Browsing by Person "Haas, Valentin Peter"

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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.