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

Project description:Background: Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is the most devastating pathogen of soybean. Many gene expression profiling studies have been conducted to investigate the responses of soybean to the infection by this pathogen using primarily the first-generation soybean genome array that covered approximately 37,500 soybean transcripts. However, no study has been reported yet using the second-generation Affymetrix soybean whole-genome transcript array (Soybean WT array) that represents approximately 66,000 predicted soybean transcripts. Results: In the present work, the gene expression profiles of two soybean plant introductions (PIs) PI 437654 and PI 567516C (both resistant to multiple SCN races) and cultivar (cv.) Magellan (susceptible to SCN) were compared in the presence or absence of the SCN inoculum at different time points (3 and 8 days post-inoculation). For this purpose, the Soybean WT array, which covers many more predicted soybean transcripts than the first-generation Affymetrix soybean array, was employed. Data analysis revealed that the two resistant soybean lines showed distinctive gene expression profiles from each other and from Magellan not only in response to the SCN inoculation, but also in the absence of SCN. Overall, 1,413 genes and many pathways, such as defense and hormonal pathways, were revealed to be differentially regulated. Among them, 297 genes were constitutively regulated in the two resistant lines (compared with cv. Magellan) and 1,146 genes were responsive to the SCN inoculation in the three lines, with 30 genes regulated both constitutively and by SCN. In addition to the findings similar to those in the published work, many genes involved in ethylene, protein degradation, and phenylpropanoid pathways were also revealed differentially regulated in the present study. GC-rich elements (e.g., GCATGC) were found over-represented in the promoter regions of certain groups of genes. These have not been observed before, and could be new defense-responsive regulatory elements. Conclusions: Different soybean lines showed different gene expression profiles in the presence and absence of the SCN inoculum. Both inducible and constitutive gene expression may contribute to resistance to multiple SCN HG Types in the resistant soybean PI lines. Ethylene, protein degradation, and phenylpropanoid pathways, as well as many other pathways reported previously, may play important roles in mediating the soybean-SCN interactions. The revealed genes, pathways, and promoter elements can be further explored to regulate or engineer soybean for resistance to SCN. Three soybean lines were compared in the study: Magellan (susceptible to SCN), PI 437654 (PI654; resistant to SCN), and PI 567516C (PI516C; resistant to SCN). Overall, thirty samples, including two biological replicates for each sample, were analyzed.

Project description:Background: Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is the most devastating pathogen of soybean. Many gene expression profiling studies have been conducted to investigate the responses of soybean to the infection by this pathogen using primarily the first-generation soybean genome array that covered approximately 37,500 soybean transcripts. However, no study has been reported yet using the second-generation Affymetrix soybean whole-genome transcript array (Soybean WT array) that represents approximately 66,000 predicted soybean transcripts. Results: In the present work, the gene expression profiles of two soybean plant introductions (PIs) PI 437654 and PI 567516C (both resistant to multiple SCN races) and cultivar (cv.) Magellan (susceptible to SCN) were compared in the presence or absence of the SCN inoculum at different time points (3 and 8 days post-inoculation). For this purpose, the Soybean WT array, which covers many more predicted soybean transcripts than the first-generation Affymetrix soybean array, was employed. Data analysis revealed that the two resistant soybean lines showed distinctive gene expression profiles from each other and from Magellan not only in response to the SCN inoculation, but also in the absence of SCN. Overall, 1,413 genes and many pathways, such as defense and hormonal pathways, were revealed to be differentially regulated. Among them, 297 genes were constitutively regulated in the two resistant lines (compared with cv. Magellan) and 1,146 genes were responsive to the SCN inoculation in the three lines, with 30 genes regulated both constitutively and by SCN. In addition to the findings similar to those in the published work, many genes involved in ethylene, protein degradation, and phenylpropanoid pathways were also revealed differentially regulated in the present study. GC-rich elements (e.g., GCATGC) were found over-represented in the promoter regions of certain groups of genes. These have not been observed before, and could be new defense-responsive regulatory elements. Conclusions: Different soybean lines showed different gene expression profiles in the presence and absence of the SCN inoculum. Both inducible and constitutive gene expression may contribute to resistance to multiple SCN HG Types in the resistant soybean PI lines. Ethylene, protein degradation, and phenylpropanoid pathways, as well as many other pathways reported previously, may play important roles in mediating the soybean-SCN interactions. The revealed genes, pathways, and promoter elements can be further explored to regulate or engineer soybean for resistance to SCN.

Project description:The transcriptome, proteome and metabolome of 16 S.cerevisiae backgrounds, combinatorially perturbed in HIS3, LEU2, URA3 and MET15strains are compared. The project was jointly supervised by Kathryn Lilley and Markus Ralser. Transcriptome data has been deposited at ArrayExpress under accession <a href="http://www.ebi.ac.uk/microarray-as/aer/result?queryFor=Experiment&eAccession=E-MTAB-3991">E-MTAB-3991</a>. Metabolome data has been deposited at Metabolights with accession number <a href="http://www.ebi.ac.uk/metabolights/MTBLS168">MTBLS168</a>. The regulation of gene expression in response to nutrient availability is fundamental to the genotype–phenotype relationship. The metabolic–genetic make-up of the cell, as reflected in auxotrophy, is hence likely to be a determinant of gene expression. Here, we address the importance of the metabolic–genetic background by monitoring transcriptome, proteome and metabolome in a repertoire of 16 Saccharomyces cerevisiae laboratory backgrounds, combinatorially perturbed in histidine, leucine, methionine and uracil biosynthesis. The metabolic background affected up to 85% of the coding genome. Suggesting widespread confounding, these transcriptional changes show, on average, 83% overlap between unrelated auxotrophs and 35% with previously published transcriptomes generated for non-metabolic gene knockouts. Background-dependent gene expression correlated with metabolic flux and acted, predominantly through masking or suppression, on 88% of transcriptional interactions epistatically. As a consequence, the deletion of the same metabolic gene in a different background could provoke an entirely different transcriptional response. Propagating to the proteome and scaling up at the metabolome, metabolic background dependencies reveal the prevalence of metabolism-dependent epistasis at all regulatory levels. Urging a fundamental change of the prevailing laboratory practice of using auxotrophs and nutrient supplemented media, these results reveal epistatic intertwining of metabolism with gene expression on the genomic scale.

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MetaboLights MTBLS117 - GNPS A Metabolic Profiling Strategy for the Dissection of Plant Defense against Fungal Pathogens (DI-MS assays)

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A metabolic profiling strategy for the dissection of plant defense against fungal pathogens.

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