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dc.contributor.advisor Simianer, Henner Prof. Dr.
dc.contributor.author Ha, Ngoc-Thuy
dc.date.accessioned 2016-12-12T10:49:38Z
dc.date.available 2016-12-12T10:49:38Z
dc.date.issued 2016-12-12
dc.identifier.uri http://hdl.handle.net/11858/00-1735-0000-002B-7CD6-3
dc.language.iso eng de
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.ddc 630 de
dc.title Lost in Transition - Genetic, Transcriptomic and Breeding Aspects of Metabolic Robustness in Dairy Cows de
dc.type cumulativeThesis de
dc.contributor.referee Simianer, Henner Prof. Dr.
dc.date.examination 2016-06-23
dc.description.abstracteng The transition phase of dairy cows is marked by severe metabolic stress resulting from a discrepancy of a high energy demand for rapidly increasing milk production and limited feed intake. Here, a failure in metabolic adaptation results in an increased susceptibility to health problems. However, even under the same environmental factors and production lev-el, the variability of how each cow deals with metabolic load is substantial, leading to the hypothesis that there might be an underlying genetic basis. The main goal of this thesis is to study this genetic basis from different points of view. In chapter 2, we studied the genetic basis of the metabolic adaptation by means of auxilia-ry phenotypes best characterizing the adaptive process. Blood samples were taken from 178 cows at three critical stages: T1 = week 3 ante-partum (no metabolic load); T2 = week 4 post-partum (lactating and high metabolic load), and T3 = week 13 post-partum (lactating and low metabolic load). Plasma concentrations of non-esterified fatty acids (NEFA), beta-hydroxybutyrate (BHBA) and glucose – metabolites characterizing the metabolic status and adaptability – were measured at T1, T2, and T3. All cows were genotyped with the Illumina HD Bovine BeadChip. After quality control, the remaining 601,455 SNPs were annotated to genes (Ensembl) and pathways (KEGG). For each gene and phenotype, we performed a modified score test based on a linear regression model with all SNPs in the gene as explanatory variables, while taking into account possible environmental or breed effects. The results were used to identify pathways enriched for significant genes using a weighted Kolmogorov-Smirnov test. We found 99 genes significantly associated with the three metabolites. For each metabolite, we found genes that are significant at T2 but not at T1 and T3 or vice versa. This strongly suggests those genes to be involved in the adaptive regulation. We further identified three pathways (‘steroid hormone biosynthesis’, ‘ether lipid metabolism’ and ‘glycerophospholipid metabolism’) jointly affecting the metabolites. Even though NEFA, BHBA and glucose are important metabolites describing the metabol-ic adaptation, they may not be fully indicative for the whole process. In order to obtain a more complete picture of the metabolic adaptation, in chapter 3 we conducted a whole transcriptome analysis of the liver, since it is the key organ controlling and regulating the metabolic adaptation. Liver samples were taken from 6 cows at 3 time-points: T1 = week 3 ante-partum; T2 = week 2 post-partum; T3 = week 3 post-partum. Using RNA-seq, we studied the transcriptomic profile of the transition cow before and after lactation. We per-formed a differential gene expression analysis (DGE) and a combination of the gene-set enrichment analysis and perturbation analysis for pathways (KEGG database). Among the ~10,000 expressed genes, we discovered ~1,000 genes to be significantly differentially expressed (FDR < 5%), of which ~43% and ~16% are linked to lipids and oxidative stress, respectively, but only ~6% to the glucose metabolism (GO database). The combined path-way analysis further revealed seven pathways to be significantly associated with the hepat-ic changes of the transition cow, including ‘adipocytokine signaling pathway’ and ‘steroid hormone biosynthesis’. The DGE and pathway analysis demonstrated that major hepatic changes from late pregnancy to early lactation relate to gluconeogenesis and fat mobiliza-tion (‘adipocytokine signaling pathway’). We further found indications for immunological changes (GPX3, ‘steroid hormone biosynthesis’ and the associated CYP and UGT tran-scripts) that may contribute to the impaired immune system of dairy cows during the tran-sition period. The outcome of this study provides new insights into the metabolic adapta-tion which should be more closely investigated in future studies. The main results of chapter 2 and chapter 3 indicate the possible existence of a genetic component of the metabolic adaptation. In other words, whether a cow is able to adapt successfully or not may be partly determined by her genetic set up. Therefore, in chapter 4, we hypothesize that some cows are genetically less well suited to cope with this metabolic stress than others, leading to adverse follow-up effects on longevity. We thus designed a reaction norm sire model linking the functional lifetime to the metabolic challenge in early lactation. To this end, we used either the sum of the milk yield or the accumulated fat/protein ratio of the first three test days to define a measure for metabolic load that a cow has to face during her early lactation. To assess the genetic merit and heritability of the metabolic adaptability, we defined a pedigree-based random regression sire model, in which a random regression term was estimated for each sire to reflect the genetic compo-nent of the reaction to the challenge. The model was fitted to data of ~580,000 daughters of ~5,000 Brown Swiss bulls with at least 10 daughters with records. We found the sire variance for the slope of the random regression to be significantly different from zero for both challenge variables, suggesting a genetic component for the ability to cope with metabolic stress. The results of the study show that the ability to cope with metabolic stress in the transition phase clearly has a genetic component and could be used to breed metabolically robust dairy cows. In conclusion, by assessing the genetic basis of the metabolic adaptation from a genetic, transcriptomic as well as a breeding point of view, we found strong evidence supporting this hypothesis. Despite the high complexity of metabolic adaption, we found several ge-netic factors affecting the adaptability even across different studies. The identified factors as well as the newly developed measure for the metabolic robustness are not only a valua-ble contribution to the understanding of the transition cow, but an effective tool for the dairy industry to breed for metabolically robust dairy cows. de
dc.contributor.coReferee Schlather, Martin Prof. Dr.
dc.contributor.thirdReferee Kneib, Thomas Prof. Dr.
dc.subject.eng transition cow de
dc.subject.eng early lactation de
dc.subject.eng gwas de
dc.subject.eng reaction norm model de
dc.subject.eng rna seq de
dc.identifier.urn urn:nbn:de:gbv:7-11858/00-1735-0000-002B-7CD6-3-5
dc.affiliation.institute Fakultät für Agrarwissenschaften de
dc.subject.gokfull Land- und Forstwirtschaft (PPN621302791) de
dc.identifier.ppn 874354684

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