Genetics and genomics of uniformity and resilience in livestock and aquaculture species: A review

Abstract

Genetic control of residual variance offers opportunities to increase uniformity and resilience of livestock and aquaculture species. Improving uniformity and resilience of animals will improve health and welfare of animals and lead to more homogenous products. Our aims in this review were to summarize the current models and methods to study genetic control of residual variance, genetic parameters and genomic results for residual variance and discuss future research directions. Typically, the genetic coefficient of variation is high (median = 0.27; range 0-0.86) and the heritability of residual variance is low (median = 0.01; range 0-0.10). Higher heritabilities can be achieved when increasing the number of records per animal. Divergent selection experiments have supported the feasibility of selecting for high or low residual variance. Genomic studies have revealed associations in regions related to stress, including those from the heat shock protein family. Although the number of studies is growing, genetic control of residual variance is still poorly understood, but big data and genomics offer great opportunities. K E Y W O R D Sgenetic control of residual variance, genetic heterogeneity of residual variance, micro-environmental sensitivity, resilience, uniformity 264 | IUNG et al.

Estimation of litter size variability phenotypes in Large White sows

“…Furthermore, an alternative method was tested (analysis not shown) to define the variability phenotypes based on direct standard deviations ( SD ) of TNB rather than residuals’ variances. The estimates of variance components and heritability for phenotype based on SD in comparison with LnVar's were similar, indicating that the genetic variation in residual variance may be studied with the usage of various phenotypes as presented by Iung et al (2019). Thus, the presented approach may be useful for other breeds and species, in which different environmental effects should be included in the statistical models.…”

“…Moreover, the log transformation is perceived as the simplest way to analyse the genetic variance in residual variance when repeated observations are available per animal. In addition, the log transformation assumes the exponential model on the variance, which enables the comparison between studies focusing on the genetic component in residual variance (Bartlett & Kendall, 1946; Iung et al, 2019).…”

“…It was done by estimating the within‐individual variance of residuals obtained from each model (every animal had at least two observations of TNB to enable variance estimation) and log‐transforming obtained values, further named LnVar. The log transformation was used to normalize the distribution of variability phenotypes (LnVar's) and to assume the exponential model for the variance (Bartlett & Kendall, 1946; Iung et al, 2019). Because for every animal three estimates of residuals (from BM, BMP and RRM) were available, three phenotypes of variability were defined: LnVarBM, LnVarBMP and LnVarRRM.…”

Genetic analysis of resilience indicators based on milk yield records in different lactations and at different lactation stages

“…In practice, the index for resilience should be incorporated into the already existing total merit index containing other important traits, such as yield, longevity, fertility, and health traits (Berghof et al, 2019b;Iung et al, 2020). Due to the favorable genetic correlations between the resilience indicators and the health, longevity, and fertility traits, inclusion of the resilience indicators will assist in genetic improvement of health, longevity, and fertility and vice versa.…”

Inflammatory Correlated Response in Two Lines of Rabbit Selected Divergently for Litter Size Environmental Variability

“…In prolific species such as pigs, rabbits and mice, environmental variability in body weight and in litter size has been related to immune response and resistance to diseases (see review by Lung [13]). A divergent selection experiment for environmental variance of litter size at birth was performed in rabbits.…”