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Identification of differentially expressed genes between developing seeds of different soybean cultivars.

ABSTRACT: Soybean is a major source of protein and oil and a primary feedstock for biodiesel production. Research on soybean seed composition and yield has revealed that protein, oil and yield are controlled quantitatively and quantitative trait loci (QTL) have been identified for each of these traits. However, very limited information is available regarding the genetic mechanisms controlling seed composition and yield. To help address this deficiency, we used Affymetrix Soybean GeneChips® to identify genes that are differentially expressed between developing seeds of the Minsoy and Archer soybean cultivars, which differ in seed weight, yield, protein content and oil content. A total of 700 probe sets were found to be expressed at significantly different (defined as having an adjusted p-value below or equal to 0.05 and an at least 2-fold difference) levels between the two cultivars at one or more of the three developmental stages and in at least one of the two years assayed. Comparison of data from soybeans collected in two different years revealed that 97 probe sets were expressed at significantly different levels in both years. Functional annotations were assigned to 78% of these 97 probe sets based on the SoyBase Affymetrix™ GeneChip® Soybean Genome Array Annotation. Genes involved in receptor binding/activity and protein binding are overrepresented among the group of 97 probe sets that were differentially expressed in both years assayed. Probe sets involved in growth/development, signal transduction, transcription, defense/stress response and protein and lipid metabolism were also identified among the 97 probe sets and their possible implications in the regulation of agronomic traits are discussed. As the Minsoy and Archer soybean cultivars differ with respect to seed size, yield, protein content and lipid content, some of the differentially expressed probe sets identified in this study may thus play important roles in controlling these traits. Others of these probe sets may be involved in regulation of general seed development or metabolism. All microarray data and expression values after GCRMA are available at the Gene Expression Omnibus (GEO) at NCBI (http://www.ncbi.nlm.nih.gov/geo), under accession number GSE21598.

SUBMITTER: Lin R

PROVIDER: S-EPMC4664686 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Identification of differentially expressed genes between developing seeds of different soybean cultivars.

Lin Rongshuang R Glazebrook Jane J Katagiri Fumiaki F Orf James H JH Gibson Susan I SI

Genomics data 20150813

Soybean is a major source of protein and oil and a primary feedstock for biodiesel production. Research on soybean seed composition and yield has revealed that protein, oil and yield are controlled quantitatively and quantitative trait loci (QTL) have been identified for each of these traits. However, very limited information is available regarding the genetic mechanisms controlling seed composition and yield. To help address this deficiency, we used Affymetrix Soybean GeneChips® to identify gen ...[more]

PMID: 26697344

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Project description:Soybean is one of the important economic crops, which supplies a great deal of vegetable oil and proteins for human. The content of nutrients in different soybean seeds is different, which is related to the expression of multiple genes, but the mechanisms are complicated and still largely uncertain. In this study, to reveal the possible causes of the nutrients difference in soybeans A7 (containing low oil and high protein) and A35 (containing high oil and low protein), RNA-seq technology was performed to compare and identify the potential differential expressed genes (DEGs) at different seed developmental stages. The results showed that DEGs mainly presented at the early stages of seeds development and more DEGs were up-regulated at the early stage than the late stages. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that the DEGs have diverged in A7 and A35. In A7, the DEGs were mainly involved in cell cycle and stresses, while in A35 were the fatty acids and sugar metabolism. Specifically, when the DEGs contributing to oil and protein metabolic pathways were analyzed, the differences between A7 and A35 mainly presented in fatty acids metabolism and seeds storage proteins (SSPs) synthesis. Furthermore, the enzymes, fatty acid dehydrogenase 2, 3-ketoacyl-CoA synthase and 9S-lipoxygenase, in the synthesis and elongation pathways of fatty acids, were revealed probably to be involved in the oil content difference between A7 and A35, the SSPs content might be due to the transcription factors: Leafy Cotyledon 2 and Abscisic acid-intensitive 3, while the sugar transporter, SWEET10a, might contribute to both oil and protein content differences. Finally, six DEGs were selected to analyze their expression using qRT-PCR, and the results were consistent with the RNA-seq results. Generally, the study provided a comprehensive and dynamic expression trends for the seed development processes, and uncovered the potential DEGs for the differences of oil in A7 and A35.

Project description:Osteocytes represent the most abundant cellular component of mammalian bones with important functions in bone mass maintenance and remodeling. To elucidate the differential gene expression between osteoblasts and osteocytes we completed a comprehensive analysis of their gene profiles. Selective identification of these two mature populations was achieved by utilization of visual markers of bone lineage cells. We have utilized dual GFP reporter mice in which osteocytes are expressing GFP (topaz) directed by the DMP1 promoter, while osteoblasts are identified by expression of GFP (cyan) driven by 2.3 kb of the Col1a1 promoter. Histological analysis of 7-day-old neonatal calvaria confirmed the expression pattern of DMP1GFP in osteocytes and Col2.3 in osteoblasts and osteocytes. To isolate distinct populations of cells we utilized fluorescent activated cell sorting (FACS). Cell suspensions were subjected to RNA extraction, in vitro transcription and labeling of cDNA and gene expression was analyzed using the Illumina WG-6v1 BeadChip. Following normalization of raw data from four biological replicates, 3444 genes were called present in all three sorted cell populations: GFP negative, Col2.3cyan(+) (osteoblasts), and DMP1topaz(+) (preosteocytes and osteocytes). We present the genes that showed in excess of a 2-fold change for gene expression between DMP1topaz(+) and Col2.3cyan(+) cells. The selected genes were classified and grouped according to their associated gene ontology terms. Genes clustered to osteogenesis and skeletal development such as Bmp4, Bmp8a, Dmp1, Enpp1, Phex and Ank were highly expressed in DMP1topaz(+)cells. Most of the genes encoding extracellular matrix components and secreted proteins had lower expression in DMP1topaz(+) cells, while most of the genes encoding plasma membrane proteins were increased. Interestingly a large number of genes associated with muscle development and function and with neuronal phenotype were increased in DMP1topaz(+) cells, indicating some new aspects of osteocyte biology. Although a large number of genes differentially expressed in DMP1topaz(+) and Col2.3cyan(+) cells in our study have already been assigned to bone development and physiology, for most of them we still lack any substantial data. Therefore, isolation of osteocyte and osteoblast cell populations and their subsequent microarray analysis allowed us to identify a number or genes and pathways with potential roles in regulation of bone mass.

Project description:BackgroundThe necrogenic enterobacterium, Erwinia amylovora is the causal agent of the fire blight (FB) disease in many Rosaceae species, including apple and pear. During the infection process, the bacteria induce an oxidative stress response with kinetics similar to those induced in an incompatible bacteria-plant interaction. No resistance mechanism to E. amylovora in host plants has yet been characterized, recent work has identified some molecular events which occur in resistant and/or susceptible host interaction with E. amylovora: In order to understand the mechanisms that characterize responses to FB, differentially expressed genes were identified by cDNA-AFLP analysis in resistant and susceptible apple genotypes after inoculation with E. amylovora.ResultscDNA were isolated from M.26 (susceptible) and G.41 (resistant) apple tissues collected 2 h and 48 h after challenge with a virulent E. amylovora strain or mock (buffer) inoculated. To identify differentially expressed transcripts, electrophoretic banding patterns were obtained from cDNAs. In the AFLP experiments, M.26 and G.41 showed different patterns of expression, including genes specifically induced, not induced, or repressed by E. amylovora. In total, 190 ESTs differentially expressed between M.26 and G.41 were identified using 42 pairs of AFLP primers. cDNA-AFLP analysis of global EST expression in a resistant and a susceptible apple genotype identified different major classes of genes. EST sequencing data showed that genes linked to resistance, encoding proteins involved in recognition, signaling, defense and apoptosis, were modulated by E. amylovora in its host plant. The expression time course of some of these ESTs selected via a bioinformatic analysis has been characterized.ConclusionThese data are being used to develop hypotheses of resistance or susceptibility mechanisms in Malus to E. amylovora and provide an initial categorization of genes possibly involved in recognition events, early signaling responses the subsequent development of resistance or susceptibility. These data also provided potential candidates for improving apple resistance to fire blight either by marker-assisted selection or genetic engineering.

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Identification of differentially expressed genes between developing seeds of different soybean cultivars.

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Identification of differentially expressed genes between developing seeds of different soybean cultivars.

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