A screen for modifiers of epigenetic reprogramming

Epigenetic modifiers are the proteins involved in establishing and maintaining the epigenome of an organism. They are particularly important for development. Changes in epigenetic modifiers have been shown be lethal, or cause diseases. Our laboratory has developed an ENU mutagenesis screen to produce mouse mutants displaying altered epigenetic gene silencing. The screen relies on a GFP transgene that is expressed in red blood cells in a variegated manner. In the orginal transgenic FVB mice expression occurs in approximately 55% of red blood cells. During the course of my Masters, I characterised four different Mommes (Modifiers of murine metastable epiallele), MommeD32, MommeD33, MommeD35 and MommeD36. For each Momme, I identified the underlying mutation, and observed the corresponding phenotype. In MommeD32 the causative mutation is in Dnmt1, (DNA methyltransferase 1). This gene was previously identified in the screen, as MommeD2, and the new allele, MommeD32 has a change in the BAH domain of the protein. MommeD33 is the result of a change at the transgene itself. MommeD35 carries a mutation in Suv39h1 (suppressor of variegation 3-9 homolog 1). This gene has not previously been identified in the screen, but it is a known epigenetic modifier. MommeD36 had the same ENU treated sire as MommeD32, and I found that it has the same mutation as MommeD32. These mutant strains provide valuable tools that can be used to further our knowledge of epigenetic reprogramming. An example being the cancer study done with MommeD9 which has a mutation in Trim28. By crossing MommeD9+/- mutant mice with Trp53+/- mice, it can be seen if Trim28 has an effect on the rate of tumour genesis. However no clear effect of Trim28 haploinsufficiency can be observed in Trp53+/- mice.

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment This fraction is the result of undesirable genotype-by-environment interactions (G x E) and measured by the genetic correlation (r(g)) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of G x E over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels