Each individual has a distinctive combination of gene variants strung together along their chromosomes. Because genes that are near one another on the chromosomes tend to be inherited together, populations harbor only a subset of all possible combinations of gene variants, yielding statistical associations between them. The vital biological process that shapes this association pattern is genetic recombination during meiosis. This study investigates the evolutionary forces that determine the relationship between association patterns and recombination rates along the chromosomes, a relationship crucial for shaping genetic diversity. A combination of experimentally evolved and natural populations will be used to tease apart the evolutionary forces shaping genetic diversity in the Caenorhabditis elegans genome at an unprecedented resolution. The proposed research will explicitly test the conformity of long-standing theoretical predictions governing the relationship between patterns of genomic association and meiotic recombination with careful experimental measurements of both. The comprehensive understanding of the relationship between genomic association patterns and meiotic recombination rates from this study will find widespread application in genome-wide association studies (which searches for genetic variants in populations), linkage mapping (which searches within families), and evolutionary genomic studies. The results and methodologies developed in the course of this research will be published in open-access format, which will facilitate the broadest possible dissemination of this research. Funding of this research will provide a female Ph.D. student with the opportunity to pursue an independent line of research from that of her mentor.
Genomes include thousands of genes, but these genes are distributed on a much smaller number of DNA segments, the chromosomes. The physical structure of the genome influences how traits are coinherited, because genes that are near one another on the DNA are usually inherited together (a phenomenon known as linkage). The exact probability of coinheritance of adjacent genes is governed by poorly understood factors and in most species is uncharacterized. In this project, PhD student Taniya Kaur experimentally determined the pattern of linkage along a section of chromosome in a model animal species, the nematode C. elegans. The detailed characterization achieved unprecedented resolution, allowing for the first time the demonstration that these animals have a very different distribution of coinheritance probabilities than other well-studied species. The project also developed new analytical approaches and statistical methods that are applicable to a wide range of studies. These results were reported in a paper published in the journal Genetics. Following the experimental characterization of coinheritance probabilities, the project investigated the realized patterns of co-occurence of genes in wild populations and in laboratory-evolved popuations. The result is a unique dataset showing the relationship between the experimental data, which report on the molecular mechansisms that link genes, and the population data, which report on the evolutionary outcomes of population-level processes. The interaction between mechanistic and population-level processes governs the distribution of traits in populations of all species. Finally, this project trained a young scientist in a broad range of experimental, statistical, and computational methods.
