Source: NORTH CAROLINA STATE UNIV submitted to
MOLECULAR AND GENETIC BASIS OF QUANTITATIVE VARIATION IN DROSOPHILA
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
TERMINATED
Funding Source
HATCH
Reporting Frequency
Annual
Accession No.
0207292
Grant No.
(N/A)
Project No.
NC06869
Proposal No.
(N/A)
Multistate No.
(N/A)
Program Code
(N/A)
Project Start Date
Oct 1, 2006
Project End Date
Sep 30, 2012
Grant Year
(N/A)
Project Director
Mackay, TR.
Recipient Organization
NORTH CAROLINA STATE UNIV
(N/A)
RALEIGH,NC 27695
Performing Department
Genetics
Non Technical Summary
Complex, or quantitative traits, are affected by multiple interacting genes that are sensitive to the environment. Most characters that are important for agriculture (production and yield traits), human health (for example, susceptibility to heart disease, cancer or diabetes); and adaptation of populations to their environments are complex traits. A major challenge is to determine what genes affect complex genotypes, as genetic methods of analysis developed for single genes with large effects are not appropriate. The use of model genetic systems, such as the fruit fly, Drosophila melanogaster, enables quick and efficient testing of new methods of analysis. We propose to use Drosophila to identify networks of genes responsible for naturally occurring variation in aggression. Given the evolutionary conservation of function for fundamental traits, such as aggression, genes and pathways discovered in Drosophila can be incorporated as candidate genes in studies to identifysusceptibility factors for increased levels of aggression in agriculturally important animals, as well as humans suffering from behavioral disorders.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
(N/A)
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
30431101080100%
Knowledge Area
304 - Animal Genome;

Subject Of Investigation
3110 - Insects;

Field Of Science
1080 - Genetics;
Goals / Objectives
The long-term goal is to understand the molecular and genetic basis of quantitative variation. The goal of this project is to use Drosophila melanogaster, a model system amenable to high-throughput genetic analysis, to identify networks of genes affecting aggressive behavior; the subset of genes responsible for naturally occurring variation in aggression that are the substrate for evolutionary forces; and to determine how interactions between genetic networks and environmental factors shape the expression of aggressive behavior in Drosophila. The immediate goals for this project period are: (1) To identify new candidate genes that affect aggressive behavior by screening a collection of 800 co-isogenic single P-element insert lines with known transposon insertion sites, many of which are in predicted genes; and to assess epistatic interactions between mutations at novel genes affecting aggressive behavior. (2) To use a systems biology approach, in which whole genometranscriptional profiling is applied to genetically divergent lines for aggressive behavior, to identify co-regulated genetic networks affecting aggression, and test model predictions by assessing effects of mutations of the co-regulated genes on aggression. (3) To map quantitative trait loci (QTLs) affecting naturally occurring variation in aggressive behavior, in a large (3000 individuals) F2 mapping population from parental lines selected for high and low levels of aggressive behavior from a heterogeneous population derived from nature.
Project Methods
We have developed a high throughput, reproducible assay to quantify levels of inter-male aggression in Drosophila, which we will use in all three projects to understand the genetic architecture of aggressive behavior. To identify new genes that affect aggressive behavior, we will conduct a forward genetic screen of 800 lines with single P-element insertions that were derived in a co-isogenic background. We will characterize the pleiotropic effects of these mutations on other traits, and determine the extent to which they interact to form a genetic network. In addition, we will use whole genome transcriptional profiling to identify genes that are up-and down-regulated in 10 of these mutant lines and lines that have been artificially selected for high and low levels of aggression. We will build a model of genetic interactions based on these data, and test this model by analyzing the effects of mutations of co-regulated genes on aggressive behavior. Finally, we will mapquantitative trait loci (QTLs) affecting natural variation in aggression. We will inbreed the high and low aggression lines derived by artificial selection to provide homozygous parental lines to construct a mapping population of 3000 F2 individuals. We will genotype these individuals with molecular markers to map QTLs with high resolution, and identify the casual genes by complementation tests to deficiencies and mutations of positional candidate genes.

Progress 10/01/06 to 09/30/12

Outputs
Target Audience: Quantitative genetics and behavioral genetics community, Drosophila and human geneticists. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Three graduate students (AC Edwards, JF Ayroles, L Zwarts) and three postdoctoral research fellows (TJ Morgan, SM Rollmann, MM Magwire) have been involved in this project. Drs. Edwards, Morgan and Rollmann are now in independent faculty positions, Drs. Ayroles and Zwarts are performing postdoctoral research, and Dr. Magwire has a scientist position in industry. How have the results been disseminated to communities of interest? The results of this project have been presented in 9 scientific publications, as well as at many national and international conferences. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? We developed a rapid and reproducible assay to quantify levels of inter-male aggression in Drosophila. We used this assay to assess aggressive behavior for 170 co-isogenic P-element insertion lines, and identified 59 mutations in 57 genes that affect aggressive behavior, none of which had been previously implicated to affect aggression, and many of which affected the development and function of the nervous system. We identified three different P-element mutations affecting aggressive behavior were in the neuralized (neur) gene, which encodes a ubiquitin ligase that is involved in cell fate commitment during development of the nervous system by processing the Notch ligand Delta. We showed that these mutations also affect sensory bristle number, olfactory behavior, startle-induced locomotion, brain morphology, and expression of 135 genes. We performed an analysis to assess interactions among the 10 most hyper-aggressive mutations, and found that six of these mutations formed an interaction network affecting aggression. These six mutations also formed interaction networks for five aspects of brain morphology and 830 gene expression traits, but the interactions networks were typically distinct from the network observed for aggressive behavior. Taken together, our analyses of the genetic architecture of Drosophila aggression from studying de novo mutations show pervasive pleiotropy, extensive gene-gene interactions (epistasis), a large mutational target size, and correlations between brain structure and behavior. We performed three different analyses of quantitative trait loci (QTLs) affecting natural variation in Drosophila aggression. The first was a linkage analyses utilizing 20 segmental introgression lines derived from two strains, one of which (Ore) was twice as aggressive as the other (2b). The segmental introgression lines each contained a fraction of the 2b genome in an otherwise isogenic Ore background. Surprisingly, we found that all but one introgression line were significantly more aggressive than Ore, and all were more aggressive than 2b. These results indicate that 2b contains multiple QTLs which individually increase aggressive behavior relative to Ore, but which together exhibit diminishing epistasis, such that their sum is much less than their individual effects. Thus, the extensive epistasis for aggression observed for de novo mutations also occurs between naturally segregating polymorphisms affecting aggression. In the second study we derived replicated artificial selection lines for increased and decreased aggression, as well as unselected control lines, from a heterogeneous base population derived from the Raleigh, NC natural population. We found a significant response to selection. We assessed the genome wide changes in gene expression in the selection lines, and identified 1,539 genes with different expression levels between the selection lines. We tested the aggressive behavior of mutation lines for 19 of these genes, and found that 15 did indeed affect aggressive behavior, suggesting that this trait is highly polygenic in natural populations. In the third study we used association mapping combined with systems genetic analyses to identify 266 novel candidate genes associated with aggressive behavior, and to derive a transcriptional genetic network associated with natural variation in aggressive behavior. The network consists of nine modules of correlated transcripts that are enriched for genes affecting common functions, tissue-specific expression patterns, and/or DNA sequence motifs. This study forms the basis of our current work on the quantitative systems genomics of aggressive behavior, utilizing genome wide association mapping for aggressive behavior in the ~200 sequenced inbred lines of the Drosophila Genetic Reference Panel, combined with genome wide analysis of variation in gene expression to derive causal transcriptional networks associated with this important complex trait.

Publications

  • Type: Journal Articles Status: Published Year Published: 2008 Citation: Rollmann SM, Edwards AC, Yamamoto A, Zwarts L, Callaerts P, Norga K, Mackay TFC & Anholt RRH. 2008. Pleiotropic effects of Drosophila neuralized on complex behaviors and brain structure. Genetics 179: 1327-1336.
  • Type: Journal Articles Status: Published Year Published: 2009 Citation: Edwards AC & Mackay TFC 2009. Quantitative trait loci for aggressive behavior in Drosophila melanogaster. Genetics 182: 889-897.
  • Type: Journal Articles Status: Published Year Published: 2012 Citation: Anholt RRH & Mackay TFC. 2012. Genetics of aggression. Annu. Rev. Genet. 46: 145-164.
  • Type: Journal Articles Status: Published Year Published: 2006 Citation: Edwards AC, Rollmann SM, Morgan TJ & Mackay TFC. 2006. Quantitative genomics of aggressive behavior in Drosophila melanogaster. PLoS Genetics 2: e154.
  • Type: Journal Articles Status: Published Year Published: 2009 Citation: Edwards AC, Ayroles JF, Stone EA, Carbone MA, Lyman RF & Mackay TFC. 2009. A transcriptional network associated with natural variation in Drosophila aggressive behavior. Genome Biology 10: R76.
  • Type: Journal Articles Status: Published Year Published: 2009 Citation: Edwards AC, Zwarts L, Yamamoto A, Callaerts P & Mackay TFC. 2009. Mutations in many genes subtly affect aggressive behavior in Drosophila melanogaster. BMC Biology 7: 29.
  • Type: Journal Articles Status: Published Year Published: 2009 Citation: Mackay TFC. 2009. The genetic architecture of complex behaviors: Lessons from Drosophila. Genetica 136: 295-302.
  • Type: Journal Articles Status: Published Year Published: 2011 Citation: Zwarts L, Magwire MM, Carbone MA, Yamamoto A, Versteven M, Anholt RRH, Callaerts P & Mackay TFC. 2011. Complex genetic architecture of Drosophila aggressive behavior. Proc. Natl. Acad. Sci. USA 108: 17070-17075.
  • Type: Journal Articles Status: Published Year Published: 2006 Citation: Mackay TFC & Anholt RRH. 2006. Of flies and man: Drosophila as a model for human complex traits. Ann. Rev. Genomics Hum. Genetics 7: 339-367.


Progress 10/01/08 to 09/30/09

Outputs
OUTPUTS: Most human diseases and characters of economic importance to plant and animals breeders are complex (or quantitative) traits, with multiple interacting genes that are sensitive to the environment contributing to the observed phenotype. We are taking advantage of the excellent genetic and genomic resources available in the fruit fly, Drosophila melanogaster, to determine the genetic architecture of quantitative traits. The first step in this analysis is to determine what loci affect the expression of the quantitative trait, combining quantitative analysis of phenotypes with construction of single, transposable-element-tagged mutations in a highly inbred background. Then, to determine what subset of these loci affect naturally occurring variation in the traits, we map the quantitative trait loci (QTL) by linkage to molecular markers in large mapping populations derived from divergent strains, or by whole genome association analyses. We have derived a Drosophila Genetic Reference Population of 192 inbred lines from the Raleigh, NC population. We have screened these lines for a battery of quantitative traits (numbers of sensory bristles, olfactory behavior, longevity, locomotor activity, mating behavior, aggression, alcohol sensitivity, starvation resistance and time to recover from a chill-induced coma). We have identified extreme lines that we are using as parents for QTL mapping. In addition, we measured whole genome transcript levels on a sample of 40 of the lines, and identified modules of correlated transcripts associated with each of the quantitative traits. We are obtaining complete DNA sequences of the entire reference population, in collaboration with the Baylor College of Medicine Human Genome Sequencing Center. Thus, we will soon be able to perform genome wide association tests to identify novel genes and pathways affecting quantitative traits, and gain insight about the molecular basis of pleiotropy and genotype by environment interaction. These lines are publicly available from the Bloomington Drosophila Stock Center, and all genotype and phenotype data will be deposited in public databases. PARTICIPANTS: Not relevant to this project. TARGET AUDIENCES: Not relevant to this project. PROJECT MODIFICATIONS: Not relevant to this project.

Impacts
Many putative genes found by genome sequencing projects have no known function. We have shown that we can infer function of these novel genes based on their genetic correlations in gene expression with known genes and higher level organismal phenotypes. We also identified hundreds to thousands of transcripts associated with each quantitative trait, as well as transcripts with pleiotropic effects on multiple traits. We have shown that genotype-phenotype relationships are highly context-dependent, and vary according to the environment and genetic background, as well as sex. Multiple functional polymorphic alleles at a single gene segregate in natural populations, with different alleles affecting different traits. Further, multiple polymorphisms in a single gene can be associated with a single trait.

Publications

  • Ayroles, J. F., Carbone, M. A., Stone, E. A., Jordan, K. W., Lyman, R. F., Magwire, M. M., Rollmann, S. M., Duncan, L. H., Lawrence, F., Anholt, R. R. H. & Mackay, T. F. C. 2009. Systems genetics of complex traits in Drosophila melanogaster. Nat. Genet. 41: 299-307.
  • Carbone, M. A., Ayroles, J. F., Yamamoto, A., Morozova, T. V., West, S. A., Magwire, M. M., Mackay, T. F. C. & Anholt, R. R. H. 2009. Overexpression of myocilin in the Drosophila eye activates the unfolded protein response: Implications for glaucoma. PLoS ONE 4: e4216.
  • Edwards, A. C. & Mackay, T. F. C. 2009. Quantitative trait loci for aggressive behavior in Drosophila melanogaster. Genetics 182: 889-897.
  • Edwards, A. C., Ayroles, J. F., Stone, E. A., Carbone, M. A., Lyman, R. F. & Mackay, T. F. C. 2009. A transcriptional network associated with natural variation in Drosophila aggressive behavior. Genome Biology 10: R76.
  • Edwards, A. C., Zwarts, L., Yamamoto, A. Callaerts, P. & Mackay, T. F. C. 2009. Mutations in many genes subtly affect aggressive behavior in Drosophila melanogaster. BMC Biology 7: 29.
  • Flint, J. & Mackay, T. F. C. 2009. Genetic architecture of quantitative traits in mice, flies and humans. Genome Res. 19: 723-733.
  • Harbison, S. T., Carbone, M. A., Ayroles, J. F., Stone, E. A., Lyman, R. F. & Mackay, T. F. C. 2009. Co-regulated transcriptional networks contribute to natural genetic variation in Drosophila sleep. Nat. Genet. 41: 371-375.
  • Harbison, S. T., Mackay, T. F. C. & Anholt, R. R. H. 2009. Understanding the neurogenetics of sleep: Progress from Drosophila. Trends Genet. 25: 262-269.
  • Mackay, T. F. C. 2009. The genetic architecture of complex behaviors: Lessons from Drosophila. Genetica 136: 295-302.
  • Mackay, T. F. C. 2009. Q&A: Genetic analysis of quantitative traits. J. Biol. 8: 23.
  • Mackay, T. F. C. 2009. A-maize-ing diversity. Science 325: 688-689.
  • Mackay, T. F. C., Stone, E. A. & Ayroles, J. F. 2009. The genetics of quantitative traits: Challenges and prospects. Nat. Rev. Genet. 10: 565-577.
  • Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., Cho, J. H., Guttmacher, A. E., Kong, A., Kruglyak, L., Mardis, E., Rotimi, C. N., Slatkin, M., Valle, D., Whittemore, A. S., Boehnke, M., Clark, A., Eichler, E. E., Gibson, G., Haines, J. L., Mackay, T. F. C., McCarroll, S. A. & Visscher, P. M. 2009. Finding the missing heritability of complex diseases. Nature 461: 747-753.
  • Morozova, T. V., Ayroles, J. F., Jordan, K. W., Duncan, L. H., Carbone, M. A., Lyman, R. F., Stone, E. A., Govindaraju, D. R., Ellison, C. R., Mackay, T. F. C. and Anholt, R. R. H. 2009. Alcohol sensitivity in Drosophila: Translational potential of systems genetics. Genetics 83: 733-745.
  • Yamamoto, A., Anholt, R. R. H. & Mackay, T. F. C. 2009. Epistatic interactions attenuate mutations affecting startle behaviour in Drosophila melanogaster. Genet. Res. 91: 373-382. Zhou, S., Stone, E. A., Mackay, T. F. C. & Anholt, R. R. H. 2009. Plasticity of the chemoreceptor repertoire in Drosophila melanogaster. PLoS Genetics 5: e1000681.


Progress 10/01/07 to 09/30/08

Outputs
OUTPUTS: Most human diseases and characters of economic importance to plant and animals breeders are complex (or quantitative) traits, with multiple interacting genes that are sensitive to the environment contributing to the observed phenotype. We are taking advantage of the excellent genetic and genomic resources available in the fruit fly, Drosophila melanogaster, to determine the genetic architecture of quantitative traits. The first step in this analysis is to determine what loci affect the expression of the quantitative trait, combining quantitative analysis of phenotypes with construction of single, transposable-element-tagged mutations in a highly inbred background. Then, to determine what subset of these loci affect naturally occurring variation in the traits, we map the quantitative trait loci (QTL) by linkage to molecular markers in large mapping populations derived from divergent strains, or by whole genome association analyses. We have derived a Drosophila Genetic Reference Population of 192 inbred lines from the Raleigh, NC population. We have screened these lines for a battery of quantitative traits (numbers of sensory bristles, olfactory behavior, longevity, locomotor activity, mating behavior, aggression, alcohol sensitivity, starvation resistance and time to recover from a chill-induced coma). We have identified extreme lines that we are using a parents for QTL mapping. In addition, we measured whole genome transcript levels on a sample of 40 of the lines, and identified modules of correlated transcripts associated with each of the quantitative traits. We are obtaining complete DNA sequences of the entire reference population, in collaboration with the Baylor College of Medicine Sequencing Center. Thus, we will soon be able to perform genome wide association tests to identify novel genes and pathways affecting quantitative traits, and gain insight about the molecular basis of pleiotropy and genotype by environment interaction. These lines are publicly available from the Bloomington Drosophila Stock Center, and all genotype and phenotype data will be deposited in public databases. PARTICIPANTS: Not relevant to this project. TARGET AUDIENCES: Not relevant to this project. PROJECT MODIFICATIONS: Not relevant to this project.

Impacts
Many putative genes found by genome sequencing projects have no known function. We have shown that we can infer function of these novel genes based on their genetic correlations in gene expression with known genes and higher level organismal phenotypes. We also identified hundreds to thousands of transcripts associated with each quantitative trait, as well as transcripts with pleiotropic effects on multiple traits. We have shown that genotype-phenotype relationships are highly context-dependent, and vary according to the environment and genetic background, as well as sex. Multiple functional polymorphic alleles at a single gene segregate in natural populations, with different alleles affecting different traits. Further, multiple polymorphisms in a single gene can be associated with a single trait.

Publications

  • Rollmann, S. M., Edwards, A. C., Yamamoto, A., Zwarts, L., Callaerts, P., Norga, K., Mackay, T. F. C. & Anholt, R. R. H. 2008. Pleiotropic effects of Drosophila neuralized on complex behaviors and brain structure. Genetics 179: 1327-1336.
  • Sambandan, D., Carbone, M. A., Anholt, R. R. H. & Mackay, T. F. C. 2008. Phenotypic plasticity and genotype by environment interaction for olfactory behavior in Drosophila melanogaster. Genetics 179: 1079-1088.
  • Yamamoto, A., Zwarts, L., Callaerts, P., Norga, K., Mackay, T. F. C. & Anholt, R. R. H. 2008. Neurogenetic networks for startle-induced locomotion in Drosophila melanogaster. Proc. Natl. Acad. Sci. U.S.A. 105: 12393-12398.


Progress 10/01/06 to 09/30/07

Outputs
Most human diseases and characters of economic importance to plant and animals breeders are complex (or quantitative) traits, with multiple interacting genes that are sensitive to the environment contributing to the observed phenotype. We are taking advantage of the excellent genetic and genomic resources available in the fruit fly, Drosophila melanogaster, to determine the genetic architecture of quantitative traits. The first step in this analysis is to determine what loci affect the expression of the quantitative trait, combining quantitative analysis of phenotypes with construction of single, transposable-element-tagged mutations in a highly inbred background. Then, to determine what subset of these loci affect naturally occurring variation in the traits, we map the quantitative trait loci (QTL) affecting the trait in recombinant inbred lines. Next, deficiency mapping is used to further refine the QTL map positions, followed by complementation tests of QTL alleles to mutants at positional candidate genes. We use linkage disequilibrium mapping to determine the molecular basis of naturally occurring quantitative variation at the candidate genes, by associating molecular polymorphisms in the gene with phenotypic variation in the trait. Finally, we use whole-genome transcriptional profiling to understand the regulatory networks of genes affecting quantitative traits, and variation in quantitative traits between genetically distinct lines with different trait phenotypes. We are applying all of these approaches to determine the genetic architecture of sensory bristle number, olfactory behavior, longevity, locomotor activity, mating behavior, aggression, alcohol sensitivity and starvation resistance in Drosophila. These projects were in progress during this project period.

Impacts
Many putative genes found by genome sequencing projects have no known function. High resolution QTL analysis can detect genes with subtle phenotypic effects and is an important gene discovery tool. Molecular marker-phenotype association studies are used to determine whether candidate genes are associated with disease status. Our results point to the need to use multiple markers per candidate gene, and attribute functional importance to non-protein coding gene regions.

Publications

  • Jordan, K. W., Carbone, M. A., Yamamoto, A., Morgan, T. J. & Mackay, T. F. C. 2007. Quantitative genomics of locomotor behavior in Drosophila melanogaster. Genome Biology 8: R172. doi:10.1186/gb-2007-8-8-r172.
  • Lai, C. Q., Parnell, L., Lyman, R. F., Ordovas, J. M. & Mackay, T. F. C. 2007. Candidate genes affecting drosophila life span identified by integrating microarray gene expression analysis and QTL mapping. Mech. Ageing Dev. 128: 237-249.
  • Lai, C. Q., Leips, J. Zou, W. Roberts, J. F., Wollenberg, K. R., Parnell, L D., Zeng, Z. B., Ordovas, J. M. & Mackay, T. F. C. 2007. Speed-mapping quantitative trait loci using microarrays. Nat. Methods 10: 839-841.
  • Mackay, T. F. C. & Anholt, R. R. H. 2007. Ain't misbehavin'? Genotype-environment interactions and the genetics of behavior. Trends Genet. 23: 311-314.
  • Morozova, T. V., Anholt, R. R. H. And Mackay, T. F. C. 2007. Phenotypic and transcriptional response to selection for alcohol sensitivity in Drosophila melanogaster. Genome Biology 8: R231. doi:10.1186/gb-2007-8-10-r231.
  • Riedl, C. A. L., Riedl, M., Mackay, T. F. C. & Sokolowski, M. B. 2007. Genetic and behavioral analysis of natural variation in Drosophila melanogaster pupation position. Fly 1: http://www.landesbioscience.com/journals/fly/article/3830
  • Rollmann, S. M., Yamamoto, A., Goossens, T., Zwarts, L., Callaerts, P., Norga, K., Mackay, T. F. C. & Anholt, R. R. H. 2007. The early neurodevelopmental gene Semaphorin 5c is essential for olfactory behavior in adult Drosophila. Genetics 176: 947-956.