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Search Results: 1 - 10 of 32824 matches for " Dianjing Guo "
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Comparative Epigenetic Analyses of Acute and Chronic Leukemia  [PDF]
Yan Zhang, Dianjing Guo
Journal of Biosciences and Medicines (JBM) , 2015, DOI: 10.4236/jbm.2015.36005

Comparative analysis of epigenetic alterations between acute vs. chronic leukemia, with an emphasis on histone modifications, was conducted. We focus on the promoter regions of the whole genomes as well as oncogenes. Our results revealed that obvious differential histone modifications pattern exists between the two subtypes. H3K27ac has a high tag density in the promoter region in both Dnd41 cell lines and K562 cell lines. H3K27ac and H3K4me1 have high correlation between the two cell lines of oncogenes. Similar results were also achieved in the promoter region of high expression genes in the Jurkat and K562 cell lines based on RNA-seq data. This suggests that H2K27ac and H3K4me1 are active regulators in leukemia cell lines.

Comparative Epigenetics Analyses of Acute and Chronic Leukemia  [PDF]
Zhang Yan, Dianjing Guo
Journal of Biosciences and Medicines (JBM) , 2015, DOI: 10.4236/jbm.2015.37002
Abstract: Comparative analysis of epigenetic alterations between acute and chronic leukemia, with an emphasis on histone modifications, was conducted. We focused on the promoter regions of the whole genomes as well as oncogenes. Our results revealed that obvious differential histone modifications pattern existed between the two subtypes. H3K27ac had a high tag density in the promoter region in both Dnd41 cell lines and K562 cell lines. H3K27ac and H3K4me1 had high correlation between the two cell lines of oncogenes. Similar results were also achieved in the promoter region of high expression genes in the Jurkat and K562 cell lines based on RNA-seq data. This suggested that H2K27ac and H3K4me1 were active regulators in leukemia cell lines.
An Artemisia WD40-Repeat Gene Regulates Multiple Cellular Functions in Arabidopsis  [PDF]
Wei Wang, Qing Zhang, Dianjing Guo
Journal of Biosciences and Medicines (JBM) , 2016, DOI: 10.4236/jbm.2016.45003
Abstract: In this study, we isolated a WD40-repeat gene from Artemisia annua glandular trichomes. This gene shows 69.97% sequence similarity to Arabidopsis TTG1 at aminoacid level. Sub-cellular localization study shows that AaWD40 protein diffuses in both cell nucleus and cytosol. The correct nuclear localization of AaWD40 was observed when co-expressed with AabHLH, a putative A. thaliana AtTTG1 homologue cloned from Artemisia annua glandular trichomes. When AaWD40 gene was ectopically over expressed in Arabidopsis transparent testa glabrous1-1 (ttg1-1) mutants of A. thaliana, PAs production in seeds was restored, and the trichomeless phenotypes of mutant were rescued. Real-time PCR analysis results revealed that ETC1, CPC, TTG2 and BAN (the downstream targets of AtTTG1 depend on regulatory complex), which regulate the epidermal differentiation and anthocyanin biosynthesis were differentially expressed as a result of AaWD40 over expression. Furthermore, the CLV1, CLV2, CLV3 and WUS, which are required to maintain the stem-cell niche of Arabidopsis shoot apex, were also modulated by AaWD40 and Arabidopsis TTG1. The transcriptions of AP2/ERF, bHLH, MYB, WRKY and NACs family proteins, which are mostly involved in defense, stress response and development regulation, were remarkably modulated by AaWD40 over expression. We hypothesize that WD40 repeat proteins act as a crucial factor in regulating a wide variety of cellular functions in A. thaliana.
Investigation of Glandular Trichome Proteins in Artemisia annua L. Using Comparative Proteomics
Ting Wu, Yejun Wang, Dianjing Guo
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0041822
Abstract: Glandular secreting trichomes (GSTs) are called biofactories because they are active in synthesizing, storing and secreting various types of plant secondary metabolites. As the most effective drug against malaria, artemisinin, a sesquiterpene lactone is derived from GSTs of Artemisia annua. However, low artemisinin content (0.001%~1.54% of dry weight) has hindered its wide application. We investigate the GST-expressed proteins in Artemisia annua using a comparative proteomics approach, aiming for a better understanding of the trichome proteome and arteminisin metabolism. 2D-electrophoresis was employed to compare the protein profiles of GSTs and leaves. More than 700 spots were resolved for GSTs, of which ~93 non-redundant proteins were confidently identified by searching NCBI and Artemisia EST databases. Over 70% of these proteins were highly expressed in GTSs. Functional classification of these GSTs enriched proteins revealed that many of them participate in major plant metabolic processes such as electron transport, transcription and translation.
T3DB: an integrated database for bacterial type III secretion system
Yejun Wang, He Huang, Ming'an Sun, Qing Zhang, Dianjing Guo
BMC Bioinformatics , 2012, DOI: 10.1186/1471-2105-13-66
Abstract: A T3SS-related Database (T3DB) was developed. T3DB serves as an integrated platform for sequence collection, function annotation, and ortholog classification for T3SS related apparatus, effector, chaperone and regulatory genes. The collection of T3SS-containing bacteria, T3SS-related genes, function annotation, and the ortholog information were all manually curated from literature. BPBAac, a highly efficient T3SS effector prediction tool, was also implemented.T3DB is the first systematic platform integrating well-annotated T3SS-related gene and protein information to facilitate T3SS and bacterial pathogenecity related research. The newly constructed T3 ortholog clusters may faciliate effective communication between different research groups and will promote de novo discoveries. Besides, the manually-curated high-quality effector and chaperone data are useful for feature analysis and evolutionary studies of these important proteins.
Global characterization of Artemisia annua glandular trichome transcriptome using 454 pyrosequencing
Wei Wang, Yejun Wang, Qing Zhang, Yan Qi, Dianjing Guo
BMC Genomics , 2009, DOI: 10.1186/1471-2164-10-465
Abstract: We present a global characterization of A. annua glandular trichome transcriptome using 454 pyrosequencing. Sequencing runs using two normalized cDNA collections from glandular trichomes yielded 406,044 expressed sequence tags (average length = 210 nucleotides), which assembled into 42,678 contigs and 147,699 singletons. Performing a second sequencing run only increased the number of genes identified by ~30%, indicating that massively parallel pyrosequencing provides deep coverage of the A. annua trichome transcriptome. By BLAST search against the NCBI non-redundant protein database, putative functions were assigned to over 28,573 unigenes, including previously undescribed enzymes likely involved in sesquiterpene biosynthesis. Comparison with ESTs derived from trichome collections of other plant species revealed expressed genes in common functional categories across different plant species. RT-PCR analysis confirmed the expression of selected unigenes and novel transcripts in A. annua glandular trichomes.The presence of contigs corresponding to enzymes for terpenoids and flavonoids biosynthesis suggests important metabolic activity in A. annua glandular trichomes. Our comprehensive survey of genes expressed in glandular trichome will facilitate new gene discovery and shed light on the regulatory mechanism of artemisinin metabolism and trichome function in A. annua.Secreting glandular trichomes (GTs) are a major site for biosynthesis and accumulation of a wide range of plant natural products. These plant natural products often function to protect the plants against insect predation [1,2], and contribute to the flavour and aroma of plants. Many of the natural products also have pharmacological effects, such as the analgesic drug morphine, the anticancer compound taxol, and the antimalarial drug artemisinin. Artemisinin, a sesquiterpene lactone, is currently recognized as one of the most prominent anti-malarial treatment [3]. A complete understanding of the artemisinin
Effective Identification of Bacterial Type III Secretion Signals Using Joint Element Features
Yejun Wang, Ming’an Sun, Hongxia Bao, Qing Zhang, Dianjing Guo
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0059754
Abstract: Type III secretion system (T3SS) plays important roles in bacteria and host cell interactions by specifically translocating type III effectors into the cytoplasm of the host cells. The N-terminal amino acid sequences of the bacterial type III effectors determine their specific secretion via type III secretion conduits. It is still unclear as to how the N-terminal sequences guide this specificity. In this work, the amino acid composition, secondary structure, and solvent accessibility in the N-termini of type III and non-type III secreted proteins were compared and contrasted. A high-efficacy mathematical model based on these joint features was developed to distinguish the type III proteins from the non-type III ones. The results indicate that secondary structure and solvent accessibility may make important contribution to the specific recognition of type III secretion signals. Analysis also showed that the joint feature of the N-terminal 6th–10th amino acids are especially important for guiding specific type III secretion. Furthermore, a genome-wide screening was performed to predict Salmonella type III secreted proteins, and 8 new candidates were experimentally validated. Interestingly, type III secretion signals were also predicted in gram-positive bacteria and yeasts. Experimental validation showed that two candidates from yeast can indeed be secreted through Salmonella type III secretion conduit. This research provides the first line of direct evidence that secondary structure and solvent accessibility contain important features for guiding specific type III secretion. The new software based on these joint features ensures a high accuracy (general cross-validation sensitivity of ~96% at a specificity of ~98%) in silico identification of new type III secreted proteins, which may facilitate our understanding about the specificity of type III secretion and the evolution of type III secreted proteins.
A Model-Based Method for Gene Dependency Measurement
Qing Zhang, Xiaodan Fan, Yejun Wang, Mingan Sun, Samuel S. M. Sun, Dianjing Guo
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0040918
Abstract: Many computational methods have been widely used to identify transcription regulatory interactions based on gene expression profiles. The selection of dependency measure is very important for successful regulatory network inference. In this paper, we develop a new method–DBoMM (Difference in BIC of Mixture Models)–for estimating dependency of gene by fitting the gene expression profiles into mixture Gaussian models. We show that DBoMM out-performs 4 other existing methods, including Kendall’s tau correlation (TAU), Pearson Correlation (COR), Euclidean distance (EUC) and Mutual information (MI) using Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster, Arabidopsis thaliana data and synthetic data. DBoMM can also identify condition-dependent regulatory interactions and is robust to noisy data. Of the 741 Escherichia coli regulatory interactions inferred by DBoMM at a 60% true positive rate, 65 are previously known interactions and 676 are novel predictions. To validate the new prediction, the promoter sequences of target genes regulated by the same transcription factors were analyzed and significant motifs were identified.
Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks
Yong Li, Lili Liu, Xi Bai, Hua Cai, Wei Ji, Dianjing Guo, Yanming Zhu
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-520
Abstract: In this study, we propose a new discretization method "bikmeans", and compare its performance with four other widely-used discretization methods using different datasets, modeling algorithms and number of intervals. Sensitivities, specificities and total accuracies were calculated and statistical analysis was carried out. Bikmeans method always gave high total accuracies.Our results indicate that proper discretization methods can consistently improve gene regulatory network inference independent of network modeling algorithms and datasets. Our new method, bikmeans, resulted in significant better total accuracies than other methods.Inferring gene regulatory networks (GRN) using time course microarray data is one of the most important goals in systems biology [1]. A number of algorithms have been proposed to infer the transcription networks, including Boolean Networks [2,3], Gaussian Networks [4], Bayesian Networks [5,6], and Dynamic Bayesian Networks [7]. Most algorithms require discrete data as input. However, the selection of the discretization method is often arbitrary due to the lack of empirical data about the performance of different discretization methods. Discretization methods based on transitions between time points obtain better results than those using absolute values for biclustering time series gene expression data [8]. We proposed therefore that some discretization methods will produce superior results than others when inferring GRN.Many discretization methods commonly used in data mining and knowledge discovery have been also used to discretize time series gene expression data (see [8] for review). However, most of these methods are not suitable to be used during preprocessing in time course microarray data analysis, and more specifically they are not suitable, or perform poorly, when used to discretize gene expression data during the process of GRN inference. Discretization algorithms can be divided into two categories: supervised and unsupervised. S
Global transcriptome profiling of wild soybean (Glycine soja) roots under NaHCO3 treatment
Ying Ge, Yong Li, Yan-Ming Zhu, Xi Bai, De-Kang Lv, Dianjing Guo, Wei Ji, Hua Cai
BMC Plant Biology , 2010, DOI: 10.1186/1471-2229-10-153
Abstract: Using Affymetrix? Soybean GeneChip?, we conducted transcriptional profiling on Glycine soja roots subjected to 50 mmol/L NaHCO3 treatment. In a total of 7088 probe sets, 3307 were up-regulated and 5720 were down-regulated at various time points. The number of significantly stress regulated genes increased dramatically after 3 h stress treatment and peaked at 6 h. GO enrichment test revealed that most of the differentially expressed genes were involved in signal transduction, energy, transcription, secondary metabolism, transporter, disease and defence response. We also detected 11 microRNAs regulated by NaHCO3 stress.This is the first comprehensive wild soybean root transcriptome analysis under alkaline stress. These analyses have identified an inventory of genes with altered expression regulated by alkaline stress. The data extend the current understanding of wild soybean alkali stress response by providing a set of robustly selected, differentially expressed genes for further investigation.Soil salinity-alkalinity is one of the major environmental challenges limiting crop productivity globally. For example, the western Songnen Plain of China, which has 3.73 million ha of sodic land, is one of the three major contiguous sodic soil regions in the world. Understanding the molecular basis of plant response under saline-alkaline conditions will facilitate biotechnology efforts to breed crop plants with enhanced tolerance to high saline-alkaline. Root is an important organ for carrying water and mineral nutrients to the rest of the plant. As the primary site of perception and injury for salinity and alkaline stress, roots provide an ideal target for study of the molecular mechanism underlying plant saline-alkaline stress tolerance and adaptation [1].Soybean is rich in nutraceutical compounds, e.g., isoflavone and saponins. Its high symbiotic nitrogen fixing capacity (100 Kg/ha/year; FAO data 1984) helps to replenish soil nitrogen. Therefore, soybean is an ideal crop for
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