January 12-16, 2008
Town & Country Convention Center
San Diego, CA
BABU VALLIYODAN1 , Huong Tran1 , Trupti Joshi2 , Jeremy Schmutz3 , Marc Libault1 , Gary Stacey1 , Robert E. Sharp1 , Dong Xu3 , Henry T. Nguyen1
Drought is the major abiotic stress factor limiting crop productivity worldwide and in the US. It is reported that the average yield losses are more than 40% in soybean due to drought stress. The efforts to understand the physiological mechanisms and the genetic dissection of the drought stress responses in legumes, especially in soybean are still in the early stages. A better understanding of abiotic stress tolerance mechanisms at gene, protein and metabolite levels are pre-requisite for the gene discovery and further crop improvement. Our research program focuses on an integrated functional genomics approach using soybean seedling as a model to dissect the molecular processes from transcriptome to phenome. Previous work showed that the soybean primary root adapts to low water potential (-1.6 MPa) by maintaining longitudinal expansion in the apical 4 mm (region 1), whereas in the adjacent 4 mm (region 2) longitudinal expansion reaches a maximum in well-watered roots but is progressively inhibited at low water potential. To identify mechanisms that determine these responses to low water potential, and to elucidate the regulatory networks involved, we have profiled the transcript expression in these regions of water-stressed and well-watered roots. Also, we have compared the gene expression between region 2 of water-stressed roots and the growth deceleration zone in well-watered roots (region 3) to sort out stress-responsive genes in region 2 from those involved in cell maturation. We have identified several root region specific and stress responsive transcripts. The substantial difference in gene expression pattern between the later stage (48 h) and early stage (5 h) of water deficits, and the major metabolic and transcriptional regulatory pathway responses to water deficit conditions will be discussed. The differentially expressed transcripts will be compared to the available soybean genome sequence information.