Institute of Clinical Science, Imperial College London
Doi
Abstract
This study focuses on integrating and applying computational techniques for modelling
quantitative traits and complex diseases, such as hypertension and diabetes,
using the rat model system and translating the findings to humans. Complex disease
traits are heritable, highly polygenic, and influenced by environmental factors.
Human studies, like Genome Wide Association Studies (GWAS), have identified
many genetic determinants underlying these traits but have provided little information
about the functional effects of these variants and mechanisms regulating
the disease. This study takes a systems-level approach for looking at the genetic
regulation of complex traits in the rat by analysing multiple phenotypes, genomewide
genetic variation and gene expression data in multiple tissues. I integrated
these multi-modality datasets in the BXH/HXB rat Recombinant Inbred (RI)
lines, an established model of the human metabolic syndrome, to identify candidate
genes, pathways and networks associated with complex disease phenotypes. I
evaluated methods for Expression Quantitative Trait Locus (eQTL) analysis and
used sparse Bayesian regression approaches to map eQTLs in the RI lines, delineating
a new, large eQTL data resource for the rat genetic community. I have
also developed and applied signal processing and time series analysis methods to
physiological traits to extract more detailed indices of blood pressure, and integrated
these with genetic, expression and eQTL data to inform on the regulation
of these traits. Then, using publicly available data, I used comparative genomics
approaches to elucidate a set of genes and pathways that can play a role in human
diseases. This study has provided a valuable resource for future work in the rat,
by means of new eQTLs in multiple tissues, and physiological time series phenotypes
and approaches. This has enabled an integrative analysis of these data to
give new insights into the regulation of complex traits in rats and humans