Each year millions of Americans are diagnosed with diseases such as diabetes, heart disease, Alzheimer's, and various forms of cancer. In concert with environmental variation, risk for these diseases is controlled by large, heterogeneous sets of genetic factors. By characterizing those genes that increase risk, the biomedical community can describe the molecular pathways involved in human health and disease, ultimately enabling the rational design of novel treatments. Unfortunately, progress towards identifying the catalog of genetic risk alleles has been slow. Despite our ability to carry out massive population-based case-control genetic association studies in humans, only a tiny fraction of causative sites are known for any given complex disease. Over the last few years several groups, including ourselves, have been exploring the utility of advanced generation, multiparental mapping panels for routine, powerful, and high-resolution dissection of complex trait variation in model genetic systems (e.g., the mouse Collaborative Cross, the rat NIH heterogeneous stock, the Drosophila Synthetic Population Resource, or DSPR). Model systems exhibit similar genetic, cellular, physiological, and behavioral processes to humans, and offer a complementary avenue for obtaining insight into the factors that underlie complex trait variation. We successfully developed the DSPR during the first period of grant funding, and provide this as a freely-available community resource for the genetic dissection of trait variation in flies. Our project delivered a framework that can map causative variants to small genomic intervals, and has the power to map rare variants, and genes that harbor multiple causative alleles, both of which human association studies struggle to interrogate. Here we will continue to extend our work developing the DSPR as a powerful set of enabling resources for the Drosophila biomedical community. First, we will employ long-read, high-throughput sequencing to generate genome assemblies for all lines founding the DSPR. These novel assemblies will allow us to identify structural, and copy number variants in the lines, complementing our existing data to provide the complete catalog of segregating variation in the DSPR. Second, we will carry out genomewide gene expression profiling on multiple tissues for a large set of lines, allowing us to identify genes contributing to expression variation. Additionally, we will identify regions of the genome likely t recruit regulatory proteins. Integrating these datasets will facilitate the detection of causative, regulatory variants, which are thought to contribute significantly to trait variation. Finally, buiding on our considerable success mapping loci underlying biomedically-relevant trait variation in the DSPR, we will carry out extremely large-scale phenotyping screens for two traits in a testcross design (crossing each DSPR line to a set of unrelated strains). This work will allow us to detail the degree to which mapped loci have effects that are dependent on the genetic background of the mapping population. These results will have important implications for the design of mapping experiments in model systems.

Public Health Relevance

Genomewide association studies have immeasurably improved our understanding of the genetic basis of disease risk, yet known associations explain limited fractions of disease variation, and only in a few cases do we know the precise molecular nature of causative sites. Our novel mapping resources enable a rapid transition from mapped regions to candidate genes and causative variants, and can be easily-shared with other researchers, facilitating the genetic dissection of a myriad of complex traits. Our method is complementary to population-based association studies, and has distinct advantages if causative variants belong to particular functional categories, offering the possibility of a genera understanding of the molecular genetic basis of biomedically-relevant trait variation.

Agency
National Institute of Health (NIH)
Institute
Office of The Director, National Institutes of Health (OD)
Type
Research Project (R01)
Project #
5R01OD010974-10
Application #
9698454
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Zou, Sige
Project Start
2008-07-15
Project End
2020-05-31
Budget Start
2019-06-01
Budget End
2020-05-31
Support Year
10
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Kansas Lawrence
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
076248616
City
Lawrence
State
KS
Country
United States
Zip Code
66045
Mostafa, Heba H; Thompson, Thornton W; Konen, Adam J et al. (2018) Herpes Simplex Virus 1 Mutant with Point Mutations in UL39 Is Impaired for Acute Viral Replication in Mice, Establishment of Latency, and Explant-Induced Reactivation. J Virol 92:
Baldwin-Brown, James G; Weeks, Stephen C; Long, Anthony D (2018) A New Standard for Crustacean Genomes: The Highly Contiguous, Annotated Genome Assembly of the Clam Shrimp Eulimnadia texana Reveals HOX Gene Order and Identifies the Sex Chromosome. Genome Biol Evol 10:143-156
Najarro, Michael A; Hackett, Jennifer L; Macdonald, Stuart J (2017) Loci Contributing to Boric Acid Toxicity in Two Reference Populations of Drosophila melanogaster. G3 (Bethesda) 7:1631-1641
Mahdipour-Shirayeh, A; Darooneh, A H; Long, A D et al. (2017) Genotype by random environmental interactions gives an advantage to non-favored minor alleles. Sci Rep 7:5193
King, Elizabeth G; Long, Anthony D (2017) The Beavis Effect in Next-Generation Mapping Panels in Drosophila melanogaster. G3 (Bethesda) 7:1643-1652
Highfill, Chad A; Tran, Jonathan H; Nguyen, Samantha K T et al. (2017) Naturally Segregating Variation at Ugt86Dd Contributes to Nicotine Resistance in Drosophila melanogaster. Genetics 207:311-325
Sanjak, Jaleal S; Long, Anthony D; Thornton, Kevin R (2017) A Model of Compound Heterozygous, Loss-of-Function Alleles Is Broadly Consistent with Observations from Complex-Disease GWAS Datasets. PLoS Genet 13:e1006573
Chakraborty, Mahul; Baldwin-Brown, James G; Long, Anthony D et al. (2016) Contiguous and accurate de novo assembly of metazoan genomes with modest long read coverage. Nucleic Acids Res 44:e147
Highfill, Chad A; Reeves, G Adam; Macdonald, Stuart J (2016) Genetic analysis of variation in lifespan using a multiparental advanced intercross Drosophila mapping population. BMC Genet 17:113
Sanjak, Jaleal S; Long, Anthony D; Thornton, Kevin R (2016) Efficient Software for Multi-marker, Region-Based Analysis of GWAS Data. G3 (Bethesda) 6:1023-30

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