hohPublica :: Browsing by Person "Bennewitz, Jörn"

Browsing by Person "Bennewitz, Jörn"

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Analyse komplexer Merkmale beim Schwein mittels SNP-Chip Genotypen, Darmmikrobiota- und Genexpressionsdaten
(2017) Maushammer, Maria; Bennewitz, Jörn
In the present scientific research, SNP chip genotypes, gut microbiota and gene expression data were used for analysing complex traits in a Piétrain population. These data were collected from around 200 performance tested sows and were used for genetic and microbial analyses of complex trait as well as for structural and functional meat quality traits. The gut microbiome plays a major role in the immune system development, state of health and energy supply of the host. Quantitative-genetic methods were applied to analyse the interrelationship between pig gut microbiota compositions, complex traits (daily gain, feed conversion and feed intake) and pig genomes. The specific aims were to characterize the gut microbiota of the pigs, to analyse the effects of host genetics on gut microbial composition, and to investigate the role of gut microbial composition on the host’s complex traits. The pigs were genotyped with a standard 60K SNP chip. Microbial composition was characterized by 16S rRNA gene amplicon sequencing technology. Ten out of 51 investigated bacterial genera showed a significant host heritability, ranging from 0.32 to 0.57. Conducting genome wide association analysis showed associations of 22 SNPs and six bacterial genera. The potential candidate genes identified are involved in the immune system, mucosa structure and secretion of digestive juice. These results show, that parts of the gut microbiota are heritable and that the gut microbiome can be seen as quantitative trait. Microbial mixed linear models were applied to estimate the microbiota variance for each of the investigated traits. The fraction of phenotypic variance explained by the microbial variance was 0.28, 0.21, and 0.16 for daily gain, feed conversion, and feed intake, respectively. The SNP data and the microbiota data were used to predict the phenotypes of the traits using both, genomic best linear unbiased prediction (G-BLUP) and microbial best linear unbiased prediction (M-BLUP) methods. The prediction accuracies of G-BLUP were 0.35, 0.23, and 0.20 for daily gain, feed conversion, and feed intake, respectively. The corresponding prediction accuracies of M-BLUP were 0.41, 0.33, and 0.33. Thus, the gut microbiota can be seen as an explaining variable for complex traits like daily gain, feed conversion and feed intake. In addition, in combination with meat quality traits, transcript levels of muscle tissue were analysed at time of slaughtering. This study should give an insight into the biological processes involved in meat quality characteristics. The aims were to functionally characterise differentially expressed genes, to link the functional information with structural information obtained from GWAS, and to identify potential candidate genes based on these results. An important meat quality trait is the intramuscular fat content, since it affects the juiciness, the taste and the tenderness of the meat. Another important trait is drip loss which causes not only a loss of weight but also a loss of important proteins. Both traits have an impact on the consumer acceptance of fresh meat products. For each of the two traits, eight discordant sibling pairs were selected out of the Piétrain sample and were used for genome-wide gene expression analyses. Thirty five and 114 genes were identified as differentially expressed and trait correlated genes for intramuscular fat content and drip loss, respectively. On the basis of functional annotation, gene groups belonging to the energy metabolism of the mitochondria, the immune response and the metabolism of fat, were associated with intramuscular fat content. Gene groups associated with protein ubiquitination, mitochondrial metabolism, and muscle structural proteins were associated with drip loss. Furthermore, genome-wide association analyses were carried out for these traits and their results were linked to the genome-wide expression analysis by functional annotation. In this context, intramuscular fat was related to muscle contraction, transmembrane transport and nucleotide binding. Drip loss was characterized by the endomembrane system, the energy generation of cells, and phosphorus metabolic processes. Three and four potential candidate genes were identified for intramuscular fat content and drip loss, respectively.
Analyses of quantitative traits in varying environments in pigs and Brown Swiss cattle
(2020) Imort-Just, Nina Annik; Bennewitz, Jörn
Complex breeding programmes are used worldwide to achieve genetic progress in quantitative traits. These programmes are basically similarly structured, independent of breed and species, and are characterised by successive steps. The adjustment and revision of breeding programmes is of ongoing interest due to several reasons, e.g. research findings and various political, economic, social and ethical aspects. For the long-term improvement of livestock populations, multiple traits are included in the breeding goals of such programmes. Unfavourable genetic correlations between economically important production traits and functional traits compromise the genetic progress in animal health and welfare. Novel functional and behavioural traits and the adjustment of relative economic weights for the optimisation of total merit indices are investigated in research projects. In addition, genotype by environment interactions (GxE) can influence the genetic improvement of livestock populations and their consideration is crucial due to the globalisation of breeding structures and associated varying production environments. The main objectives of this thesis were 1) to investigate novel behavioural traits in pig breeding, 2) to derive environmental-specific relative economic weights based on consumers preferences for Brown Swiss cattle, 3) to estimate GxE at a trait and an index level by applying bivariate sire models in Brown Swiss cattle and 4) to analyse GxE for different production and functional traits in Brown Swiss cattle using reaction norm models. In Chapter 1 genetic parameters for mothering ability traits were estimated. Heritabilities (h²) were estimated by applying a linear mixed- and a threshold model, ranging between 0.02 to 0.07 and 0.05 to 0.15, respectively. The slightly higher estimates for the repeatability ranged from 0.05 to 0.09 and from 0.08 to 0.17, indicating the influence of the permanent environment. Highest h² were found for the group- and nursing behaviour of the sows. Highest genetic correlations were found between group-/nursing behaviour and litter balance and piglet weaning weight with estimates between 0.71 and 0.86. Accelerating genetic gain for improved mothering ability in sows is possible. In Chapter 2, the importance of breeding traits of Brown Swiss cattle in terms of selection decisions of farm managers was evaluated by using a discrete choice experiment (DCE). Environment-specific relative economic weights (REW) and the marginal willingness to pay were estimated by using a conditional logit model. Several trait complexes, the semen price, interactions between these traits and specific characteristics of the farms were included. Farmers showed highest preferences for the milk value, conformation/udder and fitness. Interactions indicated a great importance of the fitness trait complex for organically managed farms compared to conventional farmers. The latter weighted the milk value and the trait complex conformation/udder high. The method is suitable to judge farmers’ preferences for specific traits, especially those which have not yet been monetarily evaluated. Chapter 3 investigated GxE at a trait and an index level for Brown Swiss sires. Bivariate sire models were used to estimate genetic correlations between organic and conventional production systems and two altitude level of the farms for milk production traits and several functional traits. Furthermore, to determine possible GxE and rerankings at an index level, total merit indices for the sires were calculated. The genetic correlations were high between the analysed environments, ranging from 0.79 (first insemination to conception between different altitude levels) to 0.99 (calving to first insemination, cystic ovaries, maternal stillbirth between production systems). The results indicate no severe GxE at a trait level. No putative GxE effects were found for the production system environments at an index level. In Chapter 4, GxE for various production and functional traits in Brown Swiss cattle were analysed using random regression reaction norm models. The continuous environmental descriptor milk energy yield (MEY) was calculated as a linear combination of average herd effects, obtained from the routine breeding value estimation, of milk-, fat- and protein yield. The applied reaction norm model included a random sire effect and a random sire slope effect (environmental sensitivity), i.e. the random regression coefficient of the regression of a specific sire on the environmental descriptor MEY. To investigate putative GxE effects, breeding values for the sires were estimated. Results showed no severe GxE for the functional traits but for the production trait fat yield. In addition, the slope variances as descriptors of the environmental sensitivity and the Spearman rank correlations between the estimated breeding values of the sires at different environmental levels indicate no severe GxE for the investigated traits.
Analysis of phosphorus utilization using the host genome and microbiota variability in Japanese quail
(2021) Vollmar, Solveig Deniece; Bennewitz, Jörn
Phosphorus (P) is an essential element for growth and performance of avian species. It is predominantly bound as phytic acids and salts (phytate) in plant seeds. Phytases and other phosphatases can harness P by cleaving P groups. Nonruminants have low endogenous phytase activity in the gastrointestinal tract, and thus, the requirement of this element is not met from exclusive plant-based diets. Therefore, mineral P or phytase enzymes are supplemented in poultry feed. Due to the finite quantities of high quality mineral P worldwide, it is of great economic interest. P supplementation is increasingly causing environmental problems. Past studies investigated the P utilization (PU) of different poultry species. They revealed a high phenotypic variation in PU among individuals. Moderate heritabilities indicates that breeding for this trait is in principle possible. The overall aim of this thesis was to gain a deeper understanding of the variability of P utilization in relation to host genetics, ileal microbiota composition and their interaction in the model species Japanese quail. The objective of chapter two was to verify whether variation in PU in quail is a heritable trait conditioned by a few quantitative trait loci (QTL) with detectable effects. For this purpose, individuals were genome-wide genotyped with a 4k SNP chip, and a linkage map was generated. Based on this map, QTL linkage analysis was performed using multimarker regression analysis in a line-crossing model to map QTL for PU. We identified a few QTL regions with significant effects. Among them was a QTL peak at Coturnix japonica chromosome (CJA) 3 for PU. Several genes were found in the region surrounding this peak, which requires further functional gene analysis. Based on these results, we hypothesized that these traits are polygenically determined due to several small QTL effects, which we could not detect significantly. The overlap of the QTL regions indicated linkage of the traits and confirmed their genetic correlations. With the aim of predicting microbiota-related host traits, chapter three examined the composition of the ileum microbiota and differential abundance analysis (DAA). Based on this study, it was shown that a sex-specific influence on microbiota composition exists. The digesta samples of all animals were dominated by five genera, which contributed to more than 70% of the total ileum microbial community. In examining the microbiota composition of each of the 50 animals with the highest and lowest PU, DAA revealed genera significantly associated with PU. In chapter four, we characterized the influence of performance-related gut microbiota to unravel the microbial architecture of the traits evaluated. The aim of this study was to determine whether the variation in PU is partly driven by the microbial community in the ileum. We used microbial mixed linear models to estimate microbiabilities (m^2). This determines the fraction of phenotypic variance that can be explained by the gut microbiota. The estimation of m^2 was 0.15 for PU and was highly significant. It was also highly significant for feed intake, body weight gain and feed per gain. This model was bivariately extended and showed a high microbial correlation of the traits. Based on both results, the ileum microbiota composition plays a substantial role in PU as well as in performance traits, and there is a considerable animal microbiota correlation, showing that the microbiota affects multiple traits. The microbial drivers of this microbial fraction were identified by applying microbiome-wide association studies (MWAS). By back-solving the microbial linear mixed model, we approximated the effect of single OTUs on the phenotypic traits from the microbial model solutions. An MWAS at the genus level uncovered several traits associated with bacterial genera. Subsequently, we assessed whether the microbial community in the ileum is a heritable host trait that can be used for breeding individuals with improved PU. In chapter five we applied QTL analysis using specific genera to examine whether they are linked with genomic SNP markers. These QTL analyses revealed a link between some microbiota species and host genomic regions of chromosomes and SNP markers. By estimating significant heritabilities for some genera, we were able to provide evidence for the hypothesis that the microbial community and microbial features are at least partially related to host genetics. We predicted the animal microbial effects on PU and correlated performance traits by applying microbial best linear unbiased predictions (M-BLUP). In addition, genomic best linear unbiased predictions (G-BLUP) were used to predict the SNP effect for the predicted animal microbial effect. A combination of those two may help to predict genomic breeding values of the microbiota effects for future hologenomic breeding programs.
Climate change adaptation, social networks, and agricultural extension reforms in Ethiopia
(2016) Tensay, Teferi Mequaninte; Bennewitz, Jörn
Research on the impact of climate change in sub-Saharan Africa shows that climate change is expected to cause an increased frequency of extreme events such as high temperature and rainfall intensity, droughts and floods, desertification, and spread of animal and human diseases. These extreme events are likely to have a negative impact on food security. Using the case of Ethiopia, this thesis analyses the role that social network and agricultural extension can play in enhancing farmers’ ability to adapt to climate change. The thesis builds on recent research, which has highlighted the role of social networks and extension in promoting adaptation to the negative impacts of climate change. Social networks between farmers can build community resilience and increase adaptation to climate change. They also affect technology adoption and climate change adaptation through social learning, joint evaluation of new technologies and collective action. Current research on social networks in Ethiopia has mainly focused on the effects of network size on technology adoption and there is no empirical study on which types of social networks matter the most, and how do such types of social networks matter for climate change adaptation. Agricultural extension is expected to facilitate climate change adaptation through training and education of farmers, enabling them to anticipate climate change and to update their knowledge, attitudes and adaptive capabilities in response to climate change. In addition to their well-established function of promoting technologies and natural resource management practices, agricultural extension services are expected to play new roles in building farmers’ social networks and supporting climate change adaptation strategies. There are various studies on agricultural extension reforms in Ethiopia, but there are still gaps in this literature, especially regarding the capacity of the extension service to promote adaptation to climate change and to promote social networks. The purpose of this thesis is, therefore, to fill these knowledge gaps and to contribute to the current debate on the dynamic links between climate change, social networks and extension reforms. The thesis combines quantitative and qualitative methods for analysis of three inter-related research topics. First, the thesis examines farmers’ vulnerabilities to climate change and the role of adaptation in increasing productivity at the household level. Second, it assesses how the different types of social networks are related with the adoption of sustainable land management practices for climate change adaptation. Third, by examining what works and what does not work well in the agricultural extension reforms in Ethiopia, the thesis investigates the interactions between climate change, social networks and extension reforms in Amhara region of Ethiopia. The thesis is based on a mixed methods approach. It combines a quantitative analysis, using World Bank data from a survey conducted in 2011 covering 1338 farmers. The analytical methods include a probit model, an OLS analysis and an endogenous switching regression model. Qualitative research methods included Focus Group Discussions (FGDs) combined with an individual scoring technique, and a Climate Vulnerability and Capacity Analysis. The study on climate change adaptation found that the effects of climate change and adaptation practices differ across agro-ecological zones and adopter groups. In the kolla agro-ecologies, the major hazards were drought, floods, and migration. In contrast, snowfall, landslides and crop diseases were the main hazards in the dega and woyna-dega agro-ecologies. Erratic rainfall, soil erosion and livestock diseases were common hazards to all agro-ecologies. Households’ responses to the hazards were differed across the different agro-ecologies. In the kolla agro-ecologies, the most common coping strategies were reducing the number of daily meals, migration, livestock selling and utilization of irrigation. In the dega and woyna-dega agro-ecologies common coping strategies included: changing consumption patterns; adopting drought resistant crops (sorghum and millet); sale of chickens, eggs, sheep, goats, eucalyptus trees; soil conservation and tree planting; zero grazing and water harvesting. In all agro-ecologies, local institutions support communal adaptation strategies such as communal water harvesting and irrigation schemes, reforestation, rangeland enclosure and prevention of soil erosion. The empirical results also revealed that farmers who implemented climate change adaptation strategies have significantly increased their food productivity and food security, compared to farmers who did not implement such strategies. The findings regarding the relationship between social networks and sustainable land management revealed that networks with relatives have a positive impact on planting trees, but the impact of such networks on soil conservation was found to be negative. This finding can be interpreted as an incidence of self-interested behavior, since farmers may plant trees as a means of securing land holdings. When farmers are faced with the risk of losing their land to relatives, due to common heritage, they prefer planting trees to soil conservation. Farmers can reclaim all their investment costs by cutting trees, should they lose their land holding rights to relatives. In contrast, it would be difficult to regain soil conservation investment costs in this case. Friendship networks were found to be insignificant in both planting trees and soil conservation, while neighborhood ties only had a significant association with tree planting. This suggests the potential contributions of friendship and neighborhood networks, which can significantly affect sustainable land management practices, but may remain untapped. The analysis of extension conducted as part of this thesis suggests that a uniform reform approach, as pursued in Ethiopia, does not fit well with the diverse agro-ecologies and extension challenges in the country. While the number of service providers increased substantially, they still lack skills, incentives and resources, which affect their work motivation and job performance. Moreover, the planning, monitoring and evaluation system was found not to be very effective in regularly assessing what has been achieved at the farmers’ training centers and what remains to be done in the future. Similarly, there is room to improve partnerships and linkages of actors, especially by including key actors that are currently missing. Based on the above findings, this thesis derived the following policy implications: 1. The potential capacity of schools and religious organizations in supporting climate change adaptation should be tapped. The case study identified agricultural extension, health extension, NGOs, cooperatives, indigenous institutions (Iddir, Kirre, Jiggie, Debo, Iquib), microfinance institutions, schools, local governments, youth and women groups as key institutions providing rural services. However, extension organizations, cooperatives/unions, local governments and NGOs were the only institutions providing services relevant for climate change adaptation. Surprisingly, important local institutions (schools and religious organizations) did not have any short or long term plans to support climate change adaptation efforts despite the fact that they have the social capital to plan and implement some communal strategies such as terracing and planting trees on communal lands. 2. The regional and national policies should support local climate change adaptation strategies. The study showed that adaptation efforts should not be left to only farmers and local governments. Regional and national policies should support the local adaptation strategies. It was found that the absence of communal land and natural resource use policies was encouraging farmers to over utilize natural resources, and the long delay in land use rights (certification) was discouraging farmers from making long term investments on their land (e.g., tree planting and soil conservation). Therefore, the findings suggest that it would be useful to promote the introduction of communal land and natural resource use policy and a speedy land certification process. 3. The potential contributions of social networks as alternative channels of extension services should be tapped. The findings revealed that funds for agricultural extension are declining and extension managers should look for alternative source of funding and move away from a “one-size-fits-all” thinking to a “best fit” approach. It needs to become a priority for the current extension system to better understand what types of social networks matter most for technology adoption. 4. The findings also indicate that extension reforms should consider current agricultural challenges, especially climate change. In dega and woyna-daga agro-ecologies, the main challenges were getting information on climate change related hazards (rainfall and temperature), commercial marketing (cooperative development, price and new markets), post-harvest handling (drying and storage technique). In the kolla agro-ecologies, the major problems were lack of dry land farming methods (contour plowing, mulching, strip farming, summer fallow, seedbed preparation and planning in rows). So far, the extension system is not geared towards addressing these different challenges, which calls for aligning the extension reforms to the different local farming systems. 5. It can also be derived from the findings of this study that the regional government should design a new incentive system for the extension service. The case study showed that current incentives are inconsistent with the regional goal of promoting commercially oriented agriculture. Service providers in the region were found to lack the soft skills, incentives and resources to provide commercially oriented services. This finding calls for designing a new incentive system, which may include better salary, improved career prospects, and recognition as well as incentives for extra work. Such provisions will motivate and enable frontline service providers. 6. The governance and management structures of the Agricultural Development Partners’ Linkage Advisory Councils (ADPLACs) should be redesigned. The case study revealed that when measured against indicators such as information sharing and feedback, joint planning, monitoring, evaluation and implementation, the linkages between farmers, NGOs and research institutes were very weak. This calls for redesigning the governance and management structures of the Agricultural Development Partners’ Linkage Advisory Councils (ADPLACs), which was responsible for facilitating the partnership and linkages of extension actors in the region. 7. The findings of this thesis also suggest that the roles of NGOs and the private sector in the provision of extension service should be enhanced. The case study found that key actors such as the private sector and NGOs were missing from effective provision of extension services. The private sector and NGOs may have a comparative advantage in activities such as provision of improved seeds, fertilizers, pesticides, vaccination, deworming and artificial inseminations. NGO and private sector engagement in these areas will allow the regional government to free up and reallocate funds to its broader extension strategies such as development of new incentive schemes, education and training, technical advisory services, sustainable natural resource management practices and organizing farmers to link them with new markets.
Detailed genomic analysis of correlation and causality between milk production and health traits in German Holstein cattle using high-dimensional genomic data and novel statistical methods
(2024) Schneider, Helen Hiam; Bennewitz, Jörn
Adverse side effects of high milk production on animal health have been mentioned frequently. They are compromising animal welfare, the farmers` economy, and the ecological footprint as well as the social acceptance of milk production. Consequently, many countries started to include functional traits into their breeding goal a few decades ago. The intention is thereby to avoid putative undesirable side effects of high production and to improve the cows` health in the long term through genetic gain. Indeed, positive genetic trends for various functional and health traits have been described in the literature. At the same time, the genetic trend of milk production traits remained positive. In general, sustainable genetic gain requires an appropriate weight of the individual traits in the selection index and a comprehensive understanding of the traits` genetic architecture and their interrelationship. This can be facilitated by recent innovations that enable the widespread availability of whole genome sequence (WGS) data. WGS data contains genomic information about millions of SNPs, derived either from sequencing or from imputing lower density SNP chip data to sequence level. Using external information about these sequence variants in genomic analyses, e.g., concerning their function during transcription and translation, has been shown to reveal additional knowledge about biological and molecular mechanisms shaping complex traits. Hence, applying external information to estimate genetic correlations might help to dissect the traits` interrelationship in more detail. Additionally, going beyond global genetic correlations, this is, reflecting the shared genetic effect throughout the genome, to the local scale, this is, the genetic sharing in specific genomic regions, would be an alternative to provide novel knowledge about the extent and direction of the shared genetic effect and its localization in the genome. The expected information is desired to understand and to avoid potential detrimental effects of selection decisions on animal health. Moreover, moving away from correlation towards causation would enable to predict the impact of management decisions and external interventions. The aim of this thesis was to scrutinize the genetic connection between health and milk production traits in dairy cattle using a large sample of 34,497 German Holstein cows with pedigree, 50K SNP chip, and imputed WGS data consisting of ~17 million variants. To this end, standard quantitative genetic analyses were augmented by a set of novel approaches to detect genomic regions with a substantial genetic effect on several traits and to investigate causal associations. Chapter one applied the 50K chip data to estimate additive genetic and dominance variance components for the milk production and health traits. This was done since substantial nonadditive genetic effects for functional traits have been mentioned in the literature, whereas little is known about these effects for the health traits examined in this thesis. It was demonstrated that the contribution of the dominance variance to the phenotypic variance was rather small for all traits. However, regarding the health traits, the contribution of the dominance variance to the genetic variance was almost as high as, and sometimes even higher than the contribution of the additive genetic variance. In addition, significant inbreeding depression was found for the milk production traits. Chapter two consisted of three steps. First, pedigree-based heritabilities of and global genetic correlations between milk production and health traits were estimated. Most heritabilities of the health traits and their genetic correlations with the milk production traits were low, whereby the genetic correlations were in an unfavorable direction. Next, genome-wide association studies (GWAS) were performed for each trait utilizing the 50K chip data to generate summary statistics. The summary statistics are required as input data for the last step that applied a tool to detect shared genomic regions. Genomic regions simultaneously affecting milk production and health traits were identified for each trait combination, of which some also had a sign in the favorable direction. This chapter confirmed the advantage of scrutinizing global genetic correlations down to the local scale. Chapter three utilized the 50K chip as well as the imputed WGS data. The latter was thereby divided into 27 subsets depending on the variants` functional and evolutionary annotation, e.g., as gene expression quantitative trait loci or selection signature. Heritabilities of and genetic correlations between milk yield and several health traits were estimated for the 50K chip and each of the 27 subsets. The results indicate that the 50K chip appears to be sufficient to explain the genetic variance of the investigated traits, whereas it seems to underestimate their genetic covariance. Furthermore, the importance of alternative splicing for the (co-)variation of quantitative traits and the important role of the negative energy balance causing the unfavorable side effects of high production on animal health has been confirmed. Chapter four was a Mendelian randomization (MR) analysis. Here, the causal effect of milk yield on a set of health traits was examined using a method that is based on summary statistics. In this chapter, the summary statistics were generated using the imputed WGS data. Unfavorable causal effects of milk yield on most health traits were identified that were strongest for mastitis and digital phlegmon. This indicates potential detrimental consequences for these traits with increasing milk yields, owed to selection decisions or inappropriately chosen weights in the selection index. The general discussion is addressing the negative side effects of high production on animal health with special focus on the negative energy balance. Moreover, including feed efficiency and resilience indicator traits into the breeding goal is discussed with respect to the results reported in the previous chapters. Besides, additional information about the methodology of MR analyses and the results of a MR analysis investigating the causal effect of protein and fat yield on the health traits are presented and debated. The general discussion ends with practical implications of the results regarding hologenomic selection strategies and strategies including functional information in genomic prediction.
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.
Genome-wide mapping and functional analysis of genes determining the meat quality in pigs
(2014) Stratz, Patrick; Bennewitz, Jörn
In chapter one QTL were mapped and tested for pairwise epistasis for meat quality traits in three connected porcine F2 crosses comprising around 1000 individuals. The crosses were derived from Chinese Meishan, European Wild Boar and Piétrain. The animals were genotyped genomewide for approximately 250 genetic markers and phenotyped for seven meat quality traits. QTL mapping was done using a multi-QTL multi-allele model. It considered additive (a), dominance (d) and imprinting (i) effects. The major gene RYR1:G.1843C>T affecting the meat quality was included as a cofactor in the model. The mapped QTL were tested for possible epistatic effects between the main effects, leading to nine orthogonal forms of epistasis (aa, ad, da, di, id, ai, ia, dd and ii). Numerous QTL were found; the most interesting are located on chromosome SSC6. Epistasis was significant (FDR q-value<0.2) for the pairwise QTL on SSC12 and SSC14 for pH 24 h after slaughter and for the QTL on SSC2 and SSC5 for rigour. In chapter two around 500 progeny tested Piétrain sires were genotyped with the PorcineSNP60 BeadChip. After data filtering around 48k SNPs were useable in this sample. These SNPs were used to conduct a genome-wide association analysis for growth, muscularity and meat quality traits. Because it is known, that a mutation in the RYR1 gene located on chromosome 6 shows a major effect on meat quality, this mutation was included in the models. Single-marker and multi-marker association analysis were performed. The results revealed between one and eight significant associations per trait with P-value<0.00005. Of special interest are SNPs located on SSC6, 10 and 15. In chapter three a literature search was conducted to search putative candidate genes in the vicinity of significant SNPs found in the association analysis. MYOD1 was suggested as putative candidate gene. The expression of MYOD1 was measured in muscle tissue from 20 Piétrain sires. Growth, muscularity and meat quality traits were available. DNA was isolated out of blood tissue to genotype the SNP ASGA0010149:g. 47980126G>A. Significant Correlations (FDR q-value<0.15) between the expression of MYOD1 and growth and muscularity traits were found. Association between the traits, respectively MYOD1, and ASGA0010149:g. 47980126G>A was tested, but was only significant (FDR q-value<0.15) for two muscularity traits. In chapter four the LD structure in the genome of the Piétrain pigs was characterized using data from the PorcineSNP60 BeadChip. The Relative Extended Haplotype Homozygosity test was conducted genome-wide to search for selection signatures using core haplotypes above a frequency of 0.25. The test was also conduct in targeted regions, where significant SNPs were already found in association analysis. A small subdivision of the population with regard to the geographical origin of the individuals was observed. As a measure of the extent of linkage disequilibrium, r2 was calculated genome-wide for SNP pairs with a distance 5Mb and was on average 0.34. Six selection signatures having a P-value<0.001 were genome-wide detected, located on SSC1, 2, 6 and 17. In targeted regions, it was possible to successfully annotate nine SNPs to core regions. Strong evidence for recent selection was not found in those regions. Three selection signatures with P-value<0.1 were detected on SSC2, 5 and 16. To reduce the costs of genomic selection, selection candidates can be genotyped with an SNP panel of reduced density (384 SNPs). The aim of chapter five was to investigate two strategies for the selection of SNPs to be considered in the above mentioned SNP panel, using 895 progeny tested and genotyped German Piétrain boars. In the first strategy equal spaced SNPs were selected, which were used to impute the high density genotypes. In the second strategy SNPs were selected based on results of association analysis. Direct genomic values were estimated with GBLUP from deregressed estimated breeding values. Accuracies of direct genomic values for the two strategies were obtained from cross validation. A regression approach to correct for the upward bias of the cross validation accuracy of the direct genomic values was used. The first strategy resulted in more accurate direct genomic values. This implies that imputation is beneficial even if only 384 SNPs are genotyped for the selection candidates.
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.
Genomic and microbial analyses of quantitative traits in poultry
(2023) Haas, Valentin Peter; Bennewitz, Jörn
Feed and nutrient efficiency will become increasingly important in poultry production in the coming years. In addition to feed efficiency, particular attention is paid to phosphorus (P) in nonruminants. Especially growing animals have a high demand of P but through the low usability of plant-based P sources for nonruminants, mineral P is added to their feeds. Due to worldwide limited mineral P sources, the high environmental impact of P in excretions and high supplementation costs, a better utilization of P from feed components is required. Animals’ P utilization (PU) is known to be influenced by the host genetics and by gastrointestinal microbiota. The overall aim of this thesis was to investigate the relationships between host genetics, gastrointestinal microbiota composition and quantitative traits with the focus on PU and related traits in F2 cross Japanese quail (Coturnix japonica). Japanese quail represent a model species for agriculturally important poultry species. In Chapter one, a genetic linkage map for 4k genome-wide distributed SNPs in the study design was constructed and quantitative trait loci (QTL) linkage mapping for performance as well as bone ash traits using a multi-marker regression approach was conducted. Several genome-wide significant QTL were mapped, and subsequent single marker association analyses were performed to find trait associated marker within the significant QTL regions. The analyses revealed a polygenic nature of the traits with few significant QTL and many undetectable QTL. Some overlapping QTL regions for different traits were found, which agreed with the genetic correlations between the traits. Potential candidate genes within the discovered QTL regions were identified and discussed. Chapter two provided a new perspective on utilization and efficiency traits by incorporating gastrointestinal microbiota and investigated the links between host genetics, gastrointestinal microbiota and quantitative traits. We demonstrated the host genetic influences on parts of the microbial colonization localized in the ileum by estimating heritabilities and mapping QTL regions. From 59 bacterial genera, 24 showed a significant heritability and six genome-wide significant QTL were found. Structural equation models (SEM) were applied to determine causal relationships between the heritable part of the microbiota and efficiency traits. Furthermore, accuracies of different microbial and genomic trait predictions were compared and a hologenomic selection approach was investigated based on the host genome and the heritable part of the ileum microbiota composition. This chapter confirmed the indirect influence of host genetics via the microbiota composition on the quantitative traits. Chapter three further extended the approaches to identify causalities from chapter two. Bayesian learning algorithms were used to discover causal networks. In this approach, microbial diversity was considered as an additional quantitative trait and analyzed jointly with the efficiency traits in order to model and identify their directional relationships. The detected directional relationships were confirmed using SEM and extended to SEM association analyses to separate total SNP effects on a trait into direct or indirect SNP effects mediated by upstream traits. This chapter showed that up to one half of the total SNP effects on a trait are composed of indirect SNP effects via mediating traits. A method for detecting causal relationships between microbial and efficiency traits was established, allowing separation of direct and indirect SNP effects. Chapter four includes an invited review on the major genetic-statistical studies involving the gut microbiota information of nonruminants. The review discussed the analyses conducted in chapter one to three and places the analyses published in these chapters in the context of other statistical approaches. Chapter four completed the microbial genetic approaches published to date and discussed the potential use of microbial information in poultry and pig breeding. The general discussion includes further results not presented in any of the chapters and discusses the general findings across the chapters.
Genomic methods for rotational crossbreeding in local dairy cattle breeds
(2022) Stock, Joana; Bennewitz, Jörn
Local dairy breeds, such as German Angler, usually have small population sizes and thus a reduced genetic gain, compared to high-yielding breeds. Especially since genomic selection is widely used in the latter, the performance gap between local breeds and high-yielding breeds increased further, as it requires large reference populations in order to achieve accurate estimated breeding values. As a result, many farmers switched to high-yielding breeds. On the other hand, to increase the performance of local breeds the introgression of high-yielding breeds was a common strategy in the past, which resulted in high amounts of foreign genetic material in many of them. Much of the original genetic background got lost, however, they do not achieve the same performance level as high-yielding breeds. Local breeds are therefore faced with the risk of two types of extinction, i.e. a numerical extinction due to the small and decreasing numbers of breeding animals, and a genetic extinction due to massive introgression from high-yielding breeds. To promote local dairy breeds, the implementation of a genomic rotational crossbreeding scheme can be a promising strategy. Local breeds can benefit from a genomic rotational crossbreeding scheme with a high-yielding breed due to 1) an enlarged reference population including both the local breed and crossbred animals, and 2) the increased performance level of crossbred animals. On the other hand, crossbreeding is particularly known to improve functional traits by the exploitation of heterosis. Thus, it appears to be an appealling option for high-yielding breeds, as well, as they tend to struggle with fitness related problems. This thesis aimed to develop genomic methods for numerically small local dairy breeds in crossbreeding schemes in order to improve their genetic gain, genetic uniqueness, and their ability to compete with high-yielding breeds. In Chapter 2 a review study conducted a comparison of different genomic models which are suitable for crossbred data. Different additive models (such as the parental model, a model with breed-specific allele effects, and a single step model) and dominance models, which were either line-dependent, line-independent or included imprinting were discussed. It was concluded that the model choice needs to be made based on desired accuracies, computational possibilities, and data availability. In general, dominance models showed to result in higher accuracies compared to additive models. A breed of origin of alleles model approach was introduced in Chapter 3, which assumes different SNP effects for different origins of haplotypes. This model is suitable for the multi-breed genomic prediction of breeding values of numerically small breeds (i.e. German Angler) that have experienced introgression from high-yielding breeds in the past. The breed of origin of alleles model approach tended to be advantageous for Angler over multi-breed and within-breed genomic predictions with GBLUP. Chapter 4 contains a simulation study about the implementation of a rotational crossbreeding scheme including German Angler x German Holstein, while introducing genomic selection in Angler. Different sizes and structures of growing reference populations and selection goals of Angler were examined. The results showed that crossbred animals had a small overall superiority to both Holstein and Angler populations. In addition, a reference population containing both Angler and crossbred animals, in combination with a selection based on the purebred performance of Angler, gave the highest response to selection in the purebred Angler population and in the crossbred population. The difference between selection methods for Angler individuals could only be observed in the long term, as the purebred-crossbred correlations decreased. In Chapter 5 a simulation study on rotational crossbreeding was performed including different Optimum Contribution Selection methods, in order to realize genetic gain while regaining the original genetic background of Angler. Different constraints regarding mean kinships, native kinships, and migrant contributions from Holstein were applied to investigate their effects on Angler, crossbred, and Holstein populations. Constraining the amount of migrant contribution in Angler increased their genetic uniqueness. However, it led to a notable reduction of genetic gain and thus a reduced superiority of the crossbred animals. The slowed rate of genetic gain and thus the large difference of the performance between the parental breeds could not be compensated by heterosis effects. In Chapter 6 the thesis ends with a general discussion about further genomic models for crossbreeding, and the practical relevance of crossbreeding in dairy cattle.
Genomische und mikrobielle Analysen von Effizienzmerkmalen beim Schwein
(2022) Weishaar, Ramona Ribanna; Bennewitz, Jörn
Most traits in animal breeding, including efficiency traits in pigs, are influenced by many genes with small effect and have moderate heritabilities between 0.1 and 0.5, which enables efficient selection. These so-called quantitative traits are influenced by genetic factors and environmental factors. The use of next-generation sequencing methods, such as 16S rRNA sequencing to analyse the gut microbiome of livestock, allows identification and analysis of the gut microbiota. It has been shown that the composition of the microbiota in the gastrointestinal tract is heritable and has an influence on efficiency traits. Thus, the animal genome influences the phenotype not only directly by altering metabolic pathways, but also indirectly by changing the composition of the microbiota. This increases the interest in implementing gut microbiota into existing breeding strategies as an explanatory variable. The potential of an efficient utilization and absorption of nutrients varies between individuals. Differences in nutrient absorption depend on feed intake, digestion of dietary components in the stomach and intestine, and intake of digested nutrients from the gastrointestinal tract into blood and lymphatic vessels. Undigested nitrogen is excreted as urea and can be detected by blood urea nitrogen (BUN). The BUN is correlated with efficiency traits and there exist differences between pig breeds. Thus, therefore the BUN would be conceivable as an easier recordable trait for nitrogen utilisation efficiency in pig breeding. In the first chapter of this study, an existing data set of the Department for Animal Genetics and Breeding of the University of Hohenheim was used. This is a data set with 207 phenotyped and genotyped Piétrain sows. The relationship between gut microbial composition, efficiency traits and the porcine genome is investigated using quantitative genetic methods. The heritabilities of the traits FVW, RFI, TZ, and FI ranged from 0.11 to 0.47. The microbiabilities of the traits were significant and ranged from 0.16 to 0.45. In a further step, the previously generated microbial animal effects were used as observation vector for a genomic mixed model. Subsequently, heritabilities for the microbial animal effect were estimated, ranging from 0.20 to 0.61. The similarity of the heritabilities and microbiabilities suggests that the traits are influenced to a similar extent by both genetics and gut microbiota and that the microbial animal effect is determined by the host. These results are underlined by the identification of genera and phyla with significant effects on efficiency traits. The microbial architecture of the traits demonstrated a poly-microbial nature, there are many OTUs with small effects involved in the variation of the observed traits. Genomic Best Linear Unbiased Predictions (G-BLUP) and Microbial Best Linear Unbiased Predictions (M-BLUP) were performed to predict complex traits. The accuracies of M-BLUP and G-BLUP were all in a similar range between 0.14-0.41. This shows that gut microbiota could be used to predict performance traits or be included as a variable in the existing models of breeding value estimation to realize an increase in accuracies. The second part of the paper analysed a dataset from a research project called "ProtiPig". The data set included 475 sows and castrates of crossbreds of German Landrace x Piétrain and was analysed for protein utilization efficiency and nitrogen(N)-utilization efficiency. N-utilization efficiency is a trait that is difficult to record. Because conventional metabolic cage methods are a very complex procedure and difficult to integrate in the standard recording, it was tested whether the BUN is suitable as a proxy trait. Moderate to medium heritabilities could be estimated for all traits and ranged from 0.13 to 0.49. The genome-wide association studies showed that the traits were polygenic. For the BUN, SNPs could be detected that were above the genome-wide significance level. Significant genetic and phenotypic correlations were found between some traits. In particular, the heritabilities of BUNs and the significant genetic correlation between BUN and N-utilization efficiency indicate an opportunity to use the BUN to select for improved N-utilization efficiency. Before the research results generated here can be implemented in breeding practice, further questions must be clarified. In addition, a larger number of animals is needed to validate the results. The results presented here demonstrate the potential of microbial-assisted breeding value estimation and the use of BUN to identify selection candidates for breeding for increased efficiency.
Improving the accuracy of multi-breed prediction in admixed populations by accounting for the breed origin of haplotype segments
(2022) Schmid, Markus; Stock, Joana; Bennewitz, Jörn; Wellmann, Robin
Numerically small breeds have often been upgraded with mainstream breeds. This historic introgression predisposes the breeds for joint genomic evaluations with mainstream breeds. The linkage disequilibrium structure differs between breeds. The marker effects of a haplotype segment may, therefore, depend on the breed from which the haplotype segment originates. An appropriate method for genomic evaluation would account for this dependency. This study proposes a method for the computation of genomic breeding values for small admixed breeds that incorporate phenotypic and genomic information from large introgressed breeds by considering the breed origin of alleles (BOA) in the evaluation. The proposed BOA model classifies haplotype segments according to their origins and assumes different but correlated SNP effects for the different origins. The BOA model was compared in a simulation study to conventional within-breed genomic best linear unbiased prediction (GBLUP) and conventional multi-breed GBLUP models. The BOA model outperformed within-breed GBLUP as well as multi-breed GBLUP in most cases.
Investigations on major gene by polygene and gene by environment interaction in German Holstein dairy cattle
(2014) Streit, Melanie; Bennewitz, Jörn
Putative interaction effects between DGAT1 K232A mutation and the polygenic terms (all genes except DGAT1) were investigated in chapter one. This was done for five milk production traits (milk yield, protein yield, fat yield, protein percentage and fat percentage) in the German Holstein dairy cattle population. Therefore, mixed models are used. The test for interaction relied on the comparison of polygenic variance components depending on the sire?s genotypes at DGAT1 K232A. Found substitution effects were highly significant for all traits. Significant interactions between DGAT1 K232A and the polygenic term were found for milk fat and protein percentage. These interactions could be used in breeding schemes. Depending on the DGAT1 K232A genotypes of the sample, in which the sire will be used, three polygenic breeding values of a sire can be calculated. Because the genotypes of the samples are often unknown and usually heterogeneous, this is not a practical approach. Rank correlations between the three polygenic EBVs were always above 0.95, which suggested very little re-ranking. GxE were studied in chapter two. For this, reaction norm random regression sire models were used in the German Holstein dairy cattle population. Around 2300 sires with a minimum of 50 daughters per sire and at minimum seven first-lactation test day observations per daughter were analyzed. As traits, corrected test day records for milk yield, protein yield, fat yield and somatic cell score (SCS) were used. As environmental descriptors, we used herd test day solutions (htds) for milk traits, milk energy yield or SCS. Second-order orthogonal polynomial regressions were applied to the sire effects. Results showed significant slope variances of the reaction norms, which caused a non-constant additive genetic variance across the environmental ranges considered, which pointed to the presence of minor GxE effects. When the environment improved, the additive genetic variance increased, meaning higher (lower) htds for milk traits (SCS). This was also influenced by pure scaling effects, because the non-genetic variance increased in an improved environment and the heritability was less influenced by the environment. For the environmental ranges considered in this study, GxE effects caused very little re-ranking of the sires. To obtain unbiased genetic parameters, it was important to model heterogeneous residual variances. A large genome-wide association analysis was conducted in chapter three to identify SNPs that affect general production (GP) and environmental sensitivity (ES) of milk traits. Around 13 million daughter records were used to calculate sire estimates for GP and ES with help of linear reaction norm models. Daughters were offspring from 2297 sires. The sires were genotyped with a 54k SNP chip. As environmental descriptor, the average milk energy yield performance of the herds at the time where the daughter observations were recorded was used. The sire estimates were used as observations in genome-wide association analyses using 1797 sires. With help of an independent validation set (500 sires of the same population), significant SNPs were confirmed. To separate GxE scaling and other GxE effects, the observations were log-transformed. GxE effects could be found with help of reaction norm models and numerous significant SNPs could be validated for GP and ES, whereas many SNPs affecting GP also affected ES. ES of milk traits is a typical quantitative trait, which is controlled by many genes with small effects and few genes with larger effect. Effects of some SNPs for ES were not removable by log-transformation of observations, indicating that these are not solely scaling effects. Positions of founded clusters were often in well-known candidate regions affecting milk traits. No SNPs, which show effects for GP and ES in opposite directions could be found. Environmental descriptor in GxE analyses is often modelled by average herd milk production levels. Another possibility could be the level of hygiene and udder health. In chapter four, the same models were used as in chapter three. A genome-wide association analysis was done using htds for SCS as an environmental descriptor. With help of this, several SNP clusters affecting intercept and slope could be detected and confirmed. Many SNPs or clusters affecting intercept and slope could be identified, but in total, the number of SNPs affecting intercept was larger. The same SNPs could be detected and validated with and without considering GxE in reaction norm models. Some SNPs affecting only slope were found. For slope, nearly the same SNPs could be found with SCS as an environmental descriptor as presented in chapter three, although both environmental descriptors were only slightly correlated.
Investigations on methodological and strategic aspects of genomic selection in dairy cattle using real and simulated data
(2018) Plieschke, Laura Isabel; Bennewitz, Jörn
In Chapter one a method was developed to separate the genomic relationship matrix into two independent covariance matrices. Here, the base group component describes the covariance that results from systematic differences in allele frequencies between groups at the pedigree base. The remaining segregation component describes the genomic relationship that is corrected for the differences between base populations. To investigate the proposed decomposition three different models were tested on six traits, where the covariance between animals was described either only by the segregation component or by a combination of the two components. An additional variant examining the effect of a fixed modeling of the group effects was included. In total, 7965 genotyped Fleckvieh and 4257 genotyped Brown Swiss and 143 genotyped Original Braunvieh bulls were available for this study. The proposed decomposition of the genomic relationship matrix helped to examine the relative importance of the effects of base groups and segregation component in a given population. It was possible to estimate significant differences between the means of base groups in most cases for both breeds and for the traits analyzed. Analysis of the matrix of base group contributions to the populations investigated revealed several general breed-specific aspects. Comparing the three models, it was concluded that the segregation component is not sufficient to describe the covariance completely. However, it also was found that the model applied has no strong impact on predictive power if the animals used for validation show no differences in their genetic composition with respect to the base groups and if the majority of them have complete pedigrees of sufficient depth. The subject of the chapter two was investigation to systematically increase the reliability of genomic breeding values by integrating cows into the reference population of genomic breeding value estimation. For this purpose a dataset was generated by simulation resembling the German-Austrian dual-purpose Fleckvieh population.. The concept investigated is based on genotyping a fixed number of daughters of each AI bull of the last or last two generation of the reference population and, together with their phenotypic performance, to integrate them into the reference population of the genomic evaluation. Different scenarios with different numbers of daughters per bull were compared. In the base scenario the reference population was made up of 4200 bulls. In the extended scenarios, more and more daughters were gradually integrated in the reference population. The reference population of the most extended scenario contained 4200 bulls and 420,000 cows. It was found that the inclusion of genotypes and phenotypes of female animals can increase the reliabilities genomic breeding values considerably. Changes in validation reliability of 6-54% for a trait with a heritability of 0.4 depending on scenario were found. As the number of daughters increased, the validation reliability increased as well. It should be noted that the composition of the daughter samples had a very great influence on whether the additional genotyped and phenotyped animals in the reference population can have a positive effect on the reliability of genomic breeding values. If pre-selected daughter samples were genotyped, the mean validation reliability decreased significantly compared to a correspondingly large unselected daughter sample. In addition, a higher bias was observable in these cases. Chapter three expands the investigations of chapter two by a low-heritability trait, as well as the aspect of so called new traits. The results found in chapter two were confirmed in chapter three for a low-heritability trait. Changes in validation reliability of 5-21% for a heritability of 0.05 depending on scenario were found. The negative effects of pre-selected daughter samples were even more pronounced in chapter three. In the case of an ‘old’ trait, the number of phenotypes is expected to be (nearly) unlimited, since a recording system is well established. In the case of a new trait recording of phenotypes just started, therefore the number of phenotypes is limited. Two different genotyping strategies were compared for new traits. On the one hand, the sires of the phenotyped cows were genotyped and on the other hand the phenotyped cows were genotyped themselves. It was found in all compared scenarios that it is more sensible to genotype cows themselves instead of the genotyping their sires. However, if usual strategy of phenotyping female animals and genotyping of males is applied, it is at least important to ensure that many daughters are phenotyped in a balanced system. If different numbers of daughters per bull are phenotyped and unbalancedness becomes severe, the average validation reliability decreased significantly.
Is heat stress a growing problem for dairy cattle husbandry in the temperate regions? A case study of Baden-Württemberg in Germany
(2024) Leandro, Miguel António; Stock, Joana; Bennewitz, Jörn; Chagunda, Mizeck G. G.
Heat stress with measurable effects in dairy cattle is a growing concern in temperate regions. Heat stress in temperate regions differs between environments with different geophysical characteristics. Microclimates specific to each environment were found to greatly impact at what level heat stress occurs and will occur in the future. The landlocked state of Baden-Württemberg, Germany, provides several different environments, hence, a good case-study. Temperature–Humidity Index (THI) from 17 weather stations for the years 2003 to 2022 was calculated and milking yields from 22 farms for the years 2017 to 2022 were collected. The occurrences and evolving patterns of heat stress were analyzed with the use of a THI, and the effect of heat stress on milk yield was analyzed based on milking records from Automated Milking Systems. Daily average THI was calculated using hourly readings of relative humidity and ambient temperature, disregarding solar radiation and wind, as all animals were permanently stabled. Based on studies conducted in Baden-Württemberg and neighboring regions, cited ahead in the section of THI, THI = 60 was the threshold for heat stress occurrence. Findings show that the heat stress period varied between stations from 64 to 120 d with THI ≥ 60 in a year. This aligns with yearly and summer averages, also steadily increasing from May to September. The length of the heat stress period was found to increase 1 extra day every year. Extreme weather events such as heat waves did not increase the heat stress period of that year in length but increased the average THI. Milk yield was found to be significantly (α = 0.05) different between counties grouped into different zones according to heat stress severity and rate of increase in daily average THI. Future attempts at managing heat stress on dairy cattle farms in the temperate regions should account for microclimate, as geographical proximity does not mean that the increase in heat stress severity will be the same in the 2 neighboring areas.
Joint QTL analysis of three connected F2-crosses in pigs
(2012) Rückert, Christine; Bennewitz, Jörn
Mapping Quantitative Trait Loci (QTL) has received considerable attention in livestock genetic research over the last two decades. Knowledge of the location, the mode of inheritance and the size of effects of QTL contribute to a deeper understanding of the genetic architecture of quantitative or complex traits. Furthermore, mapped QTL were envisaged for use in so-called marker assisted selection programs. Before the era of genomics started, microsatellites were usually used as genetic markers for QTL mapping. In pigs, F2-crosses were frequently established from divergently selected founder breeds. Usually, the sizes of these F2-experiments are in the range of 300 individuals, which is too small to obtain sufficient statistical power to map QTL precisely. One large F2-experiment was set up in the 90th of the last century at the University of Hohenheim. Three F2-crosses from three genetically different founder breeds (Meishan, Pietrain and European Wild Boar) with almost 1000 individuals were genotyped and phenotyped for around 50 quantitative traits. In further studies, each of the crosses were analysed separately and more complex modes of inheritance were ignored. However, several researchers showed that a combined analysis with several QTL experiments can boost statistical power. Additionally, the mode of inheritance is sometimes not restricted to additive and dominant gene action. The overall aim of this thesis was the joint analysis of these three F2-crosses with more appropriate statistical models and to draw more precise conclusions about the QTL segregating within these experimental designs.
Optimization strategies to adapt sheep breeding programs to pasture-based production environments: A simulation study
(2023) Martin, Rebecca; Pook, Torsten; Bennewitz, Jörn; Schmid, Markus
Strong differences between the selection (indoor fattening) and production environment (pasture fattening) are expected to reduce genetic gain due to possible genotype-by-environment interactions (G × E). To investigate how to adapt a sheep breeding program to a pasture-based production environment, different scenarios were simulated for the German Merino sheep population using the R package Modular Breeding Program Simulator (MoBPS). All relevant selection steps and a multivariate pedigree-based BLUP breeding value estimation were included. The reference scenario included progeny testing at stations to evaluate the fattening performance and carcass traits. It was compared to alternative scenarios varying in the progeny testing scheme for fattening traits (station and/or field). The total merit index (TMI) set pasture-based lamb fattening as a breeding goal, i.e., field fattening traits were weighted. Regarding the TMI, the scenario with progeny testing both in the field and on station led to a significant increase in genetic gain compared with the reference scenario. Regarding fattening traits, genetic gain was significantly increased in the alternative scenarios in which field progeny testing was performed. In the presence of G × E, the study showed that the selection environment should match the production environment (pasture) to avoid losses in genetic gain. As most breeding goals also contain traits not recordable in field testing, the combination of both field and station testing is required to maximize genetic gain.
Pedigreeanalysen zur Beschreibung der populations- und quantitativgenetischen Situation von baden-württembergischen Lokalrinderrassen
(2014) Hartwig, Sonja; Bennewitz, Jörn
The challenge of a conservation breeding program is to solve a conflict of goals: genetic variability and genetic autonomy should be maintained, and on time a certain amount of breeding progress has to be realized to ensure the ability to compete. The aim of the present study was to analyse the situation concerning the targets mentioned above for traditional cattle breeds of Baden-Württemberg. Furthermore, methods for the consolidation and development of these breeds should be reconsidered. In chapter 1 the organisation of a breeding program for small cattle breeds is discussed. The challenge of such a program is the conservation of agrobiodiversity, culture and traditions and the progress of traditional local breeds. Number and extend of these breeds declined due to the increasing popularity of high-yielding breeds. Additionally, some of the local breeds are used in different branches of production compared to their original usage. Breeding programs have to be fitted. The establishment of individual adapted breeding methods is required for a sophisticated solution of the conflict mentioned above. Federal support is requested. Nowadays the implementation of genomic selection is not yet practicable for small breeds. But future opportunities should be analysed. The establishment of performance tests concerning breed specific product and efforts is demanded to improve these characteristics. In the following genetic variability of Vorderwald, Hinterwald and Limpurg cattle was examined. In chapter 2 for each breed two reference populations were defined that enable to observe the development over the years. Animals within the reference population comply with restrictions concerning racial origin and completeness of pedigree. Effective population size and the effective number of founders, and ancestors were estimated. The interpretation of the results was done with regard to the history of the breeds. The absolute population size of Vorderwald cattle is the biggest one. The number of Hinterwald cattle is intermediate; Limpurg cattle have the smallest population size. Whereas the management of Hinterwald cattle seemed to maintain genetic variability, the management of Vorderwald cattle was not that target-orientated. With an effective population size greater than 100 there is enough genetic variability within Vorderwald and Hinterwald. In contrast the values of Limpurg cattle are too low. Besides genetic variability, genetic autonomy and breeding progress are the targets of a conservation breeding program. Cross-breeding was carried out to mitigate the risk of inbreeding depression and to improve the performance of local breeds. However, breeding activities for local breeds were not as intensive and target oriented as for popular high yielding breeds. While the gap between the performance of high-yielding and local breeds increase, genetic autonomy of local breeds declined due to migrant influences. Chapter 3 examined the importance of migrant breed influences for the realization of breeding progress of beef traits of Vorderwald and Hinterwald cattle. The results show that there is a high amount of migrant contributions and their effects on performance are substantial for most traits. Breeding values adjusted for the effects of the migrant breeds showed little genetic trend for beef traits. The subject of chapter 4 is the development of milk yield and the associated migrant influences. Yield deviations for milk, fat, and protein content were analysed. Migrant contributions to Vorderwald cattle were high and even rose in the latest past. All the effects of foreign breeds were positive and in most cases highly significant. Most influential breed was Montbéliard. The influences of migrant breeds were substantial for the development of milk performance. However, the trend of milk yield traits for both breeds was positive even without foreign breeds’ influences. In comparison the number of analysed Hinterwald cows was small due to the reason that just a few Hinterwald husbandries take part at the official milk performance recording. Migrant breed contributions were moderate and nearly constant over the time. The most influential migrant breed was the Vorderwald cattle. The development of milk yield shows a flat trend. Influences of migrant breeds were low. The thesis ends with a general discussion.
Phenotypic and genetic analysis of meat production traits in German Merinoland purebred and crossbred lambs
(2016) Schiller, Katja; Bennewitz, Jörn
The overall aims of the present thesis were to investigate various meat quality (MQ) traits including branched chain fatty acids and their correlation to sensory traits and to perform DNA-based and quantitative genetic analysis for growth, carcass and MQ traits using the data set with about 1600 phenotyped lambs. The lambs were Merinoland (ML) lambs and lambs of five crossbreds of meat type sire breeds and Merinoland ewes. The crosses were CH (Charollais × ML), IF (Ile de France × ML), SK (German black-headed mutton sheep (BHM) × ML), SU (Suffolk × ML) and TX (Texel × ML). In chapter one, growth curves, daily gain and feed conversion of ML sheep and the five ML crosses were investigated via mixed linear models. Linear and Gompertz models were fitted and the quality of fit was assessed. Differences in the model parameters were detected between crosses, genders and birth types. According to the parameters, coefficient of determination and mean square error, the Gompertz provided a better fit compared to the linear model. Additionally feed conversion rate and daily gain were observed, with only the crosses IF and TX showing significant superiority in these traits compared to purebred ML. For practical reasons, however, the common trait daily gain can be recommended to use for breeding purpose, despite if altering the shape of a growth curve is attractive because of e.g. possible lower maintenance costs for a flock. In chapter two, lamb meat and fat of the crosses and ML was investigated for concentration of three branched chain fatty acids (4-Me8:0, 4-ET8:0 and 4-Me9:0) and its correlation to sensory abnormality. Differences between crosses and between sexes were determined, but no significant correlations to sensory traits were found. In chapters three to five, genetic background and genetic parameters were investigated and a chromosome-wide association study imputing SNP panels was undertaken. Furthermore, the possibilities of implementation of this data to improve breeding programs were discussed. Chapter three focuses on genetic parameters of growth, carcass and MQ traits in purebred ML and crossbred lambs. A series of analyses for twelve traits were performed and heritabilities and genetic correlations were estimated using general linear mixed models. Several significant correlations and low to moderate heritabilities were found, indicating that selection on these traits is possible. In chapter four, a targeted association mapping was undertaken with about 330 SNPs using two different statistical models, one with estimation of SNP effects across all crosses and the other with SNP effects per cross. The investigated traits were growth, carcass and MQ traits. In this connection, several weak significant SNPs were revealed. In chapter five, F1 lambs were genotyped on selected chromosomes with a very low SNP panel and imputed via Illumina Ovine 50k SNP BeadChip genotypes from the sires and purebred ML. These were included in a haplotype bibliography before. Furthermore, chromosome-wise association analyses using single marker mixed linear models were performed for MQ, carcass, and growth traits. This was done using the imputed genotypes and the trait phenotypes. Several significant associations were detected, e.g. for the traits shoulder width and cutlet area, and these were discussed with regard to other literature reports as well as their use for practical breeding purpose. The thesis ends with a general discussion.
Potential for quantifying general environmental resilience of dairy cattle in sub-Saharan Africa using deviations in milk yield
(2023) Oloo, Richard D.; Mrode, Raphael; Bennewitz, Jörn; Ekine-Dzivenu, Chinyere C.; Ojango, Julie M. K.; Gebreyohanes, Gebregziabher; Mwai, Okeyo A.; Chagunda, Mizeck G. G.
Introduction: Genetic improvement of general resilience of dairy cattle is deemed as a part of the solution to low dairy productivity and poor cattle adaptability in sub-Saharan Africa (SSA). While indicators of general resilience have been proposed and evaluated in other regions, their applicability in SSA remains unexplored. This study sought to test the viability of utilizing log-transformed variance (LnVar), autocorrelation (rauto), and skewness (Skew) of deviations in milk yield as indicators of general resilience of dairy cows performing in the tropical environment of Kenya. Methods: Test-day milk yield records of 2,670 first-parity cows performing in three distinct agroecological zones of Kenya were used. To predict expected milk yield, quantile regression was used to model lactation curve for each cow. Subsequently, resilience indicators were defined based on actual and standardized deviations of observed milk yield from the expected milk yield. The genetic parameters of these indicators were estimated, and their associations with longevity and average test-day milk yield were examined. Results: All indicators were heritable except skewness of actual and standardized deviation. The log-transformed variance of actual (LnVar1) and standardized (LnVar2) deviations had the highest heritabilities of 0.19 ± 0.04 and 0.17 ± 0.04, respectively. Auto-correlation of actual (rauto1) and standardized (rauto2) deviations had heritabilities of 0.05 ± 0.03 and 0.07 ± 0.03, respectively. Weak to moderate genetic correlations were observed among resilience indicators. Both rauto and Skew indicators had negligible genetic correlations with both longevity and average test-day milk yield. LnVar1 and LnVar2 were genetically associated with better longevity (rg = −0.47 ± 0.26 and −0.49 ± 0.26, respectively). Whereas LnVar1 suggested that resilient animals produce lower average test-day milk yield, LnVar2 revealed a genetic association between resilience and higher average test-day milk yield. Discussion: Log transformed variance of deviations in milk yield holds a significant potential as a robust resilience indicator for dairy animals performing in SSA. Moreover, standardized as opposed to actual deviations should be employed in defining resilience indicators because the resultant indicator does not inaccurately infer that low-producing animals are inherently resilient. This study offers an opportunity for enhancing the productivity of dairy cattle performing in SSA through selective breeding for resilience to environmental stressors.

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