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The Genetics of Physiological Dispersion in Signs of Diabetes Using Murine Models

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The Genetics of Physiological Dispersion in Signs of Diabetes Using Murine Models The Genetics of Physiological Dispersion in Signs of Diabetes Using Murine Models Dayna Brown Department of Biology University of Prince Edward Island Charlottetown, PEI, Canada A thesis submitted in partial fulfilment of the requirements of the Honours Programme in the Department of Biology This Thesis is ___________________________________ Accepted Dean of Science University of Prince Edward Island May 2018 ii ABSTRACT Diabetes is a collection of diseases that affects hundreds of millions of people, with type 2 (T2D) being the most prevalent. The heritability of T2D has yet to be explained, despite many studies. This study aims to determine a piece of the missing heritability by using the newly emerging phenomenon of ‘phenotypic dispersion’ (PD) which refers to genes affecting not only mean effects but also the residual variance within genotypes. The association of loci to residual variance of traits is the method used to determine genes that may contribute to T2D development. Eight in silico mouse data sets were analyzed to test for relationships between mapped microsatellite markers and the PD of diabetic plasma variables (cholesterol, high and low-density lipoprotein, and triglyceride). 29 loci were found to be significantly associated with PD of traits within the data sets. Single nucleotide polymorphisms (SNPs) in genes nearby the associated loci were identified, with Fto, Apoa2, Foxa2, Bpifb6, and Apt1a4 being the most notable genes involved. The association between genotype and PD at all associated loci showed that when the genotype was dominant that it was dominant for low dispersion, which is suggestive of a genetic mechanism controlling the dispersion of traits. These findings suggest that there may be genes that influence the dispersion of traits associated with developing T2D. iii ACKNOWLEDGEMENTS I would like to acknowledge my co-supervisors, Dr. Guy Perry for his continued support and effort throughout the duration of my honours, and Dr. Larry Hale for his guidance and assistance. I truly appreciate the skills and abilities I have gained conducting research under their supervision. My father, Stephen Brown, and my grandmother, Rowena Brown, deserve significant recognition for their unconditional encouragement and support in my education. I am eternally grateful to them for all that they have done for me. I would also like to thank the Biology Department for allowing me to do this honours research, and for making my undergraduate degree the great experience that it was. iv Table of Contents Abstract................................................................................................................................ii Acknowledgments...............................................................................................................iii Table of Contents................................................................................................................iv List of Tables.......................................................................................................................vi List of Figures.....................................................................................................................ix Introduction and Literature Review................................................................................1 Diabetes as a Disease...............................................................................................1 Genetics of Diabetes.................................................................................................2 Materials and Methods......................................................................................................6 In silico data.............................................................................................................7 Ishimori et al. 2004......................................................................................7 Kim et al. 2001............................................................................................8 Li et al. 2008..............................................................................................10 Smith Richards et al. 2002.........................................................................11 Stylianou et al. 2006b.................................................................................13 Stylianou et al. 2006c-e..............................................................................13 Comparison Between Studies.....................................................................15 Statistical Analysis.................................................................................................15 Genomic SNP Targets............................................................................................17 Results................................................................................................................................19 Covariates...............................................................................................................19 Qualitative and Limited Dependent Variable Model.............................................26 Ishimori et al. 2004....................................................................................26 Kim et al. 2001...........................................................................................36 Li et al. 2008..............................................................................................36 Smith Richards et al. 2002.........................................................................40 v Table of Contents Continued Stylianou et al. 2006b.................................................................................40 Stylianou et al. 2006c.................................................................................47 Stylianou et al. 2006d.................................................................................47 Stylianou et al. 20006e...............................................................................47 Gene Candidates.....................................................................................................50 Ishimori et al. 2004....................................................................................50 Li et al. 2008..............................................................................................59 Smith Richards et al. 2002.........................................................................59 Stylianou et al. 2006b.................................................................................68 Discussion........................................................................................................................100 Summary..............................................................................................................104 Literature Cited.................................................................................................................105 vi List of Tables Table 1. Association of multi-locus heterozygosity (MLH) with original and dispersed plasma traits (plasma high-density lipoprotein (pHDL; mg/dl), plasma non-HDL (pnonHDL; mg/dl), plasma cholesterol (pChol; mg/dl) and plasma triglyceride (pTG; mg/dl) in general linear modeling (GLM) in Ishimori et al. 2004........................................................................................................................20 Table 2. Influence of multi-locus heterozygosity (MLH) on original (general linear modeling, GLM) and phenotypic dispersion (PD) (qualitative and limited dependent modeling; QLIM) analysis in traits from Kim et al. 2001. pGlu = plasma glucose (mg/dl), pIns = plasma insulin (ng/ml).........................................21 Table 3. The effects of multi-locus heterozygosity (MLH) on original and phenotypic dispersion (PD) in plasma cholesterol (pChol; mg/dl), plasma high-density lipoprotein (pHDL; mg/dl) and plasma triglyceride (pTG; mg/dl) in Li et al. 2008........................................................................................................................22 Table 4. The association of multi-locus heterozygosity (MLH), paternal grandmother (pgm), and F1 sire with original traits and phenotypic dispersion (PD) in plasma glucose (pGlu; mg/dl) and plasma triglyceride (pTG; mg/dl) from Smith Richards et al. 2002........................................................................................................................23 Table 5. The influence of multi-locus heterozygosity (MLH) and sex on original phenotypic dispersion (PD) traits (plasma triglyceride (pTG; mg/dl), plasma high- density lipoprotein (pHDL; mg/dl) and plasma cholesterol (pChol; mg/dl)) in Stylianou et al. 2006b.............................................................................................24 Table 6. The association of sex and multi-locus heterozygosity (MLH) original traits and phenotypic dispersion (PD) for plasma cholesterol (pChol; mg/dl), plasma high- density lipoprotein (pHDL; mg/dl), plasma triglyceride (pTG; mg/dl) and plasma nonHDL (pnonHDL; mg/dl) from Stylianou et al. 2006c......................................25 Table 7. The association of sex and multi-locus heterozygosity (MLH) with original and dispersive plasma cholesterol (pChol; mg/dl), plasma triglyceride (pTG; mg/dl), plasma high-density lipoprotein (pHDL; mg/dl) and plasma nonHDL (pnonHDL; mg/dl) from Stylianou et al. 2006d........................................................................27 Table 8. The association of sex and multi-locus heterozygosity (MLH) with
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