Project description:The diurnal transcriptome of field-grown Glycine max was investigated in relation to diurnal physiological processes in the field and compared to diurnal transcription data from growth chamber studies
Project description:Cytosine methylation is a base modification that is often used by genomes to store information that is stably inherited through mitotic cell divisions. Most cytosine DNA methylation is stable throughout different cell types or by exposure to different environmental conditions in plant genomes. Here, we profile the epigenomes of ~100 Glycine max lines to explore the extent of natural epigenomic variation. We also use these data to determine the extent to which DNA methylation variants are linked to genetic variations.
Project description:Two Near Isogenic soybean (Glycine max) lines were grown in hydroponic conditions with either 50uM ferric nitrate or 100uM ferric nitrate. After 10 days, half the plants were harvested (total root tissue). At 12 days after planting, iron was added to plants grown in low iron conditions bringing them up to sufficient iron growth conditions. Root tissue was harvested for the remaining plants at 14 days after planting. Gene expression analysis from root tissue of two Near Isogenic Lines (NILs), Clark (PI548553) and IsoClark (PI547430), grown in iron stress or iron stress recovered conditions.
Project description:The temporal expression profile of Glycine max seeds was carried out to identify genes that are differentially expressed (DE) during seed development. Using the Affymetrix chip, we have for the first time provided a holistic view of the transcriptional landscape during seed development in four different developmental stages in Glycine max. cv. Pusa 16. The analysis of the differential expression patterns and functional category enrichment of DE genes highlighted specific and common significant coordination and enrichment of various biological processes during seed development which have led to the identification of few candidate genes related to inositol metabolism and especially in phytate biosynthesis. In conclusion, we have shown here a logical approach to identify possible candidate genes for fine tuning the metabolic flux for phytate generation, which may be altered by metabolic engineering in developing a low phytate phenotype.
