A unified linear mixed model for familial relatedness and population structure in genetic association studies.

Familial relatedness (FR) and population structure (PS) are two major sources for genetic correlation. In the human population, both FR and PS can further break down into additive and dominant components to account for potential additive and dominant genetic effects. In this study, besides the classical additive genomic relationship matrix, a dominant genomic relationship matrix is introduced. A link between the additive/dominant genomic relationship matrices and the coancestry (or kinship)/double coancestry coefficients is also established. In addition, a way to separate the FR and PS correlations based on the estimates of coancestry and double coancestry coefficients from the genomic relationship matrices is proposed. A unified linear mixed model is also developed, which can account for both the additive and dominance effects of FR and PS correlations as well as their possible random interactions. Finally, this unified linear mixed model is applied to analyze two study cohorts from UK Biobank.

INVESTIGATING ASSOCIATIONS AMONG RELATEDNESS, GENETIC DIVERSITY, AND CAUSES OF MORTALITY IN SOUTHERN SEA OTTERS (ENHYDRA LUTRIS NEREIS).

Southern sea otter (Enhydra lutris nereis) population recovery is influenced by a variety of factors, including predation, biotoxin exposure, infectious disease, oil spills, habitat degradation, and resource limitation. This population has also experienced a significant genetic bottleneck, resulting in low genetic diversity. We investigated how two metrics, familial relatedness and genetic diversity, are correlated with common causes of mortality in southern sea otters, including cardiomyopathy, acanthocephalan (Profilicollis spp.) peritonitis, systemic protozoal infection (Toxoplasma gondii and Sarcocystis neurona), domoic acid intoxication, end-lactation syndrome, and shark bite. Microsatellite genetic markers were used to examine this association in 356 southern sea otters necropsied from 1998 to 2012. Significant associations with genetic diversity or familial relatedness (P<0.05) were observed for cardiomyopathy, acanthocephalan peritonitis, and sarcocystosis, and these associations varied by sex. Adult male cardiomyopathy cases (n=86) were more related than the null expectation (P<0.049). Conversely, female acanthocephalan peritonitis controls (n=110) were more related than the null expectation (P<0.004). Including genetic diversity as a predictor for fatal acanthocephalan peritonitis in the multivariate logistic model significantly improved model fit; lower genetic diversity was associated with reduced odds of sea otter death due to acanthocephalan peritonitis. Finally, male sarcocystosis controls (n=158) were more related than the null expectation (P<0.011). Including genetic diversity in the multivariate logistic model for fatal S. neurona infection improved model fit; lower genetic diversity was associated with increased odds of sea otter death due to S. neurona. Our study suggests that genetic diversity and familial relatedness, in conjunction with other factors such as age and sex, may influence outcome (survival or death) in relation to several common southern sea otter diseases. Our findings can inform policy for conservation management, such as potential reintroduction efforts, as part of species recovery.