Animal Science, Department of
First Advisor
Matthew L. Spangler
Committee Members
Samodha Fernando, Reka Howard, Warren Snelling
Date of this Version
12-2024
Document Type
Thesis
Citation
A dissertation presented to the faculty of the Graduate College at the University of Nebraska in partial fulfillment of the requirements for the degree of Doctor of Philosophy
Major: Animal Science
Under the supervision of Professor Matthew L. Spangler
Lincoln, Nebraska, December 2024
Abstract
As sequencing technology becomes more affordable and throughput increases, microbiome information is becoming more readily available. For beef cattle selection, microbial information has a variety of uses including being a target for genetic prediction or used as a means to explicitly describe additional phenotypic variability in other traits.
Infectious bovine keratoconjunctivitis (IBK), commonly known as pinkeye, is a disease that infects the ocular surface and surrounding tissue which is an animal health and producer economic concern. Vaccinations have shown to have variable effectiveness, while limited genetics studies have suggested that direct genetic selection for resistance would be slow. Therefore, an investigation into the host genetic component of the ocular microbiome was conducted. Ocular microbiome samples were taken on pre-weaned beef calves at four time points. Diversity metrics demonstrated non-zero heritability estimates at multiple time points. The relative abundances of a portion of the total ocular were influenced by host genetics at various sampling times. A small collection of microbes with relationships to IBK have moderate to high heritability estimates at multiple sampling time points. This indicates selection for reduced pathogen load is possible.
Metagenomic sequencing is the process of extracting all the genetic information from a given sample. Most metagenomic studies remove any host reads as a matter of course. However, host reads can be used as the basis for genotype imputation to obtain whole genomic sequences. The accuracy of these imputed genotypic calls was tested using a commercial genotype array. Overall, imputed genotype calls proved to have a high concordance with array genotype calls. Accuracy increased as filters for host read depth and imputed call confidence were implemented. Further, identity verification of the metagenomic samples can be carried out if the host is genotyped on another platform.
The bovine rumen contains millions of unique microbial genes. A few studies have shown the abundance of these genes to be influenced by host genetics. Yet, those studies were either limited by sample size or a carefully curated set of microbial genes. This study examined the abundance of 16,583 microbial genes from over 700 animals on differing diets. Over 50% of the rumen microbial genes had nonzero heritability estimates and more than 10% had heritability estimates greater than 0.20. Some highly heritable rumen microbial genes had genetic correlations with production traits, which provides selection candidates to increase efficiency. Multiple host genes were associated with microbial gene abundance with the majority of host gene functionality classified generally as either immune-related, metabolism-related, or possibly involved in host-microbiome cross talk.
Phenotypic prediction can be useful for management decisions. The average daily gain (ADG) and average daily dry matter intake (ADDMI) of 717 animals was predicted using host genomic information, rumen microbiome information, or some combination thereof. Predictions were most accurate when multiple sources of information were used. Although minimal, differences existed in parameter estimates and validation accuracy depending on how the microbial effect was modelled.
Advisor: Matthew L. Spangler
Comments
Copyright 2024, Andrew D. Lakamp. Used by permission