Mendel's first law describes how the two alleles in a heterozygous individual have equal chances of being transmitted to its progeny. Decades of work have revealed that different types of selfish DNAs can parasitize host species and subvert Mendel's first law to increase their transmission to offspring and their frequency in populations. These selfish DNAs are deleterious as they can reduce fertility and distort allele frequencies of host genes in populations. The asymmetric meiosis found in the females of many species including humans is particularly prone to attack by selfish DNAs because only one meiotic product forms an egg while the remainder become polar bodies. Meiotic drivers exploit this asymmetry by biasing their transmission to the egg. Moderate-strength meiotic drivers that bias their transmission by a few percent may be prevalent in populations but have been challenging to identify due to the necessity of distinguishing them from viability effects. This proposal will determine the identity and mechanism of a recently discovered candidate meiotic driver discovered in a natural population of the fruit fly Drosophila melanogaster that causes an approximately 4% deviation from normal Mendelian segregation. This candidate maps broadly to a centromeric region, leading to the working hypothesis that it corresponds to a variant in heterochromatic repetitive DNA. Novel methods will first be used to track the genotype and state of development of individuals throughout the life cycle, from meiosis in their mothers through adulthood, in order to determine the mechanism of meiotic drive. Heterochromatic regions have long been considered inaccessible to conventional genetic mapping approaches due to their complete suppression of meiotic recombination. A new approach is developed here to generate recombinants across the centromeric region in order to perform a high-resolution association study of repeat type and abundance relative to meiotic drive. Importantly, this approach does not require genome assembly across the centromere. We will also apply both short-read and long-read sequencing technologies to identify candidate sequences responsible for drive. Following these mapping and sequencing approaches, experimental manipulation will be used to test and confirm identity of the meiotic driver. Evolutionary theory predicts that meiotic drive will vary in degree between populations. This proposal will investigate the magnitude of drive in both related and unrelated populations, and then map and identify major-effect modifier alleles. Other candidate meiotic drivers will also be characterized by the approaches developed here. This proposal will provide an unprecedented level of information about the identity and mechanism of meiotic drivers that are segregating in natural populations, and provide a framework and series of methods that can be applied to other types of non-Mendelian transmission in a wide range of organisms.

Public Health Relevance

The successful transmission of chromosomes to eggs and sperm is essential for human fertility and health, yet animals are continually challenged by selfish DNAs that subvert the process of chromosome segregation to gametes. We will determine the identity and mechanism whereby one type of selfish DNA termed meiotic drivers are able to distort normal chromosome segregation into eggs. This research will reveal fundamental information about how animals including humans are able to maintain robust fertility.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM074737-14
Application #
9850974
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Janes, Daniel E
Project Start
2019-01-16
Project End
2022-12-31
Budget Start
2020-01-01
Budget End
2020-12-31
Support Year
14
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Cornell University
Department
Biochemistry
Type
Schools of Arts and Sciences
DUNS #
872612445
City
Ithaca
State
NY
Country
United States
Zip Code
14850
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