Details of Award
NERC Reference : NE/T009322/1
NSFDEB-NERC: The Origin of Sperm Parasitism through the Looking Glass of the Amazon Molly
Grant Award
- Principal Investigator:
- Dr F Ubeda, Royal Holloway, Univ of London, Biological Sciences
- Grant held at:
- Royal Holloway, Univ of London, Biological Sciences
- Science Area:
- Atmospheric
- Earth
- Freshwater
- Marine
- Terrestrial
- Overall Classification:
- Panel A
- ENRIs:
- Biodiversity
- Environmental Risks and Hazards
- Global Change
- Natural Resource Management
- Pollution and Waste
- Science Topics:
- Adaptation
- Breeding system evolution
- Evolution & populations
- Evolutionary genetics
- Population genetics
- Selection
- Sex chromosomes
- Speciation
- Evolution & populations
- Mutation
- Predictive modelling
- Sex ratio
- Population Genetics/Evolution
- Adaptive/Evol. Math. Process
- Non-linear Systems Mathematics
- Abstract:
- The vast majority of species have two sexes and both are needed to reproduce. But one mode of reproduction is especially interesting because it combines a seemingly impossible combination of traits. In this mode, gynogenesis, eggs have to be fertilized by males of a different species, but the genes provided by males are not incorporated into the offspring, which means that the resulting offspring are identical to their mothers. More importantly, it is often assumed that several important evolutionary changes, such as the loss of males and formation of diploid eggs, happened at the same time. Theoretically, he accumulation of large transitions in a single evolutionary step is highly unlikely, but this is nonetheless the prevailing explanation. In the proposed project, the researchers will attempt to form a synthetic gynogenetic species by carefully establishing the evolutionary and molecular pathway that led to the origin of a fish species, the Amazon molly. The research will test the assumption that major evolutionary transitions can happen simultaneously. The team located in Great Britain will be using mathematical models to guide actual experiments crossing existing species and their hybrids by a team located in the USA. This will allow a much deeper understanding of the process that leads to gynogenesis in particular and sexual reproduction in general. Furthermore, this research will provide a platform for outreach to the public via workshops and training opportunities for multiple young scientists in the STEM field. The research aims at artificially forming a species through hybridization of two existing species determining the most likely evolutionary pathway from one to the other. The existing species at the origin of the new species are fishes from Texas and Mexico, and the new species results of a hybridization event in nature. To retrace the evolution of this species the research team will use several mathematical techniques, including differential equations and Monte-Carlo Simulations to model the most likely pathway for the evolution of a unique set of traits, including unisexuality, formation of unreduced eggs, and clonality. Current thinking claims that all of these massive changes happened in one giant evolutionary step, but this seems unlikely from a theory point of view. Guided by the mathematical models, a large-scale crossing experiment will be conducted to actually form a gynogenetic species in the laboratory. This will involve crossing sexual fishes, and also crossing the resulting F1 individuals amongst each other, and backcrossing them. Every unique cross will further be characterized genomically, genetically, and morphologically.
- NERC Reference:
- NE/T009322/1
- Grant Stage:
- Completed
- Scheme:
- Standard Grant FEC
- Grant Status:
- Closed
- Programme:
- Lead Agency Grant
This grant award has a total value of £300,621
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DI - Staff | DA - Estate Costs | DI - T&S | DA - Other Directly Allocated |
|---|---|---|---|---|---|---|
| £19,512 | £120,849 | £32,045 | £73,594 | £28,505 | £24,489 | £1,626 |
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