Are you looking for a PhD and interested in animal breeding? Then, this PhD vacancy may be of interest to you.
PhD position combining high dimensional data for the genomic prediction of methane emissions.
Wageningen University & Research’s Animal Breeding and Genomics group leads the Global Methane Genetics (GMG) initiative in collaboration with the Global Methane Hub and the Bezos Earth Fund. The global program with more than 50 partners across 25 countries aims to accelerate genetic progress in methane emission in ruminants in the Global North and South. The PhD will work in an international setting, and their work will be critical to underpin the success of this initiative.
Operating animal breeding programs is a complex task and outcomes of a certain decision in practice often becoming apparent only after several years. Therefore, effective and long-term breeding programs require reliable insights in the consequence of selection. One of the key elements is the estimation of breeding values for individual animals, combining phenotypes, pedigree and DNA information. Breeding values allow breeders to rank the animals and subsequently select the best animals to breed the next generation.
Next to the rapid increase of DNA information and its use in genetic evaluations, the dimensionality and complexity of genetic evaluations are expanding rapidly. For example, for methane emission different recording techniques might be used, records might be collected at different biological stages or in different environments, and highly dimensional indicator traits, like microbiome or mid infra-red measurements, might be available. In the ideal world, the quantitative genetic framework will used to analyse all traits simultaneously and using the correct variance components, such that all available information can be optimised in genetic evaluations and breeding program design.
However, estimation of many (co)variance components and the combination of a small dataset with many traits is giving estimation problems. More parsimonious models are required For example, factor analytical models might provide a solution to estimate variance components using rank reduction to reduce dimensionality of the available datasets.
As a PhD student, you will work on:
- using (inter-)national datasets of different cattle breeds to estimate variance components between different traits, including methane emissions at different biological stages and in different environments, and including high-dimensional microbiome data;
- investigating the accuracy of estimation the variance component and the robustness of factor analytical models;
- contributing to the development of variance component estimation software;
- translating methodological developments into practical insights for breeding organizations and stakeholders.
Your other duties and responsibilities include:
- communicating and disseminating results through presentations at scientific conferences and by writing scientific articles and a PhD thesis;
- attending PhD courses as part of the graduate education program.