Genetic Regulation of Grain Quality in Cereals
Dr Sinead Drea
Dr E Mallon
Applications accepted all year round
Self-Funded PhD Students Only
Cereal grain quality is a complex trait that determines yield and end uses (as feed, flour, germplasm etc.). It is influenced by intrinsic factors including the compositional profile of starch and protein within the grain’s endosperm. Despite extensive knowledge about cereal grain protein and starch metabolism we know relatively little about its regulation, particularly in temperate climate cereals such as wheat. If we can establish detailed accounts of the regulatory mechanisms of genes in storage protein and starch metabolism, we will be able to examine variations in regulatory processes between cultivars and species and explain variation in quality profiles with the ultimate possibility of being able to manipulate them.
Our hypothesis is therefore that variation in the regulation of genes in storage protein and starch metabolism between cultivars and species could explain variation in quality profiles. To assess regulatory variation we focus on candidate Transcription Factors (TFs) and examine sequence, phylogeny, gene expression and function of these TFs in diverse cereals.
The grain of cereals is a unique fruit form restricted to the grass family, the Poaceae. In the cultivated cereals we can see how this fruit type has been sculpted by artificial selection through agriculture and domestication. In this era of genomics and transcriptomics we propose that specific regulators of distinctive features of grain biology – particularly those influencing nutrition and quality – can be identified by a combination of phylogenomics and transcriptomics i.e., TFs with patterns of duplication/loss distinctive to Poaceae and expressed during grain maturation. To this end we will use the PlantTFDB, Ensembl Plants, Phytozome databases as starting points for obtaining sequence data for analysis. We will use Arabidopsis as a reference species in the core eudicots and include rice, maize, Sorghum, barley, wheat and Brachypodium from the Poaceae family in addition to the non-grass monocot Phoenix dactylifera (date palm; Arecaceae). Inclusion of a monocot outside of the Poaceae will help us distinguish between patterns of duplication/loss in Poaceae specifically. Using these taxa will also facilitate the identification of TFs that are not only phylogenetically distinctive in cereals generally but to the Pooideae subfamily and even the Triticeae tribe containing wheat and barley specifically.
TFs will be further classified by their expression patterns in grain development in Brachypodium, using our own data, and in wheat using extensive published expression data. Our work on Brachypodium, a related but uncultivated temperate grass with an extensive molecular toolkit, has proved an invaluable point of comparison for cultivated crops, providing insights in the evolution of the grain and into the genetic basis of characters essential to grain quality and yield. Using existing wheat genome/transcriptome data and our own rye grain transcriptome (assembled in collaboration with Eamonn Mallon) we will identify genome specific orthologues of genes and conduct detailed spatial and temporal expression profiles in hexaploid, tetraploid, diploid wheats as well as rye and Triticale (rye/wheat hybrid). All have very different grain quality profiles which determines their uses in food production (e.g., bread, pasta, animal feeds). Expression analyses will involve detailed interrogation of transcriptomic data from several species, RT-PCR and tissue-specific assays using mRNA in situ hybridization.
We have adopted this approach in an ongoing PhD project in the lab with the focus on two TFs of central importance in starch and protein metabolic regulation in cereals: the OPAQUE2 TF regulating storage protein gene expression and an AP2/ERF TF shown recently to regulate starch accumulation in rice grains. Therefore this PhD project provides an opportunity for a keen researcher to start learning techniques and collecting data immediately.
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FTE Category A staff submitted: 37.40
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