Approximately 8.5 million people have osteoarthritis in the UK, but no disease modifying therapeutics are currently available. Chondrocytes are the sole cell type in cartilage that is damaged in osteoarthritis. Multipotent mesenchymal stem cell (MSC) differentiation into chondrocytes, known as chondrogenesis, not only serves as an in vitro model for cartilage development, but also provides an important source of cartilage for tissue engineering purposes e.g cartilage defect repair.
To help understand the process of chondrogenesis, the supervisory team have performed high-throughput global omics methods such as RNA-seq, ATAC-seq and proteomics to characterise the molecular changes at multiple regulatory levels during in vitro differentiation.
In this project, the student will receive training in both lab and computational approaches to combine these datasets to help predict and test what regulates chondrogenesis, feeding into our fundamental understanding of osteoarthritis and healthy ageing.
Main goals:
1) Using network-based approaches, the student will integrate the omics data to identify pathways altered at multiple molecular levels.
2) The student will use data mining to extract known regulators of chondrogenesis from the biomedical literature. These known regulators alongside the integrated omics data will be used with machine learning methods to predict what proteins can improve chondrogenesis in vitro.
3) Using in vitro models, the student will assess the importance of these identified regulators in driving chondrogenesis. The computational predictions will be experimentally validated in collaboration with Professor Mandy Peffers (Liverpool) and Professor David Young (Newcastle). These in vitro chondrogenesis assays will allow investigation of the impact of regulator perturbation of chondrogenesis using stem cell, molecular biology and biochemical techniques.
This is an exciting opportunity to work in the area of genomic “Big Data” to combine existing, and new datasets to help understand what regulates chondrogenesis. This project is suitable for students from biology or bioinformatics backgrounds with a willingness to learn. Students will be able to take MSc bioinformatics modules, as well as be strongly supported by a knowledgeable supervisory team. This PhD offers hand-on training from a multidisciplinary team in highly sought-after quantitative skills (machine learning, bioinformatics) as well as the modern stem cell and molecular biology skills needed translate their computational work to impactful results.
HOW TO APPLY
Applications should be made by emailing [Email Address Removed] with:
· a CV (including contact details of at least two academic (or other relevant) referees);
· a covering letter – clearly stating your first choice project, and optionally 2nd ranked project, as well as including whatever additional information you feel is pertinent to your application; you may wish to indicate, for example, why you are particularly interested in the selected project(s) and at the selected University;
· copies of your relevant undergraduate degree transcripts and certificates;
· a copy of your IELTS or TOEFL English language certificate (where required);
· a copy of your passport (photo page).
A GUIDE TO THE FORMAT REQUIRED FOR THE APPLICATION DOCUMENTS IS AVAILABLE AT https://www.nld-dtp.org.uk/how-apply. Applications not meeting these criteria may be rejected.
In addition to the above items, please email a completed copy of the Additional Details Form (as a Word document) to [Email Address Removed]. A blank copy of this form can be found at: https://www.nld-dtp.org.uk/how-apply.
Informal enquiries may be made to [Email Address Removed]
The deadline for all applications is 12noon on Monday 9th January 2023.
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