Unraveling the actual background of second litter syndrome in pigs: based on Large White data.

Second litter syndrome (SLS) in sows is when fertility performance is lower in the second parity than in the first parity. The causes of SLS have been associated with lactation weight loss, premature first insemination, short lactation length, short weaning to insemination interval, season, and farm of farrowing. There is little known about the genetic background of SLS or if it is a real biological problem or just a statistical issue.

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

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.

The Impact of Genomic and Traditional Selection on the Contribution of Mutational Variance to Long-Term Selection Response and Genetic Variance.

mutations (DNM) create new genetic variance and are an important driver for long-term selection response. We hypothesized that genomic selection exploits mutational variance less than traditional selection methods such as mass selection or selection on pedigree-based breeding values, because DNM in selection candidates are not captured when the selection candidates' own phenotype is not used in genomic selection, DNM are not on SNP chips and DNM are not in linkage disequilibrium with the SNP on the chip. We tested this hypothesis with Monte Carlo simulation.

Selecting for changes in average "parity curve" pattern of litter size in Large White pigs.

This study aimed to analyse genetic background of variation in reproductive performance between parities of a sow and to investigate selection strategies to change the "parity curve". Total number born (TNB) recorded in Large White sows was provided by Topigs Norsvin. Analysis with basic (BM) and random regression (RRM) models was done in ASReml 4.

Genomic regions underlying uniformity of yearling weight in Nellore cattle evaluated under different response variables.

Background: In livestock, residual variance has been studied because of the interest to improve uniformity of production. Several studies have provided evidence that residual variance is partially under genetic control; however, few investigations have elucidated genes that control it. The aim of this study was to identify genomic regions associated with within-family residual variance of yearling weight (YW; N = 423) in Nellore bulls with high density SNP data, using different response variables.

Genetic Selection to Enhance Animal Welfare Using Meat Inspection Data from Slaughter Plants.

Animal health and welfare are monitored during meat inspection in many slaughter plants around the world. Carcasses are examined by meat inspectors and remarks are made with respect to different diseases, injuries, and other abnormalities. This is a valuable data resource for disease prevention and enhancing animal welfare, but it is rarely used for this purpose.

Heritable environmental variance causes nonlinear relationships between traits: application to birth weight and stillbirth of pigs.

There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of other traits, however. A genetic covariance between these is expected to lead to nonlinearity between them, for example between birth weight and survival of piglets, where animals of extreme weights have lower survival.

Strategic test-day recording regimes to estimate lactation yield in tropical dairy animals.

Background: In developing dairy sectors, genetic improvement programs have limited resources and recording of herds is minimal. This study evaluated different methods to estimate lactation yield and sampling schedules with fewer test-day records per lactation to determine recording regimes that (1) estimate lactation yield with a minimal impact on the accuracy of selection and (2) optimise the available resources.

Methods: Using Sahiwal cattle as a tropical dairy breed example, weekly milk records from 464 cows were used in a simulation study to generate different shaped lactation curves.

Identification of proteomic biomarkers in M. Longissimus dorsi as potential predictors of pork quality.

Meat quality traits have low heritability and large environmental influences. To predict, improve and manage meat quality, proteomic biomarkers are superior to genetic markers. The objectives of this research were (1) to find associations between proteome profiles of longissimus muscle at slaughter and meat quality accuracies of prediction of traits ranged from 20 up to 80%.

Gene expression patterns in four brain areas associate with quantitative measure of estrous behavior in dairy cows.

Background: The decline noticed in several fertility traits of dairy cattle over the past few decades is of major concern. Understanding of the genomic factors underlying fertility, which could have potential applications to improve fertility, is very limited. Here, we aimed to identify and study those genes that associated with a key fertility trait namely estrous behavior, among genes expressed in four bovine brain areas (hippocampus, amygdala, dorsal hypothalamus and ventral hypothalamus), either at the start of estrous cycle, or at mid cycle, or regardless of the phase of cycle.

Genetic heterogeneity of residual variance - estimation of variance components using double hierarchical generalized linear models.

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used.