About the Project
High-throughput quantitative brain-wide analysis of structural changes in long-range connections has recently become feasible using an approach that goes with the acronym MAPSeq (Multiplex Analysis of Projections by Sequencing)2,3. MAPSeq relies on tagging individual neurons with a unique molecular identifier, a barcode RNA, that is transported to the neuron’s axon terminals. Quantifying the levels of barcode RNA in areas of interest reveals the targets of the labelled neurons and the strength of projections. In one experiment, the individual projection profile of thousands of neurons can be investigated, making MAPSeq an unprecedented tool for high-throughput, high-resolution assessment of brain-wide connectivity. We have already successfully applied this technique to the study of memory networks in my lab.
We can envision a number of ways in which structural connectophies could manifest in ASD. For example, axons might be misrouted to abnormal targets. Alternatively, axonal branching en route to targets or at the target site might be disrupted. Distinguishing between these and other models would greatly help understand the mechanistic basis of ASDs. These problems are well suited to MAPseq approaches, but would be difficult and unfeasibly time consuming to address using current functional imaging or anatomical labeling techniques.
In this project we will apply MAPseq and 3D imaging on inter-area connections to investigate connectopathies in rodent models of ASD in a quantitative manner. Our goal is to identify communication pathways with altered structural connectivity from three key nodes of memory, attention and social behaviour networks (Prefrontal cortex mPFC, Posterior parietal area PPA and amygdala AMY). We will focus on the mouse models of autism spectrum disorders associated with Fmr1, Syngap and Neurexin genes. Structural changes in afferent inputs to visual areas were reported in FMRP-/y mice suggesting a systemic connectivity problem4, but the precise nature of these deficits is unclear and the issue has otherwise received very little attention.
The data obtained will directly test long range hypo-connectivity hypotheses and will reveal the nature of specific connectivity deficits involved.
1. Expertise in mathematical and statistical methods for analysis of large datasets.
2. Expertise in methods for computational modeling.
3. Expertise in high-throughput RNA sequencing methods for transcriptomic profiling.
These skills are applicable in a broad range of research disciplines in science, medicine and industry.
Practical lab experience in the Surmeli Lab:
-Tissue preparation and imaging using light sheet microscopy.
-Rodent brain surgery.
-Viral intervention approaches.
-Tissue slice preparation and dissection.
Analytical lab experience in the Surmeli and Hennig Labs with input from Dr. Simpson:
-Analysis of axonal tracts in 3D using currently available computational tools available and in development for light sheet microscopy images.
-Implementation of statistical modelling tools for processing of deep sequencing data.
This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.
All applications should be made via the University of Edinburgh, irrespective of project location. For those applying to a University of Glasgow project, your application along with any supporting documents will be shared with University of Glasgow.
Please note, you must apply to one of the projects and you must contact the primary supervisor prior to making your application. Additional information on the application process is available from the link above.
For more information about Precision Medicine visit:
Qualifications criteria: Applicants applying for an MRC DTP in Precision Medicine studentship must have obtained, or will soon obtain, a first or upper-second class UK honours degree or equivalent non-UK qualification, in an appropriate science/technology area. The MRC DTP in Precision Medicine grant provides tuition fees and stipend of at least £15,285 (UKRI rate 2020/21).
Full eligibility details are available: View Website
Enquiries regarding programme: firstname.lastname@example.org
2. Kebschull, J. M. et al. High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA. Neuron 91, 975–987 (2016).
3. Han, Y. et al. The logic of single-cell projections from visual cortex. Nature 556, 51–56 (2018).
4. Haberl, M. G. et al. Structural-functional connectivity deficits of neocortical circuits in the Fmr1−/y mouse model of autism. Science Advances 1, e1500775 (2015).
Why not add a message here
Based on your current searches we recommend the following search filters.
Based on your current search criteria we thought you might be interested in these.