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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/28327
Title: An analysis of complex trait variation using Drosophila melanogaster
Authors: Neves, Amanda
Advisor: Dworkin, Ian
Department: Biology
Keywords: complex traits;quantitative genetics;drosophila melanogaster;genotype-phenotype map;bioinformatics;multivariate statistics
Publication Date: 2022
Abstract: Complex traits are traits which vary quantitatively along a normal distribution. Their variation is influenced by many loci throughout the genome, each contributing a small fraction to trait heritability. Complex traits are also shaped by gene-gene interactions between focal alleles with genetic modifiers, as well as gene-environment interactions. In this thesis, I study complex traits from multiple angles using Drosophila melanogaster as a model system. First, the relationship between variation in gene expression in developing wing tissue and variation in adult wing shape is assessed, where the complex trait in question is wing shape. Using gene wise multivariate linear models, I show that at the level of natural variation, no single gene’s variation in expression has a “significant” effect on variation in wing shape. When genes are grouped into functional categories using Gene Ontology (GO) terms, I show that not only can the signal of effect be recovered, but also that genes from within a GO term group have similar effects on wing shape even when accounting for correlations in gene expression between genes. I also study gene expression and trait expressivity and penetrance under a complex trait framework. An sd/vg allelic series is used to study the joint effect of genetic background and the magnitude of allelic perturbation on global gene expression in the developing wing tissue. I show that global transcriptional variation is largely correlated with wildtype genetic background, and not with strength of perturbation as might have been expected. Further, variation in cell shape or cell size are shown to be candidate mechanisms contributing to background-dependent phenotypic variation, and specific genes are suggested for follow-up functional analysis.
URI: http://hdl.handle.net/11375/28327
Appears in Collections:Open Access Dissertations and Theses

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