Genetic parameters for large white pigs reared under intensive management systems in Kenya

Random regression models for genetic analysis of body weight in crossbred pigs

“…Huisman et al (2002) in pigs and Begli et al (2016) in poultry also noticed steady increase in additive genetic and maternal permanent environmental variance over time for live-weight using random regression models. Increase in phenotypic variance with age has also been observed in previous investigations in Large White pigs in Kenya (Ouko et al 2017).…”

“…Hence, use of random regression model with quadratic Legendre polynomials was suggested for genetic analysis of pig data for growth. Lukovic et al (2003), Lukovic et al (2004) and Ouko et al (2017) also observed that the first three eigen values of the coefficient matrix of the additive genetic covariance accounted for >98% of the sum of the eigen values. Meyer (2000) also concluded that random regression models were well suited to the analysis of growth data in Australian beef cattle.…”

“…Their heritability estimates were also low ranging between 0.13 and 0.20 and were comparable to the heritability estimates of our investigation. Ouko et al (2017) also estimated variance components of growth in Large White pigs in Kenya using random regression models by fitting different orders of Legendre polynomials. They observed direct heritability estimates ranging between 0.20±0.04 and 0.52±0.08 and permanent environmental heritability between 0±0.01 and 0.15±0.10.…”

“…Main advantages of the random regression models in comparison to multiple-trait models are requirement of fewer parameters to describe longitudinal data, smoother and less biased (co)variance estimates, accounting for genotype×environment interaction, reducing deviation in sire rankings and possibility to predict covariance structure and breeding value of animal at any point along trajectory. Random regression models in pigs are mainly being used for growth, feed intake and litter size (Lukovic et al 2003, Lukovic et al 2004, Martina et al 2015, Ouko et al 2017. The aim of this investigation was to determine heritability estimates of body weight in crossbred pigs using random regression model with Legendre (LP) polynomials of quadratic power.…”

Cardiac and Skeletal Muscle Transcriptome Response to Heat Stress in Kenyan Chicken Ecotypes Adapted to Low and High Altitudes Reveal Differences in Thermal Tolerance and Stress Response

“…Previous studies on HS adapted and nonadapted chickens revealed the biological mechanisms regulated by HS and identified differential immune response between lowland- and highland-adapted chickens exposed to tropical conditions (Park et al, 2019; Te Pas et al, 2019). In this study, we exposed chickens collected from local farmers in Mombasa, which is located at an elevation of approximately 50 m (lowland) in the Kenyan coast with an average temperature between 22°C and 35°C (Njarui et al, 2016), and from Naivasha, located at an elevation of approximately 1800 m (highland) with an average temperature of 8°C to 26°C (Ouko et al, 2017), to a short-term HS treatment (acute) and a repeated longer-term HS treatment (chronic) and analyzed the transcriptome response of skeletal and cardiac tissues using RNA sequencing. Exposure of chicken embryo to elevated temperature induces an adaptive response to HS at later stages in their life (Janke et al, 2004; Loyau et al, 2014; Loyau et al, 2015; Loyau et al, 2016; Fleming et al, 2017).…”