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Genes are the functional units of heredity. However, the functions of many genes remain unknown, which impedes the understanding of the underlying mechanism of complex traits and diseases. Systems genetics approaches try to understand the complexity underlining phenotypic traits using high-throughput experimental and computational approaches. In this thesis, I describe a list of novel systems genetics approaches to identify gene functions based on publicly available datasets. In Chapter 2, I focused on the multi-omics datasets collected from the BXD mouse cohort, which is one of the most studied mouse genetic reference populations. Over the past 40 years, the BXD community has generated tremendous amounts of data covering different omics layers, making the BXD GRP a perfect data source to conduct systems genetics analyses to discover biological insights. By integrating the data from different omics layers, I developed phenome-wide association study (PheWAS) and expression-based PheWAS (ePheWAS) to reveal the associations between genes and phenotypic traits, as well as mediation and reverse-mediation analysis to identify the regulatory connections between genes. In Chapter 3, I analyzed the transcriptome datasets from six different model organisms, ranging from yeast to human. It is commonly believed that genes with similar functions tend to have similar expression patterns. Therefore by using the co-expression patterns of genes, one can annotate a gene from its correlating genes with known functions. I proposed here a new systems genetics method, termed gene-module association determination (G-MAD), which assigns novel functions of genes and proposes new components of pathway modules. Several new associations, including DDT as a novel mitochondrial protein, were experimentally validated. In addition, G-MAD was further extended to determine the interconnection between pathway modules, for example those between mitochondria and proteasome, as well as ribosome and lipid biosynthesis. Altogether, this thesis described several novel systems genetics approaches to identify the associations between genes, pathway modules, phenotypic traits, and diseases. The approaches and data described in this thesis have been deposited in a publicly accessible web source at, and will hopefully facilitate the identification of new gene functions.