Imprinting status of type III iodothyronine deiodinase in cattle as QTL candidate for birthweight
This project aims to determine if the bovine type III iodothyronine deiodinase gene (DIO3) is imprinted - i.e. is expressed only from the paternally inherited allele as described for mouse.
The research will also analyse effects of imprinted DIO3 alleles on birthweight in a Droughtmaster resource population.
Thyroid hormones are essential regulators of pre and postnatal growth and development. Three deiodinases, type I, II, and III, contribute to activation and inactivation of the initially released hormone precursor T4 (thyroxine) into the biologically active T3 (triiodothyronine) or the inactive rT3 (reverse triiodothyronine). Inactivation of T4 by conversion into rT3 is particularly important during prenatal development.
Type III iodothyronine deiodinase (DIO3) converts T4 into rT3 and is pivotal for fetal growth regulation. The DIO3 gene in cattle is localised in a QTL region for birth weight and the gene is subject to genomic imprinting with expression from the paternal allele only in mouse.
Our real-time qPCR data from fetal tissue of purebred and reciprocal cross Angus and Brahman fetuses show genetic effects consistent with imprinting of DIO3, but allele-specific imprinted expression has not been demonstrated.
A SNP that can be used to track parent-of-origin specific allelic expression, i.e., demonstrate imprinting, and test QTL effects on birth weight and other traits in our Droughtmaster resource population has been identified.
- You will gain an understanding of endocrine factors and (epi)genetic mechanisms controlling prenatal growth and its impact on postnatal outcomes.
- Standard molecular tools such as PCR and restriction enzyme digests as well as more advanced techniques such as pyrosequencing will be applied to obtain data.
- Allelic effects will be validated and quantified using linear models in SPSS or SAS.
Study animal and veterinary bioscience
We focus on identification of non-mendelian genetic and epigenetic components in the molecular architecture of quantitative traits. We uncover novel epigenetic and genetic effects on prenatal growth and their interactions with environmental factors.
This allows us to identify and to develop new (epi)genetic markers and approaches to achieve optimal programming outcomes at birth that impact on postnatal health and performance.