymorphic nuclear microsatellite markers (SSRs). Bayesian clustering within plots identified 3 to 11 genetic clusters (within-plot θ ST ranged from 0.025 to 0.124). The proportion of within-population genetic variation due to genetic substructuring (F CluPlot = 0.067) was higher than the differentiation among the 10 plots (F PlotTot = 0.045). Focusing on the comparison between managed and unmanaged plots, disturbance mostly explains differences in the complexity of within-population genetic structure, determining a reduction of the number of genetic clusters present in a standardized area. Our results show that: i) genetic substructuring needs to be investigated when studying the within-population genetic structure in forest tree populations, and ii) indices describing subtle characteristics of the within-population genetic structure are good candidates for providing early signals of the consequences of forest management, and of disturbance events in general.

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“…cross trait assortative mating) then assortment can also induce genetic correlations between traits in offspring. 52 Assortative mating can lead to population stratification if it is sub-population specific, 53 and to disproportionate inheritance of the environment in addition to genotype if dynastic effects exist. Assortative mating can therefore bias estimates of genetic correlation and Mendelian randomization.…”

Section: The Causes Of Genetic Associations: Mechanisms and Tools To mentioning

confidence: 99%

Why are education, socioeconomic position and intelligence genetically correlated?

Morris

Davies

Hemani

et al. 2019

Preprint

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Genetic associations and correlations are perceived as confirmation that genotype influences one or more phenotypes respectively. However, genetic correlations can arise from non-biological or indirect mechanisms including population stratification, dynastic effects, and assortative mating. In this paper, we outline these mechanisms and demonstrate available tools and analytic methods that can be used to assess their presence in estimates of genetic correlations and genetic associations. Using educational attainment and parental socioeconomic position data as an exemplar, we demonstrate that both heritability and genetic correlation estimates may be inflated by these indirect mechanisms. The results highlight the limitations of between-individual estimates obtained from samples of unrelated individuals and the potential value of family-based studies. Use of the highlighted tools in combination with within-sibling or mother-father-offspring trio data may offer researchers greater opportunity to explore the underlying mechanisms behind genetic associations and correlations and identify the underlying causes of estimate inflation.

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A brief note on the resemblance between relatives in the presence of population stratification

Cited by 16 publications

References 10 publications

Structured mating: Patterns and implications

Structured mating: Patterns and implications

Within-Population Genetic Structure in Beech (Fagus sylvatica L.) Stands Characterized by Different Disturbance Histories: Does Forest Management Simplify Population Substructure?

Why are education, socioeconomic position and intelligence genetically correlated?

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