Molecular genetic analyses of extracellular signaling pathways during murine retinal development

Extracellular signaling pathways initiated by secreted proteins are important in the co-ordination of tissue interactions in multi-cellular organisms, particularly during embryonic development. These signaling cascades direct diverse cellular events, including proliferation, differentiation and migration, in both autocrine and paracrine modes. In adult animals, abnormal function of these proteins often results in degenerative and tumourigenic syndromes. In this study, I have focused on elucidating the role of Bone Morphogenetic Protein (Bmp) signal transduction during neuronal specification and differentiation in the vertebrate embryo, using the mouse retina as a model. Using tissue-specific conditional knock-out approaches, the consequences of genetic loss-of-function of this signaling pathway on retinal physiology were examined. Mutant mice lacking Bmp type I receptor function displayed a range of retinal phenotypes, each of which appeared to be regulated at a different threshold of Bmp receptor activity. Novel essential functions for Bmp signaling were uncovered for retinal neurogenesis, cell survival, and axonal pathfinding at the optic disc. Further, BmprIa and BmprIa exhibited genetic interactions suggestive of functional redundancy. To further characterize the underlying molecular bases for the pleiotropic effects of Bmp receptors, retina-specific loss-of-function mutants of the obligate Bmp-activated transcriptional mediator Smad4 were generated. A comparison of the retina-specific Smad4 mutant phenotypes with those of the Bmp receptor mutant retina revealed that only a subset of retinal phenotypes, namely optic disc axon pathfinding and axial patterning were common for both classes of mutant animals. Thus, these results suggest that, contrary to the classic scheme of Bmp signal transduction, Smad4-independent pathways may be operative downstream of the type I receptors. Indeed, such alternative intracellular signaling cascades may constitute a molecular basis for the multiple cellular responses elicited by Bmp signaling. Finally, I tested whether the potential Bmp pathway targets, the extracellular ligands Fgf9 and Fgf15, mediate essential cellular processes in the retina. The analyses of Fgf9 −/−; Fgf15−/− mutant mice posit a novel shared role for these genes in intra-retinal axon pathfinding. Collectively, these studies have elucidated part of the molecular machinery directing mammalian neuro-retinal development, and provided useful in vivo models to study visual function. ^

DNA incisions stimulate genetic instability of triplet repeat sequences related to human hereditary neurological diseases

The molecular mechanisms responsible for the expansion and deletion of trinucleotide repeat sequences (TRS) are the focus of our studies. Several hereditary neurological diseases including Huntington's disease, myotonic dystrophy, and fragile X syndrome are associated with the instability of TRS. Using the well defined and controllable model system of Escherichia coli, the influences of three types of DNA incisions on genetic instability of CTG•CAG repeats were studied: DNA double-strand breaks (DSB), single-strand nicks, and single-strand gaps. The DNA incisions were generated in pUC19 derivatives by in vitro cleavage with restriction endonucleases. The cleaved DNA was then transformed into E. coli parental and mutant strains. Double-strand breaks induced deletions throughout the TRS region in an orientation dependent manner relative to the origin of replication. The extent of instability was enhanced by the repeat length and sequence (CTG•CAG vs. CGG•CCG). Mutations in recA and recBC increased deletions, mutations in recF stabilized the TRS, whereas mutations in ruvA had no effect. DSB were repaired by intramolecular recombination, versus an intermolecular gene conversion or crossover mechanism. 30 nt gaps formed a distinct 30 nt deletion product, whereas single strand nicks and gaps of 15 nts did not induce expansions or deletions. Formation of this deletion product required the CTG•CAG repeats to be present in the single-stranded region and was stimulated by E. coli DNA ligase, but was not dependent upon the RecFOR pathway. Models are presented to explain the DSB induced instabilities and formation of the 30 nucleotide deletion product. In addition to the in vitro creation of DSBs, several attempts to generate this incision in vivo with the use of EcoR I restriction modification systems were conducted. ^

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.