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ABSTRACT: Turfgrass species are agriculturally and economically important perennial crops. Turfgrass species are highly susceptible to a wide range of fungal pathogens. Dollar spot and brown patch, two important diseases caused by fungal pathogens Sclerotinia homoecarpa and Rhizoctonia solani, respectively, are among the most severe turfgrass diseases. Currently, turf fungal disease control mainly relies on fungicide treatments, which raises many concerns for human health and the environment. Antimicrobial peptides found in various organisms play an important role in innate immune response.
The antimicrobial peptide - Penaeidin4-1 (Pen4-1) from the shrimp, Litopenaeus setiferus has been reported to possess in vitro antifungal and antibacterial activities against various economically important fungal and bacterial pathogens. In this study, we have studied the feasibility of using this novel peptide for engineering enhanced disease resistance into creeping bentgrass plants (Agrostis stolonifera L., cv. Penn A-4). Two DNA constructs were prepared containing either the coding sequence of a single peptide, Pen4-1 or the DNA sequence coding for the transit signal peptide of the secreted tobacco AP24 protein translationally fused to the Pen4-1 coding sequence. A maize ubiquitin promoter was used in both constructs to drive gene expression. Transgenic turfgrass plants containing different DNA constructs were generated by Agrobacterium-mediated transformation and analyzed for transgene insertion and expression. In replicated in vitro and in vivo experiments under controlled environments, transgenic plants exhibited significantly enhanced resistance to dollar spot and brown patch, the two major fungal diseases in turfgrass. The targeting of Pen4-1 to endoplasmic reticulum by the transit peptide of AP24 protein did not significantly impact disease resistance in transgenic plants.
Our results demonstrate the effectiveness of Pen4-1 in a perennial species against fungal pathogens and suggest a potential strategy for engineering broad-spectrum fungal disease resistance in crop species.
PLoS ONE 01/2011; 6(9):e24677. · 4.09 Impact Factor
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ABSTRACT: Lingzhi (ganoderma) is an important woody mushroom that is known for its medicinal benefits in China since ancient times. The mode of action in humans is still not clear. Using microarray technology, we have compared the ethanol extracts of two different lingzhi (red lingzhi, G. lucidum; and purple lingzhi, G. sinense) for their effects on gene expression profile in human monocytic cells. Our results suggest that at best approximately 25% of target genes are common to the two lingzhi: functionally ranging from cell development, negative regulation of cellular process, and cellular protein metabolic process to signal transduction and transcription. The pathways mediated by purple lingzhi focus on inflammation and immune response, whereas red lingzhi modestly increases levels of expression for genes involved in macromolecule metabolism. Furthermore, our ethanolic extracts of both red and purple lingzhi do not inhibit monocytic cell growth. The extract of red lingzhi does not have significant effect on the genes in the nuclear factor kappa B (NFkappaB) pathway (an important inflammation pathway), whereas the extract of purple lingzhi can increase multiple key genes in the NFkappaB pathway. Altogether, our results suggest that the common mode of action for lingzhi is complex; and different species of Ganoderma can modulate different pathways in human cells.
Nutrition and Cancer 01/2010; 62(5):648-58. · 2.78 Impact Factor
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ABSTRACT: We have developed a set of online tools for measuring the semantic similarities of Gene Ontology (GO) terms and the functional similarities of gene products, and for further discovering biomedical knowledge from the GO database. The tools have been used for about 6.9 million times by 417 institutions from 43 countries since October 2006. The online tools are available at: http://bioinformatics.clemson.edu/G-SESAME.
Nucleic Acids Research 07/2009; 37(Web Server issue):W345-9. · 8.03 Impact Factor
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ABSTRACT: Intellectual disability (ID) is a common developmental disability observed in 1 to 3% of the human population. A possible role for the Angiotensin II type 2 receptor (AGTR2) in brain function, affecting learning, memory, and behavior, has been suggested in humans and rodents. Mice lacking the Agtr2 gene (Agtr2(-/y)) showed significant impairment in their spatial memory and exhibited abnormal dendritic spine morphology. To identify Agtr2 influenced genes and pathways, we performed whole genome microarray analysis on RNA isolated from brains of Agtr2(-/y) and control male mice at embryonic day 15 (E15) and postnatal day one (P1). The gene expression profiles of the Agtr2(-/y) brain samples were significantly different when compared to profiles of the age-matched control brains. We identified 62 differently expressed genes (p< or =0.005) at E15 and in P1 brains of the Agtr2(-/y) mice. We verified the differential expression of several of these genes in brain samples using quantitative RT-PCR. Differentially expressed genes encode molecules involved in multiple cellular processes including microtubule functions associated with dendritic spine morphology. This study provides insight into Agtr2 influenced candidate genes and suggests that expression dysregulation of these genes may modulate Agtr2 actions in the brain that influences learning and memory.
Genomics 06/2009; 94(3):188-95. · 3.02 Impact Factor
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ABSTRACT: Mice of the genus Peromyscus are found in nearly every habitat from Alaska to Central America and from the Atlantic to the Pacific. They provide an evolutionary outgroup to the Mus/Rattus lineage and serve as an intermediary between that lineage and humans. Although Peromyscus has been studied extensively under both field and laboratory conditions, research has been limited by the lack of molecular resources. Genes associated with reproduction typically evolve rapidly and thus are excellent sources of evolutionary information. In this study we describe the generation of two cDNA libraries, one from placenta and one from testis, characterize the resulting ESTs, and describe their utility for mapping the Peromyscus genome.
The 5' ends of 1,510 placenta and 4,798 testis clones were sequenced. Low quality sequences were removed and after clustering and contig assembly, 904 unique placenta and 2,002 unique testis sequences remained. Average lengths of placenta and testis ESTs were 711 bp and 826 bp, respectively. Approximately 82% of all ESTs were identified using the BLASTX algorithm to Mus and Rattus, and 34 - 54% of all ESTs could be assigned to a biological process gene ontology category in either Mus or Rattus. Because the Peromyscus genome organization resembles the Rattus genome more closely than Mus we examined the distribution of the Peromyscus ESTs across the rat genome finding markers on all rat chromosomes except the Y. Approximately 40% of all ESTs were specific to only one location in the Mus genome and spanned introns of an appropriate size for sequencing and SNP detection. Of the primers that were tried 54% provided useful assays for genotyping on interspecific backcross and whole-genome radiation hybrid cell panels.
The 2,906 Peromyscus placenta and testis ESTs described here significantly expands the molecular resources available for the genus. These ESTs allow for specific PCR amplification and broad coverage across the genome, creating an excellent genetic marker resource for the generation of a medium-density genomic map. Thus, this resource will significantly aid research of a genus that is uniquely well-suited to both laboratory and field research.
BMC Genomics 02/2008; 9:300. · 4.07 Impact Factor
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ABSTRACT: Abstract
Background
Mice of the genus Peromyscus are found in nearly every habitat from Alaska to Central America and from the Atlantic to the Pacific. They provide an evolutionary outgroup to the Mus/Rattus lineage and serve as an intermediary between that lineage and humans. Although Peromyscus has been studied extensively under both field and laboratory conditions, research has been limited by the lack of molecular resources. Genes associated with reproduction typically evolve rapidly and thus are excellent sources of evolutionary information. In this study we describe the generation of two cDNA libraries, one from placenta and one from testis, characterize the resulting ESTs, and describe their utility for mapping the Peromyscus genome.
Results
The 5' ends of 1,510 placenta and 4,798 testis clones were sequenced. Low quality sequences were removed and after clustering and contig assembly, 904 unique placenta and 2,002 unique testis sequences remained. Average lengths of placenta and testis ESTs were 711 bp and 826 bp, respectively. Approximately 82% of all ESTs were identified using the BLASTX algorithm to Mus and Rattus , and 34 – 54% of all ESTs could be assigned to a biological process gene ontology category in either Mus or Rattus . Because the Peromyscus genome organization resembles the Rattus genome more closely than Mus we examined the distribution of the Peromyscus ESTs across the rat genome finding markers on all rat chromosomes except the Y. Approximately 40% of all ESTs were specific to only one location in the Mus genome and spanned introns of an appropriate size for sequencing and SNP detection. Of the primers that were tried 54% provided useful assays for genotyping on interspecific backcross and whole-genome radiation hybrid cell panels.
Conclusion
The 2,906 Peromyscus placenta and testis ESTs described here significantly expands the molecular resources available for the genus. These ESTs allow for specific PCR amplification and broad coverage across the genome, creating an excellent genetic marker resource for the generation of a medium-density genomic map. Thus, this resource will significantly aid research of a genus that is uniquely well-suited to both laboratory and field research.
BMC Genomics. 01/2008;
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ABSTRACT: Gene ontology (GO) is a large public database which not only provides a set of controlled biological and biochemical vocabularies (terms) to describe gene products based upon their functions in the cell, but also contains gene annotation data from heterogeneous data sources. In this paper, using a new method to measure the semantic similarity of GO terms, an efficient algorithm is proposed to find genes that have similar biological functions with a given gene. An online tool is then implemented to search the top N genes having similar biological functions with a particular gene within the same or cross different species. Furthermore, various performance enhancement techniques are utilized to reduce the user query response time of the online tool. This tool is available at: http://bioinformatics.cletnson.edu/G-SESAME/Programs/geneTopl.php.
Bioinformatics and Biomedicine, 2007. BIBM 2007. IEEE International Conference on; 12/2007
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ABSTRACT: The herb feverfew is a folk remedy for various conditions, including inflammation, fever, psoriasis, rheumatism, and asthma. Like many herbal medicines, feverfew's mechanisms of action in the human body are largely unknown and its active ingredients remain elusive. Very often, different extraction methods of herb material produce different physical and biochemical properties and variation in clinical efficacy. We identified 3 major methods of extraction for feverfew aerial parts and used microarray technology to test the hypothesis that extracts produced by different methods elicit different gene expression profiles. We have identified approximately 200 genes that are consistently regulated by the 2 presumptive active antimigraine feverfew extracts but not associated with the inactive extract. Our results suggest that the presumptive active feverfew extracts potently stimulate more genes in human cells than the inactive extracts. We also identified several genes as unique signatures for these active extracts. All 3 feverfew extracts exhibited similar blockades on lipopolysaccharide-mediated TNF-alpha (tumor necrosis factor alpha) release, implicating that TNF-alpha is not responsible for the differences in the effects of the 3 feverfew extracts in human cells. In contrast, the active extracts more effectively suppressed CCL2 (also known as monocyte chemoattractant protein 1, MCP-1) than the inactive extracts, suggesting that CCL2 is a potential cellular target for feverfew's antimigraine effects.
Canadian Journal of Physiology and Pharmacology 12/2007; 85(11):1108-15. · 1.95 Impact Factor
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ABSTRACT: The herb feverfew is a folk remedy for various symptoms including inflammation. Inflammation has recently been implicated in the genesis of many diseases including cancers, atherosclerosis and rheumatoid arthritis. The mechanisms of action of feverfew in the human body are largely unknown. To determine the cellular targets of feverfew extracts, we have utilized oligo microarrays to study the gene expression profiles elicited by feverfew extracts in human monocytic THP-1 cells. We have identified 400 genes that are consistently regulated by feverfew extracts. Most of the genes are involved in cellular metabolism. However, the genes undergoing the highest degree of change by feverfew treatment are involved in other pathways including chemokine function, water homeostasis and heme-mediated signaling. Our results also suggest that feverfew extracts effectively reduce Lipopolysaccharides (LPS)-mediated TNF-alpha and CCL2 (MCP-1) releases by THP-1 cells. We hypothesize that feverfew components mediate metabolism, cell migration and cytokine production in human monocytes/macrophages.
Evidence-based Complementary and Alternative Medicine 07/2007; 6(1):91-8. · 4.77 Impact Factor
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ABSTRACT: Although controlled biochemical or biological vocabularies, such as Gene Ontology (GO) (http://www.geneontology.org), address the need for consistent descriptions of genes in different data sources, there is still no effective method to determine the functional similarities of genes based on gene annotation information from heterogeneous data sources.
To address this critical need, we proposed a novel method to encode a GO term's semantics (biological meanings) into a numeric value by aggregating the semantic contributions of their ancestor terms (including this specific term) in the GO graph and, in turn, designed an algorithm to measure the semantic similarity of GO terms. Based on the semantic similarities of GO terms used for gene annotation, we designed a new algorithm to measure the functional similarity of genes. The results of using our algorithm to measure the functional similarities of genes in pathways retrieved from the saccharomyces genome database (SGD), and the outcomes of clustering these genes based on the similarity values obtained by our algorithm are shown to be consistent with human perspectives. Furthermore, we developed a set of online tools for gene similarity measurement and knowledge discovery.
The online tools are available at: http://bioinformatics.clemson.edu/G-SESAME.
http://bioinformatics.clemson.edu/Publication/Supplement/gsp.htm.
Bioinformatics 06/2007; 23(10):1274-81. · 5.47 Impact Factor
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ABSTRACT: Accumulating evidence suggests that biological systems are composed of interacting, separable, functional modules. Identifying these modules is essential to understand the organization of biological systems.
In this paper, we present a framework to identify modules within biological networks. In this approach, the concept of degree is extended from the single vertex to the sub-graph, and a formal definition of module in a network is used. A new agglomerative algorithm was developed to identify modules from the network by combining the new module definition with the relative edge order generated by the Girvan-Newman (G-N) algorithm. A JAVA program, MoNet, was developed to implement the algorithm. Applying MoNet to the yeast core protein interaction network from the database of interacting proteins (DIP) identified 86 simple modules with sizes larger than three proteins. The modules obtained are significantly enriched in proteins with related biological process Gene Ontology terms. A comparison between the MoNet modules and modules defined by Radicchi et al. (2004) indicates that MoNet modules show stronger co-clustering of related genes and are more robust to ties in betweenness values. Further, the MoNet output retains the adjacent relationships between modules and allows the construction of an interaction web of modules providing insight regarding the relationships between different functional modules. Thus, MoNet provides an objective approach to understand the organization and interactions of biological processes in cellular systems.
MoNet is available upon request from the authors.
Bioinformatics 02/2007; 23(2):207-14. · 5.47 Impact Factor
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Bioinformatics. 01/2007; 23:1274-1281.
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ABSTRACT: Gene expression profiling by microarray technology is usually difficult to interpret into a simpler pattern. One approach to resolve the complexity of gene expression profiles is the application of artificial neural networks (ANNs). A potential difficulty in this strategy, however, is that the non-linear nature of ANN makes it essentially a 'black-box' computation process. Addition of a fuzzy logic approach is useful because it can complement ANN by explicitly specifying membership function during computation. We employed a hybrid approach of neural network and fuzzy logic to further analyze a published microarray study of gene responses to eight bacteria in human macrophages. The original analysis by hierarchical clustering found common gene responses to all bacteria but did not address individual responses. Our method allowed exploration of the gene response of the host to individual bacterium. We implemented a two-layer, feed-forward neural network containing the principle of 'competitive learning' (i.e. 'winner-take-all'). The weights of the trained neural network were fed into a fuzzy logic inference system. A new measurement, called the impact rating (IR) was also introduced to explore the degree of importance of each gene. To assess the reliability of the IR value, a bootstrap re-sampling method was applied to the dataset and a confidence level for each IR was obtained. Our approach has successfully uncovered the unique features of host response to individual bacterium. Further, application of gene ontology (GO) annotation to the genes of high IR values in each response has suggested new biological pathways for individual host-pathogen interactions.
Computational Biology and Chemistry 11/2006; 30(5):372-81. · 1.55 Impact Factor
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Norberto de la Cruz,
Susan Bromberg,
Dean Pasko,
Mary Shimoyama,
Simon Twigger,
Jiali Chen, Chin-Fu Chen,
Chunyu Fan,
Cindy Foote,
Gopal R Gopinath, [......],
Rajni Nigam,
Victoria Petri,
Dorothy Reilly,
Weiye Wang,
Wenhua Wu,
Angela Zuniga-Meyer,
Lan Zhao,
Anne Kwitek,
Peter Tonellato,
Howard Jacob
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ABSTRACT: The Rat Genome Database (RGD) (http://rgd.mcw.edu) aims to meet the needs of its community by providing genetic and genomic infrastructure while also annotating the strengths of rat research: biochemistry, nutrition, pharmacology and physiology. Here, we report on RGD's development towards creating a phenome database. Recent developments can be categorized into three groups. (i) Improved data collection and integration to match increased volume and biological scope of research. (ii) Knowledge representation augmented by the implementation of a new ontology and annotation system. (iii) The addition of quantitative trait loci data, from rat, mouse and human to our advanced comparative genomics tools, as well as the creation of new, and enhancement of existing, tools to enable users to efficiently browse and survey research data. The emphasis is on helping researchers find genes responsible for disease through the use of rat models. These improvements, combined with the genomic sequence of the rat, have led to a successful year at RGD with over two million page accesses that represent an over 4-fold increase in a year. Future plans call for increased annotation of biological information on the rat elucidated through its use as a model for human pathobiology. The continued development of toolsets will facilitate integration of these data into the context of rat genomic sequence, as well as allow comparisons of biological and genomic data with the human genomic sequence and of an increasing number of organisms.
Nucleic Acids Research 02/2005; 33(Database issue):D485-91. · 8.03 Impact Factor
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ABSTRACT: Levels of recombination vary among species, among chromosomes within species, and among regions within chromosomes in mammals. This heterogeneity may affect levels of diversity, efficiency of selection, and genome composition, as well as have practical consequences for the genetic mapping of traits. We compared the genetic maps to the genome sequence assemblies of rat, mouse, and human to estimate local recombination rates across these genomes. Humans have greater overall levels of recombination, as well as greater variance. In rat and mouse, the size of the chromosome and proximity to telomere have less effect on local recombination rate than in human. At the chromosome level, rat and mouse X chromosomes have the lowest recombination rates, whereas human chromosome X does not show the same pattern. In all species, local recombination rate is significantly correlated with several sequence variables, including GC%, CpG density, repetitive elements, and the neutral mutation rate, with some pronounced differences between species. Recombination rate in one species is not strongly correlated with the rate in another, when comparing homologous syntenic blocks of the genome. This comparative approach provides additional insight into the causes and consequences of genomic heterogeneity in recombination.
Genome Research 05/2004; 14(4):528-38. · 13.61 Impact Factor
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ABSTRACT: The data-mining challenge presented is composed of two fundamental problems. Problem one is the separation of forty-one subjects into two classifications based on the data produced by the mass spectrometry of protein samples from each subject. Problem two is to find the specific differences between protein expression data of two sets of subjects. In each problem, one group of subjects has a disease, while the other group is nondiseased. Each problem was approached with the intent to introduce a new and potentially useful tool to analyze protein expression from mass spectrometry data. A variety of methodologies, both conventional and nonconventional were used in the analysis of these problems. The results presented show both overlap and discrepancies. What is important is the breadth of the techniques and the future direction this analysis will create.
PROTEOMICS 10/2003; 3(9):1704-9. · 4.51 Impact Factor
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Mammalian Genome 02/2003; 14(1):61-4. · 2.89 Impact Factor
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Simon Twigger,
Jian Lu,
Mary Shimoyama,
Dan Chen,
Dean Pasko,
Hanping Long,
Jessica Ginster, Chin-Fu Chen,
Rajni Nigam,
Anne Kwitek,
Janan Eppig,
Lois Maltais,
Donna Maglott,
Greg Schuler,
Howard Jacob,
Peter J Tonellato
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ABSTRACT: The Rat Genome Database (RGD, http://rgd.mcw.edu) is an NIH-funded project whose stated mission is 'to collect, consolidate and integrate data generated from ongoing rat genetic and genomic research efforts and make these data widely available to the scientific community'. In a collaboration between the Bioinformatics Research Center at the Medical College of Wisconsin, the Jackson Laboratory and the National Center for Biotechnology Information, RGD has been created to meet these stated aims. The rat is uniquely suited to its role as a model of human disease and the primary focus of RGD is to aid researchers in their study of the rat and in applying their results to studies in a wider context. In support of this we have integrated a large amount of rat genetic and genomic resources in RGD and these are constantly being expanded through ongoing literature and bulk dataset curation. RGD version 2.0, released in June 2001, includes curated data on rat genes, quantitative trait loci (QTL), microsatellite markers and rat strains used in genetic and genomic research. VCMap, a dynamic sequence-based homology tool was introduced, and allows researchers of rat, mouse and human to view mapped genes and sequences and their locations in the other two organisms, an essential tool for comparative genomics. In addition, RGD provides tools for gene prediction, radiation hybrid mapping, polymorphic marker selection and more. Future developments will include the introduction of disease-based curation expanding the curated information to cover popular disease systems studied in the rat. This will be integrated with the emerging rat genomic sequence and annotation pipelines to provide a high-quality disease-centric resource, applicable to human and mouse via comparative tools such as VCMap. RGD has a defined community outreach focus with a Visiting Scientist program and the Rat Community Forum, a web-based forum for rat researchers and others interested in using the rat as an experimental model. Thus, RGD is not only a valuable resource for those working with the rat but also for researchers in other model organisms wishing to harness the existing genetic and physiological data available in the rat to complement their own work.
Nucleic Acids Research 02/2002; 30(1):125-8. · 8.03 Impact Factor
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Simon N. Twigger,
Jian Lu,
Mary Shimoyama,
Dan Chen,
Dean Pasko,
Hanping Long,
Jessica Ginster, Chin-Fu Chen,
Rajni Nigam,
Anne E. Kwitek,
Janan T. Eppig,
Lois Maltais,
Donna R. Maglott,
Gregory D. Schuler,
Howard J. Jacob,
Peter J. Tonellato
Nucleic Acids Research. 01/2002; 30:125-128.
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ABSTRACT: Understanding the response of human white blood cells (macrophages) to pathogens may provide insights to both the mechanisms of host defenses and the tactics used by pathogens to circumvent these defenses. The DNA microarray method has evolved to become one of the most powerful tools to understand the dynamics of gene response. Currently there is no standard approach to systematically analyze the data and the interpretation of results can vary dramatically. In this paper, we employed a new hybrid Self-Organizing Map (SOM) and Fuzzy Logic data mining approach to explore patterns of time sequence data from eight bacteria with 977 gene responses that showed significant changes on a microarray chip. We annotated the genes by their "biological processes" of Gene Ontology (GO). Our result suggests that the SOM-Fuzzy logic data mining approach is effective in exploring how human macrophages respond to each bacterium with a unique combination of shared biological processes. The shared processes include: signal transduction, transcription, metabolism, and cell cycle and proliferation. Our result also suggests that there are similar responses (identical genes) to several bacteria and the similarities may be related to the shared mechanism of bacterial pathogenesis.
