Browsing by Subject "Genetic parameters"

Now showing 1 - 2 of 2

Genetic analyses of feather pecking and related behavior traits of laying hens
(2016) Lutz, Vanessa; Bennewitz, Jörn
The main objective of the present study was to study the genetic foundation of behaviour traits, especially feather pecking behaviour, and to infer ethological interrelationship between certain traits of laying hens. The data of two divergently selected lines for feather pecking behaviour was available, and additionally a large F2-cross, set up from these divergently selected lines, was established. Chickens of a White Leghorn layer line were divergently selected for high and low feather pecking for 11 generations. The selection started in the Danish Institute of Animal Sciences, Foulum, Denmark, for the first six generations (0-5). Thereafter, five rounds of selection took place at the Institute of Animal Science, University of Hohenheim, Germany. The large F2-cross was established from the 10th selection generation, and a comprehensive data collection of behaviour and performance traits of 960 hens was performed. These two data sets were used for the following five research chapters. In chapter one, a quantitative genetic analysis of fear traits and feather pecking as well as aggressive pecking using data from the large F2-cross was performed. Fear was recorded by the tonic immobility test, the open field activity and the emergence box test. These were recorded at a juvenile and adult age. Behavior traits as feather pecking and aggressive pecking were recorded in groups of 36 to 40 animals at the age of 27 weeks. The genetic parameters were estimated using a linear mixed model. Aggressive pecking showed the highest heritability (0.27) followed by feather pecking (0.14). The fear test traits showed heritabilities in the range of 0.07 to 0.14. The appreciable genetic correlation between fear traits and feather pecking was tonic immobility at juvenile age (rg=0.27). In chapter two we used dispersed Poisson models to estimate variance components, heritabilities of feather and aggressive pecking of different observation periods. The short period included the number of feather pecks in 20 min and the medium period was the summed bouts within one day. The results showed that modelling the data as repeated observations (short and medium period) and analysing them with a dispersed Poisson model is a suitable option to separate the important permanent environment effects from the additive animal effects and to account for the non-normal distribution of the data. The objective of chapter three was to analyze the interrelationship between feather pecking and feather eating as well as general locomotor activity using structural equation models. The estimated heritabilities of feather eating, general locomotor activity and feather pecking were 0.36, 0.29 and 0.20, respectively. The genetic correlation between feather pecking and feather eating (general locomotor activity) was 0.17 (0.04). A high genetic correlation of 0.47 was estimated between feather eating and general locomotor activity. The recursive effect from feather eating to feather pecking was λ ̂_(FP,FE)= 0.258, and from general locomotor activity to feather pecking λ ̂_(FP,GLA)= 0.046. These results imply that an increase of feather eating leads to an increased feather pecking behavior and that an increase in general locomotor activity results in a higher feather pecking value. The objective of chapter four was to perform a quantitative genetic analysis and to map signatures of selection in two divergent laying hen lines selected for feather pecking behaviour. In the selection experiment, lines were selected for low or high feather pecking for 11 generations. Pedigree and phenotypic data were available for the last six generations of both lines for the statistical analysis with a standard mixed linear model and a Poisson model. The mixed linear model failed to analyse the low feather pecker data because of the large number of 0s in the observation vector. The Poisson model fitted the data well and revealed a small but continuous genetic trend in both lines. From the 11th generation 75 birds, 41 high feather peckers and 34 low feather peckers were genotyped using the Illumina 60K chicken Infinium iSelect chip. An FST-based approach was used to map selection signature. We detected 17 genome-wide significant SNPs with a FST-value of 1, i.e. alleles were divergently fixed in the two lines, which are mostly located on chromosome 3 and 4, and a number of additional significant SNPs with a p-value of ≤ 5x10-4 and ≤ 5x10-5, respectively. Based on the assumption that selection affects several consecutive SNPs, 13 clusters were identified. In chapter five, we used the data from the large F2-cross experiment to perform a genome-wide association study for feather pecking and aggressive pecking behaviour, to combine the results of this GWAS with the results from the selection experiment (chapter four) in a meta-analysis, and to link the results to those obtained from a differential gene expression study. 817 F2-hens were genotyped with the Illumina 60K chicken Infinium iSelect chip. We used single marker association analysis and a Poisson model. We detected four genome-wide significant SNPs for aggressive pecking delivered, but none for feather pecking and aggressive pecking received. However, a number of significant SNPs at p≤5x10-5 were mapped for feather pecking and aggressive pecking received. In the meta analysis we identified nine genome-wide significant SNPs for feather pecking delivered, which were localized in chromosomal clusters (3 Mb). A previously conducted differential gene expression analysis provided eight significantly differential expressed genes within the feather pecking associated chromosomal clusters. The thesis ends with a general discussion.
Genetic and phenotypic correlations among feed efficiency, immune and production traits in indigenous chicken of Kenya
(2023) Miyumo, Sophie A.; Wasike, Chrilukovian B.; Ilatsia, Evans D.; Bennewitz, Jorn; Chagunda, Mizeck G. G.
This study aimed at estimating genetic and phenotypic relationships among feed efficiency, immune and production traits measured pre- (9–20 weeks of age) and post- (12 weeks from on-set of lay) maturity. Production traits were average daily gain (ADG) and average daily feed-intake (ADFI1) in the pre-maturity period and age at first egg (AFE), average daily feed-intake (ADFI2) and average daily egg mass (EM) in the post-maturity period. Feed efficiency comprised of residual feed intake (RFI) estimated in both periods. Natural antibodies binding to keyhole limpet hemocyanin (KLH-IgM) and specific antibodies binding to Newcastle disease virus (NDV-IgG) measured at 16 and 28 weeks of age represented immune traits pre- and post-maturity, respectively. In the growing period, 1,820 records on ADG, KLH-IgM and NDV-IgG, and 1,559 records on ADFI1 and RFI were available for analyses. In the laying period, 1,340 records on AFE, EM, KLH-IgM and NDV-IgG, and 1,288 records on ADFI2 and RFI were used in the analyses. Bi-variate animal mixed model was fitted to estimate (co)variance components, heritability and correlations among the traits. The model constituted sex, population, generation, line and genotype as fixed effects, and animal and residual effects as random variables. During the growing period, moderate to high heritability (0.36–0.68) was estimated for the production traits and RFI while the antibody traits had low (0.10–0.22) heritability estimates. Post-maturity, the production traits and RFI were moderately (0.30–0.37) heritable while moderate to high (0.25–0.41) heritability was estimated for the antibody traits. Genetic correlations between feed efficiency and production traits in both periods showed that RFI had negative genetic correlations with ADG (−0.47) and EM (−0.56) but was positively correlated with ADFI1 (0.60), ADFI2 (0.74) and AFE (0.35). Among immune and production traits, KLH-IgM and NDV-IgG had negative genetic correlations with ADG (−0.22; −0.56), AFE (−0.39; −0.42) and EM (−0.35; −0.16) but were positively correlated with ADFI1 (0.41; 0.34) and ADFI2 (0.47; 0.52). Genetic correlations between RFI with KLH-IgM (0.62; 0.33) and NDV-IgG (0.58; 0.50) were positive in both production periods. Feed intake, RFI and antibody traits measured in both production periods were positively correlated with estimates ranging from 0.48 to 0.82. Results from this study indicate selection possibilities to improve production, feed efficiency and immune-competence in indigenous chicken. The genetic correlations suggest that improved feed efficiency would be associated with high growth rates, early maturing chicken, high egg mass and reduced feed intake. In contrast, improved general (KLH-IgM) and specific (NDV-IgG) immunity would result in lower growth rates and egg mass but associated with early sexual maturation and high feed intake. Unfavorable genetic correlations between feed efficiency and immune traits imply that chicken of higher productivity and antibody levels will consume more feed to support both functions. These associations indicate that selective breeding for feed efficiency and immune-competence may have genetic consequences on production traits and should therefore be accounted for in indigenous chicken improvement programs