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Glycine max

ABSTRACT: Complementary genetic and genomic approaches help characterize the linkage group I seed protein QTL

PROVIDER: PRJNA79599 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR037388.fastq.gz	Fastqsanger.gz
	SRR037389.fastq.gz	Fastqsanger.gz
	SRR037390.fastq.gz	Fastqsanger.gz
	SRR037391.fastq.gz	Fastqsanger.gz
	SRR037392.fastq.gz	Fastqsanger.gz

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Glycine max strain:93B15 Transcriptome or Gene expression

Project description:The seed coat is a vital tissue for directing nutrient supply to the embryo and cotyledons during development. By forming a sucrose gradient, the seed coat promotes transport of sugars from source leaves to seeds, thereby increasing sink strength. Understanding how gene regulation in sink tissue is altered by climate change factors will help elucidate the role these genes play in determining yield. This project aims to determine how elevated temperature, drought and ozone alter gene expression in the seed coat. Overall this study discovered high abundance seed coat specific genes, which may be candidates for functional genomic analysis in the future.

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Project description:Methylation Changes During Soybean Seed Development

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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.

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