Complex mutations are a source of evolutionary innovation that can form new genes, modify expression of existing genes, and contribute to the genetic basis of evolutionary change. They are known to be associated with multiple diseases in humans and to contribute to adaptive changes in natural populations. Still, these mutations remain understudied, as they can be more difficult to identify in genomes compared with single site changes. This proposal will fill the gap concerning complex mutations shaping natural variation and adaptation. We will study complex mutations in detail using D. yakuba and D. santomea as a genetic model. We will identify complex mutations that form the genetic basis of local adaptation under shifting environments. We will explore regulatory changes and new gene formation caused by these mutations to determine how the molecular impacts of these mutations contribute to local adaptation We will then explore broad patterns in the diversity of complex mutations in natural populations of other Drosophila to better understand how generalizable these patterns are across the genus. We will identify any species-specific differences in how complex mutations contribute to adaptation in nature. Finally, we will explore the same mutations in humans, facilitating the translation of basic knowledge to human health. This work will further assess how biological rules hold across the tree of life. I will discern what themes are general across taxa. Where do different species show different evolutionary outcomes because of their genome architecture, population genetic parameters, and biological processes? We have seen general themes emerge of new gene formation associated with male reproduction in Drosophila and in humans. We expect new rules for model systems that will hold true in human biology. When we do not observe such concordance, we may perform more focused analyses to determine why species differ. Each evolutionary system has been thoroughly studied for SNP variation but not for structural variants. Some of these systems were previously sequenced using only single-end reads, making searches for complex mutations nearly impossible! Because these interesting mutations have been neglected, we are missing important information about genetic innovation and evolution. A full study of complex mutations will require a focused analysis from a lab that has the bioinformatic expertise to identify these changes. This proposal takes advantage of MIRA's flexible research goals to analyze genome structure changes in multiple species of Drosophila and in humans, a task that would be difficult under the umbrella of other support mechanisms. Researchers often lament the gap between model organism genetics and human genetic research. There is no better means to facilitate this translation to humans than to have a single research group perform similar analyses on similar mutations in model organisms and in humans. These results impact human health, as they describe natural variation in human genomes that was previously ignored.

Public Health Relevance

This research explores how duplications, deletions, and chromosomal rearrangements create brand new genes that are important for adaptation. These mutations are associated with human diseases such as cancer, autism, and infertility. Understanding the molecular and evolutionary impacts of complex mutations will help us understand how they cause disease and why they are important for human health.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Unknown (R35)
Project #
1R35GM133376-01
Application #
9795639
Study Section
Special Emphasis Panel (ZGM1)
Program Officer
Janes, Daniel E
Project Start
2019-08-01
Project End
2024-07-31
Budget Start
2019-08-01
Budget End
2020-07-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of North Carolina Charlotte
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
066300096
City
Charlotte
State
NC
Country
United States
Zip Code
28223