147 research outputs found
NanoUPLC-MSE proteomic data assessment of soybean seeds using the Uniprot database.
Background: Recombinant DNA technology has been extensively employed to generate a variety of products from genetically modified organisms (GMOs) over the last decade, and the development of technologies capable of analyzing these products is crucial to understanding gene expression patterns. Liquid chromatography coupled with mass spectrometry is a powerful tool for analyzing protein contents and possible expression modifications in GMOs. Specifically, the NanoUPLC-MSE technique provides rapid protein analyses of complex mixtures with supported steps for high sample throughput, identification and quantization using low sample quantities with outstanding repeatability. Here, we present an assessment of the peptide and protein identification and quantification of soybean seed EMBRAPA BR16 cultivar contents using NanoUPLC-MSE and provide a comparison to the theoretical tryptic digestion of soybean sequences from Uniprot database. Results: The NanoUPLC-MSE peptide analysis resulted in 3,400 identified peptides, 58% of which were identified to have no miscleavages. The experiment revealed that 13% of the peptides underwent in-source fragmentation, and 82% of the peptides were identified with a mass measurement accuracy of less than 5 ppm. More than 75% of the identified proteins have at least 10 matched peptides, 88% of the identified proteins have greater than 30% of coverage, and 87% of the identified proteins occur in all four replicates. 78% of the identified proteins correspond to all glycinin and betaconglycinin chains. The theoretical Uniprot peptide database has 723,749 entries, and 548,336 peptides have molecular weights of greater than 500 Da. Seed proteins represent 0.86% of the protein database entries. At the peptide level, trypsin-digested seed proteins represent only 0.3% of the theoretical Uniprot peptide database. A total of 22% of all database peptides have a pI value of less than 5, and 25% of them have a pI value between 5 and 8. Based on the detection range of typical NanoUPLC-MSE experiments, i.e., 500 to 5000 Da, 64 proteins will not be identified. Conclusions: NanoUPLC-MSE experiments provide good protein coverage within a peptide error of 5 ppm and a wide MW detection range from 500 to 5000 Da. A second digestion enzyme should be used depending on the tissue or proteins to be analyzed. In the case of seed tissue, trypsin protein digestion results offer good databank coverage. The Uniprot database has many duplicate entries that may result in false protein homolog associations when using NanoUPLC-MSE analysis. The proteomic profile of the EMBRAPA BR-16 seed lacks certain described proteins relative to the profiles of transgenic soybeans reported in other works
Transgenic soybean seed as protein expression system: aqueous extraction of recombinant b-glucuronidase.
Recombinant biosynthesis of functional human growth hormone and coagulation factor IX in transgenic soybean seeds.
Edição do Congress of the Brazilian Biotechnology Society, Florianópolis, 2013
Detection and expression analysis of recombinant proteins in plant-derived complex mixtures using nanoUPLC-MSE.
Metabolic engineering of fatty acids from soybean seeds.
Edição do Congress of the Brazilian Biotechnology Society, Florianópolis, 2013
Expression, purification and analysis of the anti-HIV Cyanovirin-N produced in transgenic soybeans seeds.
Edição do Congress of the Brazilian Biotechnology Society, Florianópolis, 2013
Coupling in-depth genome annotations with genome editing technology for harnessing genomic variation to promote precision breeding in tropical soybean.
ABSTRACT: Directional selection during crop domestication and advanced breeding has resulted in significant changes in plant genomes. The extent of intraspecific variation in a crop documents domestication and highlights variants underlying complex traits. Studies demonstrate that most naturally occurring variants in crops are low frequency, and only a small fraction of those might have important functions to trait variation. To understand the inheritance of quantitative traits, diversity panels have become available by crossing inbred lines to produce genomic maps that relate phenotypic variation to recombination and ultimately to genome structure. Using these resources, genomics studies have suggested that selection performs poorly in pericentromeric regions because of reduced recombination frequency (RF). Thus, manipulating RF and meiotic crossover location is an appealing issue to advance crop breeding. In our study, we are using genomic analysis to characterize intragenomic diversity of tropical elite soybean lines in terms of heterozygosity, RF, chromatin structure and accessibility. Our results to date include the generation of draft genome assemblies for two soybean advanced lines using PACBIO long-read sequencing, Chromium Linked-Reads sequencing and an approach rooted in polymer physics that determines the most likely genome structure using chromosomal contact data. In-depth genome-wide characterization is ongoing using ATAC-Seq and Parent-Progeny resequencing. We also present our efforts to apply DNA-free editing tools in implementing genetic alterations that are expected to engineer desirable traits in soybeans by modifying meiotic specific expression. These changes are expected to increase genetic and epigenetic variations with favorable outcomes in seed oil and protein pathway regulation. Financial support: Embrapa-Monsanto Fund/Project:03.17.03.002.00.0
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