Distribution Modelling of Gene Drive-Modified Mosquitoes and Their Effects on Wild Populations
(2020) In Master Thesis in Geographical Information Science GISM01 20202Dept of Physical Geography and Ecosystem Science
- Abstract
- Emerging technologies have the potential to bring numerous new opportunities and solutions to the existing challenges, including addressing sustainable development goals (SDGs). Particular hopes are given to areas of the life that require our urgent action, these include but are not limited to medicine and food security. Scientists investigate how these technological advances can be applied for the benefit of humanity by making more robust crops, eliminating diseases, or trying to extend our longevity. One technology that attracted and kept on attracting attention is the so-called “gene drives.” Genes in sexually reproducing organisms have, on average, a 50% chance of being inherited by the offspring. There are, however, genes that have a... (More)
- Emerging technologies have the potential to bring numerous new opportunities and solutions to the existing challenges, including addressing sustainable development goals (SDGs). Particular hopes are given to areas of the life that require our urgent action, these include but are not limited to medicine and food security. Scientists investigate how these technological advances can be applied for the benefit of humanity by making more robust crops, eliminating diseases, or trying to extend our longevity. One technology that attracted and kept on attracting attention is the so-called “gene drives.” Genes in sexually reproducing organisms have, on average, a 50% chance of being inherited by the offspring. There are, however, genes that have a higher chance of being inherited. In a long-term, such dominant genes can affect the entire population by adding, replacing, suppressing, or editing genetic traits. Being able to eradicate invasive local species, alter mosquito genomes to eliminate Zika, dengue fever, and malaria or produce more environmentally robust to plant species is something to aim for.
The study uses computational modelling techniques in which gene drive inheritance model are combined with distribution models of mosquito species to develop unified modelling approach to evaluate the factors related to gene drive altered species and their capability to eradicate population of wild species. The study shows how gene drive altered mosquitoes can influence wild mosquito populations to prevent them from vectoring malaria and other vector-borne diseases.
The study focuses on malaria spread that is associated with one specific species - Anopheles mosquitoes. The study area is Kenya due to a number of reported cases of malaria. The proliferation of malaria mosquitoes was selected due to a number of spatial distribution models that have been developed over the years, as well as the availability of existing remote sensing data. (Less) - Popular Abstract
- Performed computational simulations show that genetically modified mosquitoes can replace wild mosquito population within a decade or less. The genetic modification introduced in the mosquitoes prevents them from transmitting the malaria parasite. In addition, the genetic modification presented in this study makes the chance of inheritance of the modified gene significantly higher than the usual 50%. Hence, the number of malaria cases can be significantly reduced. Further, because of the high inheritance chance for modified mosquitoes to pass introduced genetic traits onto their offspring, the time required to make the entire mosquito population unable to transmit malaria is significantly reduced. The computational model also assumed that... (More)
- Performed computational simulations show that genetically modified mosquitoes can replace wild mosquito population within a decade or less. The genetic modification introduced in the mosquitoes prevents them from transmitting the malaria parasite. In addition, the genetic modification presented in this study makes the chance of inheritance of the modified gene significantly higher than the usual 50%. Hence, the number of malaria cases can be significantly reduced. Further, because of the high inheritance chance for modified mosquitoes to pass introduced genetic traits onto their offspring, the time required to make the entire mosquito population unable to transmit malaria is significantly reduced. The computational model also assumed that some mosquitoes would develop resistance to this genetic modification. Such mosquitoes should still be able to transmit malaria. The complete elimination of malaria is not possible using a genetic modification pathway due to developed resistance.
Simulation outcomes show a clear relationship between the inheritance frequency of the genetic modification, which corresponds to a chance of this genetically engineered trait to be inherited by the offspring, and the time required to replace the wild mosquito population. The higher the inheritance ratio, the faster the mosquito population replacement. Finally, an increase in the number of genetically modified mosquitoes released within the study area compared to the number of mosquitoes in the wild population reduces the time required to replace the wild mosquito population. Release of those modified mosquitoes from multiple locations is also of benefit in terms of replacement time. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9032512
- author
- Kolodziejczyk, Bartlomiej LU
- supervisor
- organization
- course
- GISM01 20202
- year
- 2020
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Geography, Geographical Information Systems, GIS, Physical Geography, Mosquito Distribution, Malaria Modelling, Gene Drives
- publication/series
- Master Thesis in Geographical Information Science
- report number
- 123
- language
- English
- additional info
- External supervisor: Valentijn Venus, University of Twente
- id
- 9032512
- date added to LUP
- 2020-12-03 11:02:19
- date last changed
- 2020-12-03 11:02:19
@misc{9032512,
abstract = {{Emerging technologies have the potential to bring numerous new opportunities and solutions to the existing challenges, including addressing sustainable development goals (SDGs). Particular hopes are given to areas of the life that require our urgent action, these include but are not limited to medicine and food security. Scientists investigate how these technological advances can be applied for the benefit of humanity by making more robust crops, eliminating diseases, or trying to extend our longevity. One technology that attracted and kept on attracting attention is the so-called “gene drives.” Genes in sexually reproducing organisms have, on average, a 50% chance of being inherited by the offspring. There are, however, genes that have a higher chance of being inherited. In a long-term, such dominant genes can affect the entire population by adding, replacing, suppressing, or editing genetic traits. Being able to eradicate invasive local species, alter mosquito genomes to eliminate Zika, dengue fever, and malaria or produce more environmentally robust to plant species is something to aim for.
The study uses computational modelling techniques in which gene drive inheritance model are combined with distribution models of mosquito species to develop unified modelling approach to evaluate the factors related to gene drive altered species and their capability to eradicate population of wild species. The study shows how gene drive altered mosquitoes can influence wild mosquito populations to prevent them from vectoring malaria and other vector-borne diseases.
The study focuses on malaria spread that is associated with one specific species - Anopheles mosquitoes. The study area is Kenya due to a number of reported cases of malaria. The proliferation of malaria mosquitoes was selected due to a number of spatial distribution models that have been developed over the years, as well as the availability of existing remote sensing data.}},
author = {{Kolodziejczyk, Bartlomiej}},
language = {{eng}},
note = {{Student Paper}},
series = {{Master Thesis in Geographical Information Science}},
title = {{Distribution Modelling of Gene Drive-Modified Mosquitoes and Their Effects on Wild Populations}},
year = {{2020}},
}