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Application of random regression and genomic models to study growth curves in UK beef cattle and sheep and estimate Genotype x Environment interactions

  • Full or part time
  • Application Deadline
    Friday, February 07, 2020
  • 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 populations but these models are inadequate in modelling the growth curves of animals when multiple weight records have been taken over the life of the animal. This project involves modelling growth curves of UK beef and sheep breeds using body weight from birth to 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 trait 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 carcasses. 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 abattoirs to evaluate the economic aspects of different carcasses 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 will have worked previously with animal breeding data, and have some knowledge of software for variance component analysis and breeding value estimation. The student will work closely with members of EGENES and will gain from the considerable experience that exists there. Experience of working with genotypic data would be an added advantage. The candidate should hold a good bachelors 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 2020 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 for a PhD at the University of Edinburgh and receive an annual student stipend (£15,009 at the 2020/21 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 the 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)

Click here to see the results for all UK universities

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