Gene regulatory network models for single-cell data from in vitro direct neuronal reprogramming
(2024) FYSK04 20241Department of Physics
- Abstract
- Direct neuronal reprogramming has many medical applications that are at the forefront of medical research. There are known genes, such as Ascl1, Dlx5 and Lhx6, that induce the reprogramming into neuronal cells. However, because there are numerous genetic variables involved in direct reprogramming, the current methods for conversion is inefficient. Hence, we proposed a strategy to group genes and map them to observed cell states. Next, a gene regulatory network was formulated with candidate genes selected from our organized gene groups. A dynamical model of the network was developed for comparison with experimental data. The dynamics of our model suggest that the technique proposed here is able to identify viable gene candidates that might... (More)
- Direct neuronal reprogramming has many medical applications that are at the forefront of medical research. There are known genes, such as Ascl1, Dlx5 and Lhx6, that induce the reprogramming into neuronal cells. However, because there are numerous genetic variables involved in direct reprogramming, the current methods for conversion is inefficient. Hence, we proposed a strategy to group genes and map them to observed cell states. Next, a gene regulatory network was formulated with candidate genes selected from our organized gene groups. A dynamical model of the network was developed for comparison with experimental data. The dynamics of our model suggest that the technique proposed here is able to identify viable gene candidates that might be involved in the direct reprogramming of glial cells to paravalbumin interneurons. Lastly, our proposed network might serve as the foundation for the regulatory mechanism governing this conversion. (Less)
- Popular Abstract
- Specialized cells, such as skin cells or brain cells, are formed through a process called cell differentiation. During differentiation, certain genes are switched on or off as the cells develop. At the end, a specialized cell has a specific set of genes switched on, unique to the type of cell. Cell differentiation was once thought to be a one-way transition. However, developments in new experimental techniques have shown that cells can change their cell identity in a process called reprogramming. Currently, such methods have low efficiency. By exploring computational methods to study cell reprogramming experiments, we can try to uncover areas of the system to improve the conversion efficiency. In the future, these improvements could allow... (More)
- Specialized cells, such as skin cells or brain cells, are formed through a process called cell differentiation. During differentiation, certain genes are switched on or off as the cells develop. At the end, a specialized cell has a specific set of genes switched on, unique to the type of cell. Cell differentiation was once thought to be a one-way transition. However, developments in new experimental techniques have shown that cells can change their cell identity in a process called reprogramming. Currently, such methods have low efficiency. By exploring computational methods to study cell reprogramming experiments, we can try to uncover areas of the system to improve the conversion efficiency. In the future, these improvements could allow for cell reprogramming to be a viable option in medical treatments, in areas such as regenerative medicine. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9162023
- author
- Lee, Enver LU
- supervisor
- organization
- course
- FYSK04 20241
- year
- 2024
- type
- M2 - Bachelor Degree
- subject
- keywords
- gene regulatory networks, single-cell RNA sequencing, direct neuronal reprogramming, PV interneurons, glial cells
- language
- English
- id
- 9162023
- date added to LUP
- 2024-06-19 09:03:08
- date last changed
- 2024-06-19 09:03:08
@misc{9162023,
abstract = {{Direct neuronal reprogramming has many medical applications that are at the forefront of medical research. There are known genes, such as Ascl1, Dlx5 and Lhx6, that induce the reprogramming into neuronal cells. However, because there are numerous genetic variables involved in direct reprogramming, the current methods for conversion is inefficient. Hence, we proposed a strategy to group genes and map them to observed cell states. Next, a gene regulatory network was formulated with candidate genes selected from our organized gene groups. A dynamical model of the network was developed for comparison with experimental data. The dynamics of our model suggest that the technique proposed here is able to identify viable gene candidates that might be involved in the direct reprogramming of glial cells to paravalbumin interneurons. Lastly, our proposed network might serve as the foundation for the regulatory mechanism governing this conversion.}},
author = {{Lee, Enver}},
language = {{eng}},
note = {{Student Paper}},
title = {{Gene regulatory network models for single-cell data from in vitro direct neuronal reprogramming}},
year = {{2024}},
}