The Additive Genetic Variance of Fitness in Semi-Natural and Laboratory Environments
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Biological Sciences
Abstract
Fitness - the capacity of individuals to produce descendants - is the central concept of Darwin's theory of natural selection. However, if fitness does not have a genetic basis then fit individuals cannot transmit their superiority to their offspring, and evolution by natural selection is impossible. Because of this, the degree to which fitness is heritable is of central importance to evolutionary biologists. However, measuring the genetic determinism of fitness is very difficult because traditionally a large number of individuals and their relatives need to be tracked and their births and deaths recorded. Consequently, we only have estimates from the wild for a limited range of species, all of which come with considerable uncertainty. Estimates from the laboratory are more commonplace, but it is not clear how relevant they are since the fitnesses of wild individuals are probably dependent on how well they combat parasites, evade predators and compete with competitors, all of which may be absent in the laboratory.
Using mathematics and computer simulations we have shown that the genetic determinism of fitness can also be measured by tracking all genes in the genome and measuring how many descendants they leave. Given the falling costs of genome sequencing this alternative method has many advantages, and is currently the only feasible solution for the vast majority of species which cannot be individually tracked. The fruit fly, Drosophila melanogaster, is one of the best studied laboratory organisms in the world and is extensively used in evolutionary biology and beyond. In this grant we aim to measure the genetic determinism of fitness in wild flies raised in conditions which simulate the wild, to provide the first estimate for a non-vertebrate animal. We will also perform the same experiment under laboratory conditions to see if those genes that leave more descendants in the laboratory are the same genes that leave more descendants in the wild. If this is the case, then fitness measured in the laboratory is probably a good surrogate for that in the wild, but if different genes are involved then laboratory studies may have little relevance in a natural context.
An additional advantage of tracking genes rather than individuals is that we can see what features make successful genes successful. Is it because they encode for a more useful protein, or is it because they deploy an existing protein to a greater extent or at a better time and place? Do successful genes tend to have functions that relate to immunity? Are successful genes more likely to be located on the X chromosome? These questions, and many similar ones, have been repeatedly asked by geneticists who have sought to answer them indirectly, by looking at historical signatures left behind in genomes. Here, we hope to address these types of questions in real-time using an organism in which gene location and function are exceptionally well understood.
Using mathematics and computer simulations we have shown that the genetic determinism of fitness can also be measured by tracking all genes in the genome and measuring how many descendants they leave. Given the falling costs of genome sequencing this alternative method has many advantages, and is currently the only feasible solution for the vast majority of species which cannot be individually tracked. The fruit fly, Drosophila melanogaster, is one of the best studied laboratory organisms in the world and is extensively used in evolutionary biology and beyond. In this grant we aim to measure the genetic determinism of fitness in wild flies raised in conditions which simulate the wild, to provide the first estimate for a non-vertebrate animal. We will also perform the same experiment under laboratory conditions to see if those genes that leave more descendants in the laboratory are the same genes that leave more descendants in the wild. If this is the case, then fitness measured in the laboratory is probably a good surrogate for that in the wild, but if different genes are involved then laboratory studies may have little relevance in a natural context.
An additional advantage of tracking genes rather than individuals is that we can see what features make successful genes successful. Is it because they encode for a more useful protein, or is it because they deploy an existing protein to a greater extent or at a better time and place? Do successful genes tend to have functions that relate to immunity? Are successful genes more likely to be located on the X chromosome? These questions, and many similar ones, have been repeatedly asked by geneticists who have sought to answer them indirectly, by looking at historical signatures left behind in genomes. Here, we hope to address these types of questions in real-time using an organism in which gene location and function are exceptionally well understood.