Sample records for accelerate gene discovery

  1. Function-driven discovery of disease genes in zebrafish using an integrated genomics big data resource.

    PubMed

    Shim, Hongseok; Kim, Ji Hyun; Kim, Chan Yeong; Hwang, Sohyun; Kim, Hyojin; Yang, Sunmo; Lee, Ji Eun; Lee, Insuk

    2016-11-16

    Whole exome sequencing (WES) accelerates disease gene discovery using rare genetic variants, but further statistical and functional evidence is required to avoid false-discovery. To complement variant-driven disease gene discovery, here we present function-driven disease gene discovery in zebrafish (Danio rerio), a promising human disease model owing to its high anatomical and genomic similarity to humans. To facilitate zebrafish-based function-driven disease gene discovery, we developed a genome-scale co-functional network of zebrafish genes, DanioNet (www.inetbio.org/danionet), which was constructed by Bayesian integration of genomics big data. Rigorous statistical assessment confirmed the high prediction capacity of DanioNet for a wide variety of human diseases. To demonstrate the feasibility of the function-driven disease gene discovery using DanioNet, we predicted genes for ciliopathies and performed experimental validation for eight candidate genes. We also validated the existence of heterozygous rare variants in the candidate genes of individuals with ciliopathies yet not in controls derived from the UK10K consortium, suggesting that these variants are potentially involved in enhancing the risk of ciliopathies. These results showed that an integrated genomics big data for a model animal of diseases can expand our opportunity for harnessing WES data in disease gene discovery. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. Translational Research 2.0: a framework for accelerating collaborative discovery.

    PubMed

    Asakiewicz, Chris

    2014-05-01

    The world wide web has revolutionized the conduct of global, cross-disciplinary research. In the life sciences, interdisciplinary approaches to problem solving and collaboration are becoming increasingly important in facilitating knowledge discovery and integration. Web 2.0 technologies promise to have a profound impact - enabling reproducibility, aiding in discovery, and accelerating and transforming medical and healthcare research across the healthcare ecosystem. However, knowledge integration and discovery require a consistent foundation upon which to operate. A foundation should be capable of addressing some of the critical issues associated with how research is conducted within the ecosystem today and how it should be conducted for the future. This article will discuss a framework for enhancing collaborative knowledge discovery across the medical and healthcare research ecosystem. A framework that could serve as a foundation upon which ecosystem stakeholders can enhance the way data, information and knowledge is created, shared and used to accelerate the translation of knowledge from one area of the ecosystem to another.

  3. Choosing experiments to accelerate collective discovery

    DOE PAGES

    Rzhetsky, Andrey; Foster, Jacob G.; Foster, Ian T.; ...

    2015-11-24

    Scientists perform a tiny subset of all possible experiments. What characterizes the experiments they choose? What are the consequences of those choices for the pace of scientific discovery? We model scientific knowledge as a network and science as a sequence of experiments designed to gradually uncover it. By analyzing millions of biomedical articles published over 30 y, we find that biomedical scientists pursue conservative research strategies exploring the local neighborhood of central, important molecules. Although such strategies probably serve scientific careers, we show that they slow scientific advance, especially in mature fields, where more risk and less redundant experimentation wouldmore » accelerate discovery of the network. Lastly, we also consider institutional arrangements that could help science pursue these more efficient strategies.« less

  4. Accelerating the Rate of Astronomical Discovery

    NASA Astrophysics Data System (ADS)

    Norris, Ray P. Ruggles, Clive L. N.

    2010-05-01

    Special Session 5 on Accelerating the Rate of Astronomical Discovery addressed a range of potential limits to progress - paradigmatic, technological, organisational, and political - examining each issue both from modern and historical perspectives, and drawing lessons to guide future progress. A number of issues were identified which potentially regulate the flow of discoveries, such as the balance between large strongly-focussed projects and instruments, designed to answer the most fundamental questions confronting us, and the need to maintain a creative environment with room for unorthodox thinkers and bold, high risk, projects. Also important is the need to maintain historical and cultural perspectives, and the need to engage the minds of the most brilliant young people on the planet, regardless of their background, ethnicity, gender, or geography.

  5. Modern plant metabolomics: Advanced natural product gene discoveries, improved technologies, and future prospects

    DOE PAGES

    Sumner, Lloyd W.; Lei, Zhentian; Nikolau, Basil J.; ...

    2014-10-24

    Plant metabolomics has matured and modern plant metabolomics has accelerated gene discoveries and the elucidation of a variety of plant natural product biosynthetic pathways. This study highlights specific examples of the discovery and characterization of novel genes and enzymes associated with the biosynthesis of natural products such as flavonoids, glucosinolates, terpenoids, and alkaloids. Additional examples of the integration of metabolomics with genome-based functional characterizations of plant natural products that are important to modern pharmaceutical technology are also reviewed. This article also provides a substantial review of recent technical advances in mass spectrometry imaging, nuclear magnetic resonance imaging, integrated LC-MS-SPE-NMR formore » metabolite identifications, and x-ray crystallography of microgram quantities for structural determinations. The review closes with a discussion on the future prospects of metabolomics related to crop species and herbal medicine.« less

  6. Metagenomics and novel gene discovery

    PubMed Central

    Culligan, Eamonn P; Sleator, Roy D; Marchesi, Julian R; Hill, Colin

    2014-01-01

    Metagenomics provides a means of assessing the total genetic pool of all the microbes in a particular environment, in a culture-independent manner. It has revealed unprecedented diversity in microbial community composition, which is further reflected in the encoded functional diversity of the genomes, a large proportion of which consists of novel genes. Herein, we review both sequence-based and functional metagenomic methods to uncover novel genes and outline some of the associated problems of each type of approach, as well as potential solutions. Furthermore, we discuss the potential for metagenomic biotherapeutic discovery, with a particular focus on the human gut microbiome and finally, we outline how the discovery of novel genes may be used to create bioengineered probiotics. PMID:24317337

  7. Collaborative Workspaces to Accelerate Discovery

    NASA Astrophysics Data System (ADS)

    Meade, Bernard; Fluke, Christopher; Cooke, Jeff; Andreoni, Igor; Pritchard, Tyler; Curtin, Christopher; Bernard, Stephanie R.; Asher, Albany; Mack, Katherine J.; Murphy, Michael T.; Vohl, Dany; Codoreanu, Alex; Kotuš, Srđan M.; Rumokoy, Fanuel; Horst, Chuck; Reynolds, Tristan

    2017-05-01

    By applying a display ecology to the Deeper, Wider, Faster proactive, simultaneous telescope observing campaign, we have shown a dramatic reduction in the time taken to inspect DECam CCD images for potential transient candidates and to produce time-critical triggers to standby telescopes. We also show how facilitating rapid corroboration of potential candidates and the exclusion of non-candidates improves the accuracy of detection; and establish that a practical and enjoyable workspace can improve the experience of an otherwise taxing task for astronomers. We provide a critical road test of two advanced displays in a research context-a rare opportunity to demonstrate how they can be used rather than simply discuss how they might be used to accelerate discovery.

  8. Accelerating pathway evolution by increasing the gene dosage of chromosomal segments.

    PubMed

    Tumen-Velasquez, Melissa; Johnson, Christopher W; Ahmed, Alaa; Dominick, Graham; Fulk, Emily M; Khanna, Payal; Lee, Sarah A; Schmidt, Alicia L; Linger, Jeffrey G; Eiteman, Mark A; Beckham, Gregg T; Neidle, Ellen L

    2018-06-18

    Experimental evolution is a critical tool in many disciplines, including metabolic engineering and synthetic biology. However, current methods rely on the chance occurrence of a key step that can dramatically accelerate evolution in natural systems, namely increased gene dosage. Our studies sought to induce the targeted amplification of chromosomal segments to facilitate rapid evolution. Since increased gene dosage confers novel phenotypes and genetic redundancy, we developed a method, Evolution by Amplification and Synthetic Biology (EASy), to create tandem arrays of chromosomal regions. In Acinetobacter baylyi , EASy was demonstrated on an important bioenergy problem, the catabolism of lignin-derived aromatic compounds. The initial focus on guaiacol (2-methoxyphenol), a common lignin degradation product, led to the discovery of Amycolatopsis genes ( gcoAB ) encoding a cytochrome P450 enzyme that converts guaiacol to catechol. However, chromosomal integration of gcoAB in Pseudomonas putida or A. baylyi did not enable guaiacol to be used as the sole carbon source despite catechol being a growth substrate. In ∼1,000 generations, EASy yielded alleles that in single chromosomal copy confer growth on guaiacol. Different variants emerged, including fusions between GcoA and CatA (catechol 1,2-dioxygenase). This study illustrates the power of harnessing chromosomal gene amplification to accelerate the evolution of desirable traits.

  9. Genomics-Based Discovery of Plant Genes for Synthetic Biology of Terpenoid Fragrances: A Case Study in Sandalwood oil Biosynthesis.

    PubMed

    Celedon, J M; Bohlmann, J

    2016-01-01

    Terpenoid fragrances are powerful mediators of ecological interactions in nature and have a long history of traditional and modern industrial applications. Plants produce a great diversity of fragrant terpenoid metabolites, which make them a superb source of biosynthetic genes and enzymes. Advances in fragrance gene discovery have enabled new approaches in synthetic biology of high-value speciality molecules toward applications in the fragrance and flavor, food and beverage, cosmetics, and other industries. Rapid developments in transcriptome and genome sequencing of nonmodel plant species have accelerated the discovery of fragrance biosynthetic pathways. In parallel, advances in metabolic engineering of microbial and plant systems have established platforms for synthetic biology applications of some of the thousands of plant genes that underlie fragrance diversity. While many fragrance molecules (eg, simple monoterpenes) are abundant in readily renewable plant materials, some highly valuable fragrant terpenoids (eg, santalols, ambroxides) are rare in nature and interesting targets for synthetic biology. As a representative example for genomics/transcriptomics enabled gene and enzyme discovery, we describe a strategy used successfully for elucidation of a complete fragrance biosynthetic pathway in sandalwood (Santalum album) and its reconstruction in yeast (Saccharomyces cerevisiae). We address questions related to the discovery of specific genes within large gene families and recovery of rare gene transcripts that are selectively expressed in recalcitrant tissues. To substantiate the validity of the approaches, we describe the combination of methods used in the gene and enzyme discovery of a cytochrome P450 in the fragrant heartwood of tropical sandalwood, responsible for the fragrance defining, final step in the biosynthesis of (Z)-santalols. © 2016 Elsevier Inc. All rights reserved.

  10. SpS5: Accelerating the Rate of Astronomical Discovery

    NASA Astrophysics Data System (ADS)

    Norris, Ray P.

    2010-11-01

    Special Session 5 on Accelerating the Rate of Astronomical Discovery addressed a range of potential limits to progress: paradigmatic, technological, organizational, and political. It examined each issue both from modern and historical perspectives, and drew lessons to guide future progress. A number of issues were identified which may regulate the flow of discoveries, such as the balance between large strongly-focussed projects and instruments, designed to answer the most fundamental questions confronting us, and the need to maintain a creative environment with room for unorthodox thinkers and bold, high risk, projects. Also important is the need to maintain historical and cultural perspectives, and the need to engage the minds of the most brilliant young people on the planet, regardless of their background, ethnicity, gender, or geography.

  11. Copper homeostasis gene discovery in Drosophila melanogaster.

    PubMed

    Norgate, Melanie; Southon, Adam; Zou, Sige; Zhan, Ming; Sun, Yu; Batterham, Phil; Camakaris, James

    2007-06-01

    Recent studies have shown a high level of conservation between Drosophila melanogaster and mammalian copper homeostasis mechanisms. These studies have also demonstrated the efficiency with which this species can be used to characterize novel genes, at both the cellular and whole organism level. As a versatile and inexpensive model organism, Drosophila is also particularly useful for gene discovery applications and thus has the potential to be extremely useful in identifying novel copper homeostasis genes and putative disease genes. In order to assess the suitability of Drosophila for this purpose, three screening approaches have been investigated. These include an analysis of the global transcriptional response to copper in both adult flies and an embryonic cell line using DNA microarray analysis. Two mutagenesis-based screens were also utilized. Several candidate copper homeostasis genes have been identified through this work. In addition, the results of each screen were carefully analyzed to identify any factors influencing efficiency and sensitivity. These are discussed here with the aim of maximizing the efficiency of future screens and the most suitable approaches are outlined. Building on this information, there is great potential for the further use of Drosophila for copper homeostasis gene discovery.

  12. Accelerating Gene Discovery by Phenotyping Whole-Genome Sequenced Multi-mutation Strains and Using the Sequence Kernel Association Test (SKAT)

    PubMed Central

    Garland, Stephanie J.; Mohan, Swetha; Flibotte, Stephane; Muncaster, Quintin; Cai, Jerry; Rademakers, Suzanne; Moerman, Donald G.; Leroux, Michel R.

    2016-01-01

    Forward genetic screens represent powerful, unbiased approaches to uncover novel components in any biological process. Such screens suffer from a major bottleneck, however, namely the cloning of corresponding genes causing the phenotypic variation. Reverse genetic screens have been employed as a way to circumvent this issue, but can often be limited in scope. Here we demonstrate an innovative approach to gene discovery. Using C. elegans as a model system, we used a whole-genome sequenced multi-mutation library, from the Million Mutation Project, together with the Sequence Kernel Association Test (SKAT), to rapidly screen for and identify genes associated with a phenotype of interest, namely defects in dye-filling of ciliated sensory neurons. Such anomalies in dye-filling are often associated with the disruption of cilia, organelles which in humans are implicated in sensory physiology (including vision, smell and hearing), development and disease. Beyond identifying several well characterised dye-filling genes, our approach uncovered three genes not previously linked to ciliated sensory neuron development or function. From these putative novel dye-filling genes, we confirmed the involvement of BGNT-1.1 in ciliated sensory neuron function and morphogenesis. BGNT-1.1 functions at the trans-Golgi network of sheath cells (glia) to influence dye-filling and cilium length, in a cell non-autonomous manner. Notably, BGNT-1.1 is the orthologue of human B3GNT1/B4GAT1, a glycosyltransferase associated with Walker-Warburg syndrome (WWS). WWS is a multigenic disorder characterised by muscular dystrophy as well as brain and eye anomalies. Together, our work unveils an effective and innovative approach to gene discovery, and provides the first evidence that B3GNT1-associated Walker-Warburg syndrome may be considered a ciliopathy. PMID:27508411

  13. Combinatorial materials approach to accelerate materials discovery for transportation (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Tong, Wei

    2017-04-01

    Combinatorial material research offers fast and efficient solutions to identify promising and advanced materials. It has revolutionized the pharmaceutical industry and now is being applied to accelerate the discovery of other new compounds, e.g. superconductors, luminescent materials, catalysts etc. Differing from the traditional trial-and-error process, this approach allows for the synthesis of a large number of compositionally diverse compounds by varying the combinations of the components and adjusting the ratios. It largely reduces the cost of single-sample synthesis/characterization, along with the turnaround time in the material discovery process, therefore, could dramatically change the existing paradigm for discovering and commercializing new materials. This talk outlines the use of combinatorial materials approach in the material discovery in transportation sector. It covers the general introduction to the combinatorial material concept, state of art for its application in energy-related research. At the end, LBNL capabilities in combinatorial materials synthesis and high throughput characterization that are applicable for material discovery research will be highlighted.

  14. cudaMap: a GPU accelerated program for gene expression connectivity mapping

    PubMed Central

    2013-01-01

    Background Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take > 2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping. Results cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance. Conclusion Emerging ‘omics’ technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http

  15. cudaMap: a GPU accelerated program for gene expression connectivity mapping.

    PubMed

    McArt, Darragh G; Bankhead, Peter; Dunne, Philip D; Salto-Tellez, Manuel; Hamilton, Peter; Zhang, Shu-Dong

    2013-10-11

    Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take > 2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping. cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance. Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

  16. Accelerators for Discovery Science and Security applications

    NASA Astrophysics Data System (ADS)

    Todd, A. M. M.; Bluem, H. P.; Jarvis, J. D.; Park, J. H.; Rathke, J. W.; Schultheiss, T. J.

    2015-05-01

    Several Advanced Energy Systems (AES) accelerator projects that span applications in Discovery Science and Security are described. The design and performance of the IR and THz free electron laser (FEL) at the Fritz-Haber-Institut der Max-Planck-Gesellschaft in Berlin that is now an operating user facility for physical chemistry research in molecular and cluster spectroscopy as well as surface science, is highlighted. The device was designed to meet challenging specifications, including a final energy adjustable in the range of 15-50 MeV, low longitudinal emittance (<50 keV-psec) and transverse emittance (<20 π mm-mrad), at more than 200 pC bunch charge with a micropulse repetition rate of 1 GHz and a macropulse length of up to 15 μs. Secondly, we will describe an ongoing effort to develop an ultrafast electron diffraction (UED) source that is scheduled for completion in 2015 with prototype testing taking place at the Brookhaven National Laboratory (BNL) Accelerator Test Facility (ATF). This tabletop X-band system will find application in time-resolved chemical imaging and as a resource for drug-cell interaction analysis. A third active area at AES is accelerators for security applications where we will cover some top-level aspects of THz and X-ray systems that are under development and in testing for stand-off and portal detection.

  17. A brief history of Alzheimer's disease gene discovery.

    PubMed

    Tanzi, Rudolph E

    2013-01-01

    The rich and colorful history of gene discovery in Alzheimer's disease (AD) over the past three decades is as complex and heterogeneous as the disease, itself. Twin and family studies indicate that genetic factors are estimated to play a role in at least 80% of AD cases. The inheritance of AD exhibits a dichotomous pattern. On one hand, rare mutations inAPP, PSEN1, and PSEN2 are fully penetrant for early-onset (<60 years) familial AD, which represents <5% of AD. On the other hand, common gene polymorphisms, such as the 4 and 2 variants of the APOE gene, influence susceptibility for common (>95%) late-onset AD. These four genes account for 30-50% of the inheritability of AD. Genome-wide association studies have recently led to the identification of additional highly confirmed AD candidate genes. Here, I review the past, present, and future of attempts to elucidate the complex and heterogeneous genetic underpinnings of AD along with some of the unique events that made these discoveries possible.

  18. Discovery and validation of a glioblastoma co-expressed gene module

    PubMed Central

    Dunwoodie, Leland J.; Poehlman, William L.; Ficklin, Stephen P.; Feltus, Frank Alexander

    2018-01-01

    Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network. PMID:29541392

  19. Discovery and validation of a glioblastoma co-expressed gene module.

    PubMed

    Dunwoodie, Leland J; Poehlman, William L; Ficklin, Stephen P; Feltus, Frank Alexander

    2018-02-16

    Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network.

  20. GWATCH: a web platform for automated gene association discovery analysis.

    PubMed

    Svitin, Anton; Malov, Sergey; Cherkasov, Nikolay; Geerts, Paul; Rotkevich, Mikhail; Dobrynin, Pavel; Shevchenko, Andrey; Guan, Li; Troyer, Jennifer; Hendrickson, Sher; Dilks, Holli Hutcheson; Oleksyk, Taras K; Donfield, Sharyne; Gomperts, Edward; Jabs, Douglas A; Sezgin, Efe; Van Natta, Mark; Harrigan, P Richard; Brumme, Zabrina L; O'Brien, Stephen J

    2014-01-01

    As genome-wide sequence analyses for complex human disease determinants are expanding, it is increasingly necessary to develop strategies to promote discovery and validation of potential disease-gene associations. Here we present a dynamic web-based platform - GWATCH - that automates and facilitates four steps in genetic epidemiological discovery: 1) Rapid gene association search and discovery analysis of large genome-wide datasets; 2) Expanded visual display of gene associations for genome-wide variants (SNPs, indels, CNVs), including Manhattan plots, 2D and 3D snapshots of any gene region, and a dynamic genome browser illustrating gene association chromosomal regions; 3) Real-time validation/replication of candidate or putative genes suggested from other sources, limiting Bonferroni genome-wide association study (GWAS) penalties; 4) Open data release and sharing by eliminating privacy constraints (The National Human Genome Research Institute (NHGRI) Institutional Review Board (IRB), informed consent, The Health Insurance Portability and Accountability Act (HIPAA) of 1996 etc.) on unabridged results, which allows for open access comparative and meta-analysis. GWATCH is suitable for both GWAS and whole genome sequence association datasets. We illustrate the utility of GWATCH with three large genome-wide association studies for HIV-AIDS resistance genes screened in large multicenter cohorts; however, association datasets from any study can be uploaded and analyzed by GWATCH.

  1. Standardized Plant Disease Evaluations will Enhance Resistance Gene Discovery

    USDA-ARS?s Scientific Manuscript database

    Gene discovery and marker development using DNA based tools require plant populations with well-documented phenotypes. Related crops such as apples and pears may share a number of genes, for example resistance to common diseases, and data mining in one crop may reveal genes for the other. However, u...

  2. Discovery of error-tolerant biclusters from noisy gene expression data.

    PubMed

    Gupta, Rohit; Rao, Navneet; Kumar, Vipin

    2011-11-24

    An important analysis performed on microarray gene-expression data is to discover biclusters, which denote groups of genes that are coherently expressed for a subset of conditions. Various biclustering algorithms have been proposed to find different types of biclusters from these real-valued gene-expression data sets. However, these algorithms suffer from several limitations such as inability to explicitly handle errors/noise in the data; difficulty in discovering small bicliusters due to their top-down approach; inability of some of the approaches to find overlapping biclusters, which is crucial as many genes participate in multiple biological processes. Association pattern mining also produce biclusters as their result and can naturally address some of these limitations. However, traditional association mining only finds exact biclusters, which limits its applicability in real-life data sets where the biclusters may be fragmented due to random noise/errors. Moreover, as they only work with binary or boolean attributes, their application on gene-expression data require transforming real-valued attributes to binary attributes, which often results in loss of information. Many past approaches have tried to address the issue of noise and handling real-valued attributes independently but there is no systematic approach that addresses both of these issues together. In this paper, we first propose a novel error-tolerant biclustering model, 'ET-bicluster', and then propose a bottom-up heuristic-based mining algorithm to sequentially discover error-tolerant biclusters directly from real-valued gene-expression data. The efficacy of our proposed approach is illustrated by comparing it with a recent approach RAP in the context of two biological problems: discovery of functional modules and discovery of biomarkers. For the first problem, two real-valued S.Cerevisiae microarray gene-expression data sets are used to demonstrate that the biclusters obtained from ET

  3. Phenotypic mutant library: potential for gene discovery

    USDA-ARS?s Scientific Manuscript database

    The rapid development of high throughput and affordable Next- Generation Sequencing (NGS) techniques has renewed interest in gene discovery using forward genetics. The conventional forward genetic approach starts with isolation of mutants with a phenotype of interest, mapping the mutation within a s...

  4. Biomarker discovery for colon cancer using a 761 gene RT-PCR assay.

    PubMed

    Clark-Langone, Kim M; Wu, Jenny Y; Sangli, Chithra; Chen, Angela; Snable, James L; Nguyen, Anhthu; Hackett, James R; Baker, Joffre; Yothers, Greg; Kim, Chungyeul; Cronin, Maureen T

    2007-08-15

    Reverse transcription PCR (RT-PCR) is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE) clinical study tumor specimens. This technology has also been used to develop and commercialize a widely used clinical test for breast cancer prognosis and prediction, the Onco typeDX assay. A similar need exists in colon cancer for a test that provides information on the likelihood of disease recurrence in colon cancer (prognosis) and the likelihood of tumor response to standard chemotherapy regimens (prediction). We have now scaled our RT-PCR assay to efficiently screen 761 biomarkers across hundreds of patient samples and applied this process to biomarker discovery in colon cancer. This screening strategy remains attractive due to the inherent advantages of maintaining platform consistency from discovery through clinical application. RNA was extracted from formalin fixed paraffin embedded (FPE) tissue, as old as 28 years, from 354 patients enrolled in NSABP C-01 and C-02 colon cancer studies. Multiplexed reverse transcription reactions were performed using a gene specific primer pool containing 761 unique primers. PCR was performed as independent TaqMan reactions for each candidate gene. Hierarchal clustering demonstrates that genes expected to co-express form obvious, distinct and in certain cases very tightly correlated clusters, validating the reliability of this technical approach to biomarker discovery. We have developed a high throughput, quantitatively precise multi-analyte gene expression platform for biomarker discovery that approaches low density DNA arrays in numbers of genes analyzed while maintaining the high specificity

  5. STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data

    PubMed Central

    Jupiter, Daniel; Chen, Hailin; VanBuren, Vincent

    2009-01-01

    Background Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult. Results STARNET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. STARNET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new HEATSEEKER module. Conclusion STARNET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to

  6. Developing integrated crop knowledge networks to advance candidate gene discovery.

    PubMed

    Hassani-Pak, Keywan; Castellote, Martin; Esch, Maria; Hindle, Matthew; Lysenko, Artem; Taubert, Jan; Rawlings, Christopher

    2016-12-01

    The chances of raising crop productivity to enhance global food security would be greatly improved if we had a complete understanding of all the biological mechanisms that underpinned traits such as crop yield, disease resistance or nutrient and water use efficiency. With more crop genomes emerging all the time, we are nearer having the basic information, at the gene-level, to begin assembling crop gene catalogues and using data from other plant species to understand how the genes function and how their interactions govern crop development and physiology. Unfortunately, the task of creating such a complete knowledge base of gene functions, interaction networks and trait biology is technically challenging because the relevant data are dispersed in myriad databases in a variety of data formats with variable quality and coverage. In this paper we present a general approach for building genome-scale knowledge networks that provide a unified representation of heterogeneous but interconnected datasets to enable effective knowledge mining and gene discovery. We describe the datasets and outline the methods, workflows and tools that we have developed for creating and visualising these networks for the major crop species, wheat and barley. We present the global characteristics of such knowledge networks and with an example linking a seed size phenotype to a barley WRKY transcription factor orthologous to TTG2 from Arabidopsis, we illustrate the value of integrated data in biological knowledge discovery. The software we have developed (www.ondex.org) and the knowledge resources (http://knetminer.rothamsted.ac.uk) we have created are all open-source and provide a first step towards systematic and evidence-based gene discovery in order to facilitate crop improvement.

  7. FastGCN: A GPU Accelerated Tool for Fast Gene Co-Expression Networks

    PubMed Central

    Liang, Meimei; Zhang, Futao; Jin, Gulei; Zhu, Jun

    2015-01-01

    Gene co-expression networks comprise one type of valuable biological networks. Many methods and tools have been published to construct gene co-expression networks; however, most of these tools and methods are inconvenient and time consuming for large datasets. We have developed a user-friendly, accelerated and optimized tool for constructing gene co-expression networks that can fully harness the parallel nature of GPU (Graphic Processing Unit) architectures. Genetic entropies were exploited to filter out genes with no or small expression changes in the raw data preprocessing step. Pearson correlation coefficients were then calculated. After that, we normalized these coefficients and employed the False Discovery Rate to control the multiple tests. At last, modules identification was conducted to construct the co-expression networks. All of these calculations were implemented on a GPU. We also compressed the coefficient matrix to save space. We compared the performance of the GPU implementation with those of multi-core CPU implementations with 16 CPU threads, single-thread C/C++ implementation and single-thread R implementation. Our results show that GPU implementation largely outperforms single-thread C/C++ implementation and single-thread R implementation, and GPU implementation outperforms multi-core CPU implementation when the number of genes increases. With the test dataset containing 16,000 genes and 590 individuals, we can achieve greater than 63 times the speed using a GPU implementation compared with a single-thread R implementation when 50 percent of genes were filtered out and about 80 times the speed when no genes were filtered out. PMID:25602758

  8. FastGCN: a GPU accelerated tool for fast gene co-expression networks.

    PubMed

    Liang, Meimei; Zhang, Futao; Jin, Gulei; Zhu, Jun

    2015-01-01

    Gene co-expression networks comprise one type of valuable biological networks. Many methods and tools have been published to construct gene co-expression networks; however, most of these tools and methods are inconvenient and time consuming for large datasets. We have developed a user-friendly, accelerated and optimized tool for constructing gene co-expression networks that can fully harness the parallel nature of GPU (Graphic Processing Unit) architectures. Genetic entropies were exploited to filter out genes with no or small expression changes in the raw data preprocessing step. Pearson correlation coefficients were then calculated. After that, we normalized these coefficients and employed the False Discovery Rate to control the multiple tests. At last, modules identification was conducted to construct the co-expression networks. All of these calculations were implemented on a GPU. We also compressed the coefficient matrix to save space. We compared the performance of the GPU implementation with those of multi-core CPU implementations with 16 CPU threads, single-thread C/C++ implementation and single-thread R implementation. Our results show that GPU implementation largely outperforms single-thread C/C++ implementation and single-thread R implementation, and GPU implementation outperforms multi-core CPU implementation when the number of genes increases. With the test dataset containing 16,000 genes and 590 individuals, we can achieve greater than 63 times the speed using a GPU implementation compared with a single-thread R implementation when 50 percent of genes were filtered out and about 80 times the speed when no genes were filtered out.

  9. Discovery of Cationic Polymers for Non-viral Gene Delivery using Combinatorial Approaches

    PubMed Central

    Barua, Sutapa; Ramos, James; Potta, Thrimoorthy; Taylor, David; Huang, Huang-Chiao; Montanez, Gabriela; Rege, Kaushal

    2015-01-01

    Gene therapy is an attractive treatment option for diseases of genetic origin, including several cancers and cardiovascular diseases. While viruses are effective vectors for delivering exogenous genes to cells, concerns related to insertional mutagenesis, immunogenicity, lack of tropism, decay and high production costs necessitate the discovery of non-viral methods. Significant efforts have been focused on cationic polymers as non-viral alternatives for gene delivery. Recent studies have employed combinatorial syntheses and parallel screening methods for enhancing the efficacy of gene delivery, biocompatibility of the delivery vehicle, and overcoming cellular level barriers as they relate to polymer-mediated transgene uptake, transport, transcription, and expression. This review summarizes and discusses recent advances in combinatorial syntheses and parallel screening of cationic polymer libraries for the discovery of efficient and safe gene delivery systems. PMID:21843141

  10. Label-assisted mass spectrometry for the acceleration of reaction discovery and optimization

    NASA Astrophysics Data System (ADS)

    Cabrera-Pardo, Jaime R.; Chai, David I.; Liu, Song; Mrksich, Milan; Kozmin, Sergey A.

    2013-05-01

    The identification of new reactions expands our knowledge of chemical reactivity and enables new synthetic applications. Accelerating the pace of this discovery process remains challenging. We describe a highly effective and simple platform for screening a large number of potential chemical reactions in order to discover and optimize previously unknown catalytic transformations, thereby revealing new chemical reactivity. Our strategy is based on labelling one of the reactants with a polyaromatic chemical tag, which selectively undergoes a photoionization/desorption process upon laser irradiation, without the assistance of an external matrix, and enables rapid mass spectrometric detection of any products originating from such labelled reactants in complex reaction mixtures without any chromatographic separation. This method was successfully used for high-throughput discovery and subsequent optimization of two previously unknown benzannulation reactions.

  11. Cancer gene discovery: exploiting insertional mutagenesis

    PubMed Central

    Ranzani, Marco; Annunziato, Stefano; Adams, David J.; Montini, Eugenio

    2013-01-01

    Insertional mutagenesis has been utilized as a functional forward genetics screen for the identification of novel genes involved in the pathogenesis of human cancers. Different insertional mutagens have been successfully used to reveal new cancer genes. For example, retroviruses (RVs) are integrating viruses with the capacity to induce the deregulation of genes in the neighborhood of the insertion site. RVs have been employed for more than 30 years to identify cancer genes in the hematopoietic system and mammary gland. Similarly, another tool that has revolutionized cancer gene discovery is the cut-and-paste transposons. These DNA elements have been engineered to contain strong promoters and stop cassettes that may function to perturb gene expression upon integration proximal to genes. In addition, complex mouse models characterized by tissue-restricted activity of transposons have been developed to identify oncogenes and tumor suppressor genes that control the development of a wide range of solid tumor types, extending beyond those tissues accessible using RV-based approaches. Most recently, lentiviral vectors (LVs) have appeared on the scene for use in cancer gene screens. LVs are replication defective integrating vectors that have the advantage of being able to infect non-dividing cells, in a wide range of cell types and tissues. In this review, we describe the various insertional mutagens focusing on their advantages/limitations and we discuss the new and promising tools that will improve the insertional mutagenesis screens of the future. PMID:23928056

  12. Genes@Work: an efficient algorithm for pattern discovery and multivariate feature selection in gene expression data.

    PubMed

    Lepre, Jorge; Rice, J Jeremy; Tu, Yuhai; Stolovitzky, Gustavo

    2004-05-01

    Despite the growing literature devoted to finding differentially expressed genes in assays probing different tissues types, little attention has been paid to the combinatorial nature of feature selection inherent to large, high-dimensional gene expression datasets. New flexible data analysis approaches capable of searching relevant subgroups of genes and experiments are needed to understand multivariate associations of gene expression patterns with observed phenotypes. We present in detail a deterministic algorithm to discover patterns of multivariate gene associations in gene expression data. The patterns discovered are differential with respect to a control dataset. The algorithm is exhaustive and efficient, reporting all existent patterns that fit a given input parameter set while avoiding enumeration of the entire pattern space. The value of the pattern discovery approach is demonstrated by finding a set of genes that differentiate between two types of lymphoma. Moreover, these genes are found to behave consistently in an independent dataset produced in a different laboratory using different arrays, thus validating the genes selected using our algorithm. We show that the genes deemed significant in terms of their multivariate statistics will be missed using other methods. Our set of pattern discovery algorithms including a user interface is distributed as a package called Genes@Work. This package is freely available to non-commercial users and can be downloaded from our website (http://www.research.ibm.com/FunGen).

  13. Comprehensive Clinical Phenotyping and Genetic Mapping for the Discovery of Autism Susceptibility Genes

    DTIC Science & Technology

    2013-03-14

    SUPPLEMENTARY NOTES 14. ABSTRACT Autism is an extremely common and heterogeneous neurodevelopmental disorder. While genetic factors are known to play...AFRL-SA-WP-TR-2013-0013 Comprehensive Clinical Phenotyping and Genetic Mapping for the Discovery of Autism Susceptibility Genes...Genetic Mapping for the Discovery of Autism Susceptibility Genes 5a. CONTRACT NUMBER N/A 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER N/A 6

  14. Functional Gene Discovery and Characterization of Genes and Alleles Affecting Wood Biomass Yield and Quality in Populus

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Busov, Victor

    Adoption of biofuels as economically and environmentally viable alternative to fossil fuels would require development of specialized bioenergy varieties. A major goal in the breeding of such varieties is the improvement of lignocellulosic biomass yield and quality. These are complex traits and understanding the underpinning molecular mechanism can assist and accelerate their improvement. This is particularly important for tree bioenergy crops like poplars (species and hybrids from the genus Populus), for which breeding progress is extremely slow due to long generation cycles. A variety of approaches have been already undertaken to better understand the molecular bases of biomass yield andmore » quality in poplar. An obvious void in these undertakings has been the application of mutagenesis. Mutagenesis has been instrumental in the discovery and characterization of many plant traits including such that affect biomass yield and quality. In this proposal we use activation tagging to discover genes that can significantly affect biomass associated traits directly in poplar, a premier bioenergy crop. We screened a population of 5,000 independent poplar activation tagging lines under greenhouse conditions for a battery of biomass yield traits. These same plants were then analyzed for changes in wood chemistry using pyMBMS. As a result of these screens we have identified nearly 800 mutants, which are significantly (P<0.05) different when compared to wild type. Of these majority (~700) are affected in one of ten different biomass yield traits and 100 in biomass quality traits (e.g., lignin, S/G ration and C6/C5 sugars). We successfully recovered the position of the tag in approximately 130 lines, showed activation in nearly half of them and performed recapitulation experiments with 20 genes prioritized by the significance of the phenotype. Recapitulation experiments are still ongoing for many of the genes but the results are encouraging. For example, we have shown

  15. Nearing saturation of cancer driver gene discovery.

    PubMed

    Hsiehchen, David; Hsieh, Antony

    2018-06-15

    Extensive sequencing efforts of cancer genomes such as The Cancer Genome Atlas (TCGA) have been undertaken to uncover bona fide cancer driver genes which has enhanced our understanding of cancer and revealed therapeutic targets. However, the number of driver gene mutations is bounded, indicating that there must be a point when further sequencing efforts will be excessive. We found that there was a significant positive correlation between sample size and identified driver gene mutations across 33 cancers sequenced by the TCGA, which is expected if additional sequencing is still leading to the identification of more driver genes. However, the rate of new cancer driver genes being discovered with larger samples is declining rapidly. Our analysis provides a general guide for determining which cancer types would likely benefit from additional sequencing efforts, particularly those with relatively high rates of cancer driver gene discovery. Our results argue that past strategies of indiscriminately sequencing as many specimens as possible for all cancer types is becoming inefficient. In addition, without significant investments into applying our knowledge of cancer genomes, we risk sequencing more cancer genomes for the sake of sequencing rather than meaningful patient benefit.

  16. Standardized plant disease evaluations will enhance resistance gene discovery

    USDA-ARS?s Scientific Manuscript database

    Gene discovery and marker development using DNA-based tools require plant populations with well documented phenotypes. If dissimilar phenotype evaluation methods or data scoring techniques are employed with different crops, or at different labs for the same crops, then data mining for genetic marker...

  17. Literature Mining for the Discovery of Hidden Connections between Drugs, Genes and Diseases

    PubMed Central

    Frijters, Raoul; van Vugt, Marianne; Smeets, Ruben; van Schaik, René; de Vlieg, Jacob; Alkema, Wynand

    2010-01-01

    The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs. PMID:20885778

  18. Identification of differentially expressed genes and false discovery rate in microarray studies.

    PubMed

    Gusnanto, Arief; Calza, Stefano; Pawitan, Yudi

    2007-04-01

    To highlight the development in microarray data analysis for the identification of differentially expressed genes, particularly via control of false discovery rate. The emergence of high-throughput technology such as microarrays raises two fundamental statistical issues: multiplicity and sensitivity. We focus on the biological problem of identifying differentially expressed genes. First, multiplicity arises due to testing tens of thousands of hypotheses, rendering the standard P value meaningless. Second, known optimal single-test procedures such as the t-test perform poorly in the context of highly multiple tests. The standard approach of dealing with multiplicity is too conservative in the microarray context. The false discovery rate concept is fast becoming the key statistical assessment tool replacing the P value. We review the false discovery rate approach and argue that it is more sensible for microarray data. We also discuss some methods to take into account additional information from the microarrays to improve the false discovery rate. There is growing consensus on how to analyse microarray data using the false discovery rate framework in place of the classical P value. Further research is needed on the preprocessing of the raw data, such as the normalization step and filtering, and on finding the most sensitive test procedure.

  19. Accelerating scientific discovery : 2007 annual report.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Beckman, P.; Dave, P.; Drugan, C.

    2008-11-14

    As a gateway for scientific discovery, the Argonne Leadership Computing Facility (ALCF) works hand in hand with the world's best computational scientists to advance research in a diverse span of scientific domains, ranging from chemistry, applied mathematics, and materials science to engineering physics and life sciences. Sponsored by the U.S. Department of Energy's (DOE) Office of Science, researchers are using the IBM Blue Gene/L supercomputer at the ALCF to study and explore key scientific problems that underlie important challenges facing our society. For instance, a research team at the University of California-San Diego/ SDSC is studying the molecular basis ofmore » Parkinson's disease. The researchers plan to use the knowledge they gain to discover new drugs to treat the disease and to identify risk factors for other diseases that are equally prevalent. Likewise, scientists from Pratt & Whitney are using the Blue Gene to understand the complex processes within aircraft engines. Expanding our understanding of jet engine combustors is the secret to improved fuel efficiency and reduced emissions. Lessons learned from the scientific simulations of jet engine combustors have already led Pratt & Whitney to newer designs with unprecedented reductions in emissions, noise, and cost of ownership. ALCF staff members provide in-depth expertise and assistance to those using the Blue Gene/L and optimizing user applications. Both the Catalyst and Applications Performance Engineering and Data Analytics (APEDA) teams support the users projects. In addition to working with scientists running experiments on the Blue Gene/L, we have become a nexus for the broader global community. In partnership with the Mathematics and Computer Science Division at Argonne National Laboratory, we have created an environment where the world's most challenging computational science problems can be addressed. Our expertise in high-end scientific computing enables us to provide guidance for

  20. Accelerating target discovery using pre-competitive open science-patients need faster innovation more than anyone else.

    PubMed

    Low, Eric; Bountra, Chas; Lee, Wen Hwa

    2016-01-01

    We are experiencing a new era enabled by unencumbered access to high quality data through the emergence of open science initiatives in the historically challenging area of early stage drug discovery. At the same time, many patient-centric organisations are taking matters into their own hands by participating in, enabling and funding research. Here we present the rationale behind the innovative partnership between the Structural Genomics Consortium (SGC)-an open, pre-competitive pre-clinical research consortium and the research-focused patient organisation Myeloma UK to create a new, comprehensive platform to accelerate the discovery and development of new treatments for multiple myeloma.

  1. Shortening tobacco life cycle accelerates functional gene identification in genomic research.

    PubMed

    Ning, G; Xiao, X; Lv, H; Li, X; Zuo, Y; Bao, M

    2012-11-01

    Definitive allocation of function requires the introduction of genetic mutations and analysis of their phenotypic consequences. Novel, rapid and convenient techniques or materials are very important and useful to accelerate gene identification in functional genomics research. Here, over-expression of PmFT (Prunus mume), a novel FT orthologue, and PtFT (Populus tremula) lead to shortening of the tobacco life cycle. A series of novel short life cycle stable tobacco lines (30-50 days) were developed through repeated self-crossing selection breeding. Based on the second transformation via a gusA reporter gene, the promoter from BpFULL1 in silver birch (Betula pendula) and the gene (CPC) from Arabidopsis thaliana were effectively tested using short life cycle tobacco lines. Comparative analysis among wild type, short life cycle tobacco and Arabidopsis transformation system verified that it is optional to accelerate functional gene studies by shortening host plant material life cycle, at least in these short life cycle tobacco lines. The results verified that the novel short life cycle transgenic tobacco lines not only combine the advantages of economic nursery requirements and a simple transformation system, but also provide a robust, effective and stable host system to accelerate gene analysis. Thus, shortening tobacco life cycle strategy is feasible to accelerate heterologous or homologous functional gene identification in genomic research. © 2012 German Botanical Society and The Royal Botanical Society of the Netherlands.

  2. Lung tumor diagnosis and subtype discovery by gene expression profiling.

    PubMed

    Wang, Lu-yong; Tu, Zhuowen

    2006-01-01

    The optimal treatment of patients with complex diseases, such as cancers, depends on the accurate diagnosis by using a combination of clinical and histopathological data. In many scenarios, it becomes tremendously difficult because of the limitations in clinical presentation and histopathology. To accurate diagnose complex diseases, the molecular classification based on gene or protein expression profiles are indispensable for modern medicine. Moreover, many heterogeneous diseases consist of various potential subtypes in molecular basis and differ remarkably in their response to therapies. It is critical to accurate predict subgroup on disease gene expression profiles. More fundamental knowledge of the molecular basis and classification of disease could aid in the prediction of patient outcome, the informed selection of therapies, and identification of novel molecular targets for therapy. In this paper, we propose a new disease diagnostic method, probabilistic boosting tree (PB tree) method, on gene expression profiles of lung tumors. It enables accurate disease classification and subtype discovery in disease. It automatically constructs a tree in which each node combines a number of weak classifiers into a strong classifier. Also, subtype discovery is naturally embedded in the learning process. Our algorithm achieves excellent diagnostic performance, and meanwhile it is capable of detecting the disease subtype based on gene expression profile.

  3. OpenZika: An IBM World Community Grid Project to Accelerate Zika Virus Drug Discovery.

    PubMed

    Ekins, Sean; Perryman, Alexander L; Horta Andrade, Carolina

    2016-10-01

    The Zika virus outbreak in the Americas has caused global concern. To help accelerate this fight against Zika, we launched the OpenZika project. OpenZika is an IBM World Community Grid Project that uses distributed computing on millions of computers and Android devices to run docking experiments, in order to dock tens of millions of drug-like compounds against crystal structures and homology models of Zika proteins (and other related flavivirus targets). This will enable the identification of new candidates that can then be tested in vitro, to advance the discovery and development of new antiviral drugs against the Zika virus. The docking data is being made openly accessible so that all members of the global research community can use it to further advance drug discovery studies against Zika and other related flaviviruses.

  4. OpenZika: An IBM World Community Grid Project to Accelerate Zika Virus Drug Discovery

    PubMed Central

    Perryman, Alexander L.; Horta Andrade, Carolina

    2016-01-01

    The Zika virus outbreak in the Americas has caused global concern. To help accelerate this fight against Zika, we launched the OpenZika project. OpenZika is an IBM World Community Grid Project that uses distributed computing on millions of computers and Android devices to run docking experiments, in order to dock tens of millions of drug-like compounds against crystal structures and homology models of Zika proteins (and other related flavivirus targets). This will enable the identification of new candidates that can then be tested in vitro, to advance the discovery and development of new antiviral drugs against the Zika virus. The docking data is being made openly accessible so that all members of the global research community can use it to further advance drug discovery studies against Zika and other related flaviviruses. PMID:27764115

  5. Microbial genome mining for accelerated natural products discovery: is a renaissance in the making?

    PubMed

    Bachmann, Brian O; Van Lanen, Steven G; Baltz, Richard H

    2014-02-01

    Microbial genome mining is a rapidly developing approach to discover new and novel secondary metabolites for drug discovery. Many advances have been made in the past decade to facilitate genome mining, and these are reviewed in this Special Issue of the Journal of Industrial Microbiology and Biotechnology. In this Introductory Review, we discuss the concept of genome mining and why it is important for the revitalization of natural product discovery; what microbes show the most promise for focused genome mining; how microbial genomes can be mined; how genome mining can be leveraged with other technologies; how progress on genome mining can be accelerated; and who should fund future progress in this promising field. We direct interested readers to more focused reviews on the individual topics in this Special Issue for more detailed summaries on the current state-of-the-art.

  6. Turning publicly available gene expression data into discoveries using gene set context analysis.

    PubMed

    Ji, Zhicheng; Vokes, Steven A; Dang, Chi V; Ji, Hongkai

    2016-01-08

    Gene Set Context Analysis (GSCA) is an open source software package to help researchers use massive amounts of publicly available gene expression data (PED) to make discoveries. Users can interactively visualize and explore gene and gene set activities in 25,000+ consistently normalized human and mouse gene expression samples representing diverse biological contexts (e.g. different cells, tissues and disease types, etc.). By providing one or multiple genes or gene sets as input and specifying a gene set activity pattern of interest, users can query the expression compendium to systematically identify biological contexts associated with the specified gene set activity pattern. In this way, researchers with new gene sets from their own experiments may discover previously unknown contexts of gene set functions and hence increase the value of their experiments. GSCA has a graphical user interface (GUI). The GUI makes the analysis convenient and customizable. Analysis results can be conveniently exported as publication quality figures and tables. GSCA is available at https://github.com/zji90/GSCA. This software significantly lowers the bar for biomedical investigators to use PED in their daily research for generating and screening hypotheses, which was previously difficult because of the complexity, heterogeneity and size of the data. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.

    PubMed

    Hassani-Pak, Keywan; Rawlings, Christopher

    2017-06-13

    Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.

  8. Accelerating the discovery of materials for clean energy in the era of smart automation

    NASA Astrophysics Data System (ADS)

    Tabor, Daniel P.; Roch, Loïc M.; Saikin, Semion K.; Kreisbeck, Christoph; Sheberla, Dennis; Montoya, Joseph H.; Dwaraknath, Shyam; Aykol, Muratahan; Ortiz, Carlos; Tribukait, Hermann; Amador-Bedolla, Carlos; Brabec, Christoph J.; Maruyama, Benji; Persson, Kristin A.; Aspuru-Guzik, Alán

    2018-05-01

    The discovery and development of novel materials in the field of energy are essential to accelerate the transition to a low-carbon economy. Bringing recent technological innovations in automation, robotics and computer science together with current approaches in chemistry, materials synthesis and characterization will act as a catalyst for revolutionizing traditional research and development in both industry and academia. This Perspective provides a vision for an integrated artificial intelligence approach towards autonomous materials discovery, which, in our opinion, will emerge within the next 5 to 10 years. The approach we discuss requires the integration of the following tools, which have already seen substantial development to date: high-throughput virtual screening, automated synthesis planning, automated laboratories and machine learning algorithms. In addition to reducing the time to deployment of new materials by an order of magnitude, this integrated approach is expected to lower the cost associated with the initial discovery. Thus, the price of the final products (for example, solar panels, batteries and electric vehicles) will also decrease. This in turn will enable industries and governments to meet more ambitious targets in terms of reducing greenhouse gas emissions at a faster pace.

  9. Accelerating Chemical Discovery with Machine Learning: Simulated Evolution of Spin Crossover Complexes with an Artificial Neural Network.

    PubMed

    Janet, Jon Paul; Chan, Lydia; Kulik, Heather J

    2018-03-01

    Machine learning (ML) has emerged as a powerful complement to simulation for materials discovery by reducing time for evaluation of energies and properties at accuracy competitive with first-principles methods. We use genetic algorithm (GA) optimization to discover unconventional spin-crossover complexes in combination with efficient scoring from an artificial neural network (ANN) that predicts spin-state splitting of inorganic complexes. We explore a compound space of over 5600 candidate materials derived from eight metal/oxidation state combinations and a 32-ligand pool. We introduce a strategy for error-aware ML-driven discovery by limiting how far the GA travels away from the nearest ANN training points while maximizing property (i.e., spin-splitting) fitness, leading to discovery of 80% of the leads from full chemical space enumeration. Over a 51-complex subset, average unsigned errors (4.5 kcal/mol) are close to the ANN's baseline 3 kcal/mol error. By obtaining leads from the trained ANN within seconds rather than days from a DFT-driven GA, this strategy demonstrates the power of ML for accelerating inorganic material discovery.

  10. Discovery of cancer common and specific driver gene sets

    PubMed Central

    2017-01-01

    Abstract Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found. PMID:28168295

  11. Comparative Analysis of Syntenic Genes in Grass Genomes Reveals Accelerated Rates of Gene Structure and Coding Sequence Evolution in Polyploid Wheat1[W][OA

    PubMed Central

    Akhunov, Eduard D.; Sehgal, Sunish; Liang, Hanquan; Wang, Shichen; Akhunova, Alina R.; Kaur, Gaganpreet; Li, Wanlong; Forrest, Kerrie L.; See, Deven; Šimková, Hana; Ma, Yaqin; Hayden, Matthew J.; Luo, Mingcheng; Faris, Justin D.; Doležel, Jaroslav; Gill, Bikram S.

    2013-01-01

    Cycles of whole-genome duplication (WGD) and diploidization are hallmarks of eukaryotic genome evolution and speciation. Polyploid wheat (Triticum aestivum) has had a massive increase in genome size largely due to recent WGDs. How these processes may impact the dynamics of gene evolution was studied by comparing the patterns of gene structure changes, alternative splicing (AS), and codon substitution rates among wheat and model grass genomes. In orthologous gene sets, significantly more acquired and lost exonic sequences were detected in wheat than in model grasses. In wheat, 35% of these gene structure rearrangements resulted in frame-shift mutations and premature termination codons. An increased codon mutation rate in the wheat lineage compared with Brachypodium distachyon was found for 17% of orthologs. The discovery of premature termination codons in 38% of expressed genes was consistent with ongoing pseudogenization of the wheat genome. The rates of AS within the individual wheat subgenomes (21%–25%) were similar to diploid plants. However, we uncovered a high level of AS pattern divergence between the duplicated homeologous copies of genes. Our results are consistent with the accelerated accumulation of AS isoforms, nonsynonymous mutations, and gene structure rearrangements in the wheat lineage, likely due to genetic redundancy created by WGDs. Whereas these processes mostly contribute to the degeneration of a duplicated genome and its diploidization, they have the potential to facilitate the origin of new functional variations, which, upon selection in the evolutionary lineage, may play an important role in the origin of novel traits. PMID:23124323

  12. Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments

    PubMed Central

    Wolverton, Christopher; Hattrick-Simpers, Jason; Mehta, Apurva

    2018-01-01

    With more than a hundred elements in the periodic table, a large number of potential new materials exist to address the technological and societal challenges we face today; however, without some guidance, searching through this vast combinatorial space is frustratingly slow and expensive, especially for materials strongly influenced by processing. We train a machine learning (ML) model on previously reported observations, parameters from physiochemical theories, and make it synthesis method–dependent to guide high-throughput (HiTp) experiments to find a new system of metallic glasses in the Co-V-Zr ternary. Experimental observations are in good agreement with the predictions of the model, but there are quantitative discrepancies in the precise compositions predicted. We use these discrepancies to retrain the ML model. The refined model has significantly improved accuracy not only for the Co-V-Zr system but also across all other available validation data. We then use the refined model to guide the discovery of metallic glasses in two additional previously unreported ternaries. Although our approach of iterative use of ML and HiTp experiments has guided us to rapid discovery of three new glass-forming systems, it has also provided us with a quantitatively accurate, synthesis method–sensitive predictor for metallic glasses that improves performance with use and thus promises to greatly accelerate discovery of many new metallic glasses. We believe that this discovery paradigm is applicable to a wider range of materials and should prove equally powerful for other materials and properties that are synthesis path–dependent and that current physiochemical theories find challenging to predict. PMID:29662953

  13. Computational drug discovery

    PubMed Central

    Ou-Yang, Si-sheng; Lu, Jun-yan; Kong, Xiang-qian; Liang, Zhong-jie; Luo, Cheng; Jiang, Hualiang

    2012-01-01

    Computational drug discovery is an effective strategy for accelerating and economizing drug discovery and development process. Because of the dramatic increase in the availability of biological macromolecule and small molecule information, the applicability of computational drug discovery has been extended and broadly applied to nearly every stage in the drug discovery and development workflow, including target identification and validation, lead discovery and optimization and preclinical tests. Over the past decades, computational drug discovery methods such as molecular docking, pharmacophore modeling and mapping, de novo design, molecular similarity calculation and sequence-based virtual screening have been greatly improved. In this review, we present an overview of these important computational methods, platforms and successful applications in this field. PMID:22922346

  14. Discovery of a widely distributed toxin biosynthetic gene cluster

    PubMed Central

    Lee, Shaun W.; Mitchell, Douglas A.; Markley, Andrew L.; Hensler, Mary E.; Gonzalez, David; Wohlrab, Aaron; Dorrestein, Pieter C.; Nizet, Victor; Dixon, Jack E.

    2008-01-01

    Bacteriocins represent a large family of ribosomally produced peptide antibiotics. Here we describe the discovery of a widely conserved biosynthetic gene cluster for the synthesis of thiazole and oxazole heterocycles on ribosomally produced peptides. These clusters encode a toxin precursor and all necessary proteins for toxin maturation and export. Using the toxin precursor peptide and heterocycle-forming synthetase proteins from the human pathogen Streptococcus pyogenes, we demonstrate the in vitro reconstitution of streptolysin S activity. We provide evidence that the synthetase enzymes, as predicted from our bioinformatics analysis, introduce heterocycles onto precursor peptides, thereby providing molecular insight into the chemical structure of streptolysin S. Furthermore, our studies reveal that the synthetase exhibits relaxed substrate specificity and modifies toxin precursors from both related and distant species. Given our findings, it is likely that the discovery of similar peptidic toxins will rapidly expand to existing and emerging genomes. PMID:18375757

  15. Streptomyces species: Ideal chassis for natural product discovery and overproduction.

    PubMed

    Liu, Ran; Deng, Zixin; Liu, Tiangang

    2018-05-28

    There is considerable interest in mining organisms for new natural products (NPs) and in improving methods to overproduce valuable NPs. Because of the rapid development of tools and strategies for metabolic engineering and the markedly increased knowledge of the biosynthetic pathways and genetics of NP-producing organisms, genome mining and overproduction of NPs can be dramatically accelerated. In particular, Streptomyces species have been proposed as suitable chassis organisms for NP discovery and overproduction because of their many unique characteristics not shared with yeast, Escherichia coli, or other microorganisms. In this review, we summarize the methods for genome sequencing, gene cluster prediction, and gene editing in Streptomyces, as well as metabolic engineering strategies for NP overproduction and approaches for generating new products. Finally, two strategies for utilizing Streptomyces as the chassis for NP discovery and overproduction are emphasized. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  16. MAGIC database and interfaces: an integrated package for gene discovery and expression.

    PubMed

    Cordonnier-Pratt, Marie-Michèle; Liang, Chun; Wang, Haiming; Kolychev, Dmitri S; Sun, Feng; Freeman, Robert; Sullivan, Robert; Pratt, Lee H

    2004-01-01

    The rapidly increasing rate at which biological data is being produced requires a corresponding growth in relational databases and associated tools that can help laboratories contend with that data. With this need in mind, we describe here a Modular Approach to a Genomic, Integrated and Comprehensive (MAGIC) Database. This Oracle 9i database derives from an initial focus in our laboratory on gene discovery via production and analysis of expressed sequence tags (ESTs), and subsequently on gene expression as assessed by both EST clustering and microarrays. The MAGIC Gene Discovery portion of the database focuses on information derived from DNA sequences and on its biological relevance. In addition to MAGIC SEQ-LIMS, which is designed to support activities in the laboratory, it contains several additional subschemas. The latter include MAGIC Admin for database administration, MAGIC Sequence for sequence processing as well as sequence and clone attributes, MAGIC Cluster for the results of EST clustering, MAGIC Polymorphism in support of microsatellite and single-nucleotide-polymorphism discovery, and MAGIC Annotation for electronic annotation by BLAST and BLAT. The MAGIC Microarray portion is a MIAME-compliant database with two components at present. These are MAGIC Array-LIMS, which makes possible remote entry of all information into the database, and MAGIC Array Analysis, which provides data mining and visualization. Because all aspects of interaction with the MAGIC Database are via a web browser, it is ideally suited not only for individual research laboratories but also for core facilities that serve clients at any distance.

  17. IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes.

    PubMed

    Hadjithomas, Michalis; Chen, I-Min A; Chu, Ken; Huang, Jinghua; Ratner, Anna; Palaniappan, Krishna; Andersen, Evan; Markowitz, Victor; Kyrpides, Nikos C; Ivanova, Natalia N

    2017-01-04

    Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic gene clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  18. IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes

    DOE PAGES

    Hadjithomas, Michalis; Chen, I-Min A.; Chu, Ken; ...

    2016-11-29

    Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic genemore » clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery.« less

  19. IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hadjithomas, Michalis; Chen, I-Min A.; Chu, Ken

    Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic genemore » clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery.« less

  20. In silico mining and PCR-based approaches to transcription factor discovery in non-model plants: gene discovery of the WRKY transcription factors in conifers.

    PubMed

    Liu, Jun-Jun; Xiang, Yu

    2011-01-01

    WRKY transcription factors are key regulators of numerous biological processes in plant growth and development, as well as plant responses to abiotic and biotic stresses. Research on biological functions of plant WRKY genes has focused in the past on model plant species or species with largely characterized transcriptomes. However, a variety of non-model plants, such as forest conifers, are essential as feed, biofuel, and wood or for sustainable ecosystems. Identification of WRKY genes in these non-model plants is equally important for understanding the evolutionary and function-adaptive processes of this transcription factor family. Because of limited genomic information, the rarity of regulatory gene mRNAs in transcriptomes, and the sequence divergence to model organism genes, identification of transcription factors in non-model plants using methods similar to those generally used for model plants is difficult. This chapter describes a gene family discovery strategy for identification of WRKY transcription factors in conifers by a combination of in silico-based prediction and PCR-based experimental approaches. Compared to traditional cDNA library screening or EST sequencing at transcriptome scales, this integrated gene discovery strategy provides fast, simple, reliable, and specific methods to unveil the WRKY gene family at both genome and transcriptome levels in non-model plants.

  1. A new approach to the rationale discovery of polymeric biomaterials

    PubMed Central

    Kohn, Joachim; Welsh, William J.; Knight, Doyle

    2007-01-01

    This paper attempts to illustrate both the need for new approaches to biomaterials discovery as well as the significant promise inherent in the use of combinatorial and computational design strategies. The key observation of this Leading Opinion Paper is that the biomaterials community has been slow to embrace advanced biomaterials discovery tools such as combinatorial methods, high throughput experimentation, and computational modeling in spite of the significant promise shown by these discovery tools in materials science, medicinal chemistry and the pharmaceutical industry. It seems that the complexity of living cells and their interactions with biomaterials has been a conceptual as well as a practical barrier to the use of advanced discovery tools in biomaterials science. However, with the continued increase in computer power, the goal of predicting the biological response of cells in contact with biomaterials surfaces is within reach. Once combinatorial synthesis, high throughput experimentation, and computational modeling are integrated into the biomaterials discovery process, a significant acceleration is possible in the pace of development of improved medical implants, tissue regeneration scaffolds, and gene/drug delivery systems. PMID:17644176

  2. Systematic Evaluation of Molecular Networks for Discovery of Disease Genes.

    PubMed

    Huang, Justin K; Carlin, Daniel E; Yu, Michael Ku; Zhang, Wei; Kreisberg, Jason F; Tamayo, Pablo; Ideker, Trey

    2018-04-25

    Gene networks are rapidly growing in size and number, raising the question of which networks are most appropriate for particular applications. Here, we evaluate 21 human genome-wide interaction networks for their ability to recover 446 disease gene sets identified through literature curation, gene expression profiling, or genome-wide association studies. While all networks have some ability to recover disease genes, we observe a wide range of performance with STRING, ConsensusPathDB, and GIANT networks having the best performance overall. A general tendency is that performance scales with network size, suggesting that new interaction discovery currently outweighs the detrimental effects of false positives. Correcting for size, we find that the DIP network provides the highest efficiency (value per interaction). Based on these results, we create a parsimonious composite network with both high efficiency and performance. This work provides a benchmark for selection of molecular networks in human disease research. Copyright © 2018 Elsevier Inc. All rights reserved.

  3. Global Landscape of a Co-Expressed Gene Network in Barley and its Application to Gene Discovery in Triticeae Crops

    PubMed Central

    Mochida, Keiichi; Uehara-Yamaguchi, Yukiko; Yoshida, Takuhiro; Sakurai, Tetsuya; Shinozaki, Kazuo

    2011-01-01

    Accumulated transcriptome data can be used to investigate regulatory networks of genes involved in various biological systems. Co-expression analysis data sets generated from comprehensively collected transcriptome data sets now represent efficient resources that are capable of facilitating the discovery of genes with closely correlated expression patterns. In order to construct a co-expression network for barley, we analyzed 45 publicly available experimental series, which are composed of 1,347 sets of GeneChip data for barley. On the basis of a gene-to-gene weighted correlation coefficient, we constructed a global barley co-expression network and classified it into clusters of subnetwork modules. The resulting clusters are candidates for functional regulatory modules in the barley transcriptome. To annotate each of the modules, we performed comparative annotation using genes in Arabidopsis and Brachypodium distachyon. On the basis of a comparative analysis between barley and two model species, we investigated functional properties from the representative distributions of the gene ontology (GO) terms. Modules putatively involved in drought stress response and cellulose biogenesis have been identified. These modules are discussed to demonstrate the effectiveness of the co-expression analysis. Furthermore, we applied the data set of co-expressed genes coupled with comparative analysis in attempts to discover potentially Triticeae-specific network modules. These results demonstrate that analysis of the co-expression network of the barley transcriptome together with comparative analysis should promote the process of gene discovery in barley. Furthermore, the insights obtained should be transferable to investigations of Triticeae plants. The associated data set generated in this analysis is publicly accessible at http://coexpression.psc.riken.jp/barley/. PMID:21441235

  4. Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ren, Fang; Ward, Logan; Williams, Travis

    With more than a hundred elements in the periodic table, a large number of potential new materials exist to address the technological and societal challenges we face today; however, without some guidance, searching through this vast combinatorial space is frustratingly slow and expensive, especially for materials strongly influenced by processing. We train a machine learning (ML) model on previously reported observations, parameters from physiochemical theories, and make it synthesis method–dependent to guide high-throughput (HiTp) experiments to find a new system of metallic glasses in the Co-V-Zr ternary. Experimental observations are in good agreement with the predictions of the model, butmore » there are quantitative discrepancies in the precise compositions predicted. We use these discrepancies to retrain the ML model. The refined model has significantly improved accuracy not only for the Co-V-Zr system but also across all other available validation data. We then use the refined model to guide the discovery of metallic glasses in two additional previously unreported ternaries. Although our approach of iterative use of ML and HiTp experiments has guided us to rapid discovery of three new glass-forming systems, it has also provided us with a quantitatively accurate, synthesis method–sensitive predictor for metallic glasses that improves performance with use and thus promises to greatly accelerate discovery of many new metallic glasses. We believe that this discovery paradigm is applicable to a wider range of materials and should prove equally powerful for other materials and properties that are synthesis path–dependent and that current physiochemical theories find challenging to predict.« less

  5. Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments

    DOE PAGES

    Ren, Fang; Ward, Logan; Williams, Travis; ...

    2018-04-01

    With more than a hundred elements in the periodic table, a large number of potential new materials exist to address the technological and societal challenges we face today; however, without some guidance, searching through this vast combinatorial space is frustratingly slow and expensive, especially for materials strongly influenced by processing. We train a machine learning (ML) model on previously reported observations, parameters from physiochemical theories, and make it synthesis method–dependent to guide high-throughput (HiTp) experiments to find a new system of metallic glasses in the Co-V-Zr ternary. Experimental observations are in good agreement with the predictions of the model, butmore » there are quantitative discrepancies in the precise compositions predicted. We use these discrepancies to retrain the ML model. The refined model has significantly improved accuracy not only for the Co-V-Zr system but also across all other available validation data. We then use the refined model to guide the discovery of metallic glasses in two additional previously unreported ternaries. Although our approach of iterative use of ML and HiTp experiments has guided us to rapid discovery of three new glass-forming systems, it has also provided us with a quantitatively accurate, synthesis method–sensitive predictor for metallic glasses that improves performance with use and thus promises to greatly accelerate discovery of many new metallic glasses. We believe that this discovery paradigm is applicable to a wider range of materials and should prove equally powerful for other materials and properties that are synthesis path–dependent and that current physiochemical theories find challenging to predict.« less

  6. Accelerated oral nanomedicine discovery from miniaturized screening to clinical production exemplified by paediatric HIV nanotherapies

    NASA Astrophysics Data System (ADS)

    Giardiello, Marco; Liptrott, Neill J.; McDonald, Tom O.; Moss, Darren; Siccardi, Marco; Martin, Phil; Smith, Darren; Gurjar, Rohan; Rannard, Steve P.; Owen, Andrew

    2016-10-01

    Considerable scope exists to vary the physical and chemical properties of nanoparticles, with subsequent impact on biological interactions; however, no accelerated process to access large nanoparticle material space is currently available, hampering the development of new nanomedicines. In particular, no clinically available nanotherapies exist for HIV populations and conventional paediatric HIV medicines are poorly available; one current paediatric formulation utilizes high ethanol concentrations to solubilize lopinavir, a poorly soluble antiretroviral. Here we apply accelerated nanomedicine discovery to generate a potential aqueous paediatric HIV nanotherapy, with clinical translation and regulatory approval for human evaluation. Our rapid small-scale screening approach yields large libraries of solid drug nanoparticles (160 individual components) targeting oral dose. Screening uses 1 mg of drug compound per library member and iterative pharmacological and chemical evaluation establishes potential candidates for progression through to clinical manufacture. The wide applicability of our strategy has implications for multiple therapy development programmes.

  7. Modern approaches to accelerate discovery of new antischistosomal drugs.

    PubMed

    Neves, Bruno Junior; Muratov, Eugene; Machado, Renato Beilner; Andrade, Carolina Horta; Cravo, Pedro Vitor Lemos

    2016-06-01

    The almost exclusive use of only praziquantel for the treatment of schistosomiasis has raised concerns about the possible emergence of drug-resistant schistosomes. Consequently, there is an urgent need for new antischistosomal drugs. The identification of leads and the generation of high quality data are crucial steps in the early stages of schistosome drug discovery projects. Herein, the authors focus on the current developments in antischistosomal lead discovery, specifically referring to the use of automated in vitro target-based and whole-organism screens and virtual screening of chemical databases. They highlight the strengths and pitfalls of each of the above-mentioned approaches, and suggest possible roadmaps towards the integration of several strategies, which may contribute for optimizing research outputs and led to more successful and cost-effective drug discovery endeavors. Increasing partnerships and access to funding for drug discovery have strengthened the battle against schistosomiasis in recent years. However, the authors believe this battle also includes innovative strategies to overcome scientific challenges. In this context, significant advances of in vitro screening as well as computer-aided drug discovery have contributed to increase the success rate and reduce the costs of drug discovery campaigns. Although some of these approaches were already used in current antischistosomal lead discovery pipelines, the integration of these strategies in a solid workflow should allow the production of new treatments for schistosomiasis in the near future.

  8. Choosing experiments to accelerate collective discovery

    PubMed Central

    Rzhetsky, Andrey; Foster, Jacob G.; Foster, Ian T.

    2015-01-01

    A scientist’s choice of research problem affects his or her personal career trajectory. Scientists’ combined choices affect the direction and efficiency of scientific discovery as a whole. In this paper, we infer preferences that shape problem selection from patterns of published findings and then quantify their efficiency. We represent research problems as links between scientific entities in a knowledge network. We then build a generative model of discovery informed by qualitative research on scientific problem selection. We map salient features from this literature to key network properties: an entity’s importance corresponds to its degree centrality, and a problem’s difficulty corresponds to the network distance it spans. Drawing on millions of papers and patents published over 30 years, we use this model to infer the typical research strategy used to explore chemical relationships in biomedicine. This strategy generates conservative research choices focused on building up knowledge around important molecules. These choices become more conservative over time. The observed strategy is efficient for initial exploration of the network and supports scientific careers that require steady output, but is inefficient for science as a whole. Through supercomputer experiments on a sample of the network, we study thousands of alternatives and identify strategies much more efficient at exploring mature knowledge networks. We find that increased risk-taking and the publication of experimental failures would substantially improve the speed of discovery. We consider institutional shifts in grant making, evaluation, and publication that would help realize these efficiencies. PMID:26554009

  9. VISIONET: intuitive visualisation of overlapping transcription factor networks, with applications in cardiogenic gene discovery.

    PubMed

    Nim, Hieu T; Furtado, Milena B; Costa, Mauro W; Rosenthal, Nadia A; Kitano, Hiroaki; Boyd, Sarah E

    2015-05-01

    Existing de novo software platforms have largely overlooked a valuable resource, the expertise of the intended biologist users. Typical data representations such as long gene lists, or highly dense and overlapping transcription factor networks often hinder biologists from relating these results to their expertise. VISIONET, a streamlined visualisation tool built from experimental needs, enables biologists to transform large and dense overlapping transcription factor networks into sparse human-readable graphs via numerically filtering. The VISIONET interface allows users without a computing background to interactively explore and filter their data, and empowers them to apply their specialist knowledge on far more complex and substantial data sets than is currently possible. Applying VISIONET to the Tbx20-Gata4 transcription factor network led to the discovery and validation of Aldh1a2, an essential developmental gene associated with various important cardiac disorders, as a healthy adult cardiac fibroblast gene co-regulated by cardiogenic transcription factors Gata4 and Tbx20. We demonstrate with experimental validations the utility of VISIONET for expertise-driven gene discovery that opens new experimental directions that would not otherwise have been identified.

  10. Accelerating glioblastoma drug discovery: Convergence of patient-derived models, genome editing and phenotypic screening.

    PubMed

    O'Duibhir, Eoghan; Carragher, Neil O; Pollard, Steven M

    2017-04-01

    Patients diagnosed with glioblastoma (GBM) continue to face a bleak prognosis. It is critical that new effective therapeutic strategies are developed. GBM stem cells have molecular hallmarks of neural stem and progenitor cells and it is possible to propagate both non-transformed normal neural stem cells and GBM stem cells, in defined, feeder-free, adherent culture. These primary stem cell lines provide an experimental model that is ideally suited to cell-based drug discovery or genetic screens in order to identify tumour-specific vulnerabilities. For many solid tumours, including GBM, the genetic disruptions that drive tumour initiation and growth have now been catalogued. CRISPR/Cas-based genome editing technologies have recently emerged, transforming our ability to functionally annotate the human genome. Genome editing opens prospects for engineering precise genetic changes in normal and GBM-derived neural stem cells, which will provide more defined and reliable genetic models, with critical matched pairs of isogenic cell lines. Generation of more complex alleles such as knock in tags or fluorescent reporters is also now possible. These new cellular models can be deployed in cell-based phenotypic drug discovery (PDD). Here we discuss the convergence of these advanced technologies (iPS cells, neural stem cell culture, genome editing and high content phenotypic screening) and how they herald a new era in human cellular genetics that should have a major impact in accelerating glioblastoma drug discovery. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  11. Accelerated oral nanomedicine discovery from miniaturized screening to clinical production exemplified by paediatric HIV nanotherapies

    PubMed Central

    Giardiello, Marco; Liptrott, Neill J.; McDonald, Tom O.; Moss, Darren; Siccardi, Marco; Martin, Phil; Smith, Darren; Gurjar, Rohan; Rannard, Steve P.; Owen, Andrew

    2016-01-01

    Considerable scope exists to vary the physical and chemical properties of nanoparticles, with subsequent impact on biological interactions; however, no accelerated process to access large nanoparticle material space is currently available, hampering the development of new nanomedicines. In particular, no clinically available nanotherapies exist for HIV populations and conventional paediatric HIV medicines are poorly available; one current paediatric formulation utilizes high ethanol concentrations to solubilize lopinavir, a poorly soluble antiretroviral. Here we apply accelerated nanomedicine discovery to generate a potential aqueous paediatric HIV nanotherapy, with clinical translation and regulatory approval for human evaluation. Our rapid small-scale screening approach yields large libraries of solid drug nanoparticles (160 individual components) targeting oral dose. Screening uses 1 mg of drug compound per library member and iterative pharmacological and chemical evaluation establishes potential candidates for progression through to clinical manufacture. The wide applicability of our strategy has implications for multiple therapy development programmes. PMID:27767027

  12. Big Data and Comparative Effectiveness Research in Radiation Oncology: Synergy and Accelerated Discovery.

    PubMed

    Trifiletti, Daniel M; Showalter, Timothy N

    2015-01-01

    Several advances in large data set collection and processing have the potential to provide a wave of new insights and improvements in the use of radiation therapy for cancer treatment. The era of electronic health records, genomics, and improving information technology resources creates the opportunity to leverage these developments to create a learning healthcare system that can rapidly deliver informative clinical evidence. By merging concepts from comparative effectiveness research with the tools and analytic approaches of "big data," it is hoped that this union will accelerate discovery, improve evidence for decision making, and increase the availability of highly relevant, personalized information. This combination offers the potential to provide data and analysis that can be leveraged for ultra-personalized medicine and high-quality, cutting-edge radiation therapy.

  13. Pine Gene Discovery Project - Final Report - 08/31/1997 - 02/28/2001

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Whetten, R. W.; Sederoff, R. R.; Kinlaw, C.

    2001-04-30

    Integration of pines into the large scope of plant biology research depends on study of pines in parallel with study of annual plants, and on availability of research materials from pine to plant biologists interested in comparing pine with annual plant systems. The objectives of the Pine Gene Discovery Project were to obtain 10,000 partial DNA sequences of genes expressed in loblolly pine, to determine which of those pine genes were similar to known genes from other organisms, and to make the DNA sequences and isolated pine genes available to plant researchers to stimulate integration of pines into the widermore » scope of plant biology research. Those objectives have been completed, and the results are available to the public. Requests for pine genes have been received from a number of laboratories that would otherwise not have included pine in their research, indicating that progress is being made toward the goal of integrating pine research into the larger molecular biology research community.« less

  14. An Endogenous Accelerator for Viral Gene Expression Confers a Fitness Advantage

    PubMed Central

    Teng, Melissa W.; Bolovan-Fritts, Cynthia; Dar, Roy D.; Womack, Andrew; Simpson, Michael L.; Shenk, Thomas; Weinberger, Leor S.

    2012-01-01

    Many signaling circuits face a fundamental tradeoff between accelerating their response speed while maintaining final levels below a cytotoxic threshold. Here, we describe a transcriptional circuitry that dynamically converts signaling inputs into faster rates without amplifying final equilibrium levels. Using time-lapse microscopy, we find that transcriptional activators accelerate human cytomegalovirus (CMV) gene expression in single cells without amplifying steady-state expression levels, and this acceleration generates a significant replication advantage. We map the accelerator to a highly self-cooperative transcriptional negative-feedback loop (Hill coefficient ~ 7) generated by homo-multimerization of the virus’s essential transactivator protein IE2 at nuclear PML bodies. Eliminating the IE2-accelerator circuit reduces transcriptional strength through mislocalization of incoming viral genomes away from PML bodies and carries a heavy fitness cost. In general, accelerators may provide a mechanism for signal-transduction circuits to respond quickly to external signals without increasing steady-state levels of potentially cytotoxic molecules. PMID:23260143

  15. Genome-wide ENU mutagenesis for the discovery of novel male fertility regulators.

    PubMed

    Jamsai, Duangporn; O'Bryan, Moira K

    2010-06-01

    The completion of genome sequencing projects has provided an extensive knowledge of the contents of the genomes of human, mouse, and many other organisms. Despite this, the function of most of the estimated 25,000 human genes remains largely unknown. Attention has now turned to elucidating gene function and identifying biological pathways that contribute to human diseases, including male infertility. Our understanding of the genetic regulation of male fertility has been accelerated through the use of genetically modified mouse models including knockout, knock-in, gene-trapped, and transgenic mice. Such reverse genetic approaches however, require some fore-knowledge of a gene's function and, as such, bias against the discovery of completely novel genes and biological pathways. To facilitate high throughput gene discovery, genome-wide mouse mutagenesis via the use of a potent chemical mutagen, N-ethyl-N-nitrosourea (ENU), has been developed over the past decade. This forward genetic, or phenotype-driven, approach relies upon observing a phenotype first, then subsequently defining the underlining genetic defect. Mutations are randomly introduced into the mouse genome via ENU exposure. Through a controlled breeding scheme, mutations causing a phenotype of interest (e.g., male infertility) are then identified by linkage analysis and candidate gene sequencing. This approach allows for the possibility of revealing comprehensive phenotype-genotype relationships for a range of genes and pathways i.e. in addition to null alleles, mice containing partial loss of function or gain-of-function mutations, can be recovered. Such point mutations are likely to be more reflective of those that occur within the human population. Many research groups have successfully used this approach to generate infertile mouse lines and some novel male fertility genes have been revealed. In this review, we focus on the utility of ENU mutagenesis for the discovery of novel male fertility regulators.

  16. The Last Word: An Interview with Gene Chasin, CEO of Accelerated Schools Plus

    ERIC Educational Resources Information Center

    Siegle, Del

    2006-01-01

    This article presents an interview with Gene Chasin, CEO of Accelerated Schools Plus. Chasin discusses changing schools and improving student achievement. Accelerated Schools is a national endeavor that is designed to transform whole school communities. It views the community as being much broader. It includes students, teachers, parents, other…

  17. PharMillenium '99--the second world pharmaceutical congress and exhibition. Accelerating the pipeline: from drug discovery to market. 1-3 February 1999, Washington DC, USA.

    PubMed

    Fernandes, M

    1999-04-01

    This highly interactive meeting effectively covered critical issues on every transaction from drug discovery through to development and commercialization. The program included company-specific descriptions of new discovery products, together with seminars by clinical research and site management organizations on the acceleration of development, pharmaco-economics, branding of products, direct-to-consumer advertising, global marketing, management, information technology and business strategy. There were approximately 50 sessions covered by 70 speakers.

  18. Big Data and Comparative Effectiveness Research in Radiation Oncology: Synergy and Accelerated Discovery

    PubMed Central

    Trifiletti, Daniel M.; Showalter, Timothy N.

    2015-01-01

    Several advances in large data set collection and processing have the potential to provide a wave of new insights and improvements in the use of radiation therapy for cancer treatment. The era of electronic health records, genomics, and improving information technology resources creates the opportunity to leverage these developments to create a learning healthcare system that can rapidly deliver informative clinical evidence. By merging concepts from comparative effectiveness research with the tools and analytic approaches of “big data,” it is hoped that this union will accelerate discovery, improve evidence for decision making, and increase the availability of highly relevant, personalized information. This combination offers the potential to provide data and analysis that can be leveraged for ultra-personalized medicine and high-quality, cutting-edge radiation therapy. PMID:26697409

  19. Comprehensive Clinical Phenotyping & Genetic Mapping for the Discovery of Autism Susceptibility Genes

    DTIC Science & Technology

    2012-12-05

    Bisgaier J, Levinson D, Cutts DB, & Rhodes KV., (2011) Access to autism evaluation appointments with developmental-behavioral and neurodevelopmental ...W403 Columbus, OH 43205 Final Report Comprehensive Clinical Phenotyping & Genetic Mapping for the Discovery of Autism Susceptibility Genes...QFOXGHDUHDFRGH 1.0 Summary In 2006, the Central Ohio Registry for Autism (CORA) was initiated as a collaboration between Wright-Patterson Air

  20. Whole-genome resequencing: changing the paradigms of SNP detection, molecular mapping and gene discovery

    USDA-ARS?s Scientific Manuscript database

    The next generation sequencing (NGS) technologies have opened a wealth of opportunities for plant breeding and genomics research, and changed the paradigms of marker detection, genotyping, and gene discovery. Abundant genomic resources have been generated using a whole genome resequencing (WGR) str...

  1. Defeating copper tolerance: an example of how “omics” research can accelerate discovery of new wood protection compounds

    Treesearch

    Juliet D. Tang; Tina Ciaramitaro; Darrel D. Nicholas; Maria Tomaso-Peterson; Susan V. Diehl

    2017-01-01

    Imagine if you could measure all the genes being expressed at any one time in an organism and you knew what all the genes did in a cell. The power of this knowledge would allow you to determine how organisms regulate gene activity to survive. This is the essence of how “omics” science accelerates biological understanding. From a wood protections standpoint,...

  2. Toward Routine Automatic Pathway Discovery from On-line Scientific Text Abstracts.

    PubMed

    Ng; Wong

    1999-01-01

    We are entering a new era of research where the latest scientific discoveries are often first reported online and are readily accessible by scientists worldwide. This rapid electronic dissemination of research breakthroughs has greatly accelerated the current pace in genomics and proteomics research. The race to the discovery of a gene or a drug has now become increasingly dependent on how quickly a scientist can scan through voluminous amount of information available online to construct the relevant picture (such as protein-protein interaction pathways) as it takes shape amongst the rapidly expanding pool of globally accessible biological data (e.g. GENBANK) and scientific literature (e.g. MEDLINE). We describe a prototype system for automatic pathway discovery from on-line text abstracts, combining technologies that (1) retrieve research abstracts from online sources, (2) extract relevant information from the free texts, and (3) present the extracted information graphically and intuitively. Our work demonstrates that this framework allows us to routinely scan online scientific literature for automatic discovery of knowledge, giving modern scientists the necessary competitive edge in managing the information explosion in this electronic age.

  3. Adeno-associated virus at 50: a golden anniversary of discovery, research, and gene therapy success--a personal perspective.

    PubMed

    Hastie, Eric; Samulski, R Jude

    2015-05-01

    Fifty years after the discovery of adeno-associated virus (AAV) and more than 30 years after the first gene transfer experiment was conducted, dozens of gene therapy clinical trials are in progress, one vector is approved for use in Europe, and breakthroughs in virus modification and disease modeling are paving the way for a revolution in the treatment of rare diseases, cancer, as well as HIV. This review will provide a historical perspective on the progression of AAV for gene therapy from discovery to the clinic, focusing on contributions from the Samulski lab regarding basic science and cloning of AAV, optimized large-scale production of vectors, preclinical large animal studies and safety data, vector modifications for improved efficacy, and successful clinical applications.

  4. Pulse - Accelerator Science in Medicine

    Science.gov Websites

    discoveries in particle accelerator science may lead to unexpected applications for medical diagnosis, healing perhaps to new tools for medical science. National laboratories build particle accelerators for physicists

  5. Discovery of rare protein-coding genes in model methylotroph Methylobacterium extorquens AM1.

    PubMed

    Kumar, Dhirendra; Mondal, Anupam Kumar; Yadav, Amit Kumar; Dash, Debasis

    2014-12-01

    Proteogenomics involves the use of MS to refine annotation of protein-coding genes and discover genes in a genome. We carried out comprehensive proteogenomic analysis of Methylobacterium extorquens AM1 (ME-AM1) from publicly available proteomics data with a motive to improve annotation for methylotrophs; organisms capable of surviving in reduced carbon compounds such as methanol. Besides identifying 2482(50%) proteins, 29 new genes were discovered and 66 annotated gene models were revised in ME-AM1 genome. One such novel gene is identified with 75 peptides, lacks homolog in other methylobacteria but has glycosyl transferase and lipopolysaccharide biosynthesis protein domains, indicating its potential role in outer membrane synthesis. Many novel genes are present only in ME-AM1 among methylobacteria. Distant homologs of these genes in unrelated taxonomic classes and low GC-content of few genes suggest lateral gene transfer as a potential mode of their origin. Annotations of methylotrophy related genes were also improved by the discovery of a short gene in methylotrophy gene island and redefining a gene important for pyrroquinoline quinone synthesis, essential for methylotrophy. The combined use of proteogenomics and rigorous bioinformatics analysis greatly enhanced the annotation of protein-coding genes in model methylotroph ME-AM1 genome. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Accelerating early anti-tuberculosis drug discovery by creating mycobacterial indicator strains that predict mode of action.

    PubMed

    Boot, Maikel; Commandeur, Susanna; Subudhi, Amit K; Bahira, Meriem; Smith, Trever C; Abdallah, Abdallah M; van Gemert, Mae; Lelièvre, Joël; Ballell, Lluís; Aldridge, Bree B; Pain, Arnab; Speer, Alexander; Bitter, Wilbert

    2018-04-16

    Due to the rise of drug resistant forms of tuberculosis there is an urgent need for novel antibiotics to effectively combat these cases and shorten treatment regimens. Recently, drug screens using whole cell analyses have been shown to be successful. However, current high-throughput screens focus mostly on stricto sensu life-death screening that give little qualitative information. In doing so, promising compound scaffolds or non-optimized compounds that fail to reach inhibitory concentrations are missed. To accelerate early TB drug discovery, we performed RNA sequencing on Mycobacterium tuberculosis and Mycobacterium marinum to map the stress responses that follow upon exposure to sub-inhibitory concentrations of antibiotics with known targets: ciprofloxacin, ethambutol, isoniazid, streptomycin and rifampicin. The resulting dataset comprises the first overview of transcriptional stress responses of mycobacteria to different antibiotics. We show that antibiotics can be distinguished based on their specific transcriptional stress fingerprint. Notably, this fingerprint was more distinctive in M. marinum. We decided to use this to our advantage and continue with this model organism. A selection of diverse antibiotic stress genes was used to construct stress reporters. In total, three functional reporters were constructed to respond to DNA damage, cell wall damage and ribosomal inhibition. Subsequently, these reporter strains were used to screen a small anti-TB compound library to predict the mode of action. In doing so, we could identify the putative mode of action for three novel compounds, which confirms our approach. Copyright © 2018 American Society for Microbiology.

  7. Automated Discovery of Functional Generality of Human Gene Expression Programs

    PubMed Central

    Gerber, Georg K; Dowell, Robin D; Jaakkola, Tommi S; Gifford, David K

    2007-01-01

    An important research problem in computational biology is the identification of expression programs, sets of co-expressed genes orchestrating normal or pathological processes, and the characterization of the functional breadth of these programs. The use of human expression data compendia for discovery of such programs presents several challenges including cellular inhomogeneity within samples, genetic and environmental variation across samples, uncertainty in the numbers of programs and sample populations, and temporal behavior. We developed GeneProgram, a new unsupervised computational framework based on Hierarchical Dirichlet Processes that addresses each of the above challenges. GeneProgram uses expression data to simultaneously organize tissues into groups and genes into overlapping programs with consistent temporal behavior, to produce maps of expression programs, which are sorted by generality scores that exploit the automatically learned groupings. Using synthetic and real gene expression data, we showed that GeneProgram outperformed several popular expression analysis methods. We applied GeneProgram to a compendium of 62 short time-series gene expression datasets exploring the responses of human cells to infectious agents and immune-modulating molecules. GeneProgram produced a map of 104 expression programs, a substantial number of which were significantly enriched for genes involved in key signaling pathways and/or bound by NF-κB transcription factors in genome-wide experiments. Further, GeneProgram discovered expression programs that appear to implicate surprising signaling pathways or receptor types in the response to infection, including Wnt signaling and neurotransmitter receptors. We believe the discovered map of expression programs involved in the response to infection will be useful for guiding future biological experiments; genes from programs with low generality scores might serve as new drug targets that exhibit minimal “cross-talk,” and

  8. Discovery of new candidate genes related to brain development using protein interaction information.

    PubMed

    Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Tao; Cai, Yu-Dong

    2015-01-01

    Human brain development is a dramatic process composed of a series of complex and fine-tuned spatiotemporal gene expressions. A good comprehension of this process can assist us in developing the potential of our brain. However, we have only limited knowledge about the genes and gene functions that are involved in this biological process. Therefore, a substantial demand remains to discover new brain development-related genes and identify their biological functions. In this study, we aimed to discover new brain-development related genes by building a computational method. We referred to a series of computational methods used to discover new disease-related genes and developed a similar method. In this method, the shortest path algorithm was executed on a weighted graph that was constructed using protein-protein interactions. New candidate genes fell on at least one of the shortest paths connecting two known genes that are related to brain development. A randomization test was then adopted to filter positive discoveries. Of the final identified genes, several have been reported to be associated with brain development, indicating the effectiveness of the method, whereas several of the others may have potential roles in brain development.

  9. Sex-Specific Associations between Particulate Matter Exposure and Gene Expression in Independent Discovery and Validation Cohorts of Middle-Aged Men and Women.

    PubMed

    Vrijens, Karen; Winckelmans, Ellen; Tsamou, Maria; Baeyens, Willy; De Boever, Patrick; Jennen, Danyel; de Kok, Theo M; Den Hond, Elly; Lefebvre, Wouter; Plusquin, Michelle; Reynders, Hans; Schoeters, Greet; Van Larebeke, Nicolas; Vanpoucke, Charlotte; Kleinjans, Jos; Nawrot, Tim S

    2017-04-01

    Particulate matter (PM) exposure leads to premature death, mainly due to respiratory and cardiovascular diseases. Identification of transcriptomic biomarkers of air pollution exposure and effect in a healthy adult population. Microarray analyses were performed in 98 healthy volunteers (48 men, 50 women). The expression of eight sex-specific candidate biomarker genes (significantly associated with PM 10 in the discovery cohort and with a reported link to air pollution-related disease) was measured with qPCR in an independent validation cohort (75 men, 94 women). Pathway analysis was performed using Gene Set Enrichment Analysis. Average daily PM 2.5 and PM 10 exposures over 2-years were estimated for each participant's residential address using spatiotemporal interpolation in combination with a dispersion model. Average long-term PM 10 was 25.9 (± 5.4) and 23.7 (± 2.3) μg/m 3 in the discovery and validation cohorts, respectively. In discovery analysis, associations between PM 10 and the expression of individual genes differed by sex. In the validation cohort, long-term PM 10 was associated with the expression of DNAJB5 and EAPP in men and ARHGAP4 ( p = 0.053) in women. AKAP6 and LIMK1 were significantly associated with PM 10 in women, although associations differed in direction between the discovery and validation cohorts. Expression of the eight candidate genes in the discovery cohort differentiated between validation cohort participants with high versus low PM 10 exposure (area under the receiver operating curve = 0.92; 95% CI: 0.85, 1.00; p = 0.0002 in men, 0.86; 95% CI: 0.76, 0.96; p = 0.004 in women). Expression of the sex-specific candidate genes identified in the discovery population predicted PM 10 exposure in an independent cohort of adults from the same area. Confirmation in other populations may further support this as a new approach for exposure assessment, and may contribute to the discovery of molecular mechanisms for PM-induced health effects.

  10. Underbody Blast Models of TBI Caused by Hyper-Acceleration and Secondary Head Impact

    DTIC Science & Technology

    2016-02-01

    discovery rate (FDR), which controls for the expected proportion of false rejected hypotheses. ANOVA was performed to evaluate the significance in gene...acceleration/deceleration11,27 and blast4,13 have also been designed for the purpose of evaluating coup-contrecoup and blast wave energies potentially... evaluation of different angles/ locations of the projectile impact to the surface of the rat head. Finally, pilot studies were conducted to provide further

  11. Gene discovery by chemical mutagenesis and whole-genome sequencing in Dictyostelium.

    PubMed

    Li, Cheng-Lin Frank; Santhanam, Balaji; Webb, Amanda Nicole; Zupan, Blaž; Shaulsky, Gad

    2016-09-01

    Whole-genome sequencing is a useful approach for identification of chemical-induced lesions, but previous applications involved tedious genetic mapping to pinpoint the causative mutations. We propose that saturation mutagenesis under low mutagenic loads, followed by whole-genome sequencing, should allow direct implication of genes by identifying multiple independent alleles of each relevant gene. We tested the hypothesis by performing three genetic screens with chemical mutagenesis in the social soil amoeba Dictyostelium discoideum Through genome sequencing, we successfully identified mutant genes with multiple alleles in near-saturation screens, including resistance to intense illumination and strong suppressors of defects in an allorecognition pathway. We tested the causality of the mutations by comparison to published data and by direct complementation tests, finding both dominant and recessive causative mutations. Therefore, our strategy provides a cost- and time-efficient approach to gene discovery by integrating chemical mutagenesis and whole-genome sequencing. The method should be applicable to many microbial systems, and it is expected to revolutionize the field of functional genomics in Dictyostelium by greatly expanding the mutation spectrum relative to other common mutagenesis methods. © 2016 Li et al.; Published by Cold Spring Harbor Laboratory Press.

  12. SSHscreen and SSHdb, generic software for microarray based gene discovery: application to the stress response in cowpea

    PubMed Central

    2010-01-01

    Background Suppression subtractive hybridization is a popular technique for gene discovery from non-model organisms without an annotated genome sequence, such as cowpea (Vigna unguiculata (L.) Walp). We aimed to use this method to enrich for genes expressed during drought stress in a drought tolerant cowpea line. However, current methods were inefficient in screening libraries and management of the sequence data, and thus there was a need to develop software tools to facilitate the process. Results Forward and reverse cDNA libraries enriched for cowpea drought response genes were screened on microarrays, and the R software package SSHscreen 2.0.1 was developed (i) to normalize the data effectively using spike-in control spot normalization, and (ii) to select clones for sequencing based on the calculation of enrichment ratios with associated statistics. Enrichment ratio 3 values for each clone showed that 62% of the forward library and 34% of the reverse library clones were significantly differentially expressed by drought stress (adjusted p value < 0.05). Enrichment ratio 2 calculations showed that > 88% of the clones in both libraries were derived from rare transcripts in the original tester samples, thus supporting the notion that suppression subtractive hybridization enriches for rare transcripts. A set of 118 clones were chosen for sequencing, and drought-induced cowpea genes were identified, the most interesting encoding a late embryogenesis abundant Lea5 protein, a glutathione S-transferase, a thaumatin, a universal stress protein, and a wound induced protein. A lipid transfer protein and several components of photosynthesis were down-regulated by the drought stress. Reverse transcriptase quantitative PCR confirmed the enrichment ratio values for the selected cowpea genes. SSHdb, a web-accessible database, was developed to manage the clone sequences and combine the SSHscreen data with sequence annotations derived from BLAST and Blast2GO. The self

  13. Evaluation of tools for highly variable gene discovery from single-cell RNA-seq data.

    PubMed

    Yip, Shun H; Sham, Pak Chung; Wang, Junwen

    2018-02-21

    Traditional RNA sequencing (RNA-seq) allows the detection of gene expression variations between two or more cell populations through differentially expressed gene (DEG) analysis. However, genes that contribute to cell-to-cell differences are not discoverable with RNA-seq because RNA-seq samples are obtained from a mixture of cells. Single-cell RNA-seq (scRNA-seq) allows the detection of gene expression in each cell. With scRNA-seq, highly variable gene (HVG) discovery allows the detection of genes that contribute strongly to cell-to-cell variation within a homogeneous cell population, such as a population of embryonic stem cells. This analysis is implemented in many software packages. In this study, we compare seven HVG methods from six software packages, including BASiCS, Brennecke, scLVM, scran, scVEGs and Seurat. Our results demonstrate that reproducibility in HVG analysis requires a larger sample size than DEG analysis. Discrepancies between methods and potential issues in these tools are discussed and recommendations are made.

  14. The Matchmaker Exchange: A Platform for Rare Disease Gene Discovery

    PubMed Central

    Philippakis, Anthony A.; Azzariti, Danielle R.; Beltran, Sergi; Brookes, Anthony J.; Brownstein, Catherine A.; Brudno, Michael; Brunner, Han G.; Buske, Orion J.; Carey, Knox; Doll, Cassie; Dumitriu, Sergiu; Dyke, Stephanie O.M.; den Dunnen, Johan T.; Firth, Helen V.; Gibbs, Richard A.; Girdea, Marta; Gonzalez, Michael; Haendel, Melissa A.; Hamosh, Ada; Holm, Ingrid A.; Huang, Lijia; Hurles, Matthew E.; Hutton, Ben; Krier, Joel B.; Misyura, Andriy; Mungall, Christopher J.; Paschall, Justin; Paten, Benedict; Robinson, Peter N.; Schiettecatte, François; Sobreira, Nara L.; Swaminathan, Ganesh J.; Taschner, Peter E.; Terry, Sharon F.; Washington, Nicole L.; Züchner, Stephan; Boycott, Kym M.; Rehm, Heidi L.

    2015-01-01

    There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for “the needle in a haystack” to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can “match” these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow. PMID:26295439

  15. High Throughput Screening for Anti–Trypanosoma cruzi Drug Discovery

    PubMed Central

    Alonso-Padilla, Julio; Rodríguez, Ana

    2014-01-01

    The discovery of new therapeutic options against Trypanosoma cruzi, the causative agent of Chagas disease, stands as a fundamental need. Currently, there are only two drugs available to treat this neglected disease, which represents a major public health problem in Latin America. Both available therapies, benznidazole and nifurtimox, have significant toxic side effects and their efficacy against the life-threatening symptomatic chronic stage of the disease is variable. Thus, there is an urgent need for new, improved anti–T. cruzi drugs. With the objective to reliably accelerate the drug discovery process against Chagas disease, several advances have been made in the last few years. Availability of engineered reporter gene expressing parasites triggered the development of phenotypic in vitro assays suitable for high throughput screening (HTS) as well as the establishment of new in vivo protocols that allow faster experimental outcomes. Recently, automated high content microscopy approaches have also been used to identify new parasitic inhibitors. These in vitro and in vivo early drug discovery approaches, which hopefully will contribute to bring better anti–T. cruzi drug entities in the near future, are reviewed here. PMID:25474364

  16. High throughput screening for anti-Trypanosoma cruzi drug discovery.

    PubMed

    Alonso-Padilla, Julio; Rodríguez, Ana

    2014-12-01

    The discovery of new therapeutic options against Trypanosoma cruzi, the causative agent of Chagas disease, stands as a fundamental need. Currently, there are only two drugs available to treat this neglected disease, which represents a major public health problem in Latin America. Both available therapies, benznidazole and nifurtimox, have significant toxic side effects and their efficacy against the life-threatening symptomatic chronic stage of the disease is variable. Thus, there is an urgent need for new, improved anti-T. cruzi drugs. With the objective to reliably accelerate the drug discovery process against Chagas disease, several advances have been made in the last few years. Availability of engineered reporter gene expressing parasites triggered the development of phenotypic in vitro assays suitable for high throughput screening (HTS) as well as the establishment of new in vivo protocols that allow faster experimental outcomes. Recently, automated high content microscopy approaches have also been used to identify new parasitic inhibitors. These in vitro and in vivo early drug discovery approaches, which hopefully will contribute to bring better anti-T. cruzi drug entities in the near future, are reviewed here.

  17. NASA's GeneLab Phase II: Federated Search and Data Discovery

    NASA Technical Reports Server (NTRS)

    Berrios, Daniel C.; Costes, Sylvain V.; Tran, Peter B.

    2017-01-01

    GeneLab is currently being developed by NASA to accelerate 'open science' biomedical research in support of the human exploration of space and the improvement of life on earth. Phase I of the four-phase GeneLab Data Systems (GLDS) project emphasized capabilities for submission, curation, search, and retrieval of genomics, transcriptomics and proteomics ('omics') data from biomedical research of space environments. The focus of development of the GLDS for Phase II has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.

  18. NASAs GeneLab Phase II: Federated Search and Data Discovery

    NASA Technical Reports Server (NTRS)

    Berrios, Daniel C.; Costes, Sylvain; Tran, Peter

    2017-01-01

    GeneLab is currently being developed by NASA to accelerate open science biomedical research in support of the human exploration of space and the improvement of life on earth. Phase I of the four-phase GeneLab Data Systems (GLDS) project emphasized capabilities for submission, curation, search, and retrieval of genomics, transcriptomics and proteomics (omics) data from biomedical research of space environments. The focus of development of the GLDS for Phase II has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.

  19. Sex-Specific Associations between Particulate Matter Exposure and Gene Expression in Independent Discovery and Validation Cohorts of Middle-Aged Men and Women

    PubMed Central

    Vrijens, Karen; Winckelmans, Ellen; Tsamou, Maria; Baeyens, Willy; De Boever, Patrick; Jennen, Danyel; de Kok, Theo M.; Den Hond, Elly; Lefebvre, Wouter; Plusquin, Michelle; Reynders, Hans; Schoeters, Greet; Van Larebeke, Nicolas; Vanpoucke, Charlotte; Kleinjans, Jos; Nawrot, Tim S.

    2016-01-01

    Background: Particulate matter (PM) exposure leads to premature death, mainly due to respiratory and cardiovascular diseases. Objectives: Identification of transcriptomic biomarkers of air pollution exposure and effect in a healthy adult population. Methods: Microarray analyses were performed in 98 healthy volunteers (48 men, 50 women). The expression of eight sex-specific candidate biomarker genes (significantly associated with PM10 in the discovery cohort and with a reported link to air pollution-related disease) was measured with qPCR in an independent validation cohort (75 men, 94 women). Pathway analysis was performed using Gene Set Enrichment Analysis. Average daily PM2.5 and PM10 exposures over 2-years were estimated for each participant’s residential address using spatiotemporal interpolation in combination with a dispersion model. Results: Average long-term PM10 was 25.9 (± 5.4) and 23.7 (± 2.3) μg/m3 in the discovery and validation cohorts, respectively. In discovery analysis, associations between PM10 and the expression of individual genes differed by sex. In the validation cohort, long-term PM10 was associated with the expression of DNAJB5 and EAPP in men and ARHGAP4 (p = 0.053) in women. AKAP6 and LIMK1 were significantly associated with PM10 in women, although associations differed in direction between the discovery and validation cohorts. Expression of the eight candidate genes in the discovery cohort differentiated between validation cohort participants with high versus low PM10 exposure (area under the receiver operating curve = 0.92; 95% CI: 0.85, 1.00; p = 0.0002 in men, 0.86; 95% CI: 0.76, 0.96; p = 0.004 in women). Conclusions: Expression of the sex-specific candidate genes identified in the discovery population predicted PM10 exposure in an independent cohort of adults from the same area. Confirmation in other populations may further support this as a new approach for exposure assessment, and may contribute to the discovery of molecular

  20. Peroxidase gene discovery from the horseradish transcriptome.

    PubMed

    Näätsaari, Laura; Krainer, Florian W; Schubert, Michael; Glieder, Anton; Thallinger, Gerhard G

    2014-03-24

    Horseradish peroxidases (HRPs) from Armoracia rusticana have long been utilized as reporters in various diagnostic assays and histochemical stainings. Regardless of their increasing importance in the field of life sciences and suggested uses in medical applications, chemical synthesis and other industrial applications, the HRP isoenzymes, their substrate specificities and enzymatic properties are poorly characterized. Due to lacking sequence information of natural isoenzymes and the low levels of HRP expression in heterologous hosts, commercially available HRP is still extracted as a mixture of isoenzymes from the roots of A. rusticana. In this study, a normalized, size-selected A. rusticana transcriptome library was sequenced using 454 Titanium technology. The resulting reads were assembled into 14871 isotigs with an average length of 1133 bp. Sequence databases, ORF finding and ORF characterization were utilized to identify peroxidase genes from the 14871 isotigs generated by de novo assembly. The sequences were manually reviewed and verified with Sanger sequencing of PCR amplified genomic fragments, resulting in the discovery of 28 secretory peroxidases, 23 of them previously unknown. A total of 22 isoenzymes including allelic variants were successfully expressed in Pichia pastoris and showed peroxidase activity with at least one of the substrates tested, thus enabling their development into commercial pure isoenzymes. This study demonstrates that transcriptome sequencing combined with sequence motif search is a powerful concept for the discovery and quick supply of new enzymes and isoenzymes from any plant or other eukaryotic organisms. Identification and manual verification of the sequences of 28 HRP isoenzymes do not only contribute a set of peroxidases for industrial, biological and biomedical applications, but also provide valuable information on the reliability of the approach in identifying and characterizing a large group of isoenzymes.

  1. Peroxidase gene discovery from the horseradish transcriptome

    PubMed Central

    2014-01-01

    Background Horseradish peroxidases (HRPs) from Armoracia rusticana have long been utilized as reporters in various diagnostic assays and histochemical stainings. Regardless of their increasing importance in the field of life sciences and suggested uses in medical applications, chemical synthesis and other industrial applications, the HRP isoenzymes, their substrate specificities and enzymatic properties are poorly characterized. Due to lacking sequence information of natural isoenzymes and the low levels of HRP expression in heterologous hosts, commercially available HRP is still extracted as a mixture of isoenzymes from the roots of A. rusticana. Results In this study, a normalized, size-selected A. rusticana transcriptome library was sequenced using 454 Titanium technology. The resulting reads were assembled into 14871 isotigs with an average length of 1133 bp. Sequence databases, ORF finding and ORF characterization were utilized to identify peroxidase genes from the 14871 isotigs generated by de novo assembly. The sequences were manually reviewed and verified with Sanger sequencing of PCR amplified genomic fragments, resulting in the discovery of 28 secretory peroxidases, 23 of them previously unknown. A total of 22 isoenzymes including allelic variants were successfully expressed in Pichia pastoris and showed peroxidase activity with at least one of the substrates tested, thus enabling their development into commercial pure isoenzymes. Conclusions This study demonstrates that transcriptome sequencing combined with sequence motif search is a powerful concept for the discovery and quick supply of new enzymes and isoenzymes from any plant or other eukaryotic organisms. Identification and manual verification of the sequences of 28 HRP isoenzymes do not only contribute a set of peroxidases for industrial, biological and biomedical applications, but also provide valuable information on the reliability of the approach in identifying and characterizing a large group

  2. Cloud computing approaches to accelerate drug discovery value chain.

    PubMed

    Garg, Vibhav; Arora, Suchir; Gupta, Chitra

    2011-12-01

    Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.

  3. Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Duncan, Katherine R.; Crüsemann, Max; Lechner, Anna

    Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. In this paper, we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains, including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated themore » identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. Finally, these efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches.« less

  4. Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species

    DOE PAGES

    Duncan, Katherine R.; Crüsemann, Max; Lechner, Anna; ...

    2015-04-09

    Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. In this paper, we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains, including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated themore » identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. Finally, these efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches.« less

  5. Molecular Networking and Pattern-Based Genome Mining Improves discovery of biosynthetic gene clusters and their products from Salinispora species

    PubMed Central

    Duncan, Katherine R.; Crüsemann, Max; Lechner, Anna; Sarkar, Anindita; Li, Jie; Ziemert, Nadine; Wang, Mingxun; Bandeira, Nuno; Moore, Bradley S.; Dorrestein, Pieter C.; Jensen, Paul R.

    2015-01-01

    Summary Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. Here we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated the identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. These efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches. PMID:25865308

  6. New strategies in drug discovery.

    PubMed

    Ohlstein, Eliot H; Johnson, Anthony G; Elliott, John D; Romanic, Anne M

    2006-01-01

    Gene identification followed by determination of the expression of genes in a given disease and understanding of the function of the gene products is central to the drug discovery process. The ability to associate a specific gene with a disease can be attributed primarily to the extraordinary progress that has been made in the areas of gene sequencing and information technologies. Selection and validation of novel molecular targets have become of great importance in light of the abundance of new potential therapeutic drug targets that have emerged from human gene sequencing. In response to this revolution within the pharmaceutical industry, the development of high-throughput methods in both biology and chemistry has been necessitated. Further, the successful translation of basic scientific discoveries into clinical experimental medicine and novel therapeutics is an increasing challenge. As such, a new paradigm for drug discovery has emerged. This process involves the integration of clinical, genetic, genomic, and molecular phenotype data partnered with cheminformatics. Central to this process, the data generated are managed, collated, and interpreted with the use of informatics. This review addresses the use of new technologies that have arisen to deal with this new paradigm.

  7. Cogena, a novel tool for co-expressed gene-set enrichment analysis, applied to drug repositioning and drug mode of action discovery.

    PubMed

    Jia, Zhilong; Liu, Ying; Guan, Naiyang; Bo, Xiaochen; Luo, Zhigang; Barnes, Michael R

    2016-05-27

    Drug repositioning, finding new indications for existing drugs, has gained much recent attention as a potentially efficient and economical strategy for accelerating new therapies into the clinic. Although improvement in the sensitivity of computational drug repositioning methods has identified numerous credible repositioning opportunities, few have been progressed. Arguably the "black box" nature of drug action in a new indication is one of the main blocks to progression, highlighting the need for methods that inform on the broader target mechanism in the disease context. We demonstrate that the analysis of co-expressed genes may be a critical first step towards illumination of both disease pathology and mode of drug action. We achieve this using a novel framework, co-expressed gene-set enrichment analysis (cogena) for co-expression analysis of gene expression signatures and gene set enrichment analysis of co-expressed genes. The cogena framework enables simultaneous, pathway driven, disease and drug repositioning analysis. Cogena can be used to illuminate coordinated changes within disease transcriptomes and identify drugs acting mechanistically within this framework. We illustrate this using a psoriatic skin transcriptome, as an exemplar, and recover two widely used Psoriasis drugs (Methotrexate and Ciclosporin) with distinct modes of action. Cogena out-performs the results of Connectivity Map and NFFinder webservers in similar disease transcriptome analyses. Furthermore, we investigated the literature support for the other top-ranked compounds to treat psoriasis and showed how the outputs of cogena analysis can contribute new insight to support the progression of drugs into the clinic. We have made cogena freely available within Bioconductor or https://github.com/zhilongjia/cogena . In conclusion, by targeting co-expressed genes within disease transcriptomes, cogena offers novel biological insight, which can be effectively harnessed for drug discovery and

  8. The promise of disease gene discovery in South Asia

    PubMed Central

    Nakatsuka, Nathan; Moorjani, Priya; Rai, Niraj; Sarkar, Biswanath; Tandon, Arti; Patterson, Nick; Bhavani, Gandham SriLakshmi; Girisha, Katta Mohan; Mustak, Mohammed S; Srinivasan, Sudha; Kaushik, Amit; Vahab, Saadi Abdul; Jagadeesh, Sujatha M.; Satyamoorthy, Kapaettu; Singh, Lalji; Reich, David; Thangaraj, Kumarasamy

    2017-01-01

    The more than 1.5 billion people who live in South Asia are correctly viewed not as a single large population, but as many small endogamous groups. We assembled genome-wide data from over 2,800 individuals from over 260 distinct South Asian groups. We identify 81 unique groups, of which 14 have estimated census sizes of more than a million, that descend from founder events more extreme than those in Ashkenazi Jews and Finns, both of which have high rates of recessive disease due to founder events. We identify multiple examples of recessive diseases in South Asia that are the result of such founder events. This study highlights an under-appreciated opportunity for reducing disease burden among South Asians through the discovery of and testing for recessive disease genes. PMID:28714977

  9. Genome Enabled Discovery of Carbon Sequestration Genes in Poplar

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Filichkin, Sergei; Etherington, Elizabeth; Ma, Caiping

    2007-02-22

    The goals of the S.H. Strauss laboratory portion of 'Genome-enabled discovery of carbon sequestration genes in poplar' are (1) to explore the functions of candidate genes using Populus transformation by inserting genes provided by Oakridge National Laboratory (ORNL) and the University of Florida (UF) into poplar; (2) to expand the poplar transformation toolkit by developing transformation methods for important genotypes; and (3) to allow induced expression, and efficient gene suppression, in roots and other tissues. As part of the transformation improvement effort, OSU developed transformation protocols for Populus trichocarpa 'Nisqually-1' clone and an early flowering P. alba clone, 6K10. Completemore » descriptions of the transformation systems were published (Ma et. al. 2004, Meilan et. al 2004). Twenty-one 'Nisqually-1' and 622 6K10 transgenic plants were generated. To identify root predominant promoters, a set of three promoters were tested for their tissue-specific expression patterns in poplar and in Arabidopsis as a model system. A novel gene, ET304, was identified by analyzing a collection of poplar enhancer trap lines generated at OSU (Filichkin et. al 2006a, 2006b). Other promoters include the pGgMT1 root-predominant promoter from Casuarina glauca and the pAtPIN2 promoter from Arabidopsis root specific PIN2 gene. OSU tested two induction systems, alcohol- and estrogen-inducible, in multiple poplar transgenics. Ethanol proved to be the more efficient when tested in tissue culture and greenhouse conditions. Two estrogen-inducible systems were evaluated in transgenic Populus, neither of which functioned reliably in tissue culture conditions. GATEWAY-compatible plant binary vectors were designed to compare the silencing efficiency of homologous (direct) RNAi vs. heterologous (transitive) RNAi inverted repeats. A set of genes was targeted for post transcriptional silencing in the model Arabidopsis system; these include the floral meristem identity gene

  10. The Matchmaker Exchange: a platform for rare disease gene discovery.

    PubMed

    Philippakis, Anthony A; Azzariti, Danielle R; Beltran, Sergi; Brookes, Anthony J; Brownstein, Catherine A; Brudno, Michael; Brunner, Han G; Buske, Orion J; Carey, Knox; Doll, Cassie; Dumitriu, Sergiu; Dyke, Stephanie O M; den Dunnen, Johan T; Firth, Helen V; Gibbs, Richard A; Girdea, Marta; Gonzalez, Michael; Haendel, Melissa A; Hamosh, Ada; Holm, Ingrid A; Huang, Lijia; Hurles, Matthew E; Hutton, Ben; Krier, Joel B; Misyura, Andriy; Mungall, Christopher J; Paschall, Justin; Paten, Benedict; Robinson, Peter N; Schiettecatte, François; Sobreira, Nara L; Swaminathan, Ganesh J; Taschner, Peter E; Terry, Sharon F; Washington, Nicole L; Züchner, Stephan; Boycott, Kym M; Rehm, Heidi L

    2015-10-01

    There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow. © 2015 WILEY PERIODICALS, INC.

  11. The Matchmaker Exchange: A Platform for Rare Disease Gene Discovery

    DOE PAGES

    Philippakis, Anthony A.; Azzariti, Danielle R.; Beltran, Sergi; ...

    2015-09-17

    There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be amore » reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. In conclusion, three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.« less

  12. The Matchmaker Exchange: A Platform for Rare Disease Gene Discovery

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Philippakis, Anthony A.; Azzariti, Danielle R.; Beltran, Sergi

    There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be amore » reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. In conclusion, three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.« less

  13. CuAAC click chemistry accelerates the discovery of novel chemical scaffolds as promising protein tyrosine phosphatases inhibitors.

    PubMed

    He, X-P; Xie, J; Tang, Y; Li, J; Chen, G-R

    2012-01-01

    Protein tyrosine phosphatases (PTPs) are crucial regulators for numerous biological processes in nature. The dysfunction and overexpression of many PTP members have been demonstrated to cause fatal human diseases such as cancers, diabetes, obesity, neurodegenerative diseases and autoimmune disorders. In the past decade, considerable efforts have been devoted to the production of PTPs inhibitors by both academia and the pharmaceutical industry. However, there are only limited drug candidates in clinical trials and no commercial drugs have been approved, implying that further efficient discovery of novel chemical entities competent for inhibition of the specific PTP target in vivo remains yet a challenge. In light of the click-chemistry paradigm which advocates the utilization of concise and selective carbon-heteroatom ligation reactions for the modular construction of useful compound libraries, the Cu(I)-catalyzed azidealkyne 1,3-dipolar cycloaddition reaction (CuAAC) has fueled enormous energy into the modern drug discovery. Recently, this ingenious chemical ligation tool has also revealed efficacious and expeditious in establishing large combinatorial libraries for the acquisition of novel PTPs inhibitors with promising pharmacological profiles. We thus offer here a comprehensive review highlighting the development of PTPs inhibitors accelerated by the CuAAC click chemistry.

  14. Live Cell in Vitro and in Vivo Imaging Applications: Accelerating Drug Discovery

    PubMed Central

    Isherwood, Beverley; Timpson, Paul; McGhee, Ewan J; Anderson, Kurt I; Canel, Marta; Serrels, Alan; Brunton, Valerie G; Carragher, Neil O

    2011-01-01

    Dynamic regulation of specific molecular processes and cellular phenotypes in live cell systems reveal unique insights into cell fate and drug pharmacology that are not gained from traditional fixed endpoint assays. Recent advances in microscopic imaging platform technology combined with the development of novel optical biosensors and sophisticated image analysis solutions have increased the scope of live cell imaging applications in drug discovery. We highlight recent literature examples where live cell imaging has uncovered novel insight into biological mechanism or drug mode-of-action. We survey distinct types of optical biosensors and associated analytical methods for monitoring molecular dynamics, in vitro and in vivo. We describe the recent expansion of live cell imaging into automated target validation and drug screening activities through the development of dedicated brightfield and fluorescence kinetic imaging platforms. We provide specific examples of how temporal profiling of phenotypic response signatures using such kinetic imaging platforms can increase the value of in vitro high-content screening. Finally, we offer a prospective view of how further application and development of live cell imaging technology and reagents can accelerate preclinical lead optimization cycles and enhance the in vitro to in vivo translation of drug candidates. PMID:24310493

  15. A genomics based discovery of secondary metabolite biosynthetic gene clusters in Aspergillus ustus.

    PubMed

    Pi, Borui; Yu, Dongliang; Dai, Fangwei; Song, Xiaoming; Zhu, Congyi; Li, Hongye; Yu, Yunsong

    2015-01-01

    Secondary metabolites (SMs) produced by Aspergillus have been extensively studied for their crucial roles in human health, medicine and industrial production. However, the resulting information is almost exclusively derived from a few model organisms, including A. nidulans and A. fumigatus, but little is known about rare pathogens. In this study, we performed a genomics based discovery of SM biosynthetic gene clusters in Aspergillus ustus, a rare human pathogen. A total of 52 gene clusters were identified in the draft genome of A. ustus 3.3904, such as the sterigmatocystin biosynthesis pathway that was commonly found in Aspergillus species. In addition, several SM biosynthetic gene clusters were firstly identified in Aspergillus that were possibly acquired by horizontal gene transfer, including the vrt cluster that is responsible for viridicatumtoxin production. Comparative genomics revealed that A. ustus shared the largest number of SM biosynthetic gene clusters with A. nidulans, but much fewer with other Aspergilli like A. niger and A. oryzae. These findings would help to understand the diversity and evolution of SM biosynthesis pathways in genus Aspergillus, and we hope they will also promote the development of fungal identification methodology in clinic.

  16. A Genomics Based Discovery of Secondary Metabolite Biosynthetic Gene Clusters in Aspergillus ustus

    PubMed Central

    Pi, Borui; Yu, Dongliang; Dai, Fangwei; Song, Xiaoming; Zhu, Congyi; Li, Hongye; Yu, Yunsong

    2015-01-01

    Secondary metabolites (SMs) produced by Aspergillus have been extensively studied for their crucial roles in human health, medicine and industrial production. However, the resulting information is almost exclusively derived from a few model organisms, including A. nidulans and A. fumigatus, but little is known about rare pathogens. In this study, we performed a genomics based discovery of SM biosynthetic gene clusters in Aspergillus ustus, a rare human pathogen. A total of 52 gene clusters were identified in the draft genome of A. ustus 3.3904, such as the sterigmatocystin biosynthesis pathway that was commonly found in Aspergillus species. In addition, several SM biosynthetic gene clusters were firstly identified in Aspergillus that were possibly acquired by horizontal gene transfer, including the vrt cluster that is responsible for viridicatumtoxin production. Comparative genomics revealed that A. ustus shared the largest number of SM biosynthetic gene clusters with A. nidulans, but much fewer with other Aspergilli like A. niger and A. oryzae. These findings would help to understand the diversity and evolution of SM biosynthesis pathways in genus Aspergillus, and we hope they will also promote the development of fungal identification methodology in clinic. PMID:25706180

  17. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis.

    PubMed

    Mallik, Saurav; Zhao, Zhongming

    2017-12-28

    For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures-weighted rank-based Jaccard and Cosine measures-and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s) through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm-RANWAR-was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

  18. Gene Discovery in the Apicomplexa as Revealed by EST Sequencing and Assembly of a Comparative Gene Database

    PubMed Central

    Li, Li; Brunk, Brian P.; Kissinger, Jessica C.; Pape, Deana; Tang, Keliang; Cole, Robert H.; Martin, John; Wylie, Todd; Dante, Mike; Fogarty, Steven J.; Howe, Daniel K.; Liberator, Paul; Diaz, Carmen; Anderson, Jennifer; White, Michael; Jerome, Maria E.; Johnson, Emily A.; Radke, Jay A.; Stoeckert, Christian J.; Waterston, Robert H.; Clifton, Sandra W.; Roos, David S.; Sibley, L. David

    2003-01-01

    Large-scale EST sequencing projects for several important parasites within the phylum Apicomplexa were undertaken for the purpose of gene discovery. Included were several parasites of medical importance (Plasmodium falciparum, Toxoplasma gondii) and others of veterinary importance (Eimeria tenella, Sarcocystis neurona, and Neospora caninum). A total of 55,192 ESTs, deposited into dbEST/GenBank, were included in the analyses. The resulting sequences have been clustered into nonredundant gene assemblies and deposited into a relational database that supports a variety of sequence and text searches. This database has been used to compare the gene assemblies using BLAST similarity comparisons to the public protein databases to identify putative genes. Of these new entries, ∼15%–20% represent putative homologs with a conservative cutoff of p < 10−9, thus identifying many conserved genes that are likely to share common functions with other well-studied organisms. Gene assemblies were also used to identify strain polymorphisms, examine stage-specific expression, and identify gene families. An interesting class of genes that are confined to members of this phylum and not shared by plants, animals, or fungi, was identified. These genes likely mediate the novel biological features of members of the Apicomplexa and hence offer great potential for biological investigation and as possible therapeutic targets. [The sequence data from this study have been submitted to dbEST division of GenBank under accession nos.: Toxoplasma gondii: –, –, –, –, – , –, –, –, –. Plasmodium falciparum: –, –, –, –. Sarcocystis neurona: , , , , , , , , , , , , , –, –, –, –, –. Eimeria tenella: –, –, –, –, –, –, –, –, – , –, –, –, –, –, –, –, –, –, –, –. Neospora caninum: –, –, , – , –, –.] PMID:12618375

  19. Computational Materials Science and Chemistry: Accelerating Discovery and Innovation through Simulation-Based Engineering and Science

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Crabtree, George; Glotzer, Sharon; McCurdy, Bill

    This report is based on a SC Workshop on Computational Materials Science and Chemistry for Innovation on July 26-27, 2010, to assess the potential of state-of-the-art computer simulations to accelerate understanding and discovery in materials science and chemistry, with a focus on potential impacts in energy technologies and innovation. The urgent demand for new energy technologies has greatly exceeded the capabilities of today's materials and chemical processes. To convert sunlight to fuel, efficiently store energy, or enable a new generation of energy production and utilization technologies requires the development of new materials and processes of unprecedented functionality and performance. Newmore » materials and processes are critical pacing elements for progress in advanced energy systems and virtually all industrial technologies. Over the past two decades, the United States has developed and deployed the world's most powerful collection of tools for the synthesis, processing, characterization, and simulation and modeling of materials and chemical systems at the nanoscale, dimensions of a few atoms to a few hundred atoms across. These tools, which include world-leading x-ray and neutron sources, nanoscale science facilities, and high-performance computers, provide an unprecedented view of the atomic-scale structure and dynamics of materials and the molecular-scale basis of chemical processes. For the first time in history, we are able to synthesize, characterize, and model materials and chemical behavior at the length scale where this behavior is controlled. This ability is transformational for the discovery process and, as a result, confers a significant competitive advantage. Perhaps the most spectacular increase in capability has been demonstrated in high performance computing. Over the past decade, computational power has increased by a factor of a million due to advances in hardware and software. This rate of improvement, which shows no sign of

  20. Gene signature critical to cancer phenotype as a paradigm for anti-cancer drug discovery

    PubMed Central

    Sampson, Erik R.; McMurray, Helene R.; Hassane, Duane C.; Newman, Laurel; Salzman, Peter; Jordan, Craig T.; Land, Hartmut

    2013-01-01

    Malignant cell transformation commonly results in the deregulation of thousands of cellular genes, an observation that suggests a complex biological process and an inherently challenging scenario for the development of effective cancer interventions. To better define the genes/pathways essential to regulating the malignant phenotype, we recently described a novel strategy based on the cooperative nature of carcinogenesis that focuses on genes synergistically deregulated in response to cooperating oncogenic mutations. These so-called “cooperation response genes” (CRGs) are highly enriched for genes critical for the cancer phenotype, thereby suggesting their causal role in the malignant state. Here we show that CRGs play an essential role in drug-mediated anti-cancer activity and that anti-cancer agents can be identified through their ability to antagonize the CRG expression profile. These findings provide proof-of-concept for the use of the CRG signature as a novel means of drug discovery with relevance to underlying anti-cancer drug mechanisms. PMID:22964631

  1. IMG-ABC. A knowledge base to fuel discovery of biosynthetic gene clusters and novel secondary metabolites

    DOE PAGES

    Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; ...

    2015-07-14

    In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG’s comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve asmore » the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC’s focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in lphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG’s extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG

  2. IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.

    PubMed

    Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; Ratner, Anna; Palaniappan, Krishna; Szeto, Ernest; Huang, Jinghua; Reddy, T B K; Cimermančič, Peter; Fischbach, Michael A; Ivanova, Natalia N; Markowitz, Victor M; Kyrpides, Nikos C; Pati, Amrita

    2015-07-14

    In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of "big" genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to

  3. Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis.

    PubMed

    Shchetynsky, Klementy; Diaz-Gallo, Lina-Marcella; Folkersen, Lasse; Hensvold, Aase Haj; Catrina, Anca Irinel; Berg, Louise; Klareskog, Lars; Padyukov, Leonid

    2017-02-02

    Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). RNA-sequencing-(RNA-seq)-based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated patients with RA, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of "connector" genes derived from pathway analysis was tested for differential expression in the initial discovery cohort and validated in blood cells from 73 patients with RA and in 35 healthy controls. There were 11 qualifying genes selected for pathway analysis and these were grouped into two evidence-based functional networks, containing 29 and 27 additional connector molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. Differences in the expression of ERBB2, TP53 and THOP1 were similar in both treated and non-treated patients with RA and an additional nine genes were differentially expressed in at least one group of patients compared to healthy controls. The ERBB2, TP53. THOP1 expression profile was successfully replicated in RNA-seq data from peripheral blood mononuclear cells from healthy controls and non-treated patients with RA, in an independent collection of samples. Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes, ERBB2, TP53 and THOP1 in the pathogenesis of RA.

  4. Sphingosine 1-Phosphate Receptor Modulators and Drug Discovery

    PubMed Central

    Park, Soo-Jin; Im, Dong-Soon

    2017-01-01

    Initial discovery on sphingosine 1-phosphate (S1P) as an intracellular second messenger was faced unexpectedly with roles of S1P as a first messenger, which subsequently resulted in cloning of its G protein-coupled receptors, S1P1–5. The molecular identification of S1P receptors opened up a new avenue for pathophysiological research on this lipid mediator. Cellular and molecular in vitro studies and in vivo studies on gene deficient mice have elucidated cellular signaling pathways and the pathophysiological meanings of S1P receptors. Another unexpected finding that fingolimod (FTY720) modulates S1P receptors accelerated drug discovery in this field. Fingolimod was approved as a first-in-class, orally active drug for relapsing multiple sclerosis in 2010, and its applications in other disease conditions are currently under clinical trials. In addition, more selective S1P receptor modulators with better pharmacokinetic profiles and fewer side effects are under development. Some of them are being clinically tested in the contexts of multiple sclerosis and other autoimmune and inflammatory disorders, such as, psoriasis, Crohn’s disease, ulcerative colitis, polymyositis, dermatomyositis, liver failure, renal failure, acute stroke, and transplant rejection. In this review, the authors discuss the state of the art regarding the status of drug discovery efforts targeting S1P receptors and place emphasis on potential clinical applications. PMID:28035084

  5. FORGE Canada Consortium: outcomes of a 2-year national rare-disease gene-discovery project.

    PubMed

    Beaulieu, Chandree L; Majewski, Jacek; Schwartzentruber, Jeremy; Samuels, Mark E; Fernandez, Bridget A; Bernier, Francois P; Brudno, Michael; Knoppers, Bartha; Marcadier, Janet; Dyment, David; Adam, Shelin; Bulman, Dennis E; Jones, Steve J M; Avard, Denise; Nguyen, Minh Thu; Rousseau, Francois; Marshall, Christian; Wintle, Richard F; Shen, Yaoqing; Scherer, Stephen W; Friedman, Jan M; Michaud, Jacques L; Boycott, Kym M

    2014-06-05

    Inherited monogenic disease has an enormous impact on the well-being of children and their families. Over half of the children living with one of these conditions are without a molecular diagnosis because of the rarity of the disease, the marked clinical heterogeneity, and the reality that there are thousands of rare diseases for which causative mutations have yet to be identified. It is in this context that in 2010 a Canadian consortium was formed to rapidly identify mutations causing a wide spectrum of pediatric-onset rare diseases by using whole-exome sequencing. The FORGE (Finding of Rare Disease Genes) Canada Consortium brought together clinicians and scientists from 21 genetics centers and three science and technology innovation centers from across Canada. From nation-wide requests for proposals, 264 disorders were selected for study from the 371 submitted; disease-causing variants (including in 67 genes not previously associated with human disease; 41 of these have been genetically or functionally validated, and 26 are currently under study) were identified for 146 disorders over a 2-year period. Here, we present our experience with four strategies employed for gene discovery and discuss FORGE's impact in a number of realms, from clinical diagnostics to the broadening of the phenotypic spectrum of many diseases to the biological insight gained into both disease states and normal human development. Lastly, on the basis of this experience, we discuss the way forward for rare-disease genetic discovery both in Canada and internationally. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  6. Systems-based biological concordance and predictive reproducibility of gene set discovery methods in cardiovascular disease.

    PubMed

    Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying

    2011-08-01

    The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

  7. Discovery and validation of gene classifiers for endocrine-disrupting chemicals in zebrafish (danio rerio)

    PubMed Central

    2012-01-01

    -tissue conditions, thus suggesting a need for a preliminary survey of transcriptomic responses before launching a full scale classifier discovery effort. Classifier discovery based on individual TF networks could yield more mechanistically-oriented biomarkers. GSEA proved to be a flexible and effective tool for application of gene classifiers but a similar and more refined algorithm, connectivity mapping, should also be explored. The distribution characteristics of classifiers across tissues, chemicals, and TF networks suggested a differential biological impact among the EDCs on zebrafish transcriptome involving some basic cellular functions. PMID:22849515

  8. Gene discovery using next-generation pyrosequencing to develop ESTs for Phalaenopsis orchids

    PubMed Central

    2011-01-01

    Background Orchids are one of the most diversified angiosperms, but few genomic resources are available for these non-model plants. In addition to the ecological significance, Phalaenopsis has been considered as an economically important floriculture industry worldwide. We aimed to use massively parallel 454 pyrosequencing for a global characterization of the Phalaenopsis transcriptome. Results To maximize sequence diversity, we pooled RNA from 10 samples of different tissues, various developmental stages, and biotic- or abiotic-stressed plants. We obtained 206,960 expressed sequence tags (ESTs) with an average read length of 228 bp. These reads were assembled into 8,233 contigs and 34,630 singletons. The unigenes were searched against the NCBI non-redundant (NR) protein database. Based on sequence similarity with known proteins, these analyses identified 22,234 different genes (E-value cutoff, e-7). Assembled sequences were annotated with Gene Ontology, Gene Family and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Among these annotations, over 780 unigenes encoding putative transcription factors were identified. Conclusion Pyrosequencing was effective in identifying a large set of unigenes from Phalaenopsis. The informative EST dataset we developed constitutes a much-needed resource for discovery of genes involved in various biological processes in Phalaenopsis and other orchid species. These transcribed sequences will narrow the gap between study of model organisms with many genomic resources and species that are important for ecological and evolutionary studies. PMID:21749684

  9. An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation

    PubMed Central

    Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander

    2016-01-01

    Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894

  10. How the serotonin story is being rewritten by new gene-based discoveries principally related to SLC6A4, the serotonin transporter gene, which functions to influence all cellular serotonin systems.

    PubMed

    Murphy, Dennis L; Fox, Meredith A; Timpano, Kiara R; Moya, Pablo R; Ren-Patterson, Renee; Andrews, Anne M; Holmes, Andrew; Lesch, Klaus-Peter; Wendland, Jens R

    2008-11-01

    Discovered and crystallized over sixty years ago, serotonin's important functions in the brain and body were identified over the ensuing years by neurochemical, physiological and pharmacological investigations. This 2008 M. Rapport Memorial Serotonin Review focuses on some of the most recent discoveries involving serotonin that are based on genetic methodologies. These include examples of the consequences that result from direct serotonergic gene manipulation (gene deletion or overexpression) in mice and other species; an evaluation of some phenotypes related to functional human serotonergic gene variants, particularly in SLC6A4, the serotonin transporter gene; and finally, a consideration of the pharmacogenomics of serotonergic drugs with respect to both their therapeutic actions and side effects. The serotonin transporter (SERT) has been the most comprehensively studied of the serotonin system molecular components, and will be the primary focus of this review. We provide in-depth examples of gene-based discoveries primarily related to SLC6A4 that have clarified serotonin's many important homeostatic functions in humans, non-human primates, mice and other species.

  11. ATOM - Accelerating Therapeutics for Opportunities in Medicine | FNLCR Staging

    Cancer.gov

    The Frederick National Lab is a founding member of the Accelerating Therapeutics for Opportunities in Medicine (ATOM) Consortium,a public-private partnership with themission oftransforming drug discovery by accelerating the deve

  12. Radiation Detection Material Discovery Initiative at PNNL

    NASA Astrophysics Data System (ADS)

    Milbrath, Brian

    2006-05-01

    Today's security threats are being met with 30-year old radiation technology. Discovery of new radiation detection materials is currently a slow and Edisonian process. With heightened concerns over nuclear proliferation, terrorism and unconventional warfare, an alternative strategy for identification and development of potential radiation detection materials must be adopted. Through the Radiation Detection Materials Discovery Initiative, PNNL focuses on the science-based discovery of next generation materials for radiation detection by addressing three ``grand challenges'': fundamental understanding of radiation detection, identification of new materials, and accelerating the discovery process. The new initiative has eight projects addressing these challenges, which will be described, including early work, paths forward and the opportunities for collaboration.

  13. TOXICOGENOMICS DRUG DISCOVERY AND THE PATHOLOGIST

    EPA Science Inventory

    Toxicogenomics, drug discovery, and pathologist.

    The field of toxicogenomics, which currently focuses on the application of large-scale differential gene expression (DGE) data to toxicology, is starting to influence drug discovery and development in the pharmaceutical indu...

  14. An integrative model for in-silico clinical-genomics discovery science.

    PubMed

    Lussier, Yves A; Sarkar, Indra Nell; Cantor, Michael

    2002-01-01

    Human Genome discovery research has set the pace for Post-Genomic Discovery Research. While post-genomic fields focused at the molecular level are intensively pursued, little effort is being deployed in the later stages of molecular medicine discovery research, such as clinical-genomics. The objective of this study is to demonstrate the relevance and significance of integrating mainstream clinical informatics decision support systems to current bioinformatics genomic discovery science. This paper is a feasibility study of an original model enabling novel "in-silico" clinical-genomic discovery science and that demonstrates its feasibility. This model is designed to mediate queries among clinical and genomic knowledge bases with relevant bioinformatic analytic tools (e.g. gene clustering). Briefly, trait-disease-gene relationships were successfully illustrated using QMR, OMIM, SNOMED-RT, GeneCluster and TreeView. The analyses were visualized as two-dimensional dendrograms of clinical observations clustered around genes. To our knowledge, this is the first study using knowledge bases of clinical decision support systems for genomic discovery. Although this study is a proof of principle, it provides a framework for the development of clinical decision-support-system driven, high-throughput clinical-genomic technologies which could potentially unveil significant high-level functions of genes.

  15. Empowering Accelerated Personal, Professional and Scholarly Discovery among Information Seekers: An Educational Vision

    ERIC Educational Resources Information Center

    Harmon, Glynn

    2013-01-01

    The term discovery applies herein to the successful outcome of inquiry in which a significant personal, professional or scholarly breakthrough or insight occurs, and which is individually or socially acknowledged as a key contribution to knowledge. Since discoveries culminate at fixed points in time, discoveries can serve as an outcome metric for…

  16. Discovery of rice essential genes by characterizing a CRISPR-edited mutation of closely related rice MAP kinase genes.

    PubMed

    Minkenberg, Bastian; Xie, Kabin; Yang, Yinong

    2017-02-01

    The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 nuclease (Cas9) system depends on a guide RNA (gRNA) to specify its target. By efficiently co-expressing multiple gRNAs that target different genomic sites, the polycistronic tRNA-gRNA gene (PTG) strategy enables multiplex gene editing in the family of closely related mitogen-activated protein kinase (MPK) genes in Oryza sativa (rice). In this study, we identified MPK1 and MPK6 (Arabidopsis AtMPK6 and AtMPK4 orthologs, respectively) as essential genes for rice development by finding the preservation of MPK functional alleles and normal phenotypes in CRISPR-edited mutants. The true knock-out mutants of MPK1 were severely dwarfed and sterile, and homozygous mpk1 seeds from heterozygous parents were defective in embryo development. By contrast, heterozygous mpk6 mutant plants completely failed to produce homozygous mpk6 seeds. In addition, the functional importance of specific MPK features could be evaluated by characterizing CRISPR-induced allelic variation in the conserved kinase domain of MPK6. By simultaneously targeting between two and eight genomic sites in the closely related MPK genes, we demonstrated 45-86% frequency of biallelic mutations and the successful creation of single, double and quadruple gene mutants. Indels and fragment deletion were both stably inherited to the next generations, and transgene-free mutants of rice MPK genes were readily obtained via genetic segregation, thereby eliminating any positional effects of transgene insertions. Taken together, our study reveals the essentiality of MPK1 and MPK6 in rice development, and enables the functional discovery of previously inaccessible genes or domains with phenotypes masked by lethality or redundancy. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

  17. Co-fuse: a new class discovery analysis tool to identify and prioritize recurrent fusion genes from RNA-sequencing data.

    PubMed

    Paisitkriangkrai, Sakrapee; Quek, Kelly; Nievergall, Eva; Jabbour, Anissa; Zannettino, Andrew; Kok, Chung Hoow

    2018-06-07

    Recurrent oncogenic fusion genes play a critical role in the development of various cancers and diseases and provide, in some cases, excellent therapeutic targets. To date, analysis tools that can identify and compare recurrent fusion genes across multiple samples have not been available to researchers. To address this deficiency, we developed Co-occurrence Fusion (Co-fuse), a new and easy to use software tool that enables biologists to merge RNA-seq information, allowing them to identify recurrent fusion genes, without the need for exhaustive data processing. Notably, Co-fuse is based on pattern mining and statistical analysis which enables the identification of hidden patterns of recurrent fusion genes. In this report, we show that Co-fuse can be used to identify 2 distinct groups within a set of 49 leukemic cell lines based on their recurrent fusion genes: a multiple myeloma (MM) samples-enriched cluster and an acute myeloid leukemia (AML) samples-enriched cluster. Our experimental results further demonstrate that Co-fuse can identify known driver fusion genes (e.g., IGH-MYC, IGH-WHSC1) in MM, when compared to AML samples, indicating the potential of Co-fuse to aid the discovery of yet unknown driver fusion genes through cohort comparisons. Additionally, using a 272 primary glioma sample RNA-seq dataset, Co-fuse was able to validate recurrent fusion genes, further demonstrating the power of this analysis tool to identify recurrent fusion genes. Taken together, Co-fuse is a powerful new analysis tool that can be readily applied to large RNA-seq datasets, and may lead to the discovery of new disease subgroups and potentially new driver genes, for which, targeted therapies could be developed. The Co-fuse R source code is publicly available at https://github.com/sakrapee/co-fuse .

  18. High-throughput platform for the discovery of elicitors of silent bacterial gene clusters.

    PubMed

    Seyedsayamdost, Mohammad R

    2014-05-20

    Over the past decade, bacterial genome sequences have revealed an immense reservoir of biosynthetic gene clusters, sets of contiguous genes that have the potential to produce drugs or drug-like molecules. However, the majority of these gene clusters appear to be inactive for unknown reasons prompting terms such as "cryptic" or "silent" to describe them. Because natural products have been a major source of therapeutic molecules, methods that rationally activate these silent clusters would have a profound impact on drug discovery. Herein, a new strategy is outlined for awakening silent gene clusters using small molecule elicitors. In this method, a genetic reporter construct affords a facile read-out for activation of the silent cluster of interest, while high-throughput screening of small molecule libraries provides potential inducers. This approach was applied to two cryptic gene clusters in the pathogenic model Burkholderia thailandensis. The results not only demonstrate a prominent activation of these two clusters, but also reveal that the majority of elicitors are themselves antibiotics, most in common clinical use. Antibiotics, which kill B. thailandensis at high concentrations, act as inducers of secondary metabolism at low concentrations. One of these antibiotics, trimethoprim, served as a global activator of secondary metabolism by inducing at least five biosynthetic pathways. Further application of this strategy promises to uncover the regulatory networks that activate silent gene clusters while at the same time providing access to the vast array of cryptic molecules found in bacteria.

  19. A New Omics Data Resource of Pleurocybella porrigens for Gene Discovery

    PubMed Central

    Dohra, Hideo; Someya, Takumi; Takano, Tomoyuki; Harada, Kiyonori; Omae, Saori; Hirai, Hirofumi; Yano, Kentaro; Kawagishi, Hirokazu

    2013-01-01

    Background Pleurocybella porrigens is a mushroom-forming fungus, which has been consumed as a traditional food in Japan. In 2004, 55 people were poisoned by eating the mushroom and 17 people among them died of acute encephalopathy. Since then, the Japanese government has been alerting Japanese people to take precautions against eating the P . porrigens mushroom. Unfortunately, despite efforts, the molecular mechanism of the encephalopathy remains elusive. The genome and transcriptome sequence data of P . porrigens and the related species, however, are not stored in the public database. To gain the omics data in P . porrigens , we sequenced genome and transcriptome of its fruiting bodies and mycelia by next generation sequencing. Methodology/Principal Findings Short read sequences of genomic DNAs and mRNAs in P . porrigens were generated by Illumina Genome Analyzer. Genome short reads were de novo assembled into scaffolds using Velvet. Comparisons of genome signatures among Agaricales showed that P . porrigens has a unique genome signature. Transcriptome sequences were assembled into contigs (unigenes). Biological functions of unigenes were predicted by Gene Ontology and KEGG pathway analyses. The majority of unigenes would be novel genes without significant counterparts in the public omics databases. Conclusions Functional analyses of unigenes present the existence of numerous novel genes in the basidiomycetes division. The results mean that the omics information such as genome, transcriptome and metabolome in basidiomycetes is short in the current databases. The large-scale omics information on P . porrigens , provided from this research, will give a new data resource for gene discovery in basidiomycetes. PMID:23936076

  20. IMG-ABC: An Atlas of Biosynthetic Gene Clusters to Fuel the Discovery of Novel Secondary Metabolites

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chen, I-Min; Chu, Ken; Ratner, Anna

    2014-10-28

    In the discovery of secondary metabolites (SMs), large-scale analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of relevant computational resources. We present IMG-ABC (https://img.jgi.doe.gov/abc/) -- An Atlas of Biosynthetic gene Clusters within the Integrated Microbial Genomes (IMG) system1. IMG-ABC is a rich repository of both validated and predicted biosynthetic clusters (BCs) in cultured isolates, single-cells and metagenomes linked with the SM chemicals they produce and enhanced with focused analysis tools within IMG. The underlying scalable framework enables traversal of phylogenetic dark matter and chemical structure space -- serving as a doorwaymore » to a new era in the discovery of novel molecules.« less

  1. A comparative review of estimates of the proportion unchanged genes and the false discovery rate

    PubMed Central

    Broberg, Per

    2005-01-01

    Background In the analysis of microarray data one generally produces a vector of p-values that for each gene give the likelihood of obtaining equally strong evidence of change by pure chance. The distribution of these p-values is a mixture of two components corresponding to the changed genes and the unchanged ones. The focus of this article is how to estimate the proportion unchanged and the false discovery rate (FDR) and how to make inferences based on these concepts. Six published methods for estimating the proportion unchanged genes are reviewed, two alternatives are presented, and all are tested on both simulated and real data. All estimates but one make do without any parametric assumptions concerning the distributions of the p-values. Furthermore, the estimation and use of the FDR and the closely related q-value is illustrated with examples. Five published estimates of the FDR and one new are presented and tested. Implementations in R code are available. Results A simulation model based on the distribution of real microarray data plus two real data sets were used to assess the methods. The proposed alternative methods for estimating the proportion unchanged fared very well, and gave evidence of low bias and very low variance. Different methods perform well depending upon whether there are few or many regulated genes. Furthermore, the methods for estimating FDR showed a varying performance, and were sometimes misleading. The new method had a very low error. Conclusion The concept of the q-value or false discovery rate is useful in practical research, despite some theoretical and practical shortcomings. However, it seems possible to challenge the performance of the published methods, and there is likely scope for further developing the estimates of the FDR. The new methods provide the scientist with more options to choose a suitable method for any particular experiment. The article advocates the use of the conjoint information regarding false positive and

  2. Accelerating Innovation in the Creation of Biovalue: The Cell and Gene Therapy Catapult.

    PubMed

    Gardner, John; Webster, Andrew

    2017-09-01

    The field of regenerative medicine (RM) has considerable therapeutic promise that is proving difficult to realize. As a result, governments have supported the establishment of intermediary agencies to "accelerate" innovation. This article examines in detail one such agency, the United Kingdom's Cell and Gene Therapy Catapult (CGTC). We describe CGTC's role as an accelerator agency and its value narrative, which combines both "health and wealth." Drawing on the notion of sociotechnical imaginaries, we unpack the tensions within this narrative and its instantiation as the CGTC cell therapy infrastructure is built and engages with other agencies, some of which have different priorities and roles to play within the RM field.

  3. Gene Discovery of Characteristic Metabolic Pathways in the Tea Plant (Camellia sinensis) Using ‘Omics’-Based Network Approaches: A Future Perspective

    PubMed Central

    Zhang, Shihua; Zhang, Liang; Tai, Yuling; Wang, Xuewen; Ho, Chi-Tang; Wan, Xiaochun

    2018-01-01

    Characteristic secondary metabolites, including flavonoids, theanine and caffeine, in the tea plant (Camellia sinensis) are the primary sources of the rich flavors, fresh taste, and health benefits of tea. The decoding of genes involved in these characteristic components is still significantly lagging, which lays an obstacle for applied genetic improvement and metabolic engineering. With the popularity of high-throughout transcriptomics and metabolomics, ‘omics’-based network approaches, such as gene co-expression network and gene-to-metabolite network, have emerged as powerful tools for gene discovery of plant-specialized (secondary) metabolism. Thus, it is pivotal to summarize and introduce such system-based strategies in facilitating gene identification of characteristic metabolic pathways in the tea plant (or other plants). In this review, we describe recent advances in transcriptomics and metabolomics for transcript and metabolite profiling, and highlight ‘omics’-based network strategies using successful examples in model and non-model plants. Further, we summarize recent progress in ‘omics’ analysis for gene identification of characteristic metabolites in the tea plant. Limitations of the current strategies are discussed by comparison with ‘omics’-based network approaches. Finally, we demonstrate the potential of introducing such network strategies in the tea plant, with a prospects ending for a promising network discovery of characteristic metabolite genes in the tea plant. PMID:29915604

  4. A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.

    PubMed

    Ficklin, Stephen P; Feltus, Frank Alex

    2013-01-01

    Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with

  5. Accelerating Drug Development: Antiviral Therapies for Emerging Viruses as a Model.

    PubMed

    Everts, Maaike; Cihlar, Tomas; Bostwick, J Robert; Whitley, Richard J

    2017-01-06

    Drug discovery and development is a lengthy and expensive process. Although no one, simple, single solution can significantly accelerate this process, steps can be taken to avoid unnecessary delays. Using the development of antiviral therapies as a model, we describe options for acceleration that cover target selection, assay development and high-throughput screening, hit confirmation, lead identification and development, animal model evaluations, toxicity studies, regulatory issues, and the general drug discovery and development infrastructure. Together, these steps could result in accelerated timelines for bringing antiviral therapies to market so they can treat emerging infections and reduce human suffering.

  6. Transient Hypermutagenesis Accelerates the Evolution of Legume Endosymbionts following Horizontal Gene Transfer

    PubMed Central

    Remigi, Philippe; Capela, Delphine; Clerissi, Camille; Tasse, Léna; Torchet, Rachel; Bouchez, Olivier; Batut, Jacques; Cruveiller, Stéphane; Rocha, Eduardo P. C.; Masson-Boivin, Catherine

    2014-01-01

    Horizontal gene transfer (HGT) is an important mode of adaptation and diversification of prokaryotes and eukaryotes and a major event underlying the emergence of bacterial pathogens and mutualists. Yet it remains unclear how complex phenotypic traits such as the ability to fix nitrogen with legumes have successfully spread over large phylogenetic distances. Here we show, using experimental evolution coupled with whole genome sequencing, that co-transfer of imuABC error-prone DNA polymerase genes with key symbiotic genes accelerates the evolution of a soil bacterium into a legume symbiont. Following introduction of the symbiotic plasmid of Cupriavidus taiwanensis, the Mimosa symbiont, into pathogenic Ralstonia solanacearum we challenged transconjugants to become Mimosa symbionts through serial plant-bacteria co-cultures. We demonstrate that a mutagenesis imuABC cassette encoded on the C. taiwanensis symbiotic plasmid triggered a transient hypermutability stage in R. solanacearum transconjugants that occurred before the cells entered the plant. The generated burst in genetic diversity accelerated symbiotic adaptation of the recipient genome under plant selection pressure, presumably by improving the exploration of the fitness landscape. Finally, we show that plasmid imuABC cassettes are over-represented in rhizobial lineages harboring symbiotic plasmids. Our findings shed light on a mechanism that may have facilitated the dissemination of symbiotic competency among α- and β-proteobacteria in natura and provide evidence for the positive role of environment-induced mutagenesis in the acquisition of a complex lifestyle trait. We speculate that co-transfer of complex phenotypic traits with mutagenesis determinants might frequently enhance the ecological success of HGT. PMID:25181317

  7. CREB and the discovery of cognitive enhancers.

    PubMed

    Scott, Roderick; Bourtchuladze, Rusiko; Gossweiler, Scott; Dubnau, Josh; Tully, Tim

    2002-01-01

    In the past few years, a series of molecular-genetic, biochemical, cellular and behavioral studies in fruit flies, sea slugs and mice have confirmed a long-standing notion that long-term memory formation depends on the synthesis of new proteins. Experiments focused on the cAMP-responsive transcription factor, CREB, have established that neural activity-induced regulation of gene transcription promotes a synaptic growth process that strengthens the connections among active neurons. This process constitutes a physical basis for the engram--and CREB is a "molecular switch" to produce the engram. Helicon Therapeutics has been formed to identify drug compounds that enhance memory formation via augmentation of CREB biochemistry. Candidate compounds have been identified from a high throughput cell-based screen and are being evaluated in animal models of memory formation. A gene discovery program also seeks to identify new genes, which function downstream of CREB during memory formation, as a source for new drug discoveries in the future. Together, these drug and gene discovery efforts promise new class of pharmaceutical therapies for the treatment of various forms of cognitive dysfunction.

  8. Genomics-driven discovery of the pneumocandin biosynthetic gene cluster in the fungus Glarea lozoyensis

    PubMed Central

    2013-01-01

    Background The antifungal therapy caspofungin is a semi-synthetic derivative of pneumocandin B0, a lipohexapeptide produced by the fungus Glarea lozoyensis, and was the first member of the echinocandin class approved for human therapy. The nonribosomal peptide synthetase (NRPS)-polyketide synthases (PKS) gene cluster responsible for pneumocandin biosynthesis from G. lozoyensis has not been elucidated to date. In this study, we report the elucidation of the pneumocandin biosynthetic gene cluster by whole genome sequencing of the G. lozoyensis wild-type strain ATCC 20868. Results The pneumocandin biosynthetic gene cluster contains a NRPS (GLNRPS4) and a PKS (GLPKS4) arranged in tandem, two cytochrome P450 monooxygenases, seven other modifying enzymes, and genes for L-homotyrosine biosynthesis, a component of the peptide core. Thus, the pneumocandin biosynthetic gene cluster is significantly more autonomous and organized than that of the recently characterized echinocandin B gene cluster. Disruption mutants of GLNRPS4 and GLPKS4 no longer produced the pneumocandins (A0 and B0), and the Δglnrps4 and Δglpks4 mutants lost antifungal activity against the human pathogenic fungus Candida albicans. In addition to pneumocandins, the G. lozoyensis genome encodes a rich repertoire of natural product-encoding genes including 24 PKSs, six NRPSs, five PKS-NRPS hybrids, two dimethylallyl tryptophan synthases, and 14 terpene synthases. Conclusions Characterization of the gene cluster provides a blueprint for engineering new pneumocandin derivatives with improved pharmacological properties. Whole genome estimation of the secondary metabolite-encoding genes from G. lozoyensis provides yet another example of the huge potential for drug discovery from natural products from the fungal kingdom. PMID:23688303

  9. BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation

    PubMed Central

    2011-01-01

    We present BioGraph, a data integration and data mining platform for the exploration and discovery of biomedical information. The platform offers prioritizations of putative disease genes, supported by functional hypotheses. We show that BioGraph can retrospectively confirm recently discovered disease genes and identify potential susceptibility genes, outperforming existing technologies, without requiring prior domain knowledge. Additionally, BioGraph allows for generic biomedical applications beyond gene discovery. BioGraph is accessible at http://www.biograph.be. PMID:21696594

  10. Discovery and Classification in Astronomy

    NASA Astrophysics Data System (ADS)

    Dick, Steven J.

    2012-01-01

    Three decades after Martin Harwit's pioneering Cosmic Discovery (1981), and following on the recent IAU Symposium "Accelerating the Rate of Astronomical Discovery,” we have revisited the problem of discovery in astronomy, emphasizing new classes of objects. 82 such classes have been identified and analyzed, including 22 in the realm of the planets, 36 in the realm of the stars, and 24 in the realm of the galaxies. We find an extended structure of discovery, consisting of detection, interpretation and understanding, each with its own nuances and a microstructure including conceptual, technological and social roles. This is true with a remarkable degree of consistency over the last 400 years of telescopic astronomy, ranging from Galileo's discovery of satellites, planetary rings and star clusters, to the discovery of quasars and pulsars. Telescopes have served as "engines of discovery” in several ways, ranging from telescope size and sensitivity (planetary nebulae and spiral galaxies), to specialized detectors (TNOs) and the opening of the electromagnetic spectrum for astronomy (pulsars, pulsar planets, and most active galaxies). A few classes (radiation belts, the solar wind and cosmic rays), were initially discovered without the telescope. Classification also plays an important role in discovery. While it might seem that classification marks the end of discovery, or a post-discovery phase, in fact it often marks the beginning, even a pre-discovery phase. Nowhere is this more clearly seen than in the classification of stellar spectra, long before dwarfs, giants and supergiants were known, or their evolutionary sequence recognized. Classification may also be part of a post-discovery phase, as in the MK system of stellar classification, constructed after the discovery of stellar luminosity classes. Some classes are declared rather than discovered, as in the case of gas and ice giant planets, and, infamously, Pluto as a dwarf planet.

  11. Drug discovery and development for rare genetic disorders.

    PubMed

    Sun, Wei; Zheng, Wei; Simeonov, Anton

    2017-09-01

    Approximately 7,000 rare diseases affect millions of individuals in the United States. Although rare diseases taken together have an enormous impact, there is a significant gap between basic research and clinical interventions. Opportunities now exist to accelerate drug development for the treatment of rare diseases. Disease foundations and research centers worldwide focus on better understanding rare disorders. Here, the state-of-the-art drug discovery strategies for small molecules and biological approaches for orphan diseases are reviewed. Rare diseases are usually genetic diseases; hence, employing pharmacogenetics to develop treatments and using whole genome sequencing to identify the etiologies for such diseases are appropriate strategies to exploit. Beginning with high throughput screening of small molecules, the benefits and challenges of target-based and phenotypic screens are discussed. Explanations and examples of drug repurposing are given; drug repurposing as an approach to quickly move programs to clinical trials is evaluated. Consideration is given to the category of biologics which include gene therapy, recombinant proteins, and autologous transplants. Disease models, including animal models and induced pluripotent stem cells (iPSCs) derived from patients, are surveyed. Finally, the role of biomarkers in drug discovery and development, as well as clinical trials, is elucidated. © 2017 Wiley Periodicals, Inc.

  12. Accelerated Discovery of Large Electrostrains in BaTiO3 -Based Piezoelectrics Using Active Learning.

    PubMed

    Yuan, Ruihao; Liu, Zhen; Balachandran, Prasanna V; Xue, Deqing; Zhou, Yumei; Ding, Xiangdong; Sun, Jun; Xue, Dezhen; Lookman, Turab

    2018-02-01

    A key challenge in guiding experiments toward materials with desired properties is to effectively navigate the vast search space comprising the chemistry and structure of allowed compounds. Here, it is shown how the use of machine learning coupled to optimization methods can accelerate the discovery of new Pb-free BaTiO 3 (BTO-) based piezoelectrics with large electrostrains. By experimentally comparing several design strategies, it is shown that the approach balancing the trade-off between exploration (using uncertainties) and exploitation (using only model predictions) gives the optimal criterion leading to the synthesis of the piezoelectric (Ba 0.84 Ca 0.16 )(Ti 0.90 Zr 0.07 Sn 0.03 )O 3 with the largest electrostrain of 0.23% in the BTO family. Using Landau theory and insights from density functional theory, it is uncovered that the observed large electrostrain is due to the presence of Sn, which allows for the ease of switching of tetragonal domains under an electric field. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Independent Gene Discovery and Testing

    ERIC Educational Resources Information Center

    Palsule, Vrushalee; Coric, Dijana; Delancy, Russell; Dunham, Heather; Melancon, Caleb; Thompson, Dennis; Toms, Jamie; White, Ashley; Shultz, Jeffry

    2010-01-01

    A clear understanding of basic gene structure is critical when teaching molecular genetics, the central dogma and the biological sciences. We sought to create a gene-based teaching project to improve students' understanding of gene structure and to integrate this into a research project that can be implemented by instructors at the secondary level…

  14. SNP discovery and development of genetic markers for mapping innate immune response genes in common carp (Cyprinus carpio).

    PubMed

    Kongchum, Pawapol; Palti, Yniv; Hallerman, Eric M; Hulata, Gideon; David, Lior

    2010-08-01

    Single nucleotide polymorphisms (SNPs) in immune response genes have been reported as markers for susceptibility to infectious diseases in human and livestock. A disease caused by cyprinid herpesvirus 3 (CyHV-3) is highly contagious and virulent in common carp (Cyprinus carpio). With the aim to develop molecular tools for breeding CyHV-3-resistant carp, we have amplified and sequenced 11 candidate genes for viral disease resistance including TLR2, TLR3, TLR4ba, TLR7, TLR9, TLR21, TLR22, MyD88, TRAF6, type I IFN and IL-1beta. For each gene, we initially cloned and sequenced PCR amplicons from 8 to 12 fish (2-3 fish per strain) from the SNP discovery panel. We then identified and evaluated putative SNPs for their polymorphisms in the SNP discovery panel and validated their usefulness for linkage analysis in a full-sib family using the SNaPshot method. Our sequencing results and phylogenetic analyses suggested that TLR3, TLR7 and MyD88 genes are duplicated in the common carp genome. We, therefore, developed locus-specific PCR primers and SNP genotyping assays for the duplicated loci. A total of 48 SNP markers were developed from PCR fragments of the 13 loci (7 single-locus and 3 duplicated genes). Thirty-nine markers were polymorphic with estimated minor allele frequencies of more than 0.1. The utility of the SNP markers was evaluated in one full-sib family and revealed that 20 markers from 9 loci segregated in a disomic and Mendelian pattern and would be useful for linkage analysis. Published by Elsevier Ltd.

  15. Automated Discovery of Long Intergenic RNAs Associated with Breast Cancer Progression

    DTIC Science & Technology

    2012-02-01

    manuscript in preparation), (2) development and publication of an algorithm for detecting gene fusions in RNA-Seq data [1], and (3) discovery of outlier long...subjected to de novo assembly algorithms to discover novel transcripts representing either unannotated genes or novel somatic mutations such as gene...fusions. To this end the P.I. developed and published a novel algorithm called ChimeraScan to facilitate the discovery and validation of gene

  16. Proceedings of the 2013 CINP Summit: Innovative Partnerships to Accelerate CNS Drug Discovery for Improved Patient Care

    PubMed Central

    Hongaard-Andersen, Peter; Moscicki, Richard A.; Sahakian, Barbara; Quirion, Rémi; Krishnan, K. Ranga Rama; Race, Tim

    2015-01-01

    Central nervous system (CNS) diseases and, in particular, mental health disorders, are becoming recognized as the health challenge of the 21st century. Currently, at least 10% of the global population is affected by a mental health disorder, a figure that is set to increase year on year. Meanwhile, the rate of development of new CNS drugs has not increased for many years, despite unprecedented levels of investment. In response to this state of affairs, the Collegium Internationale Neuro-Psychopharmacologicum (CINP) convened a summit to discuss ways to reverse this disturbing trend through new partnerships to accelerate CNS drug discovery. The objectives of the Summit were to explore the issues affecting the value chain (i.e. the chain of activities or stakeholders that a company engages in/with to deliver a product to market) in brain research, thereby gaining insights from key stakeholders and developing actions to address unmet needs; to identify achievable objectives to address the issues; to develop action plans to bring about measurable improvements across the value chain and accelerate CNS drug discovery; and finally, to communicate recommendations to governments, the research and development community, and other relevant stakeholders. Summit outputs include the following action plans, aligned to the pressure points within the brain research-drug development value chain: Code of conduct dealing with conflict of interest issues,Prevention, early diagnosis, and treatment,Linking science and regulation,Patient involvement in trial design, definition of endpoints, etc.,Novel trial design,Reproduction and confirmation of data,Update of intellectual property (IP) laws to facilitate repurposing and combination therapy (low priority),Large-scale, global patient registries,Editorials on nomenclature, biomarkers, and diagnostic tools, andPublic awareness, with brain disease advocates to attend G8 meetings and World Economic Forum (WEF) Annual meetings in Davos

  17. Proceedings of the 2013 CINP summit: innovative partnerships to accelerate CNS drug discovery for improved patient care.

    PubMed

    Phillips, Anthony George; Hongaard-Andersen, Peter; Moscicki, Richard A; Sahakian, Barbara; Quirion, Rémi; Krishnan, K Ranga Rama; Race, Tim

    2014-12-25

    Central nervous system (CNS) diseases and, in particular, mental health disorders, are becoming recognized as the health challenge of the 21(st) century. Currently, at least 10% of the global population is affected by a mental health disorder, a figure that is set to increase year on year. Meanwhile, the rate of development of new CNS drugs has not increased for many years, despite unprecedented levels of investment. In response to this state of affairs, the Collegium Internationale Neuro-Psychopharmacologicum (CINP) convened a summit to discuss ways to reverse this disturbing trend through new partnerships to accelerate CNS drug discovery. The objectives of the Summit were to explore the issues affecting the value chain (i.e. the chain of activities or stakeholders that a company engages in/with to deliver a product to market) in brain research, thereby gaining insights from key stakeholders and developing actions to address unmet needs; to identify achievable objectives to address the issues; to develop action plans to bring about measurable improvements across the value chain and accelerate CNS drug discovery; and finally, to communicate recommendations to governments, the research and development community, and other relevant stakeholders. Summit outputs include the following action plans, aligned to the pressure points within the brain research-drug development value chain: Code of conduct dealing with conflict of interest issues, Prevention, early diagnosis, and treatment, Linking science and regulation, Patient involvement in trial design, definition of endpoints, etc., Novel trial design, Reproduction and confirmation of data, Update of intellectual property (IP) laws to facilitate repurposing and combination therapy (low priority), Large-scale, global patient registries, Editorials on nomenclature, biomarkers, and diagnostic tools, and Public awareness, with brain disease advocates to attend G8 meetings and World Economic Forum (WEF) Annual meetings in

  18. Predicting future discoveries from current scientific literature.

    PubMed

    Petrič, Ingrid; Cestnik, Bojan

    2014-01-01

    Knowledge discovery in biomedicine is a time-consuming process starting from the basic research, through preclinical testing, towards possible clinical applications. Crossing of conceptual boundaries is often needed for groundbreaking biomedical research that generates highly inventive discoveries. We demonstrate the ability of a creative literature mining method to advance valuable new discoveries based on rare ideas from existing literature. When emerging ideas from scientific literature are put together as fragments of knowledge in a systematic way, they may lead to original, sometimes surprising, research findings. If enough scientific evidence is already published for the association of such findings, they can be considered as scientific hypotheses. In this chapter, we describe a method for the computer-aided generation of such hypotheses based on the existing scientific literature. Our literature-based discovery of NF-kappaB with its possible connections to autism was recently approved by scientific community, which confirms the ability of our literature mining methodology to accelerate future discoveries based on rare ideas from existing literature.

  19. Heuristic Bayesian segmentation for discovery of coexpressed genes within genomic regions.

    PubMed

    Pehkonen, Petri; Wong, Garry; Törönen, Petri

    2010-01-01

    Segmentation aims to separate homogeneous areas from the sequential data, and plays a central role in data mining. It has applications ranging from finance to molecular biology, where bioinformatics tasks such as genome data analysis are active application fields. In this paper, we present a novel application of segmentation in locating genomic regions with coexpressed genes. We aim at automated discovery of such regions without requirement for user-given parameters. In order to perform the segmentation within a reasonable time, we use heuristics. Most of the heuristic segmentation algorithms require some decision on the number of segments. This is usually accomplished by using asymptotic model selection methods like the Bayesian information criterion. Such methods are based on some simplification, which can limit their usage. In this paper, we propose a Bayesian model selection to choose the most proper result from heuristic segmentation. Our Bayesian model presents a simple prior for the segmentation solutions with various segment numbers and a modified Dirichlet prior for modeling multinomial data. We show with various artificial data sets in our benchmark system that our model selection criterion has the best overall performance. The application of our method in yeast cell-cycle gene expression data reveals potential active and passive regions of the genome.

  20. De Novo Transcriptomic Analysis of Peripheral Blood Lymphocytes from the Chinese Goose: Gene Discovery and Immune System Pathway Description

    PubMed Central

    Tariq, Mansoor; Chen, Rong; Yuan, Hongyu; Liu, Yanjie; Wu, Yanan; Wang, Junya; Xia, Chun

    2015-01-01

    Background The Chinese goose is one of the most economically important poultry birds and is a natural reservoir for many avian viruses. However, the nature and regulation of the innate and adaptive immune systems of this waterfowl species are not completely understood due to limited information on the goose genome. Recently, transcriptome sequencing technology was applied in the genomic studies focused on novel gene discovery. Thus, this study described the transcriptome of the goose peripheral blood lymphocytes to identify immunity relevant genes. Principal Findings De novo transcriptome assembly of the goose peripheral blood lymphocytes was sequenced by Illumina-Solexa technology. In total, 211,198 unigenes were assembled from the 69.36 million cleaned reads. The average length, N50 size and the maximum length of the assembled unigenes were 687 bp, 1,298 bp and 18,992 bp, respectively. A total of 36,854 unigenes showed similarity by BLAST search against the NCBI non-redundant (Nr) protein database. For functional classification, 163,161 unigenes were comprised of three Gene Ontology (Go) categories and 67 subcategories. A total of 15,334 unigenes were annotated into 25 eukaryotic orthologous groups (KOGs) categories. Kyoto Encyclopedia of Genes and Genomes (KEGG) database annotated 39,585 unigenes into six biological functional groups and 308 pathways. Among the 2,757 unigenes that participated in the 15 immune system KEGG pathways, 125 of the most important immune relevant genes were summarized and analyzed by STRING analysis to identify gene interactions and relationships. Moreover, 10 genes were confirmed by PCR and analyzed. Of these 125 unigenes, 109 unigenes, approximately 87%, were not previously identified in the goose. Conclusion This de novo transcriptome analysis could provide important Chinese goose sequence information and highlights the value of new gene discovery, pathways investigation and immune system gene identification, and comparison with

  1. GEM-TREND: a web tool for gene expression data mining toward relevant network discovery

    PubMed Central

    Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

    2009-01-01

    are dynamically linked to external data repositories. Conclusion GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at . PMID:19728865

  2. GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.

    PubMed

    Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

    2009-09-03

    linked to external data repositories. GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at http://cgs.pharm.kyoto-u.ac.jp/services/network.

  3. Plastid–Nuclear Interaction and Accelerated Coevolution in Plastid Ribosomal Genes in Geraniaceae

    PubMed Central

    Weng, Mao-Lun; Ruhlman, Tracey A.; Jansen, Robert K.

    2016-01-01

    Plastids and mitochondria have many protein complexes that include subunits encoded by organelle and nuclear genomes. In animal cells, compensatory evolution between mitochondrial and nuclear-encoded subunits was identified and the high mitochondrial mutation rates were hypothesized to drive compensatory evolution in nuclear genomes. In plant cells, compensatory evolution between plastid and nucleus has rarely been investigated in a phylogenetic framework. To investigate plastid–nuclear coevolution, we focused on plastid ribosomal protein genes that are encoded by plastid and nuclear genomes from 27 Geraniales species. Substitution rates were compared for five sets of genes representing plastid- and nuclear-encoded ribosomal subunit proteins targeted to the cytosol or the plastid as well as nonribosomal protein controls. We found that nonsynonymous substitution rates (dN) and the ratios of nonsynonymous to synonymous substitution rates (ω) were accelerated in both plastid- (CpRP) and nuclear-encoded subunits (NuCpRP) of the plastid ribosome relative to control sequences. Our analyses revealed strong signals of cytonuclear coevolution between plastid- and nuclear-encoded subunits, in which nonsynonymous substitutions in CpRP and NuCpRP tend to occur along the same branches in the Geraniaceae phylogeny. This coevolution pattern cannot be explained by physical interaction between amino acid residues. The forces driving accelerated coevolution varied with cellular compartment of the sequence. Increased ω in CpRP was mainly due to intensified positive selection whereas increased ω in NuCpRP was caused by relaxed purifying selection. In addition, the many indels identified in plastid rRNA genes in Geraniaceae may have contributed to changes in plastid subunits. PMID:27190001

  4. Plasma inverse transition acceleration

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Xie, Ming

    It can be proved fundamentally from the reciprocity theorem with which the electromagnetism is endowed that corresponding to each spontaneous process of radiation by a charged particle there is an inverse process which defines a unique acceleration mechanism, from Cherenkov radiation to inverse Cherenkov acceleration (ICA) [1], from Smith-Purcell radiation to inverse Smith-Purcell acceleration (ISPA) [2], and from undulator radiation to inverse undulator acceleration (IUA) [3]. There is no exception. Yet, for nearly 30 years after each of the aforementioned inverse processes has been clarified for laser acceleration, inverse transition acceleration (ITA), despite speculation [4], has remained the least understood,more » and above all, no practical implementation of ITA has been found, until now. Unlike all its counterparts in which phase synchronism is established one way or the other such that a particle can continuously gain energy from an acceleration wave, the ITA to be discussed here, termed plasma inverse transition acceleration (PITA), operates under fundamentally different principle. As a result, the discovery of PITA has been delayed for decades, waiting for a conceptual breakthrough in accelerator physics: the principle of alternating gradient acceleration [5, 6, 7, 8, 9, 10]. In fact, PITA was invented [7, 8] as one of several realizations of the new principle.« less

  5. A Systems-Genetics Approach and Data Mining Tool to Assist in the Discovery of Genes Underlying Complex Traits in Oryza sativa

    PubMed Central

    Ficklin, Stephen P.; Feltus, Frank Alex

    2013-01-01

    Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with

  6. Genome-Scale Discovery of Cell Wall Biosynthesis Genes in Populus (JGI Seventh Annual User Meeting 2012: Genomics of Energy and Environment)

    ScienceCinema

    Muchero, Wellington

    2018-01-15

    Wellington Muchero from Oak Ridge National Laboratory gives a talk titled "Discovery of Cell Wall Biosynthesis Genes in Populus" at the JGI 7th Annual Users Meeting: Genomics of Energy & Environment Meeting on March 22, 2012 in Walnut Creek, California.

  7. Natural Product Libraries to Accelerate the High Throughput Discovery of Therapeutic Leads±

    PubMed Central

    Johnson, Tyler A.; Sohn, Johann; Inman, Wayne D.; Estee, Samarkand A.; Loveridge, Steven T.; Vervoort, Helene C.; Tenney, Karen; Liu, Junke; Ang, Kenny Kean-Hooi; Ratnam, Joseline; Bray, Walter M.; Gassner, Nadine C.; Shen, Young Y.; Lokey, R. Scott; McKerrow, James H.; Boundy-Mills, Kyria; Nukanto, Arif; Kanti, Atit; Julistiono, Heddy; Kardono, Leonardus B. S.; Bjeldanes, Leonard F.; Crews, Phillip

    2011-01-01

    A high throughput (HT) paradigm generating LC-MS-UV-ELSD based natural product libraries to discover compounds with new bioactivities and or molecular structures is presented. To validate this methodology an extract of the Indo Pacific marine sponge Cacospongia mycofijiensis was evaluated using assays involving cytoskeletal profiling, tumor cell lines, and parasites. Twelve known compounds were identified including the latrunculins (1–4, 10), fijianolides (5, 8–9), mycothiazole (11), the aignopsanes (6–7) and sacrotride A (13). Compounds 1–4, 5, 8–11 exhibited bioactivity not previously reported against the parasite T. brucei, while 11 showed selectivity for lymphoma (U937) tumor cell lines. Four new compounds were also discovered including: aignopsanoic acid B (13), apo latrunculin T (14), 20-methoxy-fijianolide A (15) and aignopsane ketal (16). Compounds 13 and 16 represent important derivatives of the aignopsane class, 14 exhibited inhibition of T. brucei without disrupting microfilament assembly and 15 demonstrated modest microtubule stabilizing effects. The use of removable well plate libraries to avoid false positives from extracts enriched with only 1–2 major metabolites is also discussed. Overall, these results highlight the advantages of applying modern methods in natural products-based research to accelerate the HT discovery of therapeutic leads and or new molecular structures using LC-MS-UV-ELSD based libraries. PMID:22129061

  8. Exploiting Pre-rRNA Processing in Diamond Blackfan Anemia Gene Discovery and Diagnosis

    PubMed Central

    Farrar, Jason E.; Quarello, Paola; Fisher, Ross; O’Brien, Kelly A.; Aspesi, Anna; Parrella, Sara; Henson, Adrianna L.; Seidel, Nancy E.; Atsidaftos, Eva; Prakash, Supraja; Bari, Shahla; Garelli, Emanuela; Arceci, Robert J.; Dianzani, Irma; Ramenghi, Ugo; Vlachos, Adrianna; Lipton, Jeffrey M.; Bodine, David M.; Ellis, Steven R.

    2014-01-01

    Diamond Blackfan anemia (DBA), a syndrome primarily characterized by anemia and physical abnormalities, is one among a group of related inherited bone marrow failure syndromes (IBMFS) which share overlapping clinical features. Heterozygous mutations or single-copy deletions have been identified in 12 ribosomal protein genes in approximately 60% of DBA cases, with the genetic etiology unexplained in most remaining patients. Unlike many IBMFS, for which functional screening assays complement clinical and genetic findings, suspected DBA in the absence of typical alterations of the known genes must frequently be diagnosed after exclusion of other IBMFS. We report here a novel deletion in a child that presented such a diagnostic challenge and prompted development of a novel functional assay that can assist in the diagnosis of a significant fraction of patients with DBA. The ribosomal proteins affected in DBA are required for pre-rRNA processing, a process which can be interrogated to monitor steps in the maturation of 40S and 60S ribosomal subunits. In contrast to prior methods used to assess pre-rRNA processing, the assay reported here, based on capillary electrophoresis measurement of the maturation of rRNA in pre-60S ribosomal subunits, would be readily amenable to use in diagnostic laboratories. In addition to utility as a diagnostic tool, we applied this technique to gene discovery in DBA, resulting in the identification of RPL31 as a novel DBA gene. PMID:25042156

  9. NIH/NSF accelerate biomedical research innovations

    Cancer.gov

    A collaboration between the National Science Foundation and the National Institutes of Health will give NIH-funded researchers training to help them evaluate their scientific discoveries for commercial potential, with the aim of accelerating biomedical in

  10. Four disruptive strategies for removing drug discovery bottlenecks.

    PubMed

    Ekins, Sean; Waller, Chris L; Bradley, Mary P; Clark, Alex M; Williams, Antony J

    2013-03-01

    Drug discovery is shifting focus from industry to outside partners and, in the process, creating new bottlenecks. Technologies like high throughput screening (HTS) have moved to a larger number of academic and institutional laboratories in the USA, with little coordination or consideration of the outputs and creating a translational gap. Although there have been collaborative public-private partnerships in Europe to share pharmaceutical data, the USA has seemingly lagged behind and this may hold it back. Sharing precompetitive data and models may accelerate discovery across the board, while finding the best collaborators, mining social media and mobile approaches to open drug discovery should be evaluated in our efforts to remove drug discovery bottlenecks. We describe four strategies to rectify the current unsustainable situation. Copyright © 2012 Elsevier Ltd. All rights reserved.

  11. Accelerators for America's Future

    NASA Astrophysics Data System (ADS)

    Bai, Mei

    2016-03-01

    Particle accelerator, a powerful tool to energize beams of charged particles to a desired speed and energy, has been the working horse for investigating the fundamental structure of matter and fundermental laws of nature. Most known examples are the 2-mile long Stanford Linear Accelerator at SLAC, the high energy proton and anti-proton collider Tevatron at FermiLab, and Large Hadron Collider that is currently under operation at CERN. During the less than a century development of accelerator science and technology that led to a dazzling list of discoveries, particle accelerators have also found various applications beyond particle and nuclear physics research, and become an indispensible part of the economy. Today, one can find a particle accelerator at almost every corner of our lives, ranging from the x-ray machine at the airport security to radiation diagnostic and therapy in hospitals. This presentation will give a brief introduction of the applications of this powerful tool in fundermental research as well as in industry. Challenges in accelerator science and technology will also be briefly presented

  12. Application of industrial scale genomics to discovery of therapeutic targets in heart failure.

    PubMed

    Mehraban, F; Tomlinson, J E

    2001-12-01

    In recent years intense activity in both academic and industrial sectors has provided a wealth of information on the human genome with an associated impressive increase in the number of novel gene sequences deposited in sequence data repositories and patent applications. This genomic industrial revolution has transformed the way in which drug target discovery is now approached. In this article we discuss how various differential gene expression (DGE) technologies are being utilized for cardiovascular disease (CVD) drug target discovery. Other approaches such as sequencing cDNA from cardiovascular derived tissues and cells coupled with bioinformatic sequence analysis are used with the aim of identifying novel gene sequences that may be exploited towards target discovery. Additional leverage from gene sequence information is obtained through identification of polymorphisms that may confer disease susceptibility and/or affect drug responsiveness. Pharmacogenomic studies are described wherein gene expression-based techniques are used to evaluate drug response and/or efficacy. Industrial-scale genomics supports and addresses not only novel target gene discovery but also the burgeoning issues in pharmaceutical and clinical cardiovascular medicine relative to polymorphic gene responses.

  13. Reinventing the Accelerator for the High Energy Frontier

    ScienceCinema

    Rosenzweig, James [UCLA, Los Angeles, California, United States

    2017-12-09

    The history of discovery in high-energy physics has been intimately connected with progress in methods of accelerating particles for the past 75 years. This remains true today, as the post-LHC era in particle physics will require significant innovation and investment in a superconducting linear collider. The choice of the linear collider as the next-generation discovery machine, and the selection of superconducting technology has rather suddenly thrown promising competing techniques -- such as very large hadron colliders, muon colliders, and high-field, high frequency linear colliders -- into the background. We discuss the state of such conventional options, and the likelihood of their eventual success. We then follow with a much longer view: a survey of a new, burgeoning frontier in high energy accelerators, where intense lasers, charged particle beams, and plasmas are all combined in a cross-disciplinary effort to reinvent the accelerator from its fundamental principles on up.

  14. Plant-derived isoprenoid sweeteners: recent progress in biosynthetic gene discovery and perspectives on microbial production.

    PubMed

    Seki, Hikaru; Tamura, Keita; Muranaka, Toshiya

    2018-06-01

    Increased public awareness of negative health effects associated with excess sugar consumption has triggered increasing interest in plant-derived natural sweeteners. Steviol glycosides are a group of highly sweet diterpene glycosides contained in the leaves of stevia (Stevia rebaudiana). Mogrosides, extracted from monk fruit (Siraitia grosvenorii), are a group of cucurbitane-type triterpenoid glycosides. Glycyrrhizin is an oleanane-type triterpenoid glycoside derived from the underground parts of Glycyrrhiza plants (licorice). This review focuses on the natural isoprenoid sweetening agents steviol glycosides, mogrosides, and glycyrrhizin, and describes recent progress in gene discovery and elucidation of the catalytic functions of their biosynthetic enzymes. Recently, remarkable progress has been made in engineering the production of various plant-specialized metabolites in microbial hosts such as Saccharomyces cerevisiae via the introduction of biosynthetic enzyme genes. Perspectives on the microbial production of plant-derived natural sweeteners are also discussed.

  15. Systems Pharmacology-Based Discovery of Natural Products for Precision Oncology Through Targeting Cancer Mutated Genes.

    PubMed

    Fang, J; Cai, C; Wang, Q; Lin, P; Zhao, Z; Cheng, F

    2017-03-01

    Massive cancer genomics data have facilitated the rapid revolution of a novel oncology drug discovery paradigm through targeting clinically relevant driver genes or mutations for the development of precision oncology. Natural products with polypharmacological profiles have been demonstrated as promising agents for the development of novel cancer therapies. In this study, we developed an integrated systems pharmacology framework that facilitated identifying potential natural products that target mutated genes across 15 cancer types or subtypes in the realm of precision medicine. High performance was achieved for our systems pharmacology framework. In case studies, we computationally identified novel anticancer indications for several US Food and Drug Administration-approved or clinically investigational natural products (e.g., resveratrol, quercetin, genistein, and fisetin) through targeting significantly mutated genes in multiple cancer types. In summary, this study provides a powerful tool for the development of molecularly targeted cancer therapies through targeting the clinically actionable alterations by exploiting the systems pharmacology of natural products. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

  16. The Discovery of the Higgs Boson: America's Role

    ScienceCinema

    None

    2018-05-30

    The discovery of the Higgs boson was an international endeavor, involving thousands of physicists from across the world. While the accelerator at which the experimental work was done is located on Europe, the US supplied more physicists than any other single country. America had a very large role in the discovery of the Higgs particle and continues to have a leading role in the ongoing studies of the boson's properties. This video describes some of the contributions of U.S. universities and laboratories.

  17. Phenome-driven disease genetics prediction toward drug discovery.

    PubMed

    Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

    2015-06-15

    Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e(-4)) and 81.3% (P < e(-12)) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn's disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn's disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn's disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. nlp. edu/public/data/DMN © The Author 2015. Published by Oxford University Press.

  18. Phenome-driven disease genetics prediction toward drug discovery

    PubMed Central

    Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

    2015-01-01

    Motivation: Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. Results: To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e−4) and 81.3% (P < e−12) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn’s disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn’s disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn’s disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. Availability and implementation: nlp

  19. iCOSSY: An Online Tool for Context-Specific Subnetwork Discovery from Gene Expression Data

    PubMed Central

    Saha, Ashis; Jeon, Minji; Tan, Aik Choon; Kang, Jaewoo

    2015-01-01

    Pathway analyses help reveal underlying molecular mechanisms of complex biological phenotypes. Biologists tend to perform multiple pathway analyses on the same dataset, as there is no single answer. It is often inefficient for them to implement and/or install all the algorithms by themselves. Online tools can help the community in this regard. Here we present an online gene expression analytical tool called iCOSSY which implements a novel pathway-based COntext-specific Subnetwork discoverY (COSSY) algorithm. iCOSSY also includes a few modifications of COSSY to increase its reliability and interpretability. Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context). They can also interactively visualize the resulting subnetworks. iCOSSY is a web server that finds subnetworks that are differentially expressed in two phenotypes. Users can visualize the subnetworks to understand the biology of the difference. PMID:26147457

  20. Plastid-Nuclear Interaction and Accelerated Coevolution in Plastid Ribosomal Genes in Geraniaceae.

    PubMed

    Weng, Mao-Lun; Ruhlman, Tracey A; Jansen, Robert K

    2016-06-27

    Plastids and mitochondria have many protein complexes that include subunits encoded by organelle and nuclear genomes. In animal cells, compensatory evolution between mitochondrial and nuclear-encoded subunits was identified and the high mitochondrial mutation rates were hypothesized to drive compensatory evolution in nuclear genomes. In plant cells, compensatory evolution between plastid and nucleus has rarely been investigated in a phylogenetic framework. To investigate plastid-nuclear coevolution, we focused on plastid ribosomal protein genes that are encoded by plastid and nuclear genomes from 27 Geraniales species. Substitution rates were compared for five sets of genes representing plastid- and nuclear-encoded ribosomal subunit proteins targeted to the cytosol or the plastid as well as nonribosomal protein controls. We found that nonsynonymous substitution rates (dN) and the ratios of nonsynonymous to synonymous substitution rates (ω) were accelerated in both plastid- (CpRP) and nuclear-encoded subunits (NuCpRP) of the plastid ribosome relative to control sequences. Our analyses revealed strong signals of cytonuclear coevolution between plastid- and nuclear-encoded subunits, in which nonsynonymous substitutions in CpRP and NuCpRP tend to occur along the same branches in the Geraniaceae phylogeny. This coevolution pattern cannot be explained by physical interaction between amino acid residues. The forces driving accelerated coevolution varied with cellular compartment of the sequence. Increased ω in CpRP was mainly due to intensified positive selection whereas increased ω in NuCpRP was caused by relaxed purifying selection. In addition, the many indels identified in plastid rRNA genes in Geraniaceae may have contributed to changes in plastid subunits. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  1. Repurposed transcriptomic data facilitate discovery of innate immunity toll-like receptor (TLR) Genes across Lophotrochozoa.

    PubMed

    Halanych, Kenneth M; Kocot, Kevin M

    2014-10-01

    The growing volume of genomic data from across life represents opportunities for deriving valuable biological information from data that were initially collected for another purpose. Here, we use transcriptomes collected for phylogenomic studies to search for toll-like receptor (TLR) genes in poorly sampled lophotrochozoan clades (Annelida, Mollusca, Brachiopoda, Phoronida, and Entoprocta) and one ecdysozoan clade (Priapulida). TLR genes are involved in innate immunity across animals by recognizing potential microbial infection. They have an extracellular leucine-rich repeat (LRR) domain connected to a transmembrane domain and an intracellular toll/interleukin-1 receptor (TIR) domain. Consequently, these genes are important in initiating a signaling pathway to trigger defense. We found at least one TLR ortholog in all but two taxa examined, suggesting that a broad array of lophotrochozoans may have innate immune systems similar to those observed in vertebrates and arthropods. Comparison to the SMART database confirmed the presence of both the LRR and the TIR protein motifs characteristic of TLR genes. Because we looked at only one transcriptome per species, discovery of TLR genes was limited for most taxa. However, several TRL-like genes that vary in the number and placement of LRR domains were found in phoronids. Additionally, several contigs contained LRR domains but lacked TIR domains, suggesting they were not TLRs. Many of these LRR-containing contigs had other domains (e.g., immunoglobin) and are likely involved in innate immunity. © 2014 Marine Biological Laboratory.

  2. iSyTE 2.0: a database for expression-based gene discovery in the eye

    PubMed Central

    Kakrana, Atul; Yang, Andrian; Anand, Deepti; Djordjevic, Djordje; Ramachandruni, Deepti; Singh, Abhyudai; Huang, Hongzhan

    2018-01-01

    Abstract Although successful in identifying new cataract-linked genes, the previous version of the database iSyTE (integrated Systems Tool for Eye gene discovery) was based on expression information on just three mouse lens stages and was functionally limited to visualization by only UCSC-Genome Browser tracks. To increase its efficacy, here we provide an enhanced iSyTE version 2.0 (URL: http://research.bioinformatics.udel.edu/iSyTE) based on well-curated, comprehensive genome-level lens expression data as a one-stop portal for the effective visualization and analysis of candidate genes in lens development and disease. iSyTE 2.0 includes all publicly available lens Affymetrix and Illumina microarray datasets representing a broad range of embryonic and postnatal stages from wild-type and specific gene-perturbation mouse mutants with eye defects. Further, we developed a new user-friendly web interface for direct access and cogent visualization of the curated expression data, which supports convenient searches and a range of downstream analyses. The utility of these new iSyTE 2.0 features is illustrated through examples of established genes associated with lens development and pathobiology, which serve as tutorials for its application by the end-user. iSyTE 2.0 will facilitate the prioritization of eye development and disease-linked candidate genes in studies involving transcriptomics or next-generation sequencing data, linkage analysis and GWAS approaches. PMID:29036527

  3. Increased gibberellin contents contribute to accelerated growth and development of transgenic tobacco overexpressing a wheat ubiquitin gene.

    PubMed

    Wang, Guo-Kun; Zhang, Meng; Gong, Jiang-Feng; Guo, Qi-Fang; Feng, Ya-Nan; Wang, Wei

    2012-12-01

    Overexpressing TaUb2 promoted stem growth and resulted in early flowering in transgenic tobacco plants. Ubiquitin are involved in the production, metabolism and proper function of gibberellin. The ubiquitin-26S proteasome system (UPS), in which ubiquitin (Ub) functions as a marker, is a post-translational regulatory system that plays a prominent role in various biological processes. To investigate the impact of different Ub levels on plant growth and development, transgenic tobacco (Nicotiana tabacum L.) plants were engineered to express an Ub gene (TaUb2) from wheat (Triticum aestivum L.) under the control of cauliflower mosaic virus 35S promoter. Transgenic tobacco plants overexpressing TaUb2 demonstrated an accelerated growth rate at early stage and an early flowering phenotype in development. The preceding expression of MADS-box genes also corresponded to the accelerated developmental phenotypes of the transgenic tobacco plants compared to that of wild-type (WT). Total gibberellin (GA) and active GA contents in transgenic tobacco plants were higher than those in WT at the corresponding developmental stages, and some GA metabolism genes were upregulated. Treatment with GA(3) conferred a similarly accelerated grown rate in WT plants to that of transgenic tobacco plants, while growth was inhibited when transgenic tobacco plants were treated with a GA biosynthesis inhibitor. Thus, the results suggest that Ub are involved in the production, metabolism and proper function of GA, which is important in the regulation of plant growth and development.

  4. Applications of chemogenomic library screening in drug discovery.

    PubMed

    Jones, Lyn H; Bunnage, Mark E

    2017-04-01

    The allure of phenotypic screening, combined with the industry preference for target-based approaches, has prompted the development of innovative chemical biology technologies that facilitate the identification of new therapeutic targets for accelerated drug discovery. A chemogenomic library is a collection of selective small-molecule pharmacological agents, and a hit from such a set in a phenotypic screen suggests that the annotated target or targets of that pharmacological agent may be involved in perturbing the observable phenotype. In this Review, we describe opportunities for chemogenomic screening to considerably expedite the conversion of phenotypic screening projects into target-based drug discovery approaches. Other applications are explored, including drug repositioning, predictive toxicology and the discovery of novel pharmacological modalities.

  5. KENNEDY SPACE CENTER, FLA. - In the Orbiter Processing Facility, KSC employee Gene Peavler works in the wheel area on the orbiter Discovery. The vehicle has undergone Orbiter Major Modifications in the past year. Discovery is scheduled to fly on mission STS-121 to the International Space Station.

    NASA Image and Video Library

    2003-12-09

    KENNEDY SPACE CENTER, FLA. - In the Orbiter Processing Facility, KSC employee Gene Peavler works in the wheel area on the orbiter Discovery. The vehicle has undergone Orbiter Major Modifications in the past year. Discovery is scheduled to fly on mission STS-121 to the International Space Station.

  6. Discovery of novel drugs for promising targets.

    PubMed

    Martell, Robert E; Brooks, David G; Wang, Yan; Wilcoxen, Keith

    2013-09-01

    Once a promising drug target is identified, the steps to actually discover and optimize a drug are diverse and challenging. The goal of this study was to provide a road map to navigate drug discovery. Review general steps for drug discovery and provide illustrating references. A number of approaches are available to enhance and accelerate target identification and validation. Consideration of a variety of potential mechanisms of action of potential drugs can guide discovery efforts. The hit to lead stage may involve techniques such as high-throughput screening, fragment-based screening, and structure-based design, with informatics playing an ever-increasing role. Biologically relevant screening models are discussed, including cell lines, 3-dimensional culture, and in vivo screening. The process of enabling human studies for an investigational drug is also discussed. Drug discovery is a complex process that has significantly evolved in recent years. © 2013 Elsevier HS Journals, Inc. All rights reserved.

  7. Discovery of Tumor Suppressor Gene Function.

    ERIC Educational Resources Information Center

    Oppenheimer, Steven B.

    1995-01-01

    This is an update of a 1991 review on tumor suppressor genes written at a time when understanding of how the genes work was limited. A recent major breakthrough in the understanding of the function of tumor suppressor genes is discussed. (LZ)

  8. Saul Perlmutter, Distant Supernovae, Dark Energy, and the Accelerating

    Science.gov Websites

    , Distant Supernovae, Dark Energy, and the Accelerating Expansion of the Universe Resources with Additional nature of dark energy.'1 'The accelerating expansion means that the universe could expand forever until , in the distant future, it is cold and dark. The teams' discovery led to speculation that there is a

  9. The PhytoClust tool for metabolic gene clusters discovery in plant genomes

    PubMed Central

    Fuchs, Lisa-Maria

    2017-01-01

    Abstract The existence of Metabolic Gene Clusters (MGCs) in plant genomes has recently raised increased interest. Thus far, MGCs were commonly identified for pathways of specialized metabolism, mostly those associated with terpene type products. For efficient identification of novel MGCs, computational approaches are essential. Here, we present PhytoClust; a tool for the detection of candidate MGCs in plant genomes. The algorithm employs a collection of enzyme families related to plant specialized metabolism, translated into hidden Markov models, to mine given genome sequences for physically co-localized metabolic enzymes. Our tool accurately identifies previously characterized plant MGCs. An exhaustive search of 31 plant genomes detected 1232 and 5531 putative gene cluster types and candidates, respectively. Clustering analysis of putative MGCs types by species reflected plant taxonomy. Furthermore, enrichment analysis revealed taxa- and species-specific enrichment of certain enzyme families in MGCs. When operating through our web-interface, PhytoClust users can mine a genome either based on a list of known cluster types or by defining new cluster rules. Moreover, for selected plant species, the output can be complemented by co-expression analysis. Altogether, we envisage PhytoClust to enhance novel MGCs discovery which will in turn impact the exploration of plant metabolism. PMID:28486689

  10. Biomimicry as a basis for drug discovery.

    PubMed

    Kolb, V M

    1998-01-01

    Selected works are discussed which clearly demonstrate that mimicking various aspects of the process by which natural products evolved is becoming a powerful tool in contemporary drug discovery. Natural products are an established and rich source of drugs. The term "natural product" is often used synonymously with "secondary metabolite." Knowledge of genetics and molecular evolution helps us understand how biosynthesis of many classes of secondary metabolites evolved. One proposed hypothesis is termed "inventive evolution." It invokes duplication of genes, and mutation of the gene copies, among other genetic events. The modified duplicate genes, per se or in conjunction with other genetic events, may give rise to new enzymes, which, in turn, may generate new products, some of which may be selected for. Steps of the inventive evolution can be mimicked in several ways for purpose of drug discovery. For example, libraries of chemical compounds of any imaginable structure may be produced by combinatorial synthesis. Out of these libraries new active compounds can be selected. In another example, genetic system can be manipulated to produce modified natural products ("unnatural natural products"), from which new drugs can be selected. In some instances, similar natural products turn up in species that are not direct descendants of each other. This is presumably due to a horizontal gene transfer. The mechanism of this inter-species gene transfer can be mimicked in therapeutic gene delivery. Mimicking specifics or principles of chemical evolution including experimental and test-tube evolution also provides leads for new drug discovery.

  11. Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships.

    PubMed

    Manda, Prashanti; McCarthy, Fiona; Bridges, Susan M

    2013-10-01

    The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

  12. An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

    PubMed

    Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

    2003-11-01

    Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

  13. Jupiter's Auroras Acceleration Processes

    NASA Image and Video Library

    2017-09-06

    This image, created with data from Juno's Ultraviolet Imaging Spectrometer (UVS), marks the path of Juno's readings of Jupiter's auroras, highlighting the electron measurements that show the discovery of the so-called discrete auroral acceleration processes indicated by the "inverted Vs" in the lower panel (Figure 1). This signature points to powerful magnetic-field-aligned electric potentials that accelerate electrons toward the atmosphere to energies that are far greater than what drive the most intense aurora at Earth. Scientists are looking into why the same processes are not the main factor in Jupiter's most powerful auroras. https://photojournal.jpl.nasa.gov/catalog/PIA21937

  14. Antibiotic discovery throughout the Small World Initiative: A molecular strategy to identify biosynthetic gene clusters involved in antagonistic activity.

    PubMed

    Davis, Elizabeth; Sloan, Tyler; Aurelius, Krista; Barbour, Angela; Bodey, Elijah; Clark, Brigette; Dennis, Celeste; Drown, Rachel; Fleming, Megan; Humbert, Allison; Glasgo, Elizabeth; Kerns, Trent; Lingro, Kelly; McMillin, MacKenzie; Meyer, Aaron; Pope, Breanna; Stalevicz, April; Steffen, Brittney; Steindl, Austin; Williams, Carolyn; Wimberley, Carmen; Zenas, Robert; Butela, Kristen; Wildschutte, Hans

    2017-06-01

    The emergence of bacterial pathogens resistant to all known antibiotics is a global health crisis. Adding to this problem is that major pharmaceutical companies have shifted away from antibiotic discovery due to low profitability. As a result, the pipeline of new antibiotics is essentially dry and many bacteria now resist the effects of most commonly used drugs. To address this global health concern, citizen science through the Small World Initiative (SWI) was formed in 2012. As part of SWI, students isolate bacteria from their local environments, characterize the strains, and assay for antibiotic production. During the 2015 fall semester at Bowling Green State University, students isolated 77 soil-derived bacteria and genetically characterized strains using the 16S rRNA gene, identified strains exhibiting antagonistic activity, and performed an expanded SWI workflow using transposon mutagenesis to identify a biosynthetic gene cluster involved in toxigenic compound production. We identified one mutant with loss of antagonistic activity and through subsequent whole-genome sequencing and linker-mediated PCR identified a 24.9 kb biosynthetic gene locus likely involved in inhibitory activity in that mutant. Further assessment against human pathogens demonstrated the inhibition of Bacillus cereus, Listeria monocytogenes, and methicillin-resistant Staphylococcus aureus in the presence of this compound, thus supporting our molecular strategy as an effective research pipeline for SWI antibiotic discovery and genetic characterization. © 2017 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

  15. Emerging Concepts and Methodologies in Cancer Biomarker Discovery.

    PubMed

    Lu, Meixia; Zhang, Jinxiang; Zhang, Lanjing

    2017-01-01

    Cancer biomarker discovery is a critical part of cancer prevention and treatment. Despite the decades of effort, only a small number of cancer biomarkers have been identified for and validated in clinical settings. Conceptual and methodological breakthroughs may help accelerate the discovery of additional cancer biomarkers, particularly their use for diagnostics. In this review, we have attempted to review the emerging concepts in cancer biomarker discovery, including real-world evidence, open access data, and data paucity in rare or uncommon cancers. We have also summarized the recent methodological progress in cancer biomarker discovery, such as high-throughput sequencing, liquid biopsy, big data, artificial intelligence (AI), and deep learning and neural networks. Much attention has been given to the methodological details and comparison of the methodologies. Notably, these concepts and methodologies interact with each other and will likely lead to synergistic effects when carefully combined. Newer, more innovative concepts and methodologies are emerging as the current emerging ones became mainstream and widely applied to the field. Some future challenges are also discussed. This review contributes to the development of future theoretical frameworks and technologies in cancer biomarker discovery and will contribute to the discovery of more useful cancer biomarkers.

  16. Is the GAIN Act a turning point in new antibiotic discovery?

    PubMed

    Brown, Eric D

    2013-03-01

    The United States GAIN (Generating Antibiotic Incentives Now) Act is a call to action for new antibiotic discovery and development that arises from a ground swell of concern over declining activity in this therapeutic area in the pharmaceutical sector. The GAIN Act aims to provide economic incentives for antibiotic drug discovery in the form of market exclusivity and accelerated drug approval processes. The legislation comes on the heels of nearly two decades of failure using the tools of modern drug discovery to find new antibiotic drugs. The lessons of failure are examined herein as are the prospects for a renewed effort in antibiotic drug discovery and development stimulated by new investments in both the public and private sector.

  17. STS-114: Discovery Impromptu Briefing

    NASA Technical Reports Server (NTRS)

    2005-01-01

    Dr. Griffin, NASA Administrator, is accompanied by members of The U.S. House of Representatives in this STS-114 Discovery Impromptu briefing. The U.S. House of Representatives present include: Sherwood Boehlert, House Science Committee Chairman, Senator Hutchinson, Sheila Jackson, 18th Congressional District Texas, Al Green, 9th Congressional District, Representative Jim Davis, Florida, and Gene Green, 29th District, Texas. Griffin talks about the problem that occurred with the external fuel tank sensor of the Space Shuttle Discovery and the effort NASA is pursuing to track the problem, and identify the root cause. He answers questions from the news media about the next steps for the Space Shuttle Discovery, time frame for the launch, and activities for the astronauts for the next few days.

  18. Accelerated Evolution of the ASPM Gene Controlling Brain Size Begins Prior to Human Brain Expansion

    PubMed Central

    Solomon, Gregory; Gersch, William; Yoon, Young-Ho; Collura, Randall; Ruvolo, Maryellen; Barrett, J. Carl; Woods, C. Geoffrey; Walsh, Christopher A

    2004-01-01

    Primary microcephaly (MCPH) is a neurodevelopmental disorder characterized by global reduction in cerebral cortical volume. The microcephalic brain has a volume comparable to that of early hominids, raising the possibility that some MCPH genes may have been evolutionary targets in the expansion of the cerebral cortex in mammals and especially primates. Mutations in ASPM, which encodes the human homologue of a fly protein essential for spindle function, are the most common known cause of MCPH. Here we have isolated large genomic clones containing the complete ASPM gene, including promoter regions and introns, from chimpanzee, gorilla, orangutan, and rhesus macaque by transformation-associated recombination cloning in yeast. We have sequenced these clones and show that whereas much of the sequence of ASPM is substantially conserved among primates, specific segments are subject to high Ka/Ks ratios (nonsynonymous/synonymous DNA changes) consistent with strong positive selection for evolutionary change. The ASPM gene sequence shows accelerated evolution in the African hominoid clade, and this precedes hominid brain expansion by several million years. Gorilla and human lineages show particularly accelerated evolution in the IQ domain of ASPM. Moreover, ASPM regions under positive selection in primates are also the most highly diverged regions between primates and nonprimate mammals. We report the first direct application of TAR cloning technology to the study of human evolution. Our data suggest that evolutionary selection of specific segments of the ASPM sequence strongly relates to differences in cerebral cortical size. PMID:15045028

  19. SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate

    USGS Publications Warehouse

    Roffler, Gretchen H.; Amish, Stephen J.; Smith, Seth; Cosart, Ted F.; Kardos, Marty; Schwartz, Michael K.; Luikart, Gordon

    2016-01-01

    Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identify SNP markers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein-coding and nearby 5′ and 3′ untranslated regions of chosen candidate genes. Targeted sequences were taken from bighorn sheep (Ovis canadensis) exon capture data and directly from the domestic sheep genome (Ovis aries v. 3; oviAri3). The bighorn sheep sequences used in the Dall's sheep (Ovis dalli dalli) exon capture aligned to 2350 genes on the oviAri3 genome with an average of 2 exons each. We developed a microfluidic qPCR-based SNP chip to genotype 476 Dall's sheep from locations across their range and test for patterns of selection. Using multiple corroborating approaches (lositan and bayescan), we detected 28 SNP loci potentially under selection. We additionally identified candidate loci significantly associated with latitude, longitude, precipitation and temperature, suggesting local environmental adaptation. The three methods demonstrated consistent support for natural selection on nine genes with immune and disease-regulating functions (e.g. Ovar-DRA, APC, BATF2, MAGEB18), cell regulation signalling pathways (e.g. KRIT1, PI3K, ORRC3), and respiratory health (CYSLTR1). Characterizing adaptive allele distributions from novel genetic techniques will facilitate investigation of the influence of environmental variation on local adaptation of a northern alpine ungulate throughout its range. This research demonstrated the utility of exon capture for gene-targeted SNP discovery and subsequent SNP chip genotyping using low-quality samples in a nonmodel species.

  20. The PhytoClust tool for metabolic gene clusters discovery in plant genomes.

    PubMed

    Töpfer, Nadine; Fuchs, Lisa-Maria; Aharoni, Asaph

    2017-07-07

    The existence of Metabolic Gene Clusters (MGCs) in plant genomes has recently raised increased interest. Thus far, MGCs were commonly identified for pathways of specialized metabolism, mostly those associated with terpene type products. For efficient identification of novel MGCs, computational approaches are essential. Here, we present PhytoClust; a tool for the detection of candidate MGCs in plant genomes. The algorithm employs a collection of enzyme families related to plant specialized metabolism, translated into hidden Markov models, to mine given genome sequences for physically co-localized metabolic enzymes. Our tool accurately identifies previously characterized plant MGCs. An exhaustive search of 31 plant genomes detected 1232 and 5531 putative gene cluster types and candidates, respectively. Clustering analysis of putative MGCs types by species reflected plant taxonomy. Furthermore, enrichment analysis revealed taxa- and species-specific enrichment of certain enzyme families in MGCs. When operating through our web-interface, PhytoClust users can mine a genome either based on a list of known cluster types or by defining new cluster rules. Moreover, for selected plant species, the output can be complemented by co-expression analysis. Altogether, we envisage PhytoClust to enhance novel MGCs discovery which will in turn impact the exploration of plant metabolism. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  1. Discovery of Possible Gene Relationships through the Application of Self-Organizing Maps to DNA Microarray Databases

    PubMed Central

    Chavez-Alvarez, Rocio; Chavoya, Arturo; Mendez-Vazquez, Andres

    2014-01-01

    DNA microarrays and cell cycle synchronization experiments have made possible the study of the mechanisms of cell cycle regulation of Saccharomyces cerevisiae by simultaneously monitoring the expression levels of thousands of genes at specific time points. On the other hand, pattern recognition techniques can contribute to the analysis of such massive measurements, providing a model of gene expression level evolution through the cell cycle process. In this paper, we propose the use of one of such techniques –an unsupervised artificial neural network called a Self-Organizing Map (SOM)–which has been successfully applied to processes involving very noisy signals, classifying and organizing them, and assisting in the discovery of behavior patterns without requiring prior knowledge about the process under analysis. As a test bed for the use of SOMs in finding possible relationships among genes and their possible contribution in some biological processes, we selected 282 S. cerevisiae genes that have been shown through biological experiments to have an activity during the cell cycle. The expression level of these genes was analyzed in five of the most cited time series DNA microarray databases used in the study of the cell cycle of this organism. With the use of SOM, it was possible to find clusters of genes with similar behavior in the five databases along two cell cycles. This result suggested that some of these genes might be biologically related or might have a regulatory relationship, as was corroborated by comparing some of the clusters obtained with SOMs against a previously reported regulatory network that was generated using biological knowledge, such as protein-protein interactions, gene expression levels, metabolism dynamics, promoter binding, and modification, regulation and transport of proteins. The methodology described in this paper could be applied to the study of gene relationships of other biological processes in different organisms. PMID:24699245

  2. Is there a best strategy for drug discovery?--SMR Meeting. 13 March 2003, London, UK.

    PubMed

    Lunec, Anna

    2003-05-01

    This gathering of members from academia and industry allowed the sharing of ideas and techniques or the acceleration of drug discovery, and it was clear that there is a need for a more streamlined approach to discovery and development. Clearly, new technologies will aid in the discovery process, but the abilities of the human brain to analyze and interpret data should not be overlooked, as many discoveries have been made by chance or as the result of a hunch, and it would be a shame if the advent of artificial intelligence quashed that inquisitive aspect of drug discovery.

  3. In vitro manipulation of gene expression in larval Schistosoma: a model for postgenomic approaches in Trematoda

    PubMed Central

    YOSHINO, TIMOTHY P.; DINGUIRARD, NATHALIE; DE MORAES MOURÃO, MARINA

    2013-01-01

    SUMMARY With rapid developments in DNA and protein sequencing technologies, combined with powerful bioinformatics tools, a continued acceleration of gene identification in parasitic helminths is predicted, potentially leading to discovery of new drug and vaccine targets, enhanced diagnostics and insights into the complex biology underlying host-parasite interactions. For the schistosome blood flukes, with the recent completion of genome sequencing and comprehensive transcriptomic datasets, there has accumulated massive amounts of gene sequence data, for which, in the vast majority of cases, little is known about actual functions within the intact organism. In this review we attempt to bring together traditional in vitro cultivation approaches and recent emergent technologies of molecular genomics, transcriptomics and genetic manipulation to illustrate the considerable progress made in our understanding of trematode gene expression and function during development of the intramolluscan larval stages. Using several prominent trematode families (Schistosomatidae, Fasciolidae, Echinostomatidae), we have focused on the current status of in vitro larval isolation/cultivation as a source of valuable raw material supporting gene discovery efforts in model digeneans that include whole genome sequencing, transcript and protein expression profiling during larval development, and progress made in the in vitro manipulation of genes and their expression in larval trematodes using transgenic and RNA interference (RNAi) approaches. PMID:19961646

  4. Enhancing knowledge discovery from cancer genomics data with Galaxy

    PubMed Central

    Albuquerque, Marco A.; Grande, Bruno M.; Ritch, Elie J.; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K.; Shah, Sohrab P.; Boutros, Paul C.

    2017-01-01

    Abstract The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. PMID:28327945

  5. Enhancing knowledge discovery from cancer genomics data with Galaxy.

    PubMed

    Albuquerque, Marco A; Grande, Bruno M; Ritch, Elie J; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K; Shah, Sohrab P; Boutros, Paul C; Morin, Ryan D

    2017-05-01

    The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. © The Author 2017. Published by Oxford University Press.

  6. Biomedical Information Extraction: Mining Disease Associated Genes from Literature

    ERIC Educational Resources Information Center

    Huang, Zhong

    2014-01-01

    Disease associated gene discovery is a critical step to realize the future of personalized medicine. However empirical and clinical validation of disease associated genes are time consuming and expensive. In silico discovery of disease associated genes from literature is therefore becoming the first essential step for biomarker discovery to…

  7. Explaining the Supernova Data Without Accelerating Expansion

    NASA Astrophysics Data System (ADS)

    Stuckey, W. M.; McDevitt, T. J.; Silberstein, M.

    2012-10-01

    The 2011 Nobel Prize in Physics was awarded "for the discovery of the accelerating expansion of the universe through observations of distant supernovae." However, it is not the case that the type Ia supernova data necessitates accelerating expansion. Since we do not have a successful theory of quantum gravity, we should not assume general relativity (GR) will survive unification intact, especially on cosmological scales where tests are scarce. We provide a simple example of how GR cosmology may be modified to produce a decelerating Einstein-de Sitter cosmology (EdS) that accounts for the Union2 Compilation data as well as the accelerating ΛCDM (EdS plus a cosmological constant).

  8. Multiple Testing in the Context of Gene Discovery in Sickle Cell Disease Using Genome-Wide Association Studies.

    PubMed

    Kuo, Kevin H M

    2017-01-01

    The issue of multiple testing, also termed multiplicity, is ubiquitous in studies where multiple hypotheses are tested simultaneously. Genome-wide association study (GWAS), a type of genetic association study that has gained popularity in the past decade, is most susceptible to the issue of multiple testing. Different methodologies have been employed to address the issue of multiple testing in GWAS. The purpose of the review is to examine the methodologies employed in dealing with multiple testing in the context of gene discovery using GWAS in sickle cell disease complications.

  9. Prospects for Accelerator Technology

    NASA Astrophysics Data System (ADS)

    Todd, Alan

    2011-02-01

    Accelerator technology today is a greater than US$5 billion per annum business. Development of higher-performance technology with improved reliability that delivers reduced system size and life cycle cost is expected to significantly increase the total accelerator technology market and open up new application sales. Potential future directions are identified and pitfalls in new market penetration are considered. Both of the present big market segments, medical radiation therapy units and semiconductor ion implanters, are approaching the "maturity" phase of their product cycles, where incremental development rather than paradigm shifts is the norm, but they should continue to dominate commercial sales for some time. It is anticipated that large discovery-science accelerators will continue to provide a specialty market beset by the unpredictable cycles resulting from the scale of the projects themselves, coupled with external political and economic drivers. Although fraught with differing market entry difficulties, the security and environmental markets, together with new, as yet unrealized, industrial material processing applications, are expected to provide the bulk of future commercial accelerator technology growth.

  10. Antisense oligonucleotide technologies in drug discovery.

    PubMed

    Aboul-Fadl, Tarek

    2006-09-01

    The principle of antisense oligonucleotide (AS-OD) technologies is based on the specific inhibition of unwanted gene expression by blocking mRNA activity. It has long appeared to be an ideal strategy to leverage new genomic knowledge for drug discovery and development. In recent years, AS-OD technologies have been widely used as potent and promising tools for this purpose. There is a rapid increase in the number of antisense molecules progressing in clinical trials. AS-OD technologies provide a simple and efficient approach for drug discovery and development and are expected to become a reality in the near future. This editorial describes the established and emerging AS-OD technologies in drug discovery.

  11. X-ray Observations of Cosmic Ray Acceleration

    NASA Technical Reports Server (NTRS)

    Petre, Robert

    2012-01-01

    Since the discovery of cosmic rays, detection of their sources has remained elusive. A major breakthrough has come through the identification of synchrotron X-rays from the shocks of supernova remnants through imaging and spectroscopic observations by the most recent generation of X-ray observatories. This radiation is most likely produced by electrons accelerated to relativistic energy, and thus has offered the first, albeit indirect, observational evidence that diffusive shock acceleration in supernova remnants produces cosmic rays to TeV energies, possibly as high as the "knee" in the cosmic ray spectrum. X-ray observations have provided information about the maximum energy to which these shOCks accelerate electrons, as well as indirect evidence of proton acceleration. Shock morphologies measured in X-rays have indicated that a substantial fraction of the shock energy can be diverted into particle acceleration. This presentation will summarize what we have learned about cosmic ray acceleration from X-ray observations of supernova remnants over the past two decades.

  12. CNS Anticancer Drug Discovery and Development Conference White Paper

    PubMed Central

    Levin, Victor A.; Tonge, Peter J.; Gallo, James M.; Birtwistle, Marc R.; Dar, Arvin C.; Iavarone, Antonio; Paddison, Patrick J.; Heffron, Timothy P.; Elmquist, William F.; Lachowicz, Jean E.; Johnson, Ted W.; White, Forest M.; Sul, Joohee; Smith, Quentin R.; Shen, Wang; Sarkaria, Jann N.; Samala, Ramakrishna; Wen, Patrick Y.; Berry, Donald A.; Petter, Russell C.

    2015-01-01

    Following the first CNS Anticancer Drug Discovery and Development Conference, the speakers from the first 4 sessions and organizers of the conference created this White Paper hoping to stimulate more and better CNS anticancer drug discovery and development. The first part of the White Paper reviews, comments, and, in some cases, expands on the 4 session areas critical to new drug development: pharmacological challenges, recent drug approaches, drug targets and discovery, and clinical paths. Following this concise review of the science and clinical aspects of new CNS anticancer drug discovery and development, we discuss, under the rubric “Accelerating Drug Discovery and Development for Brain Tumors,” further reasons why the pharmaceutical industry and academia have failed to develop new anticancer drugs for CNS malignancies and what it will take to change the current status quo and develop the drugs so desperately needed by our patients with malignant CNS tumors. While this White Paper is not a formal roadmap to that end, it should be an educational guide to clinicians and scientists to help move a stagnant field forward. PMID:26403167

  13. Future HEP Accelerators: The US Perspective

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bhat, Pushpalatha; Shiltsev, Vladimir

    2015-11-02

    Accelerator technology has advanced tremendously since the introduction of accelerators in the 1930s, and particle accelerators have become indispensable instruments in high energy physics (HEP) research to probe Nature at smaller and smaller distances. At present, accelerator facilities can be classified into Energy Frontier colliders that enable direct discoveries and studies of high mass scale particles and Intensity Frontier accelerators for exploration of extremely rare processes, usually at relatively low energies. The near term strategies of the global energy frontier particle physics community are centered on fully exploiting the physics potential of the Large Hadron Collider (LHC) at CERN throughmore » its high-luminosity upgrade (HL-LHC), while the intensity frontier HEP research is focused on studies of neutrinos at the MW-scale beam power accelerator facilities, such as Fermilab Main Injector with the planned PIP-II SRF linac project. A number of next generation accelerator facilities have been proposed and are currently under consideration for the medium- and long-term future programs of accelerator-based HEP research. In this paper, we briefly review the post-LHC energy frontier options, both for lepton and hadron colliders in various regions of the world, as well as possible future intensity frontier accelerator facilities.« less

  14. Biomedical discovery acceleration, with applications to craniofacial development.

    PubMed

    Leach, Sonia M; Tipney, Hannah; Feng, Weiguo; Baumgartner, William A; Kasliwal, Priyanka; Schuyler, Ronald P; Williams, Trevor; Spritz, Richard A; Hunter, Lawrence

    2009-03-01

    The profusion of high-throughput instruments and the explosion of new results in the scientific literature, particularly in molecular biomedicine, is both a blessing and a curse to the bench researcher. Even knowledgeable and experienced scientists can benefit from computational tools that help navigate this vast and rapidly evolving terrain. In this paper, we describe a novel computational approach to this challenge, a knowledge-based system that combines reading, reasoning, and reporting methods to facilitate analysis of experimental data. Reading methods extract information from external resources, either by parsing structured data or using biomedical language processing to extract information from unstructured data, and track knowledge provenance. Reasoning methods enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. Reasoning is also used to combine all sources into a knowledge network that represents the integration of all sorts of relationships between a pair of genes, and to calculate a combined reliability score. Reporting methods combine the knowledge network with a congruent network constructed from experimental data and visualize the combined network in a tool that facilitates the knowledge-based analysis of that data. An implementation of this approach, called the Hanalyzer, is demonstrated on a large-scale gene expression array dataset relevant to craniofacial development. The use of the tool was critical in the creation of hypotheses regarding the roles of four genes never previously characterized as involved in craniofacial development; each of these hypotheses was validated by further experimental work.

  15. DiscoverySpace: an interactive data analysis application

    PubMed Central

    Robertson, Neil; Oveisi-Fordorei, Mehrdad; Zuyderduyn, Scott D; Varhol, Richard J; Fjell, Christopher; Marra, Marco; Jones, Steven; Siddiqui, Asim

    2007-01-01

    DiscoverySpace is a graphical application for bioinformatics data analysis. Users can seamlessly traverse references between biological databases and draw together annotations in an intuitive tabular interface. Datasets can be compared using a suite of novel tools to aid in the identification of significant patterns. DiscoverySpace is of broad utility and its particular strength is in the analysis of serial analysis of gene expression (SAGE) data. The application is freely available online. PMID:17210078

  16. Gene/QTL discovery for Anthracnose in common bean (Phaseolus vulgaris L.) from North-western Himalayas

    PubMed Central

    Choudhary, Neeraj; Bawa, Vanya; Paliwal, Rajneesh; Singh, Bikram; Bhat, Mohd. Ashraf; Mir, Javid Iqbal; Gupta, Moni; Sofi, Parvaze A.; Thudi, Mahendar; Varshney, Rajeev K.

    2018-01-01

    Common bean (Phaseolus vulgaris L.) is one of the most important grain legume crops in the world. The beans grown in north-western Himalayas possess huge diversity for seed color, shape and size but are mostly susceptible to Anthracnose disease caused by seed born fungus Colletotrichum lindemuthianum. Dozens of QTLs/genes have been already identified for this disease in common bean world-wide. However, this is the first report of gene/QTL discovery for Anthracnose using bean germplasm from north-western Himalayas of state Jammu & Kashmir, India. A core set of 96 bean lines comprising 54 indigenous local landraces from 11 hot-spots and 42 exotic lines from 10 different countries were phenotyped at two locations (SKUAST-Jammu and Bhaderwah, Jammu) for Anthracnose resistance. The core set was also genotyped with genome-wide (91) random and trait linked SSR markers. The study of marker-trait associations (MTAs) led to the identification of 10 QTLs/genes for Anthracnose resistance. Among the 10 QTLs/genes identified, two MTAs are stable (BM45 & BM211), two MTAs (PVctt1 & BM211) are major explaining more than 20% phenotypic variation for Anthracnose and one MTA (BM211) is both stable and major. Six (06) genomic regions are reported for the first time, while as four (04) genomic regions validated the already known QTL/gene regions/clusters for Anthracnose. The major, stable and validated markers reported during the present study associated with Anthracnose resistance will prove useful in common bean molecular breeding programs aimed at enhancing Anthracnose resistance of local bean landraces grown in north-western Himalayas of state Jammu and Kashmir. PMID:29389971

  17. De novo transcriptome sequencing and discovery of genes related to copper tolerance in Paeonia ostii.

    PubMed

    Wang, Yanjie; Dong, Chunlan; Xue, Zeyun; Jin, Qijiang; Xu, Yingchun

    2016-01-15

    Paeonia ostii, an important ornamental and medicinal plant, grows normally on copper (Cu) mines with widespread Cu contamination of soils, and it has the ability to lower Cu contents in the Cu-contaminated soils. However, very little molecular information concerned with Cu resistance of P. ostii is available. In this study, high-throughput de novo transcriptome sequencing was carried out for P. ostii with and without Cu treatment using Illumina HiSeq 2000 platform. A total of 77,704 All-unigenes were obtained with a mean length of 710 bp. Of these unigenes, 47,461 were annotated with public databases based on sequence similarities. Comparative transcript profiling allowed the discovery of 4324 differentially expressed genes (DEGs), with 2207 up-regulated and 2117 down-regulated unigenes in Cu-treated library as compared to the control counterpart. Based on these DEGs, Gene Ontology (GO) enrichment analysis indicated Cu stress-relevant terms, such as 'membrane' and 'antioxidant activity'. Meanwhile, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis uncovered some important pathways, including 'biosynthesis of secondary metabolites' and 'metabolic pathways'. In addition, expression patterns of 12 selected DEGs derived from quantitative real-time polymerase chain reaction (qRT-PCR) were consistent with their transcript abundance changes obtained by transcriptomic analyses, suggesting that all the 12 genes were authentically involved in Cu tolerance in P. ostii. This is the first report to identify genes related to Cu stress responses in P. ostii, which could offer valuable information on the molecular mechanisms of Cu resistance, and provide a basis for further genomics research on this and related ornamental species for phytoremediation. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. Gene/QTL discovery for Anthracnose in common bean (Phaseolus vulgaris L.) from North-western Himalayas.

    PubMed

    Choudhary, Neeraj; Bawa, Vanya; Paliwal, Rajneesh; Singh, Bikram; Bhat, Mohd Ashraf; Mir, Javid Iqbal; Gupta, Moni; Sofi, Parvaze A; Thudi, Mahendar; Varshney, Rajeev K; Mir, Reyazul Rouf

    2018-01-01

    Common bean (Phaseolus vulgaris L.) is one of the most important grain legume crops in the world. The beans grown in north-western Himalayas possess huge diversity for seed color, shape and size but are mostly susceptible to Anthracnose disease caused by seed born fungus Colletotrichum lindemuthianum. Dozens of QTLs/genes have been already identified for this disease in common bean world-wide. However, this is the first report of gene/QTL discovery for Anthracnose using bean germplasm from north-western Himalayas of state Jammu & Kashmir, India. A core set of 96 bean lines comprising 54 indigenous local landraces from 11 hot-spots and 42 exotic lines from 10 different countries were phenotyped at two locations (SKUAST-Jammu and Bhaderwah, Jammu) for Anthracnose resistance. The core set was also genotyped with genome-wide (91) random and trait linked SSR markers. The study of marker-trait associations (MTAs) led to the identification of 10 QTLs/genes for Anthracnose resistance. Among the 10 QTLs/genes identified, two MTAs are stable (BM45 & BM211), two MTAs (PVctt1 & BM211) are major explaining more than 20% phenotypic variation for Anthracnose and one MTA (BM211) is both stable and major. Six (06) genomic regions are reported for the first time, while as four (04) genomic regions validated the already known QTL/gene regions/clusters for Anthracnose. The major, stable and validated markers reported during the present study associated with Anthracnose resistance will prove useful in common bean molecular breeding programs aimed at enhancing Anthracnose resistance of local bean landraces grown in north-western Himalayas of state Jammu and Kashmir.

  19. Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data

    PubMed Central

    Hassane, Duane C.; Guzman, Monica L.; Corbett, Cheryl; Li, Xiaojie; Abboud, Ramzi; Young, Fay; Liesveld, Jane L.; Carroll, Martin

    2008-01-01

    Increasing evidence indicates that malignant stem cells are important for the pathogenesis of acute myelogenous leukemia (AML) and represent a reservoir of cells that drive the development of AML and relapse. Therefore, new treatment regimens are necessary to prevent relapse and improve therapeutic outcomes. Previous studies have shown that the sesquiterpene lactone, parthenolide (PTL), ablates bulk, progenitor, and stem AML cells while causing no appreciable toxicity to normal hematopoietic cells. Thus, PTL must evoke cellular responses capable of mediating AML selective cell death. Given recent advances in chemical genomics such as gene expression-based high-throughput screening (GE-HTS) and the Connectivity Map, we hypothesized that the gene expression signature resulting from treatment of primary AML with PTL could be used to search for similar signatures in publicly available gene expression profiles deposited into the Gene Expression Omnibus (GEO). We therefore devised a broad in silico screen of the GEO database using the PTL gene expression signature as a template and discovered 2 new agents, celastrol and 4-hydroxy-2-nonenal, that effectively eradicate AML at the bulk, progenitor, and stem cell level. These findings suggest the use of multicenter collections of high-throughput data to facilitate discovery of leukemia drugs and drug targets. PMID:18305216

  20. Putative Independent Evolutionary Reversals from Genotypic to Temperature-Dependent Sex Determination are Associated with Accelerated Evolution of Sex-Determining Genes in Turtles.

    PubMed

    Literman, Robert; Burrett, Alexandria; Bista, Basanta; Valenzuela, Nicole

    2018-01-01

    The evolutionary lability of sex-determining mechanisms across the tree of life is well recognized, yet the extent of molecular changes that accompany these repeated transitions remain obscure. Most turtles retain the ancestral temperature-dependent sex determination (TSD) from which multiple transitions to genotypic sex determination (GSD) occurred independently, and two contrasting hypotheses posit the existence or absence of reversals back to TSD. Here we examined the molecular evolution of the coding regions of a set of gene regulators involved in gonadal development in turtles and several other vertebrates. We found slower molecular evolution in turtles and crocodilians compared to other vertebrates, but an acceleration in Trionychia turtles and at some phylogenetic branches demarcating major taxonomic diversification events. Of all gene classes examined, hormone signaling genes, and Srd5a1 in particular, evolve faster in many lineages and especially in turtles. Our data show that sex-linked genes do not follow a ubiquitous nor uniform pattern of molecular evolution. We then evaluated turtle nucleotide and protein evolution under two evolutionary hypotheses with or without GSD-to-TSD reversals, and found that when GSD-to-TSD reversals are considered, all transitional branches irrespective of direction, exhibit accelerated molecular evolution of nucleotide sequences, while GSD-to-TSD transitional branches also show acceleration in protein evolution. Significant changes in predicted secondary structure that may affect protein function were identified in three genes that exhibited hastened evolution in turtles compared to other vertebrates or in transitional versus non-transitional branches within turtles, rendering them candidates for a key role during SDM evolution in turtles.

  1. Cell and small animal models for phenotypic drug discovery.

    PubMed

    Szabo, Mihaly; Svensson Akusjärvi, Sara; Saxena, Ankur; Liu, Jianping; Chandrasekar, Gayathri; Kitambi, Satish S

    2017-01-01

    The phenotype-based drug discovery (PDD) approach is re-emerging as an alternative platform for drug discovery. This review provides an overview of the various model systems and technical advances in imaging and image analyses that strengthen the PDD platform. In PDD screens, compounds of therapeutic value are identified based on the phenotypic perturbations produced irrespective of target(s) or mechanism of action. In this article, examples of phenotypic changes that can be detected and quantified with relative ease in a cell-based setup are discussed. In addition, a higher order of PDD screening setup using small animal models is also explored. As PDD screens integrate physiology and multiple signaling mechanisms during the screening process, the identified hits have higher biomedical applicability. Taken together, this review highlights the advantages gained by adopting a PDD approach in drug discovery. Such a PDD platform can complement target-based systems that are currently in practice to accelerate drug discovery.

  2. Simple animal models for amyotrophic lateral sclerosis drug discovery.

    PubMed

    Patten, Shunmoogum A; Parker, J Alex; Wen, Xiao-Yan; Drapeau, Pierre

    2016-08-01

    Simple animal models have enabled great progress in uncovering the disease mechanisms of amyotrophic lateral sclerosis (ALS) and are helping in the selection of therapeutic compounds through chemical genetic approaches. Within this article, the authors provide a concise overview of simple model organisms, C. elegans, Drosophila and zebrafish, which have been employed to study ALS and discuss their value to ALS drug discovery. In particular, the authors focus on innovative chemical screens that have established simple organisms as important models for ALS drug discovery. There are several advantages of using simple animal model organisms to accelerate drug discovery for ALS. It is the authors' particular belief that the amenability of simple animal models to various genetic manipulations, the availability of a wide range of transgenic strains for labelling motoneurons and other cell types, combined with live imaging and chemical screens should allow for new detailed studies elucidating early pathological processes in ALS and subsequent drug and target discovery.

  3. The discovery and measurements of a Higgs boson.

    PubMed

    Gianotti, F; Virdee, T S

    2015-01-13

    In July 2012, the ATLAS and CMS collaborations at CERN's Large Hadron Collider announced the discovery of a Higgs-like boson, a new heavy particle at a mass more than 130 times the mass of a proton. Since then, further data have revealed its properties to be strikingly similar to those of the Standard Model Higgs boson, a particle expected from the mechanism introduced almost 50 years ago by six theoreticians including British physicists Peter Higgs from Edinburgh University and Tom Kibble from Imperial College London. The discovery is the culmination of a truly remarkable scientific journey and undoubtedly the most significant scientific discovery of the twenty-first century so far. Its experimental confirmation turned out to be a monumental task requiring the creation of an accelerator and experiments of unprecedented capability and complexity, designed to discern the signatures that correspond to the Higgs boson. Thousands of scientists and engineers, in each of the ATLAS and CMS teams, came together from all four corners of the world to make this massive discovery possible.

  4. High-density genetic map using whole-genome resequencing for fine mapping and candidate gene discovery for disease resistance in peanut.

    PubMed

    Agarwal, Gaurav; Clevenger, Josh; Pandey, Manish K; Wang, Hui; Shasidhar, Yaduru; Chu, Ye; Fountain, Jake C; Choudhary, Divya; Culbreath, Albert K; Liu, Xin; Huang, Guodong; Wang, Xingjun; Deshmukh, Rupesh; Holbrook, C Corley; Bertioli, David J; Ozias-Akins, Peggy; Jackson, Scott A; Varshney, Rajeev K; Guo, Baozhu

    2018-04-10

    Whole-genome resequencing (WGRS) of mapping populations has facilitated development of high-density genetic maps essential for fine mapping and candidate gene discovery for traits of interest in crop species. Leaf spots, including early leaf spot (ELS) and late leaf spot (LLS), and Tomato spotted wilt virus (TSWV) are devastating diseases in peanut causing significant yield loss. We generated WGRS data on a recombinant inbred line population, developed a SNP-based high-density genetic map, and conducted fine mapping, candidate gene discovery and marker validation for ELS, LLS and TSWV. The first sequence-based high-density map was constructed with 8869 SNPs assigned to 20 linkage groups, representing 20 chromosomes, for the 'T' population (Tifrunner × GT-C20) with a map length of 3120 cM and an average distance of 1.45 cM. The quantitative trait locus (QTL) analysis using high-density genetic map and multiple season phenotyping data identified 35 main-effect QTLs with phenotypic variation explained (PVE) from 6.32% to 47.63%. Among major-effect QTLs mapped, there were two QTLs for ELS on B05 with 47.42% PVE and B03 with 47.38% PVE, two QTLs for LLS on A05 with 47.63% and B03 with 34.03% PVE and one QTL for TSWV on B09 with 40.71% PVE. The epistasis and environment interaction analyses identified significant environmental effects on these traits. The identified QTL regions had disease resistance genes including R-genes and transcription factors. KASP markers were developed for major QTLs and validated in the population and are ready for further deployment in genomics-assisted breeding in peanut. © 2018 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

  5. Proposal for an Accelerator R&D User Facility at Fermilab's Advanced Superconducting Test Accelerator (ASTA)

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Church, M.; Edwards, H.; Harms, E.

    2013-10-01

    Fermilab is the nation’s particle physics laboratory, supported by the DOE Office of High Energy Physics (OHEP). Fermilab is a world leader in accelerators, with a demonstrated track-record— spanning four decades—of excellence in accelerator science and technology. We describe the significant opportunity to complete, in a highly leveraged manner, a unique accelerator research facility that supports the broad strategic goals in accelerator science and technology within the OHEP. While the US accelerator-based HEP program is oriented toward the Intensity Frontier, which requires modern superconducting linear accelerators and advanced highintensity storage rings, there are no accelerator test facilities that support themore » accelerator science of the Intensity Frontier. Further, nearly all proposed future accelerators for Discovery Science will rely on superconducting radiofrequency (SRF) acceleration, yet there are no dedicated test facilities to study SRF capabilities for beam acceleration and manipulation in prototypic conditions. Finally, there are a wide range of experiments and research programs beyond particle physics that require the unique beam parameters that will only be available at Fermilab’s Advanced Superconducting Test Accelerator (ASTA). To address these needs we submit this proposal for an Accelerator R&D User Facility at ASTA. The ASTA program is based on the capability provided by an SRF linac (which provides electron beams from 50 MeV to nearly 1 GeV) and a small storage ring (with the ability to store either electrons or protons) to enable a broad range of beam-based experiments to study fundamental limitations to beam intensity and to develop transformative approaches to particle-beam generation, acceleration and manipulation which cannot be done elsewhere. It will also establish a unique resource for R&D towards Energy Frontier facilities and a test-bed for SRF accelerators and high brightness beam applications in support of the

  6. Computational functional genomics-based approaches in analgesic drug discovery and repurposing.

    PubMed

    Lippmann, Catharina; Kringel, Dario; Ultsch, Alfred; Lötsch, Jörn

    2018-06-01

    Persistent pain is a major healthcare problem affecting a fifth of adults worldwide with still limited treatment options. The search for new analgesics increasingly includes the novel research area of functional genomics, which combines data derived from various processes related to DNA sequence, gene expression or protein function and uses advanced methods of data mining and knowledge discovery with the goal of understanding the relationship between the genome and the phenotype. Its use in drug discovery and repurposing for analgesic indications has so far been performed using knowledge discovery in gene function and drug target-related databases; next-generation sequencing; and functional proteomics-based approaches. Here, we discuss recent efforts in functional genomics-based approaches to analgesic drug discovery and repurposing and highlight the potential of computational functional genomics in this field including a demonstration of the workflow using a novel R library 'dbtORA'.

  7. Discovery of Host Factors and Pathways Utilized in Hantaviral Infection

    DTIC Science & Technology

    2016-09-01

    AWARD NUMBER: W81XWH-14-1-0204 TITLE: Discovery of Host Factors and Pathways Utilized in Hantaviral Infection PRINCIPAL INVESTIGATOR: Paul...Aug 2016 4. TITLE AND SUBTITLE Discovery of Host Factors and Pathways Utilized in Hantaviral Infection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c...after significance values were calculated and corrected for false discovery rate. The top hit is ATP6V0A1, a gene encoding a subunit of a vacuolar

  8. Semiconductor technology in protein kinase research and drug discovery: sensing a revolution.

    PubMed

    Bhalla, Nikhil; Di Lorenzo, Mirella; Estrela, Pedro; Pula, Giordano

    2017-02-01

    Since the discovery of protein kinase activity in 1954, close to 600 kinases have been discovered that have crucial roles in cell physiology. In several pathological conditions, aberrant protein kinase activity leads to abnormal cell and tissue physiology. Therefore, protein kinase inhibitors are investigated as potential treatments for several diseases, including dementia, diabetes, cancer and autoimmune and cardiovascular disease. Modern semiconductor technology has recently been applied to accelerate the discovery of novel protein kinase inhibitors that could become the standard-of-care drugs of tomorrow. Here, we describe current techniques and novel applications of semiconductor technologies in protein kinase inhibitor drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. A novel in silico approach to drug discovery via computational intelligence.

    PubMed

    Hecht, David; Fogel, Gary B

    2009-04-01

    A computational intelligence drug discovery platform is introduced as an innovative technology designed to accelerate high-throughput drug screening for generalized protein-targeted drug discovery. This technology results in collections of novel small molecule compounds that bind to protein targets as well as details on predicted binding modes and molecular interactions. The approach was tested on dihydrofolate reductase (DHFR) for novel antimalarial drug discovery; however, the methods developed can be applied broadly in early stage drug discovery and development. For this purpose, an initial fragment library was defined, and an automated fragment assembly algorithm was generated. These were combined with a computational intelligence screening tool for prescreening of compounds relative to DHFR inhibition. The entire method was assayed relative to spaces of known DHFR inhibitors and with chemical feasibility in mind, leading to experimental validation in future studies.

  10. Genome-wide target profiling of piggyBac and Tol2 in HEK 293: pros and cons for gene discovery and gene therapy

    PubMed Central

    2011-01-01

    Background DNA transposons have emerged as indispensible tools for manipulating vertebrate genomes with applications ranging from insertional mutagenesis and transgenesis to gene therapy. To fully explore the potential of two highly active DNA transposons, piggyBac and Tol2, as mammalian genetic tools, we have conducted a side-by-side comparison of the two transposon systems in the same setting to evaluate their advantages and disadvantages for use in gene therapy and gene discovery. Results We have observed that (1) the Tol2 transposase (but not piggyBac) is highly sensitive to molecular engineering; (2) the piggyBac donor with only the 40 bp 3'-and 67 bp 5'-terminal repeat domain is sufficient for effective transposition; and (3) a small amount of piggyBac transposases results in robust transposition suggesting the piggyBac transpospase is highly active. Performing genome-wide target profiling on data sets obtained by retrieving chromosomal targeting sequences from individual clones, we have identified several piggyBac and Tol2 hotspots and observed that (4) piggyBac and Tol2 display a clear difference in targeting preferences in the human genome. Finally, we have observed that (5) only sites with a particular sequence context can be targeted by either piggyBac or Tol2. Conclusions The non-overlapping targeting preference of piggyBac and Tol2 makes them complementary research tools for manipulating mammalian genomes. PiggyBac is the most promising transposon-based vector system for achieving site-specific targeting of therapeutic genes due to the flexibility of its transposase for being molecularly engineered. Insights from this study will provide a basis for engineering piggyBac transposases to achieve site-specific therapeutic gene targeting. PMID:21447194

  11. The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry

    PubMed Central

    Nooner, Kate Brody; Colcombe, Stanley J.; Tobe, Russell H.; Mennes, Maarten; Benedict, Melissa M.; Moreno, Alexis L.; Panek, Laura J.; Brown, Shaquanna; Zavitz, Stephen T.; Li, Qingyang; Sikka, Sharad; Gutman, David; Bangaru, Saroja; Schlachter, Rochelle Tziona; Kamiel, Stephanie M.; Anwar, Ayesha R.; Hinz, Caitlin M.; Kaplan, Michelle S.; Rachlin, Anna B.; Adelsberg, Samantha; Cheung, Brian; Khanuja, Ranjit; Yan, Chaogan; Craddock, Cameron C.; Calhoun, Vincent; Courtney, William; King, Margaret; Wood, Dylan; Cox, Christine L.; Kelly, A. M. Clare; Di Martino, Adriana; Petkova, Eva; Reiss, Philip T.; Duan, Nancy; Thomsen, Dawn; Biswal, Bharat; Coffey, Barbara; Hoptman, Matthew J.; Javitt, Daniel C.; Pomara, Nunzio; Sidtis, John J.; Koplewicz, Harold S.; Castellanos, Francisco Xavier; Leventhal, Bennett L.; Milham, Michael P.

    2012-01-01

    The National Institute of Mental Health strategic plan for advancing psychiatric neuroscience calls for an acceleration of discovery and the delineation of developmental trajectories for risk and resilience across the lifespan. To attain these objectives, sufficiently powered datasets with broad and deep phenotypic characterization, state-of-the-art neuroimaging, and genetic samples must be generated and made openly available to the scientific community. The enhanced Nathan Kline Institute-Rockland Sample (NKI-RS) is a response to this need. NKI-RS is an ongoing, institutionally centered endeavor aimed at creating a large-scale (N > 1000), deeply phenotyped, community-ascertained, lifespan sample (ages 6–85 years old) with advanced neuroimaging and genetics. These data will be publically shared, openly, and prospectively (i.e., on a weekly basis). Herein, we describe the conceptual basis of the NKI-RS, including study design, sampling considerations, and steps to synchronize phenotypic and neuroimaging assessment. Additionally, we describe our process for sharing the data with the scientific community while protecting participant confidentiality, maintaining an adequate database, and certifying data integrity. The pilot phase of the NKI-RS, including challenges in recruiting, characterizing, imaging, and sharing data, is discussed while also explaining how this experience informed the final design of the enhanced NKI-RS. It is our hope that familiarity with the conceptual underpinnings of the enhanced NKI-RS will facilitate harmonization with future data collection efforts aimed at advancing psychiatric neuroscience and nosology. PMID:23087608

  12. At the cross-roads of participatory research and biomarker discovery in autism: the need for empirical data.

    PubMed

    Yusuf, Afiqah; Elsabbagh, Mayada

    2015-12-15

    Identifying biomarkers for autism can improve outcomes for those affected by autism. Engaging the diverse stakeholders in the research process using community-based participatory research (CBPR) can accelerate biomarker discovery into clinical applications. However, there are limited examples of stakeholder involvement in autism research, possibly due to conceptual and practical concerns. We evaluate the applicability of CBPR principles to biomarker discovery in autism and critically review empirical studies adopting these principles. Using a scoping review methodology, we identified and evaluated seven studies using CBPR principles in biomarker discovery. The limited number of studies in biomarker discovery adopting CBPR principles coupled with their methodological limitations suggests that such applications are feasible but challenging. These studies illustrate three CBPR themes: community assessment, setting global priorities, and collaboration in research design. We propose that further research using participatory principles would be useful in accelerating the pace of discovery and the development of clinically meaningful biomarkers. For this goal to be successful we advocate for increased attention to previously identified conceptual and methodological challenges to participatory approaches in health research, including improving scientific rigor and developing long-term partnerships among stakeholders.

  13. Influence of smoking status and intensity on discovery of blood pressure loci through gene-smoking interactions

    PubMed Central

    Fuentes, Lisa de las; Schwander, Karen; Cupples, L. Adrienne; Rao, D. C.

    2015-01-01

    Background Genetic variation accounts for approximately 30% of blood pressure (BP) variability but most of that variability hasn't been attributed to specific variants. Interactions between genes and BP-associated factors may explain some ‘missing heritability.’ Cigarette smoking increases BP after short-term exposure and decreases BP with longer exposure. Gene-smoking interactions have discovered novel BP loci, but the contribution of smoking status and intensity to gene discovery is unknown. Methods We analyzed gene-smoking intensity interactions for association with systolic BP (SBP) in three subgroups from the Framingham Heart Study: current smokers only (N = 1,057), current and former smokers (‘ever smokers’, N = 3,374), and all subjects (N = 6,710). We used three smoking intensity variables defined at cutoffs of 10, 15, and 20 cigarettes per day (CPD). We evaluated the 1 degree-of-freedom (df) interaction and 2df joint test using generalized estimating equations. Results Analysis of current smokers using a CPD cutoff of 10 produced two loci associated with SBP. The rs9399633 minor allele was associated with increased SBP (5 mmHg) in heavy smokers (CPD>10) but decreased SBP (7 mmHg) in light smokers (CPD≤10). The rs11717948 minor allele was associated with decreased SBP (8 mmHg) in light smokers but decreased SBP (2 mmHg) in heavy smokers. Across all nine analyses, 19 additional loci reached p < 1×10−6. Discussion Analysis of current smokers may have the highest power to detect gene-smoking interactions, despite the reduced sample size. Associations of loci near SASH1 and KLHL6/KLHL24 with SBP may be modulated by tobacco smoking. PMID:25940791

  14. Influence of Smoking Status and Intensity on Discovery of Blood Pressure Loci Through Gene-Smoking Interactions.

    PubMed

    Basson, Jacob; Sung, Yun Ju; Fuentes, Lisa de Las; Schwander, Karen; Cupples, L Adrienne; Rao, D C

    2015-09-01

    Genetic variation accounts for approximately 30% of blood pressure (BP) variability but most of that variability has not been attributed to specific variants. Interactions between genes and BP-associated factors may explain some "missing heritability." Cigarette smoking increases BP after short-term exposure and decreases BP with longer exposure. Gene-smoking interactions have discovered novel BP loci, but the contribution of smoking status and intensity to gene discovery is unknown. We analyzed gene-smoking intensity interactions for association with systolic BP (SBP) in three subgroups from the Framingham Heart Study: current smokers only (N = 1,057), current and former smokers ("ever smokers," N = 3,374), and all subjects (N = 6,710). We used three smoking intensity variables defined at cutoffs of 10, 15, and 20 cigarettes per day (CPD). We evaluated the 1 degree-of-freedom (df) interaction and 2df joint test using generalized estimating equations. Analysis of current smokers using a CPD cutoff of 10 produced two loci associated with SBP. The rs9399633 minor allele was associated with increased SBP (5 mmHg) in heavy smokers (CPD > 10) but decreased SBP (7 mmHg) in light smokers (CPD ≤ 10). The rs11717948 minor allele was associated with decreased SBP (8 mmHg) in light smokers but decreased SBP (2 mmHg) in heavy smokers. Across all nine analyses, 19 additional loci reached P < 1 × 10(-6). Analysis of current smokers may have the highest power to detect gene-smoking interactions, despite the reduced sample size. Associations of loci near SASH1 and KLHL6/KLHL24 with SBP may be modulated by tobacco smoking. © 2015 WILEY PERIODICALS, INC.

  15. The State of the Art in Library Discovery 2010

    ERIC Educational Resources Information Center

    Breeding, Marshall

    2010-01-01

    Resource discovery tops the charts as the foremost issue within the realm of library automation. As a new year commences, the author sees a more pressing need to accelerate the pace with which libraries deliver content and services in ways that users will find compelling, relevant, and convenient. The evolution of the web advances relentlessly,…

  16. Pharmacological screening technologies for venom peptide discovery.

    PubMed

    Prashanth, Jutty Rajan; Hasaballah, Nojod; Vetter, Irina

    2017-12-01

    Venomous animals occupy one of the most successful evolutionary niches and occur on nearly every continent. They deliver venoms via biting and stinging apparatuses with the aim to rapidly incapacitate prey and deter predators. This has led to the evolution of venom components that act at a number of biological targets - including ion channels, G-protein coupled receptors, transporters and enzymes - with exquisite selectivity and potency, making venom-derived components attractive pharmacological tool compounds and drug leads. In recent years, plate-based pharmacological screening approaches have been introduced to accelerate venom-derived drug discovery. A range of assays are amenable to this purpose, including high-throughput electrophysiology, fluorescence-based functional and binding assays. However, despite these technological advances, the traditional activity-guided fractionation approach is time-consuming and resource-intensive. The combination of screening techniques suitable for miniaturization with sequence-based discovery approaches - supported by advanced proteomics, mass spectrometry, chromatography as well as synthesis and expression techniques - promises to further improve venom peptide discovery. Here, we discuss practical aspects of establishing a pipeline for venom peptide drug discovery with a particular emphasis on pharmacology and pharmacological screening approaches. This article is part of the Special Issue entitled 'Venom-derived Peptides as Pharmacological Tools.' Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. The principle of phase stability and the accelerator program at Berkeley, 1945--1954

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lofgren, E.J.

    1994-07-01

    The discovery of the Principle of Phase Stability by Vladimir Veksler and Edwin McMillian and the end of the war released a surge of accelerator activity at the Lawrence Berkeley Laboratory (then The University of California Radiation Laboratory). Six accelerators incorporating the Principle of Phase Stability were built in the period 1945--1954.

  18. Orphan diseases: state of the drug discovery art.

    PubMed

    Volmar, Claude-Henry; Wahlestedt, Claes; Brothers, Shaun P

    2017-06-01

    Since 1983 more than 300 drugs have been developed and approved for orphan diseases. However, considering the development of novel diagnosis tools, the number of rare diseases vastly outpaces therapeutic discovery. Academic centers and nonprofit institutes are now at the forefront of rare disease R&D, partnering with pharmaceutical companies when academic researchers discover novel drugs or targets for specific diseases, thus reducing the failure risk and cost for pharmaceutical companies. Considerable progress has occurred in the art of orphan drug discovery, and a symbiotic relationship now exists between pharmaceutical industry, academia, and philanthropists that provides a useful framework for orphan disease therapeutic discovery. Here, the current state-of-the-art of drug discovery for orphan diseases is reviewed. Current technological approaches and challenges for drug discovery are considered, some of which can present somewhat unique challenges and opportunities in orphan diseases, including the potential for personalized medicine, gene therapy, and phenotypic screening.

  19. Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Weighill, Deborah; Jones, Piet; Shah, Manesh

    Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant's sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes usemore » of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. Lastly, the resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for

  20. Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

    DOE PAGES

    Weighill, Deborah; Jones, Piet; Shah, Manesh; ...

    2018-05-11

    Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant's sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes usemore » of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. Lastly, the resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for

  1. Gene and enhancer trap tagging of vascular-expressed genes in poplar trees

    Treesearch

    Andrew Groover; Joseph R. Fontana; Gayle Dupper; Caiping Ma; Robert Martienssen; Steven Strauss; Richard Meilan

    2004-01-01

    We report a gene discovery system for poplar trees based on gene and enhancer traps. Gene and enhancer trap vectors carrying the β-glucuronidase (GUS) reporter gene were inserted into the poplar genome via Agrobacterium tumefaciens transformation, where they reveal the expression pattern of genes at or near the insertion sites. Because GUS...

  2. Discovery of numerous novel small genes in the intergenic regions of the Escherichia coli O157:H7 Sakai genome

    PubMed Central

    Hücker, Sarah M.; Ardern, Zachary; Goldberg, Tatyana; Schafferhans, Andrea; Bernhofer, Michael; Vestergaard, Gisle; Nelson, Chase W.; Schloter, Michael; Rost, Burkhard; Scherer, Siegfried

    2017-01-01

    In the past, short protein-coding genes were often disregarded by genome annotation pipelines. Transcriptome sequencing (RNAseq) signals outside of annotated genes have usually been interpreted to indicate either ncRNA or pervasive transcription. Therefore, in addition to the transcriptome, the translatome (RIBOseq) of the enteric pathogen Escherichia coli O157:H7 strain Sakai was determined at two optimal growth conditions and a severe stress condition combining low temperature and high osmotic pressure. All intergenic open reading frames potentially encoding a protein of ≥ 30 amino acids were investigated with regard to coverage by transcription and translation signals and their translatability expressed by the ribosomal coverage value. This led to discovery of 465 unique, putative novel genes not yet annotated in this E. coli strain, which are evenly distributed over both DNA strands of the genome. For 255 of the novel genes, annotated homologs in other bacteria were found, and a machine-learning algorithm, trained on small protein-coding E. coli genes, predicted that 89% of these translated open reading frames represent bona fide genes. The remaining 210 putative novel genes without annotated homologs were compared to the 255 novel genes with homologs and to 250 short annotated genes of this E. coli strain. All three groups turned out to be similar with respect to their translatability distribution, fractions of differentially regulated genes, secondary structure composition, and the distribution of evolutionary constraint, suggesting that both novel groups represent legitimate genes. However, the machine-learning algorithm only recognized a small fraction of the 210 genes without annotated homologs. It is possible that these genes represent a novel group of genes, which have unusual features dissimilar to the genes of the machine-learning algorithm training set. PMID:28902868

  3. Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

    PubMed

    Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

    2010-01-18

    The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

  4. Accelerated Evolution of the Pituitary Adenylate Cyclase-Activating Polypeptide Precursor Gene During Human Origin

    PubMed Central

    Wang, Yin-qiu; Qian, Ya-ping; Yang, Su; Shi, Hong; Liao, Cheng-hong; Zheng, Hong-Kun; Wang, Jun; Lin, Alice A.; Cavalli-Sforza, L. Luca; Underhill, Peter A.; Chakraborty, Ranajit; Jin, Li; Su, Bing

    2005-01-01

    Pituitary adenylate cyclase-activating polypeptide (PACAP) is a neuropeptide abundantly expressed in the central nervous system and involved in regulating neurogenesis and neuronal signal transduction. The amino acid sequence of PACAP is extremely conserved across vertebrate species, indicating a strong functional constraint during the course of evolution. However, through comparative sequence analysis, we demonstrated that the PACAP precursor gene underwent an accelerated evolution in the human lineage since the divergence from chimpanzees, and the amino acid substitution rate in humans is at least seven times faster than that in other mammal species resulting from strong Darwinian positive selection. Eleven human-specific amino acid changes were identified in the PACAP precursors, which are conserved from murine to African apes. Protein structural analysis suggested that a putative novel neuropeptide might have originated during human evolution and functioned in the human brain. Our data suggested that the PACAP precursor gene underwent adaptive changes during human origin and may have contributed to the formation of human cognition. PMID:15834139

  5. Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures

    PubMed Central

    Stark, Alexander; Lin, Michael F.; Kheradpour, Pouya; Pedersen, Jakob S.; Parts, Leopold; Carlson, Joseph W.; Crosby, Madeline A.; Rasmussen, Matthew D.; Roy, Sushmita; Deoras, Ameya N.; Ruby, J. Graham; Brennecke, Julius; Hodges, Emily; Hinrichs, Angie S.; Caspi, Anat; Paten, Benedict; Park, Seung-Won; Han, Mira V.; Maeder, Morgan L.; Polansky, Benjamin J.; Robson, Bryanne E.; Aerts, Stein; van Helden, Jacques; Hassan, Bassem; Gilbert, Donald G.; Eastman, Deborah A.; Rice, Michael; Weir, Michael; Hahn, Matthew W.; Park, Yongkyu; Dewey, Colin N.; Pachter, Lior; Kent, W. James; Haussler, David; Lai, Eric C.; Bartel, David P.; Hannon, Gregory J.; Kaufman, Thomas C.; Eisen, Michael B.; Clark, Andrew G.; Smith, Douglas; Celniker, Susan E.; Gelbart, William M.; Kellis, Manolis

    2008-01-01

    Sequencing of multiple related species followed by comparative genomics analysis constitutes a powerful approach for the systematic understanding of any genome. Here, we use the genomes of 12 Drosophila species for the de novo discovery of functional elements in the fly. Each type of functional element shows characteristic patterns of change, or ‘evolutionary signatures’, dictated by its precise selective constraints. Such signatures enable recognition of new protein-coding genes and exons, spurious and incorrect gene annotations, and numerous unusual gene structures, including abundant stop-codon readthrough. Similarly, we predict non-protein-coding RNA genes and structures, and new microRNA (miRNA) genes. We provide evidence of miRNA processing and functionality from both hairpin arms and both DNA strands. We identify several classes of pre- and post-transcriptional regulatory motifs, and predict individual motif instances with high confidence. We also study how discovery power scales with the divergence and number of species compared, and we provide general guidelines for comparative studies. PMID:17994088

  6. PDGF-B Gene Therapy Accelerates Bone Engineering and Oral Implant Osseointegration

    PubMed Central

    Chang, Po-Chun; Seol, Yang-Jo; Cirelli, Joni A; Pellegrini, Gaia R.; Jin, Qiming; Franco, Lea M.; Goldstein, Steven A.; Chandler, Lois A.; Sosnowski, Barbara; Giannobile, William V.

    2009-01-01

    Platelet-derived growth factor-BB (PDGF-BB) stimulates repair of healing-impaired chronic wounds such as diabetic ulcers and periodontal lesions. However, limitations in predictability of tissue regeneration occur due in part to transient growth factor bioavailability in vivo. Here, we report that gene delivery of PDGF-B stimulates repair of oral implant extraction socket defects. Alveolar ridge defects were created in rats and were treated at the time of titanium implant installation with a collagen matrix containing an adenoviral (Ad) vector encoding PDGF-B (5.5×108 or 5.5×109 pfu/ml), Ad encoding luciferase (Ad-Luc; 5.5×109 pfu/ml; control) or recombinant human PDGF-BB protein (rhPDGF-BB, 0.3 mg/ml). Bone repair and osseointegration were measured via backscattered SEM, histomorphometry, microcomputed tomography, and biomechanical assessments. Further, a panel of local and systemic safety assessments was performed. Results demonstrated bone repair was accelerated by Ad-PDGF-B and rhPDGF-BB delivery compared to Ad-Luc, with the high dose of Ad-PDGF-B more effective than the low dose. No significant dissemination of the vector construct or alteration of systemic parameters was noted. In summary, gene delivery of Ad-PDGF-B demonstrates regenerative and safety capabilities for bone tissue engineering and osseointegration in alveolar bone defects comparable to rhPDGF-BB protein delivery in vivo. PMID:19741730

  7. Advancements in Aptamer Discovery Technologies.

    PubMed

    Gotrik, Michael R; Feagin, Trevor A; Csordas, Andrew T; Nakamoto, Margaret A; Soh, H Tom

    2016-09-20

    transforms solution-phase aptamers into "aptamer particles" that can be individually screened at high-throughput via fluorescence-activated cell sorting. Using PD, we have shown the feasibility of rapidly generating aptamers with exceptional affinities, even for proteins that have previously proven intractable to aptamer discovery. We are confident that these advanced aptamer-discovery methods will accelerate the discovery of aptamer reagents with excellent affinities and specificities, perhaps even exceeding those of the best monoclonal antibodies. Since aptamers are reproducible, renewable, stable, and can be distributed as sequence information, we anticipate that these affinity reagents will become even more valuable tools for both research and clinical applications.

  8. Display technologies: application for the discovery of drug and gene delivery agents

    PubMed Central

    Sergeeva, Anna; Kolonin, Mikhail G.; Molldrem, Jeffrey J.; Pasqualini, Renata; Arap, Wadih

    2007-01-01

    Recognition of molecular diversity of cell surface proteomes in disease is essential for the development of targeted therapies. Progress in targeted therapeutics requires establishing effective approaches for high-throughput identification of agents specific for clinically relevant cell surface markers. Over the past decade, a number of platform strategies have been developed to screen polypeptide libraries for ligands targeting receptors selectively expressed in the context of various cell surface proteomes. Streamlined procedures for identification of ligand-receptor pairs that could serve as targets in disease diagnosis, profiling, imaging and therapy have relied on the display technologies, in which polypeptides with desired binding profiles can be serially selected, in a process called biopanning, based on their physical linkage with the encoding nucleic acid. These technologies include virus/phage display, cell display, ribosomal display, mRNA display and covalent DNA display (CDT), with phage display being by far the most utilized. The scope of this review is the recent advancements in the display technologies with a particular emphasis on molecular mapping of cell surface proteomes with peptide phage display. Prospective applications of targeted compounds derived from display libraries in the discovery of targeted drugs and gene therapy vectors are discussed. PMID:17123658

  9. Allele Mining in Barley Genetic Resources Reveals Genes of Race-Non-Specific Powdery Mildew Resistance

    PubMed Central

    Spies, Annika; Korzun, Viktor; Bayles, Rosemary; Rajaraman, Jeyaraman; Himmelbach, Axel; Hedley, Pete E.; Schweizer, Patrick

    2012-01-01

    Race-non-specific, or quantitative, pathogen resistance is of high importance to plant breeders due to its expected durability. However, it is usually controlled by multiple quantitative trait loci (QTL) and therefore difficult to handle in practice. Knowing the genes that underlie race-non-specific resistance (NR) would allow its exploitation in a more targeted manner. Here, we performed an association-genetic study in a customized worldwide collection of spring barley accessions for candidate genes of race-NR to the powdery mildew fungus Blumeria graminis f. sp. hordei (Bgh) and combined data with results from QTL mapping as well as functional-genomics approaches. This led to the identification of 11 associated genes with converging evidence for an important role in race-NR in the presence of the Mlo gene for basal susceptibility. Outstanding in this respect was the gene encoding the transcription factor WRKY2. The results suggest that unlocking plant genetic resources and integrating functional-genomic with genetic approaches can accelerate the discovery of genes underlying race-NR in barley and other crop plants. PMID:22629270

  10. Customizing microarrays for neuroscience drug discovery.

    PubMed

    Girgenti, Matthew J; Newton, Samuel S

    2007-08-01

    Microarray-based gene profiling has become the centerpiece of gene expression studies in the biological sciences. The ability to now interrogate the entire genome using a single chip demonstrates the progress in technology and instrumentation that has been made over the last two decades. Although this unbiased approach provides researchers with an immense quantity of data, obtaining meaningful insight is not possible without intensive data analysis and processing. Custom developed arrays have emerged as a viable and attractive alternative that can take advantage of this robust technology and tailor it to suit the needs and requirements of individual investigations. The ability to simplify data analysis, reduce noise and carefully optimize experimental conditions makes it a suitable tool that can be effectively utilized in neuroscience drug discovery efforts. Furthermore, incorporating recent advancements in fine focusing gene profiling to include specific cellular phenotypes can help resolve the complex cellular heterogeneity of the brain. This review surveys the use of microarray technology in neuroscience paying special attention to customized arrays and their potential in drug discovery. Novel applications of microarrays and ancillary techniques, such as laser microdissection, FAC sorting and RNA amplification, have also been discussed. The notion that a hypothesis-driven approach can be integrated into drug development programs is highlighted.

  11. SBCDDB: Sleeping Beauty Cancer Driver Database for gene discovery in mouse models of human cancers

    PubMed Central

    Mann, Michael B

    2018-01-01

    Abstract Large-scale oncogenomic studies have identified few frequently mutated cancer drivers and hundreds of infrequently mutated drivers. Defining the biological context for rare driving events is fundamentally important to increasing our understanding of the druggable pathways in cancer. Sleeping Beauty (SB) insertional mutagenesis is a powerful gene discovery tool used to model human cancers in mice. Our lab and others have published a number of studies that identify cancer drivers from these models using various statistical and computational approaches. Here, we have integrated SB data from primary tumor models into an analysis and reporting framework, the Sleeping Beauty Cancer Driver DataBase (SBCDDB, http://sbcddb.moffitt.org), which identifies drivers in individual tumors or tumor populations. Unique to this effort, the SBCDDB utilizes a single, scalable, statistical analysis method that enables data to be grouped by different biological properties. This allows for SB drivers to be evaluated (and re-evaluated) under different contexts. The SBCDDB provides visual representations highlighting the spatial attributes of transposon mutagenesis and couples this functionality with analysis of gene sets, enabling users to interrogate relationships between drivers. The SBCDDB is a powerful resource for comparative oncogenomic analyses with human cancer genomics datasets for driver prioritization. PMID:29059366

  12. Medicinal chemistry inspired fragment-based drug discovery.

    PubMed

    Lanter, James; Zhang, Xuqing; Sui, Zhihua

    2011-01-01

    Lead generation can be a very challenging phase of the drug discovery process. The two principal methods for this stage of research are blind screening and rational design. Among the rational or semirational design approaches, fragment-based drug discovery (FBDD) has emerged as a useful tool for the generation of lead structures. It is particularly powerful as a complement to high-throughput screening approaches when the latter failed to yield viable hits for further development. Engagement of medicinal chemists early in the process can accelerate the progression of FBDD efforts by incorporating drug-friendly properties in the earliest stages of the design process. Medium-chain acyl-CoA synthetase 2b and ketohexokinase are chosen as examples to illustrate the importance of close collaboration of medicinal chemists, crystallography, and modeling. Copyright © 2011 Elsevier Inc. All rights reserved.

  13. The case for electron re-acceleration at galaxy cluster shocks

    NASA Astrophysics Data System (ADS)

    van Weeren, Reinout J.; Andrade-Santos, Felipe; Dawson, William A.; Golovich, Nathan; Lal, Dharam V.; Kang, Hyesung; Ryu, Dongsu; Brìggen, Marcus; Ogrean, Georgiana A.; Forman, William R.; Jones, Christine; Placco, Vinicius M.; Santucci, Rafael M.; Wittman, David; Jee, M. James; Kraft, Ralph P.; Sobral, David; Stroe, Andra; Fogarty, Kevin

    2017-01-01

    On the largest scales, the Universe consists of voids and filaments making up the cosmic web. Galaxy clusters are located at the knots in this web, at the intersection of filaments. Clusters grow through accretion from these large-scale filaments and by mergers with other clusters and groups. In a growing number of galaxy clusters, elongated Mpc-sized radio sources have been found1,2 . Also known as radio relics, these regions of diffuse radio emission are thought to trace relativistic electrons in the intracluster plasma accelerated by low-Mach-number shocks generated by cluster-cluster merger events 3 . A long-standing problem is how low-Mach-number shocks can accelerate electrons so efficiently to explain the observed radio relics. Here, we report the discovery of a direct connection between a radio relic and a radio galaxy in the merging galaxy cluster Abell 3411-3412 by combining radio, X-ray and optical observations. This discovery indicates that fossil relativistic electrons from active galactic nuclei are re-accelerated at cluster shocks. It also implies that radio galaxies play an important role in governing the non-thermal component of the intracluster medium in merging clusters.

  14. Generation of cell lines for drug discovery through random activation of gene expression: application to the human histamine H3 receptor.

    PubMed

    Song, J; Doucette, C; Hanniford, D; Hunady, K; Wang, N; Sherf, B; Harrington, J J; Brunden, K R; Stricker-Krongrad, A

    2005-06-01

    Target-based high-throughput screening (HTS) plays an integral role in drug discovery. The implementation of HTS assays generally requires high expression levels of the target protein, and this is typically accomplished using recombinant cDNA methodologies. However, the isolated gene sequences to many drug targets have intellectual property claims that restrict the ability to implement drug discovery programs. The present study describes the pharmacological characterization of the human histamine H3 receptor that was expressed using random activation of gene expression (RAGE), a technology that over-expresses proteins by up-regulating endogenous genes rather than introducing cDNA expression vectors into the cell. Saturation binding analysis using [125I]iodoproxyfan and RAGE-H3 membranes revealed a single class of binding sites with a K(D) value of 0.77 nM and a B(max) equal to 756 fmol/mg of protein. Competition binding studies showed that the rank order of potency for H3 agonists was N(alpha)-methylhistamine approximately (R)-alpha- methylhistamine > histamine and that the rank order of potency for H3 antagonists was clobenpropit > iodophenpropit > thioperamide. The same rank order of potency for H3 agonists and antagonists was observed in the functional assays as in the binding assays. The Fluorometic Imaging Plate Reader assays in RAGE-H3 cells gave high Z' values for agonist and antagonist screening, respectively. These results reveal that the human H3 receptor expressed with the RAGE technology is pharmacologically comparable to that expressed through recombinant methods. Moreover, the level of expression of the H3 receptor in the RAGE-H3 cells is suitable for HTS and secondary assays.

  15. Computational discovery and in vivo validation of hnf4 as a regulatory gene in planarian regeneration.

    PubMed

    Lobo, Daniel; Morokuma, Junji; Levin, Michael

    2016-09-01

    Automated computational methods can infer dynamic regulatory network models directly from temporal and spatial experimental data, such as genetic perturbations and their resultant morphologies. Recently, a computational method was able to reverse-engineer the first mechanistic model of planarian regeneration that can recapitulate the main anterior-posterior patterning experiments published in the literature. Validating this comprehensive regulatory model via novel experiments that had not yet been performed would add in our understanding of the remarkable regeneration capacity of planarian worms and demonstrate the power of this automated methodology. Using the Michigan Molecular Interactions and STRING databases and the MoCha software tool, we characterized as hnf4 an unknown regulatory gene predicted to exist by the reverse-engineered dynamic model of planarian regeneration. Then, we used the dynamic model to predict the morphological outcomes under different single and multiple knock-downs (RNA interference) of hnf4 and its predicted gene pathway interactors β-catenin and hh Interestingly, the model predicted that RNAi of hnf4 would rescue the abnormal regenerated phenotype (tailless) of RNAi of hh in amputated trunk fragments. Finally, we validated these predictions in vivo by performing the same surgical and genetic experiments with planarian worms, obtaining the same phenotypic outcomes predicted by the reverse-engineered model. These results suggest that hnf4 is a regulatory gene in planarian regeneration, validate the computational predictions of the reverse-engineered dynamic model, and demonstrate the automated methodology for the discovery of novel genes, pathways and experimental phenotypes. michael.levin@tufts.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  16. Organic synthesis provides opportunities to transform drug discovery

    NASA Astrophysics Data System (ADS)

    Blakemore, David C.; Castro, Luis; Churcher, Ian; Rees, David C.; Thomas, Andrew W.; Wilson, David M.; Wood, Anthony

    2018-04-01

    Despite decades of ground-breaking research in academia, organic synthesis is still a rate-limiting factor in drug-discovery projects. Here we present some current challenges in synthetic organic chemistry from the perspective of the pharmaceutical industry and highlight problematic steps that, if overcome, would find extensive application in the discovery of transformational medicines. Significant synthesis challenges arise from the fact that drug molecules typically contain amines and N-heterocycles, as well as unprotected polar groups. There is also a need for new reactions that enable non-traditional disconnections, more C-H bond activation and late-stage functionalization, as well as stereoselectively substituted aliphatic heterocyclic ring synthesis, C-X or C-C bond formation. We also emphasize that syntheses compatible with biomacromolecules will find increasing use, while new technologies such as machine-assisted approaches and artificial intelligence for synthesis planning have the potential to dramatically accelerate the drug-discovery process. We believe that increasing collaboration between academic and industrial chemists is crucial to address the challenges outlined here.

  17. Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

    PubMed Central

    2010-01-01

    Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

  18. Compound scale-up at the discovery-development interface.

    PubMed

    Nikitenko, Antonia A

    2006-11-01

    As a result of an economically challenging environment within the pharmaceutical industry, pharmaceutical companies and their departments must increase productivity and cut costs to stay in line with the market. Discovery-led departments such as the medicinal chemistry and lead optimization groups focus on synthesizing large varieties of compounds in minimal amounts, while the chemical development groups must then deliver a few chosen leads employing an optimized synthesis method and using multi-kilogram quantities of material. A research group at the discovery-development interface has the task of medium-scale synthesis which is important in the lead selection stage. The primary objective of this group is the initial scale-up of promising leads for extensive physicochemical and biological testing. The challenge of the interface group involves overcoming synthetic issues within the rigid, accelerated timelines.

  19. DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes.

    PubMed

    Piñero, Janet; Queralt-Rosinach, Núria; Bravo, Àlex; Deu-Pons, Jordi; Bauer-Mehren, Anna; Baron, Martin; Sanz, Ferran; Furlong, Laura I

    2015-01-01

    DisGeNET is a comprehensive discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET contains over 380,000 associations between >16,000 genes and 13,000 diseases, which makes it one of the largest repositories currently available of its kind. DisGeNET integrates expert-curated databases with text-mined data, covers information on Mendelian and complex diseases, and includes data from animal disease models. It features a score based on the supporting evidence to prioritize gene-disease associations. It is an open access resource available through a web interface, a Cytoscape plugin and as a Semantic Web resource. The web interface supports user-friendly data exploration and navigation. DisGeNET data can also be analysed via the DisGeNET Cytoscape plugin, and enriched with the annotations of other plugins of this popular network analysis software suite. Finally, the information contained in DisGeNET can be expanded and complemented using Semantic Web technologies and linked to a variety of resources already present in the Linked Data cloud. Hence, DisGeNET offers one of the most comprehensive collections of human gene-disease associations and a valuable set of tools for investigating the molecular mechanisms underlying diseases of genetic origin, designed to fulfill the needs of different user profiles, including bioinformaticians, biologists and health-care practitioners. Database URL: http://www.disgenet.org/ © The Author(s) 2015. Published by Oxford University Press.

  20. HEx: A heterologous expression platform for the discovery of fungal natural products

    PubMed Central

    Schlecht, Ulrich; Horecka, Joe; Lin, Hsiao-Ching; Naughton, Brian; Miranda, Molly; Li, Yong Fuga; Hennessy, James R.; Vandova, Gergana A.; Steinmetz, Lars M.; Sattely, Elizabeth; Khosla, Chaitan; Hillenmeyer, Maureen E.

    2018-01-01

    For decades, fungi have been a source of U.S. Food and Drug Administration–approved natural products such as penicillin, cyclosporine, and the statins. Recent breakthroughs in DNA sequencing suggest that millions of fungal species exist on Earth, with each genome encoding pathways capable of generating as many as dozens of natural products. However, the majority of encoded molecules are difficult or impossible to access because the organisms are uncultivable or the genes are transcriptionally silent. To overcome this bottleneck in natural product discovery, we developed the HEx (Heterologous EXpression) synthetic biology platform for rapid, scalable expression of fungal biosynthetic genes and their encoded metabolites in Saccharomyces cerevisiae. We applied this platform to 41 fungal biosynthetic gene clusters from diverse fungal species from around the world, 22 of which produced detectable compounds. These included novel compounds with unexpected biosynthetic origins, particularly from poorly studied species. This result establishes the HEx platform for rapid discovery of natural products from any fungal species, even those that are uncultivable, and opens the door to discovery of the next generation of natural products. PMID:29651464

  1. Discovery and Development of ATP-Competitive mTOR Inhibitors Using Computational Approaches.

    PubMed

    Luo, Yao; Wang, Ling

    2017-11-16

    The mammalian target of rapamycin (mTOR) is a central controller of cell growth, proliferation, metabolism, and angiogenesis. This protein is an attractive target for new anticancer drug development. Significant progress has been made in hit discovery, lead optimization, drug candidate development and determination of the three-dimensional (3D) structure of mTOR. Computational methods have been applied to accelerate the discovery and development of mTOR inhibitors helping to model the structure of mTOR, screen compound databases, uncover structure-activity relationship (SAR) and optimize the hits, mine the privileged fragments and design focused libraries. Besides, computational approaches were also applied to study protein-ligand interactions mechanisms and in natural product-driven drug discovery. Herein, we survey the most recent progress on the application of computational approaches to advance the discovery and development of compounds targeting mTOR. Future directions in the discovery of new mTOR inhibitors using computational methods are also discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  2. Challenges of the information age: the impact of false discovery on pathway identification.

    PubMed

    Rog, Colin J; Chekuri, Srinivasa C; Edgerton, Mary E

    2012-11-21

    Pathways with members that have known relevance to a disease are used to support hypotheses generated from analyses of gene expression and proteomic studies. Using cancer as an example, the pitfalls of searching pathways databases as support for genes and proteins that could represent false discoveries are explored. The frequency with which networks could be generated from 100 instances each of randomly selected five and ten genes sets as input to MetaCore, a commercial pathways database, was measured. A PubMed search enumerated cancer-related literature published for any gene in the networks. Using three, two, and one maximum intervening step between input genes to populate the network, networks were generated with frequencies of 97%, 77%, and 7% using ten gene sets and 73%, 27%, and 1% using five gene sets. PubMed reported an average of 4225 cancer-related articles per network gene. This can be attributed to the richly populated pathways databases and the interest in the molecular basis of cancer. As information sources become enriched, they are more likely to generate plausible mechanisms for false discoveries.

  3. Open Science Meets Stem Cells: A New Drug Discovery Approach for Neurodegenerative Disorders

    PubMed Central

    Han, Chanshuai; Chaineau, Mathilde; Chen, Carol X.-Q.; Beitel, Lenore K.; Durcan, Thomas M.

    2018-01-01

    Neurodegenerative diseases are a challenge for drug discovery, as the biological mechanisms are complex and poorly understood, with a paucity of models that faithfully recapitulate these disorders. Recent advances in stem cell technology have provided a paradigm shift, providing researchers with tools to generate human induced pluripotent stem cells (iPSCs) from patient cells. With the potential to generate any human cell type, we can now generate human neurons and develop “first-of-their-kind” disease-relevant assays for small molecule screening. Now that the tools are in place, it is imperative that we accelerate discoveries from the bench to the clinic. Using traditional closed-door research systems raises barriers to discovery, by restricting access to cells, data and other research findings. Thus, a new strategy is required, and the Montreal Neurological Institute (MNI) and its partners are piloting an “Open Science” model. One signature initiative will be that the MNI biorepository will curate and disseminate patient samples in a more accessible manner through open transfer agreements. This feeds into the MNI open drug discovery platform, focused on developing industry-standard assays with iPSC-derived neurons. All cell lines, reagents and assay findings developed in this open fashion will be made available to academia and industry. By removing the obstacles many universities and companies face in distributing patient samples and assay results, our goal is to accelerate translational medical research and the development of new therapies for devastating neurodegenerative disorders. PMID:29467610

  4. Open Science Meets Stem Cells: A New Drug Discovery Approach for Neurodegenerative Disorders.

    PubMed

    Han, Chanshuai; Chaineau, Mathilde; Chen, Carol X-Q; Beitel, Lenore K; Durcan, Thomas M

    2018-01-01

    Neurodegenerative diseases are a challenge for drug discovery, as the biological mechanisms are complex and poorly understood, with a paucity of models that faithfully recapitulate these disorders. Recent advances in stem cell technology have provided a paradigm shift, providing researchers with tools to generate human induced pluripotent stem cells (iPSCs) from patient cells. With the potential to generate any human cell type, we can now generate human neurons and develop "first-of-their-kind" disease-relevant assays for small molecule screening. Now that the tools are in place, it is imperative that we accelerate discoveries from the bench to the clinic. Using traditional closed-door research systems raises barriers to discovery, by restricting access to cells, data and other research findings. Thus, a new strategy is required, and the Montreal Neurological Institute (MNI) and its partners are piloting an "Open Science" model. One signature initiative will be that the MNI biorepository will curate and disseminate patient samples in a more accessible manner through open transfer agreements. This feeds into the MNI open drug discovery platform, focused on developing industry-standard assays with iPSC-derived neurons. All cell lines, reagents and assay findings developed in this open fashion will be made available to academia and industry. By removing the obstacles many universities and companies face in distributing patient samples and assay results, our goal is to accelerate translational medical research and the development of new therapies for devastating neurodegenerative disorders.

  5. Accelerator-feasible N -body nonlinear integrable system

    DOE PAGES

    Danilov, V.; Nagaitsev, S.

    2014-12-23

    Nonlinear N-body integrable Hamiltonian systems, where N is an arbitrary number, attract the attention of mathematical physicists for the last several decades, following the discovery of some number of these systems. This research presents a new integrable system, which can be realized in facilities such as particle accelerators. This feature makes it more attractive than many of the previous such systems with singular or unphysical forces.

  6. De Novo Assembly of Auricularia polytricha Transcriptome Using Illumina Sequencing for Gene Discovery and SSR Marker Identification

    PubMed Central

    Zhou, Yan; Chen, Lianfu; Fan, Xiuzhi; Bian, Yinbing

    2014-01-01

    Auricularia polytricha (Mont.) Sacc., a type of edible black-brown mushroom with a gelatinous and modality-specific fruiting body, is in high demand in Asia due to its nutritional and medicinal properties. Illumina Solexa sequenceing technology was used to generate very large transcript sequences from the mycelium and the mature fruiting body of A. polytricha for gene discovery and molecular marker development. De novo assembly generated 36,483 ESTs with an N50 length of 636 bp. A total of 28,108 ESTs demonstrated significant hits with known proteins in the nr database, and 94.03% of the annotated ESTs showed the greatest similarity to A. delicata, a related species of A. polytricha. Functional categorization of the Gene Ontology (GO), Clusters of Orthologous Groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways revealed the conservation of genes involved in various biological processes in A. polytricha. Gene expression profile analysis indicated that a total of 2,057 ESTs were differentially expressed, including 1,020 ESTs that were up-regulated in the mycelium and 1,037 up-regulated in the fruiting body. Functional enrichment showed that the ESTs associated with biosynthesis, metabolism and assembly of proteins were more active in fruiting body development. The expression patterns of homologous transcription factors indicated that the molecular mechanisms of fruiting body formation and development were not exactly the same as for other agarics. Interestingly, an EST encoding tyrosinase was significantly up-regulated in the fruiting body, indicating that melanins accumulated during the processes of the formation of the black-brown color of the fruiting body in A. polytricha development. In addition, a total of 1,715 potential SSRs were detected in this transcriptome. The transcriptome analysis of A. polytricha provides valuable sequence resources and numerous molecular markers to facilitate further functional genomics studies and

  7. Gene Expression in Bone

    NASA Astrophysics Data System (ADS)

    D'Ambrogio, A.

    Skeletal system has two main functions, to provide mechanical integrity for both locomotion and protection and to play an important role in mineral homeostasis. There is extensive evidence showing loss of bone mass during long-term Space-Flights. The loss is due to a break in the equilibrium between the activity of osteoblasts (the cells that forms bone) and the activity of osteoclasts (the cells that resorbs bone). Surprisingly, there is scanty information about the possible altered gene expression occurring in cells that form bone in microgravity.(Just 69 articles result from a "gene expression in microgravity" MedLine query.) Gene-chip or microarray technology allows to screen thousands of genes at the same time: the use of this technology on samples coming from cells exposed to microgravity could provide us with many important informations. For example, the identification of the molecules or structures which are the first sensors of the mechanical stress derived from lack of gravity, could help in understanding which is the first event leading to bone loss due to long-term exposure to microgravity. Consequently, this structure could become a target for a custom-designed drug. It is evident that bone mass loss, observed during long-time stay in Space, represents an accelerated model of what happens in aging osteoporosis. Therefore, the discovery and design of drugs able to interfere with the bone-loss process, could help also in preventing negative physiological processes normally observed on Earth. Considering the aims stated above, my research is designed to:

  8. Collisionless Shocks and Particle Acceleration.

    NASA Astrophysics Data System (ADS)

    Malkov, M.

    2016-12-01

    Collisionless shocks emerged in the 50s and 60s of the last century as an important branch of plasma physics and have remained ever since. New applications pose new challenges to our understanding of collisionless shock mechanisms. Particle acceleration in astrophysical settings, primarily studied concerning the putative origin of cosmic rays (CR) in supernova remnant (SNR) shocks, stands out with the collisionless shock mechanism being the key. Among recent laboratory applications, a laser-based tabletop proton accelerator is an affordable compact alternative to big synchrotron accelerators. The much-anticipated proof of cosmic ray (CR) acceleration in supernova remnants is hindered by our limited understanding of collisionless shock mechanisms. Over the last decade, dramatically improved observations were puzzling the theorists with unexpected discoveries. The difference between the helium/carbon and proton CR rigidity (momentum to charge ratio) spectra, seemingly inconsistent with the acceleration and propagation theories, and the perplexing positron excess in the 10-300 GeV range are just two recent examples. The latter is now also actively discussed in the particle physics and CR communities as a possible signature of decay or annihilation of hypothetical dark matter particles. By considering an initial (injection) phase of a diffusive shock acceleration mechanism, including particle reflection off the shock front - where an elemental similarity of particle dynamics does not apply - I will discuss recent suggestions of how to address the new data from the collisionless shock perspective. The backreaction of accelerated particles on the shock structure, its environment, and visibility across the electromagnetic spectrum from radio to gamma rays is another key aspect of collisionless shock that will be discussed.

  9. The Future Workforce in Cancer Prevention: Advancing Discovery, Research, and Technology

    PubMed Central

    Newhauser, Wayne. D.; Scheurer, Michael. E.; Faupel-Badger, Jessica. M.; Clague, Jessica.; Weitzel, Jeffrey.; Woods, Kendra. V.

    2012-01-01

    As part of a 2 day conference on October 15 and 16, 2009, a nine-member task force composed of scientists, clinicians, educators, administrators, and students from across the United States was formed to discuss research, discovery, and technology obstacles to progress in cancer prevention and control, specifically those related to the cancer prevention workforce. This article summarizes the task force’s findings on the current state of the cancer prevention workforce in this area and its needs for the future. The task force identified two types of barriers impeding the current cancer prevention workforce in research, discovery, and technology from reaching its fullest potential: 1) limited cross-disciplinary research opportunities with underutilization of some disciplines is hampering discovery and research in cancer prevention, and 2) new research avenues are not being investigated because technology development and implementation are lagging. Examples of impediments and desired outcomes are provided in each of these areas. Recommended solutions to these problems are based on the goals of enhancing the current cancer prevention workforce and accelerating the pace of discovery and clinical translation. PMID:22314794

  10. The future workforce in cancer prevention: advancing discovery, research, and technology.

    PubMed

    Newhauser, Wayne D; Scheurer, Michael E; Faupel-Badger, Jessica M; Clague, Jessica; Weitzel, Jeffrey; Woods, Kendra V

    2012-05-01

    As part of a 2-day conference on October 15 and 16, 2009, a nine-member task force composed of scientists, clinicians, educators, administrators, and students from across the USA was formed to discuss research, discovery, and technology obstacles to progress in cancer prevention and control, specifically those related to the cancer prevention workforce. This article summarizes the task force's findings on the current state of the cancer prevention workforce in this area and its needs for the future. The task force identified two types of barriers impeding the current cancer prevention workforce in research, discovery, and technology from reaching its fullest potential: (1) limited cross-disciplinary research opportunities with underutilization of some disciplines is hampering discovery and research in cancer prevention, and (2) new research avenues are not being investigated because technology development and implementation are lagging. Examples of impediments and desired outcomes are provided in each of these areas. Recommended solutions to these problems are based on the goals of enhancing the current cancer prevention workforce and accelerating the pace of discovery and clinical translation.

  11. Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

    PubMed Central

    Li, Xia; Rao, Shaoqi; Jiang, Wei; Li, Chuanxing; Xiao, Yun; Guo, Zheng; Zhang, Qingpu; Wang, Lihong; Du, Lei; Li, Jing; Li, Li; Zhang, Tianwen; Wang, Qing K

    2006-01-01

    Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network) to address the underlying regulations of genes that can span any unit(s) of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex gene regulations related to

  12. Culture-independent discovery of natural products from soil metagenomes.

    PubMed

    Katz, Micah; Hover, Bradley M; Brady, Sean F

    2016-03-01

    Bacterial natural products have proven to be invaluable starting points in the development of many currently used therapeutic agents. Unfortunately, traditional culture-based methods for natural product discovery have been deemphasized by pharmaceutical companies due in large part to high rediscovery rates. Culture-independent, or "metagenomic," methods, which rely on the heterologous expression of DNA extracted directly from environmental samples (eDNA), have the potential to provide access to metabolites encoded by a large fraction of the earth's microbial biosynthetic diversity. As soil is both ubiquitous and rich in bacterial diversity, it is an appealing starting point for culture-independent natural product discovery efforts. This review provides an overview of the history of soil metagenome-driven natural product discovery studies and elaborates on the recent development of new tools for sequence-based, high-throughput profiling of environmental samples used in discovering novel natural product biosynthetic gene clusters. We conclude with several examples of these new tools being employed to facilitate the recovery of novel secondary metabolite encoding gene clusters from soil metagenomes and the subsequent heterologous expression of these clusters to produce bioactive small molecules.

  13. Leveraging Gene-Environment Interactions and Endotypes for Asthma Gene Discovery

    PubMed Central

    Bønnelykke, Klaus; Ober, Carole

    2016-01-01

    Asthma is a heterogeneous clinical syndrome that includes subtypes of disease with different underlying causes and disease mechanisms. Asthma is caused by a complex interaction between genes and environmental exposures; early-life exposures in particular play an important role. Asthma is also heritable, and a number of susceptibility variants have been discovered in genome-wide association studies, although the known risk alleles explain only a small proportion of the heritability. In this review, we present evidence supporting the hypothesis that focusing on more specific asthma phenotypes, such as childhood asthma with severe exacerbations, and on relevant exposures that are involved in gene-environment interactions (GEIs), such as rhinovirus infections, will improve detection of asthma genes and our understanding of the underlying mechanisms. We will discuss the challenges of considering GEIs and the advantages of studying responses to asthma-associated exposures in clinical birth cohorts, as well as in cell models of GEIs, to dissect the context-specific nature of genotypic risks, to prioritize variants in genome-wide association studies, and to identify pathways involved in pathogenesis in subgroups of patients. We propose that such approaches, in spite of their many challenges, present great opportunities for better understanding of asthma pathogenesis and heterogeneity and, ultimately, for improving prevention and treatment of disease. PMID:26947980

  14. Neoadjuvant trials in ER+ breast cancer: A tool for acceleration of drug development and discovery

    PubMed Central

    Guerrero-Zotano, Angel L.; Arteaga, Carlos L.

    2017-01-01

    Neoadjuvant therapy trials offer an excellent strategy for drug development and discovery in breast cancer, particularly in triple negative and HER2-overexpressing subtypes, where pathologic complete response is a good surrogate of long term patient benefit. For estrogen receptor (ER)-positive breast cancers, however, use of this strategy has been challenging because of the lack of validated surrogates of long term efficacy and the overall good prognosis of the majority of patients with this cancer subtype. We review below the clinical benefits of neodjuvant endocrine therapy for ER+/HER2-negative breast cancer, its use and limitations for drug development, prioritization of adjuvant and metastatic trials, and biomarker discovery. PMID:28495849

  15. Gene Discovery through Genomic Sequencing of Brucella abortus

    PubMed Central

    Sánchez, Daniel O.; Zandomeni, Ruben O.; Cravero, Silvio; Verdún, Ramiro E.; Pierrou, Ester; Faccio, Paula; Diaz, Gabriela; Lanzavecchia, Silvia; Agüero, Fernán; Frasch, Alberto C. C.; Andersson, Siv G. E.; Rossetti, Osvaldo L.; Grau, Oscar; Ugalde, Rodolfo A.

    2001-01-01

    Brucella abortus is the etiological agent of brucellosis, a disease that affects bovines and human. We generated DNA random sequences from the genome of B. abortus strain 2308 in order to characterize molecular targets that might be useful for developing immunological or chemotherapeutic strategies against this pathogen. The partial sequencing of 1,899 clones allowed the identification of 1,199 genomic sequence surveys (GSSs) with high homology (BLAST expect value < 10−5) to sequences deposited in the GenBank databases. Among them, 925 represent putative novel genes for the Brucella genus. Out of 925 nonredundant GSSs, 470 were classified in 15 categories based on cellular function. Seven hundred GSSs showed no significant database matches and remain available for further studies in order to identify their function. A high number of GSSs with homology to Agrobacterium tumefaciens and Rhizobium meliloti proteins were observed, thus confirming their close phylogenetic relationship. Among them, several GSSs showed high similarity with genes related to nodule nitrogen fixation, synthesis of nod factors, nodulation protein symbiotic plasmid, and nodule bacteroid differentiation. We have also identified several B. abortus homologs of virulence and pathogenesis genes from other pathogens, including a homolog to both the Shda gene from Salmonella enterica serovar Typhimurium and the AidA-1 gene from Escherichia coli. Other GSSs displayed significant homologies to genes encoding components of the type III and type IV secretion machineries, suggesting that Brucella might also have an active type III secretion machinery. PMID:11159979

  16. Top-K Interesting Subgraph Discovery in Information Networks

    DTIC Science & Technology

    2014-03-03

    Integrative Biomarker Discovery for Breast Cancer Metastasis from Gene Expression and Protein Interaction Data Using Error-tolerant Pattern Mining” at...Jiawei Han¶ ∗Microsoft, India . Email: gmanish@microsoft.com †State University of New York at Buffalo. Email: jing@buffalo.edu ‡University of California

  17. Data-driven discovery of new Dirac semimetal materials

    NASA Astrophysics Data System (ADS)

    Yan, Qimin; Chen, Ru; Neaton, Jeffrey

    In recent years, a significant amount of materials property data from high-throughput computations based on density functional theory (DFT) and the application of database technologies have enabled the rise of data-driven materials discovery. In this work, we initiate the extension of the data-driven materials discovery framework to the realm of topological semimetal materials and to accelerate the discovery of novel Dirac semimetals. We implement current available and develop new workflows to data-mine the Materials Project database for novel Dirac semimetals with desirable band structures and symmetry protected topological properties. This data-driven effort relies on the successful development of several automatic data generation and analysis tools, including a workflow for the automatic identification of topological invariants and pattern recognition techniques to find specific features in a massive number of computed band structures. Utilizing this approach, we successfully identified more than 15 novel Dirac point and Dirac nodal line systems that have not been theoretically predicted or experimentally identified. This work is supported by the Materials Project Predictive Modeling Center through the U.S. Department of Energy, Office of Basic Energy Sciences, Materials Sciences and Engineering Division, under Contract No. DE-AC02-05CH11231.

  18. Cracking the regulatory code of biosynthetic gene clusters as a strategy for natural product discovery.

    PubMed

    Rigali, Sébastien; Anderssen, Sinaeda; Naômé, Aymeric; van Wezel, Gilles P

    2018-01-05

    The World Health Organization (WHO) describes antibiotic resistance as "one of the biggest threats to global health, food security, and development today", as the number of multi- and pan-resistant bacteria is rising dangerously. Acquired resistance phenomena also impair antifungals, antivirals, anti-cancer drug therapy, while herbicide resistance in weeds threatens the crop industry. On the positive side, it is likely that the chemical space of natural products goes far beyond what has currently been discovered. This idea is fueled by genome sequencing of microorganisms which unveiled numerous so-called cryptic biosynthetic gene clusters (BGCs), many of which are transcriptionally silent under laboratory culture conditions, and by the fact that most bacteria cannot yet be cultivated in the laboratory. However, brute force antibiotic discovery does not yield the same results as it did in the past, and researchers have had to develop creative strategies in order to unravel the hidden potential of microorganisms such as Streptomyces and other antibiotic-producing microorganisms. Identifying the cis elements and their corresponding transcription factors(s) involved in the control of BGCs through bioinformatic approaches is a promising strategy. Theoretically, we are a few 'clicks' away from unveiling the culturing conditions or genetic changes needed to activate the production of cryptic metabolites or increase the production yield of known compounds to make them economically viable. In this opinion article, we describe and illustrate the idea beyond 'cracking' the regulatory code for natural product discovery, by presenting a series of proofs of concept, and discuss what still should be achieved to increase the rate of success of this strategy. Copyright © 2018 Elsevier Inc. All rights reserved.

  19. Discovery informatics in biological and biomedical sciences: research challenges and opportunities.

    PubMed

    Honavar, Vasant

    2015-01-01

    New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).

  20. Phenotype discovery by gene expression profiling: mapping of biological processes linked to BMP-2-mediated osteoblast differentiation.

    PubMed

    Balint, Eva; Lapointe, David; Drissi, Hicham; van der Meijden, Caroline; Young, Daniel W; van Wijnen, Andre J; Stein, Janet L; Stein, Gary S; Lian, Jane B

    2003-05-15

    osteogenic phenotype is recognized by 8 h, reflected by downregulation of most myogenic-related genes and induction of a spectrum of signaling proteins and enzymes facilitating synthesis and assembly of an extracellular skeletal environment. These genes included collagens Type I and VI and the small leucine rich repeat family of proteoglycans (e.g., decorin, biglycan, osteomodulin, fibromodulin, and osteoadherin/osteoglycin) that reached peak expression at 24 h. With extracellular matrix development, the bone phenotype was further established from 16 to 24 h by induction of genes for cell adhesion and communication and enzymes that organize the bone ECM. Our microarray analysis resulted in the discovery of a class of genes, initially described in relation to differentiation of astrocytes and oligodendrocytes that are functionally coupled to signals for cellular extensions. They include nexin, neuropilin, latexin, neuroglian, neuron specific gene 1, and Ulip; suggesting novel roles for these genes in the bone microenvironment. This global analysis identified a multistage molecular and cellular cascade that supports BMP-2-mediated osteoblast differentiation. Copyright 2003 Wiley-Liss, Inc.

  1. Using the TIGR gene index databases for biological discovery.

    PubMed

    Lee, Yuandan; Quackenbush, John

    2003-11-01

    The TIGR Gene Index web pages provide access to analyses of ESTs and gene sequences for nearly 60 species, as well as a number of resources derived from these. Each species-specific database is presented using a common format with a homepage. A variety of methods exist that allow users to search each species-specific database. Methods implemented currently include nucleotide or protein sequence queries using WU-BLAST, text-based searches using various sequence identifiers, searches by gene, tissue and library name, and searches using functional classes through Gene Ontology assignments. This protocol provides guidance for using the Gene Index Databases to extract information.

  2. SNP discovery in the bovine milk transcriptome using RNA-Seq technology.

    PubMed

    Cánovas, Angela; Rincon, Gonzalo; Islas-Trejo, Alma; Wickramasinghe, Saumya; Medrano, Juan F

    2010-12-01

    High-throughput sequencing of RNA (RNA-Seq) was developed primarily to analyze global gene expression in different tissues. However, it also is an efficient way to discover coding SNPs. The objective of this study was to perform a SNP discovery analysis in the milk transcriptome using RNA-Seq. Seven milk samples from Holstein cows were analyzed by sequencing cDNAs using the Illumina Genome Analyzer system. We detected 19,175 genes expressed in milk samples corresponding to approximately 70% of the total number of genes analyzed. The SNP detection analysis revealed 100,734 SNPs in Holstein samples, and a large number of those corresponded to differences between the Holstein breed and the Hereford bovine genome assembly Btau4.0. The number of polymorphic SNPs within Holstein cows was 33,045. The accuracy of RNA-Seq SNP discovery was tested by comparing SNPs detected in a set of 42 candidate genes expressed in milk that had been resequenced earlier using Sanger sequencing technology. Seventy of 86 SNPs were detected using both RNA-Seq and Sanger sequencing technologies. The KASPar Genotyping System was used to validate unique SNPs found by RNA-Seq but not observed by Sanger technology. Our results confirm that analyzing the transcriptome using RNA-Seq technology is an efficient and cost-effective method to identify SNPs in transcribed regions. This study creates guidelines to maximize the accuracy of SNP discovery and prevention of false-positive SNP detection, and provides more than 33,000 SNPs located in coding regions of genes expressed during lactation that can be used to develop genotyping platforms to perform marker-trait association studies in Holstein cattle.

  3. Regulators of G-protein signaling and their Gα substrates: promises and challenges in their use as drug discovery targets.

    PubMed

    Kimple, Adam J; Bosch, Dustin E; Giguère, Patrick M; Siderovski, David P

    2011-09-01

    Because G-protein coupled receptors (GPCRs) continue to represent excellent targets for the discovery and development of small-molecule therapeutics, it is posited that additional protein components of the signal transduction pathways emanating from activated GPCRs themselves are attractive as drug discovery targets. This review considers the drug discovery potential of two such components: members of the "regulators of G-protein signaling" (RGS protein) superfamily, as well as their substrates, the heterotrimeric G-protein α subunits. Highlighted are recent advances, stemming from mouse knockout studies and the use of "RGS-insensitivity" and fast-hydrolysis mutations to Gα, in our understanding of how RGS proteins selectively act in (patho)physiologic conditions controlled by GPCR signaling and how they act on the nucleotide cycling of heterotrimeric G-proteins in shaping the kinetics and sensitivity of GPCR signaling. Progress is documented regarding recent activities along the path to devising screening assays and chemical probes for the RGS protein target, not only in pursuits of inhibitors of RGS domain-mediated acceleration of Gα GTP hydrolysis but also to embrace the potential of finding allosteric activators of this RGS protein action. The review concludes in considering the Gα subunit itself as a drug target, as brought to focus by recent reports of activating mutations to GNAQ and GNA11 in ocular (uveal) melanoma. We consider the likelihood of several strategies for antagonizing the function of these oncogene alleles and their gene products, including the use of RGS proteins with Gα(q) selectivity.

  4. The Emory Chemical Biology Discovery Center: leveraging academic innovation to advance novel targets through HTS and beyond.

    PubMed

    Johns, Margaret A; Meyerkord-Belton, Cheryl L; Du, Yuhong; Fu, Haian

    2014-03-01

    The Emory Chemical Biology Discovery Center (ECBDC) aims to accelerate high throughput biology and translation of biomedical research discoveries into therapeutic targets and future medicines by providing high throughput research platforms to scientific collaborators worldwide. ECBDC research is focused at the interface of chemistry and biology, seeking to fundamentally advance understanding of disease-related biology with its HTS/HCS platforms and chemical tools, ultimately supporting drug discovery. Established HTS/HCS capabilities, university setting, and expertise in diverse assay formats, including protein-protein interaction interrogation, have enabled the ECBDC to contribute to national chemical biology efforts, empower translational research, and serve as a training ground for young scientists. With these resources, the ECBDC is poised to leverage academic innovation to advance biology and therapeutic discovery.

  5. Drug discovery strategies to outer membrane targets in Gram-negative pathogens.

    PubMed

    Brown, Dean G

    2016-12-15

    This review will cover selected recent examples of drug discovery strategies which target the outer membrane (OM) of Gram-negative bacteria either by disruption of outer membrane function or by inhibition of essential gene products necessary for outer membrane assembly. Significant advances in pathway elucidation, structural biology and molecular inhibitor designs have created new opportunities for drug discovery within this target-class space. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. A New In Vivo Screening Paradigm to Accelerate Antimalarial Drug Discovery

    PubMed Central

    Jiménez-Díaz, María Belén; Viera, Sara; Ibáñez, Javier; Mulet, Teresa; Magán-Marchal, Noemí; Garuti, Helen; Gómez, Vanessa; Cortés-Gil, Lorena; Martínez, Antonio; Ferrer, Santiago; Fraile, María Teresa; Calderón, Félix; Fernández, Esther; Shultz, Leonard D.; Leroy, Didier; Wilson, David M.; García-Bustos, José Francisco; Gamo, Francisco Javier; Angulo-Barturen, Iñigo

    2013-01-01

    The emergence of resistance to available antimalarials requires the urgent development of new medicines. The recent disclosure of several thousand compounds active in vitro against the erythrocyte stage of Plasmodium falciparum has been a major breakthrough, though converting these hits into new medicines challenges current strategies. A new in vivo screening concept was evaluated as a strategy to increase the speed and efficiency of drug discovery projects in malaria. The new in vivo screening concept was developed based on human disease parameters, i.e. parasitemia in the peripheral blood of patients on hospital admission and parasite reduction ratio (PRR), which were allometrically down-scaled into P. berghei-infected mice. Mice with an initial parasitemia (P0) of 1.5% were treated orally for two consecutive days and parasitemia measured 24 h after the second dose. The assay was optimized for detection of compounds able to stop parasite replication (PRR = 1) or induce parasite clearance (PRR >1) with statistical power >99% using only two mice per experimental group. In the P. berghei in vivo screening assay, the PRR of a set of eleven antimalarials with different mechanisms of action correlated with human-equivalent data. Subsequently, 590 compounds from the Tres Cantos Antimalarial Set with activity in vitro against P. falciparum were tested at 50 mg/kg (orally) in an assay format that allowed the evaluation of hundreds of compounds per month. The rate of compounds with detectable efficacy was 11.2% and about one third of active compounds showed in vivo efficacy comparable with the most potent antimalarials used clinically. High-throughput, high-content in vivo screening could rapidly select new compounds, dramatically speeding up the discovery of new antimalarial medicines. A global multilateral collaborative project aimed at screening the significant chemical diversity within the antimalarial in vitro hits described in the literature is a feasible task

  7. An analysis of gene expression in PTSD implicates genes involved in the glucocorticoid receptor pathway and neural responses to stress

    PubMed Central

    Logue, Mark W.; Smith, Alicia K.; Baldwin, Clinton; Wolf, Erika J.; Guffanti, Guia; Ratanatharathorn, Andrew; Stone, Annjanette; Schichman, Steven A.; Humphries, Donald; Binder, Elisabeth B.; Arloth, Janine; Menke, Andreas; Uddin, Monica; Wildman, Derek; Galea, Sandro; Aiello, Allison E.; Koenen, Karestan C.; Miller, Mark W.

    2015-01-01

    We examined the association between posttraumatic stress disorder (PTSD) and gene expression using whole blood samples from a cohort of trauma-exposed white non-Hispanic male veterans (115 cases and 28 controls). 10,264 probes of genes and gene transcripts were analyzed. We found 41 that were differentially expressed in PTSD cases versus controls (multiple-testing corrected p<0.05). The most significant was DSCAM, a neurological gene expressed widely in the developing brain and in the amygdala and hippocampus of the adult brain. We then examined the 41 differentially expressed genes in a meta-analysis using two replication cohorts and found significant associations with PTSD for 7 of the 41 (p<0.05), one of which (ATP6AP1L) survived multiple-testing correction. There was also broad evidence of overlap across the discovery and replication samples for the entire set of genes implicated in the discovery data based on the direction of effect and an enrichment of p<0.05 significant probes beyond what would be expected under the null. Finally, we found that the set of differentially expressed genes from the discovery sample was enriched for genes responsive to glucocorticoid signaling with most showing reduced expression in PTSD cases compared to controls. PMID:25867994

  8. A high-resolution network model for global gene regulation in Mycobacterium tuberculosis

    PubMed Central

    Peterson, Eliza J.R.; Reiss, David J.; Turkarslan, Serdar; Minch, Kyle J.; Rustad, Tige; Plaisier, Christopher L.; Longabaugh, William J.R.; Sherman, David R.; Baliga, Nitin S.

    2014-01-01

    The resilience of Mycobacterium tuberculosis (MTB) is largely due to its ability to effectively counteract and even take advantage of the hostile environments of a host. In order to accelerate the discovery and characterization of these adaptive mechanisms, we have mined a compendium of 2325 publicly available transcriptome profiles of MTB to decipher a predictive, systems-scale gene regulatory network model. The resulting modular organization of 98% of all MTB genes within this regulatory network was rigorously tested using two independently generated datasets: a genome-wide map of 7248 DNA-binding locations for 143 transcription factors (TFs) and global transcriptional consequences of overexpressing 206 TFs. This analysis has discovered specific TFs that mediate conditional co-regulation of genes within 240 modules across 14 distinct environmental contexts. In addition to recapitulating previously characterized regulons, we discovered 454 novel mechanisms for gene regulation during stress, cholesterol utilization and dormancy. Significantly, 183 of these mechanisms act uniquely under conditions experienced during the infection cycle to regulate diverse functions including 23 genes that are essential to host-pathogen interactions. These and other insights underscore the power of a rational, model-driven approach to unearth novel MTB biology that operates under some but not all phases of infection. PMID:25232098

  9. May I Cut in? Gene Editing Approaches in Human Induced Pluripotent Stem Cells.

    PubMed

    Brookhouser, Nicholas; Raman, Sreedevi; Potts, Christopher; Brafman, David A

    2017-02-06

    In the decade since Yamanaka and colleagues described methods to reprogram somatic cells into a pluripotent state, human induced pluripotent stem cells (hiPSCs) have demonstrated tremendous promise in numerous disease modeling, drug discovery, and regenerative medicine applications. More recently, the development and refinement of advanced gene transduction and editing technologies have further accelerated the potential of hiPSCs. In this review, we discuss the various gene editing technologies that are being implemented with hiPSCs. Specifically, we describe the emergence of technologies including zinc-finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN), and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 that can be used to edit the genome at precise locations, and discuss the strengths and weaknesses of each of these technologies. In addition, we present the current applications of these technologies in elucidating the mechanisms of human development and disease, developing novel and effective therapeutic molecules, and engineering cell-based therapies. Finally, we discuss the emerging technological advances in targeted gene editing methods.

  10. May I Cut in? Gene Editing Approaches in Human Induced Pluripotent Stem Cells

    PubMed Central

    Brookhouser, Nicholas; Raman, Sreedevi; Potts, Christopher; Brafman, David. A.

    2017-01-01

    In the decade since Yamanaka and colleagues described methods to reprogram somatic cells into a pluripotent state, human induced pluripotent stem cells (hiPSCs) have demonstrated tremendous promise in numerous disease modeling, drug discovery, and regenerative medicine applications. More recently, the development and refinement of advanced gene transduction and editing technologies have further accelerated the potential of hiPSCs. In this review, we discuss the various gene editing technologies that are being implemented with hiPSCs. Specifically, we describe the emergence of technologies including zinc-finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN), and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 that can be used to edit the genome at precise locations, and discuss the strengths and weaknesses of each of these technologies. In addition, we present the current applications of these technologies in elucidating the mechanisms of human development and disease, developing novel and effective therapeutic molecules, and engineering cell-based therapies. Finally, we discuss the emerging technological advances in targeted gene editing methods. PMID:28178187

  11. Zebrafish as tools for drug discovery.

    PubMed

    MacRae, Calum A; Peterson, Randall T

    2015-10-01

    The zebrafish has become a prominent vertebrate model for disease and has already contributed to several examples of successful phenotype-based drug discovery. For the zebrafish to become useful in drug development more broadly, key hurdles must be overcome, including a more comprehensive elucidation of the similarities and differences between human and zebrafish biology. Recent studies have begun to establish the capabilities and limitations of zebrafish for disease modelling, drug screening, target identification, pharmacology, and toxicology. As our understanding increases and as the technologies for manipulating zebrafish improve, it is hoped that the zebrafish will have a key role in accelerating the emergence of precision medicine.

  12. Transcriptome Analysis and Discovery of Genes Involved in Immune Pathways from Hepatopancreas of Microbial Challenged Mitten Crab Eriocheir sinensis

    PubMed Central

    Li, Xihong; Cui, Zhaoxia; Liu, Yuan; Song, Chengwen; Shi, Guohui

    2013-01-01

    Background The Chinese mitten crab Eriocheir sinensis is an important economic crustacean and has been seriously attacked by various diseases, which requires more and more information for immune relevant genes on genome background. Recently, high-throughput RNA sequencing (RNA-seq) technology provides a powerful and efficient method for transcript analysis and immune gene discovery. Methods/Principal Findings A cDNA library from hepatopancreas of E. sinensis challenged by a mixture of three pathogen strains (Gram-positive bacteria Micrococcus luteus, Gram-negative bacteria Vibrio alginolyticus and fungi Pichia pastoris; 108 cfu·mL−1) was constructed and randomly sequenced using Illumina technique. Totally 39.76 million clean reads were assembled to 70,300 unigenes. After ruling out short-length and low-quality sequences, 52,074 non-redundant unigenes were compared to public databases for homology searching and 17,617 of them showed high similarity to sequences in NCBI non-redundant protein (Nr) database. For function classification and pathway assignment, 18,734 (36.00%) unigenes were categorized to three Gene Ontology (GO) categories, 12,243 (23.51%) were classified to 25 Clusters of Orthologous Groups (COG), and 8,983 (17.25%) were assigned to six Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Potentially, 24, 14, 47 and 132 unigenes were characterized to be involved in Toll, IMD, JAK-STAT and MAPK pathways, respectively. Conclusions/Significance This is the first systematical transcriptome analysis of components relating to innate immune pathways in E. sinensis. Functional genes and putative pathways identified here will contribute to better understand immune system and prevent various diseases in crab. PMID:23874555

  13. Lessons learned from gene identification studies in Mendelian epilepsy disorders

    PubMed Central

    Hardies, Katia; Weckhuysen, Sarah; De Jonghe, Peter; Suls, Arvid

    2016-01-01

    Next-generation sequencing (NGS) technologies are now routinely used for gene identification in Mendelian disorders. Setting up cost-efficient NGS projects and managing the large amount of variants remains, however, a challenging job. Here we provide insights in the decision-making processes before and after the use of NGS in gene identification studies. Genetic factors are thought to have a role in ~70% of all epilepsies, and a variety of inheritance patterns have been described for seizure-associated gene defects. We therefore chose epilepsy as disease model and selected 35 NGS studies that focused on patients with a Mendelian epilepsy disorder. The strategies used for gene identification and their respective outcomes were reviewed. High-throughput NGS strategies have led to the identification of several new epilepsy-causing genes, enlarging our knowledge on both known and novel pathomechanisms. NGS findings have furthermore extended the awareness of phenotypical and genetic heterogeneity. By discussing recent studies we illustrate: (I) the power of NGS for gene identification in Mendelian disorders, (II) the accelerating pace in which this field evolves, and (III) the considerations that have to be made when performing NGS studies. Nonetheless, the enormous rise in gene discovery over the last decade, many patients and families included in gene identification studies still remain without a molecular diagnosis; hence, further genetic research is warranted. On the basis of successful NGS studies in epilepsy, we discuss general approaches to guide human geneticists and clinicians in setting up cost-efficient gene identification NGS studies. PMID:26603999

  14. Discovery of four recessive developmental disorders using probabilistic genotype and phenotype matching among 4,125 families

    PubMed Central

    Ansari, Morad; Balasubramanian, Meena; Blyth, Moira; Brady, Angela F.; Clayton, Stephen; Cole, Trevor; Deshpande, Charu; Fitzgerald, Tomas W.; Foulds, Nicola; Francis, Richard; Gabriel, George; Gerety, Sebastian S.; Goodship, Judith; Hobson, Emma; Jones, Wendy D.; Joss, Shelagh; King, Daniel; Klena, Nikolai; Kumar, Ajith; Lees, Melissa; Lelliott, Chris; Lord, Jenny; McMullan, Dominic; O'Regan, Mary; Osio, Deborah; Piombo, Virginia; Prigmore, Elena; Rajan, Diana; Rosser, Elisabeth; Sifrim, Alejandro; Smith, Audrey; Swaminathan, Ganesh J.; Turnpenny, Peter; Whitworth, James; Wright, Caroline F.; Firth, Helen V.; Barrett, Jeffrey C.; Lo, Cecilia W.; FitzPatrick, David R.; Hurles, Matthew E.

    2018-01-01

    Discovery of most autosomal recessive disease genes has involved analysis of large, often consanguineous, multiplex families or small cohorts of unrelated individuals with a well-defined clinical condition. Discovery of novel dominant causes of rare, genetically heterogenous developmental disorders has been revolutionized by exome analysis of large cohorts of phenotypically diverse parent-offspring trios 1,2. Here we analysed 4,125 families with diverse, rare, genetically heterogeneous developmental disorders and identified four novel autosomal recessive disorders. These four disorders were identified by integrating Mendelian filtering (identifying probands with rare biallelic putatively damaging variants in the same gene) with statistical assessments of (i) the likelihood of sampling the observed genotypes from the general population, and (ii) the phenotypic similarity of patients with the same recessive candidate gene. This new paradigm promises to catalyse discovery of novel recessive disorders, especially those with less consistent or nonspecific clinical presentations, and those caused predominantly by compound heterozygous genotypes. PMID:26437029

  15. Discovery of four recessive developmental disorders using probabilistic genotype and phenotype matching among 4,125 families.

    PubMed

    Akawi, Nadia; McRae, Jeremy; Ansari, Morad; Balasubramanian, Meena; Blyth, Moira; Brady, Angela F; Clayton, Stephen; Cole, Trevor; Deshpande, Charu; Fitzgerald, Tomas W; Foulds, Nicola; Francis, Richard; Gabriel, George; Gerety, Sebastian S; Goodship, Judith; Hobson, Emma; Jones, Wendy D; Joss, Shelagh; King, Daniel; Klena, Nikolai; Kumar, Ajith; Lees, Melissa; Lelliott, Chris; Lord, Jenny; McMullan, Dominic; O'Regan, Mary; Osio, Deborah; Piombo, Virginia; Prigmore, Elena; Rajan, Diana; Rosser, Elisabeth; Sifrim, Alejandro; Smith, Audrey; Swaminathan, Ganesh J; Turnpenny, Peter; Whitworth, James; Wright, Caroline F; Firth, Helen V; Barrett, Jeffrey C; Lo, Cecilia W; FitzPatrick, David R; Hurles, Matthew E

    2015-11-01

    Discovery of most autosomal recessive disease-associated genes has involved analysis of large, often consanguineous multiplex families or small cohorts of unrelated individuals with a well-defined clinical condition. Discovery of new dominant causes of rare, genetically heterogeneous developmental disorders has been revolutionized by exome analysis of large cohorts of phenotypically diverse parent-offspring trios. Here we analyzed 4,125 families with diverse, rare and genetically heterogeneous developmental disorders and identified four new autosomal recessive disorders. These four disorders were identified by integrating Mendelian filtering (selecting probands with rare, biallelic and putatively damaging variants in the same gene) with statistical assessments of (i) the likelihood of sampling the observed genotypes from the general population and (ii) the phenotypic similarity of patients with recessive variants in the same candidate gene. This new paradigm promises to catalyze the discovery of novel recessive disorders, especially those with less consistent or nonspecific clinical presentations and those caused predominantly by compound heterozygous genotypes.

  16. Water deficits accelerate ripening and induce changes in gene expression regulating flavonoid biosynthesis in grape berries.

    PubMed

    Castellarin, Simone D; Matthews, Mark A; Di Gaspero, Gabriele; Gambetta, Gregory A

    2007-12-01

    Water deficits consistently promote higher concentrations of anthocyanins in red winegrapes and their wines. However, controversy remains as to whether there is any direct effect on berry metabolism other than inhibition of growth. Early (ED) and late (LD) season water deficits, applied before or after the onset of ripening (veraison), were imposed on field grown Vitis vinifera "Cabernet Sauvignon", and the responses of gene expression in the flavonoid pathway and their corresponding metabolites were determined. ED accelerated sugar accumulation and the onset of anthocyanin synthesis. Both ED and LD increased anthocyanin accumulation after veraison. Expression profiling revealed that the increased anthocyanin accumulation resulted from earlier and greater expression of the genes controlling flux through the anthocyanin biosynthetic pathway, including F3H, DFR, UFGT and GST. Increases in total anthocyanins resulted predominantly from an increase of 3'4'5'-hydroxylated forms through the differential regulation of F3'H and F3'5'H. There were limited effects on proanthocyanidin, other flavonols, and on expression of genes committed to their synthesis. These results demonstrate that manipulation of abiotic stress through applied water deficits not only modulates compositional changes during berry ripening, but also alters the timing of particular aspects of the ripening process.

  17. Comparative Oncogenomics for Peripheral Nerve Sheath Cancer Gene Discovery

    DTIC Science & Technology

    2015-06-01

    neurofibromas and MPNSTs, establish gene signatures defining distinct tumor subtypes and functionally test the role of selected driver mutations ...allografted tumor cells, and a variety of in vitro functional assays. We will validate the relevance of these mutated mouse genes in human neurofibromas...and MPNSTs by determining whether these same genes are mutated in human tumors. 15. SUBJECT TERMS Nothing listed 16. SECURITY CLASSIFICATION OF: 17

  18. Leveraging ecological theory to guide natural product discovery.

    PubMed

    Smanski, Michael J; Schlatter, Daniel C; Kinkel, Linda L

    2016-03-01

    Technological improvements have accelerated natural product (NP) discovery and engineering to the point that systematic genome mining for new molecules is on the horizon. NP biosynthetic potential is not equally distributed across organisms, environments, or microbial life histories, but instead is enriched in a number of prolific clades. Also, NPs are not equally abundant in nature; some are quite common and others markedly rare. Armed with this knowledge, random 'fishing expeditions' for new NPs are increasingly harder to justify. Understanding the ecological and evolutionary pressures that drive the non-uniform distribution of NP biosynthesis provides a rational framework for the targeted isolation of strains enriched in new NP potential. Additionally, ecological theory leads to testable hypotheses regarding the roles of NPs in shaping ecosystems. Here we review several recent strain prioritization practices and discuss the ecological and evolutionary underpinnings for each. Finally, we offer perspectives on leveraging microbial ecology and evolutionary biology for future NP discovery.

  19. Unbiased approaches to biomarker discovery in neurodegenerative diseases

    PubMed Central

    Chen-Plotkin, Alice S.

    2014-01-01

    Neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and frontotemporal dementia have several important features in common. They are progressive, they affect a relatively inaccessible organ, and we have no disease-modifying therapies for them. For these brain-based diseases, current diagnosis and evaluation of disease severity rely almost entirely on clinical examination, which may only be a rough approximation of disease state. Thus, the development of biomarkers – objective, relatively easily measured and precise indicators of pathogenic processes – could improve patient care and accelerate therapeutic discovery. Yet existing, rigorously tested neurodegenerative disease biomarkers are few, and even fewer biomarkers have translated into clinical use. To find new biomarkers for these diseases, an unbiased, high-throughput screening approach may be needed. In this review, I will describe the potential utility of such an approach to biomarker discovery, using Parkinson’s disease as a case example. PMID:25442938

  20. De-novo discovery of differentially abundant transcription factor binding sites including their positional preference.

    PubMed

    Keilwagen, Jens; Grau, Jan; Paponov, Ivan A; Posch, Stefan; Strickert, Marc; Grosse, Ivo

    2011-02-10

    Transcription factors are a main component of gene regulation as they activate or repress gene expression by binding to specific binding sites in promoters. The de-novo discovery of transcription factor binding sites in target regions obtained by wet-lab experiments is a challenging problem in computational biology, which has not been fully solved yet. Here, we present a de-novo motif discovery tool called Dispom for finding differentially abundant transcription factor binding sites that models existing positional preferences of binding sites and adjusts the length of the motif in the learning process. Evaluating Dispom, we find that its prediction performance is superior to existing tools for de-novo motif discovery for 18 benchmark data sets with planted binding sites, and for a metazoan compendium based on experimental data from micro-array, ChIP-chip, ChIP-DSL, and DamID as well as Gene Ontology data. Finally, we apply Dispom to find binding sites differentially abundant in promoters of auxin-responsive genes extracted from Arabidopsis thaliana microarray data, and we find a motif that can be interpreted as a refined auxin responsive element predominately positioned in the 250-bp region upstream of the transcription start site. Using an independent data set of auxin-responsive genes, we find in genome-wide predictions that the refined motif is more specific for auxin-responsive genes than the canonical auxin-responsive element. In general, Dispom can be used to find differentially abundant motifs in sequences of any origin. However, the positional distribution learned by Dispom is especially beneficial if all sequences are aligned to some anchor point like the transcription start site in case of promoter sequences. We demonstrate that the combination of searching for differentially abundant motifs and inferring a position distribution from the data is beneficial for de-novo motif discovery. Hence, we make the tool freely available as a component of the open

  1. Natural products discovery from micro-organisms in the post-genome era.

    PubMed

    Ikeda, Haruo

    2017-01-01

    With the decision to award the Nobel Prize in Physiology or Medicine to Drs. S. Ōmura, W.C. Campbell, and Y. Tu, the importance and usefulness of natural drug discovery and development have been revalidated. Since the end of the twentieth century, many genome analyses of organisms have been conducted, and accordingly, numerous microbial genomes have been decoded. In particular, genomic studies of actinomycetes, micro-organisms that readily produce natural products, led to the discovery of biosynthetic gene clusters responsible for producing natural products. New explorations for natural products through a comprehensive approach combining genomic information with conventional methods show great promise for the discovery of new natural products and even systematic generation of unnaturally occurring compounds.

  2. Transcriptome Analysis of the Portunus trituberculatus: De Novo Assembly, Growth-Related Gene Identification and Marker Discovery

    PubMed Central

    Lv, Jianjian; Liu, Ping; Gao, Baoquan; Wang, Yu; Wang, Zheng; Chen, Ping; Li, Jian

    2014-01-01

    Background The swimming crab, Portunus trituberculatus, is an important farmed species in China, has been attracting extensive studies, which require more and more genome background knowledge. To date, the sequencing of its whole genome is unavailable and transcriptomic information is also scarce for this species. In the present study, we performed de novo transcriptome sequencing to produce a comprehensive transcript dataset for major tissues of Portunus trituberculatus by the Illumina paired-end sequencing technology. Results Total RNA was isolated from eyestalk, gill, heart, hepatopancreas and muscle. Equal quantities of RNA from each tissue were pooled to construct a cDNA library. Using the Illumina paired-end sequencing technology, we generated a total of 120,137 transcripts with an average length of 1037 bp. Further assembly analysis showed that all contigs contributed to 87,100 unigenes, of these, 16,029 unigenes (18.40% of the total) can be matched in the GenBank non-redundant database. Potential genes and their functions were predicted by GO, KEGG pathway mapping and COG analysis. Based on our sequence analysis and published literature, many putative genes with fundamental roles in growth and muscle development, including actin, myosin, tropomyosin, troponin and other potentially important candidate genes were identified for the first time in this specie. Furthermore, 22,673 SSRs and 66,191 high-confidence SNPs were identified in this EST dataset. Conclusion The transcriptome provides an invaluable new data for a functional genomics resource and future biological research in Portunus trituberculatus. The data will also instruct future functional studies to manipulate or select for genes influencing growth that should find practical applications in aquaculture breeding programs. The molecular markers identified in this study will provide a material basis for future genetic linkage and quantitative trait loci analyses, and will be essential for accelerating

  3. Novel Directions for Diabetes Mellitus Drug Discovery

    PubMed Central

    Maiese, Kenneth; Chong, Zhao Zhong; Shang, Yan Chen; Wang, Shaohui

    2012-01-01

    Introduction Diabetes mellitus impacts almost 200 million individuals worldwide and leads to debilitating complications. New avenues of drug discovery must target the underlying cellular processes of oxidative stress, apoptosis, autophagy, and inflammation that can mediate multi-system pathology during diabetes mellitus. Areas Covered We examine novel directions for drug discovery that involve the β-nicotinamide adenine dinucleotide (NAD+) precursor nicotinamide, the cytokine erythropoietin, the NAD+-dependent protein histone deacetylase SIRT1, the serine/threonine-protein kinase mammalian target of rapamycin (mTOR), and the wingless pathway. Implications for the targeting of these pathways that oversee gluconeogenic genes, insulin signaling and resistance, fatty acid beta-oxidation, inflammation, and cellular survival are presented. Expert Opinion Nicotinamide, erythropoietin, and the downstram pathways of SIRT1, mTOR, forkhead transcription factors, and wingless signaling offer exciting prospects for novel directions of drug discovery for the treatment of metabolic disorders. Future investigations must dissect the complex relationship and fine modulation of these pathways for the successful translation of robust reparative and regenerative strategies against diabetes mellitus and the complications of this disorder. PMID:23092114

  4. Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

    PubMed

    Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

    2015-01-01

    In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

  5. Collaborative Model for Acceleration of Individualized Therapy of Colon Cancer

    DTIC Science & Technology

    2015-12-01

    preclinical models are representative of actual patient samples and may be useful in early drug development and predictive biomarker discovery...Award Number: W81XWH-11-1-0527 TITLE: Collaborative Model for Acceleration of Individualized Therapy of Colon Cancer PRINCIPAL INVESTIGATOR: Aik...Choon Tan CONTRACTING ORGANIZATION: UNIVERSITY OF COLORADO, DENVER AURORA, CO 80045-2505 REPORT DATE: December 2015 TYPE OF REPORT: FINAL REPORT

  6. The Story of Serum Prothrombin Conversion Accelerator, Proconvertin, Stable Factor, Cothromboplastin, Prothrombin Accelerator or Autoprothrombin I, and Their Subsequent Merging into Factor VII.

    PubMed

    Girolami, Antonio; Cosi, Elisabetta; Santarossa, Claudia; Ferrari, Silvia; Luigia Randi, Maria

    2015-06-01

    Factor VII (FVII) deficiency is one of the two congenital coagulation disorders that was not discovered by the description of a new bleeding patient whose clotting pattern did not fit the blood coagulation knowledge of the time (the other is factor XIII deficiency). The existence of an additional factor capable of accelerating the conversion of prothrombin into thrombin was suspected before 1951, the year in which the first family with FVII deficiency was discovered. As several investigators were involved in the discovery of FVII deficiency from both sides of the Atlantic, several different names were tentatively suggested to define this entity, namely stable factor (in contrast with labile factor or FV), cothromboplastin, proconvertin, serum prothrombin conversion accelerator, prothrombin acceleration, and autoprothrombin I. The last term was proposed by those who denied the existence of this new entity, which was instead considered to be a derivate of prothrombin activation, namely autoprothrombin. The description of several families, from all over the world, of the same defect, however clearly demonstrated the singularity of the condition. Factor VII was then proposed to define this protein. In subsequent years, several variants were described with peculiar reactivity toward tissue thromboplastins of different origin. Molecular biology techniques demonstrated several gene mutations, usually missense mutations, often involving exon 8 of the FVII gene. Later studies dealt with the relation of FVII with tissue factor and activated FVII (FVIIa). The evaluation of circulating FVIIa was made possible by the use of a truncated form of tissue factor, which is only sensitive to FVIIa present in the circulation. The development of FVII concentrates, both plasma derived and recombinant, has facilitated therapeutic management of FVII-deficient patients. The use of FVIIa concentrates was noted to be associated with the occasional occurrence of thrombotic events, mainly

  7. The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities

    PubMed Central

    Chong, Jessica X.; Buckingham, Kati J.; Jhangiani, Shalini N.; Boehm, Corinne; Sobreira, Nara; Smith, Joshua D.; Harrell, Tanya M.; McMillin, Margaret J.; Wiszniewski, Wojciech; Gambin, Tomasz; Coban Akdemir, Zeynep H.; Doheny, Kimberly; Scott, Alan F.; Avramopoulos, Dimitri; Chakravarti, Aravinda; Hoover-Fong, Julie; Mathews, Debra; Witmer, P. Dane; Ling, Hua; Hetrick, Kurt; Watkins, Lee; Patterson, Karynne E.; Reinier, Frederic; Blue, Elizabeth; Muzny, Donna; Kircher, Martin; Bilguvar, Kaya; López-Giráldez, Francesc; Sutton, V. Reid; Tabor, Holly K.; Leal, Suzanne M.; Gunel, Murat; Mane, Shrikant; Gibbs, Richard A.; Boerwinkle, Eric; Hamosh, Ada; Shendure, Jay; Lupski, James R.; Lifton, Richard P.; Valle, David; Nickerson, Deborah A.; Bamshad, Michael J.

    2015-01-01

    Discovering the genetic basis of a Mendelian phenotype establishes a causal link between genotype and phenotype, making possible carrier and population screening and direct diagnosis. Such discoveries also contribute to our knowledge of gene function, gene regulation, development, and biological mechanisms that can be used for developing new therapeutics. As of February 2015, 2,937 genes underlying 4,163 Mendelian phenotypes have been discovered, but the genes underlying ∼50% (i.e., 3,152) of all known Mendelian phenotypes are still unknown, and many more Mendelian conditions have yet to be recognized. This is a formidable gap in biomedical knowledge. Accordingly, in December 2011, the NIH established the Centers for Mendelian Genomics (CMGs) to provide the collaborative framework and infrastructure necessary for undertaking large-scale whole-exome sequencing and discovery of the genetic variants responsible for Mendelian phenotypes. In partnership with 529 investigators from 261 institutions in 36 countries, the CMGs assessed 18,863 samples from 8,838 families representing 579 known and 470 novel Mendelian phenotypes as of January 2015. This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype. These results provide insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelian phenotypes. Discovering the gene underlying every Mendelian phenotype will require tackling challenges such as worldwide ascertainment and phenotypic characterization of families affected by Mendelian conditions, improvement in sequencing and analytical techniques, and pervasive sharing of phenotypic and genomic data among researchers, clinicians, and families. PMID:26166479

  8. Gene Discovery in Bladder Cancer Progression using cDNA Microarrays

    PubMed Central

    Sanchez-Carbayo, Marta; Socci, Nicholas D.; Lozano, Juan Jose; Li, Wentian; Charytonowicz, Elizabeth; Belbin, Thomas J.; Prystowsky, Michael B.; Ortiz, Angel R.; Childs, Geoffrey; Cordon-Cardo, Carlos

    2003-01-01

    To identify gene expression changes along progression of bladder cancer, we compared the expression profiles of early-stage and advanced bladder tumors using cDNA microarrays containing 17,842 known genes and expressed sequence tags. The application of bootstrapping techniques to hierarchical clustering segregated early-stage and invasive transitional carcinomas into two main clusters. Multidimensional analysis confirmed these clusters and more importantly, it separated carcinoma in situ from papillary superficial lesions and subgroups within early-stage and invasive tumors displaying different overall survival. Additionally, it recognized early-stage tumors showing gene profiles similar to invasive disease. Different techniques including standard t-test, single-gene logistic regression, and support vector machine algorithms were applied to identify relevant genes involved in bladder cancer progression. Cytokeratin 20, neuropilin-2, p21, and p33ING1 were selected among the top ranked molecular targets differentially expressed and validated by immunohistochemistry using tissue microarrays (n = 173). Their expression patterns were significantly associated with pathological stage, tumor grade, and altered retinoblastoma (RB) expression. Moreover, p33ING1 expression levels were significantly associated with overall survival. Analysis of the annotation of the most significant genes revealed the relevance of critical genes and pathways during bladder cancer progression, including the overexpression of oncogenic genes such as DEK in superficial tumors or immune response genes such as Cd86 antigen in invasive disease. Gene profiling successfully classified bladder tumors based on their progression and clinical outcome. The present study has identified molecular biomarkers of potential clinical significance and critical molecular targets associated with bladder cancer progression. PMID:12875971

  9. Cultivation of Hard-To-Culture Subsurface Mercury-Resistant Bacteria and Discovery of New merA Gene Sequences▿

    PubMed Central

    Rasmussen, L. D.; Zawadsky, C.; Binnerup, S. J.; Øregaard, G.; Sørensen, S. J.; Kroer, N.

    2008-01-01

    Mercury-resistant bacteria may be important players in mercury biogeochemistry. To assess the potential for mercury reduction by two subsurface microbial communities, resistant subpopulations and their merA genes were characterized by a combined molecular and cultivation-dependent approach. The cultivation method simulated natural conditions by using polycarbonate membranes as a growth support and a nonsterile soil slurry as a culture medium. Resistant bacteria were pregrown to microcolony-forming units (mCFU) before being plated on standard medium. Compared to direct plating, culturability was increased up to 2,800 times and numbers of mCFU were similar to the total number of mercury-resistant bacteria in the soils. Denaturing gradient gel electrophoresis analysis of DNA extracted from membranes suggested stimulation of growth of hard-to-culture bacteria during the preincubation. A total of 25 different 16S rRNA gene sequences were observed, including Alpha-, Beta-, and Gammaproteobacteria; Actinobacteria; Firmicutes; and Bacteroidetes. The diversity of isolates obtained by direct plating included eight different 16S rRNA gene sequences (Alpha- and Betaproteobacteria and Actinobacteria). Partial sequencing of merA of selected isolates led to the discovery of new merA sequences. With phylum-specific merA primers, PCR products were obtained for Alpha- and Betaproteobacteria and Actinobacteria but not for Bacteroidetes and Firmicutes. The similarity to known sequences ranged between 89 and 95%. One of the sequences did not result in a match in the BLAST search. The results illustrate the power of integrating advanced cultivation methodology with molecular techniques for the characterization of the diversity of mercury-resistant populations and assessing the potential for mercury reduction in contaminated environments. PMID:18441111

  10. An accelerated assay for the identification of lifespan-extending interventions in Drosophila melanogaster

    PubMed Central

    Bauer, Johannes H.; Goupil, Stephan; Garber, Graham B.; Helfand, Stephen L.

    2004-01-01

    Recent advances in aging research have uncovered genes and genetic pathways that influence lifespan in such diverse organisms as yeast, nematodes, flies, and mice. The discovery of genes and drugs that affect lifespan has been delayed by the absence of a phenotype other than survivorship, which depends on the measurement of age at death of individuals in a population. The use of survivorship to identify genetic and pharmacological interventions that prolong life is time-consuming and requires a large number of homogeneous animals. Here, we report the development of an assay in Drosophila melanogaster using the expression of molecular biomarkers that accelerates the ability to evaluate potential lifespan-altering interventions. Coupling the expression of an age-dependent molecular biomarker to a lethal toxin reduces the time needed to perform lifespan studies by 80%. The assay recapitulates the effect of the three best known environmental life-span-extending interventions in the fly: ambient temperature, reproductive status, and calorie reduction. Single gene mutations known to extend lifespan in the fly such as Indy and rpd3 also extend lifespan in this assay. We used this assay as a screen to identify drugs that extend lifespan in flies. Lipoic acid and resveratrol were identified as being beneficial in our assay and shown to extend lifespan under normal laboratory conditions. We propose that this assay can be used to screen pharmacological as well as genetic interventions more rapidly for positive effects on lifespan. PMID:15328413

  11. GENOME-ENABLED DISCOVERY OF CARBON SEQUESTRATION GENES IN POPLAR

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    DAVIS J M

    2007-10-11

    Plants utilize carbon by partitioning the reduced carbon obtained through photosynthesis into different compartments and into different chemistries within a cell and subsequently allocating such carbon to sink tissues throughout the plant. Since the phytohormones auxin and cytokinin are known to influence sink strength in tissues such as roots (Skoog & Miller 1957, Nordstrom et al. 2004), we hypothesized that altering the expression of genes that regulate auxin-mediated (e.g., AUX/IAA or ARF transcription factors) or cytokinin-mediated (e.g., RR transcription factors) control of root growth and development would impact carbon allocation and partitioning belowground (Fig. 1 - Renewal Proposal). Specifically, themore » ARF, AUX/IAA and RR transcription factor gene families mediate the effects of the growth regulators auxin and cytokinin on cell expansion, cell division and differentiation into root primordia. Invertases (IVR), whose transcript abundance is enhanced by both auxin and cytokinin, are critical components of carbon movement and therefore of carbon allocation. Thus, we initiated comparative genomic studies to identify the AUX/IAA, ARF, RR and IVR gene families in the Populus genome that could impact carbon allocation and partitioning. Bioinformatics searches using Arabidopsis gene sequences as queries identified regions with high degrees of sequence similarities in the Populus genome. These Populus sequences formed the basis of our transgenic experiments. Transgenic modification of gene expression involving members of these gene families was hypothesized to have profound effects on carbon allocation and partitioning.« less

  12. The case for electron re-acceleration at galaxy cluster shocks

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    van Weeren, Reinout J.; Andrade-Santos, Felipe; Dawson, William A.

    On the largest scales, the Universe consists of voids and filaments making up the cosmic web. Galaxy clusters are located at the knots in this web, at the intersection of filaments. Clusters grow through accretion from these large-scale filaments and by mergers with other clusters and groups. In a growing number of galaxy clusters, elongated Mpc-sized radio sources have been found. Also known as radio relics, these regions of diffuse radio emission are thought to trace relativistic electrons in the intracluster plasma accelerated by low-Mach-number shocks generated by cluster–cluster merger events. A long-standing problem is how low-Mach-number shocks can acceleratemore » electrons so efficiently to explain the observed radio relics. Here, we report the discovery of a direct connection between a radio relic and a radio galaxy in the merging galaxy cluster Abell 3411–3412 by combining radio, X-ray and optical observations. This discovery indicates that fossil relativistic electrons from active galactic nuclei are re-accelerated at cluster shocks. Lastly, it also implies that radio galaxies play an important role in governing the non-thermal component of the intracluster medium in merging clusters.« less

  13. The case for electron re-acceleration at galaxy cluster shocks

    DOE PAGES

    van Weeren, Reinout J.; Andrade-Santos, Felipe; Dawson, William A.; ...

    2017-01-04

    On the largest scales, the Universe consists of voids and filaments making up the cosmic web. Galaxy clusters are located at the knots in this web, at the intersection of filaments. Clusters grow through accretion from these large-scale filaments and by mergers with other clusters and groups. In a growing number of galaxy clusters, elongated Mpc-sized radio sources have been found. Also known as radio relics, these regions of diffuse radio emission are thought to trace relativistic electrons in the intracluster plasma accelerated by low-Mach-number shocks generated by cluster–cluster merger events. A long-standing problem is how low-Mach-number shocks can acceleratemore » electrons so efficiently to explain the observed radio relics. Here, we report the discovery of a direct connection between a radio relic and a radio galaxy in the merging galaxy cluster Abell 3411–3412 by combining radio, X-ray and optical observations. This discovery indicates that fossil relativistic electrons from active galactic nuclei are re-accelerated at cluster shocks. Lastly, it also implies that radio galaxies play an important role in governing the non-thermal component of the intracluster medium in merging clusters.« less

  14. Harnessing the potential of natural products in drug discovery from a cheminformatics vantage point.

    PubMed

    Rodrigues, Tiago

    2017-11-15

    Natural products (NPs) present a privileged source of inspiration for chemical probe and drug design. Despite the biological pre-validation of the underlying molecular architectures and their relevance in drug discovery, the poor accessibility to NPs, complexity of the synthetic routes and scarce knowledge of their macromolecular counterparts in phenotypic screens still hinder their broader exploration. Cheminformatics algorithms now provide a powerful means of circumventing the abovementioned challenges and unlocking the full potential of NPs in a drug discovery context. Herein, I discuss recent advances in the computer-assisted design of NP mimics and how artificial intelligence may accelerate future NP-inspired molecular medicine.

  15. STS-26 Discovery, OV-103, OASIS equipment is mounted in payload bay (PLB)

    NASA Image and Video Library

    1988-04-18

    S88-37764 (18 April 1988) --- OASIS, instrumentation which will record the environment experienced by Discovery during the STS-26 Space Shuttle mission, is lowered into position for attachment to the orbiter's aft port sill. Instrumentation sensors in the payload bay which are connected to the tape recorder module will document a variety of environmental measurements during various phases of the flight including temperature, pressure, vibration, sounds, acceleration, stress, and strain. OASIS will also record data during the Flight Readiness Firing. NASA is flying OASIS aboard Discovery in support of the Inertial Upper Stage (IUS) program office of the Air Force Space Division. The system was developed by Lockheed under a NASA contract, funded by the Air Force.

  16. Discovery of Herpes B Virus-Encoded MicroRNAs▿

    PubMed Central

    Besecker, Michael I.; Harden, Mallory E.; Li, Guanglin; Wang, Xiu-Jie; Griffiths, Anthony

    2009-01-01

    Herpes B virus (BV) naturally infects macaque monkeys and is a close relative of herpes simplex virus. BV can zoonotically infect humans to cause a rapidly ascending encephalitis with ∼80% mortality. Therefore, BV is a serious danger to those who come into contact with these monkeys or their tissues and cells. MicroRNAs are regulators of gene expression, and there have been reports of virus-encoded microRNAs. We hypothesize that BV-encoded microRNAs are important for the regulation of viral and cellular genes. Herein, we report the discovery of three herpes B virus-encoded microRNAs. PMID:19144716

  17. Gene discovery in EST sequences from the wheat leaf rust fungus Puccinia triticina sexual spores, asexual spores and haustoria, compared to other rust and corn smut fungi

    PubMed Central

    2011-01-01

    Background Rust fungi are biotrophic basidiomycete plant pathogens that cause major diseases on plants and trees world-wide, affecting agriculture and forestry. Their biotrophic nature precludes many established molecular genetic manipulations and lines of research. The generation of genomic resources for these microbes is leading to novel insights into biology such as interactions with the hosts and guiding directions for breakthrough research in plant pathology. Results To support gene discovery and gene model verification in the genome of the wheat leaf rust fungus, Puccinia triticina (Pt), we have generated Expressed Sequence Tags (ESTs) by sampling several life cycle stages. We focused on several spore stages and isolated haustorial structures from infected wheat, generating 17,684 ESTs. We produced sequences from both the sexual (pycniospores, aeciospores and teliospores) and asexual (germinated urediniospores) stages of the life cycle. From pycniospores and aeciospores, produced by infecting the alternate host, meadow rue (Thalictrum speciosissimum), 4,869 and 1,292 reads were generated, respectively. We generated 3,703 ESTs from teliospores produced on the senescent primary wheat host. Finally, we generated 6,817 reads from haustoria isolated from infected wheat as well as 1,003 sequences from germinated urediniospores. Along with 25,558 previously generated ESTs, we compiled a database of 13,328 non-redundant sequences (4,506 singlets and 8,822 contigs). Fungal genes were predicted using the EST version of the self-training GeneMarkS algorithm. To refine the EST database, we compared EST sequences by BLASTN to a set of 454 pyrosequencing-generated contigs and Sanger BAC-end sequences derived both from the Pt genome, and to ESTs and genome reads from wheat. A collection of 6,308 fungal genes was identified and compared to sequences of the cereal rusts, Puccinia graminis f. sp. tritici (Pgt) and stripe rust, P. striiformis f. sp. tritici (Pst), and poplar

  18. The Next Step: 25 Discoveries That Could Change Our Lives.

    ERIC Educational Resources Information Center

    Science85, 1985

    1985-01-01

    Describes (in separate articles) 25 developments in science, technology, and medicine that have potential impact on the near future. They include discoveries related to space butterflies, drugs, twenty-first century software, experimental mathematics, brain drugs, egg development, ultrasmall microchips, the biology of birth, cancer-causing genes,…

  19. Discovery of potent, reversible MetAP2 inhibitors via fragment based drug discovery and structure based drug design-Part 2.

    PubMed

    McBride, Christopher; Cheruvallath, Zacharia; Komandla, Mallareddy; Tang, Mingnam; Farrell, Pamela; Lawson, J David; Vanderpool, Darin; Wu, Yiqin; Dougan, Douglas R; Plonowski, Artur; Holub, Corine; Larson, Chris

    2016-06-15

    Methionine aminopeptidase-2 (MetAP2) is an enzyme that cleaves an N-terminal methionine residue from a number of newly synthesized proteins. This step is required before they will fold or function correctly. Pre-clinical and clinical studies with a MetAP2 inhibitor suggest that they could be used as a novel treatment for obesity. Herein we describe the discovery of a series of pyrazolo[4,3-b]indoles as reversible MetAP2 inhibitors. A fragment-based drug discovery (FBDD) approach was used, beginning with the screening of fragment libraries to generate hits with high ligand-efficiency (LE). An indazole core was selected for further elaboration, guided by structural information. SAR from the indazole series led to the design of a pyrazolo[4,3-b]indole core and accelerated knowledge-based fragment growth resulted in potent and efficient MetAP2 inhibitors, which have shown robust and sustainable body weight loss in DIO mice when dosed orally. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Model-driven discovery of underground metabolic functions in Escherichia coli.

    PubMed

    Guzmán, Gabriela I; Utrilla, José; Nurk, Sergey; Brunk, Elizabeth; Monk, Jonathan M; Ebrahim, Ali; Palsson, Bernhard O; Feist, Adam M

    2015-01-20

    Enzyme promiscuity toward substrates has been discussed in evolutionary terms as providing the flexibility to adapt to novel environments. In the present work, we describe an approach toward exploring such enzyme promiscuity in the space of a metabolic network. This approach leverages genome-scale models, which have been widely used for predicting growth phenotypes in various environments or following a genetic perturbation; however, these predictions occasionally fail. Failed predictions of gene essentiality offer an opportunity for targeting biological discovery, suggesting the presence of unknown underground pathways stemming from enzymatic cross-reactivity. We demonstrate a workflow that couples constraint-based modeling and bioinformatic tools with KO strain analysis and adaptive laboratory evolution for the purpose of predicting promiscuity at the genome scale. Three cases of genes that are incorrectly predicted as essential in Escherichia coli--aspC, argD, and gltA--are examined, and isozyme functions are uncovered for each to a different extent. Seven isozyme functions based on genetic and transcriptional evidence are suggested between the genes aspC and tyrB, argD and astC, gabT and puuE, and gltA and prpC. This study demonstrates how a targeted model-driven approach to discovery can systematically fill knowledge gaps, characterize underground metabolism, and elucidate regulatory mechanisms of adaptation in response to gene KO perturbations.

  1. De Novo Regulatory Motif Discovery Identifies Significant Motifs in Promoters of Five Classes of Plant Dehydrin Genes.

    PubMed

    Zolotarov, Yevgen; Strömvik, Martina

    2015-01-01

    Plants accumulate dehydrins in response to osmotic stresses. Dehydrins are divided into five different classes, which are thought to be regulated in different manners. To better understand differences in transcriptional regulation of the five dehydrin classes, de novo motif discovery was performed on 350 dehydrin promoter sequences from a total of 51 plant genomes. Overrepresented motifs were identified in the promoters of five dehydrin classes. The Kn dehydrin promoters contain motifs linked with meristem specific expression, as well as motifs linked with cold/dehydration and abscisic acid response. KS dehydrin promoters contain a motif with a GATA core. SKn and YnSKn dehydrin promoters contain motifs that match elements connected with cold/dehydration, abscisic acid and light response. YnKn dehydrin promoters contain motifs that match abscisic acid and light response elements, but not cold/dehydration response elements. Conserved promoter motifs are present in the dehydrin classes and across different plant lineages, indicating that dehydrin gene regulation is likely also conserved.

  2. Genetic and Epigenetic Discoveries in Human Retinoblastoma.

    PubMed

    McEvoy, Justina D; Dyer, Michael A

    2015-01-01

    Retinoblastoma is a rare pediatric cancer of the retina. Nearly all retinoblastomas are initiated through the biallelic inactivation of the retinoblastoma tumor susceptibility gene (RB1). Whole-genome sequencing has made it possible to identify secondary genetic lesions following RB1 inactivation. One of the major discoveries from retinoblastoma sequencing studies is that some retinoblastoma tumors have stable genomes. Subsequent epigenetic studies showed that changes in the epigenome contribute to the rapid progression of retinoblastoma following RB1 gene inactivation. In addition, gene amplification and elevated expression of p53 antagonists, MDM2 and MDM4, may also play an important role in retinoblastoma tumorigenesis. The knowledge gained from these recent molecular, cellular, genomic, and epigenomic analyses are now being integrated to identify new therapeutic approaches that can help save lives and vision in children with retinoblastoma, with fewer long-term side effects.

  3. Accelerator-based Neutrino Physics at Fermilab

    NASA Astrophysics Data System (ADS)

    Dukes, Edmond

    2008-10-01

    The discovery of neutrino mass has excited great interest in elucidating the properties of neutrinos and their role in nature. Experiments around the world take advantage of solar, atmospheric, reactor, and accelerator sources of neutrinos. Accelerator-based sources are particularly convenient since their parameters can be tuned to optimize the measurement in question. At Fermilab an extensive neutrino program includes the MiniBooNE, SciBooNE, and MINOS experiments. Two major new experiments, MINERvA and NOvA, are being constructed, plans for a high-intensity neutrino source to DUSEL are underway, and an R&D effort towards a large liquid argon detector is being pursued. The NOvA experiment intends to search for electron neutrino appearance using a massive surface detector 811 km from Fermilab. In addition to measuring the last unknown mixing angle, theta(13), NOvA has the possibility of seeing matter-antimatter asymmetries in neutrinos and resolving the ordering of the neutrino mass states.

  4. GPU accelerated particle visualization with Splotch

    NASA Astrophysics Data System (ADS)

    Rivi, M.; Gheller, C.; Dykes, T.; Krokos, M.; Dolag, K.

    2014-07-01

    Splotch is a rendering algorithm for exploration and visual discovery in particle-based datasets coming from astronomical observations or numerical simulations. The strengths of the approach are production of high quality imagery and support for very large-scale datasets through an effective mix of the OpenMP and MPI parallel programming paradigms. This article reports our experiences in re-designing Splotch for exploiting emerging HPC architectures nowadays increasingly populated with GPUs. A performance model is introduced to guide our re-factoring of Splotch. A number of parallelization issues are discussed, in particular relating to race conditions and workload balancing, towards achieving optimal performances. Our implementation was accomplished by using the CUDA programming paradigm. Our strategy is founded on novel schemes achieving optimized data organization and classification of particles. We deploy a reference cosmological simulation to present performance results on acceleration gains and scalability. We finally outline our vision for future work developments including possibilities for further optimizations and exploitation of hybrid systems and emerging accelerators.

  5. The web server of IBM's Bioinformatics and Pattern Discovery group.

    PubMed

    Huynh, Tien; Rigoutsos, Isidore; Parida, Laxmi; Platt, Daniel; Shibuya, Tetsuo

    2003-07-01

    We herein present and discuss the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server is operational around the clock and provides access to a variety of methods that have been published by the group's members and collaborators. The available tools correspond to applications ranging from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences and the interactive annotation of amino acid sequences. Additionally, annotations for more than 70 archaeal, bacterial, eukaryotic and viral genomes are available on-line and can be searched interactively. The tools and code bundles can be accessed beginning at http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/.

  6. The web server of IBM's Bioinformatics and Pattern Discovery group

    PubMed Central

    Huynh, Tien; Rigoutsos, Isidore; Parida, Laxmi; Platt, Daniel; Shibuya, Tetsuo

    2003-01-01

    We herein present and discuss the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server is operational around the clock and provides access to a variety of methods that have been published by the group's members and collaborators. The available tools correspond to applications ranging from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences and the interactive annotation of amino acid sequences. Additionally, annotations for more than 70 archaeal, bacterial, eukaryotic and viral genomes are available on-line and can be searched interactively. The tools and code bundles can be accessed beginning at http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/. PMID:12824385

  7. MorphDB: Prioritizing Genes for Specialized Metabolism Pathways and Gene Ontology Categories in Plants.

    PubMed

    Zwaenepoel, Arthur; Diels, Tim; Amar, David; Van Parys, Thomas; Shamir, Ron; Van de Peer, Yves; Tzfadia, Oren

    2018-01-01

    Recent times have seen an enormous growth of "omics" data, of which high-throughput gene expression data are arguably the most important from a functional perspective. Despite huge improvements in computational techniques for the functional classification of gene sequences, common similarity-based methods often fall short of providing full and reliable functional information. Recently, the combination of comparative genomics with approaches in functional genomics has received considerable interest for gene function analysis, leveraging both gene expression based guilt-by-association methods and annotation efforts in closely related model organisms. Besides the identification of missing genes in pathways, these methods also typically enable the discovery of biological regulators (i.e., transcription factors or signaling genes). A previously built guilt-by-association method is MORPH, which was proven to be an efficient algorithm that performs particularly well in identifying and prioritizing missing genes in plant metabolic pathways. Here, we present MorphDB, a resource where MORPH-based candidate genes for large-scale functional annotations (Gene Ontology, MapMan bins) are integrated across multiple plant species. Besides a gene centric query utility, we present a comparative network approach that enables researchers to efficiently browse MORPH predictions across functional gene sets and species, facilitating efficient gene discovery and candidate gene prioritization. MorphDB is available at http://bioinformatics.psb.ugent.be/webtools/morphdb/morphDB/index/. We also provide a toolkit, named "MORPH bulk" (https://github.com/arzwa/morph-bulk), for running MORPH in bulk mode on novel data sets, enabling researchers to apply MORPH to their own species of interest.

  8. Accelerating Next Generation Vaccine Development for Global Disease Prevention

    PubMed Central

    Koff, Wayne C; Burton, Dennis R.; R.Johnson, Philip; Walker, Bruce D.; King, Charles R.; Nabel, Gary J.; Ahmed, Rafi; Bhan, Maharaj Kishan; Plotkin, Stanley A.

    2014-01-01

    Summary Vaccines are among the greatest successes in the history of public health. However, past strategies for vaccine development are unlikely to succeed in the future against major global diseases such as AIDS, TB, and malaria. For such diseases, the correlates of protection are poorly defined and the pathogens evade immune detection and/or exhibit extensive genetic variability. Recent advances have heralded in a new era of vaccine discovery. However, translation of these advances into vaccines remains impeded by lack of understanding of key vaccinology principles in humans. We review these advances towards vaccine discovery and suggest that for accelerating successful vaccine development, new human immunology-based clinical research initiatives be implemented with the goal of elucidating and more effectively inducing vaccine-induced protective immune responses. PMID:23723240

  9. Computational biology for cardiovascular biomarker discovery.

    PubMed

    Azuaje, Francisco; Devaux, Yvan; Wagner, Daniel

    2009-07-01

    Computational biology is essential in the process of translating biological knowledge into clinical practice, as well as in the understanding of biological phenomena based on the resources and technologies originating from the clinical environment. One such key contribution of computational biology is the discovery of biomarkers for predicting clinical outcomes using 'omic' information. This process involves the predictive modelling and integration of different types of data and knowledge for screening, diagnostic or prognostic purposes. Moreover, this requires the design and combination of different methodologies based on statistical analysis and machine learning. This article introduces key computational approaches and applications to biomarker discovery based on different types of 'omic' data. Although we emphasize applications in cardiovascular research, the computational requirements and advances discussed here are also relevant to other domains. We will start by introducing some of the contributions of computational biology to translational research, followed by an overview of methods and technologies used for the identification of biomarkers with predictive or classification value. The main types of 'omic' approaches to biomarker discovery will be presented with specific examples from cardiovascular research. This will include a review of computational methodologies for single-source and integrative data applications. Major computational methods for model evaluation will be described together with recommendations for reporting models and results. We will present recent advances in cardiovascular biomarker discovery based on the combination of gene expression and functional network analyses. The review will conclude with a discussion of key challenges for computational biology, including perspectives from the biosciences and clinical areas.

  10. The discovery of zinc fingers and their development for practical applications in gene regulation and genome manipulation.

    PubMed

    Klug, Aaron

    2010-02-01

    A long-standing goal of molecular biologists has been to construct DNA-binding proteins for the control of gene expression. The classical Cys2His2 (C2H2) zinc finger design is ideally suited for such purposes. Discriminating between closely related DNA sequences both in vitro and in vivo, this naturally occurring design was adopted for engineering zinc finger proteins (ZFPs) to target genes specifically. Zinc fingers were discovered in 1985, arising from the interpretation of our biochemical studies on the interaction of the Xenopus protein transcription factor IIIA (TFIIIA) with 5S RNA. Subsequent structural studies revealed its three-dimensional structure and its interaction with DNA. Each finger constitutes a self-contained domain stabilized by a zinc (Zn) ion ligated to a pair of cysteines and a pair of histidines and also by an inner structural hydrophobic core. This discovery showed not only a new protein fold but also a novel principle of DNA recognition. Whereas other DNA-binding proteins generally make use of the 2-fold symmetry of the double helix, functioning as homo- or heterodimers, zinc fingers can be linked linearly in tandem to recognize nucleic acid sequences of varying lengths. This modular design offers a large number of combinatorial possibilities for the specific recognition of DNA (or RNA). It is therefore not surprising that the zinc finger is found widespread in nature, including 3% of the genes of the human genome. The zinc finger design can be used to construct DNA-binding proteins for specific intervention in gene expression. By fusing selected zinc finger peptides to repression or activation domains, genes can be selectively switched off or on by targeting the peptide to the desired gene target. It was also suggested that by combining an appropriate zinc finger peptide with other effector or functional domains, e.g. from nucleases or integrases to form chimaeric proteins, genomes could be modified or manipulated. The first example of the

  11. Experiences with Deriva: An Asset Management Platform for Accelerating eScience.

    PubMed

    Bugacov, Alejandro; Czajkowski, Karl; Kesselman, Carl; Kumar, Anoop; Schuler, Robert E; Tangmunarunkit, Hongsuda

    2017-10-01

    The pace of discovery in eScience is increasingly dependent on a scientist's ability to acquire, curate, integrate, analyze, and share large and diverse collections of data. It is all too common for investigators to spend inordinate amounts of time developing ad hoc procedures to manage their data. In previous work, we presented Deriva, a Scientific Asset Management System, designed to accelerate data driven discovery. In this paper, we report on the use of Deriva in a number of substantial and diverse eScience applications. We describe the lessons we have learned, both from the perspective of the Deriva technology, as well as the ability and willingness of scientists to incorporate Scientific Asset Management into their daily workflows.

  12. A Prerecognition Model for Hot Topic Discovery Based on Microblogging Data

    PubMed Central

    Zhu, Tongyu

    2014-01-01

    The microblogging is prevailing since its easy and anonymous information sharing at Internet, which also brings the issue of dispersing negative topics, or even rumors. Many researchers have focused on how to find and trace emerging topics for analysis. When adopting topic detection and tracking techniques to find hot topics with streamed microblogging data, it will meet obstacles like streamed microblogging data clustering, topic hotness definition, and emerging hot topic discovery. This paper schemes a novel prerecognition model for hot topic discovery. In this model, the concepts of the topic life cycle, the hot velocity, and the hot acceleration are promoted to calculate the change of topic hotness, which aims to discover those emerging hot topics before they boost and break out. Our experiments show that this new model would help to discover potential hot topics efficiently and achieve considerable performance. PMID:25254235

  13. A prerecognition model for hot topic discovery based on microblogging data.

    PubMed

    Zhu, Tongyu; Yu, Jianjun

    2014-01-01

    The microblogging is prevailing since its easy and anonymous information sharing at Internet, which also brings the issue of dispersing negative topics, or even rumors. Many researchers have focused on how to find and trace emerging topics for analysis. When adopting topic detection and tracking techniques to find hot topics with streamed microblogging data, it will meet obstacles like streamed microblogging data clustering, topic hotness definition, and emerging hot topic discovery. This paper schemes a novel prerecognition model for hot topic discovery. In this model, the concepts of the topic life cycle, the hot velocity, and the hot acceleration are promoted to calculate the change of topic hotness, which aims to discover those emerging hot topics before they boost and break out. Our experiments show that this new model would help to discover potential hot topics efficiently and achieve considerable performance.

  14. Plant Enhancers: A Call for Discovery.

    PubMed

    Weber, Blaise; Zicola, Johan; Oka, Rurika; Stam, Maike

    2016-11-01

    Higher eukaryotes typically contain many different cell types, displaying different cellular functions that are influenced by biotic and abiotic cues. The different functions are characterized by specific gene expression patterns mediated by regulatory sequences such as transcriptional enhancers. Recent genome-wide approaches have identified thousands of enhancers in animals, reviving interest in enhancers in gene regulation. Although the regulatory roles of plant enhancers are as crucial as those in animals, genome-wide approaches have only very recently been applied to plants. Here we review characteristics of enhancers at the DNA and chromatin level in plants and other species, their similarities and differences, and techniques widely used for genome-wide discovery of enhancers in animal systems that can be implemented in plants. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. From crystal to compound: structure-based antimalarial drug discovery.

    PubMed

    Drinkwater, Nyssa; McGowan, Sheena

    2014-08-01

    Despite a century of control and eradication campaigns, malaria remains one of the world's most devastating diseases. Our once-powerful therapeutic weapons are losing the war against the Plasmodium parasite, whose ability to rapidly develop and spread drug resistance hamper past and present malaria-control efforts. Finding new and effective treatments for malaria is now a top global health priority, fuelling an increase in funding and promoting open-source collaborations between researchers and pharmaceutical consortia around the world. The result of this is rapid advances in drug discovery approaches and technologies, with three major methods for antimalarial drug development emerging: (i) chemistry-based, (ii) target-based, and (iii) cell-based. Common to all three of these approaches is the unique ability of structural biology to inform and accelerate drug development. Where possible, SBDD (structure-based drug discovery) is a foundation for antimalarial drug development programmes, and has been invaluable to the development of a number of current pre-clinical and clinical candidates. However, as we expand our understanding of the malarial life cycle and mechanisms of resistance development, SBDD as a field must continue to evolve in order to develop compounds that adhere to the ideal characteristics for novel antimalarial therapeutics and to avoid high attrition rates pre- and post-clinic. In the present review, we aim to examine the contribution that SBDD has made to current antimalarial drug development efforts, covering hit discovery to lead optimization and prevention of parasite resistance. Finally, the potential for structural biology, particularly high-throughput structural genomics programmes, to identify future targets for drug discovery are discussed.

  16. Elements of discovery.

    PubMed

    Toledo-Pereyra, Luis H

    2008-01-01

    I understand discovery as the essence of thinking man, or to paraphrase the notable French philosopher René Descartes, "I think, therefore I discover." In this study, I introduce discovery as the foundation of modern science. Discovery consists of six stages or elements, including: concept, belief, ability, support, proof, and protection. Each element is discussed within the context of the whole discovery enterprise. Fundamental tenets for understanding discovery are given throughout the paper, and a few examples illustrate the significance of some of the most important elements. I invite clinicians, researchers, and/or clinical researchers to integrate themselves into the active process of discovery. Remember--I think, therefore I discover.

  17. Natural product discovery: past, present, and future.

    PubMed

    Katz, Leonard; Baltz, Richard H

    2016-03-01

    Microorganisms have provided abundant sources of natural products which have been developed as commercial products for human medicine, animal health, and plant crop protection. In the early years of natural product discovery from microorganisms (The Golden Age), new antibiotics were found with relative ease from low-throughput fermentation and whole cell screening methods. Later, molecular genetic and medicinal chemistry approaches were applied to modify and improve the activities of important chemical scaffolds, and more sophisticated screening methods were directed at target disease states. In the 1990s, the pharmaceutical industry moved to high-throughput screening of synthetic chemical libraries against many potential therapeutic targets, including new targets identified from the human genome sequencing project, largely to the exclusion of natural products, and discovery rates dropped dramatically. Nonetheless, natural products continued to provide key scaffolds for drug development. In the current millennium, it was discovered from genome sequencing that microbes with large genomes have the capacity to produce about ten times as many secondary metabolites as was previously recognized. Indeed, the most gifted actinomycetes have the capacity to produce around 30-50 secondary metabolites. With the precipitous drop in cost for genome sequencing, it is now feasible to sequence thousands of actinomycete genomes to identify the "biosynthetic dark matter" as sources for the discovery of new and novel secondary metabolites. Advances in bioinformatics, mass spectrometry, proteomics, transcriptomics, metabolomics and gene expression are driving the new field of microbial genome mining for applications in natural product discovery and development.

  18. Leaf Senescence and Starvation-Induced Chlorosis Are Accelerated by the Disruption of an Arabidopsis Autophagy Gene1

    PubMed Central

    Hanaoka, Hideki; Noda, Takeshi; Shirano, Yumiko; Kato, Tomohiko; Hayashi, Hiroaki; Shibata, Daisuke; Tabata, Satoshi; Ohsumi, Yoshinori

    2002-01-01

    Autophagy is an intracellular process for vacuolar bulk degradation of cytoplasmic components. The molecular machinery responsible for yeast and mammalian autophagy has recently begun to be elucidated at the cellular level, but the role that autophagy plays at the organismal level has yet to be determined. In this study, a genome-wide search revealed significant conservation between yeast and plant autophagy genes. Twenty-five plant genes that are homologous to 12 yeast genes essential for autophagy were discovered. We identified an Arabidopsis mutant carrying a T-DNA insertion within AtAPG9, which is the only ortholog of yeast Apg9 in Arabidopsis (atapg9-1). AtAPG9 is transcribed in every wild-type organ tested but not in the atapg9-1 mutant. Under nitrogen or carbon-starvation conditions, chlorosis was observed earlier in atapg9-1 cotyledons and rosette leaves compared with wild-type plants. Furthermore, atapg9-1 exhibited a reduction in seed set when nitrogen starved. Even under nutrient growth conditions, bolting and natural leaf senescence were accelerated in atapg9-1 plants. Senescence-associated genes SEN1 and YSL4 were up-regulated in atapg9-1 before induction of senescence, unlike in wild type. All of these phenotypes were complemented by the expression of wild-type AtAPG9 in atapg9-1 plants. These results imply that autophagy is required for maintenance of the cellular viability under nutrient-limited conditions and for efficient nutrient use as a whole plant. PMID:12114572

  19. The Tuberculosis Drug Discovery and Development Pipeline and Emerging Drug Targets

    PubMed Central

    Mdluli, Khisimuzi; Kaneko, Takushi; Upton, Anna

    2015-01-01

    The recent accelerated approval for use in extensively drug-resistant and multidrug-resistant-tuberculosis (MDR-TB) of two first-in-class TB drugs, bedaquiline and delamanid, has reinvigorated the TB drug discovery and development field. However, although several promising clinical development programs are ongoing to evaluate new TB drugs and regimens, the number of novel series represented is few. The global early-development pipeline is also woefully thin. To have a chance of achieving the goal of better, shorter, safer TB drug regimens with utility against drug-sensitive and drug-resistant disease, a robust and diverse global TB drug discovery pipeline is key, including innovative approaches that make use of recently acquired knowledge on the biology of TB. Fortunately, drug discovery for TB has resurged in recent years, generating compounds with varying potential for progression into developable leads. In parallel, advances have been made in understanding TB pathogenesis. It is now possible to apply the lessons learned from recent TB hit generation efforts and newly validated TB drug targets to generate the next wave of TB drug leads. Use of currently underexploited sources of chemical matter and lead-optimization strategies may also improve the efficiency of future TB drug discovery. Novel TB drug regimens with shorter treatment durations must target all subpopulations of Mycobacterium tuberculosis existing in an infection, including those responsible for the protracted TB treatment duration. This review summarizes the current TB drug development pipeline and proposes strategies for generating improved hits and leads in the discovery phase that could help achieve this goal. PMID:25635061

  20. Construction and Evaluation of Normalized cDNA Libraries Enriched with Full-Length Sequences for Rapid Discovery of New Genes from Sisal (Agave sisalana Perr.) Different Developmental Stages

    PubMed Central

    Zhou, Wen-Zhao; Zhang, Yan-Mei; Lu, Jun-Ying; Li, Jun-Feng

    2012-01-01

    To provide a resource of sisal-specific expressed sequence data and facilitate this powerful approach in new gene research, the preparation of normalized cDNA libraries enriched with full-length sequences is necessary. Four libraries were produced with RNA pooled from Agave sisalana multiple tissues to increase efficiency of normalization and maximize the number of independent genes by SMART™ method and the duplex-specific nuclease (DSN). This procedure kept the proportion of full-length cDNAs in the subtracted/normalized libraries and dramatically enhanced the discovery of new genes. Sequencing of 3875 cDNA clones of libraries revealed 3320 unigenes with an average insert length about 1.2 kb, indicating that the non-redundancy of libraries was about 85.7%. These unigene functions were predicted by comparing their sequences to functional domain databases and extensively annotated with Gene Ontology (GO) terms. Comparative analysis of sisal unigenes and other plant genomes revealed that four putative MADS-box genes and knotted-like homeobox (knox) gene were obtained from a total of 1162 full-length transcripts. Furthermore, real-time PCR showed that the characteristics of their transcripts mainly depended on the tight expression regulation of a number of genes during the leaf and flower development. Analysis of individual library sequence data indicated that the pooled-tissue approach was highly effective in discovering new genes and preparing libraries for efficient deep sequencing. PMID:23202944

  1. Gene Fusion Markup Language: a prototype for exchanging gene fusion data.

    PubMed

    Kalyana-Sundaram, Shanker; Shanmugam, Achiraman; Chinnaiyan, Arul M

    2012-10-16

    An avalanche of next generation sequencing (NGS) studies has generated an unprecedented amount of genomic structural variation data. These studies have also identified many novel gene fusion candidates with more detailed resolution than previously achieved. However, in the excitement and necessity of publishing the observations from this recently developed cutting-edge technology, no community standardization approach has arisen to organize and represent the data with the essential attributes in an interchangeable manner. As transcriptome studies have been widely used for gene fusion discoveries, the current non-standard mode of data representation could potentially impede data accessibility, critical analyses, and further discoveries in the near future. Here we propose a prototype, Gene Fusion Markup Language (GFML) as an initiative to provide a standard format for organizing and representing the significant features of gene fusion data. GFML will offer the advantage of representing the data in a machine-readable format to enable data exchange, automated analysis interpretation, and independent verification. As this database-independent exchange initiative evolves it will further facilitate the formation of related databases, repositories, and analysis tools. The GFML prototype is made available at http://code.google.com/p/gfml-prototype/. The Gene Fusion Markup Language (GFML) presented here could facilitate the development of a standard format for organizing, integrating and representing the significant features of gene fusion data in an inter-operable and query-able fashion that will enable biologically intuitive access to gene fusion findings and expedite functional characterization. A similar model is envisaged for other NGS data analyses.

  2. Gene Fusion Markup Language: a prototype for exchanging gene fusion data

    PubMed Central

    2012-01-01

    Background An avalanche of next generation sequencing (NGS) studies has generated an unprecedented amount of genomic structural variation data. These studies have also identified many novel gene fusion candidates with more detailed resolution than previously achieved. However, in the excitement and necessity of publishing the observations from this recently developed cutting-edge technology, no community standardization approach has arisen to organize and represent the data with the essential attributes in an interchangeable manner. As transcriptome studies have been widely used for gene fusion discoveries, the current non-standard mode of data representation could potentially impede data accessibility, critical analyses, and further discoveries in the near future. Results Here we propose a prototype, Gene Fusion Markup Language (GFML) as an initiative to provide a standard format for organizing and representing the significant features of gene fusion data. GFML will offer the advantage of representing the data in a machine-readable format to enable data exchange, automated analysis interpretation, and independent verification. As this database-independent exchange initiative evolves it will further facilitate the formation of related databases, repositories, and analysis tools. The GFML prototype is made available at http://code.google.com/p/gfml-prototype/. Conclusion The Gene Fusion Markup Language (GFML) presented here could facilitate the development of a standard format for organizing, integrating and representing the significant features of gene fusion data in an inter-operable and query-able fashion that will enable biologically intuitive access to gene fusion findings and expedite functional characterization. A similar model is envisaged for other NGS data analyses. PMID:23072312

  3. Next Generation Sequencing and ALS: known genes, different phenotyphes.

    PubMed

    Campopiano, Rosa; Ryskalin, Larisa; Giardina, Emiliano; Zampatti, Stefania; Busceti, Carla L; Biagioni, Francesca; Ferese, Rosangela; Storto, Marianna; Gambardella, Stefano; Fornai, Francesco

    2017-12-01

    Amyotrophic lateral sclerosis (ALS) is fatal neurodegenerative disease clinically characterized by upper and lower motor neuron dysfunction resulting in rapidly progressive paralysis and death from respiratory failure. Most cases appear to be sporadic, but 5-10 % of cases have a family history of the disease, and over the last decade, identification of mutations in about 20 genes predisposing to these disorders has provided the means to better understand their pathogenesis. Next Generation sequencing (NGS) is an advanced high-throughput DNA sequencing technology which have rapidly contributed to an acceleration in the discovery of genetic risk factors for both familial and sporadic neurological and neurodegenerative diseases. These strategies allowed to rapidly identify disease-associated variants and genetic risk factors for both familial (fALS) and sporadic ALS (sALS), strongly contributing to the knowledge of the genetic architecture of ALS. Moreover, as the number of ALS genes grows, many of the proteins they encode are in intracellular processes shared with other known diseases, suggesting an overlapping of clinical and phatological features between different diseases. To emphasize this concept, the review focuses on genes coding for Valosin-containing protein (VPC) and two Heterogeneous nuclear RNA-binding proteins (HNRNPA1 and hnRNPA2B1), recently idefied through NGS, where different mutations have been associated in both ALS and other neurological and neurodegenerative diseases.

  4. Co-clustering phenome–genome for phenotype classification and disease gene discovery

    PubMed Central

    Hwang, TaeHyun; Atluri, Gowtham; Xie, MaoQiang; Dey, Sanjoy; Hong, Changjin; Kumar, Vipin; Kuang, Rui

    2012-01-01

    Understanding the categorization of human diseases is critical for reliably identifying disease causal genes. Recently, genome-wide studies of abnormal chromosomal locations related to diseases have mapped >2000 phenotype–gene relations, which provide valuable information for classifying diseases and identifying candidate genes as drug targets. In this article, a regularized non-negative matrix tri-factorization (R-NMTF) algorithm is introduced to co-cluster phenotypes and genes, and simultaneously detect associations between the detected phenotype clusters and gene clusters. The R-NMTF algorithm factorizes the phenotype–gene association matrix under the prior knowledge from phenotype similarity network and protein–protein interaction network, supervised by the label information from known disease classes and biological pathways. In the experiments on disease phenotype–gene associations in OMIM and KEGG disease pathways, R-NMTF significantly improved the classification of disease phenotypes and disease pathway genes compared with support vector machines and Label Propagation in cross-validation on the annotated phenotypes and genes. The newly predicted phenotypes in each disease class are highly consistent with human phenotype ontology annotations. The roles of the new member genes in the disease pathways are examined and validated in the protein–protein interaction subnetworks. Extensive literature review also confirmed many new members of the disease classes and pathways as well as the predicted associations between disease phenotype classes and pathways. PMID:22735708

  5. Accelerated discovery of new magnets in the Heusler alloy family

    PubMed Central

    Sanvito, Stefano; Oses, Corey; Xue, Junkai; Tiwari, Anurag; Zic, Mario; Archer, Thomas; Tozman, Pelin; Venkatesan, Munuswamy; Coey, Michael; Curtarolo, Stefano

    2017-01-01

    Magnetic materials underpin modern technologies, ranging from data storage to energy conversion to contactless sensing. However, the development of a new high-performance magnet is a long and often unpredictable process, and only about two dozen magnets are featured in mainstream applications. We describe a systematic pathway to the design of novel magnetic materials, which demonstrates a high throughput and discovery speed. On the basis of an extensive electronic structure library of Heusler alloys containing 236,115 prototypical compounds, we filtered those displaying magnetic order and established whether they can be fabricated at thermodynamic equilibrium. Specifically, we carried out a full stability analysis of intermetallic Heusler alloys made only of transition metals. Among the possible 36,540 prototypes, 248 were thermodynamically stable but only 20 were magnetic. The magnetic ordering temperature, TC, was estimated by a regression calibrated on the experimental TC of about 60 known compounds. As a final validation, we attempted the synthesis of a few of the predicted compounds and produced two new magnets: Co2MnTi, which displays a remarkably high TC in perfect agreement with the predictions, and Mn2PtPd, which is an antiferromagnet. Our work paves the way for large-scale design of novel magnetic materials at potentially high speed. PMID:28439545

  6. CTD² Dashboard: a searchable web interface to connect validated results from the Cancer Target Discovery and Development Network* | Office of Cancer Genomics

    Cancer.gov

    The Cancer Target Discovery and Development (CTD2) Network aims to use functional genomics to accelerate the translation of high-throughput and high-content genomic and small-molecule data towards use in precision oncology.

  7. De Novo Transcriptome Analysis of an Aerial Microalga Trentepohlia jolithus: Pathway Description and Gene Discovery for Carbon Fixation and Carotenoid Biosynthesis

    PubMed Central

    Li, Qianqian; Liu, Jianguo; Zhang, Litao; Liu, Qian

    2014-01-01

    Background Algae in the order Trentepohliales have a broad geographic distribution and are generally characterized by the presence of abundant β-carotene. The many monographs published to date have mainly focused on their morphology, taxonomy, phylogeny, distribution and reproduction; molecular studies of this order are still rare. High-throughput RNA sequencing (RNA-Seq) technology provides a powerful and efficient method for transcript analysis and gene discovery in Trentepohlia jolithus. Methods/Principal Findings Illumina HiSeq 2000 sequencing generated 55,007,830 Illumina PE raw reads, which were assembled into 41,328 assembled unigenes. Based on NR annotation, 53.28% of the unigenes (22,018) could be assigned to gene ontology classes with 54 subcategories and 161,451 functional terms. A total of 26,217 (63.44%) assembled unigenes were mapped to 128 KEGG pathways. Furthermore, a set of 5,798 SSRs in 5,206 unigenes and 131,478 putative SNPs were identified. Moreover, the fact that all of the C4 photosynthesis genes exist in T. jolithus suggests a complex carbon acquisition and fixation system. Similarities and differences between T. jolithus and other algae in carotenoid biosynthesis are also described in depth. Conclusions/Significance This is the first broad transcriptome survey for T. jolithus, increasing the amount of molecular data available for the class Ulvophyceae. As well as providing resources for functional genomics studies, the functional genes and putative pathways identified here will contribute to a better understanding of carbon fixation and fatty acid and carotenoid biosynthesis in T. jolithus. PMID:25254555

  8. In silico discovery of metal-organic frameworks for precombustion CO2 capture using a genetic algorithm

    PubMed Central

    Chung, Yongchul G.; Gómez-Gualdrón, Diego A.; Li, Peng; Leperi, Karson T.; Deria, Pravas; Zhang, Hongda; Vermeulen, Nicolaas A.; Stoddart, J. Fraser; You, Fengqi; Hupp, Joseph T.; Farha, Omar K.; Snurr, Randall Q.

    2016-01-01

    Discovery of new adsorbent materials with a high CO2 working capacity could help reduce CO2 emissions from newly commissioned power plants using precombustion carbon capture. High-throughput computational screening efforts can accelerate the discovery of new adsorbents but sometimes require significant computational resources to explore the large space of possible materials. We report the in silico discovery of high-performing adsorbents for precombustion CO2 capture by applying a genetic algorithm to efficiently search a large database of metal-organic frameworks (MOFs) for top candidates. High-performing MOFs identified from the in silico search were synthesized and activated and show a high CO2 working capacity and a high CO2/H2 selectivity. One of the synthesized MOFs shows a higher CO2 working capacity than any MOF reported in the literature under the operating conditions investigated here. PMID:27757420

  9. An accelerated assay for the identification of lifespan-extending interventions in Drosophila melanogaster.

    PubMed

    Bauer, Johannes H; Goupil, Stephan; Garber, Graham B; Helfand, Stephen L

    2004-08-31

    Recent advances in aging research have uncovered genes and genetic pathways that influence lifespan in such diverse organisms as yeast, nematodes, flies, and mice. The discovery of genes and drugs that affect lifespan has been delayed by the absence of a phenotype other than survivorship, which depends on the measurement of age at death of individuals in a population. The use of survivorship to identify genetic and pharmacological interventions that prolong life is time-consuming and requires a large number of homogeneous animals. Here, we report the development of an assay in Drosophila melanogaster using the expression of molecular biomarkers that accelerates the ability to evaluate potential lifespan-altering interventions. Coupling the expression of an age-dependent molecular biomarker to a lethal toxin reduces the time needed to perform lifespan studies by 80%. The assay recapitulates the effect of the three best known environmental life-span-extending interventions in the fly: ambient temperature, reproductive status, and calorie reduction. Single gene mutations known to extend lifespan in the fly such as Indy and rpd3 also extend lifespan in this assay. We used this assay as a screen to identify drugs that extend lifespan in flies. Lipoic acid and resveratrol were identified as being beneficial in our assay and shown to extend lifespan under normal laboratory conditions. We propose that this assay can be used to screen pharmacological as well as genetic interventions more rapidly for positive effects on lifespan. Copyright 2004 The National Academy of Sciencs of the USA

  10. Bioactivity-guided mixed synthesis accelerate the serendipity in lead optimization: Discovery of fungicidal homodrimanyl amides.

    PubMed

    Li, Dangdang; Zhang, Shasha; Song, Zehua; Wang, Guotong; Li, Shengkun

    2017-08-18

    The bioactivity-guided mixed synthesis was conceived, in which the designed mix-reactions were run in parallel for simultaneous construction of different kinds of analogs. The valuable ones were protruded by biological screening. This tactic will facilitate more rapid incorporation of bioactive candidates into pesticide chemists' repertoire, exemplified by the optimization of less explored homodrimanes as antifungal ingredients. The discovery of D9 as a potent fungicidal agent can be completed in <2 weeks by one student, with EC 50 of 3.33 mg/L and 2.45 mg/L against S. sclerotiorum and B. cinerea, respectively. To confirm the practicability, time-efficiency, and reliability, specific homodrimanes (82 derivatives) were synthesized and elucidated separately and determined for EC 50 values. The SAR correlated well with the intentionally mixed synthesis and the potential was further confirmed by the in vivo bioassay. This methodology will foster more efficient exploration of biologically relevant chemical space of natural products in pesticide discovery, and can also be tailored readily for the lead optimization in medicinal chemistry. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  11. Toolbox for Antibiotics Discovery from Microorganisms.

    PubMed

    Fisch, Katja M; Schäberle, Till F

    2016-09-01

    Microorganisms produce a vast array of biologically active metabolites. Such compounds are applied by humans to positively influence their health and, therefore, natural products serve as drug leads for pharmaceutical and medicinal chemistry. In this minireview, tools for the discovery and the production of potential drug leads are explained. A snapshot is provided, starting from the isolation of new producer strains, across genomic mining of (meta)genomes to identify biosynthetic gene clusters corresponding to natural products, toward heterologous expression to produce potential drug leads. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Refinement of light-responsive transcript lists using rice oligonucleotide arrays: evaluation of gene-redundancy.

    PubMed

    Jung, Ki-Hong; Dardick, Christopher; Bartley, Laura E; Cao, Peijian; Phetsom, Jirapa; Canlas, Patrick; Seo, Young-Su; Shultz, Michael; Ouyang, Shu; Yuan, Qiaoping; Frank, Bryan C; Ly, Eugene; Zheng, Li; Jia, Yi; Hsia, An-Ping; An, Kyungsook; Chou, Hui-Hsien; Rocke, David; Lee, Geun Cheol; Schnable, Patrick S; An, Gynheung; Buell, C Robin; Ronald, Pamela C

    2008-10-06

    Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics.

  13. Exploitation of Fungal Biodiversity for Discovery of Novel Antibiotics.

    PubMed

    Karwehl, Sabrina; Stadler, Marc

    Fungi were among the first sources for antibiotics. The discovery and development of the penicillin-type and cephalosporin-type β-lactams and their synthetic versions were transformative in emergence of the modern pharmaceutical industry. They remain some of the most important antibiotics, even 70 years after their discovery. Meanwhile, thousands of fungal metabolites have been discovered, yet these metabolites have only contributed a few additional compounds that have entered clinical development. Substantial expansion in fungal biodiversity assessment along with the availability of modern "-OMICS" technology and revolutionary developments in fungal biotechnology have been made in the last 15 years subsequent to the exit of most of the big Pharma companies from the field of novel antibiotics discovery. Therefore, the timing seems opportune to revisit these fascinating chemically rich organisms as a reservoir of small-molecule templates for lead discovery. This review will describe ongoing interdisciplinary scenarios in which specialists in fungal biology collaborate with chemists, pharmacologists and biochemical and process engineers in order to reveal and make new antibiotics. The utility of a pre-selection process based on phylogenetic data and distribution of secondary metabolite encoding gene cluster will be highlighted. Examples of novel bioactive metabolites from fungi derived from special ecological groups and new phylogenetic lineages will also be discussed.

  14. Systems biology impact on antiepileptic drug discovery.

    PubMed

    Margineanu, Doru Georg

    2012-02-01

    Systems biology (SB), a recent trend in bioscience research to consider the complex interactions in biological systems from a holistic perspective, sees the disease as a disturbed network of interactions, rather than alteration of single molecular component(s). SB-relying network pharmacology replaces the prevailing focus on specific drug-receptor interaction and the corollary of rational drug design of "magic bullets", by the search for multi-target drugs that would act on biological networks as "magic shotguns". Epilepsy being a multi-factorial, polygenic and dynamic pathology, SB approach appears particularly fit and promising for antiepileptic drug (AED) discovery. In fact, long before the advent of SB, AED discovery already involved some SB-like elements. A reported SB project aimed to find out new drug targets in epilepsy relies on a relational database that integrates clinical information, recordings from deep electrodes and 3D-brain imagery with histology and molecular biology data on modified expression of specific genes in the brain regions displaying spontaneous epileptic activity. Since hitting a single target does not treat complex diseases, a proper pharmacological promiscuity might impart on an AED the merit of being multi-potent. However, multi-target drug discovery entails the complicated task of optimizing multiple activities of compounds, while having to balance drug-like properties and to control unwanted effects. Specific design tools for this new approach in drug discovery barely emerge, but computational methods making reliable in silico predictions of poly-pharmacology did appear, and their progress might be quite rapid. The current move away from reductionism into network pharmacology allows expecting that a proper integration of the intrinsic complexity of epileptic pathology in AED discovery might result in literally anti-epileptic drugs. Copyright © 2011 Elsevier B.V. All rights reserved.

  15. Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project.

    PubMed

    Verbist, Bie; Klambauer, Günter; Vervoort, Liesbet; Talloen, Willem; Shkedy, Ziv; Thas, Olivier; Bender, Andreas; Göhlmann, Hinrich W H; Hochreiter, Sepp

    2015-05-01

    The pharmaceutical industry is faced with steadily declining R&D efficiency which results in fewer drugs reaching the market despite increased investment. A major cause for this low efficiency is the failure of drug candidates in late-stage development owing to safety issues or previously undiscovered side-effects. We analyzed to what extent gene expression data can help to de-risk drug development in early phases by detecting the biological effects of compounds across disease areas, targets and scaffolds. For eight drug discovery projects within a global pharmaceutical company, gene expression data were informative and able to support go/no-go decisions. Our studies show that gene expression profiling can detect adverse effects of compounds, and is a valuable tool in early-stage drug discovery decision making. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  16. Discovery of digestive enzymes in carnivorous plants with focus on proteases.

    PubMed

    Ravee, Rishiesvari; Mohd Salleh, Faris 'Imadi; Goh, Hoe-Han

    2018-01-01

    Carnivorous plants have been fascinating researchers with their unique characters and bioinspired applications. These include medicinal trait of some carnivorous plants with potentials for pharmaceutical industry. This review will cover recent progress based on current studies on digestive enzymes secreted by different genera of carnivorous plants: Drosera (sundews), Dionaea (Venus flytrap) , Nepenthes (tropical pitcher plants), Sarracenia (North American pitcher plants) , Cephalotus (Australian pitcher plants) , Genlisea (corkscrew plants) , and Utricularia (bladderworts). Since the discovery of secreted protease nepenthesin in Nepenthes pitcher, digestive enzymes from carnivorous plants have been the focus of many studies. Recent genomics approaches have accelerated digestive enzyme discovery. Furthermore, the advancement in recombinant technology and protein purification helped in the identification and characterisation of enzymes in carnivorous plants. These different aspects will be described and discussed in this review with focus on the role of secreted plant proteases and their potential industrial applications.

  17. Towards Robot Scientists for autonomous scientific discovery

    PubMed Central

    2010-01-01

    We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic. We argue that the reporting of science needs to become fully formalised and that Robot Scientists can help achieve this. This will make scientific information more reproducible and reusable, and promote the integration of computers in scientific reasoning. We believe the greater automation of both the physical and intellectual aspects of scientific investigations to be essential to the future of science. Greater automation improves the accuracy and reliability of experiments, increases the pace of discovery and, in common with conventional laboratory automation, removes tedious and repetitive tasks from the human scientist. PMID:20119518

  18. Towards Robot Scientists for autonomous scientific discovery.

    PubMed

    Sparkes, Andrew; Aubrey, Wayne; Byrne, Emma; Clare, Amanda; Khan, Muhammed N; Liakata, Maria; Markham, Magdalena; Rowland, Jem; Soldatova, Larisa N; Whelan, Kenneth E; Young, Michael; King, Ross D

    2010-01-04

    We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic. We argue that the reporting of science needs to become fully formalised and that Robot Scientists can help achieve this. This will make scientific information more reproducible and reusable, and promote the integration of computers in scientific reasoning. We believe the greater automation of both the physical and intellectual aspects of scientific investigations to be essential to the future of science. Greater automation improves the accuracy and reliability of experiments, increases the pace of discovery and, in common with conventional laboratory automation, removes tedious and repetitive tasks from the human scientist.

  19. PDPR Gene Expression Correlates with Exercise-Training Insulin Sensitivity Changes

    PubMed Central

    Barberio, Matthew D.; Huffman, Kim M.; Giri, Mamta; Hoffman, Eric P.; Kraus, William E.; Hubal, Monica J.

    2016-01-01

    Purpose Whole body insulin sensitivity (Si) typically improves following aerobic exercise training; however, individual responses can be highly variable. The purpose of this study was to use global gene expression to identify skeletal muscle genes that correlate with exercise-induced Si changes. Methods Longitudinal cohorts from the Studies of Targeted Risk Reduction Intervention through Defined Exercise (STRRIDE) were utilized as Discovery (Affymetrix) and Confirmation (Illumina) of vastus lateralis gene expression profiles. Discovery (n=39; 21 men) and Confirmation (n=42; 19 men) cohorts were matched for age (52 ± 8 vs. 51 ± 10 yr), BMI (30.4 ± 2.8 vs. 29.7 ± 2.8 kg*m-2), and VO2max (30.4 ± 2.8 vs. 29.7 ± 2.8 mL/kg/min). Si was determined via intravenous glucose tolerance test pre- and post-training. Pearson product-moment correlation coefficients determined relationships between a) baseline and b) training-induced changes in gene expression and %ΔSi after training. Results Expression of 2454 (Discovery) and 1778 genes (Confirmation) at baseline were significantly (P<0.05) correlated to %ΔSi; 112 genes overlapped. Pathway analyses identified Ca2+-signaling-related transcripts in this 112-gene list. Expression changes of 1384 (Discovery) and 1288 genes (Confirmation) following training were significantly (P<0.05) correlated to % ΔSi; 33 genes overlapped, representing contractile apparatus of skeletal and smooth muscle genes. Pyruvate dehydrogenase phosphatase regulatory subunit (PDPR) expression at baseline (p=0.01, r=0.41) and post-training (p=0.01, r=0.43) were both correlated with %ΔSi. Conclusion Exercise-induced adaptations in skeletal muscle Si are related to baseline levels of Ca+2-regulating transcripts, which may prime the muscle for adaptation. Relationships between %ΔSi and PDPR, a regulatory subunit of the pyruvate dehydrogenase complex, indicate that the Si response is strongly related to key steps in metabolic regulation. PMID:27846149

  20. Automated Discovery of Elementary Chemical Reaction Steps Using Freezing String and Berny Optimization Methods.

    PubMed

    Suleimanov, Yury V; Green, William H

    2015-09-08

    We present a simple protocol which allows fully automated discovery of elementary chemical reaction steps using in cooperation double- and single-ended transition-state optimization algorithms--the freezing string and Berny optimization methods, respectively. To demonstrate the utility of the proposed approach, the reactivity of several single-molecule systems of combustion and atmospheric chemistry importance is investigated. The proposed algorithm allowed us to detect without any human intervention not only "known" reaction pathways, manually detected in the previous studies, but also new, previously "unknown", reaction pathways which involve significant atom rearrangements. We believe that applying such a systematic approach to elementary reaction path finding will greatly accelerate the discovery of new chemistry and will lead to more accurate computer simulations of various chemical processes.

  1. Discovery of naked charm particles and lifetime differences among charm species using nuclear emulsion techniques innovated in Japan

    PubMed Central

    NIU, Kiyoshi

    2008-01-01

    This is a historical review of the discovery of naked charm particles and lifetime differences among charm species. These discoveries in the field of cosmic-ray physics were made by the innovation of nuclear emulsion techniques in Japan. A pair of naked charm particles was discovered in 1971 in a cosmic-ray interaction, three years prior to the discovery of the hidden charm particle, J/Ψ, in western countries. Lifetime differences between charged and neutral charm particles were pointed out in 1975, which were later re-confirmed by the collaborative Experiment E531 at Fermilab. Japanese physicists led by K.Niu made essential contributions to it with improved emulsion techniques, complemented by electronic detectors. This review also discusses the discovery of artificially produced naked charm particles by us in an accelerator experiment at Fermilab in 1975 and of multiple-pair productions of charm particles in a single interaction in 1987 by the collaborative Experiment WA75 at CERN. PMID:18941283

  2. Integrating functional genomics to accelerate mechanistic personalized medicine.

    PubMed

    Tyner, Jeffrey W

    2017-03-01

    The advent of deep sequencing technologies has resulted in the deciphering of tremendous amounts of genetic information. These data have led to major discoveries, and many anecdotes now exist of individual patients whose clinical outcomes have benefited from novel, genetically guided therapeutic strategies. However, the majority of genetic events in cancer are currently undrugged, leading to a biological gap between understanding of tumor genetic etiology and translation to improved clinical approaches. Functional screening has made tremendous strides in recent years with the development of new experimental approaches to studying ex vivo and in vivo drug sensitivity. Numerous discoveries and anecdotes also exist for translation of functional screening into novel clinical strategies; however, the current clinical application of functional screening remains largely confined to small clinical trials at specific academic centers. The intersection between genomic and functional approaches represents an ideal modality to accelerate our understanding of drug sensitivities as they relate to specific genetic events and further understand the full mechanisms underlying drug sensitivity patterns.

  3. Knowledge discovery by accuracy maximization

    PubMed Central

    Cacciatore, Stefano; Luchinat, Claudio; Tenori, Leonardo

    2014-01-01

    Here we describe KODAMA (knowledge discovery by accuracy maximization), an unsupervised and semisupervised learning algorithm that performs feature extraction from noisy and high-dimensional data. Unlike other data mining methods, the peculiarity of KODAMA is that it is driven by an integrated procedure of cross-validation of the results. The discovery of a local manifold’s topology is led by a classifier through a Monte Carlo procedure of maximization of cross-validated predictive accuracy. Briefly, our approach differs from previous methods in that it has an integrated procedure of validation of the results. In this way, the method ensures the highest robustness of the obtained solution. This robustness is demonstrated on experimental datasets of gene expression and metabolomics, where KODAMA compares favorably with other existing feature extraction methods. KODAMA is then applied to an astronomical dataset, revealing unexpected features. Interesting and not easily predictable features are also found in the analysis of the State of the Union speeches by American presidents: KODAMA reveals an abrupt linguistic transition sharply separating all post-Reagan from all pre-Reagan speeches. The transition occurs during Reagan’s presidency and not from its beginning. PMID:24706821

  4. Research opportunities with compact accelerator-driven neutron sources

    NASA Astrophysics Data System (ADS)

    Anderson, I. S.; Andreani, C.; Carpenter, J. M.; Festa, G.; Gorini, G.; Loong, C.-K.; Senesi, R.

    2016-10-01

    Since the discovery of the neutron in 1932 neutron beams have been used in a very broad range of applications, As an aging fleet of nuclear reactor sources is retired the use of compact accelerator-driven neutron sources (CANS) is becoming more prevalent. CANS are playing a significant and expanding role in research and development in science and engineering, as well as in education and training. In the realm of multidisciplinary applications, CANS offer opportunities over a wide range of technical utilization, from interrogation of civil structures to medical therapy to cultural heritage study. This paper aims to provide the first comprehensive overview of the history, current status of operation, and ongoing development of CANS worldwide. The basic physics and engineering regarding neutron production by accelerators, target-moderator systems, and beam line instrumentation are introduced, followed by an extensive discussion of various evolving applications currently exploited at CANS.

  5. Genetics of rheumatoid arthritis contributes to biology and drug discovery.

    PubMed

    Okada, Yukinori; Wu, Di; Trynka, Gosia; Raj, Towfique; Terao, Chikashi; Ikari, Katsunori; Kochi, Yuta; Ohmura, Koichiro; Suzuki, Akari; Yoshida, Shinji; Graham, Robert R; Manoharan, Arun; Ortmann, Ward; Bhangale, Tushar; Denny, Joshua C; Carroll, Robert J; Eyler, Anne E; Greenberg, Jeffrey D; Kremer, Joel M; Pappas, Dimitrios A; Jiang, Lei; Yin, Jian; Ye, Lingying; Su, Ding-Feng; Yang, Jian; Xie, Gang; Keystone, Ed; Westra, Harm-Jan; Esko, Tõnu; Metspalu, Andres; Zhou, Xuezhong; Gupta, Namrata; Mirel, Daniel; Stahl, Eli A; Diogo, Dorothée; Cui, Jing; Liao, Katherine; Guo, Michael H; Myouzen, Keiko; Kawaguchi, Takahisa; Coenen, Marieke J H; van Riel, Piet L C M; van de Laar, Mart A F J; Guchelaar, Henk-Jan; Huizinga, Tom W J; Dieudé, Philippe; Mariette, Xavier; Bridges, S Louis; Zhernakova, Alexandra; Toes, Rene E M; Tak, Paul P; Miceli-Richard, Corinne; Bang, So-Young; Lee, Hye-Soon; Martin, Javier; Gonzalez-Gay, Miguel A; Rodriguez-Rodriguez, Luis; Rantapää-Dahlqvist, Solbritt; Arlestig, Lisbeth; Choi, Hyon K; Kamatani, Yoichiro; Galan, Pilar; Lathrop, Mark; Eyre, Steve; Bowes, John; Barton, Anne; de Vries, Niek; Moreland, Larry W; Criswell, Lindsey A; Karlson, Elizabeth W; Taniguchi, Atsuo; Yamada, Ryo; Kubo, Michiaki; Liu, Jun S; Bae, Sang-Cheol; Worthington, Jane; Padyukov, Leonid; Klareskog, Lars; Gregersen, Peter K; Raychaudhuri, Soumya; Stranger, Barbara E; De Jager, Philip L; Franke, Lude; Visscher, Peter M; Brown, Matthew A; Yamanaka, Hisashi; Mimori, Tsuneyo; Takahashi, Atsushi; Xu, Huji; Behrens, Timothy W; Siminovitch, Katherine A; Momohara, Shigeki; Matsuda, Fumihiko; Yamamoto, Kazuhiko; Plenge, Robert M

    2014-02-20

    A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ∼10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2 - 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci and pathway analyses--as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes--to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

  6. GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

    PubMed

    Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

    2018-01-01

    When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

  7. How rare bone diseases have informed our knowledge of complex diseases.

    PubMed

    Johnson, Mark L

    2016-01-01

    Rare bone diseases, generally defined as monogenic traits with either autosomal recessive or dominant patterns of inheritance, have provided a rich database of genes and associated pathways over the past 2-3 decades. The molecular genetic dissection of these bone diseases has yielded some major surprises in terms of the causal genes and/or involved pathways. The discovery of genes/pathways involved in diseases such as osteopetrosis, osteosclerosis, osteogenesis imperfecta and many other rare bone diseases have all accelerated our understanding of complex traits. Importantly these discoveries have provided either direct validation for a specific gene embedded in a group of genes within an interval identified through a complex trait genome-wide association study (GWAS) or based upon the pathway associated with a monogenic trait gene, provided a means to prioritize a large number of genes for functional validation studies. In some instances GWAS studies have yielded candidate genes that fall within linkage intervals associated with monogenic traits and resulted in the identification of causal mutations in those rare diseases. Driving all of this discovery is a complement of technologies such as genome sequencing, bioinformatics and advanced statistical analysis methods that have accelerated genetic dissection and greatly reduced the cost. Thus, rare bone disorders in partnership with GWAS have brought us to the brink of a new era of personalized genomic medicine in which the prevention and management of complex diseases will be driven by the molecular understanding of each individuals contributing genetic risks for disease.

  8. Improved accuracy of supervised CRM discovery with interpolated Markov models and cross-species comparison.

    PubMed

    Kazemian, Majid; Zhu, Qiyun; Halfon, Marc S; Sinha, Saurabh

    2011-12-01

    Despite recent advances in experimental approaches for identifying transcriptional cis-regulatory modules (CRMs, 'enhancers'), direct empirical discovery of CRMs for all genes in all cell types and environmental conditions is likely to remain an elusive goal. Effective methods for computational CRM discovery are thus a critically needed complement to empirical approaches. However, existing computational methods that search for clusters of putative binding sites are ineffective if the relevant TFs and/or their binding specificities are unknown. Here, we provide a significantly improved method for 'motif-blind' CRM discovery that does not depend on knowledge or accurate prediction of TF-binding motifs and is effective when limited knowledge of functional CRMs is available to 'supervise' the search. We propose a new statistical method, based on 'Interpolated Markov Models', for motif-blind, genome-wide CRM discovery. It captures the statistical profile of variable length words in known CRMs of a regulatory network and finds candidate CRMs that match this profile. The method also uses orthologs of the known CRMs from closely related genomes. We perform in silico evaluation of predicted CRMs by assessing whether their neighboring genes are enriched for the expected expression patterns. This assessment uses a novel statistical test that extends the widely used Hypergeometric test of gene set enrichment to account for variability in intergenic lengths. We find that the new CRM prediction method is superior to existing methods. Finally, we experimentally validate 12 new CRM predictions by examining their regulatory activity in vivo in Drosophila; 10 of the tested CRMs were found to be functional, while 6 of the top 7 predictions showed the expected activity patterns. We make our program available as downloadable source code, and as a plugin for a genome browser installed on our servers. © The Author(s) 2011. Published by Oxford University Press.

  9. Improved accuracy of supervised CRM discovery with interpolated Markov models and cross-species comparison

    PubMed Central

    Kazemian, Majid; Zhu, Qiyun; Halfon, Marc S.; Sinha, Saurabh

    2011-01-01

    Despite recent advances in experimental approaches for identifying transcriptional cis-regulatory modules (CRMs, ‘enhancers’), direct empirical discovery of CRMs for all genes in all cell types and environmental conditions is likely to remain an elusive goal. Effective methods for computational CRM discovery are thus a critically needed complement to empirical approaches. However, existing computational methods that search for clusters of putative binding sites are ineffective if the relevant TFs and/or their binding specificities are unknown. Here, we provide a significantly improved method for ‘motif-blind’ CRM discovery that does not depend on knowledge or accurate prediction of TF-binding motifs and is effective when limited knowledge of functional CRMs is available to ‘supervise’ the search. We propose a new statistical method, based on ‘Interpolated Markov Models’, for motif-blind, genome-wide CRM discovery. It captures the statistical profile of variable length words in known CRMs of a regulatory network and finds candidate CRMs that match this profile. The method also uses orthologs of the known CRMs from closely related genomes. We perform in silico evaluation of predicted CRMs by assessing whether their neighboring genes are enriched for the expected expression patterns. This assessment uses a novel statistical test that extends the widely used Hypergeometric test of gene set enrichment to account for variability in intergenic lengths. We find that the new CRM prediction method is superior to existing methods. Finally, we experimentally validate 12 new CRM predictions by examining their regulatory activity in vivo in Drosophila; 10 of the tested CRMs were found to be functional, while 6 of the top 7 predictions showed the expected activity patterns. We make our program available as downloadable source code, and as a plugin for a genome browser installed on our servers. PMID:21821659

  10. Discovery of Novel Mammary Developmental and Cancer Genes Using ENU Mutagenesis

    DTIC Science & Technology

    2002-10-01

    death rates we need new therapeutic targets, currently a major challenge facing cancer researchers This requires an understanding of the undiscovered pathways that operate to drive breast cancer cell proliferation, cell survival and cell differentiation, pathways which are also likely to operate during normal mammary development, and which go awry in cancer The discovery of signalling pathways operative in breast cancer has utilised examination of mammary gland development following systemic endocrine ablation or viral insertion, positional cloning in affected families and

  11. Discovery of Seven Novel Mammalian and Avian Coronaviruses in the Genus Deltacoronavirus Supports Bat Coronaviruses as the Gene Source of Alphacoronavirus and Betacoronavirus and Avian Coronaviruses as the Gene Source of Gammacoronavirus and Deltacoronavirus

    PubMed Central

    Woo, Patrick C. Y.; Lau, Susanna K. P.; Lam, Carol S. F.; Lau, Candy C. Y.; Tsang, Alan K. L.; Lau, John H. N.; Bai, Ru; Teng, Jade L. L.; Tsang, Chris C. C.; Wang, Ming; Zheng, Bo-Jian; Chan, Kwok-Hung

    2012-01-01

    Recently, we reported the discovery of three novel coronaviruses, bulbul coronavirus HKU11, thrush coronavirus HKU12, and munia coronavirus HKU13, which were identified as representatives of a novel genus, Deltacoronavirus, in the subfamily Coronavirinae. In this territory-wide molecular epidemiology study involving 3,137 mammals and 3,298 birds, we discovered seven additional novel deltacoronaviruses in pigs and birds, which we named porcine coronavirus HKU15, white-eye coronavirus HKU16, sparrow coronavirus HKU17, magpie robin coronavirus HKU18, night heron coronavirus HKU19, wigeon coronavirus HKU20, and common moorhen coronavirus HKU21. Complete genome sequencing and comparative genome analysis showed that the avian and mammalian deltacoronaviruses have similar genome characteristics and structures. They all have relatively small genomes (25.421 to 26.674 kb), the smallest among all coronaviruses. They all have a single papain-like protease domain in the nsp3 gene; an accessory gene, NS6 open reading frame (ORF), located between the M and N genes; and a variable number of accessory genes (up to four) downstream of the N gene. Moreover, they all have the same putative transcription regulatory sequence of ACACCA. Molecular clock analysis showed that the most recent common ancestor of all coronaviruses was estimated at approximately 8100 BC, and those of Alphacoronavirus, Betacoronavirus, Gammacoronavirus, and Deltacoronavirus were at approximately 2400 BC, 3300 BC, 2800 BC, and 3000 BC, respectively. From our studies, it appears that bats and birds, the warm blooded flying vertebrates, are ideal hosts for the coronavirus gene source, bats for Alphacoronavirus and Betacoronavirus and birds for Gammacoronavirus and Deltacoronavirus, to fuel coronavirus evolution and dissemination. PMID:22278237

  12. Discovery of seven novel Mammalian and avian coronaviruses in the genus deltacoronavirus supports bat coronaviruses as the gene source of alphacoronavirus and betacoronavirus and avian coronaviruses as the gene source of gammacoronavirus and deltacoronavirus.

    PubMed

    Woo, Patrick C Y; Lau, Susanna K P; Lam, Carol S F; Lau, Candy C Y; Tsang, Alan K L; Lau, John H N; Bai, Ru; Teng, Jade L L; Tsang, Chris C C; Wang, Ming; Zheng, Bo-Jian; Chan, Kwok-Hung; Yuen, Kwok-Yung

    2012-04-01

    Recently, we reported the discovery of three novel coronaviruses, bulbul coronavirus HKU11, thrush coronavirus HKU12, and munia coronavirus HKU13, which were identified as representatives of a novel genus, Deltacoronavirus, in the subfamily Coronavirinae. In this territory-wide molecular epidemiology study involving 3,137 mammals and 3,298 birds, we discovered seven additional novel deltacoronaviruses in pigs and birds, which we named porcine coronavirus HKU15, white-eye coronavirus HKU16, sparrow coronavirus HKU17, magpie robin coronavirus HKU18, night heron coronavirus HKU19, wigeon coronavirus HKU20, and common moorhen coronavirus HKU21. Complete genome sequencing and comparative genome analysis showed that the avian and mammalian deltacoronaviruses have similar genome characteristics and structures. They all have relatively small genomes (25.421 to 26.674 kb), the smallest among all coronaviruses. They all have a single papain-like protease domain in the nsp3 gene; an accessory gene, NS6 open reading frame (ORF), located between the M and N genes; and a variable number of accessory genes (up to four) downstream of the N gene. Moreover, they all have the same putative transcription regulatory sequence of ACACCA. Molecular clock analysis showed that the most recent common ancestor of all coronaviruses was estimated at approximately 8100 BC, and those of Alphacoronavirus, Betacoronavirus, Gammacoronavirus, and Deltacoronavirus were at approximately 2400 BC, 3300 BC, 2800 BC, and 3000 BC, respectively. From our studies, it appears that bats and birds, the warm blooded flying vertebrates, are ideal hosts for the coronavirus gene source, bats for Alphacoronavirus and Betacoronavirus and birds for Gammacoronavirus and Deltacoronavirus, to fuel coronavirus evolution and dissemination.

  13. Supernovae and the Accelerating Universe

    NASA Technical Reports Server (NTRS)

    Wood, H. John

    2003-01-01

    Orbiting high above the turbulence of the earth's atmosphere, the Hubble Space Telescope (HST) has provided breathtaking views of astronomical objects never before seen in such detail. The steady diffraction-limited images allow this medium-size telescope to reach faint galaxies of 30th stellar magnitude. Some of these galaxies are seen as early as 2 billion years after the Big Bang in a 15 billion year old universe. Up until recently, astronomers assumed that all of the laws of physics and astronomy applied back then as they do today. Now, using the discovery that certain supernovae are standard candles, astronomers have found that the universe is expanding faster today than it was back then: the universe is accelerating in its expansion.

  14. Systematic prediction of gene function in Arabidopsis thaliana using a probabilistic functional gene network

    PubMed Central

    Hwang, Sohyun; Rhee, Seung Y; Marcotte, Edward M; Lee, Insuk

    2012-01-01

    AraNet is a functional gene network for the reference plant Arabidopsis and has been constructed in order to identify new genes associated with plant traits. It is highly predictive for diverse biological pathways and can be used to prioritize genes for functional screens. Moreover, AraNet provides a web-based tool with which plant biologists can efficiently discover novel functions of Arabidopsis genes (http://www.functionalnet.org/aranet/). This protocol explains how to conduct network-based prediction of gene functions using AraNet and how to interpret the prediction results. Functional discovery in plant biology is facilitated by combining candidate prioritization by AraNet with focused experimental tests. PMID:21886106

  15. Loss of circadian clock accelerates aging in neurodegeneration-prone mutants.

    PubMed

    Krishnan, Natraj; Rakshit, Kuntol; Chow, Eileen S; Wentzell, Jill S; Kretzschmar, Doris; Giebultowicz, Jadwiga M

    2012-03-01

    Circadian clocks generate rhythms in molecular, cellular, physiological, and behavioral processes. Recent studies suggest that disruption of the clock mechanism accelerates organismal senescence and age-related pathologies in mammals. Impaired circadian rhythms are observed in many neurological diseases; however, it is not clear whether loss of rhythms is the cause or result of neurodegeneration, or both. To address this important question, we examined the effects of circadian disruption in Drosophila melanogaster mutants that display clock-unrelated neurodegenerative phenotypes. We combined a null mutation in the clock gene period (per(01)) that abolishes circadian rhythms, with a hypomorphic mutation in the carbonyl reductase gene sniffer (sni(1)), which displays oxidative stress induced neurodegeneration. We report that disruption of circadian rhythms in sni(1) mutants significantly reduces their lifespan compared to single mutants. Shortened lifespan in double mutants was coupled with accelerated neuronal degeneration evidenced by vacuolization in the adult brain. In addition, per(01)sni(1) flies showed drastically impaired vertical mobility and increased accumulation of carbonylated proteins compared to age-matched single mutant flies. Loss of per function does not affect sni mRNA expression, suggesting that these genes act via independent pathways producing additive effects. Finally, we show that per(01) mutation accelerates the onset of brain pathologies when combined with neurodegeneration-prone mutation in another gene, swiss cheese (sws(1)), which does not operate through the oxidative stress pathway. Taken together, our data suggest that the period gene may be causally involved in neuroprotective pathways in aging Drosophila. Copyright © 2011 Elsevier Inc. All rights reserved.

  16. Loss of circadian clock accelerates aging in neurodegeneration-prone mutants

    PubMed Central

    Krishnan, Natraj; Rakshit, Kuntol; Chow, Eileen S.; Wentzell, Jill S.; Kretzschmar, Doris; Giebultowicz, Jadwiga M.

    2012-01-01

    Circadian clocks generate rhythms in molecular, cellular, physiological, and behavioral processes. Recent studies suggest that disruption of the clock mechanism accelerates organismal senescence and age-related pathologies in mammals. Impaired circadian rhythms are observed in many neurological diseases; however, it is not clear whether loss of rhythms is the cause or result of neurodegeneration, or both. To address this important question, we examined the effects of circadian disruption in Drosophila melanogaster mutants that display clock-unrelated neurodegenerative phenotypes. We combined a null mutation in the clock gene period (per01) that abolishes circadian rhythms, with a hypomorphic mutation in the carbonyl reductase gene sniffer (sni1), which displays oxidative stress induced neurodegeneration. We report that disruption of circadian rhythms in sni1 mutants significantly reduces their lifespan compared to single mutants. Shortened lifespan in double mutants was coupled with accelerated neuronal degeneration evidenced by vacuolization in the adult brain. In addition, per01 sni1 flies showed drastically impaired vertical mobility and increased accumulation of carbonylated proteins compared to age-matched single mutant flies. Loss of per function does not affect sni mRNA expression, suggesting that these genes act via independent pathways producing additive effects. Finally, we show that per01 mutation accelerates the onset of brain pathologies when combined with neurodegeneration-prone mutation in another gene, swiss cheese (sws1), which does not operate through the oxidative stress pathway. Taken together, our data suggest that the period gene may be causally involved in neuroprotective pathways in aging Drosophila. PMID:22227001

  17. Ligand-accelerated enantioselective methylene C(sp3)-H bond activation.

    PubMed

    Chen, Gang; Gong, Wei; Zhuang, Zhe; Andrä, Michal S; Chen, Yan-Qiao; Hong, Xin; Yang, Yun-Fang; Liu, Tao; Houk, K N; Yu, Jin-Quan

    2016-09-02

    Effective differentiation of prochiral carbon-hydrogen (C-H) bonds on a single methylene carbon via asymmetric metal insertion remains a challenge. Here, we report the discovery of chiral acetyl-protected aminoethyl quinoline ligands that enable asymmetric palladium insertion into prochiral C-H bonds on a single methylene carbon center. We apply these palladium complexes to catalytic enantioselective functionalization of β-methylene C-H bonds in aliphatic amides. Using bidentate ligands to accelerate C-H activation of otherwise unreactive monodentate substrates is crucial for outcompeting the background reaction driven by substrate-directed cyclopalladation, thereby avoiding erosion of enantioselectivity. The potential of ligand acceleration in C-H activation is also demonstrated by enantioselective β-C-H arylation of simple carboxylic acids without installing directing groups. Copyright © 2016, American Association for the Advancement of Science.

  18. Evidence of the Red-Queen Hypothesis from Accelerated Rates of Evolution of Genes Involved in Biotic Interactions in Pneumocystis.

    PubMed

    Delaye, Luis; Ruiz-Ruiz, Susana; Calderon, Enrique; Tarazona, Sonia; Conesa, Ana; Moya, Andrés

    2018-06-01

    Pneumocystis species are ascomycete fungi adapted to live inside the lungs of mammals. These ascomycetes show extensive stenoxenism, meaning that each species of Pneumocystis infects a single species of host. Here, we study the effect exerted by natural selection on gene evolution in the genomes of three Pneumocystis species. We show that genes involved in host interaction evolve under positive selection. In the first place, we found strong evidence of episodic diversifying selection in Major surface glycoproteins (Msg). These proteins are located on the surface of Pneumocystis and are used for host attachment and probably for immune system evasion. Consistent with their function as antigens, most sites under diversifying selection in Msg code for residues with large relative surface accessibility areas. We also found evidence of positive selection in part of the cell machinery used to export Msg to the cell surface. Specifically, we found that genes participating in glycosylphosphatidylinositol (GPI) biosynthesis show an increased rate of nonsynonymous substitutions (dN) versus synonymous substitutions (dS). GPI is a molecule synthesized in the endoplasmic reticulum that is used to anchor proteins to membranes. We interpret the aforementioned findings as evidence of selective pressure exerted by the host immune system on Pneumocystis species, shaping the evolution of Msg and several proteins involved in GPI biosynthesis. We suggest that genome evolution in Pneumocystis is well described by the Red-Queen hypothesis whereby genes relevant for biotic interactions show accelerated rates of evolution.

  19. Down-Regulation of Gene Expression by RNA-Induced Gene Silencing

    NASA Astrophysics Data System (ADS)

    Travella, Silvia; Keller, Beat

    Down-regulation of endogenous genes via post-transcriptional gene silencing (PTGS) is a key to the characterization of gene function in plants. Many RNA-based silencing mechanisms such as post-transcriptional gene silencing, co-suppression, quelling, and RNA interference (RNAi) have been discovered among species of different kingdoms (plants, fungi, and animals). One of the most interesting discoveries was RNAi, a sequence-specific gene-silencing mechanism initiated by the introduction of double-stranded RNA (dsRNA), homologous in sequence to the silenced gene, which triggers degradation of mRNA. Infection of plants with modified viruses can also induce RNA silencing and is referred to as virus-induced gene silencing (VIGS). In contrast to insertional mutagenesis, these emerging new reverse genetic approaches represent a powerful tool for exploring gene function and for manipulating gene expression experimentally in cereal species such as barley and wheat. We examined how RNAi and VIGS have been used to assess gene function in barley and wheat, including molecular mechanisms involved in the process and available methodological elements, such as vectors, inoculation procedures, and analysis of silenced phenotypes.

  20. Induction of Bim and Bid gene expression during accelerated apoptosis in severe sepsis.

    PubMed

    Weber, Stefan U; Schewe, Jens-Christian; Lehmann, Lutz E; Müller, Stefan; Book, Malte; Klaschik, Sven; Hoeft, Andreas; Stüber, Frank

    2008-01-01

    In transgenic animal models of sepsis, members of the Bcl-2 family of proteins regulate lymphocyte apoptosis and survival of sepsis. This study investigates the gene regulation of pro-apoptotic and anti-apoptotic members of the Bcl-2 family of proteins in patients with early stage severe sepsis. In this prospective case-control study, patients were recruited from three intensive care units (ICUs) in a university hospital. Sixteen patients were enrolled when they fulfilled the criteria of severe sepsis. Ten critically ill but non-septic patients and 11 healthy volunteers served as controls. Blood samples were immediately obtained at inclusion. To confirm the presence of accelerated apoptosis in the patient groups, caspase-3 activation and phosphatidylserine externalisation in CD4+, CD8+ and CD19+ lymphocyte subsets were assessed using flow cytometry. Specific mRNAs of Bcl-2 family members were quantified from whole blood by real-time PCR. To test for statistical significance, Kruskal-Wallis testing with Dunn's multiple comparison test for post hoc analysis was performed. In all lymphocyte populations caspase-3 (p < 0.05) was activated, which was reflected in an increased phosphatidylserine externalisation (p < 0.05). Accordingly, lymphocyte counts were decreased in early severe sepsis. In CD4+ T-cells (p < 0.05) and B-cells (p < 0.001) the Bcl-2 protein was decreased in severe sepsis. Gene expression of the BH3-only Bim was massively upregulated as compared with critically ill patients (p < 0.001) and 51.6-fold as compared with healthy controls (p < 0.05). Bid was increased 12.9-fold compared with critically ill patients (p < 0.001). In the group of mitochondrial apoptosis inducers, Bak was upregulated 5.6-fold, while the expression of Bax showed no significant variations. By contrast, the pro-survival members Bcl-2 and Bcl-xl were both downregulated in severe sepsis (p < 0.001 and p < 0.05, respectively). In early severe sepsis a gene expression pattern with

  1. Discovery Systems

    NASA Technical Reports Server (NTRS)

    Pell, Barney

    2003-01-01

    A viewgraph presentation on NASA's Discovery Systems Project is given. The topics of discussion include: 1) NASA's Computing Information and Communications Technology Program; 2) Discovery Systems Program; and 3) Ideas for Information Integration Using the Web.

  2. MUFFINN: cancer gene discovery via network analysis of somatic mutation data.

    PubMed

    Cho, Ara; Shim, Jung Eun; Kim, Eiru; Supek, Fran; Lehner, Ben; Lee, Insuk

    2016-06-23

    A major challenge for distinguishing cancer-causing driver mutations from inconsequential passenger mutations is the long-tail of infrequently mutated genes in cancer genomes. Here, we present and evaluate a method for prioritizing cancer genes accounting not only for mutations in individual genes but also in their neighbors in functional networks, MUFFINN (MUtations For Functional Impact on Network Neighbors). This pathway-centric method shows high sensitivity compared with gene-centric analyses of mutation data. Notably, only a marginal decrease in performance is observed when using 10 % of TCGA patient samples, suggesting the method may potentiate cancer genome projects with small patient populations.

  3. 14 CFR 406.143 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 4 2014-01-01 2014-01-01 false Discovery. 406.143 Section 406.143... Transportation Adjudications § 406.143 Discovery. (a) Initiation of discovery. Any party may initiate discovery... after a complaint has been filed. (b) Methods of discovery. The following methods of discovery are...

  4. 14 CFR 406.143 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 4 2011-01-01 2011-01-01 false Discovery. 406.143 Section 406.143... Transportation Adjudications § 406.143 Discovery. (a) Initiation of discovery. Any party may initiate discovery... after a complaint has been filed. (b) Methods of discovery. The following methods of discovery are...

  5. 14 CFR 406.143 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 4 2012-01-01 2012-01-01 false Discovery. 406.143 Section 406.143... Transportation Adjudications § 406.143 Discovery. (a) Initiation of discovery. Any party may initiate discovery... after a complaint has been filed. (b) Methods of discovery. The following methods of discovery are...

  6. 14 CFR 406.143 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 4 2013-01-01 2013-01-01 false Discovery. 406.143 Section 406.143... Transportation Adjudications § 406.143 Discovery. (a) Initiation of discovery. Any party may initiate discovery... after a complaint has been filed. (b) Methods of discovery. The following methods of discovery are...

  7. 14 CFR 406.143 - Discovery.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Discovery. 406.143 Section 406.143... Transportation Adjudications § 406.143 Discovery. (a) Initiation of discovery. Any party may initiate discovery... after a complaint has been filed. (b) Methods of discovery. The following methods of discovery are...

  8. Strain Prioritization for Natural Product Discovery by a High-Throughput Real-Time PCR Method

    PubMed Central

    2015-01-01

    Natural products offer unmatched chemical and structural diversity compared to other small-molecule libraries, but traditional natural product discovery programs are not sustainable, demanding too much time, effort, and resources. Here we report a strain prioritization method for natural product discovery. Central to the method is the application of real-time PCR, targeting genes characteristic to the biosynthetic machinery of natural products with distinct scaffolds in a high-throughput format. The practicality and effectiveness of the method were showcased by prioritizing 1911 actinomycete strains for diterpenoid discovery. A total of 488 potential diterpenoid producers were identified, among which six were confirmed as platensimycin and platencin dual producers and one as a viguiepinol and oxaloterpin producer. While the method as described is most appropriate to prioritize strains for discovering specific natural products, variations of this method should be applicable to the discovery of other classes of natural products. Applications of genome sequencing and genome mining to the high-priority strains could essentially eliminate the chance elements from traditional discovery programs and fundamentally change how natural products are discovered. PMID:25238028

  9. The Fragile X Mental Retardation Syndrome 20 Years After the FMR1 Gene Discovery: an Expanding Universe of Knowledge

    PubMed Central

    Rousseau, François; Labelle, Yves; Bussières, Johanne; Lindsay, Carmen

    2011-01-01

    The fragile X mental retardation (FXMR) syndrome is one of the most frequent causes of mental retardation. Affected individuals display a wide range of additional characteristic features including behavioural and physical phenotypes, and the extent to which individuals are affected is highly variable. For these reasons, elucidation of the pathophysiology of this disease has been an important challenge to the scientific community. 1991 marks the year of the discovery of both the FMR1 gene mutations involved in this disease, and of their dynamic nature. Although a mouse model for the disease has been available for 16 years and extensive research has been performed on the FMR1 protein (FMRP), we still understand little about how the disease develops, and no treatment has yet been shown to be effective. In this review, we summarise current knowledge on FXMR with an emphasis on the technical challenges of molecular diagnostics, on its prevalence and dynamics among populations, and on the potential of screening for FMR1 mutations. PMID:21912443

  10. The fragile x mental retardation syndrome 20 years after the FMR1 gene discovery: an expanding universe of knowledge.

    PubMed

    Rousseau, François; Labelle, Yves; Bussières, Johanne; Lindsay, Carmen

    2011-08-01

    The fragile X mental retardation (FXMR) syndrome is one of the most frequent causes of mental retardation. Affected individuals display a wide range of additional characteristic features including behavioural and physical phenotypes, and the extent to which individuals are affected is highly variable. For these reasons, elucidation of the pathophysiology of this disease has been an important challenge to the scientific community. 1991 marks the year of the discovery of both the FMR1 gene mutations involved in this disease, and of their dynamic nature. Although a mouse model for the disease has been available for 16 years and extensive research has been performed on the FMR1 protein (FMRP), we still understand little about how the disease develops, and no treatment has yet been shown to be effective. In this review, we summarise current knowledge on FXMR with an emphasis on the technical challenges of molecular diagnostics, on its prevalence and dynamics among populations, and on the potential of screening for FMR1 mutations.

  11. High-throughput discovery of rare human nucleotide polymorphisms by Ecotilling

    PubMed Central

    Till, Bradley J.; Zerr, Troy; Bowers, Elisabeth; Greene, Elizabeth A.; Comai, Luca; Henikoff, Steven

    2006-01-01

    Human individuals differ from one another at only ∼0.1% of nucleotide positions, but these single nucleotide differences account for most heritable phenotypic variation. Large-scale efforts to discover and genotype human variation have been limited to common polymorphisms. However, these efforts overlook rare nucleotide changes that may contribute to phenotypic diversity and genetic disorders, including cancer. Thus, there is an increasing need for high-throughput methods to robustly detect rare nucleotide differences. Toward this end, we have adapted the mismatch discovery method known as Ecotilling for the discovery of human single nucleotide polymorphisms. To increase throughput and reduce costs, we developed a universal primer strategy and implemented algorithms for automated band detection. Ecotilling was validated by screening 90 human DNA samples for nucleotide changes in 5 gene targets and by comparing results to public resequencing data. To increase throughput for discovery of rare alleles, we pooled samples 8-fold and found Ecotilling to be efficient relative to resequencing, with a false negative rate of 5% and a false discovery rate of 4%. We identified 28 new rare alleles, including some that are predicted to damage protein function. The detection of rare damaging mutations has implications for models of human disease. PMID:16893952

  12. A comprehensive resource of drought- and salinity- responsive ESTs for gene discovery and marker development in chickpea (Cicer arietinum L.)

    PubMed Central

    2009-01-01

    and their expression profile showed predominance in specific stress-challenged libraries. Conclusion Generated set of chickpea ESTs serves as a resource of high quality transcripts for gene discovery and development of functional markers associated with abiotic stress tolerance that will be helpful to facilitate chickpea breeding. Mapping of gene-based markers in chickpea will also add more anchoring points to align genomes of chickpea and other legume species. PMID:19912666

  13. Genome and transcriptome sequencing characterises the gene space of Macadamia integrifolia (Proteaceae).

    PubMed

    Nock, Catherine J; Baten, Abdul; Barkla, Bronwyn J; Furtado, Agnelo; Henry, Robert J; King, Graham J

    2016-11-17

    The large Gondwanan plant family Proteaceae is an early-diverging eudicot lineage renowned for its morphological, taxonomic and ecological diversity. Macadamia is the most economically important Proteaceae crop and represents an ancient rainforest-restricted lineage. The family is a focus for studies of adaptive radiation due to remarkable species diversification in Mediterranean-climate biodiversity hotspots, and numerous evolutionary transitions between biomes. Despite a long history of research, comparative analyses in the Proteaceae and macadamia breeding programs are restricted by a paucity of genetic information. To address this, we sequenced the genome and transcriptome of the widely grown Macadamia integrifolia cultivar 741. Over 95 gigabases of DNA and RNA-seq sequence data were de novo assembled and annotated. The draft assembly has a total length of 518 Mb and spans approximately 79% of the estimated genome size. Following annotation, 35,337 protein-coding genes were predicted of which over 90% were expressed in at least one of the leaf, shoot or flower tissues examined. Gene family comparisons with five other eudicot species revealed 13,689 clusters containing macadamia genes and 1005 macadamia-specific clusters, and provides evidence for linage-specific expansion of gene families involved in pathogen recognition, plant defense and monoterpene synthesis. Cyanogenesis is an important defense strategy in the Proteaceae, and a detailed analysis of macadamia gene homologues potentially involved in cyanogenic glycoside biosynthesis revealed several highly expressed candidate genes. The gene space of macadamia provides a foundation for comparative genomics, gene discovery and the acceleration of molecular-assisted breeding. This study presents the first available genomic resources for the large basal eudicot family Proteaceae, access to most macadamia genes and opportunities to uncover the genetic basis of traits of importance for adaptation and crop

  14. KIF16B is a candidate gene for a novel autosomal-recessive intellectual disability syndrome.

    PubMed

    Alsahli, Saud; Arold, Stefan T; Alfares, Ahmed; Alhaddad, Bader; Al Balwi, Mohammed; Kamsteeg, Erik-Jan; Al-Twaijri, Waleed; Alfadhel, Majid

    2018-05-07

    Intellectual disability (ID) and global developmental delay are closely related; the latter is reserved for children under the age of 5 years as it is challenging to reliably assess clinical severity in this population. ID is a common condition, with up to 1%-3% of the population being affected and leading to a huge social and economic impact. ID is attributed to genetic abnormalities most of the time; however, the exact role of genetic involvement in ID is yet to be determined. Whole exome sequencing (WES) has gained popularity in the workup for ID, and multiple studies have been published examining the diagnostic yield in identification of the disease-causing variant (16%-55%), with the genetic involvement increasing as intelligence quotient decreases. WES has also accelerated novel disease gene discovery in this field. We identified a novel biallelic variant in the KIF16B gene (NM_024704.4:c.3611T > G) in two brothers that may be the cause of their phenotype. © 2018 Wiley Periodicals, Inc.

  15. Menopause accelerates biological aging

    PubMed Central

    Levine, Morgan E.; Lu, Ake T.; Chen, Brian H.; Hernandez, Dena G.; Singleton, Andrew B.; Ferrucci, Luigi; Bandinelli, Stefania; Salfati, Elias; Manson, JoAnn E.; Quach, Austin; Kusters, Cynthia D. J.; Kuh, Diana; Wong, Andrew; Teschendorff, Andrew E.; Widschwendter, Martin; Ritz, Beate R.; Absher, Devin; Assimes, Themistocles L.; Horvath, Steve

    2016-01-01

    Although epigenetic processes have been linked to aging and disease in other systems, it is not yet known whether they relate to reproductive aging. Recently, we developed a highly accurate epigenetic biomarker of age (known as the “epigenetic clock”), which is based on DNA methylation levels. Here we carry out an epigenetic clock analysis of blood, saliva, and buccal epithelium using data from four large studies: the Women's Health Initiative (n = 1,864); Invecchiare nel Chianti (n = 200); Parkinson's disease, Environment, and Genes (n = 256); and the United Kingdom Medical Research Council National Survey of Health and Development (n = 790). We find that increased epigenetic age acceleration in blood is significantly associated with earlier menopause (P = 0.00091), bilateral oophorectomy (P = 0.0018), and a longer time since menopause (P = 0.017). Conversely, epigenetic age acceleration in buccal epithelium and saliva do not relate to age at menopause; however, a higher epigenetic age in saliva is exhibited in women who undergo bilateral oophorectomy (P = 0.0079), while a lower epigenetic age in buccal epithelium was found for women who underwent menopausal hormone therapy (P = 0.00078). Using genetic data, we find evidence of coheritability between age at menopause and epigenetic age acceleration in blood. Using Mendelian randomization analysis, we find that two SNPs that are highly associated with age at menopause exhibit a significant association with epigenetic age acceleration. Overall, our Mendelian randomization approach and other lines of evidence suggest that menopause accelerates epigenetic aging of blood, but mechanistic studies will be needed to dissect cause-and-effect relationships further. PMID:27457926

  16. An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework.

    PubMed

    Chen, Yi-An; Tripathi, Lokesh P; Mizuguchi, Kenji

    2016-01-01

    Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org. © The Author(s) 2016. Published by Oxford University Press.

  17. An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework

    PubMed Central

    Chen, Yi-An; Tripathi, Lokesh P.; Mizuguchi, Kenji

    2016-01-01

    Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org PMID:26989145

  18. Machine Learning for Detecting Gene-Gene Interactions

    PubMed Central

    McKinney, Brett A.; Reif, David M.; Ritchie, Marylyn D.; Moore, Jason H.

    2011-01-01

    Complex interactions among genes and environmental factors are known to play a role in common human disease aetiology. There is a growing body of evidence to suggest that complex interactions are ‘the norm’ and, rather than amounting to a small perturbation to classical Mendelian genetics, interactions may be the predominant effect. Traditional statistical methods are not well suited for detecting such interactions, especially when the data are high dimensional (many attributes or independent variables) or when interactions occur between more than two polymorphisms. In this review, we discuss machine-learning models and algorithms for identifying and characterising susceptibility genes in common, complex, multifactorial human diseases. We focus on the following machine-learning methods that have been used to detect gene-gene interactions: neural networks, cellular automata, random forests, and multifactor dimensionality reduction. We conclude with some ideas about how these methods and others can be integrated into a comprehensive and flexible framework for data mining and knowledge discovery in human genetics. PMID:16722772

  19. Accelerated recruitment of new brain development genes into the human genome.

    PubMed

    Zhang, Yong E; Landback, Patrick; Vibranovski, Maria D; Long, Manyuan

    2011-10-01

    How the human brain evolved has attracted tremendous interests for decades. Motivated by case studies of primate-specific genes implicated in brain function, we examined whether or not the young genes, those emerging genome-wide in the lineages specific to the primates or rodents, showed distinct spatial and temporal patterns of transcription compared to old genes, which had existed before primate and rodent split. We found consistent patterns across different sources of expression data: there is a significantly larger proportion of young genes expressed in the fetal or infant brain of humans than in mouse, and more young genes in humans have expression biased toward early developing brains than old genes. Most of these young genes are expressed in the evolutionarily newest part of human brain, the neocortex. Remarkably, we also identified a number of human-specific genes which are expressed in the prefrontal cortex, which is implicated in complex cognitive behaviors. The young genes upregulated in the early developing human brain play diverse functional roles, with a significant enrichment of transcription factors. Genes originating from different mechanisms show a similar expression bias in the developing brain. Moreover, we found that the young genes upregulated in early brain development showed rapid protein evolution compared to old genes also expressed in the fetal brain. Strikingly, genes expressed in the neocortex arose soon after its morphological origin. These four lines of evidence suggest that positive selection for brain function may have contributed to the origination of young genes expressed in the developing brain. These data demonstrate a striking recruitment of new genes into the early development of the human brain.

  20. Limitations and potentials of current motif discovery algorithms

    PubMed Central

    Hu, Jianjun; Li, Bin; Kihara, Daisuke

    2005-01-01

    Computational methods for de novo identification of gene regulation elements, such as transcription factor binding sites, have proved to be useful for deciphering genetic regulatory networks. However, despite the availability of a large number of algorithms, their strengths and weaknesses are not sufficiently understood. Here, we designed a comprehensive set of performance measures and benchmarked five modern sequence-based motif discovery algorithms using large datasets generated from Escherichia coli RegulonDB. Factors that affect the prediction accuracy, scalability and reliability are characterized. It is revealed that the nucleotide and the binding site level accuracy are very low, while the motif level accuracy is relatively high, which indicates that the algorithms can usually capture at least one correct motif in an input sequence. To exploit diverse predictions from multiple runs of one or more algorithms, a consensus ensemble algorithm has been developed, which achieved 6–45% improvement over the base algorithms by increasing both the sensitivity and specificity. Our study illustrates limitations and potentials of existing sequence-based motif discovery algorithms. Taking advantage of the revealed potentials, several promising directions for further improvements are discussed. Since the sequence-based algorithms are the baseline of most of the modern motif discovery algorithms, this paper suggests substantial improvements would be possible for them. PMID:16284194

  1. Evaluating reproducibility of differential expression discoveries in microarray studies by considering correlated molecular changes.

    PubMed

    Zhang, Min; Zhang, Lin; Zou, Jinfeng; Yao, Chen; Xiao, Hui; Liu, Qing; Wang, Jing; Wang, Dong; Wang, Chenguang; Guo, Zheng

    2009-07-01

    According to current consistency metrics such as percentage of overlapping genes (POG), lists of differentially expressed genes (DEGs) detected from different microarray studies for a complex disease are often highly inconsistent. This irreproducibility problem also exists in other high-throughput post-genomic areas such as proteomics and metabolism. A complex disease is often characterized with many coordinated molecular changes, which should be considered when evaluating the reproducibility of discovery lists from different studies. We proposed metrics percentage of overlapping genes-related (POGR) and normalized POGR (nPOGR) to evaluate the consistency between two DEG lists for a complex disease, considering correlated molecular changes rather than only counting gene overlaps between the lists. Based on microarray datasets of three diseases, we showed that though the POG scores for DEG lists from different studies for each disease are extremely low, the POGR and nPOGR scores can be rather high, suggesting that the apparently inconsistent DEG lists may be highly reproducible in the sense that they are actually significantly correlated. Observing different discovery results for a disease by the POGR and nPOGR scores will obviously reduce the uncertainty of the microarray studies. The proposed metrics could also be applicable in many other high-throughput post-genomic areas.

  2. Glycosyltransferase Gene Expression Profiles Classify Cancer Types and Propose Prognostic Subtypes

    NASA Astrophysics Data System (ADS)

    Ashkani, Jahanshah; Naidoo, Kevin J.

    2016-05-01

    Aberrant glycosylation in tumours stem from altered glycosyltransferase (GT) gene expression but can the expression profiles of these signature genes be used to classify cancer types and lead to cancer subtype discovery? The differential structural changes to cellular glycan structures are predominantly regulated by the expression patterns of GT genes and are a hallmark of neoplastic cell metamorphoses. We found that the expression of 210 GT genes taken from 1893 cancer patient samples in The Cancer Genome Atlas (TCGA) microarray data are able to classify six cancers; breast, ovarian, glioblastoma, kidney, colon and lung. The GT gene expression profiles are used to develop cancer classifiers and propose subtypes. The subclassification of breast cancer solid tumour samples illustrates the discovery of subgroups from GT genes that match well against basal-like and HER2-enriched subtypes and correlates to clinical, mutation and survival data. This cancer type glycosyltransferase gene signature finding provides foundational evidence for the centrality of glycosylation in cancer.

  3. Large-Scale Discovery of Disease-Disease and Disease-Gene Associations

    PubMed Central

    Gligorijevic, Djordje; Stojanovic, Jelena; Djuric, Nemanja; Radosavljevic, Vladan; Grbovic, Mihajlo; Kulathinal, Rob J.; Obradovic, Zoran

    2016-01-01

    Data-driven phenotype analyses on Electronic Health Record (EHR) data have recently drawn benefits across many areas of clinical practice, uncovering new links in the medical sciences that can potentially affect the well-being of millions of patients. In this paper, EHR data is used to discover novel relationships between diseases by studying their comorbidities (co-occurrences in patients). A novel embedding model is designed to extract knowledge from disease comorbidities by learning from a large-scale EHR database comprising more than 35 million inpatient cases spanning nearly a decade, revealing significant improvements on disease phenotyping over current computational approaches. In addition, the use of the proposed methodology is extended to discover novel disease-gene associations by including valuable domain knowledge from genome-wide association studies. To evaluate our approach, its effectiveness is compared against a held-out set where, again, it revealed very compelling results. For selected diseases, we further identify candidate gene lists for which disease-gene associations were not studied previously. Thus, our approach provides biomedical researchers with new tools to filter genes of interest, thus, reducing costly lab studies. PMID:27578529

  4. A hybrid computational method for the discovery of novel reproduction-related genes.

    PubMed

    Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

    2015-01-01

    Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

  5. The discovery of the periodic table as a case of simultaneous discovery.

    PubMed

    Scerri, Eric

    2015-03-13

    The article examines the question of priority and simultaneous discovery in the context of the discovery of the periodic system. It is argued that rather than being anomalous, simultaneous discovery is the rule. Moreover, I argue that the discovery of the periodic system by at least six authors in over a period of 7 years represents one of the best examples of a multiple discovery. This notion is supported by a new view of the evolutionary development of science through a mechanism that is dubbed Sci-Gaia by analogy with Lovelock's Gaia hypothesis. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  6. GEneSTATION 1.0: a synthetic resource of diverse evolutionary and functional genomic data for studying the evolution of pregnancy-associated tissues and phenotypes

    PubMed Central

    Kim, Mara; Cooper, Brian A.; Venkat, Rohit; Phillips, Julie B.; Eidem, Haley R.; Hirbo, Jibril; Nutakki, Sashank; Williams, Scott M.; Muglia, Louis J.; Capra, J. Anthony; Petren, Kenneth; Abbot, Patrick; Rokas, Antonis; McGary, Kriston L.

    2016-01-01

    Mammalian gestation and pregnancy are fast evolving processes that involve the interaction of the fetal, maternal and paternal genomes. Version 1.0 of the GEneSTATION database (http://genestation.org) integrates diverse types of omics data across mammals to advance understanding of the genetic basis of gestation and pregnancy-associated phenotypes and to accelerate the translation of discoveries from model organisms to humans. GEneSTATION is built using tools from the Generic Model Organism Database project, including the biology-aware database CHADO, new tools for rapid data integration, and algorithms that streamline synthesis and user access. GEneSTATION contains curated life history information on pregnancy and reproduction from 23 high-quality mammalian genomes. For every human gene, GEneSTATION contains diverse evolutionary (e.g. gene age, population genetic and molecular evolutionary statistics), organismal (e.g. tissue-specific gene and protein expression, differential gene expression, disease phenotype), and molecular data types (e.g. Gene Ontology Annotation, protein interactions), as well as links to many general (e.g. Entrez, PubMed) and pregnancy disease-specific (e.g. PTBgene, dbPTB) databases. By facilitating the synthesis of diverse functional and evolutionary data in pregnancy-associated tissues and phenotypes and enabling their quick, intuitive, accurate and customized meta-analysis, GEneSTATION provides a novel platform for comprehensive investigation of the function and evolution of mammalian pregnancy. PMID:26567549

  7. Discovery of genomic intervals that underlie nematode responses to benzimidazoles.

    PubMed

    Zamanian, Mostafa; Cook, Daniel E; Zdraljevic, Stefan; Brady, Shannon C; Lee, Daehan; Lee, Junho; Andersen, Erik C

    2018-03-01

    Parasitic nematodes impose a debilitating health and economic burden across much of the world. Nematode resistance to anthelmintic drugs threatens parasite control efforts in both human and veterinary medicine. Despite this threat, the genetic landscape of potential resistance mechanisms to these critical drugs remains largely unexplored. Here, we exploit natural variation in the model nematodes Caenorhabditis elegans and Caenorhabditis briggsae to discover quantitative trait loci (QTL) that control sensitivity to benzimidazoles widely used in human and animal medicine. High-throughput phenotyping of albendazole, fenbendazole, mebendazole, and thiabendazole responses in panels of recombinant lines led to the discovery of over 15 QTL in C. elegans and four QTL in C. briggsae associated with divergent responses to these anthelmintics. Many of these QTL are conserved across benzimidazole derivatives, but others show drug and dose specificity. We used near-isogenic lines to recapitulate and narrow the C. elegans albendazole QTL of largest effect and identified candidate variants correlated with the resistance phenotype. These QTL do not overlap with known benzimidazole target resistance genes from parasitic nematodes and present specific new leads for the discovery of novel mechanisms of nematode benzimidazole resistance. Analyses of orthologous genes reveal conservation of candidate benzimidazole resistance genes in medically important parasitic nematodes. These data provide a basis for extending these approaches to other anthelmintic drug classes and a pathway towards validating new markers for anthelmintic resistance that can be deployed to improve parasite disease control.

  8. "Eureka, Eureka!" Discoveries in Science

    ERIC Educational Resources Information Center

    Agarwal, Pankaj

    2011-01-01

    Accidental discoveries have been of significant value in the progress of science. Although accidental discoveries are more common in pharmacology and chemistry, other branches of science have also benefited from such discoveries. While most discoveries are the result of persistent research, famous accidental discoveries provide a fascinating…

  9. A Hybrid Computational Method for the Discovery of Novel Reproduction-Related Genes

    PubMed Central

    Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

    2015-01-01

    Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations. PMID:25768094

  10. 30 CFR 44.24 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Discovery. 44.24 Section 44.24 Mineral... Discovery. Parties shall be governed in their conduct of discovery by appropriate provisions of the Federal... discovery. Alternative periods of time for discovery may be prescribed by the presiding administrative law...

  11. 39 CFR 952.21 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 39 Postal Service 1 2014-07-01 2014-07-01 false Discovery. 952.21 Section 952.21 Postal Service... AND LOTTERY ORDERS § 952.21 Discovery. (a) Voluntary discovery. The parties are encouraged to engage in voluntary discovery procedures. In connection with any deposition or other discovery procedure...

  12. 39 CFR 952.21 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 39 Postal Service 1 2013-07-01 2013-07-01 false Discovery. 952.21 Section 952.21 Postal Service... AND LOTTERY ORDERS § 952.21 Discovery. (a) Voluntary discovery. The parties are encouraged to engage in voluntary discovery procedures. In connection with any deposition or other discovery procedure...

  13. 30 CFR 44.24 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Discovery. 44.24 Section 44.24 Mineral... Discovery. Parties shall be governed in their conduct of discovery by appropriate provisions of the Federal... discovery. Alternative periods of time for discovery may be prescribed by the presiding administrative law...

  14. 30 CFR 44.24 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Discovery. 44.24 Section 44.24 Mineral... Discovery. Parties shall be governed in their conduct of discovery by appropriate provisions of the Federal... discovery. Alternative periods of time for discovery may be prescribed by the presiding administrative law...

  15. 19 CFR 356.20 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 19 Customs Duties 3 2014-04-01 2014-04-01 false Discovery. 356.20 Section 356.20 Customs Duties... § 356.20 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery... sanctions proceeding. (b) Limitations on discovery. The administrative law judge shall place such limits...

  16. 39 CFR 952.21 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 39 Postal Service 1 2012-07-01 2012-07-01 false Discovery. 952.21 Section 952.21 Postal Service... AND LOTTERY ORDERS § 952.21 Discovery. (a) Voluntary discovery. The parties are encouraged to engage in voluntary discovery procedures. In connection with any deposition or other discovery procedure...

  17. 19 CFR 356.20 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 19 Customs Duties 3 2013-04-01 2013-04-01 false Discovery. 356.20 Section 356.20 Customs Duties... § 356.20 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery... sanctions proceeding. (b) Limitations on discovery. The administrative law judge shall place such limits...

  18. 19 CFR 356.20 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 19 Customs Duties 3 2012-04-01 2012-04-01 false Discovery. 356.20 Section 356.20 Customs Duties... § 356.20 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery... sanctions proceeding. (b) Limitations on discovery. The administrative law judge shall place such limits...

  19. 30 CFR 44.24 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Discovery. 44.24 Section 44.24 Mineral... Discovery. Parties shall be governed in their conduct of discovery by appropriate provisions of the Federal... discovery. Alternative periods of time for discovery may be prescribed by the presiding administrative law...

  20. 19 CFR 356.20 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 19 Customs Duties 3 2011-04-01 2011-04-01 false Discovery. 356.20 Section 356.20 Customs Duties... § 356.20 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery... sanctions proceeding. (b) Limitations on discovery. The administrative law judge shall place such limits...

  1. 30 CFR 44.24 - Discovery.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Discovery. 44.24 Section 44.24 Mineral... Discovery. Parties shall be governed in their conduct of discovery by appropriate provisions of the Federal... discovery. Alternative periods of time for discovery may be prescribed by the presiding administrative law...

  2. 19 CFR 356.20 - Discovery.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 356.20 Section 356.20 Customs Duties... § 356.20 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery... sanctions proceeding. (b) Limitations on discovery. The administrative law judge shall place such limits...

  3. Chemical Discovery

    ERIC Educational Resources Information Center

    Brown, Herbert C.

    1974-01-01

    The role of discovery in the advance of the science of chemistry and the factors that are currently operating to handicap that function are considered. Examples are drawn from the author's work with boranes. The thesis that exploratory research and discovery should be encouraged is stressed. (DT)

  4. 22 CFR 224.21 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 22 Foreign Relations 1 2013-04-01 2013-04-01 false Discovery. 224.21 Section 224.21 Foreign....21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of... parties, discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery...

  5. 24 CFR 180.500 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 24 Housing and Urban Development 1 2013-04-01 2013-04-01 false Discovery. 180.500 Section 180.500... OPPORTUNITY CONSOLIDATED HUD HEARING PROCEDURES FOR CIVIL RIGHTS MATTERS Discovery § 180.500 Discovery. (a) In general. This subpart governs discovery in aid of administrative proceedings under this part. Discovery in...

  6. 24 CFR 180.500 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 24 Housing and Urban Development 1 2014-04-01 2014-04-01 false Discovery. 180.500 Section 180.500... OPPORTUNITY CONSOLIDATED HUD HEARING PROCEDURES FOR CIVIL RIGHTS MATTERS Discovery § 180.500 Discovery. (a) In general. This subpart governs discovery in aid of administrative proceedings under this part. Discovery in...

  7. 22 CFR 224.21 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 22 Foreign Relations 1 2011-04-01 2011-04-01 false Discovery. 224.21 Section 224.21 Foreign....21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of... parties, discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery...

  8. 22 CFR 224.21 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 22 Foreign Relations 1 2012-04-01 2012-04-01 false Discovery. 224.21 Section 224.21 Foreign....21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of... parties, discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery...

  9. 24 CFR 180.500 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 24 Housing and Urban Development 1 2012-04-01 2012-04-01 false Discovery. 180.500 Section 180.500... OPPORTUNITY CONSOLIDATED HUD HEARING PROCEDURES FOR CIVIL RIGHTS MATTERS Discovery § 180.500 Discovery. (a) In general. This subpart governs discovery in aid of administrative proceedings under this part. Discovery in...

  10. 22 CFR 224.21 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 22 Foreign Relations 1 2014-04-01 2014-04-01 false Discovery. 224.21 Section 224.21 Foreign....21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of... parties, discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery...

  11. 24 CFR 180.500 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 24 Housing and Urban Development 1 2011-04-01 2011-04-01 false Discovery. 180.500 Section 180.500... OPPORTUNITY CONSOLIDATED HUD HEARING PROCEDURES FOR CIVIL RIGHTS MATTERS Discovery § 180.500 Discovery. (a) In general. This subpart governs discovery in aid of administrative proceedings under this part. Discovery in...

  12. 24 CFR 180.500 - Discovery.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Discovery. 180.500 Section 180.500... OPPORTUNITY CONSOLIDATED HUD HEARING PROCEDURES FOR CIVIL RIGHTS MATTERS Discovery § 180.500 Discovery. (a) In general. This subpart governs discovery in aid of administrative proceedings under this part. Discovery in...

  13. 22 CFR 224.21 - Discovery.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Discovery. 224.21 Section 224.21 Foreign....21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of... parties, discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery...

  14. Genome-Wide Identification of Regulatory Sequences Undergoing Accelerated Evolution in the Human Genome

    PubMed Central

    Dong, Xinran; Wang, Xiao; Zhang, Feng; Tian, Weidong

    2016-01-01

    Accelerated evolution of regulatory sequence can alter the expression pattern of target genes, and cause phenotypic changes. In this study, we used DNase I hypersensitive sites (DHSs) to annotate putative regulatory sequences in the human genome, and conducted a genome-wide analysis of the effects of accelerated evolution on regulatory sequences. Working under the assumption that local ancient repeat elements of DHSs are under neutral evolution, we discovered that ∼0.44% of DHSs are under accelerated evolution (ace-DHSs). We found that ace-DHSs tend to be more active than background DHSs, and are strongly associated with epigenetic marks of active transcription. The target genes of ace-DHSs are significantly enriched in neuron-related functions, and their expression levels are positively selected in the human brain. Thus, these lines of evidences strongly suggest that accelerated evolution on regulatory sequences plays important role in the evolution of human-specific phenotypes. PMID:27401230

  15. 15 CFR 25.21 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 15 Commerce and Foreign Trade 1 2013-01-01 2013-01-01 false Discovery. 25.21 Section 25.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  16. 37 CFR 42.224 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2013-07-01 2013-07-01 false Discovery. 42.224 Section 42... Post-Grant Review § 42.224 Discovery. Notwithstanding the discovery provisions of subpart A: (a) Requests for additional discovery may be granted upon a showing of good cause as to why the discovery is...

  17. 15 CFR 25.21 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 15 Commerce and Foreign Trade 1 2012-01-01 2012-01-01 false Discovery. 25.21 Section 25.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  18. 15 CFR 25.21 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 15 Commerce and Foreign Trade 1 2014-01-01 2014-01-01 false Discovery. 25.21 Section 25.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  19. 19 CFR 207.109 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 19 Customs Duties 3 2014-04-01 2014-04-01 false Discovery. 207.109 Section 207.109 Customs Duties... and Committee Proceedings § 207.109 Discovery. (a) Discovery methods. All parties may obtain discovery under such terms and limitations as the administrative law judge may order. Discovery may be by one or...

  20. 5 CFR 185.122 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 5 Administrative Personnel 1 2012-01-01 2012-01-01 false Discovery. 185.122 Section 185.122... § 185.122 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  1. 37 CFR 42.224 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false Discovery. 42.224 Section 42... Post-Grant Review § 42.224 Discovery. Notwithstanding the discovery provisions of subpart A: (a) Requests for additional discovery may be granted upon a showing of good cause as to why the discovery is...

  2. 15 CFR 25.21 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 15 Commerce and Foreign Trade 1 2011-01-01 2011-01-01 false Discovery. 25.21 Section 25.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  3. 19 CFR 207.109 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 19 Customs Duties 3 2011-04-01 2011-04-01 false Discovery. 207.109 Section 207.109 Customs Duties... and Committee Proceedings § 207.109 Discovery. (a) Discovery methods. All parties may obtain discovery under such terms and limitations as the administrative law judge may order. Discovery may be by one or...

  4. 19 CFR 207.109 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 19 Customs Duties 3 2013-04-01 2013-04-01 false Discovery. 207.109 Section 207.109 Customs Duties... and Committee Proceedings § 207.109 Discovery. (a) Discovery methods. All parties may obtain discovery under such terms and limitations as the administrative law judge may order. Discovery may be by one or...

  5. 5 CFR 185.122 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 5 Administrative Personnel 1 2011-01-01 2011-01-01 false Discovery. 185.122 Section 185.122... § 185.122 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  6. 5 CFR 185.122 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 5 Administrative Personnel 1 2013-01-01 2013-01-01 false Discovery. 185.122 Section 185.122... § 185.122 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  7. 5 CFR 185.122 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 5 Administrative Personnel 1 2014-01-01 2014-01-01 false Discovery. 185.122 Section 185.122... § 185.122 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  8. 19 CFR 207.109 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 19 Customs Duties 3 2012-04-01 2012-04-01 false Discovery. 207.109 Section 207.109 Customs Duties... and Committee Proceedings § 207.109 Discovery. (a) Discovery methods. All parties may obtain discovery under such terms and limitations as the administrative law judge may order. Discovery may be by one or...

  9. 15 CFR 25.21 - Discovery.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Discovery. 25.21 Section 25.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  10. 19 CFR 207.109 - Discovery.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 207.109 Section 207.109 Customs Duties... and Committee Proceedings § 207.109 Discovery. (a) Discovery methods. All parties may obtain discovery under such terms and limitations as the administrative law judge may order. Discovery may be by one or...

  11. [Discovery of the target genes inhibited by formic acid in Candida shehatae].

    PubMed

    Cai, Peng; Xiong, Xujie; Xu, Yong; Yong, Qiang; Zhu, Junjun; Shiyuan, Yu

    2014-01-04

    At transcriptional level, the inhibitory effects of formic acid was investigated on Candida shehatae, a model yeast strain capable of fermenting xylose to ethanol. Thereby, the target genes were regulated by formic acid and the transcript profiles were discovered. On the basis of the transcriptome data of C. shehatae metabolizing glucose and xylose, the genes responsible for ethanol fermentation were chosen as candidates by the combined method of yeast metabolic pathway analysis and manual gene BLAST search. These candidates were then quantitatively detected by RQ-PCR technique to find the regulating genes under gradient doses of formic acid. By quantitative analysis of 42 candidate genes, we finally identified 10 and 5 genes as markedly down-regulated and up-regulated targets by formic acid, respectively. With regard to gene transcripts regulated by formic acid in C. shehatae, the markedly down-regulated genes ranking declines as follows: xylitol dehydrogenase (XYL2), acetyl-CoA synthetase (ACS), ribose-5-phosphate isomerase (RKI), transaldolase (TAL), phosphogluconate dehydrogenase (GND1), transketolase (TKL), glucose-6-phosphate dehydrogenase (ZWF1), xylose reductase (XYL1), pyruvate dehydrogenase (PDH) and pyruvate decarboxylase (PDC); and a declining rank for up-regulated gens as follows: fructose-bisphosphate aldolase (ALD), glucokinase (GLK), malate dehydrogenase (MDH), 6-phosphofructokinase (PFK) and alcohol dehydrogenase (ADH).

  12. An Evolutionary Genomic Approach to Identify Genes Involved in Human Birth Timing

    PubMed Central

    Orabona, Guilherme; Morgan, Thomas; Haataja, Ritva; Hallman, Mikko; Puttonen, Hilkka; Menon, Ramkumar; Kuczynski, Edward; Norwitz, Errol; Snegovskikh, Victoria; Palotie, Aarno; Fellman, Vineta; DeFranco, Emily A.; Chaudhari, Bimal P.; McGregor, Tracy L.; McElroy, Jude J.; Oetjens, Matthew T.; Teramo, Kari; Borecki, Ingrid; Fay, Justin; Muglia, Louis

    2011-01-01

    Coordination of fetal maturation with birth timing is essential for mammalian reproduction. In humans, preterm birth is a disorder of profound global health significance. The signals initiating parturition in humans have remained elusive, due to divergence in physiological mechanisms between humans and model organisms typically studied. Because of relatively large human head size and narrow birth canal cross-sectional area compared to other primates, we hypothesized that genes involved in parturition would display accelerated evolution along the human and/or higher primate phylogenetic lineages to decrease the length of gestation and promote delivery of a smaller fetus that transits the birth canal more readily. Further, we tested whether current variation in such accelerated genes contributes to preterm birth risk. Evidence from allometric scaling of gestational age suggests human gestation has been shortened relative to other primates. Consistent with our hypothesis, many genes involved in reproduction show human acceleration in their coding or adjacent noncoding regions. We screened >8,400 SNPs in 150 human accelerated genes in 165 Finnish preterm and 163 control mothers for association with preterm birth. In this cohort, the most significant association was in FSHR, and 8 of the 10 most significant SNPs were in this gene. Further evidence for association of a linkage disequilibrium block of SNPs in FSHR, rs11686474, rs11680730, rs12473870, and rs1247381 was found in African Americans. By considering human acceleration, we identified a novel gene that may be associated with preterm birth, FSHR. We anticipate other human accelerated genes will similarly be associated with preterm birth risk and elucidate essential pathways for human parturition. PMID:21533219

  13. Discovery of a rich gene pool of bat SARS-related coronaviruses provides new insights into the origin of SARS coronavirus.

    PubMed

    Hu, Ben; Zeng, Lei-Ping; Yang, Xing-Lou; Ge, Xing-Yi; Zhang, Wei; Li, Bei; Xie, Jia-Zheng; Shen, Xu-Rui; Zhang, Yun-Zhi; Wang, Ning; Luo, Dong-Sheng; Zheng, Xiao-Shuang; Wang, Mei-Niang; Daszak, Peter; Wang, Lin-Fa; Cui, Jie; Shi, Zheng-Li

    2017-11-01

    A large number of SARS-related coronaviruses (SARSr-CoV) have been detected in horseshoe bats since 2005 in different areas of China. However, these bat SARSr-CoVs show sequence differences from SARS coronavirus (SARS-CoV) in different genes (S, ORF8, ORF3, etc) and are considered unlikely to represent the direct progenitor of SARS-CoV. Herein, we report the findings of our 5-year surveillance of SARSr-CoVs in a cave inhabited by multiple species of horseshoe bats in Yunnan Province, China. The full-length genomes of 11 newly discovered SARSr-CoV strains, together with our previous findings, reveals that the SARSr-CoVs circulating in this single location are highly diverse in the S gene, ORF3 and ORF8. Importantly, strains with high genetic similarity to SARS-CoV in the hypervariable N-terminal domain (NTD) and receptor-binding domain (RBD) of the S1 gene, the ORF3 and ORF8 region, respectively, were all discovered in this cave. In addition, we report the first discovery of bat SARSr-CoVs highly similar to human SARS-CoV in ORF3b and in the split ORF8a and 8b. Moreover, SARSr-CoV strains from this cave were more closely related to SARS-CoV in the non-structural protein genes ORF1a and 1b compared with those detected elsewhere. Recombination analysis shows evidence of frequent recombination events within the S gene and around the ORF8 between these SARSr-CoVs. We hypothesize that the direct progenitor of SARS-CoV may have originated after sequential recombination events between the precursors of these SARSr-CoVs. Cell entry studies demonstrated that three newly identified SARSr-CoVs with different S protein sequences are all able to use human ACE2 as the receptor, further exhibiting the close relationship between strains in this cave and SARS-CoV. This work provides new insights into the origin and evolution of SARS-CoV and highlights the necessity of preparedness for future emergence of SARS-like diseases.

  14. Discovery of a rich gene pool of bat SARS-related coronaviruses provides new insights into the origin of SARS coronavirus

    PubMed Central

    Ge, Xing-Yi; Zhang, Wei; Li, Bei; Xie, Jia-Zheng; Shen, Xu-Rui; Zhang, Yun-Zhi; Wang, Ning; Luo, Dong-Sheng; Zheng, Xiao-Shuang; Wang, Mei-Niang; Wang, Lin-Fa

    2017-01-01

    A large number of SARS-related coronaviruses (SARSr-CoV) have been detected in horseshoe bats since 2005 in different areas of China. However, these bat SARSr-CoVs show sequence differences from SARS coronavirus (SARS-CoV) in different genes (S, ORF8, ORF3, etc) and are considered unlikely to represent the direct progenitor of SARS-CoV. Herein, we report the findings of our 5-year surveillance of SARSr-CoVs in a cave inhabited by multiple species of horseshoe bats in Yunnan Province, China. The full-length genomes of 11 newly discovered SARSr-CoV strains, together with our previous findings, reveals that the SARSr-CoVs circulating in this single location are highly diverse in the S gene, ORF3 and ORF8. Importantly, strains with high genetic similarity to SARS-CoV in the hypervariable N-terminal domain (NTD) and receptor-binding domain (RBD) of the S1 gene, the ORF3 and ORF8 region, respectively, were all discovered in this cave. In addition, we report the first discovery of bat SARSr-CoVs highly similar to human SARS-CoV in ORF3b and in the split ORF8a and 8b. Moreover, SARSr-CoV strains from this cave were more closely related to SARS-CoV in the non-structural protein genes ORF1a and 1b compared with those detected elsewhere. Recombination analysis shows evidence of frequent recombination events within the S gene and around the ORF8 between these SARSr-CoVs. We hypothesize that the direct progenitor of SARS-CoV may have originated after sequential recombination events between the precursors of these SARSr-CoVs. Cell entry studies demonstrated that three newly identified SARSr-CoVs with different S protein sequences are all able to use human ACE2 as the receptor, further exhibiting the close relationship between strains in this cave and SARS-CoV. This work provides new insights into the origin and evolution of SARS-CoV and highlights the necessity of preparedness for future emergence of SARS-like diseases. PMID:29190287

  15. 39 CFR 963.14 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 39 Postal Service 1 2012-07-01 2012-07-01 false Discovery. 963.14 Section 963.14 Postal Service... PANDERING ADVERTISEMENTS STATUTE, 39 U.S.C. 3008 § 963.14 Discovery. Discovery is to be conducted on a... such discovery as he or she deems reasonable and necessary. Discovery may include one or more of the...

  16. 39 CFR 963.14 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 39 Postal Service 1 2013-07-01 2013-07-01 false Discovery. 963.14 Section 963.14 Postal Service... PANDERING ADVERTISEMENTS STATUTE, 39 U.S.C. 3008 § 963.14 Discovery. Discovery is to be conducted on a... such discovery as he or she deems reasonable and necessary. Discovery may include one or more of the...

  17. 39 CFR 963.14 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 39 Postal Service 1 2014-07-01 2014-07-01 false Discovery. 963.14 Section 963.14 Postal Service... PANDERING ADVERTISEMENTS STATUTE, 39 U.S.C. 3008 § 963.14 Discovery. Discovery is to be conducted on a... such discovery as he or she deems reasonable and necessary. Discovery may include one or more of the...

  18. 39 CFR 963.14 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 39 Postal Service 1 2011-07-01 2011-07-01 false Discovery. 963.14 Section 963.14 Postal Service... PANDERING ADVERTISEMENTS STATUTE, 39 U.S.C. 3008 § 963.14 Discovery. Discovery is to be conducted on a... such discovery as he or she deems reasonable and necessary. Discovery may include one or more of the...

  19. 39 CFR 963.14 - Discovery.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 39 Postal Service 1 2010-07-01 2010-07-01 false Discovery. 963.14 Section 963.14 Postal Service... PANDERING ADVERTISEMENTS STATUTE, 39 U.S.C. 3008 § 963.14 Discovery. Discovery is to be conducted on a... such discovery as he or she deems reasonable and necessary. Discovery may include one or more of the...

  20. Decoding the complex genetic causes of heart diseases using systems biology.

    PubMed

    Djordjevic, Djordje; Deshpande, Vinita; Szczesnik, Tomasz; Yang, Andrian; Humphreys, David T; Giannoulatou, Eleni; Ho, Joshua W K

    2015-03-01

    The pace of disease gene discovery is still much slower than expected, even with the use of cost-effective DNA sequencing and genotyping technologies. It is increasingly clear that many inherited heart diseases have a more complex polygenic aetiology than previously thought. Understanding the role of gene-gene interactions, epigenetics, and non-coding regulatory regions is becoming increasingly critical in predicting the functional consequences of genetic mutations identified by genome-wide association studies and whole-genome or exome sequencing. A systems biology approach is now being widely employed to systematically discover genes that are involved in heart diseases in humans or relevant animal models through bioinformatics. The overarching premise is that the integration of high-quality causal gene regulatory networks (GRNs), genomics, epigenomics, transcriptomics and other genome-wide data will greatly accelerate the discovery of the complex genetic causes of congenital and complex heart diseases. This review summarises state-of-the-art genomic and bioinformatics techniques that are used in accelerating the pace of disease gene discovery in heart diseases. Accompanying this review, we provide an interactive web-resource for systems biology analysis of mammalian heart development and diseases, CardiacCode ( http://CardiacCode.victorchang.edu.au/ ). CardiacCode features a dataset of over 700 pieces of manually curated genetic or molecular perturbation data, which enables the inference of a cardiac-specific GRN of 280 regulatory relationships between 33 regulator genes and 129 target genes. We believe this growing resource will fill an urgent unmet need to fully realise the true potential of predictive and personalised genomic medicine in tackling human heart disease.

  1. Apparently low reproducibility of true differential expression discoveries in microarray studies.

    PubMed

    Zhang, Min; Yao, Chen; Guo, Zheng; Zou, Jinfeng; Zhang, Lin; Xiao, Hui; Wang, Dong; Yang, Da; Gong, Xue; Zhu, Jing; Li, Yanhui; Li, Xia

    2008-09-15

    Differentially expressed gene (DEG) lists detected from different microarray studies for a same disease are often highly inconsistent. Even in technical replicate tests using identical samples, DEG detection still shows very low reproducibility. It is often believed that current small microarray studies will largely introduce false discoveries. Based on a statistical model, we show that even in technical replicate tests using identical samples, it is highly likely that the selected DEG lists will be very inconsistent in the presence of small measurement variations. Therefore, the apparently low reproducibility of DEG detection from current technical replicate tests does not indicate low quality of microarray technology. We also demonstrate that heterogeneous biological variations existing in real cancer data will further reduce the overall reproducibility of DEG detection. Nevertheless, in small subsamples from both simulated and real data, the actual false discovery rate (FDR) for each DEG list tends to be low, suggesting that each separately determined list may comprise mostly true DEGs. Rather than simply counting the overlaps of the discovery lists from different studies for a complex disease, novel metrics are needed for evaluating the reproducibility of discoveries characterized with correlated molecular changes. Supplementaty information: Supplementary data are available at Bioinformatics online.

  2. Automated phase mapping with AgileFD and its application to light absorber discovery in the V–Mn–Nb oxide system

    DOE PAGES

    Suram, Santosh K.; Xue, Yexiang; Bai, Junwen; ...

    2016-11-21

    Rapid construction of phase diagrams is a central tenet of combinatorial materials science with accelerated materials discovery efforts often hampered by challenges in interpreting combinatorial X-ray diffraction data sets, which we address by developing AgileFD, an artificial intelligence algorithm that enables rapid phase mapping from a combinatorial library of X-ray diffraction patterns. AgileFD models alloying-based peak shifting through a novel expansion of convolutional nonnegative matrix factorization, which not only improves the identification of constituent phases but also maps their concentration and lattice parameter as a function of composition. By incorporating Gibbs’ phase rule into the algorithm, physically meaningful phase mapsmore » are obtained with unsupervised operation, and more refined solutions are attained by injecting expert knowledge of the system. The algorithm is demonstrated through investigation of the V–Mn–Nb oxide system where decomposition of eight oxide phases, including two with substantial alloying, provides the first phase map for this pseudoternary system. This phase map enables interpretation of high-throughput band gap data, leading to the discovery of new solar light absorbers and the alloying-based tuning of the direct-allowed band gap energy of MnV 2O 6. Lastly, the open-source family of AgileFD algorithms can be implemented into a broad range of high throughput workflows to accelerate materials discovery.« less

  3. Automated phase mapping with AgileFD and its application to light absorber discovery in the V–Mn–Nb oxide system

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Suram, Santosh K.; Xue, Yexiang; Bai, Junwen

    Rapid construction of phase diagrams is a central tenet of combinatorial materials science with accelerated materials discovery efforts often hampered by challenges in interpreting combinatorial X-ray diffraction data sets, which we address by developing AgileFD, an artificial intelligence algorithm that enables rapid phase mapping from a combinatorial library of X-ray diffraction patterns. AgileFD models alloying-based peak shifting through a novel expansion of convolutional nonnegative matrix factorization, which not only improves the identification of constituent phases but also maps their concentration and lattice parameter as a function of composition. By incorporating Gibbs’ phase rule into the algorithm, physically meaningful phase mapsmore » are obtained with unsupervised operation, and more refined solutions are attained by injecting expert knowledge of the system. The algorithm is demonstrated through investigation of the V–Mn–Nb oxide system where decomposition of eight oxide phases, including two with substantial alloying, provides the first phase map for this pseudoternary system. This phase map enables interpretation of high-throughput band gap data, leading to the discovery of new solar light absorbers and the alloying-based tuning of the direct-allowed band gap energy of MnV 2O 6. Lastly, the open-source family of AgileFD algorithms can be implemented into a broad range of high throughput workflows to accelerate materials discovery.« less

  4. Petrol and diesel exhaust particles accelerate the horizontal transfer of plasmid-mediated antimicrobial resistance genes.

    PubMed

    Zhang, Ye; Gu, April Z; Cen, Tianyu; Li, Xiangyang; Li, Dan; Chen, Jianmin

    2018-05-01

    Particles exhausted from petrol and diesel consumptions are major components of urban air pollution that can be exposed to human via direct inhalation or other routes due to atmospheric deposition into water and soil. Antimicrobial resistance is one of the most serious threats to modern health care. However, how the petrol and diesel exhaust particles affect the development and spread of antimicrobial resistance genes (ARGs) in various environments remain largely unknown. This study investigated the effects and potential mechanisms of four representative petrol and diesel exhaust particles, namely 97 octane petrol, 93 octane petrol, light diesel oil, and marine heavy diesel oil, on the horizontal transfer of ARGs between two opportunistic Escherichia coli (E. coli) strains, E. coli S17-1 (donor) and E. coli K12 (recipient). The results demonstrated that these four representative types of nano-scale particles induced concentration-dependent increases in conjugative transfer rates compared with the controls. The underlying mechanisms involved in the accelerated transfer of ARGs were also identified, including the generation of intracellular reactive oxygen species (ROS) and the consequent induction of oxidative stress, SOS response, changes in cell morphology, and the altered mRNA expression of membrane protein genes and those involved in the promotion of conjugative transfer. The findings provide new evidences and mechanistic insights into the antimicrobial resistance risks posed by petrol and diesel exhaust particles, and highlight the implications and need for stringent strategies on alternative fuels to mitigate air pollution and health risks. Copyright © 2018 Elsevier Ltd. All rights reserved.

  5. BioProspecting: novel marker discovery obtained by mining the bibleome.

    PubMed

    Elkin, Peter L; Tuttle, Mark S; Trusko, Brett E; Brown, Steven H

    2009-02-05

    BioProspecting is a novel approach that enabled our team to mine data related to genetic markers from the New England Journal of Medicine (NEJM) utilizing SNOMED CT and the Human Gene Onotology (HUGO). The Biomedical Informatics Research Collaborative was able to link genes and disorders using the Multi-threaded Clinical Vocabulary Server (MCVS) and natural language processing engine, whose output creates an ontology-network using the semantic encodings of the literature that is organized by these two terminologies. We identified relationships between (genes or proteins) and (diseases or drugs) as linked by metabolic functions and identified potentially novel functional relationships between, for example, genes and diseases (e.g. Article #1 ([Gene - IL27] = > {Enzyme - Dipeptidyl Carboxypeptidase 1}) and Article #2 ({Enzyme - Dipeptidyl Carboxypeptidase 1} < = [Disorder - Type II DM]) showing a metabolic link between IL27 and Type II DM). In this manuscript we describe our method for developing the database and its content as well as its potential to assist in the discovery of novel markers and drugs.

  6. Acceleration modules in linear induction accelerators

    NASA Astrophysics Data System (ADS)

    Wang, Shao-Heng; Deng, Jian-Jun

    2014-05-01

    The Linear Induction Accelerator (LIA) is a unique type of accelerator that is capable of accelerating kilo-Ampere charged particle current to tens of MeV energy. The present development of LIA in MHz bursting mode and the successful application into a synchrotron have broadened LIA's usage scope. Although the transformer model is widely used to explain the acceleration mechanism of LIAs, it is not appropriate to consider the induction electric field as the field which accelerates charged particles for many modern LIAs. We have examined the transition of the magnetic cores' functions during the LIA acceleration modules' evolution, distinguished transformer type and transmission line type LIA acceleration modules, and re-considered several related issues based on transmission line type LIA acceleration module. This clarified understanding should help in the further development and design of LIA acceleration modules.

  7. Systematic discovery of novel ciliary genes through functional genomics in the zebrafish

    PubMed Central

    Choksi, Semil P.; Babu, Deepak; Lau, Doreen; Yu, Xianwen; Roy, Sudipto

    2014-01-01

    Cilia are microtubule-based hair-like organelles that play many important roles in development and physiology, and are implicated in a rapidly expanding spectrum of human diseases, collectively termed ciliopathies. Primary ciliary dyskinesia (PCD), one of the most prevalent of ciliopathies, arises from abnormalities in the differentiation or motility of the motile cilia. Despite their biomedical importance, a methodical functional screen for ciliary genes has not been carried out in any vertebrate at the organismal level. We sought to systematically discover novel motile cilia genes by identifying the genes induced by Foxj1, a winged-helix transcription factor that has an evolutionarily conserved role as the master regulator of motile cilia biogenesis. Unexpectedly, we find that the majority of the Foxj1-induced genes have not been associated with cilia before. To characterize these novel putative ciliary genes, we subjected 50 randomly selected candidates to a systematic functional phenotypic screen in zebrafish embryos. Remarkably, we find that over 60% are required for ciliary differentiation or function, whereas 30% of the proteins encoded by these genes localize to motile cilia. We also show that these genes regulate the proper differentiation and beating of motile cilia. This collection of Foxj1-induced genes will be invaluable for furthering our understanding of ciliary biology, and in the identification of new mutations underlying ciliary disorders in humans. PMID:25139857

  8. The web server of IBM's Bioinformatics and Pattern Discovery group: 2004 update.

    PubMed

    Huynh, Tien; Rigoutsos, Isidore

    2004-07-01

    In this report, we provide an update on the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server, which is operational around the clock, provides access to a large number of methods that have been developed and published by the group's members. There is an increasing number of problems that these tools can help tackle; these problems range from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences, the identification--directly from sequence--of structural deviations from alpha-helicity and the annotation of amino acid sequences for antimicrobial activity. Additionally, annotations for more than 130 archaeal, bacterial, eukaryotic and viral genomes are now available on-line and can be searched interactively. The tools and code bundles continue to be accessible from http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/.

  9. High-throughput metabolic stability studies in drug discovery by orthogonal acceleration time-of-flight (OATOF) with analogue-to-digital signal capture (ADC).

    PubMed

    Temesi, David G; Martin, Scott; Smith, Robin; Jones, Christopher; Middleton, Brian

    2010-06-30

    Screening assays capable of performing quantitative analysis on hundreds of compounds per week are used to measure metabolic stability during early drug discovery. Modern orthogonal acceleration time-of-flight (OATOF) mass spectrometers equipped with analogue-to-digital signal capture (ADC) now offer performance levels suitable for many applications normally supported by triple quadruple instruments operated in multiple reaction monitoring (MRM) mode. Herein the merits of MRM and OATOF with ADC detection are compared for more than 1000 compounds screened in rat and/or cryopreserved human hepatocytes over a period of 3 months. Statistical comparison of a structurally diverse subset indicated good agreement for the two detection methods. The overall success rate was higher using OATOF detection and data acquisition time was reduced by around 20%. Targeted metabolites of diazepam were detected in samples from a CLint determination performed at 1 microM. Data acquisition by positive and negative ion mode switching can be achieved on high-performance liquid chromatography (HPLC) peak widths as narrow as 0.2 min (at base), thus enabling a more comprehensive first pass analysis with fast HPLC gradients. Unfortunately, most existing OATOF instruments lack the software tools necessary to rapidly convert the huge amounts of raw data into quantified results. Software with functionality similar to open access triple quadrupole systems is needed for OATOF to truly compete in a high-throughput screening environment. Copyright 2010 John Wiley & Sons, Ltd.

  10. WebMOTIFS: automated discovery, filtering and scoring of DNA sequence motifs using multiple programs and Bayesian approaches

    PubMed Central

    Romer, Katherine A.; Kayombya, Guy-Richard; Fraenkel, Ernest

    2007-01-01

    WebMOTIFS provides a web interface that facilitates the discovery and analysis of DNA-sequence motifs. Several studies have shown that the accuracy of motif discovery can be significantly improved by using multiple de novo motif discovery programs and using randomized control calculations to identify the most significant motifs or by using Bayesian approaches. WebMOTIFS makes it easy to apply these strategies. Using a single submission form, users can run several motif discovery programs and score, cluster and visualize the results. In addition, the Bayesian motif discovery program THEME can be used to determine the class of transcription factors that is most likely to regulate a set of sequences. Input can be provided as a list of gene or probe identifiers. Used with the default settings, WebMOTIFS accurately identifies biologically relevant motifs from diverse data in several species. WebMOTIFS is freely available at http://fraenkel.mit.edu/webmotifs. PMID:17584794

  11. [Effects of bushen yinao tablet on physiology and cerebral gene expression in senescence-accelerated mice].

    PubMed

    Zhang, Chong; Wang, Jin-gang; Yang, Ting

    2006-06-01

    To study the effects of Bushen Yin' ao Tablet (BSYNT) on physiology and cerebral gene expression in senescence-accelerated mice (SAM). The change of cerebral tissues mRNA expression in SAM was analyzed and compared by messenger ribonucleic acids reverse transcription differential display polymerase chain reaction (mRNA DDRT-PCR) between the medicated group and the control group. BSYNT could increase the level of hemoglobin (Hb) and amount of erythrocyte (RBC) of blood deficiency mice, improve the spatial learning and memory function and the escape response by conditional stimulus. In this study, 14 differential display bands had been discerned, and three of them had been sequenced. The sequence of the three fragments was similar to fatty acid binding protein 7, ubiquinol-cytochrome C reductase complex (7. 2 kD) and 60S ribosomal protein L21 respectively. And the homogeneity was 97% , 100% , and 99% , respectively. BSYNT has effect on the physiological changing of mice, and its effect on cerebral tissues mRNA expression maybe play an important role in anti-aging on the molecular level.

  12. Drug Discovery Prospect from Untapped Species: Indications from Approved Natural Product Drugs

    PubMed Central

    Qin, Chu; Tao, Lin; Liu, Xin; Shi, Zhe; Zhang, Cun Long; Tan, Chun Yan; Chen, Yu Zong; Jiang, Yu Yang

    2012-01-01

    Due to extensive bioprospecting efforts of the past and technology factors, there have been questions about drug discovery prospect from untapped species. We analyzed recent trends of approved drugs derived from previously untapped species, which show no sign of untapped drug-productive species being near extinction and suggest high probability of deriving new drugs from new species in existing drug-productive species families and clusters. Case histories of recently approved drugs reveal useful strategies for deriving new drugs from the scaffolds and pharmacophores of the natural product leads of these untapped species. New technologies such as cryptic gene-cluster exploration may generate novel natural products with highly anticipated potential impact on drug discovery. PMID:22808057

  13. Promzea: a pipeline for discovery of co-regulatory motifs in maize and other plant species and its application to the anthocyanin and phlobaphene biosynthetic pathways and the Maize Development Atlas.

    PubMed

    Liseron-Monfils, Christophe; Lewis, Tim; Ashlock, Daniel; McNicholas, Paul D; Fauteux, François; Strömvik, Martina; Raizada, Manish N

    2013-03-15

    The discovery of genetic networks and cis-acting DNA motifs underlying their regulation is a major objective of transcriptome studies. The recent release of the maize genome (Zea mays L.) has facilitated in silico searches for regulatory motifs. Several algorithms exist to predict cis-acting elements, but none have been adapted for maize. A benchmark data set was used to evaluate the accuracy of three motif discovery programs: BioProspector, Weeder and MEME. Analysis showed that each motif discovery tool had limited accuracy and appeared to retrieve a distinct set of motifs. Therefore, using the benchmark, statistical filters were optimized to reduce the false discovery ratio, and then remaining motifs from all programs were combined to improve motif prediction. These principles were integrated into a user-friendly pipeline for motif discovery in maize called Promzea, available at http://www.promzea.org and on the Discovery Environment of the iPlant Collaborative website. Promzea was subsequently expanded to include rice and Arabidopsis. Within Promzea, a user enters cDNA sequences or gene IDs; corresponding upstream sequences are retrieved from the maize genome. Predicted motifs are filtered, combined and ranked. Promzea searches the chosen plant genome for genes containing each candidate motif, providing the user with the gene list and corresponding gene annotations. Promzea was validated in silico using a benchmark data set: the Promzea pipeline showed a 22% increase in nucleotide sensitivity compared to the best standalone program tool, Weeder, with equivalent nucleotide specificity. Promzea was also validated by its ability to retrieve the experimentally defined binding sites of transcription factors that regulate the maize anthocyanin and phlobaphene biosynthetic pathways. Promzea predicted additional promoter motifs, and genome-wide motif searches by Promzea identified 127 non-anthocyanin/phlobaphene genes that each contained all five predicted promoter

  14. Emerging techniques for the discovery and validation of therapeutic targets for skeletal diseases.

    PubMed

    Cho, Christine H; Nuttall, Mark E

    2002-12-01

    Advances in genomics and proteomics have revolutionised the drug discovery process and target validation. Identification of novel therapeutic targets for chronic skeletal diseases is an extremely challenging process based on the difficulty of obtaining high-quality human diseased versus normal tissue samples. The quality of tissue and genomic information obtained from the sample is critical to identifying disease-related genes. Using a genomics-based approach, novel genes or genes with similar homology to existing genes can be identified from cDNA libraries generated from normal versus diseased tissue. High-quality cDNA libraries are prepared from uncontaminated homogeneous cell populations harvested from tissue sections of interest. Localised gene expression analysis and confirmation are obtained through in situ hybridisation or immunohistochemical studies. Cells overexpressing the recombinant protein are subsequently designed for primary cell-based high-throughput assays that are capable of screening large compound banks for potential hits. Afterwards, secondary functional assays are used to test promising compounds. The same overexpressing cells are used in the secondary assay to test protein activity and functionality as well as screen for small-molecule agonists or antagonists. Once a hit is generated, a structure-activity relationship of the compound is optimised for better oral bioavailability and pharmacokinetics allowing the compound to progress into development. Parallel efforts from proteomics, as well as genetics/transgenics, bioinformatics and combinatorial chemistry, and improvements in high-throughput automation technologies, allow the drug discovery process to meet the demands of the medicinal market. This review discusses and illustrates how different approaches are incorporated into the discovery and validation of novel targets and, consequently, the development of potentially therapeutic agents in the areas of osteoporosis and osteoarthritis

  15. Pharmacogenetics in type 2 diabetes: precision medicine or discovery tool?

    PubMed

    Florez, Jose C

    2017-05-01

    In recent years, technological and analytical advances have led to an explosion in the discovery of genetic loci associated with type 2 diabetes. However, their ability to improve prediction of disease outcomes beyond standard clinical risk factors has been limited. On the other hand, genetic effects on drug response may be stronger than those commonly seen for disease incidence. Pharmacogenetic findings may aid in identifying new drug targets, elucidate pathophysiology, unravel disease heterogeneity, help prioritise specific genes in regions of genetic association, and contribute to personalised or precision treatment. In diabetes, precedent for the successful application of pharmacogenetic concepts exists in its monogenic subtypes, such as MODY or neonatal diabetes. Whether similar insights will emerge for the much more common entity of type 2 diabetes remains to be seen. As genetic approaches advance, the progressive deployment of candidate gene, large-scale genotyping and genome-wide association studies has begun to produce suggestive results that may transform clinical practice. However, many barriers to the translation of diabetes pharmacogenetic discoveries to the clinic still remain. This perspective offers a contemporary overview of the field with a focus on sulfonylureas and metformin, identifies the major uses of pharmacogenetics, and highlights potential limitations and future directions.

  16. Open Access Could Transform Drug Discovery: A Case Study of JQ1.

    PubMed

    Arshad, Zeeshaan; Smith, James; Roberts, Mackenna; Lee, Wen Hwa; Davies, Ben; Bure, Kim; Hollander, Georg A; Dopson, Sue; Bountra, Chas; Brindley, David

    2016-01-01

    The cost to develop a new drug from target discovery to market is a staggering $1.8 billion, largely due to the very high attrition rate of drug candidates and the lengthy transition times during development. Open access is an emerging model of open innovation that places no restriction on the use of information and has the potential to accelerate the development of new drugs. To date, no quantitative assessment has yet taken place to determine the effects and viability of open access on the process of drug translation. This need is addressed within this study. The literature and intellectual property landscapes of the drug candidate JQ1, which was made available on an open access basis when discovered, and conventionally developed equivalents that were not are compared using the Web of Science and Thomson Innovation software, respectively. Results demonstrate that openly sharing the JQ1 molecule led to a greater uptake by a wider and more multi-disciplinary research community. A comparative analysis of the patent landscapes for each candidate also found that the broader scientific diaspora of the publically released JQ1 data enhanced innovation, evidenced by a greater number of downstream patents filed in relation to JQ1. The authors' findings counter the notion that open access drug discovery would leak commercial intellectual property. On the contrary, JQ1 serves as a test case to evidence that open access drug discovery can be an economic model that potentially improves efficiency and cost of drug discovery and its subsequent commercialization.

  17. Routine Discovery of Complex Genetic Models using Genetic Algorithms

    PubMed Central

    Moore, Jason H.; Hahn, Lance W.; Ritchie, Marylyn D.; Thornton, Tricia A.; White, Bill C.

    2010-01-01

    Simulation studies are useful in various disciplines for a number of reasons including the development and evaluation of new computational and statistical methods. This is particularly true in human genetics and genetic epidemiology where new analytical methods are needed for the detection and characterization of disease susceptibility genes whose effects are complex, nonlinear, and partially or solely dependent on the effects of other genes (i.e. epistasis or gene-gene interaction). Despite this need, the development of complex genetic models that can be used to simulate data is not always intuitive. In fact, only a few such models have been published. We have previously developed a genetic algorithm approach to discovering complex genetic models in which two single nucleotide polymorphisms (SNPs) influence disease risk solely through nonlinear interactions. In this paper, we extend this approach for the discovery of high-order epistasis models involving three to five SNPs. We demonstrate that the genetic algorithm is capable of routinely discovering interesting high-order epistasis models in which each SNP influences risk of disease only through interactions with the other SNPs in the model. This study opens the door for routine simulation of complex gene-gene interactions among SNPs for the development and evaluation of new statistical and computational approaches for identifying common, complex multifactorial disease susceptibility genes. PMID:20948983

  18. PanDaTox: A tool for accelerated metabolic engineering

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Amitai, Gil; Sorek, Rotem

    2012-07-18

    Metabolic engineering is often facilitated by cloning of genes encoding enzymes from various heterologous organisms into E. coli. Such engineering efforts are frequently hampered by foreign genes that are toxic to the E. coli host. We have developed PanDaTox (www.weizmann.ac.il/pandatox), a web-based resource that provides experimental toxicity information for more than 1.5 million genes from hundreds of different microbial genomes. The toxicity predictions, which were extensively experimentally verified, are based on serial cloning of genes into E. coli as part of the Sanger whole genome shotgun sequencing process. PanDaTox can accelerate metabolic engineering projects by allowing researchers to exclude toxicmore » genes from the engineering plan and verify the clonability of selected genes before the actual metabolic engineering experiments are conducted.« less

  19. Accelerator radiocarbon dating of evidence for prehistoric horticulture in Illinois

    USGS Publications Warehouse

    Conard, N.; Asch, D.L.; Asch, N.B.; Elmore, D.; Gove, H.; Rubin, M.; Brown, J.A.; Wiant, M.D.; Farnsworth, K.B.; Cook, T.G.

    1984-01-01

    With the development of direct detection radiocarbon dating, which uses an accelerator as part of a highly selective mass spectrometer, it is now possible to determine the age of milligram samples of organic materials1-5. One application of accelerator dating is in evaluating scanty, sometimes controversial evidence for early horticulture throughout the world. We have now used the technique to date small samples of carbonized, cultivated plant remains from archaeological sites in Illinois. The results, reported here, establish (1) that squash was introduced by 7,000 yr ago, 2,500 yr before eastern North American records previously reported; (2) that horticulture involving indigenous plants had begun by 4,000 BP in eastern North America with domestication of Iva annua, a small-seeded annual; (3) that anomalous discoveries of Archaic period maize represent contaminants; and (4) that introduction of maize by initial Middle Woodland times (~2,000 BP) is questionable.

  20. 37 CFR 11.52 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2013-07-01 2013-07-01 false Discovery. 11.52 Section 11... Disciplinary Proceedings; Jurisdiction, Sanctions, Investigations, and Proceedings § 11.52 Discovery. Discovery... establishes that discovery is reasonable and relevant, the hearing officer, under such conditions as he or she...

  1. 37 CFR 11.52 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false Discovery. 11.52 Section 11... Disciplinary Proceedings; Jurisdiction, Sanctions, Investigations, and Proceedings § 11.52 Discovery. Discovery... establishes that discovery is reasonable and relevant, the hearing officer, under such conditions as he or she...

  2. 19 CFR 354.10 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 19 Customs Duties 3 2014-04-01 2014-04-01 false Discovery. 354.10 Section 354.10 Customs Duties... ANTIDUMPING OR COUNTERVAILING DUTY ADMINISTRATIVE PROTECTIVE ORDER § 354.10 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery procedures regarding any matter, not...

  3. 19 CFR 354.10 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 19 Customs Duties 3 2011-04-01 2011-04-01 false Discovery. 354.10 Section 354.10 Customs Duties... ANTIDUMPING OR COUNTERVAILING DUTY ADMINISTRATIVE PROTECTIVE ORDER § 354.10 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery procedures regarding any matter, not...

  4. 36 CFR 1150.63 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 36 Parks, Forests, and Public Property 3 2014-07-01 2014-07-01 false Discovery. 1150.63 Section... PRACTICE AND PROCEDURES FOR COMPLIANCE HEARINGS Prehearing Conferences and Discovery § 1150.63 Discovery. (a) Parties are encouraged to engage in voluntary discovery procedures. For good cause shown under...

  5. 37 CFR 11.52 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2011-07-01 2011-07-01 false Discovery. 11.52 Section 11... Disciplinary Proceedings; Jurisdiction, Sanctions, Investigations, and Proceedings § 11.52 Discovery. Discovery... establishes that discovery is reasonable and relevant, the hearing officer, under such conditions as he or she...

  6. 36 CFR 1150.63 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 36 Parks, Forests, and Public Property 3 2012-07-01 2012-07-01 false Discovery. 1150.63 Section... PRACTICE AND PROCEDURES FOR COMPLIANCE HEARINGS Prehearing Conferences and Discovery § 1150.63 Discovery. (a) Parties are encouraged to engage in voluntary discovery procedures. For good cause shown under...

  7. 36 CFR 1150.63 - Discovery.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 36 Parks, Forests, and Public Property 3 2011-07-01 2011-07-01 false Discovery. 1150.63 Section... PRACTICE AND PROCEDURES FOR COMPLIANCE HEARINGS Prehearing Conferences and Discovery § 1150.63 Discovery. (a) Parties are encouraged to engage in voluntary discovery procedures. For good cause shown under...

  8. 19 CFR 354.10 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 19 Customs Duties 3 2013-04-01 2013-04-01 false Discovery. 354.10 Section 354.10 Customs Duties... ANTIDUMPING OR COUNTERVAILING DUTY ADMINISTRATIVE PROTECTIVE ORDER § 354.10 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery procedures regarding any matter, not...

  9. 37 CFR 11.52 - Discovery.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false Discovery. 11.52 Section 11... Disciplinary Proceedings; Jurisdiction, Sanctions, Investigations, and Proceedings § 11.52 Discovery. Discovery... establishes that discovery is reasonable and relevant, the hearing officer, under such conditions as he or she...

  10. 19 CFR 354.10 - Discovery.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 19 Customs Duties 3 2012-04-01 2012-04-01 false Discovery. 354.10 Section 354.10 Customs Duties... ANTIDUMPING OR COUNTERVAILING DUTY ADMINISTRATIVE PROTECTIVE ORDER § 354.10 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery procedures regarding any matter, not...

  11. 37 CFR 11.52 - Discovery.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Discovery. 11.52 Section 11... Disciplinary Proceedings; Jurisdiction, Sanctions, Investigations, and Proceedings § 11.52 Discovery. Discovery... establishes that discovery is reasonable and relevant, the hearing officer, under such conditions as he or she...

  12. 36 CFR 1150.63 - Discovery.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false Discovery. 1150.63 Section... PRACTICE AND PROCEDURES FOR COMPLIANCE HEARINGS Prehearing Conferences and Discovery § 1150.63 Discovery. (a) Parties are encouraged to engage in voluntary discovery procedures. For good cause shown under...

  13. 19 CFR 354.10 - Discovery.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 354.10 Section 354.10 Customs Duties... ANTIDUMPING OR COUNTERVAILING DUTY ADMINISTRATIVE PROTECTIVE ORDER § 354.10 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery procedures regarding any matter, not...

  14. Integrated Bio-Entity Network: A System for Biological Knowledge Discovery

    PubMed Central

    Bell, Lindsey; Chowdhary, Rajesh; Liu, Jun S.; Niu, Xufeng; Zhang, Jinfeng

    2011-01-01

    A significant part of our biological knowledge is centered on relationships between biological entities (bio-entities) such as proteins, genes, small molecules, pathways, gene ontology (GO) terms and diseases. Accumulated at an increasing speed, the information on bio-entity relationships is archived in different forms at scattered places. Most of such information is buried in scientific literature as unstructured text. Organizing heterogeneous information in a structured form not only facilitates study of biological systems using integrative approaches, but also allows discovery of new knowledge in an automatic and systematic way. In this study, we performed a large scale integration of bio-entity relationship information from both databases containing manually annotated, structured information and automatic information extraction of unstructured text in scientific literature. The relationship information we integrated in this study includes protein–protein interactions, protein/gene regulations, protein–small molecule interactions, protein–GO relationships, protein–pathway relationships, and pathway–disease relationships. The relationship information is organized in a graph data structure, named integrated bio-entity network (IBN), where the vertices are the bio-entities and edges represent their relationships. Under this framework, graph theoretic algorithms can be designed to perform various knowledge discovery tasks. We designed breadth-first search with pruning (BFSP) and most probable path (MPP) algorithms to automatically generate hypotheses—the indirect relationships with high probabilities in the network. We show that IBN can be used to generate plausible hypotheses, which not only help to better understand the complex interactions in biological systems, but also provide guidance for experimental designs. PMID:21738677

  15. The Undiagnosed Diseases Network: Accelerating Discovery about Health and Disease.

    PubMed

    Ramoni, Rachel B; Mulvihill, John J; Adams, David R; Allard, Patrick; Ashley, Euan A; Bernstein, Jonathan A; Gahl, William A; Hamid, Rizwan; Loscalzo, Joseph; McCray, Alexa T; Shashi, Vandana; Tifft, Cynthia J; Wise, Anastasia L

    2017-02-02

    Diagnosis at the edges of our knowledge calls upon clinicians to be data driven, cross-disciplinary, and collaborative in unprecedented ways. Exact disease recognition, an element of the concept of precision in medicine, requires new infrastructure that spans geography, institutional boundaries, and the divide between clinical care and research. The National Institutes of Health (NIH) Common Fund supports the Undiagnosed Diseases Network (UDN) as an exemplar of this model of precise diagnosis. Its goals are to forge a strategy to accelerate the diagnosis of rare or previously unrecognized diseases, to improve recommendations for clinical management, and to advance research, especially into disease mechanisms. The network will achieve these objectives by evaluating patients with undiagnosed diseases, fostering a breadth of expert collaborations, determining best practices for translating the strategy into medical centers nationwide, and sharing findings, data, specimens, and approaches with the scientific and medical communities. Building the UDN has already brought insights to human and medical geneticists. The initial focus has been on data sharing, establishing common protocols for institutional review boards and data sharing, creating protocols for referring and evaluating patients, and providing DNA sequencing, metabolomic analysis, and functional studies in model organisms. By extending this precision diagnostic model nationally, we strive to meld clinical and research objectives, improve patient outcomes, and contribute to medical science. Copyright © 2017 American Society of Human Genetics. All rights reserved.

  16. Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers.

    PubMed

    Labaj, Wojciech; Papiez, Anna; Polanski, Andrzej; Polanska, Joanna

    2017-03-01

    Large collections of data in studies on cancer such as leukaemia provoke the necessity of applying tailored analysis algorithms to ensure supreme information extraction. In this work, a custom-fit pipeline is demonstrated for thorough investigation of the voluminous MILE gene expression data set. Three analyses are accomplished, each for gaining a deeper understanding of the processes underlying leukaemia types and subtypes. First, the main disease groups are tested for differential expression against the healthy control as in a standard case-control study. Here, the basic knowledge on molecular mechanisms is confirmed quantitatively and by literature references. Second, pairwise comparison testing is performed for juxtaposing the main leukaemia types among each other. In this case by means of the Dice coefficient similarity measure the general relations are pointed out. Moreover, lists of candidate main leukaemia group biomarkers are proposed. Finally, with this approach being successful, the third analysis provides insight into all of the studied subtypes, followed by the emergence of four leukaemia subtype biomarkers. In addition, the class enhanced DEG signature obtained on the basis of novel pipeline processing leads to significantly better classification power of multi-class data classifiers. The developed methodology consisting of batch effect adjustment, adaptive noise and feature filtration coupled with adequate statistical testing and biomarker definition proves to be an effective approach towards knowledge discovery in high-throughput molecular biology experiments.

  17. Automatic Beam Path Analysis of Laser Wakefield Particle Acceleration Data

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Rubel, Oliver; Geddes, Cameron G.R.; Cormier-Michel, Estelle

    2009-10-19

    Numerical simulations of laser wakefield particle accelerators play a key role in the understanding of the complex acceleration process and in the design of expensive experimental facilities. As the size and complexity of simulation output grows, an increasingly acute challenge is the practical need for computational techniques that aid in scientific knowledge discovery. To that end, we present a set of data-understanding algorithms that work in concert in a pipeline fashion to automatically locate and analyze high energy particle bunches undergoing acceleration in very large simulation datasets. These techniques work cooperatively by first identifying features of interest in individual timesteps,more » then integrating features across timesteps, and based on the information derived perform analysis of temporally dynamic features. This combination of techniques supports accurate detection of particle beams enabling a deeper level of scientific understanding of physical phenomena than hasbeen possible before. By combining efficient data analysis algorithms and state-of-the-art data management we enable high-performance analysis of extremely large particle datasets in 3D. We demonstrate the usefulness of our methods for a variety of 2D and 3D datasets and discuss the performance of our analysis pipeline.« less

  18. Systematic discovery and characterization of fly microRNAs using 12 Drosophila genomes

    PubMed Central

    Stark, Alexander; Kheradpour, Pouya; Parts, Leopold; Brennecke, Julius; Hodges, Emily; Hannon, Gregory J.; Kellis, Manolis

    2007-01-01

    MicroRNAs (miRNAs) are short regulatory RNAs that inhibit target genes by complementary binding in 3′ untranslated regions (3′ UTRs). They are one of the most abundant classes of regulators, targeting a large fraction of all genes, making their comprehensive study a requirement for understanding regulation and development. Here we use 12 Drosophila genomes to define structural and evolutionary signatures of miRNA hairpins, which we use for their de novo discovery. We predict >41 novel miRNA genes, which encompass many unique families, and 28 of which are validated experimentally. We also define signals for the precise start position of mature miRNAs, which suggest corrections of previously known miRNAs, often leading to drastic changes in their predicted target spectrum. We show that miRNA discovery power scales with the number and divergence of species compared, suggesting that such approaches can be successful in human as dozens of mammalian genomes become available. Interestingly, for some miRNAs sense and anti-sense hairpins score highly and mature miRNAs from both strands can indeed be found in vivo. Similarly, miRNAs with weak 5′ end predictions show increased in vivo processing of multiple alternate 5′ ends and have fewer predicted targets. Lastly, we show that several miRNA star sequences score highly and are likely functional. For mir-10 in particular, both arms show abundant processing, and both show highly conserved target sites in Hox genes, suggesting a possible cooperation of the two arms, and their role as a master Hox regulator. PMID:17989255

  19. Accelerating Precision Drug Development and Drug Repurposing by Leveraging Human Genetics

    PubMed Central

    Shirey-Rice, Jana K.; Lavieri, Robert R.; Jerome, Rebecca N.; Zaleski, Nicole M.; Aronoff, David M.; Bastarache, Lisa; Niu, Xinnan; Holroyd, Kenneth J.; Roden, Dan M.; Skaar, Eric P.; Niswender, Colleen M.; Marnett, Lawrence J.; Lindsley, Craig W.; Ekstrom, Leeland B.; Bentley, Alan R.; Bernard, Gordon R.; Hong, Charles C.; Denny, Joshua C.

    2017-01-01

    Abstract The potential impact of using human genetic data linked to longitudinal electronic medical records on drug development is extraordinary; however, the practical application of these data necessitates some organizational innovations. Vanderbilt has created resources such as an easily queried database of >2.6 million de-identified electronic health records linked to BioVU, which is a DNA biobank with more than 230,000 unique samples. To ensure these data are used to maximally benefit and accelerate both de novo drug discovery and drug repurposing efforts, we created the Accelerating Drug Development and Repurposing Incubator, a multidisciplinary think tank of experts in various therapeutic areas within both basic and clinical science as well as experts in legal, business, and other operational domains. The Incubator supports a diverse pipeline of drug indication finding projects, leveraging the natural experiment of human genetics. PMID:28379727

  20. 28 CFR 76.21 - Discovery.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 28 Judicial Administration 2 2013-07-01 2013-07-01 false Discovery. 76.21 Section 76.21 Judicial... POSSESSION OF CERTAIN CONTROLLED SUBSTANCES § 76.21 Discovery. (a) Scope. Discovery under this part covers... as a general guide for discovery practices in proceedings before the Judge. However, unless otherwise...