Variations in gene expression have long been hypothesised to be the major cause of individual differences. An initial focus of this research thesis is to elucidate the genetic regulatory architecture of gene expression. Expression quantitative trait locus (eQTL) mapping analyses have been performed on expression levels of over 22,000 mRNAs from three tissues of a panel of recombinant inbred mice. These analyses are "single-locus" where "linkage" (i.e. significant correlation) between an expression trait and a putative eQTL is considered independently of other loci. Major conclusions from these analyses are: 1. Gene expression is mainly influenced by genetic (sequence) variations that act in trans rather than in cis; 2. Subsets of genes are controlled by master regulators that influence multiple genes; 3. Gene expression is a polygenic trait with multiple regulators. Single-locus mapping analyses are not designed for detecting multiple regulators of gene expression, and so observation of multiple-linkages (i.e. one expression trait mapped to multiple eQTLs) formed the basis of the second objective of this research project: to investigate the relationship between multiple-linkages and genotype pattern-association. A locus-pair is said to have associated genotype patterns if they have similar inheritance pattern across a panel of individuals, and these are attributed to one of fours sources: 1. linkage disequilibrium between loci located on the same chromosome; 2. non-syntenic association; 3. random association; 4. un-associated. To understand the validity of multiple-linkages observed in single-locus mapping studies, a newly developed method, bqtl.twolocus, is applied to confirm two-locus effects for a total of 898 out of 1,233 multiple-linkages identified from the three studies mentioned above as well as from seven publicly available eQTL-mapping studies. Combining these results with information of genotype pattern-association, a subset of 478 multiple-linkages has been deduced for which there is high confidence to be real.
| Identifer | oai:union.ndltd.org:ADTP/187345 |
| Date | January 2007 |
| Creators | Chan, Eva King-Fan, Biotechnology & Biomolecular Science, UNSW |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | http://unsworks.unsw.edu.au/copyright, http://unsworks.unsw.edu.au/copyright |
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