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Use of random regression for optimum modelling of growth curves for body weight in UK beef cattle and sheep and estimation of Genotype x Environment interactions

  • Full or part time
  • Application Deadline
    Thursday, June 20, 2019
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Currently multivariate systems are utilized for the computation of breeding values in the UK national Beef and Sheep herds but these models are inadequate in modelling the growth curves of animals. This project therefore involves modelling growth curves of UK beef and sheep breeds using body weight from birth to yearly or market age using random regression models (RRM) with various parametric and non-parametric functions. The study will also examine the genetic relationship between growth curve parameters for body weight traits and carcass traits data and formulate prediction equations for various carcass traits, with the objective of identifying the best weight and age combinations that maximize the economic value of carcass traits. For breeds such as the Limousin with genotypic data, a single step genomic random regression model will be examined. This study will also utilise the data from the Ramcompare project using reaction norms to model genotype x environment interactions. The application of RRM analysis for the analysis of growth data will enable the use of data from abattoir to evaluate the economic aspects of different carcass from different weights, age and carcass measurement combinations. Consequently the RRM could lead to optimising the economic returns to Beef and Sheep farmers in the UK through optimising the age and weight combinations at slaughter.

The studentship will involve working with large data sets and genetic models, particularly random regression models. It is expected that the candidate have worked previously with animal breeding data, and have some knowledge of software for variance component
analysis and breeding value estimation. Experience of working with genotypic data would be an added advantage. The candidate should hold a good bachelor degree in agriculture or animal sciences or a related subject, or hold a Master’s degree in animal breeding and genetics.
The expected start date is 1st of October 2019 and the candidate may be required to attend elements of the MSc course on Quantitative Genetics and Genome Analysis Programme at the University of Edinburgh, depending on experience. The student will be based at the SRUC research facility at the Roslin Institute Building, at Easter Bush near Edinburgh.

Funding Notes

The successful student will be registered at for a PhD at the University of Edinburgh) and receive an annual student stipend (£15,009 (2019/20 rate). The studentship will fund the tuition fees at the UK home fees rate only. International students must provide evidence of sufficient funds to cover the higher international student tuition fee level (approximately £17,873 per year would be required). This studentship will be based at SRUC but the student will spend up to 6 months during the PhD at AHDB offices in Warwickshire developing skills for the application of genetics in the field.

How good is research at SRUC - Scotland’s Rural College in Agriculture, Veterinary and Food Science?
(joint submission with University of Edinburgh)

FTE Category A staff submitted: 57.37

Research output data provided by the Research Excellence Framework (REF)

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