Genotype by environment interaction for stayability of Red Angus in the United States

Genetic analysis for sow stayability at different parities in purebred Landrace and Large White pigs

Genetic parameters for sow stayability were estimated from farrowing records of 10,295 Landrace sows and 8192 Large White sows. The record for sow stayability from parity k to parity k + 1 (k = 1, …, 6) was 0 when a sow had a farrowing record at parity k but not at parity k + 1, and 1 when a sow had both records. Heritability was estimated by using single‐trait linear and threshold animal models. Genetic correlations among parities were estimated by using two‐trait linear–linear and single‐trait random regression linear animal models. Genetic correlations with litter traits at birth were estimated by using a two‐trait linear–linear animal model. Heritability estimates by linear model analysis were low (0.065–0.119 in Landrace & 0.061–0.157 in Large White); those by threshold model analysis were higher (0.136–0.200 & 0.110–0.283). Genetic correlations among parities differed between breeds and models. Genetic correlation between sow stayability and number born alive was positive in many cases, implying that selection for number born alive does not reduce sow stayability. The results seem to be affected by decisions on culling made by farmers.

Powerful detection of polygenic selection and evidence of environmental adaptation in US beef cattle

Selection on complex traits can rapidly drive evolution, especially in stressful environments. This polygenic selection does not leave intense sweep signatures on the genome, rather many loci experience small allele frequency shifts, resulting in large cumulative phenotypic changes. Directional selection and local adaptation are changing populations; but, identifying loci underlying polygenic or environmental selection has been difficult. We use genomic data on tens of thousands of cattle from three populations, distributed over time and landscapes, in linear mixed models with novel dependent variables to map signatures of selection on complex traits and local adaptation. We identify 207 genomic loci associated with an animal's birth date, representing ongoing selection for monogenic and polygenic traits. Additionally, hundreds of additional loci are associated with continuous and discrete environments, providing evidence for historical local adaptation. These candidate loci highlight the nervous system's possible role in local adaptation. While advanced technologies have increased the rate of directional selection in cattle, it has likely been at the expense of historically generated local adaptation, which is especially problematic in changing climates. When applied to large, diverse cattle datasets, these selection mapping methods provide an insight into how selection on complex traits continually shapes the genome. Further, understanding the genomic loci implicated in adaptation may help us breed more adapted and efficient cattle, and begin to understand the basis for mammalian adaptation, especially in changing climates. These selection mapping approaches help clarify selective forces and loci in evolutionary, model, and agricultural contexts.

Multigenerational Effects

Environmental influences resulting in epigenetic mediation of gene expression can affect multiple generations via direct effect (first generation); direct or maternally mediated effects on the fetus (second generation), or gonadal cell lines of the fetus (third generation) when pregnant animals are exposed to the stimuli; and through generational inheritance. The cumulative effects are rapid changes in phenotypic characteristics of the population when compared with rate of phenotypic change from genetic selection. With extensive data collection, significant potential exists to propagate desired characteristics in the livestock industry through epigenetic pathways.