Over the last 10,000 years Drosophila melanogaster has spread through the world in the wake of human migration. As a consequence, populations of these flies have been exposed to novel environments and have subsequently evolved in response to these local conditions. For flies living in temperate environments, winter cold represents a novel environment and populations have evolved in response to cold temperatures in several distinct ways. First, flies living in temperate climates have evolved a suite of physiological adaptations that increase tolerance to cold and starvation. While several genes have been identified that underlie these physiological adaptations, the majority of the genes underlying these adaptations remain unknown. Second, winter conditions cause population size contractions following periods of exponential growth during the summer. These cyclic changes in population size will significantly affect background levels of genetic variation, yet these patterns have not been adequately documented throughout the genome. Herein, we propose to simultaneously identify polymorphic loci underlying adaptations to temperate climates and describe the consequences of cyclic populations boom-busts on background levels of genetic variation. To do this, we will collect samples of D. melanogaster through the growing season from replicate orchards in temperate New England. We propose to resequence the genomes of flies collected from these orchards using high-throughput sequencing technologies. By resequencing the genomes of flies collected through the growing season, we seek to accomplish two aims. First, we will identify loci which change in allele frequency in a monotonic fashion consistently among all orchards through the growing season. We hypothesize that these loci underlie balanced polymorphisms underlying adaptation to seasonal environments. Second, we aim to characterize patterns of genetic variation genome wide. We predict that cyclic population boom-busts will cause changes in heterozygosity, linkage disequilibrium and signatures of population structure through the growing season. This three year postdoctoral fellowship will train the applicant in the field of population genetics and will provide him with invaluable skills in bioinformatics, computational biology and high-throughput library construction.

Public Health Relevance

Using the model organism, Drosophila melanogaster, this project seeks to simultaneously identify genetic polymorphisms underlying adaptation to novel environments and document the effects of recent demographic events on patterns of genetic variation. Heuristic and analytic methods developed under this proposal can be applied to genomic data in humans to aid in disentangling the effects of demography and selection on patterns of genetic variation surrounding disease causing polymorphisms.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32GM097837-03
Application #
8436232
Study Section
Special Emphasis Panel (ZRG1-F08-E (20))
Program Officer
Janes, Daniel E
Project Start
2011-03-29
Project End
2014-03-28
Budget Start
2013-03-29
Budget End
2014-03-28
Support Year
3
Fiscal Year
2013
Total Cost
$52,190
Indirect Cost
Name
Stanford University
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Bergland, Alan O; Behrman, Emily L; O'Brien, Katherine R et al. (2014) Genomic evidence of rapid and stable adaptive oscillations over seasonal time scales in Drosophila. PLoS Genet 10:e1004775
Bergland, Alan O; Chae, Hyo-seok; Kim, Young-Joon et al. (2012) Fine-scale mapping of natural variation in fly fecundity identifies neuronal domain of expression and function of an aquaporin. PLoS Genet 8:e1002631