About
Males and females of a given species have the same genomic sequence. Yet, the sexes have distinct physical characters and behaviors. Some of these differences - such as primary sexual characteristics ¬- result from sex-specific genes, namely genes expressed in one sex but not the other. However, most of the phenotypic variation between the sexes - from size to coloration to mating patterns - results from genes expressed in both sexes but in different ways. Since the sexes share the same genomic information, this differentiation in expression, and therefore phenotype, creates a tug-of-war between the sexes over the optimal version of the trait.
This genomic tug-of-war between the sexes has the potential to generate differences among the sexes within a generation, potentially leading to important changes within populations over the longer term. However, the extent of this pattern is largely unknown. Importantly, the genomic regions experiencing antagonistic interaction between the sexes are often involved in fertilization and early zygote development, and so understanding the genomic basis of sexual antagonism, may assist in identifying practical solutions for sex-specific health issues, including infertility.
The aims of this project are to: i) determine how many genomic regions show a significant difference between the sexes, ii) estimate the strength of selection within these regions, and iii) link sexually differentiated genomic regions with potential associated phenotypes. We hypothesize that genomic regions on the sex chromosomes will have the highest degree of differentiation between the sexes and contribute the most to defective fertility phenotypes. To accomplish these aims, we will adapt classic population genetics statistics to consider males and females as separate populations and measure the divergence between them. The anticipated length of this project is one year.
1 Return
| Return ID | App ID | Description | Archive Date |
|---|
| 3844 | 43626 | Evaluating human autosomal loci for sexually antagonistic viability selection in two large biobanks | 17 Sep 2021 |
