Glycine max
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA277363 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1840400.fastq.gz | Fastqsanger.gz | |||
| SRR1840410.fastq.gz | Fastqsanger.gz | |||
| SRR1840401.fastq.gz | Fastqsanger.gz | |||
| SRR1840411.fastq.gz | Fastqsanger.gz | |||
| SRR1840402.fastq.gz | Fastqsanger.gz |
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Project description:Background: Pollen, the male partner in the reproduction of flowering plants, comprises either two or three cells at maturity. The current knowledge of the pollen transcriptome is limited to the model plant Arabidopsis thaliana, which has tri-cellular pollen grains at maturity. Comparative studies on pollen of other genera, particularly crop plants, are needed to understand the pollen gene networks that are subject to functional and evolutionary conservation. In this study, we used the Affymetrix Soybean GeneChip® to perform transcriptional profiling on mature bi-cellular soybean pollen. Results: Compared to the sporophyte transcriptome, the soybean pollen transcriptome revealed a restricted and unique repertoire of genes, with a significantly greater proportion of specifically expressed genes than is found in the sporophyte tissue. Comparative analysis shows that, among the 37,500 soybean unique transcripts addressed in this study, 10,299 genes (27.46%) are expressed in pollen. Of the pollen-expressed genes, about 9,489 (92.13%) are also expressed in sporophytic tissues, and 810 (7.87%) are selectively expressed in pollen. Overall, the soybean pollen transcriptome shows an enrichment of transcription factors (mostly zinc finger family proteins), cell cycle-related transcripts, signal recognition receptors, ethylene responsive factors, chromatin remodeling factors, and members of the ubiquitin proteasome proteolytic pathway. Moreover, we identify several new pollen-specific candidate genes that might play a significant role in pollen biology. Conclusion: This is the first report of a soybean pollen transcriptional profile. These data extend our current knowledge regarding regulatory pathways that govern the gene regulation and development of pollen. We also demonstrate that pollen is a rich store of regulatory proteins that are essential and sufficient for de novo gene expression. A comparison between transcription factors up-regulated in soybean and those upregulated in Arabidopsis revealed some divergence in the numbers and kinds of regulatory proteins expressed in both species.
2009-03-26 | GSE12286 | GEO
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: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