Studies in genetic model organisms are an indispensible mechanism for characterizing the mutational and selective processes that generate genetic and phenotypic diversity. In particular, Drosophila combines the advantages of efficient population sampling, well developed experimental techniques, with powerful genome engineering approaches and is therefore a uniquely valuable system for characterizing the contributions of genetic variation to phenotypic and fitness variation in natural populations. Towards this broad goal, this research program will leverage the D. melanogaster system to: (1) Enhance the Drosophila Genome Nexus (DGN), a widely used database that distributes a uniformly curated and high quality Drosophila population genomic variation dataset. Specifically, by developing methods that include known genetic variation rather than mapping to a single haploid reference genome, this research program will enhance both variation calls at single nucleotide polymorphisms as well as expand our ability to detect and accurately characterize structural variation. Similarly, research will develop and apply approaches for accurately delineating heterozygous regions in the genomes of inbred lines. By vastly improving the database, this reseach will enable a new wave of in-depth analyses of the widely-used DGN. (2) Reveal the fitness and gene expression consequences of the structural and linked allelic variation associated with natural chromosomal inversions. Genome engineering techniques enable the construction of inversions with controlled breakpoints on a genetically homogenous background. Through contrasts with naturally occurring chromosomal inversions, research will distinguish the impacts of structural and linked allelic variation on gene expression patterns. In addition, research will investigate the fitness consequences of fine- scale variation in breakpoint location. Chromatin conformation capture sequencing, Hi-C, will enable the production of sequencing libraries whose large insert sizes enable inversion breakpoint mapping. Research will apply this approach to map breakpoints of rare inversions. By comparing breakpoint structures with those of common inversions, these data will enable direct insights into the mutational forces that generate inversions as well as how these factors influence natural selection on new chromosomal arrangements. (3) Investigate the genomic and phenotypic consequences of admixture between genetically divergent subpopulations. By sequencing several admixed populations of D. melanogaster, research will determine the relative importance of gene-gene interactions in driving natural selection across diverse admixed populations. Furthermore, by leverage phenotypic data from one admixed population that has been used for a number of association studies, research will evaluate the importance of admixture in shaping complex phenotypes long after the initial gene flow event and develop local ancestry aware approaches for mapping complex trait associations.
Drosophila is a powerful model organism for understanding the interplay of genomic variation, phenotypic evolution and natural selection. Building on this tradition, this research will use vast existing datasets and develop novel computational approaches to improve and expand a widely-used Drosophila genetic variation database. Additionally, research will leverage genome engineering tools and innovative genome sequencing approaches to dissect the molecular and phenotypic consequences of genomic rearrangements and genetic mixture between isolated populations of D. melanogaster.
| Medina, Paloma; Thornlow, Bryan; Nielsen, Rasmus et al. (2018) Estimating the Timing of Multiple Admixture Pulses During Local Ancestry Inference. Genetics 210:1089-1107 |
| Thornlow, Bryan P; Hough, Josh; Roger, Jacquelyn M et al. (2018) Transfer RNA genes experience exceptionally elevated mutation rates. Proc Natl Acad Sci U S A 115:8996-9001 |
