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Gregory C. GibsonDr. Gibson has moved to the
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Reverse Quantitative Genetics of Development and BehaviorOne of the great, outstanding questions as the science of genetics enters its second century is what portion of the polymorphism at the DNA level is responsible for phenotypic variation? The advent of genomic technologies such as high-throughput sequencing and an array of genotyping methods have brought within sight the goal of scanning across genes for single nucleotide polymorphisms, and associating these with a variety of traits. In order to do this, we need good candidate genes, easily measured traits, and an organism that can be manipulated with ease. We are using the fruitfly, Drosophila melanogaster, to this end, but with a twist: rather than starting with the traits and working back to genes, we are starting with interesting sets of genes and exploring their association with candidate traits. The developmental genetic arm of the lab is studying the effect of genes involved in Ras-mediated signal transduction on components of wing shape, and modification of photoreceptor determination. The behavioral genetic arm of the lab is studying neurotransmitter receptors and their association with heart rate and headless behavior. Stunning recent advances in our understanding of how genes orchestrate development have generated much excitement among evolutionary biologists and developmental biologists alike. Since morphology is shaped by the regulation of gene expression during development, changes in morphology must be due to changes in gene expression. Much current research focuses on the differences between divergent taxa, but we are interested in the genetic variation that exists within a species. All evolutionary change starts with mutations, and moves through a phase of variation at the population level. Only by studying the genes that actually contribute to that variation will we really learn what the relative roles of selection, drift, and historical constraint are in evolution. Consequently, we're using quantitative genetic strategies to study the genetic basis of variation in wing morphology. Our analyses have led us to the hypothesis that the wing veins are crucial determinants of wing shape (Birdsall et al.), and that factors that affect the placement and growth of wing veins thereby modulate wing shape (Zimmerman et al.). Among these factors are elements of the EGF-Receptor/Ras-Raf pathway of signal transduction. This pathway, in conjunction with the Sevenless growth factor receptor, also mediates photoreceptor differentiation in the Drosophila eye. When eye development is perturbed with a dominant mutation, we can uncover enormous amounts of hidden genetic variation in wild-type genetic backgrounds (Polaczyk et al.). These two sets of observations have led us to set up experiments to detect associations between SNPs in the EGF pathway genes, and variation for vein placement and eye roughness. DNA sequence analysis reveals that there is almost no polymorphism in the central components of signal transduction (Gasperini and Gibson), so we are focusing on upstream regulators and downstream targets as sources of phenotypic variation. Behavioral and pharmacogenetics is emerging as one of the most exciting fields for genetic research in the next decade. Our entry into this field came with a study of genetic variation for heart rate in flies (Robbins et al.) that showed first that there is considerable heritability for heart rate, and second that wild type genetic backgrounds can suppress the effects of mutations in key genes such as ether-a-gogo. This gene encodes a potassium channel, and is homologous to the human HERG channel, which is mutated in certain forms of the heart arrhythmia disease Long-QT syndrome. Much effort (and money) is now being put into association studies in humans to find susceptibility loci for a variety of heart and psychological conditions, so we have begun to develop fly models for such quantitative genetic analysis. After performing a deficiency screen for regions of the genome that modify heart rate (Ashton and Gibson), we have begun to focus on the neurotransmitter receptor loci as candidate genes. In parallel, we are now working with assays for the locomotor activity of flies after removal of their heads. It turns out that there is substantial genetic variability for whether flies groom themselves, grasp objects, quiver, right themselves, or walk around, as well as for the response to exogenously applied biogenic amines. Our studies emphasize the role of environmental and background genetic influences on behavior, and are designed to provide a model system for the genetic dissection of complex multi-factorial diseases. Quantitative Gene Expression ProfilingOur second major research interest is in bridging the gap between genotype and phenotype by quantifying transcriptional variation using cDNA microarray and oligonucleotide GeneChip experiments. We have recently developed a statistical approach that allows partitioning of the effects of factors such as sex, genotype, environmental treatment, and tissue-type on gene expression. Application of this analysis of variance-based methodology (MMANMADA) to our own Drosophila data shows that over one half of the transcriptome differs significantly between the two sexes, that up to one quarter of the genes are differentially affected by sex or sex-by-genotype interaction, and that adult age has remarkably little effect on transcriptional variance. We are currently comparing the effects of sex and genotype on the effect that drugs such as nicotine and caffeine have on transcription. Association of transcriptional response with variable phenotypic sensitivity to the drugs among lines should be a powerful tool for identification of candidate genes that may be responsible for pharmacological differences. In the context of organismal biology, there are a number of fundamental issues that we will explore with our quantitative expression profiling. The first is documentation of the heritability and degree of dominance of gene expression. Do all genes vary among lines, or just a subset? Is there any population structure to the variation, and if so is it clinal and how large is the effect relative to individuals within lines and lines within populations? The second is documentation of the covariance of gene expression. Are there discrete transcriptional phenotypes within species that may correspond to coadapted gene complexes at the expression level? Are there clusters of genes that always covary, and if so what are the implications for phenotypic divergence by genetic drift? Can we identify regulatory elements and trans-acting factors that are responsible for covariation? Third, how does natural variation affect conclusions derived from analysis of mutants, and can it be used to enhance our classical genetic analyses? In pursuing these questions, we are focusing on Drosophila, but in collaboration with Dr. Prema Arasu in the Vet School at NCSU, we have recently begun to study transcriptional variation in the parasitic nematode dog hookworm, Ancylostoma caninum. Selected Publications:Dworkin, I.D., A. Palsson, and G. Gibson. 2006. Replication of an Egfr-wing shape association in a wild-caught cohort of Drosophila melanogaster. Genetics, 173: 1417-1431. Thomson, S., E. Kennerly, N. Olby, J. Mickelson, D. Hoffmann, P. Dickinson, G. Gibson, and M. Breen. 2005. Microarray analysis of differentially expressed genes of primary tumors in the canine central nervous system. Veterinary Pathology 42: 550-558. Goering, L.M. and G. Gibson. 2005. Genetic variation for dorsal-ventral patterning of the Drosophila melanogaster eggshell. Evol Dev. 7: 81-88. Gibson, G. and I.M. Dworkin 2004. Uncovering cryptic genetic variation. Nat. Rev. Genet. 5: 681-691. Yu, X., T-M. Chu, G. Gibson, and R.D. Wolfinger 2004. A mixed model approach to identify yeast transcriptional regulatory motifs via microarray experiments. SAGMB 3: Article 22. Nikoh, N., A. Duty, and G. Gibson 2004. Association between nucleotide variation in serotonin receptors and heart rate in Drosophila melanogaster. Genetics 168: 1963-1974. Kennerly, E., S. Thomson, N. Olby, M. Breen, and G. Gibson. 2004. Comparison of regional gene expression differences in the brains of the domestic dog and human. Human Genomics, 1: 435-443. Gibson, G., R. Riley, L. Harshman, A. Kopp, S. Vacha, S. Nuzhdin, and M. Wayne 2004. Extensive sex-specific non-additivity of gene expression in Drosophila melanogaster. Genetics 167: 1791-1799. Palsson, A., and G. Gibson 2004. Association between nucleotide variation in Egfr and wing shape in Drosophila melanogaster. Genetics 167: 1187-1198. Palsson, A., A. Rouse, R. Riley, I. Dworkin, and G. Gibson 2004. Nucleotide variation in the Egfr locus of Drosophila melanogaster. Genetics 167: 1199-1212. McGraw, L.A., G. Gibson, A.G. Clark, M.F. Wolfner 2004. Genes regulated by mating, sperm, or seminal proteins in mated female Drosophila melanogaster. Curr. Biol. 14: 1509-1514. Honeycutt, E. and Gibson, G. 2004. Use of regression methods to identify motifs that modulate germline transcription in Drosophila melanogaster. Genet. Res. 83: 177-188. Ranz, J., K. Namgyal, G. Gibson, and D. Hartl 2003. Meltdown of the gene expression network in interspecific hybrids of Drosophila. Genome Res. 14: 373-379. Hsieh, W.P., Chu, T.M., Wolfinger R.D. and Gibson, G.C. 2003. Mixed model reanalysis of primate dataset suggests species and tissue biases in gene expression profiles. Genetics 165: 747-57. Dworkin, I. Palsson, A., Birdsall, K. and Gibson, G. 2003. Evidence that the Egfr contributes cryptic variation for photoreceptor determination in natural populations of Drosophila melanogaster. Current Biology 13: 1888-1893. Riley, R.M., Jin, W. and Gibson, G. 2002. Contrasting selection pressures on components of Ras-mediated signal transduction in Drosophila. Mol. Ecol. 12: 1315-1323. Carrillo, R.J., and G. Gibson, G. 2002. Unusual genetic architecture of natural variation affecting drug responses in Drosophila melanogaster. Genet. Res. 80: 205-213. Wolfinger, R.D., Gibson, G.,
Wolfinger, E.D., Bennett, L., Hamadeh, H., Bushel, P., Afshari, C., and
Paules, R.S. 2001. Assessing gene significance from cDNA microarray expression
data via mixed models. J. Comp. Biol 8: 625-637. Jin, W. Riley, R., Wolfinger,
R.D., White, K.P., Passador-Gurgel, G., and Gibson, G. 2001. Contributions
of sex, genotype and age to transcriptional variance in Drosophila
melanogaster. Nature Genetics 29: 389-395. Ashton, K., Wagoner, A.-P. Carrillo, R. and Gibson, G. 2001. Quantitative trait loci for neurotransmitter-related traits in Drosophila: heart rate and headless behavior. Genetics 157: 283-294. [Abstract] Palsson, A. and Gibson, G. 2000. Quantitative developmental genetic analysis reveals that the ancestral dipteran wing vein prepattern is conserved in Drosophila melanogaster. Dev. Genes. Evol. 210: 617-622. [Abstract] Zimmerman, E., Palsson, A., and Gibson, G. 2000. Quantitative trait loci affecting components of wing shape in Drosophila melanogaster. Genetics, 155: 671-683. [Abstract] Birdsall, K., Zimmerman, E., Teeter, K. and Gibson, G. 2000. Genetic variation for the positioning of wing veins in Drosophila melanogaster. Evol. Dev. 2: 16-24. [Abstract] Teeter, K., Naeemuddin, M., Gasperini, R., Zimmerman, E., White, K.P., Hoskins, R., and Gibson, G. 2000. Haplotype dimorphism in a SNP collection from Drosophila melanogaster. J. Exp. Zool. 288: 63-75. [Abstract] For more information contact:
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