About the Project
This project addresses a research priority for patients with the inherited heart condition, hypertrophic cardiomyopathy (HCM), by investigating how the same mutation can result in widely different phenotypes. Increased variability can manifest between different individuals, regions of the heart, and from one cell to the next. To address this, you will develop a unique process for capturing structural (confocal microscopy), functional (electrophysiology and Ca2+ imaging), and transcriptomic data…
all from the same cell. Integrating function and genomics will provide unprecedented power to identify possible causal factors responsible for pathology, and opportunities for intervention.
Hypertrophic cardiomyopathy (HCM) is the most common genetic cause of heart disease (affecting ~1 in 500 people) and is the leading cause of sudden death in young adults and currently there is no cure. A better understanding of the factors driving the disease could identify new opportunities for intervention and ultimately improve patient outcomes. HCM-causing variants in myofilament proteins (essential for muscle contraction) are usually autosomal dominant, meaning that one copy of a faulty gene is sufficient to cause disease, however there is substantial variability in disease penetrance, meaning that some develop severe early onset symptoms whereas others with the same mutation may be lifelong symptom-free. HCM can unpredictably affect both atria or ventricles and their regions , the extent of hypertrophy and dysfunction of physiological processes in cardiac myocytes, and the organization of contractile proteins within cardiac myocytes themselves. Structural and functional heterogeneity may have a detrimental impact on outcomes, but the cause(s) are poorly understood.
RNA sequencing (RNA-Seq) provides insight into gene expression profile in bulk tissue homogenates but does not account for variation between/within regions. Single cell RNA-Seq provides a more detailed view of the heterogeneity in transcriptome between cells and has been combined with FACS to link single parameters, such as cell size, with differentially expressed (DE) hypertrophic gene profiles. However, these methods do not reveal how DE genes impact the functional properties of cells, nor do they capture more detailed subcellular abnormalities. Patch-Seq is technique that combines the resolution of single-cell RNA sequencing with detailed physiological assessment achieved using patchclamp electrophysiology and Ca2+ imaging, yielding fully integrated multidimensional data on each cell’s electrophysiology, morphology, and individual transcriptome. We have previously used Patch-Seq to investigate causes of action potential failure in neural stem cells and neurons. Transcriptomic data generated using Patch-Seq successfully predicted experimental electrophysiological properties of neurons, demonstrating the mechanistic value of understanding transcriptome at the cellular level. Thus Patch-Seq has the potential to be a transformative tool for understanding the molecular causes of cellular dysfunction, however no studies have used it to investigate cardiovascular disease.
The key research question this project will address is whether DE genes underlie the pathological phenotype and functional heterogeneity present in HCM. The student will establish, for the first time, Patch-Seq in cardiac cells and use it to identify the molecular pathways associated with functional disruption in HCM. Specifically, the student will use cardiac electrophysiology and Patch-Seq on mouse cardiomyocytes and on human induced pluripotent stem cell-derived cardiac myocyte (hiPSCCM).
Aims:
- Establish Patch-Seq method for RNA extraction from atrial and ventricular cardiac myocytes and validate with complementary methods (qPCR).
- Identify DE transcripts associated with the severity of cellular structural and functional abnormalities in a mouse model of HCM using confocal microscopy.
- Compare and contrast identified DE transcripts with a hiPSC-CM model of HCM
Training will be provided: In Patch-Seq, the structural and functional properties of individual cells are first recorded using patch clamp electrophysiology and fluorescence imaging, then the cell is aspirated into the electrode for single-cell cDNA library preparation. We will first optimise the procedure for mRNA extraction from single atrial and ventricular cardiac myocytes from wildtype (WT) mice, following functional characterisation using confocal imaging and patch clamp electrophysiology in the same cell. These cell types have distinct structural, physiological, and transcriptional profiles, and therefore will be ideal positive controls to validate the methodology by correlating known functional characteristics with expression levels of relevant genes. These experiments will demonstrate that Patch-Seq can distinguish between types of cardiac myocytes based on known DE genes, and to correlate gene expression levels with known functional properties.
Second aim will be addressed using transgenic mice with a severe HCM phenotype, including atrial and ventricular hypertrophy, susceptibility to tachyarrhythmias and aberrant heart functions. Using this mouse model we have identified greater variability in heart weight, electrical repolarization and myofilament organisation, however the molecular causes of these differences are not known. We will apply the Patch-Seq methodology to test whether DE genes explain the structural and functional variability within and between HCM and WT cells. Finally, we will extend the methodology to hiPSC-CM, widely used for academic and commercial drug screening research, to validate DE genes associated with structural and functional abnormalities using a human model system.
A full description of the project can be found on the GW4 BioMed website.
Academic criteria: Applicants for a studentship must have obtained, or be about to obtain, a first or upper second-class UK honours degree, or the equivalent qualification gained outside the UK.
English requirements: IELTS with an overall score of 6.5 with 5.5 in all subskills, or acceptable alternative. Please see our English Language Requirements guidance for more details.
How to Apply
A list of all the projects and how to apply is available on the GW4 BioMed website. You may select up to 2 projects and submit one application per candidate only.
Please complete an application to the GW4 BioMed3 for an ‘offer of funding’. If successful, you will also need to make an application for an 'offer to study' to your chosen institution later.
Please note that we may close the application process before the stated deadline if an unprecedented number of applications are received– check the GW4 BioMed website for details and updates.
If you are shortlisted for interview, you will be notified from Tuesday, 22nd December 2026. Interviews will be held virtually on 26th and 27th January 2027. Studentships will start on 1st October 2027.
Funding Notes
These studentships are funded through GW4 BioMed3 MRC Doctoral Landscape Programme and consist of UK tuition fees, as well as a Doctoral Stipend matching UK Research Council National Minimum (£21, 805 p.a. for 2026/27, updated each year).
Additional research training and support funding of up to £5,000 per annum is also available.
GW4 BioMed3 studentships are available to UK and International applicants
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