Gorjanc, Gregor

Prendergast, James

Mafra Fortuna, Gabriela

Biotechnology and Biological Sciences Research Council (BBSRC)

Genus ABS

EASTBIO BBSRC Doctoral Training Partnership

2026-05-26T14:49:22Z

2026-05-26

Dairy production plays a crucial role in addressing food insecurity and poverty in tropical regions by providing high-value protein and generating income for millions of smallholder farmers. It also empowers women and girls, strengthening rural communi- ties, and contributing to sustainable economic development. Tropical dairy production commonly relies on crossbreeding environmentally-adapted local Bos indicus (indicine) breeds with high-yielding exotic breeds, usually from Bos taurus (taurine) origin. This strategy aims to increase productivity by leveraging breed complementarity and heterosis. However, crossbred performance is highly variable, to the point of instability. This instability undermines the success of crossbreeding by posing short-term challenges to production management and long-term challenges to the optimisation of selective breeding. This thesis explores three fundamental aspects behind the challenges of tropical cross- breeding strategies: (i) the genetic distance between environmentally-adapted local breeds and high-yielding exotic breeds, (ii) the lack of statistical methods tailored to dealing with such genetic distance, and (iii) the genotype-by-environment (G×E) interaction that underlies the instability in crossbred performance across environments. These fundamental aspects address the long-standing objective of breeders to effectively utilise genetic variation in tropical dairy breeding. The work presented here seeks to introduce novel methods for uncovering and leveraging the genetic variation available in tropical dairy systems. The thesis is structured as follows. Chapter 1 provides a review of the evolutionary and breeding history of cattle. It outlines the origins of genetic divergence between populations adapted to the tropical climates of the Global South and those favoured in the Global North. The chapter also introduces the concepts of Ancestral Recombination Graphs (ARG) and multiplicative models; two methodological approaches used throughout the thesis to analyse genetic diversity, the effects of genetic diversity on phenotypic performance, and the effects of G×E interaction. Particular focus is paid to the inherent differences between pedigree and genomic-based models, and the benefits of ARG-based inference. The chapter concludes by stating the research objectives and the thesis structure. Chapter 2 investigates global patterns of genetic diversity and population structure in cattle. This chapter demonstrates how the fast-evolving field of ARG reconstruction can benefit livestock genomics, providing an information-rich new format for storing and analysing genomic data. The results show that tree-sequence-based ARGs capture fine-scale population structure across cattle populations worldwide. In particular, local ancestry inference with ARGs enables the assignment of breed-of-origin that can inform crossbred genomic evaluation, especially in contexts of complex ancestry composition. Chapter 3 introduces a novel ARG-based statistical model for estimating haplotype and ancestry-specific mutation effects considering the genome sequence context. The genomic distance between indicine and taurine cattle breeds underlies variation in their adaptation and performance. The distinct selective pressures experienced by these populations over time have shaped the genomic context in which mutations occur, resulting in ancestry-specific mutations and their effects. These differences limit the predictive accuracy of crossbreeding and multi-breed genetic evaluations, as current methods often assume mutations and their effects are shared across populations. By capturing the historical recombination, mutation, and coalescence processes that shape genetic variation, ARGs offer a biologically informed basis for modelling mutation effects. The proposed model, initially developed for a single, non-recombining genomic region, achieves predictive accuracy comparable to standard SNP-based approaches while reducing computational demands and providing additional biological insights. This work lays the foundation for future expansion to more complex scenarios including multiple recombining regions. Another limitation addressed in this thesis is the instability of crossbred performance across environments arising from G×E interaction, which is often ignored in tropical dairy systems. G×E interaction reflects the variable genotype performance between environments, and when not managed, reduces the predictability of the deviation in trait expression. This phenomenon increases genetic variance and alters genotype ranking across environments, hindering the optimisation of production. Chapter 4 develops a novel framework for decomposing genetic variance that exposes the variation due to G×E interaction. The framework leverages a rotated multiplicative model and subsequent visualisation approaches commonly used in plant breeding but rarely explored by animal breeders. The outputs of this analysis express the genetic variance in a way that is more accessible and actionable for breeding decisions, providing the means to identify broadly and specifically adapted individuals. Using stochastic simulations, the chapter demonstrates how G×E interaction affects crossbreeding outcomes and how adaptability patterns of underutilised genetic diversity in the exotic population can improve crossbreeding responses to specific environments. This result indicates that the correlation between environments secures genetic resources despite different breeding objectives in these environments. The chapter serves as a recommendation on how to apply the framework to inform breeding decisions, focusing on leveraging useful genetic diversity to produce crossbred that are stable yet responsive to changes in environment. Overall, my thesis introduces new methodologies to the context of dairy breeding that contribute to the analysis and understanding of genetic diversity and provides practical tools for uncovering useful genetic variation and analysing its effect on adaptation and performance in tropical environments. Chapter 5 provides a general discussion of the opportunities and challenges for future work in tropical dairy breeding.

https://era.ed.ac.uk/handle/1842/44749

https://doi.org/10.7488/era/7264

en

The University of Edinburgh. Royal (Dick) School of Veterinary Studies

C​r​e​a​t​i​v​e ​C​o​m​m​o​n​s: ​Attribution-NonCommercial-NoDerivatives 4.0 International (​CC BY-NC-ND 4.0)

https://creativecommons.org/licenses/by-nc-nd/4.0/

Dairy cattle breeding

Genetic diversity

Genotype by environment interaction

Ancestral Recombination Graphs

Methods for utilising genomic diversity in tropical dairy breeding

Thesis

Doctoral

PhD Doctor of Philosophy