Centre for Animal Science - Summer Research Programs

Primary Supervisors: 

Dr Natasha Hungerford | n.hungerford@uq.edu.au
Dr Viviene Santiago | v.santiago@uq.edu.au

Duration: 6 weeks (20 - 30 hours per week); on site (Health and Food Sciences Precinct, 39 Kessels Rd, Coopers Plains)

This project focuses on the identification and analysis of the hepatotoxic indospicine in Indigofera leaf samples. Indospicine, an unusual amino acid found in all parts of certain Indigofera species, is known to be hepatotoxic to different species of animals, including cattle, sheep, dogs, and rats. Prolonged ingestion of indospicine have been reported to result to mild to severe liver disease. This project will examine the indospicine content of leaf samples using LC-MS/MS analysis and examine isolation of indospicine from these samples using HPLC-PDA.

Expected outcomes: Scholars will gain skills in the use of HPLC and LC-MS/MS analysis and will generate research data that is expected to lead to a publication.

Suitability: This project is open to applications from students with a background in organic chemistry with an interest in analytical chemistry. Can be undertaken as a research project for assessment if required.

Primary Supervisors: 

Dr Christie Warburton | c.warburton@uq.edu.au
Professor Ben Hayes  

Duration: 6 weeks (20 - 36 hours per week); on site (St Lucia Campus)

Buffaloes are integral to India’s dairy landscape, as they contribute approximately 45% of India’s total milk production. Genomic selection holds immense promise for enhancing milking productivity in Indian buffalo species, by leveraging genetic information we can systematically improve desirable traits. However, a significant challenge lies in developing both SNP marker arrays and predictive genomic selection models that span the diverse array of buffalo breeds and crossbreeds maintained by smallholder farmers. The aim of this project is to evaluate the potential to fit multi-breed genomic evaluation models to Indian River buffalo populations to improve the accuracy of selection for desirable milk and production traits.

Expected outcomes: This project equips students with skills in quantitative genetics, project design, scientific communication, statistical analysis, and high-performance computing. Students will collaborate closely with Dr. Christie Warburton and other members of Professor Ben Hayes’ laboratory at UQ. Scholars will have the opportunity to participate in research publications and develop their science communication skills through presentations at lab group meetings.

Suitability: This project is open to applications from 3rd or 4th year undergraduate or masters students with a background in genetics, genomics, biological sciences, bioinformatics, agricultural science, biotechnology or computer science. 

Primary Supervisors: 

Dr Mehrnush Forutan |  m.forutan@uq.edu.au
Professor Ben Hayes 

Duration: 6 weeks (20 - 36 hours per week); on site (St Lucia Campus)

Interest in mapping the impacts of selection on the genome is increasing. Recent studies show that polygenic selection is the major selective force both during and after domestication in agricultural species. Under directional selection, alleles will be at significantly different frequencies in more recent generations compared with distant ones. This creates a statistical association between allele frequencies at a selected locus and an individual’s generation number. Until now, most of the studies used the selection mapping methods which rely on either allele frequency differences between diverged or artificially defined populations (e.g., FST), or the disruption of normal LD patterns (e.g., ROH) to investigate the effect of selection. In cattle, these methods have successfully identified genomic regions under selection that control Mendelian and simple traits, or large-effect genes involved in domestication. Availability of the substantial number of animals genotyped from the most recent generations provide incredible power for detecting small allele frequency changes due to ongoing selection. The study will provide insight into the biology of polygenic selection and prioritize variants that are actively responding selection. 

Expected outcomes: This project provides student with a deep understanding of bioinformatics skills, project design, scientific communication, and analysis skills in a fast-developing area of genetics research. The student will work closely with Dr Mehrnush Forutan and other members of Professor Ben Hayes laboratory at UQ.

Suitability: Suitable for students studying or interested in genetics, computer science or agricultural science. Skills in these areas are all considered favourably for this project; however, they are not mandatory.

Primary Supervisors: 

Shashi Goonetilleke | shashi.goonetilleke@uq.edu.au
A/Prof Craig Hardner
Dr Elizabeth Ross  | e.ross@uq.edu.au

For any clarification, please contact Shashi Goonetilleke (shashi.goonetilleke@uq.edu.au) and Elizabeth Ross (e.ross@uq.edu.au)

Duration: 6 weeks (20 hours per week); on site (St Lucia Campus)

In this project, the student will use advnced  and effiicient data preparation, curation tools and methods to prepare datasets ready for genomic prediction in apple. These tools will improve the efficiency in collating the datasets generated from different genotyping and phenotyping platforms.

Expected outcomes: Students will gain skiils and learn good practices in large datset handling. Develop skills in R .

Suitability: This project is open to students with a background in agricultural and plant sciences.

Primary Supervisors: 

A/Prof Sheila Ommeh | s.ommeh@uq.edu.au
Dr Stephen Ogada 

Duration: 6 weeks (30 hours per week); Hybrid (St Lucia Campus)

Bovine Viral Diarrhoea (BVD) is a complex disease caused by Bovine Viral Diarrhoeal Virus (BVDV) or simply known as Pestivirus. The disease is endemic in livestock such as Cattle in Queensland, Australia and other parts of the world. The Project will utilize immunogenomic tools to mine sequences of Pestivirus from online databases. 

Expected outcomes: Students will gain skills in data mining, Bioinformatics and Computational Biology.

Suitability: Background in Biotechnology, Biochemistry & molecular Biology, Bioinformatics, Computational Science and Genetics

Primary Supervisors: 

A/Prof Sheila Ommeh | s.ommeh@uq.edu.au
Dr Stephen Ogada 

Duration: 6 weeks (30 hours per week); Hybrid (St Lucia Campus)

Mastitis is one of the most important diseases in Queensland, Australia and worldwide. The disease causes economic losses in Dairy cattle. Most of the vaccines in use are not fully effective due to the plethora of causative pathogens involved. Consequently, this has led to the use of antimicrobials alongside these vaccines. The aim of the project will be to use the reverse genomics approach to identify pathogen sequences so far associated with Mastitis in Australia/Oceania. 

Expected outcomes: Students will gain skills in data mining, Bioinformatics and Computational Biology

Suitability: Background in Biotechnology, Biochemistry & molecular Biology, Bioinformatics, Computational Science and Genetics

Primary Supervisor: 
A/Prof Sheila Ommeh | s.ommeh@uq.edu.au
Dr Stephen Ogada 

Duration: 6 weeks (30 hours per week); Hybrid (St Lucia Campus)

Avian Influenza also known as Birdflu is a zoonotic disease primarily in birds but can easily infect other species such as livestock and humans. Recently in the USA, Birdflu has been reported to also infect cattle. The disease is often caused by either low-pathogenic or highly pathogenic avian influenza. The aim of the project will be to use a “one-health” approach to mine the literature and sequence databases for pathogen lineages that may pose a biosecurity risk to Australian livestock specifically cattle, chicken, among others. 

Expected outcomes: Students will gain skills in data mining, Bioinformatics and Computational Biology

Suitability: Background in Biotechnology, Biochemistry & molecular Biology, Bioinformatics, Computational Science and Genetics

Primary Supervisor: 
A/Prof Sheila Ommeh | s.ommeh@uq.edu.au
Dr Stephen Ogada 

Duration: 6 weeks (30 hours per week); Hybrid (St Lucia Campus)

Several invasive species currently in Australia have become pests and include Feral Animals. Some examples include feral pigs, feral deer, feral rabbits, feral buffaloes, feral camels among others. These were either introduced initially as livestock and escaped into the wild or for control of other invasive species. Most harbor pathogens that pose a threat to current livestock and destroy crops as well as the ecosystem. The aim of the project will be to search existing databases for new control methods of these feral animals in the long-term alongside other current control methods in use.

Expected outcomes: Students will gain skills in data mining, Bioinformatics and Computational Biology

Suitability: Background in Biotechnology, Biochemistry & molecular Biology, Bioinformatics, Computational Science and Genetics

Primary Supervisor: Dr Seema Yadav | For any questions or further clarification, please reach out to Dr. Seema Yadav at seema.yadav@uq.edu.au.

Duration: 6 weeks (20 - 30 hours per week); On-site (St Lucia Campus). 

Students will simulate a plant breeding program using advanced computational and simulation tools. The focus will be on predicting genetic gain, optimizing selection strategies, and assessing the impact of different breeding approaches on crop improvement.

Expected outcomes: Students will gain hands-on experience with popular simulation tools like AlphaSimR, SelectionTools or genomicSimulation, learn to manipulate genetic data, and experiment with different breeding strategies to see how they affect the outcome of a breeding program. They will also learn how to visualize and interpret the results, making it relevant to both plant science and data analytics.

Suitability: Students should have a strong foundation in either R or Python, as the project will involve significant data manipulation, statistical analysis, and simulation using these programming languages.