Browsing by Person "Weishaar, Ramona Ribanna"

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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.