Glycine max
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA151265 | ENA |
REPOSITORIES: ENA
Similar Datasets
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Project description:Genome-Wide Transcript Profiling During Soybean Seed Development and Throughout the Soybean Life Cycle
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Project description:Soybean (Glycine max) seeds are an important source of seed storage compounds, including protein, oil, and sugar used for food, feed, chemical, and biofuel production. We assessed detailed temporal transcriptional and metabolic changes in developing soybean embryos to gain a systems biology view of developmental and metabolic changes and to identify potential targets for metabolic engineering. Two major developmental and metabolic transitions were captured enabling identification of potential metabolic engineering targets specific to seed filling and to desiccation. The first transition involved a switch between different types of metabolism in dividing and elongating cells. The second transition involved the onset of maturation and desiccation tolerance during seed filling and a switch from photoheterotrophic to heterotrophic metabolism. Clustering analyses of metabolite and transcript data revealed clusters of functionally related metabolites and transcripts active in these different developmental and metabolic programs. The gene clusters provide a resource to generate predictions about the associations and interactions of unknown regulators with their targets based on guilt-by-association relationships. The inferred regulators also represent potential targets for future metabolic engineering of relevant pathways and steps in central carbon and nitrogen metabolism in soybean embryos and drought and desiccation tolerance in plants.
2013-12-13 | GSE46153 | GEO
Project description:Gene Expression Changes in the Development of the Soybean Seed-Globular Stage
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Project description:Gene Expression Changes in the Development of the Soybean Seed-Cotyledon Stage
| PRJNA246783 | ENA
Project description:Soybean (Glycine max) seeds are an important source of seed storage compounds, including protein, oil, and sugar used for food, feed, chemical, and biofuel production. We assessed detailed temporal transcriptional and metabolic changes in developing soybean embryos to gain a systems biology view of developmental and metabolic changes and to identify potential targets for metabolic engineering. Two major developmental and metabolic transitions were captured enabling identification of potential metabolic engineering targets specific to seed filling and to desiccation. The first transition involved a switch between different types of metabolism in dividing and elongating cells. The second transition involved the onset of maturation and desiccation tolerance during seed filling and a switch from photoheterotrophic to heterotrophic metabolism. Clustering analyses of metabolite and transcript data revealed clusters of functionally related metabolites and transcripts active in these different developmental and metabolic programs. The gene clusters provide a resource to generate predictions about the associations and interactions of unknown regulators with their targets based on “guilt-by-association” relationships. The inferred regulators also represent potential targets for future metabolic engineering of relevant pathways and steps in central carbon and nitrogen metabolism in soybean embryos and drought and desiccation tolerance in plants. SUBMITTER_CITATION: Biology 2013, 2(4), 1311-1337; doi:10.3390/biology2041311 Changes in RNA Splicing in Developing Soybean (Glycine max) Embryos Delasa Aghamirzaie, Mahdi Nabiyouni, Yihui Fang, Curtis Klumas, Lenwood S. Heath, Ruth Grene and Eva Collakova SUBMITTER_CITATION: Metabolites 2013, 3(2), 347-372; doi:10.3390/metabo3020347 Metabolic and Transcriptional Reprogramming in Developing Soybean (Glycine max) Embryos Eva Collakova, Delasa Aghamirzaie, Yihui Fang, Curtis Klumas, Farzaneh Tabataba, Akshay Kakumanu, Elijah Myers, Lenwood S. Heath and Ruth Grene Total mRNA profiles of 10 time course samples of Soybean developing embryos with three replicates per sample were generated by deep sequencing, using Illumina HiSeq 2000
2013-12-13 | E-GEOD-46153 | biostudies-arrayexpress