Abstract
Deer are versatile animals that display large amounts of genetic diversity. Deer are a vital agricultural species, with approximately $332 million NZD of product exported annually from New Zealand alone. However, deer are understudied compared to other ruminant species. The Rumen microbial composition (RMC) is a key area of focus for current ruminant studies, an area that has not been examined in deer. Deer thrive in a broad range of environments and across a variety of diets compared to other ruminant species. Therefore, it is likely that deer will have a different RMC, which may affect other important physiological traits to the deer industry. This thesis set out to explore the deer RMC, and how it may be used to improve selection of key economic traits. The first three chapters provide coverage of the current literature surrounding deer and the RMC, as well as the methods and materials used in this thesis. Chapters 4 to Chapter 7 of this thesis contain the main analysis of the deer RMC.
Chapter 4 explores the deer RMC. The heritability of the deer RMC was calculated and found to range from 0.22 ± 0.085 to 0.75 ± 0.066 across three different standardisation methods. The heritability of growth and seasonality traits were moderate to high (0.36 ± 0.089 to 0.61 ±0.086), and the microbiability (trait variation explained by the RMC) of the same traits were mostly moderate (around 0.1). The heritability and microbiability were reflected in the mean correlation between predicted and expected values (accuracy of breeding and microbial values) of the trait.
Chapter 5 compares the deer RMC to that of other ruminants. Ruminant species have similar RMCs, where the most abundant genera are similarly abundant across all species. Deer are most dissimilar from goats and sheep, though all show significant heritability of the RMC across standardisation methods. The RMC was consistently predictive of liveweight, however, was not as predictive as the host genome. The prediction models for liveweight also indicated a more complicated relationship between the RMC and host genome; indicating that prediction of traits with RMC across all species need to employ more robust models.
Chapter 6 examines the prediction of methane emission levels across ruminant species and sequencing methods. The methods used for quantifying microbe abundance can drastically change the data, where microbial functional data cannot be used to accurately compare RMC profiles or predict methane at this time. The RMC displayed a core RMC shared across sheep cattle and deer, where deer were not as different as hypothesised. The RMC of high and low methane sheep were very different. Cattle methane level was unable to be accurately predicted based on RMC variations displayed in high and low methane sheep. This was likely due to low number of individuals and limitations of the model used. However, prediction of methane groups across species may be possible in the future, which is vital for the deer industry as deer are difficult to measure for methane.
Chapter 7 investigates regions of the host genome associated with the RMC in deer and sheep. The results of genome wide association analyses indicated that the deer RMC is influenced by immune pathways, while the sheep RMC appears to be influenced by cell cycle pathways. The RMC and liveweight are both polygenic traits that are affected by many low effect SNPs throughout the host genome. Further studies with additional individuals are needed to identify significant regions of the host genome influencing the RMC across species.
In summary, the deer RMC was found to be heritable and exhibit core similarities to the ruminant RMC with some species-specific differences. The RMC is a useful biological component which, in combination with the host genome, can be used to predict traits such as growth, liveweight and methane, and acts as a vital tool to improving genomic selection for deer. The deer RMC is influenced by immune pathways, a factor that may be exploited to further genetic gain. The findings here are an important contribution to deer genomic research, catching the deer industry up to current agricultural developments.