Fast multiple-trait genome-wide association analysis for correlated longitudinal measurements.

Large-scale longitudinal biobank data can be leveraged to identify genetic variation contributing to human diseases progression and traits trajectories. While methods for genome-wide association studies (GWAS) of multiple correlated traits have been proposed, an efficient multiple-trait approach to model longitudinal phenotypes is not currently available. We developed GAMUT, a genome-wide association approach for multiple longitudinal traits. GAMUT employs a mixed-effects model to fit longitudinal outcomes where a fast algorithm for inversion by recursive partitioning of the random effects submatrix is introduced. To evaluate performance of the algorithms introduced and assess their statistical power and type I error, stochastic simulation was conducted. Consistent with our expectation, power was greater for cross-sectional (CS) than longitudinal (LT) effects, particularly with a diminishing LT/CS ratio. With a minimum minor allele count of 3 within genotype by time categories, observed type I error was roughly equal to theoretical genome-wide significance. Additionally, 28 blood-based biomarkers measured at 2 time points on participants of the UK Biobank were used to compare GAMUT against single-trait standard and longitudinal GWAS (including rate of change). Across all biomarkers, we observed 539 (CS) and 248 (LT) significant independent variants for the GAMUT method, and 513 (CS) and 30 (LT) for single-trait longitudinal GWAS, respectively. Only 37 variants were identified by modeling rates of change using standard GWAS.

Effects of including a quantitative trait locus in selection under different waiting plans of young bulls.

The advantage of using the genotype of a quantitative trait locus (QTL) in selection schemes of dairy cattle was quantified using stochastic simulation. Three selection plans were studied. In the first plan, young bulls waited for 3 yr until their sisters completed a lactation and then were evaluated and selected based on an animal model. In a second plan, young bulls waited for 5 yr until their daughters completed a lactation. An intermediate 4-yr waiting plan was also studied. Simulation was for 16 yr with overlapping generations. Population and model parameters were proportional to the U.S. Holstein population. The advantage of using a QTL was quantified as the percentage of superiority of QTL-assisted over QTL-free selection using cumulative genetic response. Percentage of superiority was reported for four selection pathways: active sires, young bulls, bull dams, and first lactation cows. A general trend was observed: low superiority in early years of selection that increased to a plateau in later years and then decreased. The superiority of the QTL information was greatest in the 3-yr waiting plan and least in the 4-yr waiting plan. Superiority at plateau for selection pathways ranged from 16 to 26% for the 3-yr waiting plan, from 3 to 12% for the 4-yr waiting plan, and from 5 to 13% for the 5-yr waiting plan. The contribution to selection response attributed to the QTL and the polygenes was quantified. The rate at which the favorable allele approached fixation and the accuracy of predicting breeding values on the percentage of superiority were studied.