Genetic association between sow longevity and social genetic effects on growth in pigs

Joon Ki Hong; Yong Min Kim; Kyu Ho Cho; Eun Seok Cho; Deuk Hwan Lee; Tae Jeong Choi

doi:10.5713/ajas.18.0789

Genetic association between sow longevity and social genetic effects on growth in pigs

Asian-Australasian Journal of Animal Sciences ◽

10.5713/ajas.18.0789 ◽

2019 ◽

Vol 32 (8) ◽

pp. 1077-1083 ◽

Cited By ~ 1

Author(s):

Joon Ki Hong ◽

Yong Min Kim ◽

Kyu Ho Cho ◽

Eun Seok Cho ◽

Deuk Hwan Lee ◽

...

Keyword(s):

Genetic Association ◽

Genetic Effects ◽

Sow Longevity

Download Full-text

Estimates of genetic parameters for growth and skeletal measurements in Thai swamp buffalo

Animal Science ◽

10.1017/s1357729800051742 ◽

2000 ◽

Vol 70 (3) ◽

pp. 399-406

Author(s):

K. Meyer ◽

H. -U. Graser ◽

A. Na-Chiangmai

Keyword(s):

Total Variation ◽

Genetic Association ◽

Maternal Effects ◽

Genetic Parameters ◽

Genetic Effects ◽

Environmental Correlations ◽

Length Measurements ◽

Swamp Buffalo ◽

Heritability Estimates ◽

Additive Genetic Effects

AbstractEstimates of genetic parameters were obtained for weight, hip height, heart girth and shoulder to pin length measurements on Thai swamp buffalo, recorded at birth and weaning. Direct heritability estimates were 0·26 for weights at both ages and were low for skeletal measurements, ranging from 0·11 to 0·19. Low values could, in part at least, be caused by inaccuracies in recording. All traits were subject to maternal effects, permanent environmental maternal effects on traits recorded at weaning explaining proportionately up to 0·14 of the total variation. Estimates of genetic (direct and maternal) and permanent environmental correlations between traits recorded at the same time were high throughout, ranging from 0·83 to 0·97 for additive genetic effects and being close to unity otherwise. Except for heart girth measured at weaning, there appeared to be comparatively little genetic association between traits recorded at different times, direct additive correlation estimates ranging from 0·18 to 0·55 in contrast to estimates of 0·38 to 0·65 for correlations with heart girth at weaning.

Download Full-text

Genetic association between leg conformation in young pigs and sow longevity

Journal of Animal Breeding and Genetics ◽

10.1111/jbg.12193 ◽

2015 ◽

Vol 133 (4) ◽

pp. 283-290 ◽

Cited By ~ 11

Author(s):

T.H. Le ◽

P. Madsen ◽

N. Lundeheim ◽

K. Nilsson ◽

E. Norberg

Keyword(s):

Genetic Association ◽

Young Pigs ◽

Sow Longevity

Download Full-text

Power and Sample Size Calculations for Genetic Association Studies in the Presence of Genetic Model Misspecification

Human Heredity ◽

10.1159/000508558 ◽

2019 ◽

Vol 84 (6) ◽

pp. 256-271 ◽

Cited By ~ 1

Author(s):

Camille M. Moore ◽

Sean A. Jacobson ◽

Tasha E. Fingerlin

Keyword(s):

Sample Size ◽

Genetic Association ◽

Genetic Model ◽

Association Studies ◽

Model Misspecification ◽

Genetic Association Studies ◽

Genetic Effects ◽

Degree Of Freedom ◽

Environment Interaction ◽

Sample Size Calculations

Introduction: When analyzing data from large-scale genetic association studies, such as targeted or genome-wide resequencing studies, it is common to assume a single genetic model, such as dominant or additive, for all tests of association between a given genetic variant and the phenotype. However, for many variants, the chosen model will result in poor model fit and may lack statistical power due to model misspecification. Objective: We develop power and sample size calculations for tests of gene and gene × environment interaction, allowing for misspecification of the true mode of genetic susceptibility. Methods: The power calculations are based on a likelihood ratio test framework and are implemented in an open-source R package (“genpwr”). Results: We use these methods to develop an analysis plan for a resequencing study in idiopathic pulmonary fibrosis and show that using a 2-degree of freedom test can increase power to detect recessive genetic effects while maintaining power to detect dominant and additive effects. Conclusions: Understanding the impact of model misspecification can aid in study design and developing analysis plans that maximize power to detect a range of true underlying genetic effects. In particular, these calculations help identify when a multiple degree of freedom test or other robust test of association may be advantageous.

Download Full-text