Plant & Animal Genomes XIV Conference

January 14-18, 2006
Town & Country Convention Center
San Diego, CA

Using Longsage To Study Cereal Gene Expression During Grain Development And Germination

Peter C Bundock , Allison C Crawford , Jessica White , Shane McIntosh , Giovani Cordeiro , Toni Pacey-Miller , Lee Rooke , Linh Nguyen , Gary Ablett , Loraine Watson , Robert J Henry

  Grain Foods CRC Pty Ltd., Centre for Plant Conservation Genetics, Southern Cross University, Lismore NSW 2480 Australia

Many methods of studying gene expression rely on previous knowledge of gene sequences to quantify transcript levels. However the SAGE method samples whatever transcripts are present in a given tissue and time point. In one set of experiments we targeted the development of wheat grain using longSAGE. Developing wheat caryopses were sampled for SAGE analysis at five time points - the first at eight days post anthesis and the last being mature grain (40 dpa). A total of approximately 240,000 longSAGE tags were sequenced across these five time points. In another experiment we have targeted germinating barley grain during the malting process across eight time points. From SAGE libraries made from whole caryopses we have sequenced a total of approximately 200,000 longSAGE tags across these eight time points. The results from longSAGE have revealed the expression patterns of a large number of genes across these two time courses. Results from other SAGE experiments have shown surprising levels of expression from genes that have been poorly characterised and our results are no exception. We have found for example that the most highly abundant SAGE tag in malting barley across the time course, designated B22EL8, has strong homology to metallothionein-like proteins from other plant species. The function of this transcript, as for many others, is but poorly understood. The longSAGE data provides new information on gene expression during these two critical processes in wheat and barley grain. This information should provide new insights and enable useful comparisons with other gene expression data such as that obtained from microarrays and ESTs.