Highlander Lab

Daniel Tolhurst

PhD student

Research at the Highlander Lab

Highlander Daniel

Implementing efficient linear mixed model approaches for global plant breeding programmes.

Main goals:

  • Integrated factor analytic linear mixed model (IFA-LMM) for plant breeding multi-environment trial (MET) data which includes environmental stress covariates
  • Additive and dominance genomic relationship matrices (GRMs) which account for the non-random mating (inbreeding) inherent to plant breeding populations
  • Genomic prediction of general and specific combining ability in hybrid breeding programmes in the presence of genotype by environment (GxE) interaction
  • Efficient computation of the IFA-LMM for global breeding data in real time


I have a strong theoretical and practical background in applied statistics, biometrics and quantitative genetics. Prior to moving to Edinburgh, I held a research position under Professor Brian Cullis and Dr Alison Smith at The University of Wollongong, Australia, with major projects for the Australian Grains Industry and Department of Fisheries. I am now undertaking a PhD at the Roslin Institute to implement efficient linear mixed model approaches in their global breeding pipeline.

I am specifically interested in:

  • Linear mixed models
  • Variance parameter estimation
  • Partitioning genetic variation                          
  • Hybrid breeding
  • Experimental design                                                            

Programming language and software:

  • R and Rstudio                                                         
  • LaTeX, knitr
  • R Shiny