Logo image
Quantitative genetic models for genomic imprinting
Doctoral Thesis   Open access

Quantitative genetic models for genomic imprinting

Anna Wensley Santure
Doctor of Philosophy - PhD, University of Otago
University of Otago
2006
Handle:
https://hdl.handle.net/10523/6193

Abstract

A gene is imprinted when its expression is dependent on the sex of the parent from which it was inherited. An increasing number of studies are suggesting that imprinted genes have a major influence on medically, agriculturally and evolutionarily important traits, such as disease severity and livestock production traits. While some genes have a large effect on the traits of an individual, quantitative characters such as height are influenced by many genes and by the environment, including maternal effects. The interaction between these genes and the environment produces variation in the characteristics of individuals. Many quantitative characters are likely to be influenced by a small number of imprinted genes, but at present there is no general theoretical model of the quantitative genetics of imprinting incorporating multiple loci, environmental effects and maternal effects. This research develops models for the quantitative genetics of imprinting incorporating these effects, including deriving expressions for genetic variation and resemblances between relatives. Imprinting introduces both parent-of-origin and generation dependent differences in the derivation of standard quantitative genetic models that are generally equivalent under Mendelian expression. Further, factors such as epistasis, maternal effects and interactions between genotype and environment may mask the effect of imprinting in a quantitative trait. Maternal effects may also mimic a number of signatures in variance and covariance components that are expected in a population with genomic imprinting. This research allows a more comprehensive understanding of the processes influencing an individual’s characteristics.
pdf
SantureAnna2006PhD.pdfDownloadView
PhD thesis Open Access All Rights Reserved

Metrics

217 File views/ downloads
551 Record Views

Details

Logo image