Browsing by Subject "Merkmal"

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    Genomic analyses of behavior traits in laying hen lines divergently selected for feather pecking
    (2021) Iffland, Hanna; Bennewitz, Jörn
    Feather pecking is a longstanding problem in commercial layer flocks. It often causes injured birds and even cannibalism. In the past, hens were beak trimmed to reduce feather pecking. Nevertheless, this procedure is already prohibited in some EU countries. Hence, a solution to this problem is urgently needed. The experimental populations analyzed in this thesis were formed by hens based on a White Leghorn layer strain which were divergently selected for high and low feather pecking since 1995. The first experimental population of this thesis was an F2 cross of about 900 hens which was established of the 10th generation of the pure selection lines. The second population consisted of about 500 hens of the 15th generation of these two lines. The aim of this thesis was to gain further knowledge of the genetic background of feather pecking and its relation to additional behavior traits and the gut microbiome. In chapter one, a novel model to detect extreme feather pecking hens was developed. Therefore, a mixture of two negative binomial distributions was fitted to feather pecking data of the F2 cross. With the estimated parameters, the trait posterior probability of a hen to belong to the extreme feather pecking subgroup (pEFP) was calculated. The fear tests tonic immobility and emerge box were conducted at juvenile and adult age of the hens to relate fearfulness to pEFP. After dichotomization, all traits were analyzed in a multivariate threshold model and subsequent genomewide association studies (GWAS) were performed. The fit revealed that extreme feather peckers made up a proportion of about one third of the hens. The new trait pEFP has a medium heritability of 0.35 and is positively correlated with the fear traits. Breeding for this new trait could be an option to reduce the proportion of extreme feather peckers. An index of fear related traits might serve as a proxy to breed indirectly against pEFP. In chapter two, the model to detect extreme feather pecking hens was applied to the pure selection lines. After calculation of the trait pEFP, GWAS with a subsequent post GWAS analysis were performed. Additionally, to find genomic regions influencing feather pecking, selection signatures were mapped by applying the intra-population iHS and the inter-population FST approach. Mapping of selection signatures revealed no clear regions under selection. GWAS revealed a region on chromosome one, where the existence of a quantitative trait locus (QTL) influencing feather pecking is likely. The candidate genes found in this region are a part of the GABAergic system. Despite the polygenic nature of feather pecking, selection on these candidate genes may reduce the extreme occurrence of it. In chapter three, the relation between agonistic behavior and feather pecking was analyzed. Therefore, the active parts of the traits (delivery of feather pecking, aggressive pecking or threatening) as well as the passive parts (reception of the traits) were considered. These groups of traits were additionally summarized by means of an index formation which led to the two additional traits Activity and Passivity, because all these behaviors are undesired in their excessive manifestations. Moreover, Indices were built by subtracting the passive traits from the respective active traits to obtain the feather pecking index, the aggression index and the threat index. Phenotypic correlations were estimated between all traits which were followed by heritability estimations and GWAS. Feather pecking is significantly positively correlated with the agonistic traits in both lines. The active traits and the feather pecking index show medium heritabilities. Hence, selection on high feather pecking leads to an increase of agonistic behavior whereas the correlation probably depends on the phase of establishing the social hierarchy and might disappear, after a stable ranking is established. GWAS revealed that the heritable traits in this study seem to be typical quantitative traits. Chapter four provides the analyses of the gut microbial composition of the two feather pecking lines, followed by the estimation of microbiabilities for feather pecking and the two agonistic behavior traits, to study the influence of the gut microbiome on behavior. Microbiota samples from digesta and mucosa were taken from ileum and caecum. The microbial communities were determined by using 16S RNA gene sequencing techniques. Although both lines differ significantly in some fractions of their gut microbial composition, the microbial animal effects were mostly negligibly small. Thus, the calculated microbiabilities were close to zero and not significant in both lines and for all traits investigated. Hence, trait variations were not affected by the gut microbial composition in both feather pecking lines. The thesis ends with a general discussion where additional results of a meta-analysis of pEFP and breeding strategies against feather pecking are considered.
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    Using genome-wide association studies to map genes for complex traits in porcine F2 crosses
    (2018) Schmid, Markus; Bennewitz, Jörn
    In the era of genomics, genome-wide association studies (GWASs) have become the method of choice for gene mapping. This is still of great interest to infer the genetic architecture of quantitative traits and to improve genomic selection in animal breeding. Formerly, linkage analyses were conducted in order to map genes. Therefore, many F2 cross populations were generated by crossing genetically divergent lineages in order to create informative experimental populations. However, a small number of markers and the limited meiotic divisions led to imprecise mapping results. The main objective of the present study was to investigate the use of existing porcine F2 cross data, extended towards single nucleotide polymorphism (SNP) chip genotype information, for quantitative trait loci (QTL) mapping in the genomic era. A special focus was on mapping genes that also segregate within the Piétrain breed since this is an important sire line and genomic selection is applied in this breed. Chapter 1 is a review article of statistical models and experimental populations applied in GWASs. This chapter gives an overview of methods to conduct GWASs using single-marker models and multi-marker models. Further, approaches taking non-additive genetic effects or genotype-by-environment interactions into account are described. Finally, post-GWAS analysis possibilities and GWAS mapping populations are discussed. In chapter 2, the power and precision of GWASs in different F2 populations and a segregating population was investigated using simulated whole-genome sequence data. Further, the effect of pooling data was determined. GWASs were conducted for simulated traits with a heritability of 0.5 in F2 populations derived from closely and distantly related simulated founder breeds, their pooled datasets, and a sample of the common maternal founder breed. The study showed that the mapping power was high (low) in F2 crosses derived from distantly (closely) related founder breeds and highest when several F2 datasets were pooled. By contrast, a low precision was observed in the cross with distantly related founder breeds and the pooling of data led to a precision that was between the two crosses. For genes that also segregated within the common founder breed, the precision was generally elevated and, at equal sample size, the power to map QTL was even higher in F2 crosses derived from closely related founder breeds compared with the founder breed itself. Within and across linkage disequilibrium (LD) structures of such F2 populations were examined in chapter 3 by separately and jointly (pooled dataset) analyzing four F2 datasets generated from different founder breeds. All individuals were genotyped with a 62k SNP chip. The LD decay was faster in crosses derived from closely related founder breeds compared with crosses from phylogenetically distantly related founder populations and fastest when the data of all crosses were pooled. The pooled dataset was also used to map QTL for the economically important traits dressing out and conductivity applying single-marker and Bayesian multi-marker regressions. For these traits, several genome-wide significant association signals were mapped. To infer the suitability of F2 data to map genes in a segregating breeding population, GWAS results of a pooled F2 cross were validated in two samples of the German Piétrain population (chapter 4). All individuals were genotyped using standard 62k SNP chips. The pooled cross contained the data of two F2 crosses, both had Piétrain as one founder breed, and consisted of 595 individuals. Initially, GWASs were conducted in the pooled F2 cross for the production traits dressing yield, carcass length, daily gain and drip loss. Subsequently, QTL core regions around significant trait associated peaks were defined. Finally, SNPs within these core regions were tested for association in the two samples of the current Piétrain population (771 progeny tested boars and 210 sows) in order to validate them in this breed. In total, 15 QTL were mapped and 8 (5) of them were validated in the boar (sow) validation dataset. This approach takes advantage of the high mapping power in F2 data to detect QTL that may not be found in the segregating Piétrain population. The findings showed that many of the QTL mapped in F2 crosses derived from Piétrain still segregate in this breed, and thus, these F2 datasets provide a promising database to map QTL in the Piétrain breed. The thesis ends with a general discussion.