Towards High-throughput Immunomics for Infectious Diseases: Use of Next-generation Peptide Microarrays for Rapid Discovery and Mapping of Antigenic Determinants.

PubMed

Carmona, Santiago J; Nielsen, Morten; Schafer-Nielsen, Claus; Mucci, Juan; Altcheh, Jaime; Balouz, Virginia; Tekiel, Valeria; Frasch, Alberto C; Campetella, Oscar; Buscaglia, Carlos A; Agüero, Fernán

2015-07-01

Complete characterization of antibody specificities associated to natural infections is expected to provide a rich source of serologic biomarkers with potential applications in molecular diagnosis, follow-up of chemotherapeutic treatments, and prioritization of targets for vaccine development. Here, we developed a highly-multiplexed platform based on next-generation high-density peptide microarrays to map these specificities in Chagas Disease, an exemplar of a human infectious disease caused by the protozoan Trypanosoma cruzi. We designed a high-density peptide microarray containing more than 175,000 overlapping 15 mer peptides derived from T. cruzi proteins. Peptides were synthesized in situ on microarray slides, spanning the complete length of 457 parasite proteins with fully overlapped 15 mers (1 residue shift). Screening of these slides with antibodies purified from infected patients and healthy donors demonstrated both a high technical reproducibility as well as epitope mapping consistency when compared with earlier low-throughput technologies. Using a conservative signal threshold to classify positive (reactive) peptides we identified 2,031 disease-specific peptides and 97 novel parasite antigens, effectively doubling the number of known antigens and providing a 10-fold increase in the number of fine mapped antigenic determinants for this disease. Finally, further analysis of the chip data showed that optimizing the amount of sequence overlap of displayed peptides can increase the protein space covered in a single chip by at least ∼ threefold without sacrificing sensitivity. In conclusion, we show the power of high-density peptide chips for the discovery of pathogen-specific linear B-cell epitopes from clinical samples, thus setting the stage for high-throughput biomarker discovery screenings and proteome-wide studies of immune responses against pathogens. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Massive Collection of Full-Length Complementary DNA Clones and Microarray Analyses:. Keys to Rice Transcriptome Analysis

NASA Astrophysics Data System (ADS)

Kikuchi, Shoshi

2009-02-01

Completion of the high-precision genome sequence analysis of rice led to the collection of about 35,000 full-length cDNA clones and the determination of their complete sequences. Mapping of these full-length cDNA sequences has given us information on (1) the number of genes expressed in the rice genome; (2) the start and end positions and exon-intron structures of rice genes; (3) alternative transcripts; (4) possible encoded proteins; (5) non-protein-coding (np) RNAs; (6) the density of gene localization on the chromosome; (7) setting the parameters of gene prediction programs; and (8) the construction of a microarray system that monitors global gene expression. Manual curation for rice gene annotation by using mapping information on full-length cDNA and EST assemblies has revealed about 32,000 expressed genes in the rice genome. Analysis of major gene families, such as those encoding membrane transport proteins (pumps, ion channels, and secondary transporters), along with the evolution from bacteria to higher animals and plants, reveals how gene numbers have increased through adaptation to circumstances. Family-based gene annotation also gives us a new way of comparing organisms. Massive amounts of data on gene expression under many kinds of physiological conditions are being accumulated in rice oligoarrays (22K and 44K) based on full-length cDNA sequences. Cluster analyses of genes that have the same promoter cis-elements, that have similar expression profiles, or that encode enzymes in the same metabolic pathways or signal transduction cascades give us clues to understanding the networks of gene expression in rice. As a tool for that purpose, we recently developed "RiCES", a tool for searching for cis-elements in the promoter regions of clustered genes.

BioCichlid: central dogma-based 3D visualization system of time-course microarray data on a hierarchical biological network.

PubMed

Ishiwata, Ryosuke R; Morioka, Masaki S; Ogishima, Soichi; Tanaka, Hiroshi

2009-02-15

BioCichlid is a 3D visualization system of time-course microarray data on molecular networks, aiming at interpretation of gene expression data by transcriptional relationships based on the central dogma with physical and genetic interactions. BioCichlid visualizes both physical (protein) and genetic (regulatory) network layers, and provides animation of time-course gene expression data on the genetic network layer. Transcriptional regulations are represented to bridge the physical network (transcription factors) and genetic network (regulated genes) layers, thus integrating promoter analysis into the pathway mapping. BioCichlid enhances the interpretation of microarray data and allows for revealing the underlying mechanisms causing differential gene expressions. BioCichlid is freely available and can be accessed at http://newton.tmd.ac.jp/. Source codes for both biocichlid server and client are also available.

[Oligonucleotide microarray for subtyping avian influenza virus].

PubMed

Xueqing, Han; Xiangmei, Lin; Yihong, Hou; Shaoqiang, Wu; Jian, Liu; Lin, Mei; Guangle, Jia; Zexiao, Yang

2008-09-01

Avian influenza viruses are important human and animal respiratory pathogens and rapid diagnosis of novel emerging avian influenza viruses is vital for effective global influenza surveillance. We developed an oligonucleotide microarray-based method for subtyping all avian influenza virus (16 HA and 9 NA subtypes). In total 25 pairs of primers specific for different subtypes and 1 pair of universal primers were carefully designed based on the genomic sequences of influenza A viruses retrieved from GenBank database. Several multiplex RT-PCR methods were then developed, and the target cDNAs of 25 subtype viruses were amplified by RT-PCR or overlapping PCR for evaluating the microarray. Further 52 oligonucleotide probes specific for all 25 subtype viruses were designed according to published gene sequences of avian influenza viruses in amplified target cDNAs domains, and a microarray for subtyping influenza A virus was developed. Then its specificity and sensitivity were validated by using different subtype strains and 2653 samples from 49 different areas. The results showed that all the subtypes of influenza virus could be identified simultaneously on this microarray with high sensitivity, which could reach to 2.47 pfu/mL virus or 2.5 ng target DNA. Furthermore, there was no cross reaction with other avian respiratory virus. An oligonucleotide microarray-based strategy for detection of avian influenza viruses has been developed. Such a diagnostic microarray will be useful in discovering and identifying all subtypes of avian influenza virus.

BRCA-Monet: a breast cancer specific drug treatment mode-of-action network for treatment effective prediction using large scale microarray database

PubMed Central

2013-01-01

Background Connectivity map (cMap) is a recent developed dataset and algorithm for uncovering and understanding the treatment effect of small molecules on different cancer cell lines. It is widely used but there are still remaining challenges for accurate predictions. Method Here, we propose BRCA-MoNet, a network of drug mode of action (MoA) specific to breast cancer, which is constructed based on the cMap dataset. A drug signature selection algorithm fitting the characteristic of cMap data, a quality control scheme as well as a novel query algorithm based on BRCA-MoNet are developed for more effective prediction of drug effects. Result BRCA-MoNet was applied to three independent data sets obtained from the GEO database: Estrodial treated MCF7 cell line, BMS-754807 treated MCF7 cell line, and a breast cancer patient microarray dataset. In the first case, BRCA-MoNet could identify drug MoAs likely to share same and reverse treatment effect. In the second case, the result demonstrated the potential of BRCA-MoNet to reposition drugs and predict treatment effects for drugs not in cMap data. In the third case, a possible procedure of personalized drug selection is showcased. Conclusions The results clearly demonstrated that the proposed BRCA-MoNet approach can provide increased prediction power to cMap and thus will be useful for identification of new therapeutic candidates. Website: The web based application is developed and can be access through the following link http://compgenomics.utsa.edu/BRCAMoNet/ PMID:24564956

Comprehensive Assessments of RNA-seq by the SEQC Consortium: FDA-Led Efforts Advance Precision Medicine.

PubMed

Xu, Joshua; Gong, Binsheng; Wu, Leihong; Thakkar, Shraddha; Hong, Huixiao; Tong, Weida

2016-03-15

Studies on gene expression in response to therapy have led to the discovery of pharmacogenomics biomarkers and advances in precision medicine. Whole transcriptome sequencing (RNA-seq) is an emerging tool for profiling gene expression and has received wide adoption in the biomedical research community. However, its value in regulatory decision making requires rigorous assessment and consensus between various stakeholders, including the research community, regulatory agencies, and industry. The FDA-led SEquencing Quality Control (SEQC) consortium has made considerable progress in this direction, and is the subject of this review. Specifically, three RNA-seq platforms (Illumina HiSeq, Life Technologies SOLiD, and Roche 454) were extensively evaluated at multiple sites to assess cross-site and cross-platform reproducibility. The results demonstrated that relative gene expression measurements were consistently comparable across labs and platforms, but not so for the measurement of absolute expression levels. As part of the quality evaluation several studies were included to evaluate the utility of RNA-seq in clinical settings and safety assessment. The neuroblastoma study profiled tumor samples from 498 pediatric neuroblastoma patients by both microarray and RNA-seq. RNA-seq offers more utilities than microarray in determining the transcriptomic characteristics of cancer. However, RNA-seq and microarray-based models were comparable in clinical endpoint prediction, even when including additional features unique to RNA-seq beyond gene expression. The toxicogenomics study compared microarray and RNA-seq profiles of the liver samples from rats exposed to 27 different chemicals representing multiple toxicity modes of action. Cross-platform concordance was dependent on chemical treatment and transcript abundance. Though both RNA-seq and microarray are suitable for developing gene expression based predictive models with comparable prediction performance, RNA-seq offers advantages over microarray in profiling genes with low expression. The rat BodyMap study provided a comprehensive rat transcriptomic body map by performing RNA-Seq on 320 samples from 11 organs in either sex of juvenile, adolescent, adult and aged Fischer 344 rats. Lastly, the transferability study demonstrated that signature genes of predictive models are reciprocally transferable between microarray and RNA-seq data for model development using a comprehensive approach with two large clinical data sets. This result suggests continued usefulness of legacy microarray data in the coming RNA-seq era. In conclusion, the SEQC project enhances our understanding of RNA-seq and provides valuable guidelines for RNA-seq based clinical application and safety evaluation to advance precision medicine.

Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling

PubMed Central

Fang, H; Tong, W; Perkins, R; Shi, L; Hong, H; Cao, X; Xie, Q; Yim, SH; Ward, JM; Pitot, HC; Dragan, YP

2005-01-01

Background The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in animal models. These types of studies have the potential to greatly enhance our understanding of diseases such as liver cancer in humans. Genes co-expressed across multiple species are most likely to have conserved functions. We have used various bioinformatics approaches to examine microarray expression profiles from liver neoplasms that arise in albumin-SV40 transgenic rats to elucidate genes, chromosome aberrations and pathways that might be associated with human liver cancer. Results In this study, we first identified 2223 differentially expressed genes by comparing gene expression profiles for two control, two adenoma and two carcinoma samples using an F-test. These genes were subsequently mapped to the rat chromosomes using a novel visualization tool, the Chromosome Plot. Using the same plot, we further mapped the significant genes to orthologous chromosomal locations in human and mouse. Many genes expressed in rat 1q that are amplified in rat liver cancer map to the human chromosomes 10, 11 and 19 and to the mouse chromosomes 7, 17 and 19, which have been implicated in studies of human and mouse liver cancer. Using Comparative Genomics Microarray Analysis (CGMA), we identified regions of potential aberrations in human. Lastly, a pathway analysis was conducted to predict altered human pathways based on statistical analysis and extrapolation from the rat data. All of the identified pathways have been known to be important in the etiology of human liver cancer, including cell cycle control, cell growth and differentiation, apoptosis, transcriptional regulation, and protein metabolism. Conclusion The study demonstrates that the hepatic gene expression profiles from the albumin-SV40 transgenic rat model revealed genes, pathways and chromosome alterations consistent with experimental and clinical research in human liver cancer. The bioinformatics tools presented in this paper are essential for cross species extrapolation and mapping of microarray data, its analysis and interpretation. PMID:16026603

Development and application of a DNA microarray-based yeast two-hybrid system

PubMed Central

Suter, Bernhard; Fontaine, Jean-Fred; Yildirimman, Reha; Raskó, Tamás; Schaefer, Martin H.; Rasche, Axel; Porras, Pablo; Vázquez-Álvarez, Blanca M.; Russ, Jenny; Rau, Kirstin; Foulle, Raphaele; Zenkner, Martina; Saar, Kathrin; Herwig, Ralf; Andrade-Navarro, Miguel A.; Wanker, Erich E.

2013-01-01

The yeast two-hybrid (Y2H) system is the most widely applied methodology for systematic protein–protein interaction (PPI) screening and the generation of comprehensive interaction networks. We developed a novel Y2H interaction screening procedure using DNA microarrays for high-throughput quantitative PPI detection. Applying a global pooling and selection scheme to a large collection of human open reading frames, proof-of-principle Y2H interaction screens were performed for the human neurodegenerative disease proteins huntingtin and ataxin-1. Using systematic controls for unspecific Y2H results and quantitative benchmarking, we identified and scored a large number of known and novel partner proteins for both huntingtin and ataxin-1. Moreover, we show that this parallelized screening procedure and the global inspection of Y2H interaction data are uniquely suited to define specific PPI patterns and their alteration by disease-causing mutations in huntingtin and ataxin-1. This approach takes advantage of the specificity and flexibility of DNA microarrays and of the existence of solid-related statistical methods for the analysis of DNA microarray data, and allows a quantitative approach toward interaction screens in human and in model organisms. PMID:23275563

BRCA-Monet: a breast cancer specific drug treatment mode-of-action network for treatment effective prediction using large scale microarray database.

PubMed

Ma, Chifeng; Chen, Hung-I; Flores, Mario; Huang, Yufei; Chen, Yidong

2013-01-01

Connectivity map (cMap) is a recent developed dataset and algorithm for uncovering and understanding the treatment effect of small molecules on different cancer cell lines. It is widely used but there are still remaining challenges for accurate predictions. Here, we propose BRCA-MoNet, a network of drug mode of action (MoA) specific to breast cancer, which is constructed based on the cMap dataset. A drug signature selection algorithm fitting the characteristic of cMap data, a quality control scheme as well as a novel query algorithm based on BRCA-MoNet are developed for more effective prediction of drug effects. BRCA-MoNet was applied to three independent data sets obtained from the GEO database: Estrodial treated MCF7 cell line, BMS-754807 treated MCF7 cell line, and a breast cancer patient microarray dataset. In the first case, BRCA-MoNet could identify drug MoAs likely to share same and reverse treatment effect. In the second case, the result demonstrated the potential of BRCA-MoNet to reposition drugs and predict treatment effects for drugs not in cMap data. In the third case, a possible procedure of personalized drug selection is showcased. The results clearly demonstrated that the proposed BRCA-MoNet approach can provide increased prediction power to cMap and thus will be useful for identification of new therapeutic candidates.

Quantification of the epitope diversity of HIV-1-specific binding antibodies by peptide microarrays for global HIV-1 vaccine development

DOE PAGES

Stephenson, Kathryn E.; Neubauer, George H.; Reimer, Ulf; ...

2014-11-14

An effective vaccine against human immunodeficiency virus type 1 (HIV-1) will have to provide protection against a vast array of different HIV-1 strains. Current methods to measure HIV-1-specific binding antibodies following immunization typically focus on determining the magnitude of antibody responses, but the epitope diversity of antibody responses has remained largely unexplored. Here we describe the development of a global HIV-1 peptide microarray that contains 6564 peptides from across the HIV-1 proteome and covers the majority of HIV-1 sequences in the Los Alamos National Laboratory global HIV-1 sequence database. Using this microarray, we quantified the magnitude, breadth, and depth ofmore » IgG binding to linear HIV-1 sequences in HIV-1-infected humans and HIV-1-vaccinated humans, rhesus monkeys and guinea pigs. The microarray measured potentially important differences in antibody epitope diversity, particularly regarding the depth of epitope variants recognized at each binding site. Our data suggest that the global HIV-1 peptide microarray may be a useful tool for both preclinical and clinical HIV-1 research.« less

Quantification of the epitope diversity of HIV-1-specific binding antibodies by peptide microarrays for global HIV-1 vaccine development

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

Stephenson, Kathryn E.; Neubauer, George H.; Reimer, Ulf

An effective vaccine against human immunodeficiency virus type 1 (HIV-1) will have to provide protection against a vast array of different HIV-1 strains. Current methods to measure HIV-1-specific binding antibodies following immunization typically focus on determining the magnitude of antibody responses, but the epitope diversity of antibody responses has remained largely unexplored. Here we describe the development of a global HIV-1 peptide microarray that contains 6564 peptides from across the HIV-1 proteome and covers the majority of HIV-1 sequences in the Los Alamos National Laboratory global HIV-1 sequence database. Using this microarray, we quantified the magnitude, breadth, and depth ofmore » IgG binding to linear HIV-1 sequences in HIV-1-infected humans and HIV-1-vaccinated humans, rhesus monkeys and guinea pigs. The microarray measured potentially important differences in antibody epitope diversity, particularly regarding the depth of epitope variants recognized at each binding site. Our data suggest that the global HIV-1 peptide microarray may be a useful tool for both preclinical and clinical HIV-1 research.« less

Copper-catalyzed azide-alkyne cycloaddition (click chemistry)-based Detection of Global Pathogen-host AMPylation on Self-assembled Human Protein Microarrays*

PubMed Central

Yu, Xiaobo; Woolery, Andrew R.; Luong, Phi; Hao, Yi Heng; Grammel, Markus; Westcott, Nathan; Park, Jin; Wang, Jie; Bian, Xiaofang; Demirkan, Gokhan; Hang, Howard C.; Orth, Kim; LaBaer, Joshua

2014-01-01

AMPylation (adenylylation) is a recently discovered mechanism employed by infectious bacteria to regulate host cell signaling. However, despite significant effort, only a few host targets have been identified, limiting our understanding of how these pathogens exploit this mechanism to control host cells. Accordingly, we developed a novel nonradioactive AMPylation screening platform using high-density cell-free protein microarrays displaying human proteins produced by human translational machinery. We screened 10,000 unique human proteins with Vibrio parahaemolyticus VopS and Histophilus somni IbpAFic2, and identified many new AMPylation substrates. Two of these, Rac2, and Rac3, were confirmed in vivo as bona fide substrates during infection with Vibrio parahaemolyticus. We also mapped the site of AMPylation of a non-GTPase substrate, LyGDI, to threonine 51, in a region regulated by Src kinase, and demonstrated that AMPylation prevented its phosphorylation by Src. Our results greatly expanded the repertoire of potential host substrates for bacterial AMPylators, determined their recognition motif, and revealed the first pathogen-host interaction AMPylation network. This approach can be extended to identify novel substrates of AMPylators with different domains or in different species and readily adapted for other post-translational modifications. PMID:25073739

Gene expression pattern recognition algorithm inferences to classify samples exposed to chemical agents

NASA Astrophysics Data System (ADS)

Bushel, Pierre R.; Bennett, Lee; Hamadeh, Hisham; Green, James; Ableson, Alan; Misener, Steve; Paules, Richard; Afshari, Cynthia

2002-06-01

We present an analysis of pattern recognition procedures used to predict the classes of samples exposed to pharmacologic agents by comparing gene expression patterns from samples treated with two classes of compounds. Rat liver mRNA samples following exposure for 24 hours with phenobarbital or peroxisome proliferators were analyzed using a 1700 rat cDNA microarray platform. Sets of genes that were consistently differentially expressed in the rat liver samples following treatment were stored in the MicroArray Project System (MAPS) database. MAPS identified 238 genes in common that possessed a low probability (P < 0.01) of being randomly detected as differentially expressed at the 95% confidence level. Hierarchical cluster analysis on the 238 genes clustered specific gene expression profiles that separated samples based on exposure to a particular class of compound.

High-throughput microarray technology in diagnostics of enterobacteria based on genome-wide probe selection and regression analysis.

PubMed

Friedrich, Torben; Rahmann, Sven; Weigel, Wilfried; Rabsch, Wolfgang; Fruth, Angelika; Ron, Eliora; Gunzer, Florian; Dandekar, Thomas; Hacker, Jörg; Müller, Tobias; Dobrindt, Ulrich

2010-10-21

The Enterobacteriaceae comprise a large number of clinically relevant species with several individual subspecies. Overlapping virulence-associated gene pools and the high overall genome plasticity often interferes with correct enterobacterial strain typing and risk assessment. Array technology offers a fast, reproducible and standardisable means for bacterial typing and thus provides many advantages for bacterial diagnostics, risk assessment and surveillance. The development of highly discriminative broad-range microbial diagnostic microarrays remains a challenge, because of marked genome plasticity of many bacterial pathogens. We developed a DNA microarray for strain typing and detection of major antimicrobial resistance genes of clinically relevant enterobacteria. For this purpose, we applied a global genome-wide probe selection strategy on 32 available complete enterobacterial genomes combined with a regression model for pathogen classification. The discriminative power of the probe set was further tested in silico on 15 additional complete enterobacterial genome sequences. DNA microarrays based on the selected probes were used to type 92 clinical enterobacterial isolates. Phenotypic tests confirmed the array-based typing results and corroborate that the selected probes allowed correct typing and prediction of major antibiotic resistances of clinically relevant Enterobacteriaceae, including the subspecies level, e.g. the reliable distinction of different E. coli pathotypes. Our results demonstrate that the global probe selection approach based on longest common factor statistics as well as the design of a DNA microarray with a restricted set of discriminative probes enables robust discrimination of different enterobacterial variants and represents a proof of concept that can be adopted for diagnostics of a wide range of microbial pathogens. Our approach circumvents misclassifications arising from the application of virulence markers, which are highly affected by horizontal gene transfer. Moreover, a broad range of pathogens have been covered by an efficient probe set size enabling the design of high-throughput diagnostics.

Fast gene ontology based clustering for microarray experiments.

PubMed

Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

2008-11-21

Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

Gene expression analysis of the biocontrol fungus Trichoderma harzianum in the presence of tomato plants, chitin, or glucose using a high-density oligonucleotide microarray.

PubMed

Samolski, Ilanit; de Luis, Alberto; Vizcaíno, Juan Antonio; Monte, Enrique; Suárez, M Belén

2009-10-13

It has recently been shown that the Trichoderma fungal species used for biocontrol of plant diseases are capable of interacting with plant roots directly, behaving as symbiotic microorganisms. With a view to providing further information at transcriptomic level about the early response of Trichoderma to a host plant, we developed a high-density oligonucleotide (HDO) microarray encompassing 14,081 Expressed Sequence Tag (EST)-based transcripts from eight Trichoderma spp. and 9,121 genome-derived transcripts of T. reesei, and we have used this microarray to examine the gene expression of T. harzianum either alone or in the presence of tomato plants, chitin, or glucose. Global microarray analysis revealed 1,617 probe sets showing differential expression in T. harzianum mycelia under at least one of the culture conditions tested as compared with one another. Hierarchical clustering and heat map representation showed that the expression patterns obtained in glucose medium clustered separately from the expression patterns observed in the presence of tomato plants and chitin. Annotations using the Blast2GO suite identified 85 of the 257 transcripts whose probe sets afforded up-regulated expression in response to tomato plants. Some of these transcripts were predicted to encode proteins related to Trichoderma-host (fungus or plant) associations, such as Sm1/Elp1 protein, proteases P6281 and PRA1, enchochitinase CHIT42, or QID74 protein, although previously uncharacterized genes were also identified, including those responsible for the possible biosynthesis of nitric oxide, xenobiotic detoxification, mycelium development, or those related to the formation of infection structures in plant tissues. The effectiveness of the Trichoderma HDO microarray to detect different gene responses under different growth conditions in the fungus T. harzianum strongly indicates that this tool should be useful for further assays that include different stages of plant colonization, as well as for expression studies in other Trichoderma spp. represented on it. Using this microarray, we have been able to define a number of genes probably involved in the transcriptional response of T. harzianum within the first hours of contact with tomato plant roots, which may provide new insights into the mechanisms and roles of this fungus in the Trichoderma-plant interaction.

Gene expression analysis of the biocontrol fungus Trichoderma harzianum in the presence of tomato plants, chitin, or glucose using a high-density oligonucleotide microarray

PubMed Central

2009-01-01

Background It has recently been shown that the Trichoderma fungal species used for biocontrol of plant diseases are capable of interacting with plant roots directly, behaving as symbiotic microorganisms. With a view to providing further information at transcriptomic level about the early response of Trichoderma to a host plant, we developed a high-density oligonucleotide (HDO) microarray encompassing 14,081 Expressed Sequence Tag (EST)-based transcripts from eight Trichoderma spp. and 9,121 genome-derived transcripts of T. reesei, and we have used this microarray to examine the gene expression of T. harzianum either alone or in the presence of tomato plants, chitin, or glucose. Results Global microarray analysis revealed 1,617 probe sets showing differential expression in T. harzianum mycelia under at least one of the culture conditions tested as compared with one another. Hierarchical clustering and heat map representation showed that the expression patterns obtained in glucose medium clustered separately from the expression patterns observed in the presence of tomato plants and chitin. Annotations using the Blast2GO suite identified 85 of the 257 transcripts whose probe sets afforded up-regulated expression in response to tomato plants. Some of these transcripts were predicted to encode proteins related to Trichoderma-host (fungus or plant) associations, such as Sm1/Elp1 protein, proteases P6281 and PRA1, enchochitinase CHIT42, or QID74 protein, although previously uncharacterized genes were also identified, including those responsible for the possible biosynthesis of nitric oxide, xenobiotic detoxification, mycelium development, or those related to the formation of infection structures in plant tissues. Conclusion The effectiveness of the Trichoderma HDO microarray to detect different gene responses under different growth conditions in the fungus T. harzianum strongly indicates that this tool should be useful for further assays that include different stages of plant colonization, as well as for expression studies in other Trichoderma spp. represented on it. Using this microarray, we have been able to define a number of genes probably involved in the transcriptional response of T. harzianum within the first hours of contact with tomato plant roots, which may provide new insights into the mechanisms and roles of this fungus in the Trichoderma-plant interaction. PMID:19825185

A genome-wide 20 K citrus microarray for gene expression analysis

PubMed Central

Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

2008-01-01

Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database [1] was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in citrus globular embryos. PMID:18598343

The Importance of Normalization on Large and Heterogeneous Microarray Datasets

EPA Science Inventory

DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

Low-Cost Peptide Microarrays for Mapping Continuous Antibody Epitopes.

PubMed

McBride, Ryan; Head, Steven R; Ordoukhanian, Phillip; Law, Mansun

2016-01-01

With the increasing need for understanding antibody specificity in antibody and vaccine research, pepscan assays provide a rapid method for mapping and profiling antibody responses to continuous epitopes. We have developed a relatively low-cost method to generate peptide microarray slides for studying antibody binding. Using a setup of an IntavisAG MultiPep RS peptide synthesizer, a Digilab MicroGrid II 600 microarray printer robot, and an InnoScan 1100 AL scanner, the method allows the interrogation of up to 1536 overlapping, alanine-scanning, and mutant peptides derived from the target antigens. Each peptide is tagged with a polyethylene glycol aminooxy terminus to improve peptide solubility, orientation, and conjugation efficiency to the slide surface.

Mapping the affinity landscape of Thrombin-binding aptamers on 2΄F-ANA/DNA chimeric G-Quadruplex microarrays

PubMed Central

Abou Assi, Hala; Gómez-Pinto, Irene; González, Carlos

2017-01-01

Abstract In situ fabricated nucleic acids microarrays are versatile and very high-throughput platforms for aptamer optimization and discovery, but the chemical space that can be probed against a given target has largely been confined to DNA, while RNA and non-natural nucleic acid microarrays are still an essentially uncharted territory. 2΄-Fluoroarabinonucleic acid (2΄F-ANA) is a prime candidate for such use in microarrays. Indeed, 2΄F-ANA chemistry is readily amenable to photolithographic microarray synthesis and its potential in high affinity aptamers has been recently discovered. We thus synthesized the first microarrays containing 2΄F-ANA and 2΄F-ANA/DNA chimeric sequences to fully map the binding affinity landscape of the TBA1 thrombin-binding G-quadruplex aptamer containing all 32 768 possible DNA-to-2΄F-ANA mutations. The resulting microarray was screened against thrombin to identify a series of promising 2΄F-ANA-modified aptamer candidates with Kds significantly lower than that of the unmodified control and which were found to adopt highly stable, antiparallel-folded G-quadruplex structures. The solution structure of the TBA1 aptamer modified with 2΄F-ANA at position T3 shows that fluorine substitution preorganizes the dinucleotide loop into the proper conformation for interaction with thrombin. Overall, our work strengthens the potential of 2΄F-ANA in aptamer research and further expands non-genomic applications of nucleic acids microarrays. PMID:28100695

The Ser/Thr Protein Kinase Protein-Protein Interaction Map of M. tuberculosis.

PubMed

Wu, Fan-Lin; Liu, Yin; Jiang, He-Wei; Luan, Yi-Zhao; Zhang, Hai-Nan; He, Xiang; Xu, Zhao-Wei; Hou, Jing-Li; Ji, Li-Yun; Xie, Zhi; Czajkowsky, Daniel M; Yan, Wei; Deng, Jiao-Yu; Bi, Li-Jun; Zhang, Xian-En; Tao, Sheng-Ce

2017-08-01

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, the leading cause of death among all infectious diseases. There are 11 eukaryotic-like serine/threonine protein kinases (STPKs) in Mtb, which are thought to play pivotal roles in cell growth, signal transduction and pathogenesis. However, their underlying mechanisms of action remain largely uncharacterized. In this study, using a Mtb proteome microarray, we have globally identified the binding proteins in Mtb for all of the STPKs, and constructed the first STPK protein interaction (KPI) map that includes 492 binding proteins and 1,027 interactions. Bioinformatics analysis showed that the interacting proteins reflect diverse functions, including roles in two-component system, transcription, protein degradation, and cell wall integrity. Functional investigations confirmed that PknG regulates cell wall integrity through key components of peptidoglycan (PG) biosynthesis, e.g. MurC. The global STPK-KPIs network constructed here is expected to serve as a rich resource for understanding the key signaling pathways in Mtb, thus facilitating drug development and effective control of Mtb. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Gene Expression Profiling Reveals a Massive, Aneuploidy-Dependent Transcriptional Deregulation and Distinct Differences between Lymph Node–Negative and Lymph Node–Positive Colon Carcinomas

PubMed Central

Grade, Marian; Hörmann, Patrick; Becker, Sandra; Hummon, Amanda B.; Wangsa, Danny; Varma, Sudhir; Simon, Richard; Liersch, Torsten; Becker, Heinz; Difilippantonio, Michael J.; Ghadimi, B. Michael; Ried, Thomas

2016-01-01

To characterize patterns of global transcriptional deregulation in primary colon carcinomas, we did gene expression profiling of 73 tumors [Unio Internationale Contra Cancrum stage II (n = 33) and stage III (n = 40)] using oligonucleotide microarrays. For 30 of the tumors, expression profiles were compared with those from matched normal mucosa samples. We identified a set of 1,950 genes with highly significant deregulation between tumors and mucosa samples (P < 1e–7). A significant proportion of these genes mapped to chromosome 20 (P = 0.01). Seventeen genes had a >5-fold average expression difference between normal colon mucosa and carcinomas, including up-regulation of MYC and of HMGA1, a putative oncogene. Furthermore, we identified 68 genes that were significantly differentially expressed between lymph node–negative and lymph node–positive tumors (P < 0.001), the functional annotation of which revealed a preponderance of genes that play a role in cellular immune response and surveillance. The microarray-derived gene expression levels of 20 deregulated genes were validated using quantitative real-time reverse transcription-PCR in >40 tumor and normal mucosa samples with good concordance between the techniques. Finally, we established a relationship between specific genomic imbalances, which were mapped for 32 of the analyzed colon tumors by comparative genomic hybridization, and alterations of global transcriptional activity. Previously, we had conducted a similar analysis of primary rectal carcinomas. The systematic comparison of colon and rectal carcinomas revealed a significant overlap of genomic imbalances and transcriptional deregulation, including activation of the Wnt/β-catenin signaling cascade, suggesting similar pathogenic pathways. PMID:17210682

Gene expression profiling reveals a massive, aneuploidy-dependent transcriptional deregulation and distinct differences between lymph node-negative and lymph node-positive colon carcinomas.

PubMed

Grade, Marian; Hörmann, Patrick; Becker, Sandra; Hummon, Amanda B; Wangsa, Danny; Varma, Sudhir; Simon, Richard; Liersch, Torsten; Becker, Heinz; Difilippantonio, Michael J; Ghadimi, B Michael; Ried, Thomas

2007-01-01

To characterize patterns of global transcriptional deregulation in primary colon carcinomas, we did gene expression profiling of 73 tumors [Unio Internationale Contra Cancrum stage II (n = 33) and stage III (n = 40)] using oligonucleotide microarrays. For 30 of the tumors, expression profiles were compared with those from matched normal mucosa samples. We identified a set of 1,950 genes with highly significant deregulation between tumors and mucosa samples (P < 1e-7). A significant proportion of these genes mapped to chromosome 20 (P = 0.01). Seventeen genes had a >5-fold average expression difference between normal colon mucosa and carcinomas, including up-regulation of MYC and of HMGA1, a putative oncogene. Furthermore, we identified 68 genes that were significantly differentially expressed between lymph node-negative and lymph node-positive tumors (P < 0.001), the functional annotation of which revealed a preponderance of genes that play a role in cellular immune response and surveillance. The microarray-derived gene expression levels of 20 deregulated genes were validated using quantitative real-time reverse transcription-PCR in >40 tumor and normal mucosa samples with good concordance between the techniques. Finally, we established a relationship between specific genomic imbalances, which were mapped for 32 of the analyzed colon tumors by comparative genomic hybridization, and alterations of global transcriptional activity. Previously, we had conducted a similar analysis of primary rectal carcinomas. The systematic comparison of colon and rectal carcinomas revealed a significant overlap of genomic imbalances and transcriptional deregulation, including activation of the Wnt/beta-catenin signaling cascade, suggesting similar pathogenic pathways.

Combining mouse mammary gland gene expression and comparative mapping for the identification of candidate genes for QTL of milk production traits in cattle

PubMed Central

Ron, Micha; Israeli, Galit; Seroussi, Eyal; Weller, Joel I; Gregg, Jeffrey P; Shani, Moshe; Medrano, Juan F

2007-01-01

Background Many studies have found segregating quantitative trait loci (QTL) for milk production traits in different dairy cattle populations. However, even for relatively large effects with a saturated marker map the confidence interval for QTL location by linkage analysis spans tens of map units, or hundreds of genes. Combining mapping and arraying has been suggested as an approach to identify candidate genes. Thus, gene expression analysis in the mammary gland of genes positioned in the confidence interval of the QTL can bridge the gap between fine mapping and quantitative trait nucleotide (QTN) determination. Results We hybridized Affymetrix microarray (MG-U74v2), containing 12,488 murine probes, with RNA derived from mammary gland of virgin, pregnant, lactating and involuting C57BL/6J mice in a total of nine biological replicates. We combined microarray data from two additional studies that used the same design in mice with a total of 75 biological replicates. The same filtering and normalization was applied to each microarray data using GeneSpring software. Analysis of variance identified 249 differentially expressed probe sets common to the three experiments along the four developmental stages of puberty, pregnancy, lactation and involution. 212 genes were assigned to their bovine map positions through comparative mapping, and thus form a list of candidate genes for previously identified QTLs for milk production traits. A total of 82 of the genes showed mammary gland-specific expression with at least 3-fold expression over the median representing all tissues tested in GeneAtlas. Conclusion This work presents a web tool for candidate genes for QTL (cgQTL) that allows navigation between the map of bovine milk production QTL, potential candidate genes and their level of expression in mammary gland arrays and in GeneAtlas. Three out of four confirmed genes that affect QTL in livestock (ABCG2, DGAT1, GDF8, IGF2) were over expressed in the target organ. Thus, cgQTL can be used to determine priority of candidate genes for QTN analysis based on differential expression in the target organ. PMID:17584498

Microarray as a First Genetic Test in Global Developmental Delay: A Cost-Effectiveness Analysis

ERIC Educational Resources Information Center

Trakadis, Yannis; Shevell, Michael

2011-01-01

Aim: Microarray technology has a significantly higher clinical yield than karyotyping in individuals with global developmental delay (GDD). Despite this, it has not yet been routinely implemented as a screening test owing to the perception that this approach is more expensive. We aimed to evaluate the effect that replacing karyotype with…

Microarray missing data imputation based on a set theoretic framework and biological knowledge.

PubMed

Gan, Xiangchao; Liew, Alan Wee-Chung; Yan, Hong

2006-01-01

Gene expressions measured using microarrays usually suffer from the missing value problem. However, in many data analysis methods, a complete data matrix is required. Although existing missing value imputation algorithms have shown good performance to deal with missing values, they also have their limitations. For example, some algorithms have good performance only when strong local correlation exists in data while some provide the best estimate when data is dominated by global structure. In addition, these algorithms do not take into account any biological constraint in their imputation. In this paper, we propose a set theoretic framework based on projection onto convex sets (POCS) for missing data imputation. POCS allows us to incorporate different types of a priori knowledge about missing values into the estimation process. The main idea of POCS is to formulate every piece of prior knowledge into a corresponding convex set and then use a convergence-guaranteed iterative procedure to obtain a solution in the intersection of all these sets. In this work, we design several convex sets, taking into consideration the biological characteristic of the data: the first set mainly exploit the local correlation structure among genes in microarray data, while the second set captures the global correlation structure among arrays. The third set (actually a series of sets) exploits the biological phenomenon of synchronization loss in microarray experiments. In cyclic systems, synchronization loss is a common phenomenon and we construct a series of sets based on this phenomenon for our POCS imputation algorithm. Experiments show that our algorithm can achieve a significant reduction of error compared to the KNNimpute, SVDimpute and LSimpute methods.

Microarray-assisted fine-mapping of quantitative trait loci for cold tolerance in rice.

PubMed

Liu, Fengxia; Xu, Wenying; Song, Qian; Tan, Lubin; Liu, Jiayong; Zhu, Zuofeng; Fu, Yongcai; Su, Zhen; Sun, Chuanqing

2013-05-01

Many important agronomic traits, including cold stress resistance, are complex and controlled by quantitative trait loci (QTLs). Isolation of these QTLs will greatly benefit the agricultural industry but it is a challenging task. This study explored an integrated strategy by combining microarray with QTL-mapping in order to identify cold-tolerant QTLs from a cold-tolerant variety IL112 at early-seedling stage. All the early seedlings of IL112 survived normally for 9 d at 4-5°C, while Guichao2 (GC2), an indica cultivar, died after 4 d under the same conditions. Using the F2:3 population derived from the progeny of GC2 and IL112, we identified seven QTLs for cold tolerance. Furthermore, we performed Affymetrix rice whole-genome array hybridization and obtained the expression profiles of IL112 and GC2 under both low-temperature and normal conditions. Four genes were selected as cold QTL-related candidates, based on microarray data mining and QTL-mapping. One candidate gene, LOC_Os07g22494, was shown to be highly associated with cold tolerance in a number of rice varieties and in the F2:3 population, and its overexpression transgenic rice plants displayed strong tolerance to low temperature at early-seedling stage. The results indicated that overexpression of this gene (LOC_Os07g22494) could increase cold tolerance in rice seedlings. Therefore, this study provides a promising strategy for identifying candidate genes in defined QTL regions.

Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes.

PubMed

Brock, Guy N; Shaffer, John R; Blakesley, Richard E; Lotz, Meredith J; Tseng, George C

2008-01-10

Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures x time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. We found that the optimal imputation algorithms (LSA, LLS, and BPCA) are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS) scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS) scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA) are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA) performed better on mcroarray data with lower complexity, while neighbour-based methods (KNN, OLS, LSA, LLS) performed better in data with higher complexity. We also found that the EBS and STS schemes serve as complementary and effective tools for selecting the optimal imputation algorithm.

Methylation-Sensitive Amplification Length Polymorphism (MS-AFLP) Microarrays for Epigenetic Analysis of Human Genomes.

PubMed

Alonso, Sergio; Suzuki, Koichi; Yamamoto, Fumiichiro; Perucho, Manuel

2018-01-01

Somatic, and in a minor scale also germ line, epigenetic aberrations are fundamental to carcinogenesis, cancer progression, and tumor phenotype. DNA methylation is the most extensively studied and arguably the best understood epigenetic mechanisms that become altered in cancer. Both somatic loss of methylation (hypomethylation) and gain of methylation (hypermethylation) are found in the genome of malignant cells. In general, the cancer cell epigenome is globally hypomethylated, while some regions-typically gene-associated CpG islands-become hypermethylated. Given the profound impact that DNA methylation exerts on the transcriptional profile and genomic stability of cancer cells, its characterization is essential to fully understand the complexity of cancer biology, improve tumor classification, and ultimately advance cancer patient management and treatment. A plethora of methods have been devised to analyze and quantify DNA methylation alterations. Several of the early-developed methods relied on the use of methylation-sensitive restriction enzymes, whose activity depends on the methylation status of their recognition sequences. Among these techniques, methylation-sensitive amplification length polymorphism (MS-AFLP) was developed in the early 2000s, and successfully adapted from its original gel electrophoresis fingerprinting format to a microarray format that notably increased its throughput and allowed the quantification of the methylation changes. This array-based platform interrogates over 9500 independent loci putatively amplified by the MS-AFLP technique, corresponding to the NotI sites mapped throughout the human genome.

Diversity Arrays Technology (DArT) platform for genotyping and mapping in carrot (Daucus carota L.)

USDA-ARS?s Scientific Manuscript database

Carrot is one of the most important root vegetable crops grown worldwide on more than one million hectares. Its progenitor, wild Daucus carota, is a weed commonly occurring across continents in the temperate climatic zone. Diversity Array Technology (DArT) is a microarray-based molecular marker syst...

Genetic Mapping

MedlinePlus

... Sheets A Brief Guide to Genomics About NHGRI Research About the International HapMap Project Biological Pathways Chromosome Abnormalities Chromosomes Cloning Comparative Genomics DNA Microarray Technology DNA Sequencing Deoxyribonucleic Acid ( ...

Detection and identification of intestinal pathogenic bacteria by hybridization to oligonucleotide microarrays

PubMed Central

Jin, Lian-Qun; Li, Jun-Wen; Wang, Sheng-Qi; Chao, Fu-Huan; Wang, Xin-Wei; Yuan, Zheng-Quan

2005-01-01

AIM: To detect the common intestinal pathogenic bacteria quickly and accurately. METHODS: A rapid (<3 h) experimental procedure was set up based upon the gene chip technology. Target genes were amplified and hybridized by oligonucleotide microarrays. RESULTS: One hundred and seventy strains of bacteria in pure culture belonging to 11 genera were successfully discriminated under comparatively same conditions, and a series of specific hybridization maps corresponding to each kind of bacteria were obtained. When this method was applied to 26 divided cultures, 25 (96.2%) were identified. CONCLUSION: Salmonella sp., Escherichia coli, Shigella sp., Listeria monocytogenes, Vibrio parahaemolyticus, Staphylococcus aureus, Proteus sp., Bacillus cereus, Vibrio cholerae, Enterococcus faecalis, Yersinia enterocolitica, and Campylobacter jejuni can be detected and identified by our microarrays. The accuracy, range, and discrimination power of this assay can be continually improved by adding further oligonucleotides to the arrays without any significant increase of complexity or cost. PMID:16437687

A new world natural vegetation map for global change studies.

PubMed

Lapola, David M; Oyama, Marcos D; Nobre, Carlos A; Sampaio, Gilvan

2008-06-01

We developed a new world natural vegetation map at 1 degree horizontal resolution for use in global climate models. We used the Dorman and Sellers vegetation classification with inclusion of a new biome: tropical seasonal forest, which refers to both deciduous and semi-deciduous tropical forests. SSiB biogeophysical parameters values for this new biome type are presented. Under this new vegetation classification we obtained a consensus map between two global natural vegetation maps widely used in climate studies. We found that these two maps assign different biomes in ca. 1/3 of the continental grid points. To obtain a new global natural vegetation map, non-consensus areas were filled according to regional consensus based on more than 100 regional maps available on the internet. To minimize the risk of using poor quality information, the regional maps were obtained from reliable internet sources, and the filling procedure was based on the consensus among several regional maps obtained from independent sources. The new map was designed to reproduce accurately both the large-scale distribution of the main vegetation types (as it builds on two reliable global natural vegetation maps) and the regional details (as it is based on the consensus of regional maps).

Identification of significant features by the Global Mean Rank test.

PubMed

Klammer, Martin; Dybowski, J Nikolaj; Hoffmann, Daniel; Schaab, Christoph

2014-01-01

With the introduction of omics-technologies such as transcriptomics and proteomics, numerous methods for the reliable identification of significantly regulated features (genes, proteins, etc.) have been developed. Experimental practice requires these tests to successfully deal with conditions such as small numbers of replicates, missing values, non-normally distributed expression levels, and non-identical distributions of features. With the MeanRank test we aimed at developing a test that performs robustly under these conditions, while favorably scaling with the number of replicates. The test proposed here is a global one-sample location test, which is based on the mean ranks across replicates, and internally estimates and controls the false discovery rate. Furthermore, missing data is accounted for without the need of imputation. In extensive simulations comparing MeanRank to other frequently used methods, we found that it performs well with small and large numbers of replicates, feature dependent variance between replicates, and variable regulation across features on simulation data and a recent two-color microarray spike-in dataset. The tests were then used to identify significant changes in the phosphoproteomes of cancer cells induced by the kinase inhibitors erlotinib and 3-MB-PP1 in two independently published mass spectrometry-based studies. MeanRank outperformed the other global rank-based methods applied in this study. Compared to the popular Significance Analysis of Microarrays and Linear Models for Microarray methods, MeanRank performed similar or better. Furthermore, MeanRank exhibits more consistent behavior regarding the degree of regulation and is robust against the choice of preprocessing methods. MeanRank does not require any imputation of missing values, is easy to understand, and yields results that are easy to interpret. The software implementing the algorithm is freely available for academic and commercial use.

Mapping yeast origins of replication via single-stranded DNA detection.

PubMed

Feng, Wenyi; Raghuraman, M K; Brewer, Bonita J

2007-02-01

Studies in th Saccharomyces cerevisiae have provided a framework for understanding how eukaryotic cells replicate their chromosomal DNA to ensure faithful transmission of genetic information to their daughter cells. In particular, S. cerevisiae is the first eukaryote to have its origins of replication mapped on a genomic scale, by three independent groups using three different microarray-based approaches. Here we describe a new technique of origin mapping via detection of single-stranded DNA in yeast. This method not only identified the majority of previously discovered origins, but also detected new ones. We have also shown that this technique can identify origins in Schizosaccharomyces pombe, illustrating the utility of this method for origin mapping in other eukaryotes.

Mapping autosomal recessive intellectual disability: combined microarray and exome sequencing identifies 26 novel candidate genes in 192 consanguineous families.

PubMed

Harripaul, R; Vasli, N; Mikhailov, A; Rafiq, M A; Mittal, K; Windpassinger, C; Sheikh, T I; Noor, A; Mahmood, H; Downey, S; Johnson, M; Vleuten, K; Bell, L; Ilyas, M; Khan, F S; Khan, V; Moradi, M; Ayaz, M; Naeem, F; Heidari, A; Ahmed, I; Ghadami, S; Agha, Z; Zeinali, S; Qamar, R; Mozhdehipanah, H; John, P; Mir, A; Ansar, M; French, L; Ayub, M; Vincent, J B

2018-04-01

Approximately 1% of the global population is affected by intellectual disability (ID), and the majority receive no molecular diagnosis. Previous studies have indicated high levels of genetic heterogeneity, with estimates of more than 2500 autosomal ID genes, the majority of which are autosomal recessive (AR). Here, we combined microarray genotyping, homozygosity-by-descent (HBD) mapping, copy number variation (CNV) analysis, and whole exome sequencing (WES) to identify disease genes/mutations in 192 multiplex Pakistani and Iranian consanguineous families with non-syndromic ID. We identified definite or candidate mutations (or CNVs) in 51% of families in 72 different genes, including 26 not previously reported for ARID. The new ARID genes include nine with loss-of-function mutations (ABI2, MAPK8, MPDZ, PIDD1, SLAIN1, TBC1D23, TRAPPC6B, UBA7 and USP44), and missense mutations include the first reports of variants in BDNF or TET1 associated with ID. The genes identified also showed overlap with de novo gene sets for other neuropsychiatric disorders. Transcriptional studies showed prominent expression in the prenatal brain. The high yield of AR mutations for ID indicated that this approach has excellent clinical potential and should inform clinical diagnostics, including clinical whole exome and genome sequencing, for populations in which consanguinity is common. As with other AR disorders, the relevance will also apply to outbred populations.

Martian Lobate Debris Aprons: Compilation of a New GIS-Based Global Map

NASA Astrophysics Data System (ADS)

Chuang, F. C.; Crown, D. A.; Berman, D. C.; Skinner, J. A.; Tanaka, K. L.

2011-03-01

Compilation of a new GIS-based global map of lobate debris aprons is underway to better understand the global inventory of these relict ice-rich features. We welcome contributions of GIS-based data from other investigators.

Rapid Detection of Rare Deleterious Variants by Next Generation Sequencing with Optional Microarray SNP Genotype Data

PubMed Central

Watson, Christopher M.; Crinnion, Laura A.; Gurgel‐Gianetti, Juliana; Harrison, Sally M.; Daly, Catherine; Antanavicuite, Agne; Lascelles, Carolina; Markham, Alexander F.; Pena, Sergio D. J.; Bonthron, David T.

2015-01-01

ABSTRACT Autozygosity mapping is a powerful technique for the identification of rare, autosomal recessive, disease‐causing genes. The ease with which this category of disease gene can be identified has greatly increased through the availability of genome‐wide SNP genotyping microarrays and subsequently of exome sequencing. Although these methods have simplified the generation of experimental data, its analysis, particularly when disparate data types must be integrated, remains time consuming. Moreover, the huge volume of sequence variant data generated from next generation sequencing experiments opens up the possibility of using these data instead of microarray genotype data to identify disease loci. To allow these two types of data to be used in an integrated fashion, we have developed AgileVCFMapper, a program that performs both the mapping of disease loci by SNP genotyping and the analysis of potentially deleterious variants using exome sequence variant data, in a single step. This method does not require microarray SNP genotype data, although analysis with a combination of microarray and exome genotype data enables more precise delineation of disease loci, due to superior marker density and distribution. PMID:26037133

Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping

NASA Technical Reports Server (NTRS)

Royce, Thomas E.; Rozowsky, Joel S.; Bertone, Paul; Samanta, Manoj; Stolc, Viktor; Weissman, Sherman; Snyder, Michael; Gerstein, Mark

2005-01-01

Traditional microarrays use probes complementary to known genes to quantitate the differential gene expression between two or more conditions. Genomic tiling microarray experiments differ in that probes that span a genomic region at regular intervals are used to detect the presence or absence of transcription. This difference means the same sets of biases and the methods for addressing them are unlikely to be relevant to both types of experiment. We introduce the informatics challenges arising in the analysis of tiling microarray experiments as open problems to the scientific community and present initial approaches for the analysis of this nascent technology.

Emerging Use of Gene Expression Microarrays in Plant Physiology

DOE PAGES

Wullschleger, Stan D.; Difazio, Stephen P.

2003-01-01

Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology weremore » selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.« less

eQTL Mapping Using RNA-seq Data

PubMed Central

Hu, Yijuan

2012-01-01

As RNA-seq is replacing gene expression microarrays to assess genome-wide transcription abundance, gene expression Quantitative Trait Locus (eQTL) studies using RNA-seq have emerged. RNA-seq delivers two novel features that are important for eQTL studies. First, it provides information on allele-specific expression (ASE), which is not available from gene expression microarrays. Second, it generates unprecedentedly rich data to study RNA-isoform expression. In this paper, we review current methods for eQTL mapping using ASE and discuss some future directions. We also review existing works that use RNA-seq data to study RNA-isoform expression and we discuss the gaps between these works and isoform-specific eQTL mapping. PMID:23667399

Differential binding of calmodulin-related proteins to their targets revealed through high-density Arabidopsis protein microarrays

PubMed Central

Popescu, Sorina C.; Popescu, George V.; Bachan, Shawn; Zhang, Zimei; Seay, Montrell; Gerstein, Mark; Snyder, Michael; Dinesh-Kumar, S. P.

2007-01-01

Calmodulins (CaMs) are the most ubiquitous calcium sensors in eukaryotes. A number of CaM-binding proteins have been identified through classical methods, and many proteins have been predicted to bind CaMs based on their structural homology with known targets. However, multicellular organisms typically contain many CaM-like (CML) proteins, and a global identification of their targets and specificity of interaction is lacking. In an effort to develop a platform for large-scale analysis of proteins in plants we have developed a protein microarray and used it to study the global analysis of CaM/CML interactions. An Arabidopsis thaliana expression collection containing 1,133 ORFs was generated and used to produce proteins with an optimized medium-throughput plant-based expression system. Protein microarrays were prepared and screened with several CaMs/CMLs. A large number of previously known and novel CaM/CML targets were identified, including transcription factors, receptor and intracellular protein kinases, F-box proteins, RNA-binding proteins, and proteins of unknown function. Multiple CaM/CML proteins bound many binding partners, but the majority of targets were specific to one or a few CaMs/CMLs indicating that different CaM family members function through different targets. Based on our analyses, the emergent CaM/CML interactome is more extensive than previously predicted. Our results suggest that calcium functions through distinct CaM/CML proteins to regulate a wide range of targets and cellular activities. PMID:17360592

Global trends in satellite-based emergency mapping

USGS Publications Warehouse

Voigt, Stefan; Giulio-Tonolo, Fabio; Lyons, Josh; Kučera, Jan; Jones, Brenda; Schneiderhan, Tobias; Platzeck, Gabriel; Kaku, Kazuya; Hazarika, Manzul Kumar; Czaran, Lorant; Li, Suju; Pedersen, Wendi; James, Godstime Kadiri; Proy, Catherine; Muthike, Denis Macharia; Bequignon, Jerome; Guha-Sapir, Debarati

2016-01-01

Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.

Quantitative proteomic analysis in breast cancer.

PubMed

Tabchy, A; Hennessy, B T; Gonzalez-Angulo, A M; Bernstam, F M; Lu, Y; Mills, G B

2011-02-01

Much progress has recently been made in the genomic and transcriptional characterization of tumors. However, historically the characterization of cells at the protein level has suffered limitations in reproducibility, scalability and robustness. Recent technological advances have made it possible to accurately and reproducibly portray the global levels and active states of cellular proteins. Protein microarrays examine the native post-translational conformations of proteins including activated phosphorylated states, in a comprehensive high-throughput mode, and can map activated pathways and networks of proteins inside the cells. The reverse-phase protein microarray (RPPA) offers a unique opportunity to study signal transduction networks in small biological samples such as human biopsy material and can provide critical information for therapeutic decision-making and the monitoring of patients for targeted molecular medicine. By providing the key missing link to the story generated from genomic and gene expression characterization efforts, functional proteomics offer the promise of a comprehensive understanding of cancer. Several initial successes in breast cancer are showing that such information is clinically relevant. Copyright 2011 Prous Science, S.A.U. or its licensors. All rights reserved.

A fully traits-based approach to modeling global vegetation distribution.

PubMed

van Bodegom, Peter M; Douma, Jacob C; Verheijen, Lieneke M

2014-09-23

Dynamic Global Vegetation Models (DGVMs) are indispensable for our understanding of climate change impacts. The application of traits in DGVMs is increasingly refined. However, a comprehensive analysis of the direct impacts of trait variation on global vegetation distribution does not yet exist. Here, we present such analysis as proof of principle. We run regressions of trait observations for leaf mass per area, stem-specific density, and seed mass from a global database against multiple environmental drivers, making use of findings of global trait convergence. This analysis explained up to 52% of the global variation of traits. Global trait maps, generated by coupling the regression equations to gridded soil and climate maps, showed up to orders of magnitude variation in trait values. Subsequently, nine vegetation types were characterized by the trait combinations that they possess using Gaussian mixture density functions. The trait maps were input to these functions to determine global occurrence probabilities for each vegetation type. We prepared vegetation maps, assuming that the most probable (and thus, most suited) vegetation type at each location will be realized. This fully traits-based vegetation map predicted 42% of the observed vegetation distribution correctly. Our results indicate that a major proportion of the predictive ability of DGVMs with respect to vegetation distribution can be attained by three traits alone if traits like stem-specific density and seed mass are included. We envision that our traits-based approach, our observation-driven trait maps, and our vegetation maps may inspire a new generation of powerful traits-based DGVMs.

Global Mapping Project - Applications and Development of Version 2 Dataset

NASA Astrophysics Data System (ADS)

Ubukawa, T.; Nakamura, T.; Otsuka, T.; Iimura, T.; Kishimoto, N.; Nakaminami, K.; Motojima, Y.; Suga, M.; Yatabe, Y.; Koarai, M.; Okatani, T.

2012-07-01

The Global Mapping Project aims to develop basic geospatial information of the whole land area of the globe, named Global Map, through the cooperation of National Mapping Organizations (NMOs) around the world. The Global Map data can be a base of global geospatial infrastructure and is composed of eight layers: Boundaries, Drainage, Transportation, Population Centers, Elevation, Land Use, Land Cover and Vegetation. The Global Map Version 1 was released in 2008, and the Version 2 will be released in 2013 as the data are to be updated every five years. In 2009, the International Steering Committee for Global Mapping (ISCGM) adopted new Specifications to develop the Global Map Version 2 with a change of its format so that it is compatible with the international standards, namely ISO 19136 and ISO 19115. With the support of the secretariat of ISCGM, the project participating countries are accelerating their data development toward the completion of the global coverage in 2013, while some countries have already released their Global Map version 2 datasets since 2010. Global Map data are available from the Internet free of charge for non-commercial purposes, which can be used to predict, assess, prepare for and cope with global issues by combining with other spatial data. There are a lot of Global Map applications in various fields, and further utilization of Global Map is expected. This paper summarises the activities toward the development of the Global Map Version 2 as well as some examples of the Global Map applications in various fields.

An expression database for roots of the model legume Medicago truncatula under salt stress

PubMed Central

2009-01-01

Background Medicago truncatula is a model legume whose genome is currently being sequenced by an international consortium. Abiotic stresses such as salt stress limit plant growth and crop productivity, including those of legumes. We anticipate that studies on M. truncatula will shed light on other economically important legumes across the world. Here, we report the development of a database called MtED that contains gene expression profiles of the roots of M. truncatula based on time-course salt stress experiments using the Affymetrix Medicago GeneChip. Our hope is that MtED will provide information to assist in improving abiotic stress resistance in legumes. Description The results of our microarray experiment with roots of M. truncatula under 180 mM sodium chloride were deposited in the MtED database. Additionally, sequence and annotation information regarding microarray probe sets were included. MtED provides functional category analysis based on Gene and GeneBins Ontology, and other Web-based tools for querying and retrieving query results, browsing pathways and transcription factor families, showing metabolic maps, and comparing and visualizing expression profiles. Utilities like mapping probe sets to genome of M. truncatula and In-Silico PCR were implemented by BLAT software suite, which were also available through MtED database. Conclusion MtED was built in the PHP script language and as a MySQL relational database system on a Linux server. It has an integrated Web interface, which facilitates ready examination and interpretation of the results of microarray experiments. It is intended to help in selecting gene markers to improve abiotic stress resistance in legumes. MtED is available at http://bioinformatics.cau.edu.cn/MtED/. PMID:19906315

An expression database for roots of the model legume Medicago truncatula under salt stress.

PubMed

Li, Daofeng; Su, Zhen; Dong, Jiangli; Wang, Tao

2009-11-11

Medicago truncatula is a model legume whose genome is currently being sequenced by an international consortium. Abiotic stresses such as salt stress limit plant growth and crop productivity, including those of legumes. We anticipate that studies on M. truncatula will shed light on other economically important legumes across the world. Here, we report the development of a database called MtED that contains gene expression profiles of the roots of M. truncatula based on time-course salt stress experiments using the Affymetrix Medicago GeneChip. Our hope is that MtED will provide information to assist in improving abiotic stress resistance in legumes. The results of our microarray experiment with roots of M. truncatula under 180 mM sodium chloride were deposited in the MtED database. Additionally, sequence and annotation information regarding microarray probe sets were included. MtED provides functional category analysis based on Gene and GeneBins Ontology, and other Web-based tools for querying and retrieving query results, browsing pathways and transcription factor families, showing metabolic maps, and comparing and visualizing expression profiles. Utilities like mapping probe sets to genome of M. truncatula and In-Silico PCR were implemented by BLAT software suite, which were also available through MtED database. MtED was built in the PHP script language and as a MySQL relational database system on a Linux server. It has an integrated Web interface, which facilitates ready examination and interpretation of the results of microarray experiments. It is intended to help in selecting gene markers to improve abiotic stress resistance in legumes. MtED is available at http://bioinformatics.cau.edu.cn/MtED/.

Global trends in satellite-based emergency mapping.

PubMed

Voigt, Stefan; Giulio-Tonolo, Fabio; Lyons, Josh; Kučera, Jan; Jones, Brenda; Schneiderhan, Tobias; Platzeck, Gabriel; Kaku, Kazuya; Hazarika, Manzul Kumar; Czaran, Lorant; Li, Suju; Pedersen, Wendi; James, Godstime Kadiri; Proy, Catherine; Muthike, Denis Macharia; Bequignon, Jerome; Guha-Sapir, Debarati

2016-07-15

Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective. Copyright © 2016, American Association for the Advancement of Science.

Using Web Maps to Analyze the Construction of Global Scale Cognitive Maps

ERIC Educational Resources Information Center

Pingel, Thomas J.

2018-01-01

Game-based Web sites and applications are changing the ways in which students learn the world map. In this study, a Web map-based digital learning tool was used as a study aid for a university-level geography course in order to examine the way in which global scale cognitive maps are constructed. A network analysis revealed that clicks were…

DNA Microarray Analysis of the Expression Profile of Escherichia coli in Response to Treatment with 4,5-Dihydroxy-2-Cyclopenten-1-One

PubMed Central

Phadtare, Sangita; Kato, Ikunoshin; Inouye, Masayori

2002-01-01

We carried out DNA microarray-based global transcript profiling of Escherichia coli in response to 4,5-dihydroxy-2-cyclopenten-1-one to explore the manifestation of its antibacterial activity. We show that it has widespread effects in E. coli affecting genes encoding proteins involved in cell metabolism and membrane synthesis and functions. Genes belonging to the regulon involved in synthesis of Cys are upregulated. In addition, rpoS and RpoS-regulated genes responding to various stresses and a number of genes responding to oxidative stress are upregulated. PMID:12426362

Discovery and mapping of single feature polymorphisms in wheat using Affymetrix arrays

PubMed Central

Bernardo, Amy N; Bradbury, Peter J; Ma, Hongxiang; Hu, Shengwa; Bowden, Robert L; Buckler, Edward S; Bai, Guihua

2009-01-01

Background Wheat (Triticum aestivum L.) is a staple food crop worldwide. The wheat genome has not yet been sequenced due to its huge genome size (~17,000 Mb) and high levels of repetitive sequences; the whole genome sequence may not be expected in the near future. Available linkage maps have low marker density due to limitation in available markers; therefore new technologies that detect genome-wide polymorphisms are still needed to discover a large number of new markers for construction of high-resolution maps. A high-resolution map is a critical tool for gene isolation, molecular breeding and genomic research. Single feature polymorphism (SFP) is a new microarray-based type of marker that is detected by hybridization of DNA or cRNA to oligonucleotide probes. This study was conducted to explore the feasibility of using the Affymetrix GeneChip to discover and map SFPs in the large hexaploid wheat genome. Results Six wheat varieties of diverse origins (Ning 7840, Clark, Jagger, Encruzilhada, Chinese Spring, and Opata 85) were analyzed for significant probe by variety interactions and 396 probe sets with SFPs were identified. A subset of 164 unigenes was sequenced and 54% showed polymorphism within probes. Microarray analysis of 71 recombinant inbred lines from the cross Ning 7840/Clark identified 955 SFPs and 877 of them were mapped together with 269 simple sequence repeat markers. The SFPs were randomly distributed within a chromosome but were unevenly distributed among different genomes. The B genome had the most SFPs, and the D genome had the least. Map positions of a selected set of SFPs were validated by mapping single nucleotide polymorphism using SNaPshot and comparing with expressed sequence tags mapping data. Conclusion The Affymetrix array is a cost-effective platform for SFP discovery and SFP mapping in wheat. The new high-density map constructed in this study will be a useful tool for genetic and genomic research in wheat. PMID:19480702

Stallion sperm transcriptome comprises functionally coherent coding and regulatory RNAs as revealed by microarray analysis and RNA-seq.

PubMed

Das, Pranab J; McCarthy, Fiona; Vishnoi, Monika; Paria, Nandina; Gresham, Cathy; Li, Gang; Kachroo, Priyanka; Sudderth, A Kendrick; Teague, Sheila; Love, Charles C; Varner, Dickson D; Chowdhary, Bhanu P; Raudsepp, Terje

2013-01-01

Mature mammalian sperm contain a complex population of RNAs some of which might regulate spermatogenesis while others probably play a role in fertilization and early development. Due to this limited knowledge, the biological functions of sperm RNAs remain enigmatic. Here we report the first characterization of the global transcriptome of the sperm of fertile stallions. The findings improved understanding of the biological significance of sperm RNAs which in turn will allow the discovery of sperm-based biomarkers for stallion fertility. The stallion sperm transcriptome was interrogated by analyzing sperm and testes RNA on a 21,000-element equine whole-genome oligoarray and by RNA-seq. Microarray analysis revealed 6,761 transcripts in the sperm, of which 165 were sperm-enriched, and 155 were differentially expressed between the sperm and testes. Next, 70 million raw reads were generated by RNA-seq of which 50% could be aligned with the horse reference genome. A total of 19,257 sequence tags were mapped to all horse chromosomes and the mitochondrial genome. The highest density of mapped transcripts was in gene-rich ECA11, 12 and 13, and the lowest in gene-poor ECA9 and X; 7 gene transcripts originated from ECAY. Structural annotation aligned sperm transcripts with 4,504 known horse and/or human genes, rRNAs and 82 miRNAs, whereas 13,354 sequence tags remained anonymous. The data were aligned with selected equine gene models to identify additional exons and splice variants. Gene Ontology annotations showed that sperm transcripts were associated with molecular processes (chemoattractant-activated signal transduction, ion transport) and cellular components (membranes and vesicles) related to known sperm functions at fertilization, while some messenger and micro RNAs might be critical for early development. The findings suggest that the rich repertoire of coding and non-coding RNAs in stallion sperm is not a random remnant from spermatogenesis in testes but a selectively retained and functionally coherent collection of RNAs.

Stallion Sperm Transcriptome Comprises Functionally Coherent Coding and Regulatory RNAs as Revealed by Microarray Analysis and RNA-seq

PubMed Central

Das, Pranab J.; McCarthy, Fiona; Vishnoi, Monika; Paria, Nandina; Gresham, Cathy; Li, Gang; Kachroo, Priyanka; Sudderth, A. Kendrick; Teague, Sheila; Love, Charles C.; Varner, Dickson D.; Chowdhary, Bhanu P.; Raudsepp, Terje

2013-01-01

Mature mammalian sperm contain a complex population of RNAs some of which might regulate spermatogenesis while others probably play a role in fertilization and early development. Due to this limited knowledge, the biological functions of sperm RNAs remain enigmatic. Here we report the first characterization of the global transcriptome of the sperm of fertile stallions. The findings improved understanding of the biological significance of sperm RNAs which in turn will allow the discovery of sperm-based biomarkers for stallion fertility. The stallion sperm transcriptome was interrogated by analyzing sperm and testes RNA on a 21,000-element equine whole-genome oligoarray and by RNA-seq. Microarray analysis revealed 6,761 transcripts in the sperm, of which 165 were sperm-enriched, and 155 were differentially expressed between the sperm and testes. Next, 70 million raw reads were generated by RNA-seq of which 50% could be aligned with the horse reference genome. A total of 19,257 sequence tags were mapped to all horse chromosomes and the mitochondrial genome. The highest density of mapped transcripts was in gene-rich ECA11, 12 and 13, and the lowest in gene-poor ECA9 and X; 7 gene transcripts originated from ECAY. Structural annotation aligned sperm transcripts with 4,504 known horse and/or human genes, rRNAs and 82 miRNAs, whereas 13,354 sequence tags remained anonymous. The data were aligned with selected equine gene models to identify additional exons and splice variants. Gene Ontology annotations showed that sperm transcripts were associated with molecular processes (chemoattractant-activated signal transduction, ion transport) and cellular components (membranes and vesicles) related to known sperm functions at fertilization, while some messenger and micro RNAs might be critical for early development. The findings suggest that the rich repertoire of coding and non-coding RNAs in stallion sperm is not a random remnant from spermatogenesis in testes but a selectively retained and functionally coherent collection of RNAs. PMID:23409192

Mapping International Cancer Activities – Global Cancer Project Map Launch

Cancer.gov

CGH’s Dr. Sudha Sivaram, Dr. Makeda Williams, and Ms. Kalina Duncan have partnered with Drs. Ami Bhatt and Franklin Huang at Global Oncology, Inc. (GO) to develop the Global Cancer Project Map - a web-based tool designed to facilitate cancer research and control activity planning.

Development of DNA Microarrays for Metabolic Pathway and Bioprocess Monitoring

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

Gregory Stephanopoulos

Transcriptional profiling experiments utilizing DNA microarrays to study the intracellular accumulation of PHB in Synechocystis has proved difficult in large part because strains that show significant differences in PHB which would justify global analysis of gene expression have not been isolated.

Fish connectivity mapping intermediate data files and outputs

EPA Pesticide Factsheets

RLWrankedLists.tar.gz:These lists linked to various chemical treatment conditions serve as the target collection of Cmap. Probes of the entire microarray are sorted based on their log fold changes over control conditions. RLWsignatures2015.tar.gz: These signatures linked to various chemical treatment conditions serve as queries in Cmap.This dataset is associated with the following publication:Wang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles. BMC Genomics. BioMed Central Ltd, London, UK, 17(84): 1-20, (2016).

GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms.

PubMed

Jani, Saurin D; Argraves, Gary L; Barth, Jeremy L; Argraves, W Scott

2010-04-01

An important objective of DNA microarray-based gene expression experimentation is determining inter-relationships that exist between differentially expressed genes and biological processes, molecular functions, cellular components, signaling pathways, physiologic processes and diseases. Here we describe GeneMesh, a web-based program that facilitates analysis of DNA microarray gene expression data. GeneMesh relates genes in a query set to categories available in the Medical Subject Headings (MeSH) hierarchical index. The interface enables hypothesis driven relational analysis to a specific MeSH subcategory (e.g., Cardiovascular System, Genetic Processes, Immune System Diseases etc.) or unbiased relational analysis to broader MeSH categories (e.g., Anatomy, Biological Sciences, Disease etc.). Genes found associated with a given MeSH category are dynamically linked to facilitate tabular and graphical depiction of Entrez Gene information, Gene Ontology information, KEGG metabolic pathway diagrams and intermolecular interaction information. Expression intensity values of groups of genes that cluster in relation to a given MeSH category, gene ontology or pathway can be displayed as heat maps of Z score-normalized values. GeneMesh operates on gene expression data derived from a number of commercial microarray platforms including Affymetrix, Agilent and Illumina. GeneMesh is a versatile web-based tool for testing and developing new hypotheses through relating genes in a query set (e.g., differentially expressed genes from a DNA microarray experiment) to descriptors making up the hierarchical structure of the National Library of Medicine controlled vocabulary thesaurus, MeSH. The system further enhances the discovery process by providing links between sets of genes associated with a given MeSH category to a rich set of html linked tabular and graphic information including Entrez Gene summaries, gene ontologies, intermolecular interactions, overlays of genes onto KEGG pathway diagrams and heatmaps of expression intensity values. GeneMesh is freely available online at http://proteogenomics.musc.edu/genemesh/.

Comparisons of Robustness and Sensitivity between Cancer and Normal Cells by Microarray Data

PubMed Central

Chu, Liang-Hui; Chen, Bor-Sen

2008-01-01

Robustness is defined as the ability to uphold performance in face of perturbations and uncertainties, and sensitivity is a measure of the system deviations generated by perturbations to the system. While cancer appears as a robust but fragile system, few computational and quantitative evidences demonstrate robustness tradeoffs in cancer. Microarrays have been widely applied to decipher gene expression signatures in human cancer research, and quantification of global gene expression profiles facilitates precise prediction and modeling of cancer in systems biology. We provide several efficient computational methods based on system and control theory to compare robustness and sensitivity between cancer and normal cells by microarray data. Measurement of robustness and sensitivity by linear stochastic model is introduced in this study, which shows oscillations in feedback loops of p53 and demonstrates robustness tradeoffs that cancer is a robust system with some extreme fragilities. In addition, we measure sensitivity of gene expression to perturbations in other gene expression and kinetic parameters, discuss nonlinear effects in feedback loops of p53 and extend our method to robustness-based cancer drug design. PMID:19259409

Development of the first oligonucleotide microarray for global gene expression profiling in guinea pigs: defining the transcription signature of infectious diseases.

PubMed

Jain, Ruchi; Dey, Bappaditya; Tyagi, Anil K

2012-10-02

The Guinea pig (Cavia porcellus) is one of the most extensively used animal models to study infectious diseases. However, despite its tremendous contribution towards understanding the establishment, progression and control of a number of diseases in general and tuberculosis in particular, the lack of fully annotated guinea pig genome sequence as well as appropriate molecular reagents has severely hampered detailed genetic and immunological analysis in this animal model. By employing the cross-species hybridization technique, we have developed an oligonucleotide microarray with 44,000 features assembled from different mammalian species, which to the best of our knowledge is the first attempt to employ microarray to study the global gene expression profile in guinea pigs. To validate and demonstrate the merit of this microarray, we have studied, as an example, the expression profile of guinea pig lungs during the advanced phase of M. tuberculosis infection. A significant upregulation of 1344 genes and a marked down regulation of 1856 genes in the lungs identified a disease signature of pulmonary tuberculosis infection. We report the development of first comprehensive microarray for studying the global gene expression profile in guinea pigs and validation of its usefulness with tuberculosis as a case study. An important gap in the area of infectious diseases has been addressed and a valuable molecular tool is provided to optimally harness the potential of guinea pig model to develop better vaccines and therapies against human diseases.

Generation of real-time global ionospheric map based on the global GNSS stations with only a sparse distribution

NASA Astrophysics Data System (ADS)

Li, Zishen; Wang, Ningbo; Li, Min; Zhou, Kai; Yuan, Yunbin; Yuan, Hong

2017-04-01

The Earth's ionosphere is part of the atmosphere stretching from an altitude of about 50 km to more than 1000 km. When the Global Navigation Satellite System (GNSS) signal emitted from a satellite travels through the ionosphere before reaches a receiver on or near the Earth surface, the GNSS signal is significantly delayed by the ionosphere and this delay bas been considered as one of the major errors in the GNSS measurement. The real-time global ionospheric map calculated from the real-time data obtained by global stations is an essential method for mitigating the ionospheric delay for real-time positioning. The generation of an accurate global ionospheric map generally depends on the global stations with dense distribution; however, the number of global stations that can produce the real-time data is very limited at present, which results that the generation of global ionospheric map with a high accuracy is very different when only using the current stations with real-time data. In view of this, a new approach is proposed for calculating the real-time global ionospheric map only based on the current stations with real-time data. This new approach is developed on the basis of the post-processing and the one-day predicted global ionospheric map from our research group. The performance of the proposed approach is tested by the current global stations with the real-time data and the test results are also compared with the IGS-released final global ionospheric map products.

A Granular Self-Organizing Map for Clustering and Gene Selection in Microarray Data.

PubMed

Ray, Shubhra Sankar; Ganivada, Avatharam; Pal, Sankar K

2016-09-01

A new granular self-organizing map (GSOM) is developed by integrating the concept of a fuzzy rough set with the SOM. While training the GSOM, the weights of a winning neuron and the neighborhood neurons are updated through a modified learning procedure. The neighborhood is newly defined using the fuzzy rough sets. The clusters (granules) evolved by the GSOM are presented to a decision table as its decision classes. Based on the decision table, a method of gene selection is developed. The effectiveness of the GSOM is shown in both clustering samples and developing an unsupervised fuzzy rough feature selection (UFRFS) method for gene selection in microarray data. While the superior results of the GSOM, as compared with the related clustering methods, are provided in terms of β -index, DB-index, Dunn-index, and fuzzy rough entropy, the genes selected by the UFRFS are not only better in terms of classification accuracy and a feature evaluation index, but also statistically more significant than the related unsupervised methods. The C-codes of the GSOM and UFRFS are available online at http://avatharamg.webs.com/software-code.

A Comparative Study of the Ionospheric TEC Measurements Using Global Ionospheric Maps of GPS, TOPEX Radar and the Bent Model

NASA Technical Reports Server (NTRS)

Ho, C.; Wilson, B.; Mannucci, A.; Lindqwister, U.; Yuan, D.

1997-01-01

Global ionospheric mapping (GIM) is a new, emerging technique for determining global ionospheric TEC (total electron content) based on measurements from a worldwide network of Global Positioning System (GPS) receivers.

Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways

PubMed Central

2013-01-01

Background Analysis of global gene expression by DNA microarrays is widely used in experimental molecular biology. However, the complexity of such high-dimensional data sets makes it difficult to fully understand the underlying biological features present in the data. The aim of this study is to introduce a method for DNA microarray analysis that provides an intuitive interpretation of data through dimension reduction and pattern recognition. We present the first “Archetypal Analysis” of global gene expression. The analysis is based on microarray data from five integrated studies of Pseudomonas aeruginosa isolated from the airways of cystic fibrosis patients. Results Our analysis clustered samples into distinct groups with comprehensible characteristics since the archetypes representing the individual groups are closely related to samples present in the data set. Significant changes in gene expression between different groups identified adaptive changes of the bacteria residing in the cystic fibrosis lung. The analysis suggests a similar gene expression pattern between isolates with a high mutation rate (hypermutators) despite accumulation of different mutations for these isolates. This suggests positive selection in the cystic fibrosis lung environment, and changes in gene expression for these isolates are therefore most likely related to adaptation of the bacteria. Conclusions Archetypal analysis succeeded in identifying adaptive changes of P. aeruginosa. The combination of clustering and matrix factorization made it possible to reveal minor similarities among different groups of data, which other analytical methods failed to identify. We suggest that this analysis could be used to supplement current methods used to analyze DNA microarray data. PMID:24059747

A New Synthetic Global Biomass Carbon Map for the year 2010

NASA Astrophysics Data System (ADS)

Spawn, S.; Lark, T.; Gibbs, H.

2017-12-01

Satellite technologies have facilitated a recent boom in high resolution, large-scale biomass estimation and mapping. These data are the input into a wide range of global models and are becoming the gold standard for required national carbon (C) emissions reporting. Yet their geographical and/or thematic scope may exclude some or all parts of a given country or region. Most datasets tend to focus exclusively on forest biomass. Grasslands and shrublands generally store less C than forests but cover nearly twice as much global land area and may represent a significant portion of a given country's biomass C stock. To address these shortcomings, we set out to create synthetic, global above- and below-ground biomass maps that combine recently-released satellite based data of standing forest biomass with novel estimates for non-forest biomass stocks that are typically neglected. For forests we integrated existing publicly available regional, global and biome-specific biomass maps and modeled below ground biomass using empirical relationships described in the literature. For grasslands, we developed models for both above- and below-ground biomass based on NPP, mean annual temperature and precipitation to extrapolate field measurements across the globe. Shrubland biomass was extrapolated from existing regional biomass maps using environmental factors to generate the first global estimate of shrub biomass. Our new synthetic map of global biomass carbon circa 2010 represents an update to the IPCC Tier-1 Global Biomass Carbon Map for the Year 2000 (Ruesch and Gibbs, 2008) using the best data currently available. In the absence of a single seamless remotely sensed map of global biomass, our synthetic map provides the only globally-consistent source of comprehensive biomass C data and is valuable for land change analyses, carbon accounting, and emissions modeling.

Construction of a High-Density Genetic Map from RNA-Seq Data for an Arabidopsis Bay-0 × Shahdara RIL Population

PubMed Central

Serin, Elise A. R.; Snoek, L. B.; Nijveen, Harm; Willems, Leo A. J.; Jiménez-Gómez, Jose M.; Hilhorst, Henk W. M.; Ligterink, Wilco

2017-01-01

High-density genetic maps are essential for high resolution mapping of quantitative traits. Here, we present a new genetic map for an Arabidopsis Bayreuth × Shahdara recombinant inbred line (RIL) population, built on RNA-seq data. RNA-seq analysis on 160 RILs of this population identified 30,049 single-nucleotide polymorphisms (SNPs) covering the whole genome. Based on a 100-kbp window SNP binning method, 1059 bin-markers were identified, physically anchored on the genome. The total length of the RNA-seq genetic map spans 471.70 centimorgans (cM) with an average marker distance of 0.45 cM and a maximum marker distance of 4.81 cM. This high resolution genotyping revealed new recombination breakpoints in the population. To highlight the advantages of such high-density map, we compared it to two publicly available genetic maps for the same population, comprising 69 PCR-based markers and 497 gene expression markers derived from microarray data, respectively. In this study, we show that SNP markers can effectively be derived from RNA-seq data. The new RNA-seq map closes many existing gaps in marker coverage, saturating the previously available genetic maps. Quantitative trait locus (QTL) analysis for published phenotypes using the available genetic maps showed increased QTL mapping resolution and reduced QTL confidence interval using the RNA-seq map. The new high-density map is a valuable resource that facilitates the identification of candidate genes and map-based cloning approaches. PMID:29259624

BIOPHYSICAL PROPERTIES OF NUCLEIC ACIDS AT SURFACES RELEVANT TO MICROARRAY PERFORMANCE.

PubMed

Rao, Archana N; Grainger, David W

2014-04-01

Both clinical and analytical metrics produced by microarray-based assay technology have recognized problems in reproducibility, reliability and analytical sensitivity. These issues are often attributed to poor understanding and control of nucleic acid behaviors and properties at solid-liquid interfaces. Nucleic acid hybridization, central to DNA and RNA microarray formats, depends on the properties and behaviors of single strand (ss) nucleic acids (e.g., probe oligomeric DNA) bound to surfaces. ssDNA's persistence length, radius of gyration, electrostatics, conformations on different surfaces and under various assay conditions, its chain flexibility and curvature, charging effects in ionic solutions, and fluorescent labeling all influence its physical chemistry and hybridization under assay conditions. Nucleic acid (e.g., both RNA and DNA) target interactions with immobilized ssDNA strands are highly impacted by these biophysical states. Furthermore, the kinetics, thermodynamics, and enthalpic and entropic contributions to DNA hybridization reflect global probe/target structures and interaction dynamics. Here we review several biophysical issues relevant to oligomeric nucleic acid molecular behaviors at surfaces and their influences on duplex formation that influence microarray assay performance. Correlation of biophysical aspects of single and double-stranded nucleic acids with their complexes in bulk solution is common. Such analysis at surfaces is not commonly reported, despite its importance to microarray assays. We seek to provide further insight into nucleic acid-surface challenges facing microarray diagnostic formats that have hindered their clinical adoption and compromise their research quality and value as genomics tools.

BIOPHYSICAL PROPERTIES OF NUCLEIC ACIDS AT SURFACES RELEVANT TO MICROARRAY PERFORMANCE

PubMed Central

Rao, Archana N.; Grainger, David W.

2014-01-01

Both clinical and analytical metrics produced by microarray-based assay technology have recognized problems in reproducibility, reliability and analytical sensitivity. These issues are often attributed to poor understanding and control of nucleic acid behaviors and properties at solid-liquid interfaces. Nucleic acid hybridization, central to DNA and RNA microarray formats, depends on the properties and behaviors of single strand (ss) nucleic acids (e.g., probe oligomeric DNA) bound to surfaces. ssDNA’s persistence length, radius of gyration, electrostatics, conformations on different surfaces and under various assay conditions, its chain flexibility and curvature, charging effects in ionic solutions, and fluorescent labeling all influence its physical chemistry and hybridization under assay conditions. Nucleic acid (e.g., both RNA and DNA) target interactions with immobilized ssDNA strands are highly impacted by these biophysical states. Furthermore, the kinetics, thermodynamics, and enthalpic and entropic contributions to DNA hybridization reflect global probe/target structures and interaction dynamics. Here we review several biophysical issues relevant to oligomeric nucleic acid molecular behaviors at surfaces and their influences on duplex formation that influence microarray assay performance. Correlation of biophysical aspects of single and double-stranded nucleic acids with their complexes in bulk solution is common. Such analysis at surfaces is not commonly reported, despite its importance to microarray assays. We seek to provide further insight into nucleic acid-surface challenges facing microarray diagnostic formats that have hindered their clinical adoption and compromise their research quality and value as genomics tools. PMID:24765522

Augmenting Microarray Data with Literature-Based Knowledge to Enhance Gene Regulatory Network Inference

PubMed Central

Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C.

2014-01-01

Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology. PMID:24921649

Augmenting microarray data with literature-based knowledge to enhance gene regulatory network inference.

PubMed

Chen, Guocai; Cairelli, Michael J; Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C

2014-06-01

Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology.

Mars Global Geologic Mapping Progress and Suggested Geographic-Based Hierarchal Systems for Unit Grouping and Naming

NASA Technical Reports Server (NTRS)

Tanaka, K. L.; Dohm, J. M.; Irwin, R.; Kolb, E. J.; Skinner, J. A., Jr.; Hare, T. M.

2010-01-01

We are in the fourth year of a fiveyear effort to map the global geology of Mars at 1:20M scale using mainly Mars Global Surveyor, Mars Express, and Mars Odyssey image and altimetry datasets. Previously, we reported on details of project management, mapping datasets (local and regional), initial and anticipated mapping approaches, and tactics of map unit delineation and description [1-2]. Last year, we described mapping and unit delineation results thus far, a new unit identified in the northern plains, and remaining steps to complete the map [3].

Combat Stories Map: A Historical Repository and After Action Tool for Capturing, Storing, and Analyzing Georeferenced Individual Combat Narratives

DTIC Science & Technology

2016-06-01

of technology and near-global Internet accessibility, a web -based program incorporating interactive maps to record personal combat experiences does...not exist. The Combat Stories Map addresses this deficiency. The Combat Stories Map is a web -based Geographic Information System specifically designed...iv THIS PAGE INTENTIONALLY LEFT BLANK v ABSTRACT Despite the proliferation of technology and near-global Internet accessibility, a web

Analysis of Protein-DNA Interaction by Chromatin Immunoprecipitation and DNA Tiling Microarray (ChIP-on-chip).

PubMed

Gao, Hui; Zhao, Chunyan

2018-01-01

Chromatin immunoprecipitation (ChIP) has become the most effective and widely used tool to study the interactions between specific proteins or modified forms of proteins and a genomic DNA region. Combined with genome-wide profiling technologies, such as microarray hybridization (ChIP-on-chip) or massively parallel sequencing (ChIP-seq), ChIP could provide a genome-wide mapping of in vivo protein-DNA interactions in various organisms. Here, we describe a protocol of ChIP-on-chip that uses tiling microarray to obtain a genome-wide profiling of ChIPed DNA.

Replication dynamics of the yeast genome.

PubMed

Raghuraman, M K; Winzeler, E A; Collingwood, D; Hunt, S; Wodicka, L; Conway, A; Lockhart, D J; Davis, R W; Brewer, B J; Fangman, W L

2001-10-05

Oligonucleotide microarrays were used to map the detailed topography of chromosome replication in the budding yeast Saccharomyces cerevisiae. The times of replication of thousands of sites across the genome were determined by hybridizing replicated and unreplicated DNAs, isolated at different times in S phase, to the microarrays. Origin activations take place continuously throughout S phase but with most firings near mid-S phase. Rates of replication fork movement vary greatly from region to region in the genome. The two ends of each of the 16 chromosomes are highly correlated in their times of replication. This microarray approach is readily applicable to other organisms, including humans.

A pooling-based approach to mapping genetic variants associated with DNA methylation

PubMed Central

Kaplow, Irene M.; MacIsaac, Julia L.; Mah, Sarah M.; McEwen, Lisa M.; Kobor, Michael S.; Fraser, Hunter B.

2015-01-01

DNA methylation is an epigenetic modification that plays a key role in gene regulation. Previous studies have investigated its genetic basis by mapping genetic variants that are associated with DNA methylation at specific sites, but these have been limited to microarrays that cover <2% of the genome and cannot account for allele-specific methylation (ASM). Other studies have performed whole-genome bisulfite sequencing on a few individuals, but these lack statistical power to identify variants associated with DNA methylation. We present a novel approach in which bisulfite-treated DNA from many individuals is sequenced together in a single pool, resulting in a truly genome-wide map of DNA methylation. Compared to methods that do not account for ASM, our approach increases statistical power to detect associations while sharply reducing cost, effort, and experimental variability. As a proof of concept, we generated deep sequencing data from a pool of 60 human cell lines; we evaluated almost twice as many CpGs as the largest microarray studies and identified more than 2000 genetic variants associated with DNA methylation. We found that these variants are highly enriched for associations with chromatin accessibility and CTCF binding but are less likely to be associated with traits indirectly linked to DNA, such as gene expression and disease phenotypes. In summary, our approach allows genome-wide mapping of genetic variants associated with DNA methylation in any tissue of any species, without the need for individual-level genotype or methylation data. PMID:25910490

A pooling-based approach to mapping genetic variants associated with DNA methylation

DOE PAGES

Kaplow, Irene M.; MacIsaac, Julia L.; Mah, Sarah M.; ...

2015-04-24

DNA methylation is an epigenetic modification that plays a key role in gene regulation. Previous studies have investigated its genetic basis by mapping genetic variants that are associated with DNA methylation at specific sites, but these have been limited to microarrays that cover <2% of the genome and cannot account for allele-specific methylation (ASM). Other studies have performed whole-genome bisulfite sequencing on a few individuals, but these lack statistical power to identify variants associated with DNA methylation. We present a novel approach in which bisulfite-treated DNA from many individuals is sequenced together in a single pool, resulting in a trulymore » genome-wide map of DNA methylation. Compared to methods that do not account for ASM, our approach increases statistical power to detect associations while sharply reducing cost, effort, and experimental variability. As a proof of concept, we generated deep sequencing data from a pool of 60 human cell lines; we evaluated almost twice as many CpGs as the largest microarray studies and identified more than 2000 genetic variants associated with DNA methylation. Here we found that these variants are highly enriched for associations with chromatin accessibility and CTCF binding but are less likely to be associated with traits indirectly linked to DNA, such as gene expression and disease phenotypes. In summary, our approach allows genome-wide mapping of genetic variants associated with DNA methylation in any tissue of any species, without the need for individual-level genotype or methylation data.« less

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 compare two networks. The list of genes in a STARNET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at , and does not require user registration. PMID:19828039

Visualization for genomics: the Microbial Genome Viewer.

PubMed

Kerkhoven, Robert; van Enckevort, Frank H J; Boekhorst, Jos; Molenaar, Douwe; Siezen, Roland J

2004-07-22

A Web-based visualization tool, the Microbial Genome Viewer, is presented that allows the user to combine complex genomic data in a highly interactive way. This Web tool enables the interactive generation of chromosome wheels and linear genome maps from genome annotation data stored in a MySQL database. The generated images are in scalable vector graphics (SVG) format, which is suitable for creating high-quality scalable images and dynamic Web representations. Gene-related data such as transcriptome and time-course microarray experiments can be superimposed on the maps for visual inspection. The Microbial Genome Viewer 1.0 is freely available at http://www.cmbi.kun.nl/MGV

RNA-seq based transcriptomic map reveals new insights into mouse salivary gland development and maturation.

PubMed

Gluck, Christian; Min, Sangwon; Oyelakin, Akinsola; Smalley, Kirsten; Sinha, Satrajit; Romano, Rose-Anne

2016-11-16

Mouse models have served a valuable role in deciphering various facets of Salivary Gland (SG) biology, from normal developmental programs to diseased states. To facilitate such studies, gene expression profiling maps have been generated for various stages of SG organogenesis. However these prior studies fall short of capturing the transcriptional complexity due to the limited scope of gene-centric microarray-based technology. Compared to microarray, RNA-sequencing (RNA-seq) offers unbiased detection of novel transcripts, broader dynamic range and high specificity and sensitivity for detection of genes, transcripts, and differential gene expression. Although RNA-seq data, particularly under the auspices of the ENCODE project, have covered a large number of biological specimens, studies on the SG have been lacking. To better appreciate the wide spectrum of gene expression profiles, we isolated RNA from mouse submandibular salivary glands at different embryonic and adult stages. In parallel, we processed RNA-seq data for 24 organs and tissues obtained from the mouse ENCODE consortium and calculated the average gene expression values. To identify molecular players and pathways likely to be relevant for SG biology, we performed functional gene enrichment analysis, network construction and hierarchal clustering of the RNA-seq datasets obtained from different stages of SG development and maturation, and other mouse organs and tissues. Our bioinformatics-based data analysis not only reaffirmed known modulators of SG morphogenesis but revealed novel transcription factors and signaling pathways unique to mouse SG biology and function. Finally we demonstrated that the unique SG gene signature obtained from our mouse studies is also well conserved and can demarcate features of the human SG transcriptome that is different from other tissues. Our RNA-seq based Atlas has revealed a high-resolution cartographic view of the dynamic transcriptomic landscape of the mouse SG at various stages. These RNA-seq datasets will complement pre-existing microarray based datasets, including the Salivary Gland Molecular Anatomy Project by offering a broader systems-biology based perspective rather than the classical gene-centric view. Ultimately such resources will be valuable in providing a useful toolkit to better understand how the diverse cell population of the SG are organized and controlled during development and differentiation.

Mapping of transcription factor binding regions in mammalian cells by ChIP: Comparison of array- and sequencing-based technologies

PubMed Central

Euskirchen, Ghia M.; Rozowsky, Joel S.; Wei, Chia-Lin; Lee, Wah Heng; Zhang, Zhengdong D.; Hartman, Stephen; Emanuelsson, Olof; Stolc, Viktor; Weissman, Sherman; Gerstein, Mark B.; Ruan, Yijun; Snyder, Michael

2007-01-01

Recent progress in mapping transcription factor (TF) binding regions can largely be credited to chromatin immunoprecipitation (ChIP) technologies. We compared strategies for mapping TF binding regions in mammalian cells using two different ChIP schemes: ChIP with DNA microarray analysis (ChIP-chip) and ChIP with DNA sequencing (ChIP-PET). We first investigated parameters central to obtaining robust ChIP-chip data sets by analyzing STAT1 targets in the ENCODE regions of the human genome, and then compared ChIP-chip to ChIP-PET. We devised methods for scoring and comparing results among various tiling arrays and examined parameters such as DNA microarray format, oligonucleotide length, hybridization conditions, and the use of competitor Cot-1 DNA. The best performance was achieved with high-density oligonucleotide arrays, oligonucleotides ≥50 bases (b), the presence of competitor Cot-1 DNA and hybridizations conducted in microfluidics stations. When target identification was evaluated as a function of array number, 80%–86% of targets were identified with three or more arrays. Comparison of ChIP-chip with ChIP-PET revealed strong agreement for the highest ranked targets with less overlap for the low ranked targets. With advantages and disadvantages unique to each approach, we found that ChIP-chip and ChIP-PET are frequently complementary in their relative abilities to detect STAT1 targets for the lower ranked targets; each method detected validated targets that were missed by the other method. The most comprehensive list of STAT1 binding regions is obtained by merging results from ChIP-chip and ChIP-sequencing. Overall, this study provides information for robust identification, scoring, and validation of TF targets using ChIP-based technologies. PMID:17568005

Global Ionospheric Perturbations Monitored by the Worldwide GPS Network

NASA Technical Reports Server (NTRS)

Ho, C. M.; Mannucci, A. T.; Lindqwister, U. J.; Pi, X. Q.

1996-01-01

Based on the delays of these (Global Positioning System-GPS)signals, we have generated high resolution global ionospheric TEC (Total Electronic Changes) maps at 15-minute intervals. Using a differential method comparing storm time maps with quiet time maps, we find that the ionopshere during this time storm has increased significantly (the percentage change relative to quiet times is greater than 150 percent) ...These preliminary results (those mentioned above plus other in the paper)indicate that the differential maping method, which is based on GPS network measurements appears to be a useful tool for studying the global pattern and evolution process of the entire ionospheric perturbation.

A remark on copy number variation detection methods.

PubMed

Li, Shuo; Dou, Xialiang; Gao, Ruiqi; Ge, Xinzhou; Qian, Minping; Wan, Lin

2018-01-01

Copy number variations (CNVs) are gain and loss of DNA sequence of a genome. High throughput platforms such as microarrays and next generation sequencing technologies (NGS) have been applied for genome wide copy number losses. Although progress has been made in both approaches, the accuracy and consistency of CNV calling from the two platforms remain in dispute. In this study, we perform a deep analysis on copy number losses on 254 human DNA samples, which have both SNP microarray data and NGS data publicly available from Hapmap Project and 1000 Genomes Project respectively. We show that the copy number losses reported from Hapmap Project and 1000 Genome Project only have < 30% overlap, while these reports are required to have cross-platform (e.g. PCR, microarray and high-throughput sequencing) experimental supporting by their corresponding projects, even though state-of-art calling methods were employed. On the other hand, copy number losses are found directly from HapMap microarray data by an accurate algorithm, i.e. CNVhac, almost all of which have lower read mapping depth in NGS data; furthermore, 88% of which can be supported by the sequences with breakpoint in NGS data. Our results suggest the ability of microarray calling CNVs and the possible introduction of false negatives from the unessential requirement of the additional cross-platform supporting. The inconsistency of CNV reports from Hapmap Project and 1000 Genomes Project might result from the inadequate information containing in microarray data, the inconsistent detection criteria, or the filtration effect of cross-platform supporting. The statistical test on CNVs called from CNVhac show that the microarray data can offer reliable CNV reports, and majority of CNV candidates can be confirmed by raw sequences. Therefore, the CNV candidates given by a good caller could be highly reliable without cross-platform supporting, so additional experimental information should be applied in need instead of necessarily.

ELISA-BASE: An Integrated Bioinformatics Tool for Analyzing and Tracking ELISA Microarray Data

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

White, Amanda M.; Collett, James L.; Seurynck-Servoss, Shannon L.

ELISA-BASE is an open-source database for capturing, organizing and analyzing protein enzyme-linked immunosorbent assay (ELISA) microarray data. ELISA-BASE is an extension of the BioArray Soft-ware Environment (BASE) database system, which was developed for DNA microarrays. In order to make BASE suitable for protein microarray experiments, we developed several plugins for importing and analyzing quantitative ELISA microarray data. Most notably, our Protein Microarray Analysis Tool (ProMAT) for processing quantita-tive ELISA data is now available as a plugin to the database.

Cell cycle arrest and gene expression profiling of testis in mice exposed to fluoride.

PubMed

Su, Kai; Sun, Zilong; Niu, Ruiyan; Lei, Ying; Cheng, Jing; Wang, Jundong

2017-05-01

Exposure to fluoride results in low reproductive capacity; however, the mechanism underlying the impact of fluoride on male productive system still remains obscure. To assess the potential toxicity in testis of mice administrated with fluoride, global genome microarray and real-time PCR were performed to detect and identify the altered transcriptions. The results revealed that 763 differentially expressed genes were identified, including 330 up-regulated and 433 down-regulated genes, which were involved in spermatogenesis, apoptosis, DNA damage, DNA replication, and cell differentiation. Twelve differential expressed genes were selected to confirm the microarray results using real-time PCR, and the result kept the same tendency with that of microarray. Furthermore, compared with the control group, more apoptotic spermatogenic cells were observed in the fluoride group, and the spermatogonium were markedly increased in S phase and decreased in G2/M phase by fluoride. Our findings suggested global genome microarray provides an insight into the reproductive toxicity induced by fluoride, and several important biological clues for further investigations. © 2016 Wiley Periodicals, Inc. Environ Toxicol 32: 1558-1565, 2017. © 2016 Wiley Periodicals, Inc.

Volcanism on Io: Results from Global Geologic Mapping

NASA Technical Reports Server (NTRS)

Williams, David A.; Keszthelyi, L. P.; Crown, D. A.; Geissler, P. E.; Schenk, P. M.; Yff, Jessica; Jaeger, W. L.

2010-01-01

We have completed a new 1:15,000,000 global geologic map of Jupiter's volcanic moon, Io, based on a set of 1 km/pixel combined Galileo- Voyager mosaics produced by the U.S. Geological Survey. The map was produced over the last three years using ArcGIS(TM) software, and has undergone peer-review. Here we report some of the key results from our global mapping efforts, and how these results relate to questions regarding the volcano-tectonic evolution of Io.

Evolution of regional to global paddy rice mapping methods: A review

NASA Astrophysics Data System (ADS)

Dong, Jinwei; Xiao, Xiangming

2016-09-01

Paddy rice agriculture plays an important role in various environmental issues including food security, water use, climate change, and disease transmission. However, regional and global paddy rice maps are surprisingly scarce and sporadic despite numerous efforts in paddy rice mapping algorithms and applications. With the increasing need for regional to global paddy rice maps, this paper reviewed the existing paddy rice mapping methods from the literatures ranging from the 1980s to 2015. In particular, we illustrated the evolution of these paddy rice mapping efforts, looking specifically at the future trajectory of paddy rice mapping methodologies. The biophysical features and growth phases of paddy rice were analyzed first, and feature selections for paddy rice mapping were analyzed from spectral, polarimetric, temporal, spatial, and textural aspects. We sorted out paddy rice mapping algorithms into four categories: (1) Reflectance data and image statistic-based approaches, (2) vegetation index (VI) data and enhanced image statistic-based approaches, (3) VI or RADAR backscatter-based temporal analysis approaches, and (4) phenology-based approaches through remote sensing recognition of key growth phases. The phenology-based approaches using unique features of paddy rice (e.g., transplanting) for mapping have been increasingly used in paddy rice mapping. Current applications of these phenology-based approaches generally use coarse resolution MODIS data, which involves mixed pixel issues in Asia where smallholders comprise the majority of paddy rice agriculture. The free release of Landsat archive data and the launch of Landsat 8 and Sentinel-2 are providing unprecedented opportunities to map paddy rice in fragmented landscapes with higher spatial resolution. Based on the literature review, we discussed a series of issues for large scale operational paddy rice mapping.

Combining XCO2 Measurements Derived from SCIAMACHY and GOSAT for Potentially Generating Global CO2 Maps with High Spatiotemporal Resolution

PubMed Central

Wang, Tianxing; Shi, Jiancheng; Jing, Yingying; Zhao, Tianjie; Ji, Dabin; Xiong, Chuan

2014-01-01

Global warming induced by atmospheric CO2 has attracted increasing attention of researchers all over the world. Although space-based technology provides the ability to map atmospheric CO2 globally, the number of valid CO2 measurements is generally limited for certain instruments owing to the presence of clouds, which in turn constrain the studies of global CO2 sources and sinks. Thus, it is a potentially promising work to combine the currently available CO2 measurements. In this study, a strategy for fusing SCIAMACHY and GOSAT CO2 measurements is proposed by fully considering the CO2 global bias, averaging kernel, and spatiotemporal variations as well as the CO2 retrieval errors. Based on this method, a global CO2 map with certain UTC time can also be generated by employing the pattern of the CO2 daily cycle reflected by Carbon Tracker (CT) data. The results reveal that relative to GOSAT, the global spatial coverage of the combined CO2 map increased by 41.3% and 47.7% on a daily and monthly scale, respectively, and even higher when compared with that relative to SCIAMACHY. The findings in this paper prove the effectiveness of the combination method in supporting the generation of global full-coverage XCO2 maps with higher temporal and spatial sampling by jointly using these two space-based XCO2 datasets. PMID:25119468

Global gene expression analysis of peripheral blood mononuclear cells in rhesus monkey infants with CA16 infection-induced HFMD.

PubMed

Song, Jie; Hu, Yajie; Hu, Yunguang; Wang, Jingjing; Zhang, Xiaolong; Wang, Lichun; Guo, Lei; Wang, Yancui; Ning, Ruotong; Liao, Yun; Zhang, Ying; Zheng, Huiwen; Shi, Haijing; He, Zhanlong; Li, Qihan; Liu, Longding

2016-03-02

Coxsackievirus A16 (CA16) is a dominant pathogen that results in hand, foot, and mouth disease and causes outbreaks worldwide, particularly in the Asia-Pacific region. However, the underlying molecular mechanisms remain unclear. Our previous study has demonstrated that the basic CA16 pathogenic process was successfully mimicked in rhesus monkey infant. The present study focused on the global gene expression changes in peripheral blood mononuclear cells of rhesus monkey infants with hand, foot, and mouth disease induced by CA16 infection at different time points. Genome-wide expression analysis was performed with Agilent whole-genome microarrays and established bioinformatics tools. Nine hundred and forty-eight significant differentially expressed genes that were associated with 5 gene ontology categories, including cell communication, cell cycle, immune system process, regulation of transcription and metabolic process were identified. Subsequently, the mapping of genes related to the immune system process by PANTHER pathway analysis revealed the predominance of inflammation mediated by chemokine and cytokine signaling pathways and the interleukin signaling pathway. Ultimately, co-expressed genes and their networks were analyzed. The results revealed the gene expression profile of the immune system in response to CA16 in rhesus monkey infants and suggested that such an immune response was generated as a result of the positive mobilization of the immune system. This initial microarray study will provide insights into the molecular mechanism of CA16 infection and will facilitate the identification of biomarkers for the evaluation of vaccines against this virus. Copyright © 2016 Elsevier B.V. All rights reserved.

Global Land Survey Impervious Mapping Project Web Site

NASA Technical Reports Server (NTRS)

DeColstoun, Eric Brown; Phillips, Jacqueline

2014-01-01

The Global Land Survey Impervious Mapping Project (GLS-IMP) aims to produce the first global maps of impervious cover at the 30m spatial resolution of Landsat. The project uses Global Land Survey (GLS) Landsat data as its base but incorporates training data generated from very high resolution commercial satellite data and using a Hierarchical segmentation program called Hseg. The web site contains general project information, a high level description of the science, examples of input and output data, as well as links to other relevant projects.

The Choice of the Filtering Method in Microarrays Affects the Inference Regarding Dosage Compensation of the Active X-Chromosome

PubMed Central

Zeller, Tanja; Wild, Philipp S.; Truong, Vinh; Trégouët, David-Alexandre; Munzel, Thomas; Ziegler, Andreas; Cambien, François; Blankenberg, Stefan; Tiret, Laurence

2011-01-01

Background The hypothesis of dosage compensation of genes of the X chromosome, supported by previous microarray studies, was recently challenged by RNA-sequencing data. It was suggested that microarray studies were biased toward an over-estimation of X-linked expression levels as a consequence of the filtering of genes below the detection threshold of microarrays. Methodology/Principal Findings To investigate this hypothesis, we used microarray expression data from circulating monocytes in 1,467 individuals. In total, 25,349 and 1,156 probes were unambiguously assigned to autosomes and the X chromosome, respectively. Globally, there was a clear shift of X-linked expressions toward lower levels than autosomes. We compared the ratio of expression levels of X-linked to autosomal transcripts (X∶AA) using two different filtering methods: 1. gene expressions were filtered out using a detection threshold irrespective of gene chromosomal location (the standard method in microarrays); 2. equal proportions of genes were filtered out separately on the X and on autosomes. For a wide range of filtering proportions, the X∶AA ratio estimated with the first method was not significantly different from 1, the value expected if dosage compensation was achieved, whereas it was significantly lower than 1 with the second method, leading to the rejection of the hypothesis of dosage compensation. We further showed in simulated data that the choice of the most appropriate method was dependent on biological assumptions regarding the proportion of actively expressed genes on the X chromosome comparative to the autosomes and the extent of dosage compensation. Conclusion/Significance This study shows that the method used for filtering out lowly expressed genes in microarrays may have a major impact according to the hypothesis investigated. The hypothesis of dosage compensation of X-linked genes cannot be firmly accepted or rejected using microarray-based data. PMID:21912656

Quantitative comparison of microarray experiments with published leukemia related gene expression signatures.

PubMed

Klein, Hans-Ulrich; Ruckert, Christian; Kohlmann, Alexander; Bullinger, Lars; Thiede, Christian; Haferlach, Torsten; Dugas, Martin

2009-12-15

Multiple gene expression signatures derived from microarray experiments have been published in the field of leukemia research. A comparison of these signatures with results from new experiments is useful for verification as well as for interpretation of the results obtained. Currently, the percentage of overlapping genes is frequently used to compare published gene signatures against a signature derived from a new experiment. However, it has been shown that the percentage of overlapping genes is of limited use for comparing two experiments due to the variability of gene signatures caused by different array platforms or assay-specific influencing parameters. Here, we present a robust approach for a systematic and quantitative comparison of published gene expression signatures with an exemplary query dataset. A database storing 138 leukemia-related published gene signatures was designed. Each gene signature was manually annotated with terms according to a leukemia-specific taxonomy. Two analysis steps are implemented to compare a new microarray dataset with the results from previous experiments stored and curated in the database. First, the global test method is applied to assess gene signatures and to constitute a ranking among them. In a subsequent analysis step, the focus is shifted from single gene signatures to chromosomal aberrations or molecular mutations as modeled in the taxonomy. Potentially interesting disease characteristics are detected based on the ranking of gene signatures associated with these aberrations stored in the database. Two example analyses are presented. An implementation of the approach is freely available as web-based application. The presented approach helps researchers to systematically integrate the knowledge derived from numerous microarray experiments into the analysis of a new dataset. By means of example leukemia datasets we demonstrate that this approach detects related experiments as well as related molecular mutations and may help to interpret new microarray data.

Epigenomics

MedlinePlus

... Sheets A Brief Guide to Genomics About NHGRI Research About the International HapMap Project Biological Pathways Chromosome Abnormalities Chromosomes Cloning Comparative Genomics DNA Microarray Technology DNA Sequencing Deoxyribonucleic Acid ( ...

Cloning

MedlinePlus

... Sheets A Brief Guide to Genomics About NHGRI Research About the International HapMap Project Biological Pathways Chromosome Abnormalities Chromosomes Cloning Comparative Genomics DNA Microarray Technology DNA Sequencing Deoxyribonucleic Acid ( ...

Chromosomes

MedlinePlus

... Sheets A Brief Guide to Genomics About NHGRI Research About the International HapMap Project Biological Pathways Chromosome Abnormalities Chromosomes Cloning Comparative Genomics DNA Microarray Technology DNA Sequencing Deoxyribonucleic Acid ( ...

Transcriptome

MedlinePlus

... Sheets A Brief Guide to Genomics About NHGRI Research About the International HapMap Project Biological Pathways Chromosome Abnormalities Chromosomes Cloning Comparative Genomics DNA Microarray Technology DNA Sequencing Deoxyribonucleic Acid ( ...

Biological Pathways

MedlinePlus

... Sheets A Brief Guide to Genomics About NHGRI Research About the International HapMap Project Biological Pathways Chromosome Abnormalities Chromosomes Cloning Comparative Genomics DNA Microarray Technology DNA Sequencing Deoxyribonucleic Acid ( ...

Release of (and lessons learned from mining) a pioneering large toxicogenomics database.

PubMed

Sandhu, Komal S; Veeramachaneni, Vamsi; Yao, Xiang; Nie, Alex; Lord, Peter; Amaratunga, Dhammika; McMillian, Michael K; Verheyen, Geert R

2015-07-01

We release the Janssen Toxicogenomics database. This rat liver gene-expression database was generated using Codelink microarrays, and has been used over the past years within Janssen to derive signatures for multiple end points and to classify proprietary compounds. The release consists of gene-expression responses to 124 compounds, selected to give a broad coverage of liver-active compounds. A selection of the compounds were also analyzed on Affymetrix microarrays. The release includes results of an in-house reannotation pipeline to Entrez gene annotations, to classify probes into different confidence classes. High confidence unambiguously annotated probes were used to create gene-level data which served as starting point for cross-platform comparisons. Connectivity map-based similarity methods show excellent agreement between Codelink and Affymetrix runs of the same samples. We also compared our dataset with the Japanese Toxicogenomics Project and observed reasonable agreement, especially for compounds with stronger gene signatures. We describe an R-package containing the gene-level data and show how it can be used for expression-based similarity searches. Comparing the same biological samples run on the Affymetrix and the Codelink platform, good correspondence is observed using connectivity mapping approaches. As expected, this correspondence is smaller when the data are compared with an independent dataset such as TG-GATE. We hope that this collection of gene-expression profiles will be incorporated in toxicogenomics pipelines of users.

BμG@Sbase—a microbial gene expression and comparative genomic database

PubMed Central

Witney, Adam A.; Waldron, Denise E.; Brooks, Lucy A.; Tyler, Richard H.; Withers, Michael; Stoker, Neil G.; Wren, Brendan W.; Butcher, Philip D.; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future. PMID:21948792

BμG@Sbase--a microbial gene expression and comparative genomic database.

PubMed

Witney, Adam A; Waldron, Denise E; Brooks, Lucy A; Tyler, Richard H; Withers, Michael; Stoker, Neil G; Wren, Brendan W; Butcher, Philip D; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future.

Development and Use of Integrated Microarray-Based Genomic Technologies for Assessing Microbial Community Composition and Dynamics

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

Zhou, J.; Wu, L.; Gentry, T.

2006-04-05

To effectively monitor microbial populations involved in various important processes, a 50-mer-based oligonucleotide microarray was developed based on known genes and pathways involved in: biodegradation, metal resistance and reduction, denitrification, nitrification, nitrogen fixation, methane oxidation, methanogenesis, carbon polymer decomposition, and sulfate reduction. This array contains approximately 2000 unique and group-specific probes with <85% similarity to their non-target sequences. Based on artificial probes, our results showed that at hybridization conditions of 50 C and 50% formamide, the 50-mer microarray hybridization can differentiate sequences having <88% similarity. Specificity tests with representative pure cultures indicated that the designed probes on the arrays appearedmore » to be specific to their corresponding target genes. Detection limits were about 5-10ng genomic DNA in the absence of background DNA, and 50-100ng ({approx}1.3{sup o} 10{sup 7} cells) in the presence background DNA. Strong linear relationships between signal intensity and target DNA and RNA concentration were observed (r{sup 2} = 0.95-0.99). Application of this microarray to naphthalene-amended enrichments and soil microcosms demonstrated that composition of the microflora varied depending on incubation conditions. While the naphthalene-degrading genes from Rhodococcus-type microorganisms were dominant in enrichments, the genes involved in naphthalene degradation from Gram-negative microorganisms such as Ralstonia, Comamonas, and Burkholderia were most abundant in the soil microcosms (as well as those for polyaromatic hydrocarbon and nitrotoluene degradation). Although naphthalene degradation is widely known and studied in Pseudomonas, Pseudomonas genes were not detected in either system. Real-time PCR analysis of 4 representative genes was consistent with microarray-based quantification (r{sup 2} = 0.95). Currently, we are also applying this microarray to the study of several different microbial communities and processes at the NABIR-FRC in Oak Ridge, TN. One project involves the monitoring of the development and dynamics of the microbial community of a fluidized bed reactor (FBR) used for reducing nitrate and the other project monitors microbial community responses to stimulation of uranium reducing populations via ethanol donor additions in situ and in a model system. Additionally, we are developing novel strategies for increasing microarray hybridization sensitivity. Finally, great improvements to our methods of probe design were made by the development of a new computer program, CommOligo. CommOligo designs unique and group-specific oligo probes for whole-genomes, metagenomes, and groups of environmental sequences and uses a new global alignment algorithm to design single or multiple probes for each gene or group. We are now using this program to design a more comprehensive functional gene array for environmental studies. Overall, our results indicate that the 50mer-based microarray technology has potential as a specific and quantitative tool to reveal the composition of microbial communities and their dynamics important to processes within contaminated environments.« less

An atlas of ShakeMaps for selected global earthquakes

USGS Publications Warehouse

Allen, Trevor I.; Wald, David J.; Hotovec, Alicia J.; Lin, Kuo-Wan; Earle, Paul S.; Marano, Kristin D.

2008-01-01

An atlas of maps of peak ground motions and intensity 'ShakeMaps' has been developed for almost 5,000 recent and historical global earthquakes. These maps are produced using established ShakeMap methodology (Wald and others, 1999c; Wald and others, 2005) and constraints from macroseismic intensity data, instrumental ground motions, regional topographically-based site amplifications, and published earthquake-rupture models. Applying the ShakeMap methodology allows a consistent approach to combine point observations with ground-motion predictions to produce descriptions of peak ground motions and intensity for each event. We also calculate an estimated ground-motion uncertainty grid for each earthquake. The Atlas of ShakeMaps provides a consistent and quantitative description of the distribution and intensity of shaking for recent global earthquakes (1973-2007) as well as selected historic events. As such, the Atlas was developed specifically for calibrating global earthquake loss estimation methodologies to be used in the U.S. Geological Survey Prompt Assessment of Global Earthquakes for Response (PAGER) Project. PAGER will employ these loss models to rapidly estimate the impact of global earthquakes as part of the USGS National Earthquake Information Center's earthquake-response protocol. The development of the Atlas of ShakeMaps has also led to several key improvements to the Global ShakeMap system. The key upgrades include: addition of uncertainties in the ground motion mapping, introduction of modern ground-motion prediction equations, improved estimates of global seismic-site conditions (VS30), and improved definition of stable continental region polygons. Finally, we have merged all of the ShakeMaps in the Atlas to provide a global perspective of earthquake ground shaking for the past 35 years, allowing comparison with probabilistic hazard maps. The online Atlas and supporting databases can be found at http://earthquake.usgs.gov/eqcenter/shakemap/atlas.php/.

High-throughput microarray mapping of cell wall polymers in roots and tubers during the viscosity-reducing process.

PubMed

Huang, Yuhong; Willats, William G; Lange, Lene; Jin, Yanling; Fang, Yang; Salmeán, Armando A; Pedersen, Henriette L; Busk, Peter Kamp; Zhao, Hai

2016-01-01

Viscosity reduction has a great impact on the efficiency of ethanol production when using roots and tubers as feedstock. Plant cell wall-degrading enzymes have been successfully applied to overcome the challenges posed by high viscosity. However, the changes in cell wall polymers during the viscosity-reducing process are poorly characterized. Comprehensive microarray polymer profiling, which is a high-throughput microarray, was used for the first time to map changes in the cell wall polymers of sweet potato (Ipomoea batatas), cassava (Manihot esculenta), and Canna edulis Ker. over the entire viscosity-reducing process. The results indicated that the composition of cell wall polymers among these three roots and tubers was markedly different. The gel-like matrix and glycoprotein network in the C. edulis Ker. cell wall caused difficulty in viscosity reduction. The obvious viscosity reduction of the sweet potato and the cassava was attributed to the degradation of homogalacturonan and the released 1,4-β-d-galactan and 1,5-α-l-arabinan. © 2015 International Union of Biochemistry and Molecular Biology, Inc.

Geologic map of Mars

USGS Publications Warehouse

Tanaka, Kenneth L.; Skinner, James A.; Dohm, James M.; Irwin, Rossman P.; Kolb, Eric J.; Fortezzo, Corey M.; Platz, Thomas; Michael, Gregory G.; Hare, Trent M.

2014-01-01

This global geologic map of Mars, which records the distribution of geologic units and landforms on the planet's surface through time, is based on unprecedented variety, quality, and quantity of remotely sensed data acquired since the Viking Orbiters. These data have provided morphologic, topographic, spectral, thermophysical, radar sounding, and other observations for integration, analysis, and interpretation in support of geologic mapping. In particular, the precise topographic mapping now available has enabled consistent morphologic portrayal of the surface for global mapping (whereas previously used visual-range image bases were less effective, because they combined morphologic and albedo information and, locally, atmospheric haze). Also, thermal infrared image bases used for this map tended to be less affected by atmospheric haze and thus are reliable for analysis of surface morphology and texture at even higher resolution than the topographic products.

sscMap: an extensible Java application for connecting small-molecule drugs using gene-expression signatures.

PubMed

Zhang, Shu-Dong; Gant, Timothy W

2009-07-31

Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMap.

Construction of a cDNA microarray derived from the ascidian Ciona intestinalis.

PubMed

Azumi, Kaoru; Takahashi, Hiroki; Miki, Yasufumi; Fujie, Manabu; Usami, Takeshi; Ishikawa, Hisayoshi; Kitayama, Atsusi; Satou, Yutaka; Ueno, Naoto; Satoh, Nori

2003-10-01

A cDNA microarray was constructed from a basal chordate, the ascidian Ciona intestinalis. The draft genome of Ciona has been read and inferred to contain approximately 16,000 protein-coding genes, and cDNAs for transcripts of 13,464 genes have been characterized and compiled as the "Ciona intestinalis Gene Collection Release I". In the present study, we constructed a cDNA microarray of these 13,464 Ciona genes. A preliminary experiment with Cy3- and Cy5-labeled probes showed extensive differential gene expression between fertilized eggs and larvae. In addition, there was a good correlation between results obtained by the present microarray analysis and those from previous EST analyses. This first microarray of a large collection of Ciona intestinalis cDNA clones should facilitate the analysis of global gene expression and gene networks during the embryogenesis of basal chordates.

Genetic Mapping and Exome Sequencing Identify Variants Associated with Five Novel Diseases

PubMed Central

Puffenberger, Erik G.; Jinks, Robert N.; Sougnez, Carrie; Cibulskis, Kristian; Willert, Rebecca A.; Achilly, Nathan P.; Cassidy, Ryan P.; Fiorentini, Christopher J.; Heiken, Kory F.; Lawrence, Johnny J.; Mahoney, Molly H.; Miller, Christopher J.; Nair, Devika T.; Politi, Kristin A.; Worcester, Kimberly N.; Setton, Roni A.; DiPiazza, Rosa; Sherman, Eric A.; Eastman, James T.; Francklyn, Christopher; Robey-Bond, Susan; Rider, Nicholas L.; Gabriel, Stacey; Morton, D. Holmes; Strauss, Kevin A.

2012-01-01

The Clinic for Special Children (CSC) has integrated biochemical and molecular methods into a rural pediatric practice serving Old Order Amish and Mennonite (Plain) children. Among the Plain people, we have used single nucleotide polymorphism (SNP) microarrays to genetically map recessive disorders to large autozygous haplotype blocks (mean = 4.4 Mb) that contain many genes (mean = 79). For some, uninformative mapping or large gene lists preclude disease-gene identification by Sanger sequencing. Seven such conditions were selected for exome sequencing at the Broad Institute; all had been previously mapped at the CSC using low density SNP microarrays coupled with autozygosity and linkage analyses. Using between 1 and 5 patient samples per disorder, we identified sequence variants in the known disease-causing genes SLC6A3 and FLVCR1, and present evidence to strongly support the pathogenicity of variants identified in TUBGCP6, BRAT1, SNIP1, CRADD, and HARS. Our results reveal the power of coupling new genotyping technologies to population-specific genetic knowledge and robust clinical data. PMID:22279524

Land cover mapping of North and Central America—Global Land Cover 2000

USGS Publications Warehouse

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

Mapping global cropland and field size.

PubMed

Fritz, Steffen; See, Linda; McCallum, Ian; You, Liangzhi; Bun, Andriy; Moltchanova, Elena; Duerauer, Martina; Albrecht, Fransizka; Schill, Christian; Perger, Christoph; Havlik, Petr; Mosnier, Aline; Thornton, Philip; Wood-Sichra, Ulrike; Herrero, Mario; Becker-Reshef, Inbal; Justice, Chris; Hansen, Matthew; Gong, Peng; Abdel Aziz, Sheta; Cipriani, Anna; Cumani, Renato; Cecchi, Giuliano; Conchedda, Giulia; Ferreira, Stefanus; Gomez, Adriana; Haffani, Myriam; Kayitakire, Francois; Malanding, Jaiteh; Mueller, Rick; Newby, Terence; Nonguierma, Andre; Olusegun, Adeaga; Ortner, Simone; Rajak, D Ram; Rocha, Jansle; Schepaschenko, Dmitry; Schepaschenko, Maria; Terekhov, Alexey; Tiangwa, Alex; Vancutsem, Christelle; Vintrou, Elodie; Wenbin, Wu; van der Velde, Marijn; Dunwoody, Antonia; Kraxner, Florian; Obersteiner, Michael

2015-05-01

A new 1 km global IIASA-IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo-Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA-IFPRI cropland product has been validated using very high-resolution satellite imagery via Geo-Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo-Wiki. The first ever global field size map was produced at the same resolution as the IIASA-IFPRI cropland map based on interpolation of field size data collected via a Geo-Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website. © 2015 John Wiley & Sons Ltd.

Design of microarray experiments for genetical genomics studies.

PubMed

Bueno Filho, Júlio S S; Gilmour, Steven G; Rosa, Guilherme J M

2006-10-01

Microarray experiments have been used recently in genetical genomics studies, as an additional tool to understand the genetic mechanisms governing variation in complex traits, such as for estimating heritabilities of mRNA transcript abundances, for mapping expression quantitative trait loci, and for inferring regulatory networks controlling gene expression. Several articles on the design of microarray experiments discuss situations in which treatment effects are assumed fixed and without any structure. In the case of two-color microarray platforms, several authors have studied reference and circular designs. Here, we discuss the optimal design of microarray experiments whose goals refer to specific genetic questions. Some examples are used to illustrate the choice of a design for comparing fixed, structured treatments, such as genotypic groups. Experiments targeting single genes or chromosomic regions (such as with transgene research) or multiple epistatic loci (such as within a selective phenotyping context) are discussed. In addition, microarray experiments in which treatments refer to families or to subjects (within family structures or complex pedigrees) are presented. In these cases treatments are more appropriately considered to be random effects, with specific covariance structures, in which the genetic goals relate to the estimation of genetic variances and the heritability of transcriptional abundances.

Current trends in satellite based emergency mapping - the need for harmonisation

NASA Astrophysics Data System (ADS)

Voigt, Stefan

2013-04-01

During the past years, the availability and use of satellite image data to support disaster management and humanitarian relief organisations has largely increased. The automation and data processing techniques are greatly improving as well as the capacity in accessing and processing satellite imagery in getting better globally. More and more global activities via the internet and through global organisations like the United Nations or the International Charter Space and Major Disaster engage in the topic, while at the same time, more and more national or local centres engage rapid mapping operations and activities. In order to make even more effective use of this very positive increase of capacity, for the sake of operational provision of analysis results, for fast validation of satellite derived damage assessments, for better cooperation in the joint inter agency generation of rapid mapping products and for general scientific use, rapid mapping results in general need to be better harmonized, if not even standardized. In this presentation, experiences from various years of rapid mapping gained by the DLR Center for satellite based Crisis Information (ZKI) within the context of the national activities, the International Charter Space and Major Disasters, GMES/Copernicus etc. are reported. Furthermore, an overview on how automation, quality assurance and optimization can be achieved through standard operation procedures within a rapid mapping workflow is given. Building on this long term rapid mapping experience, and building on the DLR initiative to set in pace an "International Working Group on Satellite Based Emergency Mapping" current trends in rapid mapping are discussed and thoughts on how the sharing of rapid mapping information can be optimized by harmonizing analysis results and data structures are presented. Such an harmonization of analysis procedures, nomenclatures and representations of data as well as meta data are the basis to better cooperate within the global rapid mapping community throughout local/national, regional/supranational and global scales

A method of recovering the initial vectors of globally coupled map lattices based on symbolic dynamics

NASA Astrophysics Data System (ADS)

Sun, Li-Sha; Kang, Xiao-Yun; Zhang, Qiong; Lin, Lan-Xin

2011-12-01

Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices (CMLs). It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence (CD). Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to-noise ratios (SNRs) are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors using symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems.

Translating standards into practice - one Semantic Web API for Gene Expression.

PubMed

Deus, Helena F; Prud'hommeaux, Eric; Miller, Michael; Zhao, Jun; Malone, James; Adamusiak, Tomasz; McCusker, Jim; Das, Sudeshna; Rocca Serra, Philippe; Fox, Ronan; Marshall, M Scott

2012-08-01

Sharing and describing experimental results unambiguously with sufficient detail to enable replication of results is a fundamental tenet of scientific research. In today's cluttered world of "-omics" sciences, data standards and standardized use of terminologies and ontologies for biomedical informatics play an important role in reporting high-throughput experiment results in formats that can be interpreted by both researchers and analytical tools. Increasing adoption of Semantic Web and Linked Data technologies for the integration of heterogeneous and distributed health care and life sciences (HCLSs) datasets has made the reuse of standards even more pressing; dynamic semantic query federation can be used for integrative bioinformatics when ontologies and identifiers are reused across data instances. We present here a methodology to integrate the results and experimental context of three different representations of microarray-based transcriptomic experiments: the Gene Expression Atlas, the W3C BioRDF task force approach to reporting Provenance of Microarray Experiments, and the HSCI blood genomics project. Our approach does not attempt to improve the expressivity of existing standards for genomics but, instead, to enable integration of existing datasets published from microarray-based transcriptomic experiments. SPARQL Construct is used to create a posteriori mappings of concepts and properties and linking rules that match entities based on query constraints. We discuss how our integrative approach can encourage reuse of the Experimental Factor Ontology (EFO) and the Ontology for Biomedical Investigations (OBIs) for the reporting of experimental context and results of gene expression studies. Copyright © 2012 Elsevier Inc. All rights reserved.

Global maps of the magnetic thickness and magnetization of the Earth's lithosphere

NASA Astrophysics Data System (ADS)

Vervelidou, Foteini; Thébault, Erwan

2015-10-01

We have constructed global maps of the large-scale magnetic thickness and magnetization of Earth's lithosphere. Deriving such large-scale maps based on lithospheric magnetic field measurements faces the challenge of the masking effect of the core field. In this study, the maps were obtained through analyses in the spectral domain by means of a new regional spatial power spectrum based on the Revised Spherical Cap Harmonic Analysis (R-SCHA) formalism. A series of regional spectral analyses were conducted covering the entire Earth. The R-SCHA surface power spectrum for each region was estimated using the NGDC-720 spherical harmonic (SH) model of the lithospheric magnetic field, which is based on satellite, aeromagnetic, and marine measurements. These observational regional spectra were fitted to a recently proposed statistical expression of the power spectrum of Earth's lithospheric magnetic field, whose free parameters include the thickness and magnetization of the magnetic sources. The resulting global magnetic thickness map is compared to other crustal and magnetic thickness maps based upon different geophysical data. We conclude that the large-scale magnetic thickness of the lithosphere is on average confined to a layer that does not exceed the Moho.

Global seafloor geomorphic features map: applications for ocean conservation and management

NASA Astrophysics Data System (ADS)

Harris, P. T.; Macmillan-Lawler, M.; Rupp, J.; Baker, E.

2013-12-01

Seafloor geomorphology, mapped and measured by marine scientists, has proven to be a very useful physical attribute for ocean management because different geomorphic features (eg. submarine canyons, seamounts, spreading ridges, escarpments, plateaus, trenches etc.) are commonly associated with particular suites of habitats and biological communities. Although we now have better bathymetric datasets than ever before, there has been little effort to integrate these data to create an updated map of seabed geomorphic features or habitats. Currently the best available global seafloor geomorphic features map is over 30 years old. A new global seafloor geomorphic features map (GSGM) has been created based on the analysis and interpretation of the SRTM (Shuttle Radar Topography Mission) 30 arc-second (~1 km) global bathymetry grid. The new map includes global spatial data layers for 29 categories of geomorphic features, defined by the International Hydrographic Organisation. The new geomorphic features map will allow: 1) Characterization of bioregions in terms of their geomorphic content (eg. GOODS bioregions, Large Marine Ecosystems (LMEs), ecologically or biologically significant areas (EBSA)); 2) Prediction of the potential spatial distribution of vulnerable marine ecosystems (VME) and marine genetic resources (MGR; eg. associated with hydrothermal vent communities, shelf-incising submarine canyons and seamounts rising to a specified depth); and 3) Characterization of national marine jurisdictions in terms of their inventory of geomorphic features and their global representativeness of features. To demonstrate the utility of the GSGM, we have conducted an analysis of the geomorphic feature content of the current global inventory of marine protected areas (MPAs) to assess the extent to which features are currently represented. The analysis shows that many features have very low representation, for example fans and rises have less than 1 per cent of their total area inside existing protected areas. The ';best' represented features, trenches and troughs, have only 8.7 and 5.9 per cent respectively of their total area inside existing protected areas. Seamounts have only 2.8% of their area within existing MPAs. Diagram showing the hierarchy of geomorphic features mapped in the present study. Base layer features are the shelf, slope, abyss and hadal zones. The occurrence of some features is confined to one of the base layers, whereas the occurrence of other features is confined to two or more base layers, as illustrated by shading. Basins and sills are the only features that occur over all four base layers.

Investigating the epigenetic effects of a prototype smoke-derived carcinogen in human cells.

PubMed

Tommasi, Stella; Kim, Sang-in; Zhong, Xueyan; Wu, Xiwei; Pfeifer, Gerd P; Besaratinia, Ahmad

2010-05-12

Global loss of DNA methylation and locus/gene-specific gain of DNA methylation are two distinct hallmarks of carcinogenesis. Aberrant DNA methylation is implicated in smoking-related lung cancer. In this study, we have comprehensively investigated the modulation of DNA methylation consequent to chronic exposure to a prototype smoke-derived carcinogen, benzo[a]pyrene diol epoxide (B[a]PDE), in genomic regions of significance in lung cancer, in normal human cells. We have used a pulldown assay for enrichment of the CpG methylated fraction of cellular DNA combined with microarray platforms, followed by extensive validation through conventional bisulfite-based analysis. Here, we demonstrate strikingly similar patterns of DNA methylation in non-transformed B[a]PDE-treated cells vs control using high-throughput microarray-based DNA methylation profiling confirmed by conventional bisulfite-based DNA methylation analysis. The absence of aberrant DNA methylation in our model system within a timeframe that precedes cellular transformation suggests that following carcinogen exposure, other as yet unknown factors (secondary to carcinogen treatment) may help initiate global loss of DNA methylation and region-specific gain of DNA methylation, which can, in turn, contribute to lung cancer development. Unveiling the initiating events that cause aberrant DNA methylation in lung cancer has tremendous public health relevance, as it can help define future strategies for early detection and prevention of this highly lethal disease.

Investigating the Epigenetic Effects of a Prototype Smoke-Derived Carcinogen in Human Cells

PubMed Central

Tommasi, Stella; Kim, Sang-in; Zhong, Xueyan; Wu, Xiwei; Pfeifer, Gerd P.; Besaratinia, Ahmad

2010-01-01

Global loss of DNA methylation and locus/gene-specific gain of DNA methylation are two distinct hallmarks of carcinogenesis. Aberrant DNA methylation is implicated in smoking-related lung cancer. In this study, we have comprehensively investigated the modulation of DNA methylation consequent to chronic exposure to a prototype smoke-derived carcinogen, benzo[a]pyrene diol epoxide (B[a]PDE), in genomic regions of significance in lung cancer, in normal human cells. We have used a pulldown assay for enrichment of the CpG methylated fraction of cellular DNA combined with microarray platforms, followed by extensive validation through conventional bisulfite-based analysis. Here, we demonstrate strikingly similar patterns of DNA methylation in non-transformed B[a]PDE-treated cells vs control using high-throughput microarray-based DNA methylation profiling confirmed by conventional bisulfite-based DNA methylation analysis. The absence of aberrant DNA methylation in our model system within a timeframe that precedes cellular transformation suggests that following carcinogen exposure, other as yet unknown factors (secondary to carcinogen treatment) may help initiate global loss of DNA methylation and region-specific gain of DNA methylation, which can, in turn, contribute to lung cancer development. Unveiling the initiating events that cause aberrant DNA methylation in lung cancer has tremendous public health relevance, as it can help define future strategies for early detection and prevention of this highly lethal disease. PMID:20485678

Web Map Services (WMS) Global Mosaic

NASA Technical Reports Server (NTRS)

Percivall, George; Plesea, Lucian

2003-01-01

The WMS Global Mosaic provides access to imagery of the global landmass using an open standard for web mapping. The seamless image is a mosaic of Landsat 7 scenes; geographically-accurate with 30 and 15 meter resolutions. By using the OpenGIS Web Map Service (WMS) interface, any organization can use the global mosaic as a layer in their geospatial applications. Based on a trade study, an implementation approach was chosen that extends a previously developed WMS hosting a Landsat 5 CONUS mosaic developed by JPL. The WMS Global Mosaic supports the NASA Geospatial Interoperability Office goal of providing an integrated digital representation of the Earth, widely accessible for humanity's critical decisions.

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

PubMed Central

Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

Evolution of regional to global paddy rice mapping methods

NASA Astrophysics Data System (ADS)

Dong, J.; Xiao, X.

2016-12-01

Paddy rice agriculture plays an important role in various environmental issues including food security, water use, climate change, and disease transmission. However, regional and global paddy rice maps are surprisingly scarce and sporadic despite numerous efforts in paddy rice mapping algorithms and applications. In this presentation we would like to review the existing paddy rice mapping methods from the literatures ranging from the 1980s to 2015. In particular, we illustrated the evolution of these paddy rice mapping efforts, looking specifically at the future trajectory of paddy rice mapping methodologies. The biophysical features and growth phases of paddy rice were analyzed first, and feature selections for paddy rice mapping were analyzed from spectral, polarimetric, temporal, spatial, and textural aspects. We sorted out paddy rice mapping algorithms into four categories: 1) Reflectance data and image statistic-based approaches, 2) vegetation index (VI) data and enhanced image statistic-based approaches, 3) VI or RADAR backscatter-based temporal analysis approaches, and 4) phenology-based approaches through remote sensing recognition of key growth phases. The phenology-based approaches using unique features of paddy rice (e.g., transplanting) for mapping have been increasingly used in paddy rice mapping. Based on the literature review, we discussed a series of issues for large scale operational paddy rice mapping.

A list of tables summarizing various Cmap analysis, from which the final tables in the manuscript are based on

EPA Pesticide Factsheets

Various Cmap analyses within and across species and microarray platforms conducted and summarized to generate the tables in the publication.This dataset is associated with the following publication:Wang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles. BMC Genomics. BioMed Central Ltd, London, UK, 17(84): 1-20, (2016).

Array-Based Gene Discovery with Three Unrelated Subjects Shows SCARB2/LIMP-2 Deficiency Causes Myoclonus Epilepsy and Glomerulosclerosis

PubMed Central

Berkovic, Samuel F.; Dibbens, Leanne M.; Oshlack, Alicia; Silver, Jeremy D.; Katerelos, Marina; Vears, Danya F.; Lüllmann-Rauch, Renate; Blanz, Judith; Zhang, Ke Wei; Stankovich, Jim; Kalnins, Renate M.; Dowling, John P.; Andermann, Eva; Andermann, Frederick; Faldini, Enrico; D'Hooge, Rudi; Vadlamudi, Lata; Macdonell, Richard A.; Hodgson, Bree L.; Bayly, Marta A.; Savige, Judy; Mulley, John C.; Smyth, Gordon K.; Power, David A.; Saftig, Paul; Bahlo, Melanie

2008-01-01

Action myoclonus-renal failure syndrome (AMRF) is an autosomal-recessive disorder with the remarkable combination of focal glomerulosclerosis, frequently with glomerular collapse, and progressive myoclonus epilepsy associated with storage material in the brain. Here, we employed a novel combination of molecular strategies to find the responsible gene and show its effects in an animal model. Utilizing only three unrelated affected individuals and their relatives, we used homozygosity mapping with single-nucleotide polymorphism chips to localize AMRF. We then used microarray-expression analysis to prioritize candidates prior to sequencing. The disorder was mapped to 4q13-21, and microarray-expression analysis identified SCARB2/Limp2, which encodes a lysosomal-membrane protein, as the likely candidate. Mutations in SCARB2/Limp2 were found in all three families used for mapping and subsequently confirmed in two other unrelated AMRF families. The mutations were associated with lack of SCARB2 protein. Reanalysis of an existing Limp2 knockout mouse showed intracellular inclusions in cerebral and cerebellar cortex, and the kidneys showed subtle glomerular changes. This study highlights that recessive genes can be identified with a very small number of subjects. The ancestral lysosomal-membrane protein SCARB2/LIMP-2 is responsible for AMRF. The heterogeneous pathology in the kidney and brain suggests that SCARB2/Limp2 has pleiotropic effects that may be relevant to understanding the pathogenesis of other forms of glomerulosclerosis or collapse and myoclonic epilepsies. PMID:18308289

HOTEX: An Approach for Global Mapping of Human Built-Up and Settlement Extent

NASA Technical Reports Server (NTRS)

Wang, Panshi; Huang, Chengquan; Tilton, James C.; Tan, Bin; Brown De Colstoun, Eric C.

2017-01-01

Understanding the impacts of urbanization requires accurate and updatable urban extent maps. Here we present an algorithm for mapping urban extent at global scale using Landsat data. An innovative hierarchical object-based texture (HOTex) classification approach was designed to overcome spectral confusion between urban and nonurban land cover types. VIIRS nightlights data and MODIS vegetation index datasets are integrated as high-level features under an object-based framework. We applied the HOTex method to the GLS-2010 Landsat images to produce a global map of human built-up and settlement extent. As shown by visual assessments, our method could effectively map urban extent and generate consistent results using images with inconsistent acquisition time and vegetation phenology. Using scene-level cross validation for results in Europe, we assessed the performance of HOTex and achieved a kappa coefficient of 0.91, compared to 0.74 from a baseline method using per-pixel classification using spectral information.

Multi-Gene Detection and Identification of Mosquito-Borne RNA Viruses Using an Oligonucleotide Microarray

PubMed Central

Grubaugh, Nathan D.; McMenamy, Scott S.; Turell, Michael J.; Lee, John S.

2013-01-01

Background Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae), Alphavirus (Togaviridae), Orthobunyavirus (Bunyaviridae), and Phlebovirus (Bunyaviridae). Methodology/Principal Findings The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. Conclusions/Significance We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish public health priorities, detect disease outbreaks, and evaluate control programs. PMID:23967358

Integration of Neuroimaging and Microarray Datasets through Mapping and Model-Theoretic Semantic Decomposition of Unstructured Phenotypes

PubMed Central

Pantazatos, Spiro P.; Li, Jianrong; Pavlidis, Paul; Lussier, Yves A.

2009-01-01

An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP) and a knowledge-based phenotype organizer system (PhenOS) to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®). The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50), and precision of the semantic mapping between these terms across datasets was 98% (n = 100). To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets. PMID:20495688

Analysis of global oceanic rainfall from microwave data

NASA Technical Reports Server (NTRS)

Rao, M.

1978-01-01

A Global Rainfall Atlas was prepared from Nimbus 5 ESMR data. The Atlas includes global oceanic rainfall maps based on weekly, monthly and seasonal averages, complete through the end of 1975. Similar maps for 1973 and 1974 were studied. They reveal several previously unknown areas of enhanced rainfall and preliminary data on interannual variability of oceanic rainfall.

Topographical Hill Shading Map Production Based Tianditu (map World)

NASA Astrophysics Data System (ADS)

Wang, C.; Zha, Z.; Tang, D.; Yang, J.

2018-04-01

TIANDITU (Map World) is the public version of National Platform for Common Geospatial Information Service, and the terrain service is an important channel for users on the platform. With the development of TIANDITU, topographical hill shading map production for providing and updating global terrain map on line becomes necessary for the characters of strong intuition, three-dimensional sense and aesthetic effect. As such, the terrain service of TIANDITU focuses on displaying the different scales of topographical data globally. And this paper mainly aims to research the method of topographical hill shading map production globally using DEM (Digital Elevation Model) data between the displaying scales about 1 : 140,000,000 to 1 : 4,000,000, corresponded the display level from 2 to 7 on TIANDITU website.

Strand-specific transcriptome profiling with directly labeled RNA on genomic tiling microarrays

PubMed Central

2011-01-01

Background With lower manufacturing cost, high spot density, and flexible probe design, genomic tiling microarrays are ideal for comprehensive transcriptome studies. Typically, transcriptome profiling using microarrays involves reverse transcription, which converts RNA to cDNA. The cDNA is then labeled and hybridized to the probes on the arrays, thus the RNA signals are detected indirectly. Reverse transcription is known to generate artifactual cDNA, in particular the synthesis of second-strand cDNA, leading to false discovery of antisense RNA. To address this issue, we have developed an effective method using RNA that is directly labeled, thus by-passing the cDNA generation. This paper describes this method and its application to the mapping of transcriptome profiles. Results RNA extracted from laboratory cultures of Porphyromonas gingivalis was fluorescently labeled with an alkylation reagent and hybridized directly to probes on genomic tiling microarrays specifically designed for this periodontal pathogen. The generated transcriptome profile was strand-specific and produced signals close to background level in most antisense regions of the genome. In contrast, high levels of signal were detected in the antisense regions when the hybridization was done with cDNA. Five antisense areas were tested with independent strand-specific RT-PCR and none to negligible amplification was detected, indicating that the strong antisense cDNA signals were experimental artifacts. Conclusions An efficient method was developed for mapping transcriptome profiles specific to both coding strands of a bacterial genome. This method chemically labels and uses extracted RNA directly in microarray hybridization. The generated transcriptome profile was free of cDNA artifactual signals. In addition, this method requires fewer processing steps and is potentially more sensitive in detecting small amount of RNA compared to conventional end-labeling methods due to the incorporation of more fluorescent molecules per RNA fragment. PMID:21235785

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

Fluorescence-based bioassays for the detection and evaluation of food materials.

PubMed

Nishi, Kentaro; Isobe, Shin-Ichiro; Zhu, Yun; Kiyama, Ryoiti

2015-10-13

We summarize here the recent progress in fluorescence-based bioassays for the detection and evaluation of food materials by focusing on fluorescent dyes used in bioassays and applications of these assays for food safety, quality and efficacy. Fluorescent dyes have been used in various bioassays, such as biosensing, cell assay, energy transfer-based assay, probing, protein/immunological assay and microarray/biochip assay. Among the arrays used in microarray/biochip assay, fluorescence-based microarrays/biochips, such as antibody/protein microarrays, bead/suspension arrays, capillary/sensor arrays, DNA microarrays/polymerase chain reaction (PCR)-based arrays, glycan/lectin arrays, immunoassay/enzyme-linked immunosorbent assay (ELISA)-based arrays, microfluidic chips and tissue arrays, have been developed and used for the assessment of allergy/poisoning/toxicity, contamination and efficacy/mechanism, and quality control/safety. DNA microarray assays have been used widely for food safety and quality as well as searches for active components. DNA microarray-based gene expression profiling may be useful for such purposes due to its advantages in the evaluation of pathway-based intracellular signaling in response to food materials.

Fluorescence-Based Bioassays for the Detection and Evaluation of Food Materials

PubMed Central

Nishi, Kentaro; Isobe, Shin-Ichiro; Zhu, Yun; Kiyama, Ryoiti

2015-01-01

We summarize here the recent progress in fluorescence-based bioassays for the detection and evaluation of food materials by focusing on fluorescent dyes used in bioassays and applications of these assays for food safety, quality and efficacy. Fluorescent dyes have been used in various bioassays, such as biosensing, cell assay, energy transfer-based assay, probing, protein/immunological assay and microarray/biochip assay. Among the arrays used in microarray/biochip assay, fluorescence-based microarrays/biochips, such as antibody/protein microarrays, bead/suspension arrays, capillary/sensor arrays, DNA microarrays/polymerase chain reaction (PCR)-based arrays, glycan/lectin arrays, immunoassay/enzyme-linked immunosorbent assay (ELISA)-based arrays, microfluidic chips and tissue arrays, have been developed and used for the assessment of allergy/poisoning/toxicity, contamination and efficacy/mechanism, and quality control/safety. DNA microarray assays have been used widely for food safety and quality as well as searches for active components. DNA microarray-based gene expression profiling may be useful for such purposes due to its advantages in the evaluation of pathway-based intracellular signaling in response to food materials. PMID:26473869

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping.

PubMed

Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren; Nielsen, Morten

2017-01-01

Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope.

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

PubMed Central

Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren

2017-01-01

Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope. PMID:28095436

The developmental transcriptome of Drosophila melanogaster

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

University of Connecticut; Graveley, Brenton R.; Brooks, Angela N.

Drosophila melanogaster is one of the most well studied genetic model organisms; nonetheless, its genome still contains unannotated coding and non-coding genes, transcripts, exons and RNA editing sites. Full discovery and annotation are pre-requisites for understanding how the regulation of transcription, splicing and RNA editing directs the development of this complex organism. Here we used RNA-Seq, tiling microarrays and cDNA sequencing to explore the transcriptome in 30 distinct developmental stages. We identified 111,195 new elements, including thousands of genes, coding and non-coding transcripts, exons, splicing and editing events, and inferred protein isoforms that previously eluded discovery using established experimental, predictionmore » and conservation-based approaches. These data substantially expand the number of known transcribed elements in the Drosophila genome and provide a high-resolution view of transcriptome dynamics throughout development. Drosophila melanogaster is an important non-mammalian model system that has had a critical role in basic biological discoveries, such as identifying chromosomes as the carriers of genetic information and uncovering the role of genes in development. Because it shares a substantial genic content with humans, Drosophila is increasingly used as a translational model for human development, homeostasis and disease. High-quality maps are needed for all functional genomic elements. Previous studies demonstrated that a rich collection of genes is deployed during the life cycle of the fly. Although expression profiling using microarrays has revealed the expression of, 13,000 annotated genes, it is difficult to map splice junctions and individual base modifications generated by RNA editing using such approaches. Single-base resolution is essential to define precisely the elements that comprise the Drosophila transcriptome. Estimates of the number of transcript isoforms are less accurate than estimates of the number of genes. Whereas, 20% of Drosophila genes are annotated as encoding alternatively spliced premRNAs, splice-junction microarray experiments indicate that this number is at least 40% (ref. 7). Determining the diversity of mRNAs generated by alternative promoters, alternative splicing and RNA editing will substantially increase the inferred protein repertoire. Non-coding RNA genes (ncRNAs) including short interfering RNAs (siRNAs) and microRNAS (miRNAs) (reviewed in ref. 10), and longer ncRNAs such as bxd (ref. 11) and rox (ref. 12), have important roles in gene regulation, whereas others such as small nucleolar RNAs (snoRNAs)and small nuclear RNAs (snRNAs) are important components of macromolecular machines such as the ribosome and spliceosome. The transcription and processing of these ncRNAs must also be fully documented and mapped. As part of the modENCODE project to annotate the functional elements of the D. melanogaster and Caenorhabditis elegans genomes, we used RNA-Seq and tiling microarrays to sample the Drosophila transcriptome at unprecedented depth throughout development from early embryo to ageing male and female adults. We report on a high-resolution view of the discovery, structure and dynamic expression of the D. melanogaster transcriptome.« less

TRAM (Transcriptome Mapper): database-driven creation and analysis of transcriptome maps from multiple sources

PubMed Central

2011-01-01

Background Several tools have been developed to perform global gene expression profile data analysis, to search for specific chromosomal regions whose features meet defined criteria as well as to study neighbouring gene expression. However, most of these tools are tailored for a specific use in a particular context (e.g. they are species-specific, or limited to a particular data format) and they typically accept only gene lists as input. Results TRAM (Transcriptome Mapper) is a new general tool that allows the simple generation and analysis of quantitative transcriptome maps, starting from any source listing gene expression values for a given gene set (e.g. expression microarrays), implemented as a relational database. It includes a parser able to assign univocal and updated gene symbols to gene identifiers from different data sources. Moreover, TRAM is able to perform intra-sample and inter-sample data normalization, including an original variant of quantile normalization (scaled quantile), useful to normalize data from platforms with highly different numbers of investigated genes. When in 'Map' mode, the software generates a quantitative representation of the transcriptome of a sample (or of a pool of samples) and identifies if segments of defined lengths are over/under-expressed compared to the desired threshold. When in 'Cluster' mode, the software searches for a set of over/under-expressed consecutive genes. Statistical significance for all results is calculated with respect to genes localized on the same chromosome or to all genome genes. Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated. We present the results of a biological model test, based on a meta-analysis comparison between a sample pool of human CD34+ hematopoietic progenitor cells and a sample pool of megakaryocytic cells. Biologically relevant chromosomal segments and gene clusters with differential expression during the differentiation toward megakaryocyte were identified. Conclusions TRAM is designed to create, and statistically analyze, quantitative transcriptome maps, based on gene expression data from multiple sources. The release includes FileMaker Pro database management runtime application and it is freely available at http://apollo11.isto.unibo.it/software/, along with preconfigured implementations for mapping of human, mouse and zebrafish transcriptomes. PMID:21333005

Global Expression Profiling in Atopic Eczema Reveals Reciprocal Expression of Inflammatory and Lipid Genes

PubMed Central

Sääf, Annika M.; Tengvall-Linder, Maria; Chang, Howard Y.; Adler, Adam S.; Wahlgren, Carl-Fredrik; Scheynius, Annika; Nordenskjöld, Magnus; Bradley, Maria

2008-01-01

Background Atopic eczema (AE) is a common chronic inflammatory skin disorder. In order to dissect the genetic background several linkage and genetic association studies have been performed. Yet very little is known about specific genes involved in this complex skin disease, and the underlying molecular mechanisms are not fully understood. Methodology/Findings We used human DNA microarrays to identify a molecular picture of the programmed responses of the human genome to AE. The transcriptional program was analyzed in skin biopsy samples from lesional and patch-tested skin from AE patients sensitized to Malassezia sympodialis (M. sympodialis), and corresponding biopsies from healthy individuals. The most notable feature of the global gene-expression pattern observed in AE skin was a reciprocal expression of induced inflammatory genes and repressed lipid metabolism genes. The overall transcriptional response in M. sympodialis patch-tested AE skin was similar to the gene-expression signature identified in lesional AE skin. In the constellation of genes differentially expressed in AE skin compared to healthy control skin, we have identified several potential susceptibility genes that may play a critical role in the pathological condition of AE. Many of these genes, including genes with a role in immune responses, lipid homeostasis, and epidermal differentiation, are localized on chromosomal regions previously linked to AE. Conclusions/Significance Through genome-wide expression profiling, we were able to discover a distinct reciprocal expression pattern of induced inflammatory genes and repressed lipid metabolism genes in skin from AE patients. We found a significant enrichment of differentially expressed genes in AE with cytobands associated to the disease, and furthermore new chromosomal regions were found that could potentially guide future region-specific linkage mapping in AE. The full data set is available at http://microarray-pubs.stanford.edu/eczema. PMID:19107207

Brief Guide to Genomics: DNA, Genes and Genomes

MedlinePlus

... Sheets A Brief Guide to Genomics About NHGRI Research About the International HapMap Project Biological Pathways Chromosome Abnormalities Chromosomes Cloning Comparative Genomics DNA Microarray Technology DNA Sequencing Deoxyribonucleic Acid ( ...

Geodatabase model for global geologic mapping: concept and implementation in planetary sciences

NASA Astrophysics Data System (ADS)

Nass, Andrea

2017-04-01

One aim of the NASA Dawn mission is to generate global geologic maps of the asteroid Vesta and the dwarf planet Ceres. To accomplish this, the Dawn Science Team followed the technical recommendations for cartographic basemap production. The geological mapping campaign of Vesta was completed and published, but mapping of the dwarf planet Ceres is still ongoing. The tiling schema for the geological mapping is the same for both planetary bodies and for Ceres it is divided into two parts: four overview quadrangles (Survey Orbit, 415 m/pixel) and 15 more detailed quadrangles (High Altitude Mapping HAMO, 140 m/pixel). The first global geologic map was based on survey images (415 m/pixel). The combine 4 Survey quadrangles completed by HAMO data served as basis for generating a more detailed view of the geologic history and also for defining the chronostratigraphy and time scale of the dwarf planet. The most detailed view can be expected within the 15 mapping quadrangles based on HAMO resolution and completed by the Low Altitude Mapping (LAMO) data with 35 m/pixel. For the interpretative mapping process of each quadrangle one responsible mapper was assigned. Unifying the geological mapping of each quadrangle and bringing this together to regional and global valid statements is already a very time intensive task. However, another challenge that has to be accomplished is to consider how the 15 individual mappers can generate one homogenous GIS-based project (w.r.t. geometrical and visual character) thus produce a geologically-consistent final map. Our approach this challenge was already discussed for mapping of Vesta. To accommodate the map requirements regarding rules for data storage and database management, the computer-based GIS environment used for the interpretative mapping process must be designed in a way that it can be adjusted to the unique features of the individual investigation areas. Within this contribution the template will be presented that uses standards for digitizing, visualization, data merging and synchronization in the processes of interpretative mapping project. Following the new technological innovations within GIS software and the individual requirements for mapping Ceres, a template was developed based on the symbology and framework. The template for (GIS-base) mapping presented here directly links the generically descriptive attributes of planetary objects to the predefined and standardized symbology in one data structure. Using this template the map results are more comparable and better controllable. Furthermore, merging and synchronization of the individual maps, map projects and sheets will be far more efficient. The template can be adapted to any other planetary body and or within future discovery missions (e.g., Lucy and Psyche which was selected to explore the early solar system by NASA) for generating reusable map results.

Fast and Accurate Construction of Ultra-Dense Consensus Genetic Maps Using Evolution Strategy Optimization

PubMed Central

Mester, David; Ronin, Yefim; Schnable, Patrick; Aluru, Srinivas; Korol, Abraham

2015-01-01

Our aim was to develop a fast and accurate algorithm for constructing consensus genetic maps for chip-based SNP genotyping data with a high proportion of shared markers between mapping populations. Chip-based genotyping of SNP markers allows producing high-density genetic maps with a relatively standardized set of marker loci for different mapping populations. The availability of a standard high-throughput mapping platform simplifies consensus analysis by ignoring unique markers at the stage of consensus mapping thereby reducing mathematical complicity of the problem and in turn analyzing bigger size mapping data using global optimization criteria instead of local ones. Our three-phase analytical scheme includes automatic selection of ~100-300 of the most informative (resolvable by recombination) markers per linkage group, building a stable skeletal marker order for each data set and its verification using jackknife re-sampling, and consensus mapping analysis based on global optimization criterion. A novel Evolution Strategy optimization algorithm with a global optimization criterion presented in this paper is able to generate high quality, ultra-dense consensus maps, with many thousands of markers per genome. This algorithm utilizes "potentially good orders" in the initial solution and in the new mutation procedures that generate trial solutions, enabling to obtain a consensus order in reasonable time. The developed algorithm, tested on a wide range of simulated data and real world data (Arabidopsis), outperformed two tested state-of-the-art algorithms by mapping accuracy and computation time. PMID:25867943

Biomarkers of the Hedgehog/Smoothened pathway in healthy volunteers

PubMed Central

Kadam, Sunil K; Patel, Bharvin K R; Jones, Emma; Nguyen, Tuan S; Verma, Lalit K; Landschulz, Katherine T; Stepaniants, Sergey; Li, Bin; Brandt, John T; Brail, Leslie H

2012-01-01

The Hedgehog (Hh) pathway is involved in oncogenic transformation and tumor maintenance. The primary objective of this study was to select surrogate tissue to measure messenger ribonucleic acid (mRNA) levels of Hh pathway genes for measurement of pharmacodynamic effect. Expression of Hh pathway specific genes was measured by quantitative real time polymerase chain reaction (qRT-PCR) and global gene expression using Affymetrix U133 microarrays. Correlations were made between the expression of specific genes determined by qRT-PCR and normalized microarray data. Gene ontology analysis using microarray data for a broader set of Hh pathway genes was performed to identify additional Hh pathway-related markers in the surrogate tissue. RNA extracted from blood, hair follicle, and skin obtained from healthy subjects was analyzed by qRT-PCR for 31 genes, whereas 8 samples were analyzed for a 7-gene subset. Twelve sample sets, each with ≤500 ng total RNA derived from hair, skin, and blood, were analyzed using Affymetrix U133 microarrays. Transcripts for several Hh pathway genes were undetectable in blood using qRT-PCR. Skin was the most desirable matrix, followed by hair follicle. Whether processed by robust multiarray average or microarray suite 5 (MAS5), expression patterns of individual samples showed co-clustered signals; both normalization methods were equally effective for unsupervised analysis. The MAS5- normalized probe sets appeared better suited for supervised analysis. This work provides the basis for selection of a surrogate tissue and an expression analysis-based approach to evaluate pathway-related genes as markers of pharmacodynamic effect with novel inhibitors of the Hh pathway. PMID:22611475

Promise and progress in environmental genomics: a status report on the applications of gene expression-based microarray studies in ecologically relevant fish species.

PubMed

Hook, S E

2010-12-01

The advent of any new technology is typically met with great excitement. So it was a few years ago, when the combination of advances in sequencing technology and the development of microarray technology made measurements of global gene expression in ecologically relevant species possible. Many of the review papers published around that time promised that these new technologies would revolutionize environmental biology as they had revolutionized medicine and related fields. A few years have passed since these technological advancements have been made, and the use of microarray studies in non-model fish species has been adopted in many laboratories internationally. Has the relatively widespread adoption of this technology really revolutionized the fields of environmental biology, including ecotoxicology, aquaculture and ecology, as promised? Or have these studies merely become a novelty and a potential distraction for scientists addressing environmentally relevant questions? In this review, the promises made in early review papers, in particular about the advances that the use of microarrays would enable, are summarized; these claims are compared to the results of recent studies to determine whether the forecasted changes have materialized. Some applications, as discussed in the paper, have been realized and have led to advances in their field, others are still under development. © 2010 CSIRO. Journal of Fish Biology © 2010 The Fisheries Society of the British Isles.

SoyNet: a database of co-functional networks for soybean Glycine max.

PubMed

Kim, Eiru; Hwang, Sohyun; Lee, Insuk

2017-01-04

Soybean (Glycine max) is a legume crop with substantial economic value, providing a source of oil and protein for humans and livestock. More than 50% of edible oils consumed globally are derived from this crop. Soybean plants are also important for soil fertility, as they fix atmospheric nitrogen by symbiosis with microorganisms. The latest soybean genome annotation (version 2.0) lists 56 044 coding genes, yet their functional contributions to crop traits remain mostly unknown. Co-functional networks have proven useful for identifying genes that are involved in a particular pathway or phenotype with various network algorithms. Here, we present SoyNet (available at www.inetbio.org/soynet), a database of co-functional networks for G. max and a companion web server for network-based functional predictions. SoyNet maps 1 940 284 co-functional links between 40 812 soybean genes (72.8% of the coding genome), which were inferred from 21 distinct types of genomics data including 734 microarrays and 290 RNA-seq samples from soybean. SoyNet provides a new route to functional investigation of the soybean genome, elucidating genes and pathways of agricultural importance. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

SacconePhD, Scott F; Chesler, Elissa J; Bierut, Laura J

Commercial SNP microarrays now provide comprehensive and affordable coverage of the human genome. However, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is thought to be influenced by complex interactions among many relevant genes and pathways. We have assembled a list of 486 biologically relevant genes nominated by a panel of experts on addiction. We then added 424 genes that showed evidence of association with addiction phenotypes through mouse QTL mappings and gene co-expression analysis. We demonstrate that there are a substantial number of SNPs in these genes that are not well representedmore » by commercial SNP platforms. We address this problem by introducing a publicly available SNP database for addiction. The database is annotated using numeric prioritization scores indicating the extent of biological relevance. The scores incorporate a number of factors such as SNP/gene functional properties (including synonymy and promoter regions), data from mouse systems genetics and measures of human/mouse evolutionary conservation. We then used HapMap genotyping data to determine if a SNP is tagged by a commercial microarray through linkage disequilibrium. This combination of biological prioritization scores and LD tagging annotation will enable addiction researchers to supplement commercial SNP microarrays to ensure comprehensive coverage of biologically relevant regions.« less

Project Loon based augmentation for global ionospheric modeling over Southern Hemisphere

NASA Astrophysics Data System (ADS)

Wang, Cheng; Shi, Chuang; Zhang, Hongping

2017-04-01

Global ionospheric products of vertical total electron content (VTEC) derived from GNSS measurements may have low accuracy over oceans and southern latitudes where there are not rich observations. Project Loon provides a great opportunity to enhance the measurements over those areas. In this contribution, a simulation of Project Loon based augmentation for global ionospheric modeling is performed by using the international reference ionosphere (IRI) which could simulate VTEC measurements for the balloons. The performance of the enhanced method based on simulation of Project Loon is investigated by comparing with VTEC maps from Ionosphere Associate Analysis Centers (IAACs) as well as IGS final GIMs. The comparison indicates that there is a better consistency between the VTEC maps by the enhanced method and IGS final GIMs. Also, obvious improvements of RMS maps in GIMs for the middle latitudes and southern latitudes are enabled by the augmentation of Project Loon. Additionally, JASON data are used to validate the specific improvement of the VTEC maps. The results show that the performance of VTEC maps is improved slightly, especially in southern latitudes. It is possible that the VTEC maps could be improved significantly by using real GPS measurements from balloons of Project Loon in the near future.

Project Loon based augmentation for global ionospheric modeling over Southern Hemisphere.

PubMed

Wang, Cheng; Shi, Chuang; Zhang, Hongping

2017-04-06

Global ionospheric products of vertical total electron content (VTEC) derived from GNSS measurements may have low accuracy over oceans and southern latitudes where there are not rich observations. Project Loon provides a great opportunity to enhance the measurements over those areas. In this contribution, a simulation of Project Loon based augmentation for global ionospheric modeling is performed by using the international reference ionosphere (IRI) which could simulate VTEC measurements for the balloons. The performance of the enhanced method based on simulation of Project Loon is investigated by comparing with VTEC maps from Ionosphere Associate Analysis Centers (IAACs) as well as IGS final GIMs. The comparison indicates that there is a better consistency between the VTEC maps by the enhanced method and IGS final GIMs. Also, obvious improvements of RMS maps in GIMs for the middle latitudes and southern latitudes are enabled by the augmentation of Project Loon. Additionally, JASON data are used to validate the specific improvement of the VTEC maps. The results show that the performance of VTEC maps is improved slightly, especially in southern latitudes. It is possible that the VTEC maps could be improved significantly by using real GPS measurements from balloons of Project Loon in the near future.

Project Loon based augmentation for global ionospheric modeling over Southern Hemisphere

PubMed Central

Wang, Cheng; Shi, Chuang; Zhang, Hongping

2017-01-01

Global ionospheric products of vertical total electron content (VTEC) derived from GNSS measurements may have low accuracy over oceans and southern latitudes where there are not rich observations. Project Loon provides a great opportunity to enhance the measurements over those areas. In this contribution, a simulation of Project Loon based augmentation for global ionospheric modeling is performed by using the international reference ionosphere (IRI) which could simulate VTEC measurements for the balloons. The performance of the enhanced method based on simulation of Project Loon is investigated by comparing with VTEC maps from Ionosphere Associate Analysis Centers (IAACs) as well as IGS final GIMs. The comparison indicates that there is a better consistency between the VTEC maps by the enhanced method and IGS final GIMs. Also, obvious improvements of RMS maps in GIMs for the middle latitudes and southern latitudes are enabled by the augmentation of Project Loon. Additionally, JASON data are used to validate the specific improvement of the VTEC maps. The results show that the performance of VTEC maps is improved slightly, especially in southern latitudes. It is possible that the VTEC maps could be improved significantly by using real GPS measurements from balloons of Project Loon in the near future. PMID:28383058

Plant-pathogen interactions: what microarray tells about it?

PubMed

Lodha, T D; Basak, J

2012-01-01

Plant defense responses are mediated by elementary regulatory proteins that affect expression of thousands of genes. Over the last decade, microarray technology has played a key role in deciphering the underlying networks of gene regulation in plants that lead to a wide variety of defence responses. Microarray is an important tool to quantify and profile the expression of thousands of genes simultaneously, with two main aims: (1) gene discovery and (2) global expression profiling. Several microarray technologies are currently in use; most include a glass slide platform with spotted cDNA or oligonucleotides. Till date, microarray technology has been used in the identification of regulatory genes, end-point defence genes, to understand the signal transduction processes underlying disease resistance and its intimate links to other physiological pathways. Microarray technology can be used for in-depth, simultaneous profiling of host/pathogen genes as the disease progresses from infection to resistance/susceptibility at different developmental stages of the host, which can be done in different environments, for clearer understanding of the processes involved. A thorough knowledge of plant disease resistance using successful combination of microarray and other high throughput techniques, as well as biochemical, genetic, and cell biological experiments is needed for practical application to secure and stabilize yield of many crop plants. This review starts with a brief introduction to microarray technology, followed by the basics of plant-pathogen interaction, the use of DNA microarrays over the last decade to unravel the mysteries of plant-pathogen interaction, and ends with the future prospects of this technology.

An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies

PubMed Central

2012-01-01

Background The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. Results We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. Conclusion T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially. PMID:22276688

MiMiR – an integrated platform for microarray data sharing, mining and analysis

PubMed Central

Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence

2008-01-01

Background Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. Results A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. Conclusion The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies. PMID:18801157

MiMiR--an integrated platform for microarray data sharing, mining and analysis.

PubMed

Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence

2008-09-18

Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies.

Microarray-integrated optoelectrofluidic immunoassay system

PubMed Central

Han, Dongsik

2016-01-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection. PMID:27190571

Microarray-integrated optoelectrofluidic immunoassay system.

PubMed

Han, Dongsik; Park, Je-Kyun

2016-05-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

EPA Science Inventory

The second phase of the MicroArray Quality Control (MAQC-II) project evaluated common practices for developing and validating microarray-based models aimed at predicting toxicological and clinical endpoints. Thirty-six teams developed classifiers for 13 endpoints - some easy, som...

Analysis of terrain map matching using multisensing techniques for applications to autonomous vehicle navigation

NASA Technical Reports Server (NTRS)

Page, Lance; Shen, C. N.

1991-01-01

This paper describes skyline-based terrain matching, a new method for locating the vantage point of laser range-finding measurements on a global map previously prepared by satellite or aerial mapping. Skylines can be extracted from the range-finding measurements and modelled from the global map, and are represented in parametric, cylindrical form with azimuth angle as the independent variable. The three translational parameters of the vantage point are determined with a three-dimensional matching of these two sets of skylines.

Mutual information estimation reveals global associations between stimuli and biological processes

PubMed Central

Suzuki, Taiji; Sugiyama, Masashi; Kanamori, Takafumi; Sese, Jun

2009-01-01

Background Although microarray gene expression analysis has become popular, it remains difficult to interpret the biological changes caused by stimuli or variation of conditions. Clustering of genes and associating each group with biological functions are often used methods. However, such methods only detect partial changes within cell processes. Herein, we propose a method for discovering global changes within a cell by associating observed conditions of gene expression with gene functions. Results To elucidate the association, we introduce a novel feature selection method called Least-Squares Mutual Information (LSMI), which computes mutual information without density estimaion, and therefore LSMI can detect nonlinear associations within a cell. We demonstrate the effectiveness of LSMI through comparison with existing methods. The results of the application to yeast microarray datasets reveal that non-natural stimuli affect various biological processes, whereas others are no significant relation to specific cell processes. Furthermore, we discover that biological processes can be categorized into four types according to the responses of various stimuli: DNA/RNA metabolism, gene expression, protein metabolism, and protein localization. Conclusion We proposed a novel feature selection method called LSMI, and applied LSMI to mining the association between conditions of yeast and biological processes through microarray datasets. In fact, LSMI allows us to elucidate the global organization of cellular process control. PMID:19208155

Validation of the high-throughput marker technology DArT using the model plant Arabidopsis thaliana.

PubMed

Wittenberg, Alexander H J; van der Lee, Theo; Cayla, Cyril; Kilian, Andrzej; Visser, Richard G F; Schouten, Henk J

2005-08-01

Diversity Arrays Technology (DArT) is a microarray-based DNA marker technique for genome-wide discovery and genotyping of genetic variation. DArT allows simultaneous scoring of hundreds of restriction site based polymorphisms between genotypes and does not require DNA sequence information or site-specific oligonucleotides. This paper demonstrates the potential of DArT for genetic mapping by validating the quality and molecular basis of the markers, using the model plant Arabidopsis thaliana. Restriction fragments from a genomic representation of the ecotype Landsberg erecta (Ler) were amplified by PCR, individualized by cloning and spotted onto glass slides. The arrays were then hybridized with labeled genomic representations of the ecotypes Columbia (Col) and Ler and of individuals from an F(2) population obtained from a Col x Ler cross. The scoring of markers with specialized software was highly reproducible and 107 markers could unambiguously be ordered on a genetic linkage map. The marker order on the genetic linkage map coincided with the order on the DNA sequence map. Sequencing of the Ler markers and alignment with the available Col genome sequence confirmed that the polymorphism in DArT markers is largely a result of restriction site polymorphisms.

ShakeMap Atlas 2.0: an improved suite of recent historical earthquake ShakeMaps for global hazard analyses and loss model calibration

USGS Publications Warehouse

Garcia, D.; Mah, R.T.; Johnson, K.L.; Hearne, M.G.; Marano, K.D.; Lin, K.-W.; Wald, D.J.

2012-01-01

We introduce the second version of the U.S. Geological Survey ShakeMap Atlas, which is an openly-available compilation of nearly 8,000 ShakeMaps of the most significant global earthquakes between 1973 and 2011. This revision of the Atlas includes: (1) a new version of the ShakeMap software that improves data usage and uncertainty estimations; (2) an updated earthquake source catalogue that includes regional locations and finite fault models; (3) a refined strategy to select prediction and conversion equations based on a new seismotectonic regionalization scheme; and (4) vastly more macroseismic intensity and ground-motion data from regional agencies All these changes make the new Atlas a self-consistent, calibrated ShakeMap catalogue that constitutes an invaluable resource for investigating near-source strong ground-motion, as well as for seismic hazard, scenario, risk, and loss-model development. To this end, the Atlas will provide a hazard base layer for PAGER loss calibration and for the Earthquake Consequences Database within the Global Earthquake Model initiative.

arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays

PubMed Central

Menten, Björn; Pattyn, Filip; De Preter, Katleen; Robbrecht, Piet; Michels, Evi; Buysse, Karen; Mortier, Geert; De Paepe, Anne; van Vooren, Steven; Vermeesch, Joris; Moreau, Yves; De Moor, Bart; Vermeulen, Stefan; Speleman, Frank; Vandesompele, Jo

2005-01-01

Background The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH). One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. Results We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment) supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. Conclusion ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at . PMID:15910681

GStream: Improving SNP and CNV Coverage on Genome-Wide Association Studies

PubMed Central

Alonso, Arnald; Marsal, Sara; Tortosa, Raül; Canela-Xandri, Oriol; Julià, Antonio

2013-01-01

We present GStream, a method that combines genome-wide SNP and CNV genotyping in the Illumina microarray platform with unprecedented accuracy. This new method outperforms previous well-established SNP genotyping software. More importantly, the CNV calling algorithm of GStream dramatically improves the results obtained by previous state-of-the-art methods and yields an accuracy that is close to that obtained by purely CNV-oriented technologies like Comparative Genomic Hybridization (CGH). We demonstrate the superior performance of GStream using microarray data generated from HapMap samples. Using the reference CNV calls generated by the 1000 Genomes Project (1KGP) and well-known studies on whole genome CNV characterization based either on CGH or genotyping microarray technologies, we show that GStream can increase the number of reliably detected variants up to 25% compared to previously developed methods. Furthermore, the increased genome coverage provided by GStream allows the discovery of CNVs in close linkage disequilibrium with SNPs, previously associated with disease risk in published Genome-Wide Association Studies (GWAS). These results could provide important insights into the biological mechanism underlying the detected disease risk association. With GStream, large-scale GWAS will not only benefit from the combined genotyping of SNPs and CNVs at an unprecedented accuracy, but will also take advantage of the computational efficiency of the method. PMID:23844243

Data-based estimates of the ocean carbon sink variability - results of the Surface Ocean pCO2 Mapping intercomparison (SOCOM)

NASA Astrophysics Data System (ADS)

Rödenbeck, Christian; Bakker, Dorothee; Gruber, Nicolas; Iida, Yosuke; Jacobson, Andy; Jones, Steve; Landschützer, Peter; Metzl, Nicolas; Nakaoka, Shin-ichiro; Olsen, Are; Park, Geun-Ha; Peylin, Philippe; Rodgers, Keith; Sasse, Tristan; Schuster, Ute; Shutler, James; Valsala, Vinu; Wanninkhof, Rik; Zeng, Jiye

2016-04-01

Using measurements of the surface-ocean COtwo partial pressure (pCOtwo) from the SOCAT and LDEO data bases and 14 different pCOtwo mapping methods recently collated by the Surface Ocean pCOtwo Mapping intercomparison (SOCOM) initiative, variations in regional and global sea-air COtwo fluxes are investigated. Though the available mapping methods use widely different approaches, we find relatively consistent estimates of regional pCOtwo seasonality, in line with previous estimates. In terms of interannual variability (IAV), all mapping methods estimate the largest variations to occur in the Eastern equatorial Pacific. Despite considerable spread in the detailed variations, mapping methods that fit the data more closely also tend to agree more closely with each other in regional averages. Encouragingly, this includes mapping methods belonging to complementary types - taking variability either directly from the pCOtwo data or indirectly from driver data via regression. From a weighted ensemble average, we find an IAV amplitude of the global sea-air COtwo flux of IAVampl (standard deviation over AnalysisPeriod), which is larger than simulated by biogeochemical process models. On a decadal perspective, the global ocean COtwo uptake is estimated to have gradually increased since about 2000, with little decadal change prior to that. The weighted mean net global ocean COtwo sink estimated by the SOCOM ensemble is -1.75 UPgCyr (AnalysisPeriod), consistent within uncertainties with estimates from ocean-interior carbon data or atmospheric oxygen trends. Using data-based sea-air COtwo fluxes in atmospheric COtwo inversions also helps to better constrain land-atmosphere COtwo fluxes.

Infrared and visible image fusion method based on saliency detection in sparse domain

NASA Astrophysics Data System (ADS)

Liu, C. H.; Qi, Y.; Ding, W. R.

2017-06-01

Infrared and visible image fusion is a key problem in the field of multi-sensor image fusion. To better preserve the significant information of the infrared and visible images in the final fused image, the saliency maps of the source images is introduced into the fusion procedure. Firstly, under the framework of the joint sparse representation (JSR) model, the global and local saliency maps of the source images are obtained based on sparse coefficients. Then, a saliency detection model is proposed, which combines the global and local saliency maps to generate an integrated saliency map. Finally, a weighted fusion algorithm based on the integrated saliency map is developed to achieve the fusion progress. The experimental results show that our method is superior to the state-of-the-art methods in terms of several universal quality evaluation indexes, as well as in the visual quality.

Comparative physical mapping between wheat chromosome arm 2BL and rice chromosome 4.

PubMed

Lee, Tong Geon; Lee, Yong Jin; Kim, Dae Yeon; Seo, Yong Weon

2010-12-01

Physical maps of chromosomes provide a framework for organizing and integrating diverse genetic information. DNA microarrays are a valuable technique for physical mapping and can also be used to facilitate the discovery of single feature polymorphisms (SFPs). Wheat chromosome arm 2BL was physically mapped using a Wheat Genome Array onto near-isogenic lines (NILs) with the aid of wheat-rice synteny and mapped wheat EST information. Using high variance probe set (HVP) analysis, 314 HVPs constituting genes present on 2BL were identified. The 314 HVPs were grouped into 3 categories: HVPs that match only rice chromosome 4 (298 HVPs), those that match only wheat ESTs mapped on 2BL (1), and those that match both rice chromosome 4 and wheat ESTs mapped on 2BL (15). All HVPs were converted into gene sets, which represented either unique rice gene models or mapped wheat ESTs that matched identified HVPs. Comparative physical maps were constructed for 16 wheat gene sets and 271 rice gene sets. Of the 271 rice gene sets, 257 were mapped to the 18-35 Mb regions on rice chromosome 4. Based on HVP analysis and sequence similarity between the gene models in the rice chromosomes and mapped wheat ESTs, the outermost rice gene model that limits the translocation breakpoint to orthologous regions was identified.

Arctic Security in a Warming World

DTIC Science & Technology

2010-03-01

2009). 3 Map based on: “Northwest Passage - Map of Arctic Sea Ice: Global Warming is Opening Canada’s Arctic” http://geology.com/articles/northwest...War College, February 17, 2009) 3. 5 Scott G. Borgerson, “Arctic Meltdown: the Economic and Security Implications of Global Warming ”, Foreign Affairs...april/kirkpatrick.pdf (accessed February 10, 2010). 45 Thomas R. McCarthy, Jr., Global Warming Threatens National Interests in the Arctic, Strategy

The effect of column purification on cDNA indirect labelling for microarrays

PubMed Central

Molas, M Lia; Kiss, John Z

2007-01-01

Background The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. Results We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Conclusion Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays. PMID:17597522

The effect of column purification on cDNA indirect labelling for microarrays.

PubMed

Molas, M Lia; Kiss, John Z

2007-06-27

The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays.

Mapping or Tracing? Rethinking Curriculum Mapping in Higher Education

ERIC Educational Resources Information Center

Wang, Chia-Ling

2015-01-01

Curriculum mapping has been emphasized in recent curriculum innovations in higher education in the drive for global competitiveness. This paper begins by providing an outline of current discourses of curriculum mapping in higher education. Curriculum mapping is frequently associated with outcome-based learning and work readiness, and guiding the…

A Web-Based Multi-Database System Supporting Distributed Collaborative Management and Sharing of Microarray Experiment Information

PubMed Central

Burgarella, Sarah; Cattaneo, Dario; Masseroli, Marco

2006-01-01

We developed MicroGen, a multi-database Web based system for managing all the information characterizing spotted microarray experiments. It supports information gathering and storing according to the Minimum Information About Microarray Experiments (MIAME) standard. It also allows easy sharing of information and data among all multidisciplinary actors involved in spotted microarray experiments. PMID:17238488

An experimental system for flood risk forecasting at global scale

NASA Astrophysics Data System (ADS)

Alfieri, L.; Dottori, F.; Kalas, M.; Lorini, V.; Bianchi, A.; Hirpa, F. A.; Feyen, L.; Salamon, P.

2016-12-01

Global flood forecasting and monitoring systems are nowadays a reality and are being applied by an increasing range of users and practitioners in disaster risk management. Furthermore, there is an increasing demand from users to integrate flood early warning systems with risk based forecasts, combining streamflow estimations with expected inundated areas and flood impacts. To this end, we have developed an experimental procedure for near-real time flood mapping and impact assessment based on the daily forecasts issued by the Global Flood Awareness System (GloFAS). The methodology translates GloFAS streamflow forecasts into event-based flood hazard maps based on the predicted flow magnitude and the forecast lead time and a database of flood hazard maps with global coverage. Flood hazard maps are then combined with exposure and vulnerability information to derive flood risk. Impacts of the forecasted flood events are evaluated in terms of flood prone areas, potential economic damage, and affected population, infrastructures and cities. To further increase the reliability of the proposed methodology we integrated model-based estimations with an innovative methodology for social media monitoring, which allows for real-time verification of impact forecasts. The preliminary tests provided good results and showed the potential of the developed real-time operational procedure in helping emergency response and management. In particular, the link with social media is crucial for improving the accuracy of impact predictions.

Controlled hydrostatic pressure stress downregulates the expression of ribosomal genes in preimplantation embryos: a possible protection mechanism?

PubMed

Bock, I; Raveh-Amit, H; Losonczi, E; Carstea, A C; Feher, A; Mashayekhi, K; Matyas, S; Dinnyes, A; Pribenszky, C

2016-04-01

The efficiency of various assisted reproductive techniques can be improved by preconditioning the gametes and embryos with sublethal hydrostatic pressure treatment. However, the underlying molecular mechanism responsible for this protective effect remains unknown and requires further investigation. Here, we studied the effect of optimised hydrostatic pressure treatment on the global gene expression of mouse oocytes after embryonic genome activation. Based on a gene expression microarray analysis, a significant effect of treatment was observed in 4-cell embryos derived from treated oocytes, revealing a transcriptional footprint of hydrostatic pressure-affected genes. Functional analysis identified numerous genes involved in protein synthesis that were downregulated in 4-cell embryos in response to hydrostatic pressure treatment, suggesting that regulation of translation has a major role in optimised hydrostatic pressure-induced stress tolerance. We present a comprehensive microarray analysis and further delineate a potential mechanism responsible for the protective effect of hydrostatic pressure treatment.

Evaluation of automated global mapping of Reference Soil Groups of WRB2015

NASA Astrophysics Data System (ADS)

Mantel, Stephan; Caspari, Thomas; Kempen, Bas; Schad, Peter; Eberhardt, Einar; Ruiperez Gonzalez, Maria

2017-04-01

SoilGrids is an automated system that provides global predictions for standard numeric soil properties at seven standard depths down to 200 cm, currently at spatial resolutions of 1km and 250m. In addition, the system provides predictions of depth to bedrock and distribution of soil classes based on WRB and USDA Soil Taxonomy (ST). In SoilGrids250m(1), soil classes (WRB, version 2006) consist of the RSG and the first prefix qualifier, whereas in SoilGrids1km(2), the soil class was assessed at RSG level. Automated mapping of World Reference Base (WRB) Reference Soil Groups (RSGs) at a global level has great advantages. Maps can be updated in a short time span with relatively little effort when new data become available. To translate soil names of older versions of FAO/WRB and national classification systems of the source data into names according to WRB 2006, correlation tables are used in SoilGrids. Soil properties and classes are predicted independently from each other. This means that the combinations of soil properties for the same cells or soil property-soil class combinations do not necessarily yield logical combinations when the map layers are studied jointly. The model prediction procedure is robust and probably has a low source of error in the prediction of RSGs. It seems that the quality of the original soil classification in the data and the use of correlation tables are the largest sources of error in mapping the RSG distribution patterns. Predicted patterns of dominant RSGs were evaluated in selected areas and sources of error were identified. Suggestions are made for improvement of WRB2015 RSG distribution predictions in SoilGrids. Keywords: Automated global mapping; World Reference Base for Soil Resources; Data evaluation; Data quality assurance References 1 Hengl T, de Jesus JM, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, et al. (2016) SoilGrids250m: global gridded soil information based on Machine Learning. Earth System Science Data (ESSD), in review. 2 Hengl T, de Jesus JM, MacMillan RA, Batjes NH, Heuvelink GBM, et al. (2014) SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE 9(8): e105992. doi:10.1371/journal.pone.0105992

Global Ionosphere Perturbations Monitored by the Worldwide GPS Network

NASA Technical Reports Server (NTRS)

Ho, C. M.; Manucci, A. T.; Lindqwister, U. J.; Pi, X.

1996-01-01

For the first time, measurements from the Global Positioning System (GPS) worldwide network are employed to study the global ionospheric total electron content(TEC) changes during a magnetic storm (November 26, 1994). These measurements are obtained from more than 60 world-wide GPS stations which continuously receive dual-frequency signals. Based on the delays of the signals, we have generated high resolution global ionospheric maps (GIM) of TEC at 15 minute intervals. Using a differential method comparing storm time maps with quiet time maps, we find that significant TEC increases (the positive effect ) are the major feature in the winter hemisphere during this storm (the maximum percent change relative to quiet times is about 150 percent).

Epigenetics of prostate cancer and the prospect of identification of novel drug targets by RNAi screening of epigenetic enzymes.

PubMed

Björkman, Mari; Rantala, Juha; Nees, Matthias; Kallioniemi, Olli

2010-10-01

Alterations in epigenetic processes probably underlie most human malignancies. Novel genome-wide techniques, such as chromatin immunoprecipitation and high-throughput sequencing, have become state-of-the-art methods to map the epigenomic landscape of development and disease, such as in cancers. Despite these advances, the functional significance of epigenetic enzymes in cancer progression, such as prostate cancer, remain incompletely understood. A comprehensive mapping and functional understanding of the cancer epigenome will hopefully help to facilitate development of novel cancer therapy targets and improve future diagnostics. The authors have developed a novel cell microarray-based high-content siRNA screening technique suitable to address the putative functional role and impact of all known putative and novel epigenetic enzymes in cancer, including prostate cancer.

Protein Microarray Analysis in Patients With Asthma*

PubMed Central

Kim, Hyo-Bin; Kim, Chang-Keun; Iijima, Koji; Kobayashi, Takao; Kita, Hirohito

2010-01-01

Background Microarray technology offers a new opportunity to gain insight into global gene and protein expression profiles in asthma. To identify novel factors produced in the asthmatic airway, we analyzed sputum samples by using a membrane-based human cytokine microarray technology in patients with bronchial asthma (BA). Methods Induced sputum was obtained from 28 BA subjects, 20 nonasthmatic atopic control (AC) subjects, and 38 nonasthmatic nonatopic normal control (NC) subjects. The microarray samples of subjects were randomly selected from nine BA subjects, three AC subjects, and six NC subjects. Sputum supernatants were analyzed using a custom human cytokine array (RayBio Custom Human Cytokine Array; RayBiotech; Norcross, GA) designed to analyze 79 specific cytokines simultaneously. The levels of growth-regulated oncogene (GRO)-α, eotaxin-2, and pulmonary and activation-regulated chemokine (PARC)/CCL18 were measured by sandwich enzyme-linked immunosorbent assays (ELISAs), and eosinophil-derived neurotoxin (EDN) was measured by radioimmunoassay. Results By microarray, the signal intensities for GRO-α, eotaxin-2, and PARC were significantly higher in BA subjects than in AC and NC subjects (p = 0.036, p = 0.042, and p = 0.033, respectively). By ELISA, the sputum PARC protein levels were significantly higher in BA subjects than in AC and NC subjects (p < 0.0001). Furthermore, PARC levels correlated significantly with sputum eosinophil percentages (r = 0.570, p < 0.0001) and the levels of EDN(r = 0.633, p < 0.0001), the regulated upon activation, normal T cell expressed and secreted cytokine (r = 0.440, p < 0.001), interleukin-4 (r = 0.415, p < 0.01), and interferon-γ (r = 0.491, p < 0.001). Conclusions By a nonbiased screening approach, a chemokine, PARC, is elevated in sputum specimens from patients with asthma. PARC may play important roles in development of airway eosinophilic inflammation in asthma. PMID:19017877

Microarray Analyses and Comparisons of Upper or Lower Flanks of Rice Shoot Base Preceding Gravitropic Bending

PubMed Central

Zang, Aiping; Chen, Haiying; Dou, Xianying; Jin, Jing; Cai, Weiming

2013-01-01

Gravitropism is a complex process involving a series of physiological pathways. Despite ongoing research, gravitropism sensing and response mechanisms are not well understood. To identify the key transcripts and corresponding pathways in gravitropism, a whole-genome microarray approach was used to analyze transcript abundance in the shoot base of rice (Oryza sativa sp. japonica) at 0.5 h and 6 h after gravistimulation by horizontal reorientation. Between upper and lower flanks of the shoot base, 167 transcripts at 0.5 h and 1202 transcripts at 6 h were discovered to be significantly different in abundance by 2-fold. Among these transcripts, 48 were found to be changed both at 0.5 h and 6 h, while 119 transcripts were only changed at 0.5 h and 1154 transcripts were changed at 6 h in association with gravitropism. MapMan and PageMan analyses were used to identify transcripts significantly changed in abundance. The asymmetric regulation of transcripts related to phytohormones, signaling, RNA transcription, metabolism and cell wall-related categories between upper and lower flanks were demonstrated. Potential roles of the identified transcripts in gravitropism are discussed. Our results suggest that the induction of asymmetrical transcription, likely as a consequence of gravitropic reorientation, precedes gravitropic bending in the rice shoot base. PMID:24040303

Genome Mapping and Molecular Breeding of Tomato

PubMed Central

Foolad, Majid R.

2007-01-01

The cultivated tomato, Lycopersicon esculentum, is the second most consumed vegetable worldwide and a well-studied crop species in terms of genetics, genomics, and breeding. It is one of the earliest crop plants for which a genetic linkage map was constructed, and currently there are several molecular maps based on crosses between the cultivated and various wild species of tomato. The high-density molecular map, developed based on an L. esculentum × L. pennellii cross, includes more than 2200 markers with an average marker distance of less than 1 cM and an average of 750 kbp per cM. Different types of molecular markers such as RFLPs, AFLPs, SSRs, CAPS, RGAs, ESTs, and COSs have been developed and mapped onto the 12 tomato chromosomes. Markers have been used extensively for identification and mapping of genes and QTLs for many biologically and agriculturally important traits and occasionally for germplasm screening, fingerprinting, and marker-assisted breeding. The utility of MAS in tomato breeding has been restricted largely due to limited marker polymorphism within the cultivated species and economical reasons. Also, when used, MAS has been employed mainly for improving simply-inherited traits and not much for improving complex traits. The latter has been due to unavailability of reliable PCR-based markers and problems with linkage drag. Efforts are being made to develop high-throughput markers with greater resolution, including SNPs. The expanding tomato EST database, which currently includes ∼214 000 sequences, the new microarray DNA chips, and the ongoing sequencing project are expected to aid development of more practical markers. Several BAC libraries have been developed that facilitate map-based cloning of genes and QTLs. Sequencing of the euchromatic portions of the tomato genome is paving the way for comparative and functional analysis of important genes and QTLs. PMID:18364989

Mapping of Epitopes Occurring in Bovine α(s1)-Casein Variants by Peptide Microarray Immunoassay.

PubMed

Lisson, Maria; Erhardt, Georg

2016-01-01

Immunoglobulin E epitope mapping of milk proteins reveals important information about their immunologic properties. Genetic variants of αS1-casein, one of the major allergens in bovine milk, are until now not considered when discussing the allergenic potential. Here we describe the complete procedure to assess the allergenicity of αS1-casein variants B and C, which are frequent in most breeds, starting from milk with identification and purification of casein variants by isoelectric focusing (IEF) and anion-exchange chromatography, followed by in vitro gastrointestinal digestion of the casein variants, identification of the resulting peptides by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), in silico analysis of the variant-specific peptides as allergenic epitopes, and determination of their IgE-binding properties by microarray immunoassay with cow's milk allergic human sera.

A genome-scale map of expression for a mouse brain section obtained using voxelation

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

Chin, Mark H.; Geng, Alex B.; Khan, Arshad H.

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological diseases. We have reconstructed 2- dimensional images of gene expression for 20,000 genes in a coronal slice of the mouse brain at the level of the striatum by using microarrays in combination with voxelation at a resolution of 1 mm3. Good reliability of the microarray results were confirmed using multiple replicates, subsequent quantitative RT-PCR voxelation, mass spectrometry voxelation and publicly available in situ hybridization data. Known and novel genes were identified with expression patterns localized to defined substructures within the brain. In addition, genesmore » with unexpected patterns were identified and cluster analysis identified a set of genes with a gradient of dorsal/ventral expression not restricted to known anatomical boundaries. The genome-scale maps of gene expression obtained using voxelation will be a valuable tool for the neuroscience community.« less

A short treatise concerning a musical approach for the interpretation of gene expression data

PubMed Central

Staege, Martin S.

2015-01-01

Recent technical developments allow the genome-wide and near-complete analysis of gene expression in a given sample, e.g. by usage of high-density DNA microarrays or next generation sequencing. The generated data structure is usually multi-dimensional and requires extensive processing not only for analysis but also for presentation of the results. Today, such data are usually presented graphically, e.g. in the form of heat maps. In the present paper, we propose an alternative form of analysis and presentation which is based on the transformation of gene expression data into sounds that are characterized by their frequency (pitch) and tone duration. Using DNA microarray data from a panel of neuroblastoma and Ewing sarcoma cell lines as well as from Hodgkin’s lymphoma cell lines and normal B cells, we demonstrate that this Gene Expression Music Algorithm (GEMusicA) can be used for discrimination between samples with different biology and for the characterization of differentially expressed genes. PMID:26472273

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

PubMed

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

A High-Density Genetic Map with Array-Based Markers Facilitates Structural and Quantitative Trait Locus Analyses of the Common Wheat Genome

PubMed Central

Iehisa, Julio Cesar Masaru; Ohno, Ryoko; Kimura, Tatsuro; Enoki, Hiroyuki; Nishimura, Satoru; Okamoto, Yuki; Nasuda, Shuhei; Takumi, Shigeo

2014-01-01

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map. PMID:24972598

A high-density genetic map with array-based markers facilitates structural and quantitative trait locus analyses of the common wheat genome.

PubMed

Iehisa, Julio Cesar Masaru; Ohno, Ryoko; Kimura, Tatsuro; Enoki, Hiroyuki; Nishimura, Satoru; Okamoto, Yuki; Nasuda, Shuhei; Takumi, Shigeo

2014-10-01

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data.

PubMed

Ben-Ari Fuchs, Shani; Lieder, Iris; Stelzer, Gil; Mazor, Yaron; Buzhor, Ella; Kaplan, Sergey; Bogoch, Yoel; Plaschkes, Inbar; Shitrit, Alina; Rappaport, Noa; Kohn, Asher; Edgar, Ron; Shenhav, Liraz; Safran, Marilyn; Lancet, Doron; Guan-Golan, Yaron; Warshawsky, David; Shtrichman, Ronit

2016-03-01

Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from "data-to-knowledge-to-innovation," a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ ( geneanalytics.genecards.org ), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®--the human gene database; the MalaCards-the human diseases database; and the PathCards--the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®--the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene-tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell "cards" in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics, pharmacogenomics, vaccinomics, and others yet to emerge on the postgenomics horizon.

Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach.

PubMed

Li, Dongmei; Le Pape, Marc A; Parikh, Nisha I; Chen, Will X; Dye, Timothy D

2013-01-01

Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially expressed genes is large for both normally and non-normally distributed data. Finally, the Resampling-based empirical Bayes Methods are generalizable to next generation sequencing RNA-seq data analysis.

Reconstruction of spatially detailed global map of NH4+ and NO3- application in synthetic nitrogen fertilizer

NASA Astrophysics Data System (ADS)

Nishina, Kazuya; Ito, Akihiko; Hanasaki, Naota; Hayashi, Seiji

2017-02-01

Currently, available historical global N fertilizer map as an input data to global biogeochemical model is still limited and existing maps were not considered NH4+ and NO3- in the fertilizer application rates. This paper provides a method for constructing a new historical global nitrogen fertilizer application map (0.5° × 0.5° resolution) for the period 1961-2010 based on country-specific information from Food and Agriculture Organization statistics (FAOSTAT) and various global datasets. This new map incorporates the fraction of NH4+ (and NO3-) in N fertilizer inputs by utilizing fertilizer species information in FAOSTAT, in which species can be categorized as NH4+- and/or NO3--forming N fertilizers. During data processing, we applied a statistical data imputation method for the missing data (19 % of national N fertilizer consumption) in FAOSTAT. The multiple imputation method enabled us to fill gaps in the time-series data using plausible values using covariates information (year, population, GDP, and crop area). After the imputation, we downscaled the national consumption data to a gridded cropland map. Also, we applied the multiple imputation method to the available chemical fertilizer species consumption, allowing for the estimation of the NH4+ / NO3- ratio in national fertilizer consumption. In this study, the synthetic N fertilizer inputs in 2000 showed a general consistency with the existing N fertilizer map (Potter et al., 2010) in relation to the ranges of N fertilizer inputs. Globally, the estimated N fertilizer inputs based on the sum of filled data increased from 15 to 110 Tg-N during 1961-2010. On the other hand, the global NO3- input started to decline after the late 1980s and the fraction of NO3- in global N fertilizer decreased consistently from 35 to 13 % over a 50-year period. NH4+-forming fertilizers are dominant in most countries; however, the NH4+ / NO3- ratio in N fertilizer inputs shows clear differences temporally and geographically. This new map can be utilized as input data to global model studies and bring new insights for the assessment of historical terrestrial N cycling changes. Datasets available at doi:10.1594/PANGAEA.861203.

THE HOLDRIDGE LIFE ZONES OF THE CONTERMINOUS UNITED STATES IN RELATION TO ECOSYSTEM MAPPING

EPA Science Inventory

Our main goals were to develop a map of the life zones for the conterminous United States, based on the Holdridge Life Zone system as a tool for ecosystem mapping, and to compare the map of Holdridge life zones with other global vegetation classification and mapping efforts.
...

Methylation oligonucleotide microarray: a novel tool to analyze methylation patterns

NASA Astrophysics Data System (ADS)

Hou, Peng; Ji, Meiju; He, Nongyao; Lu, Zuhong

2003-04-01

A new technique to analyze methylation patterns in several adjacent CpG sites was developed and reported here. We selected a 336bp segment of the 5"-untranslated region and the first exon of the p16Ink4a gene, which include the most densely packed CpG fragment of the islands containing 32 CpG dinucleotides, as the investigated target. The probes that include all types of methylation patterns were designed to fabricate a DNA microarray to determine the methylation patterns of seven adjacent CpG dinucleotides sites. High accuracy and reproducibility were observed in several parallel experiments. The results led us to the conclusion that the methylation oligonucleotide microarray can be applied as a novel and powerful tool to map methylation patterns and changes in multiple CpG island loci in a variety of tumors.

Towards a Quasi-global precipitation-induced Landslide Detection System using Remote Sensing Information

NASA Astrophysics Data System (ADS)

Adler, B.; Hong, Y.; Huffman, G.; Negri, A.; Pando, M.

2006-05-01

Landslides and debris flows are one of the most widespread natural hazards on Earth, responsible for thousands of deaths and billions of dollars in property damage per year. Currently, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides. In this study, global landslide susceptibility is mapped using USGS GTOPO30 Digital Elevation, hydrological derivatives (slopes and wetness index etc.) from HYDRO1k data, soil type information downscaled from Digital Soil Map of the World (Sand, Loam, Silt, or Clay etc.), and MODIS land cover/use classification data. These variables are then combined with empirical landslide inventory data, if available, to derive a global landslide susceptibility map at elemental resolution of 1 x 1 km. This map can then be overlain with the driving force, namely rainfall estimates from the TRMM-based Multiple-satellite Precipitation Analysis to identify when areas with significant landslide potential receive heavy rainfall. The relations between rainfall intensity and rainstorm duration are regionally specific and often take the form of a power-law relation. Several empirical landslide-triggering Rainfall Intensity-Duration thresholds are implemented regionally using the 8-year TRMM-based precipitation with or without the global landslide susceptibility map at continuous space and time domain. Finally, the effectiveness of this system is validated by studying several recent deadly landslide/mudslide events. This study aims to build up a prototype quasi-global potential landslide warning system. Spatially-distributed landslide susceptibility maps and regional empirical rainfall intensity-duration thresholds, in combination with real-time rainfall measurements from space and rainfall forecasts from models, will be the basis for this experimental system.

KUTE-BASE: storing, downloading and exporting MIAME-compliant microarray experiments in minutes rather than hours.

PubMed

Draghici, Sorin; Tarca, Adi L; Yu, Longfei; Ethier, Stephen; Romero, Roberto

2008-03-01

The BioArray Software Environment (BASE) is a very popular MIAME-compliant, web-based microarray data repository. However in BASE, like in most other microarray data repositories, the experiment annotation and raw data uploading can be very timeconsuming, especially for large microarray experiments. We developed KUTE (Karmanos Universal daTabase for microarray Experiments), as a plug-in for BASE 2.0 that addresses these issues. KUTE provides an automatic experiment annotation feature and a completely redesigned data work-flow that dramatically reduce the human-computer interaction time. For instance, in BASE 2.0 a typical Affymetrix experiment involving 100 arrays required 4 h 30 min of user interaction time forexperiment annotation, and 45 min for data upload/download. In contrast, for the same experiment, KUTE required only 28 min of user interaction time for experiment annotation, and 3.3 min for data upload/download. http://vortex.cs.wayne.edu/kute/index.html.

Clustering-based spot segmentation of cDNA microarray images.

PubMed

Uslan, Volkan; Bucak, Ihsan Ömür

2010-01-01

Microarrays are utilized as that they provide useful information about thousands of gene expressions simultaneously. In this study segmentation step of microarray image processing has been implemented. Clustering-based methods, fuzzy c-means and k-means, have been applied for the segmentation step that separates the spots from the background. The experiments show that fuzzy c-means have segmented spots of the microarray image more accurately than the k-means.

Next-generation sequencing strategies enable routine detection of balanced chromosome rearrangements for clinical diagnostics and genetic research.

PubMed

Talkowski, Michael E; Ernst, Carl; Heilbut, Adrian; Chiang, Colby; Hanscom, Carrie; Lindgren, Amelia; Kirby, Andrew; Liu, Shangtao; Muddukrishna, Bhavana; Ohsumi, Toshiro K; Shen, Yiping; Borowsky, Mark; Daly, Mark J; Morton, Cynthia C; Gusella, James F

2011-04-08

The contribution of balanced chromosomal rearrangements to complex disorders remains unclear because they are not detected routinely by genome-wide microarrays and clinical localization is imprecise. Failure to consider these events bypasses a potentially powerful complement to single nucleotide polymorphism and copy-number association approaches to complex disorders, where much of the heritability remains unexplained. To capitalize on this genetic resource, we have applied optimized sequencing and analysis strategies to test whether these potentially high-impact variants can be mapped at reasonable cost and throughput. By using a whole-genome multiplexing strategy, rearrangement breakpoints could be delineated at a fraction of the cost of standard sequencing. For rearrangements already mapped regionally by karyotyping and fluorescence in situ hybridization, a targeted approach enabled capture and sequencing of multiple breakpoints simultaneously. Importantly, this strategy permitted capture and unique alignment of up to 97% of repeat-masked sequences in the targeted regions. Genome-wide analyses estimate that only 3.7% of bases should be routinely omitted from genomic DNA capture experiments. Illustrating the power of these approaches, the rearrangement breakpoints were rapidly defined to base pair resolution and revealed unexpected sequence complexity, such as co-occurrence of inversion and translocation as an underlying feature of karyotypically balanced alterations. These findings have implications ranging from genome annotation to de novo assemblies and could enable sequencing screens for structural variations at a cost comparable to that of microarrays in standard clinical practice. Copyright © 2011 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Mars Global Geologic Mapping: About Half Way Done

NASA Technical Reports Server (NTRS)

Tanaka, K. L.; Dohm, J. M.; Irwin, R.; Kolb, E. J.; Skinner, J. A., Jr.; Hare, T. M.

2009-01-01

We are in the third year of a five-year effort to map the geology of Mars using mainly Mars Global Surveyor, Mars Express, and Mars Odyssey imaging and altimetry datasets. Previously, we have reported on details of project management, mapping datasets (local and regional), initial and anticipated mapping approaches, and tactics of map unit delineation and description [1-2]. For example, we have seen how the multiple types and huge quantity of image data as well as more accurate and detailed altimetry data now available allow for broader and deeper geologic perspectives, based largely on improved landform perception, characterization, and analysis. Here, we describe mapping and unit delineation results thus far, a new unit identified in the northern plains, and remaining steps to complete the map.

Global localization of 3D point clouds in building outline maps of urban outdoor environments.

PubMed

Landsiedel, Christian; Wollherr, Dirk

2017-01-01

This paper presents a method to localize a robot in a global coordinate frame based on a sparse 2D map containing outlines of building and road network information and no location prior information. Its input is a single 3D laser scan of the surroundings of the robot. The approach extends the generic chamfer matching template matching technique from image processing by including visibility analysis in the cost function. Thus, the observed building planes are matched to the expected view of the corresponding map section instead of to the entire map, which makes a more accurate matching possible. Since this formulation operates on generic edge maps from visual sensors, the matching formulation can be expected to generalize to other input data, e.g., from monocular or stereo cameras. The method is evaluated on two large datasets collected in different real-world urban settings and compared to a baseline method from literature and to the standard chamfer matching approach, where it shows considerable performance benefits, as well as the feasibility of global localization based on sparse building outline data.

Global transcriptional responses of Bacillus subtilis to xenocoumacin 1.

PubMed

Zhou, T; Zeng, H; Qiu, D; Yang, X; Wang, B; Chen, M; Guo, L; Wang, S

2011-09-01

To determine the global transcriptional response of Bacillus subtilis to an antimicrobial agent, xenocoumacin 1 (Xcn1). Subinhibitory concentration of Xcn1 applied to B. subtilis was measured according to Hutter's method for determining optimal concentrations. cDNA microarray technology was used to study the global transcriptional response of B. subtilis to Xcn1. Real-time RT-PCR was employed to verify alterations in the transcript levels of six genes. The subinhibitory concentration was determined to be 1 μg ml(-1). The microarray data demonstrated that Xcn1 treatment of B. subtilis led to more than a 2.0-fold up-regulation of 480 genes and more than a 2.0-fold down-regulation of 479 genes (q ≤ 0.05). The transcriptional responses of B. subtilis to Xcn1 were determined, and several processes were affected by Xcn1. Additionally, cluster analysis of gene expression profiles after treatment with Xcn1 or 37 previously studied antibiotics indicated that Xcn1 has similar mechanisms of action to protein synthesis inhibitors. These microarray data showed alterations of gene expression in B. subtilis after exposure to Xcn1. From the results, we identified various processes affected by Xcn1. This study provides a whole-genome perspective to elucidate the action of Xcn1 as a potential antimicrobial agent. © 2011 The Authors. Journal of Applied Microbiology © 2011 The Society for Applied Microbiology.

Probabilistic atlas-based segmentation of combined T1-weighted and DUTE MRI for calculation of head attenuation maps in integrated PET/MRI scanners.

PubMed

Poynton, Clare B; Chen, Kevin T; Chonde, Daniel B; Izquierdo-Garcia, David; Gollub, Randy L; Gerstner, Elizabeth R; Batchelor, Tracy T; Catana, Ciprian

2014-01-01

We present a new MRI-based attenuation correction (AC) approach for integrated PET/MRI systems that combines both segmentation- and atlas-based methods by incorporating dual-echo ultra-short echo-time (DUTE) and T1-weighted (T1w) MRI data and a probabilistic atlas. Segmented atlases were constructed from CT training data using a leave-one-out framework and combined with T1w, DUTE, and CT data to train a classifier that computes the probability of air/soft tissue/bone at each voxel. This classifier was applied to segment the MRI of the subject of interest and attenuation maps (μ-maps) were generated by assigning specific linear attenuation coefficients (LACs) to each tissue class. The μ-maps generated with this "Atlas-T1w-DUTE" approach were compared to those obtained from DUTE data using a previously proposed method. For validation of the segmentation results, segmented CT μ-maps were considered to the "silver standard"; the segmentation accuracy was assessed qualitatively and quantitatively through calculation of the Dice similarity coefficient (DSC). Relative change (RC) maps between the CT and MRI-based attenuation corrected PET volumes were also calculated for a global voxel-wise assessment of the reconstruction results. The μ-maps obtained using the Atlas-T1w-DUTE classifier agreed well with those derived from CT; the mean DSCs for the Atlas-T1w-DUTE-based μ-maps across all subjects were higher than those for DUTE-based μ-maps; the atlas-based μ-maps also showed a lower percentage of misclassified voxels across all subjects. RC maps from the atlas-based technique also demonstrated improvement in the PET data compared to the DUTE method, both globally as well as regionally.

Rapid genotyping with DNA micro-arrays for high-density linkage mapping and QTL mapping in common buckwheat (Fagopyrum esculentum Moench)

PubMed Central

Yabe, Shiori; Hara, Takashi; Ueno, Mariko; Enoki, Hiroyuki; Kimura, Tatsuro; Nishimura, Satoru; Yasui, Yasuo; Ohsawa, Ryo; Iwata, Hiroyoshi

2014-01-01

For genetic studies and genomics-assisted breeding, particularly of minor crops, a genotyping system that does not require a priori genomic information is preferable. Here, we demonstrated the potential of a novel array-based genotyping system for the rapid construction of high-density linkage map and quantitative trait loci (QTL) mapping. By using the system, we successfully constructed an accurate, high-density linkage map for common buckwheat (Fagopyrum esculentum Moench); the map was composed of 756 loci and included 8,884 markers. The number of linkage groups converged to eight, which is the basic number of chromosomes in common buckwheat. The sizes of the linkage groups of the P1 and P2 maps were 773.8 and 800.4 cM, respectively. The average interval between adjacent loci was 2.13 cM. The linkage map constructed here will be useful for the analysis of other common buckwheat populations. We also performed QTL mapping for main stem length and detected four QTL. It took 37 days to process 178 samples from DNA extraction to genotyping, indicating the system enables genotyping of genome-wide markers for a few hundred buckwheat plants before the plants mature. The novel system will be useful for genomics-assisted breeding in minor crops without a priori genomic information. PMID:25914583

Rapid genotyping with DNA micro-arrays for high-density linkage mapping and QTL mapping in common buckwheat (Fagopyrum esculentum Moench).

PubMed

Yabe, Shiori; Hara, Takashi; Ueno, Mariko; Enoki, Hiroyuki; Kimura, Tatsuro; Nishimura, Satoru; Yasui, Yasuo; Ohsawa, Ryo; Iwata, Hiroyoshi

2014-12-01

For genetic studies and genomics-assisted breeding, particularly of minor crops, a genotyping system that does not require a priori genomic information is preferable. Here, we demonstrated the potential of a novel array-based genotyping system for the rapid construction of high-density linkage map and quantitative trait loci (QTL) mapping. By using the system, we successfully constructed an accurate, high-density linkage map for common buckwheat (Fagopyrum esculentum Moench); the map was composed of 756 loci and included 8,884 markers. The number of linkage groups converged to eight, which is the basic number of chromosomes in common buckwheat. The sizes of the linkage groups of the P1 and P2 maps were 773.8 and 800.4 cM, respectively. The average interval between adjacent loci was 2.13 cM. The linkage map constructed here will be useful for the analysis of other common buckwheat populations. We also performed QTL mapping for main stem length and detected four QTL. It took 37 days to process 178 samples from DNA extraction to genotyping, indicating the system enables genotyping of genome-wide markers for a few hundred buckwheat plants before the plants mature. The novel system will be useful for genomics-assisted breeding in minor crops without a priori genomic information.

Shrinkage regression-based methods for microarray missing value imputation.

PubMed

Wang, Hsiuying; Chiu, Chia-Chun; Wu, Yi-Ching; Wu, Wei-Sheng

2013-01-01

Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods.

Global radiation maps and their modulation by clouds. - An assessment of limitations and deficiencies in global modelling

NASA Astrophysics Data System (ADS)

Kinne, Stefan; Stubenrauch, Claudia; Raschke, Erhard

2010-05-01

Satellite sensed solar and infrared broadband radiation maps at the top of the atmosphere (ToA) usually serve as reference and constrains to global modelling. Complimentary radiation maps at the surface are less certain, as they require accurate knowledge about atmospheric and environmental properties. Despite differences among multi-decadal data-projects of ISCCP, the SRB and the CERES, their diversity is small in comparison to efforts in global modelling. Based on simulations for the IPCC fourth assessment, clear biases on a regional and seasonal basis are identified and illustrate deficiencies in the representation of clouds. These deficiencies are explored in the context of available cloud data from passive and active remote sensing from space.

Mapping local and global variability in plant trait distributions

DOE PAGES

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc; ...

2017-12-01

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

Mapping local and global variability in plant trait distributions

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

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

Global gene expression in channel catfish after vaccination with an attenuated Edwardsiella ictaluri

USDA-ARS?s Scientific Manuscript database

To understand the global gene expression in channel catfish after immersion vaccination with an attenuated Edwardsiella ictaluri (AquaVac ESCTM), microarray analysis of 65,182 UniGene transcripts were performed. With a filter of false-discovery rate less than 0.05 and fold change greater than 2, a t...

Mars Global Geologic Mapping: Amazonian Results

NASA Technical Reports Server (NTRS)

Tanaka, K. L.; Dohm, J. M.; Irwin, R.; Kolb, E. J.; Skinner, J. A., Jr.; Hare, T. M.

2008-01-01

We are in the second year of a five-year effort to map the geology of Mars using mainly Mars Global Surveyor, Mars Express, and Mars Odyssey imaging and altimetry datasets. Previously, we have reported on details of project management, mapping datasets (local and regional), initial and anticipated mapping approaches, and tactics of map unit delineation and description [1-2]. For example, we have seen how the multiple types and huge quantity of image data as well as more accurate and detailed altimetry data now available allow for broader and deeper geologic perspectives, based largely on improved landform perception, characterization, and analysis. Here, we describe early mapping results, which include updating of previous northern plains mapping [3], including delineation of mainly Amazonian units and regional fault mapping, as well as other advances.

A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae

PubMed Central

Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol; Scalcinati, Gionata; Fagerberg, Linn; Uhlén, Matthias; Nielsen, Jens

2012-01-01

RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated with the Illumina platform, and to perform a cross-platform comparison based on the results obtained through Affymetrix microarray. As a case study for our work we, used the Saccharomyces cerevisiae strain CEN.PK 113-7D, grown under two different conditions (batch and chemostat). Here, we asses the influence of genetic variation on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and TopHat) on S288c genome, the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and NOISeq) and we explored the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays) for gene expression analysis and addresses the contribution of the different steps involved in the analysis of RNA-seq data. PMID:22965124

Determination of Minimum Training Sample Size for Microarray-Based Cancer Outcome Prediction–An Empirical Assessment

PubMed Central

Cheng, Ningtao; Wu, Leihong; Cheng, Yiyu

2013-01-01

The promise of microarray technology in providing prediction classifiers for cancer outcome estimation has been confirmed by a number of demonstrable successes. However, the reliability of prediction results relies heavily on the accuracy of statistical parameters involved in classifiers. It cannot be reliably estimated with only a small number of training samples. Therefore, it is of vital importance to determine the minimum number of training samples and to ensure the clinical value of microarrays in cancer outcome prediction. We evaluated the impact of training sample size on model performance extensively based on 3 large-scale cancer microarray datasets provided by the second phase of MicroArray Quality Control project (MAQC-II). An SSNR-based (scale of signal-to-noise ratio) protocol was proposed in this study for minimum training sample size determination. External validation results based on another 3 cancer datasets confirmed that the SSNR-based approach could not only determine the minimum number of training samples efficiently, but also provide a valuable strategy for estimating the underlying performance of classifiers in advance. Once translated into clinical routine applications, the SSNR-based protocol would provide great convenience in microarray-based cancer outcome prediction in improving classifier reliability. PMID:23861920

Plasma long noncoding RNA expression profile identified by microarray in patients with Crohn's disease.

PubMed

Chen, Dong; Liu, Jiang; Zhao, Hui-Ying; Chen, Yi-Peng; Xiang, Zun; Jin, Xi

2016-05-21

To investigate the expression pattern of plasma long noncoding RNAs (lncRNAs) in Chrohn's disease (CD) patients. Microarray screening and qRT-PCR verification of lncRNAs and mRNAs were performed in CD and control subjects, followed by hierarchy clustering, GO and KEGG pathway analyses. Significantly dysregulated lncRNAs were categorized into subgroups of antisense lncRNAs, enhancer lncRNAs and lincRNAs. To predict the regulatory effect of lncRNAs on mRNAs, a CNC network analysis was performed and cross linked with significantly changed lncRNAs. The overlapping lncRNAs were randomly selected and verified by qRT-PCR in a larger cohort. Initially, there were 1211 up-regulated and 777 down-regulated lncRNAs as well as 1020 up-regulated and 953 down-regulated mRNAs after microarray analysis; a heat map based on these results showed good categorization into the CD and control groups. GUSBP2 and AF113016 had the highest fold change of the up- and down-regulated lncRNAs, whereas TBC1D17 and CCL3L3 had the highest fold change of the up- and down-regulated mRNAs. Six (SNX1, CYFIP2, CD6, CMTM8, STAT4 and IGFBP7) of 10 mRNAs and 8 (NR_033913, NR_038218, NR_036512, NR_049759, NR_033951, NR_045408, NR_038377 and NR_039976) of 14 lncRNAs showed the same change trends on the microarray and qRT-PCR results with statistical significance. Based on the qRT-PCR verified mRNAs, 1358 potential lncRNAs with 2697 positive correlations and 2287 negative correlations were predicted by the CNC network. The plasma lncRNAs profiles provide preliminary data for the non-invasive diagnosis of CD and a resource for further specific lncRNA-mRNA pathway exploration.

Genome-wide polymorphisms and development of a microarray platform to detect genetic variations in Plasmodium yoelii.

PubMed

Nair, Sethu C; Pattaradilokrat, Sittiporn; Zilversmit, Martine M; Dommer, Jennifer; Nagarajan, Vijayaraj; Stephens, Melissa T; Xiao, Wenming; Tan, John C; Su, Xin-Zhuan

2014-01-01

The rodent malaria parasite Plasmodium yoelii is an important model for studying malaria immunity and pathogenesis. One approach for studying malaria disease phenotypes is genetic mapping, which requires typing a large number of genetic markers from multiple parasite strains and/or progeny from genetic crosses. Hundreds of microsatellite (MS) markers have been developed to genotype the P. yoelii genome; however, typing a large number of MS markers can be labor intensive, time consuming, and expensive. Thus, development of high-throughput genotyping tools such as DNA microarrays that enable rapid and accurate large-scale genotyping of the malaria parasite will be highly desirable. In this study, we sequenced the genomes of two P. yoelii strains (33X and N67) and obtained a large number of single nucleotide polymorphisms (SNPs). Based on the SNPs obtained, we designed sets of oligonucleotide probes to develop a microarray that could interrogate ∼11,000 SNPs across the 14 chromosomes of the parasite in a single hybridization. Results from hybridizations of DNA samples of five P. yoelii strains or cloned lines (17XNL, YM, 33X, N67 and N67C) and two progeny from a genetic cross (N67×17XNL) to the microarray showed that the array had a high call rate (∼97%) and accuracy (99.9%) in calling SNPs, providing a simple and reliable tool for typing the P. yoelii genome. Our data show that the P. yoelii genome is highly polymorphic, although isogenic pairs of parasites were also detected. Additionally, our results indicate that the 33X parasite is a progeny of 17XNL (or YM) and an unknown parasite. The highly accurate and reliable microarray developed in this study will greatly facilitate our ability to study the genetic basis of important traits and the disease it causes. Published by Elsevier B.V.

Mapping the Rainforest of the Sea: Global Coral Reef Maps for Global Conservation

NASA Technical Reports Server (NTRS)

Robinson, Julie A.

2006-01-01

Coral reefs are the center of marine biodiversity, yet are under threat with an estimated 60% of coral reef habitats considered at risk by the World Resources Institute. The location and extent of coral reefs in the world are the basic information required for resource management and as a baseline for monitoring change. A NASA sponsored partnership between remote sensing scientists, international agencies and NGOs, has developed a new generation of global reef maps based on data collected by satellites. The effort, dubbed the Millennium Coral Reef Map aims to develop new methods for wide distribution of voluminous satellite data of use to the conservation and management communities. We discuss the tradeoffs between remote sensing data sources, mapping objectives, and the needs for conservation and resource management. SeaWiFS data were used to produce a composite global shallow bathymetry map at 1 km resolution. Landsat 7/ETM+ data acquisition plans were modified to collect global reefs and new operational methods were designed to generate the firstever global coral reef geomorphology map. We discuss the challenges encountered to build these databases and in implementing the geospatial data distribution strategies. Conservation applications include a new assessment of the distribution of the world s marine protected areas (UNEPWCMC), improved spatial resolution in the Reefs at Risk analysis for the Caribbean (WRI), and a global basemap for the Census of Marine Life's OBIS database. The Millennium Coral Reef map and digital image archive will pay significant dividends for local and regional conservation projects around the globe. Complete details of the project are available at http://eol.jsc.nasa.gov/reefs.

mRNA-Based Parallel Detection of Active Methanotroph Populations by Use of a Diagnostic Microarray

PubMed Central

Bodrossy, Levente; Stralis-Pavese, Nancy; Konrad-Köszler, Marianne; Weilharter, Alexandra; Reichenauer, Thomas G.; Schöfer, David; Sessitsch, Angela

2006-01-01

A method was developed for the mRNA-based application of microbial diagnostic microarrays to detect active microbial populations. DNA- and mRNA-based analyses of environmental samples were compared and confirmed via quantitative PCR. Results indicated that mRNA-based microarray analyses may provide additional information on the composition and functioning of microbial communities. PMID:16461725

Mapping 2000 2010 Impervious Surface Change in India Using Global Land Survey Landsat Data

NASA Technical Reports Server (NTRS)

Wang, Panshi; Huang, Chengquan; Brown De Colstoun, Eric C.

2017-01-01

Understanding and monitoring the environmental impacts of global urbanization requires better urban datasets. Continuous field impervious surface change (ISC) mapping using Landsat data is an effective way to quantify spatiotemporal dynamics of urbanization. It is well acknowledged that Landsat-based estimation of impervious surface is subject to seasonal and phenological variations. The overall goal of this paper is to map 200-02010 ISC for India using Global Land Survey datasets and training data only available for 2010. To this end, a method was developed that could transfer the regression tree model developed for mapping 2010 impervious surface to 2000 using an iterative training and prediction (ITP) approach An independent validation dataset was also developed using Google Earth imagery. Based on the reference ISC from the validation dataset, the RMSE of predicted ISC was estimated to be 18.4%. At 95% confidence, the total estimated ISC for India between 2000 and 2010 is 2274.62 +/- 7.84 sq km.

Genome image programs: visualization and interpretation of Escherichia coli microarray experiments.

PubMed

Zimmer, Daniel P; Paliy, Oleg; Thomas, Brian; Gyaneshwar, Prasad; Kustu, Sydney

2004-08-01

We have developed programs to facilitate analysis of microarray data in Escherichia coli. They fall into two categories: manipulation of microarray images and identification of known biological relationships among lists of genes. A program in the first category arranges spots from glass-slide DNA microarrays according to their position in the E. coli genome and displays them compactly in genome order. The resulting genome image is presented in a web browser with an image map that allows the user to identify genes in the reordered image. Another program in the first category aligns genome images from two or more experiments. These images assist in visualizing regions of the genome with common transcriptional control. Such regions include multigene operons and clusters of operons, which are easily identified as strings of adjacent, similarly colored spots. The images are also useful for assessing the overall quality of experiments. The second category of programs includes a database and a number of tools for displaying biological information about many E. coli genes simultaneously rather than one gene at a time, which facilitates identifying relationships among them. These programs have accelerated and enhanced our interpretation of results from E. coli DNA microarray experiments. Examples are given. Copyright 2004 Genetics Society of America

Expanding probe repertoire and improving reproducibility in human genomic hybridization

PubMed Central

Dorman, Stephanie N.; Shirley, Ben C.; Knoll, Joan H. M.; Rogan, Peter K.

2013-01-01

Diagnostic DNA hybridization relies on probes composed of single copy (sc) genomic sequences. Sc sequences in probe design ensure high specificity and avoid cross-hybridization to other regions of the genome, which could lead to ambiguous results that are difficult to interpret. We examine how the distribution and composition of repetitive sequences in the genome affects sc probe performance. A divide and conquer algorithm was implemented to design sc probes. With this approach, sc probes can include divergent repetitive elements, which hybridize to unique genomic targets under higher stringency experimental conditions. Genome-wide custom probe sets were created for fluorescent in situ hybridization (FISH) and microarray genomic hybridization. The scFISH probes were developed for detection of copy number changes within small tumour suppressor genes and oncogenes. The microarrays demonstrated increased reproducibility by eliminating cross-hybridization to repetitive sequences adjacent to probe targets. The genome-wide microarrays exhibited lower median coefficients of variation (17.8%) for two HapMap family trios. The coefficients of variations of commercial probes within 300 nt of a repetitive element were 48.3% higher than the nearest custom probe. Furthermore, the custom microarray called a chromosome 15q11.2q13 deletion more consistently. This method for sc probe design increases probe coverage for FISH and lowers variability in genomic microarrays. PMID:23376933

Bayesian hierarchical modeling for subject-level response classification in peptide microarray immunoassays

PubMed Central

Imholte, Gregory; Gottardo, Raphael

2017-01-01

Summary The peptide microarray immunoassay simultaneously screens sample serum against thousands of peptides, determining the presence of antibodies bound to array probes. Peptide microarrays tiling immunogenic regions of pathogens (e.g. envelope proteins of a virus) are an important high throughput tool for querying and mapping antibody binding. Because of the assay’s many steps, from probe synthesis to incubation, peptide microarray data can be noisy with extreme outliers. In addition, subjects may produce different antibody profiles in response to an identical vaccine stimulus or infection, due to variability among subjects’ immune systems. We present a robust Bayesian hierarchical model for peptide microarray experiments, pepBayes, to estimate the probability of antibody response for each subject/peptide combination. Heavy-tailed error distributions accommodate outliers and extreme responses, and tailored random effect terms automatically incorporate technical effects prevalent in the assay. We apply our model to two vaccine trial datasets to demonstrate model performance. Our approach enjoys high sensitivity and specificity when detecting vaccine induced antibody responses. A simulation study shows an adaptive thresholding classification method has appropriate false discovery rate control with high sensitivity, and receiver operating characteristics generated on vaccine trial data suggest that pepBayes clearly separates responses from non-responses. PMID:27061097

A Lithology Based Map Unit Schema For Onegeology Regional Geologic Map Integration

NASA Astrophysics Data System (ADS)

Moosdorf, N.; Richard, S. M.

2012-12-01

A system of lithogenetic categories for a global lithological map (GLiM, http://www.ifbm.zmaw.de/index.php?id=6460&L=3) has been compiled based on analysis of lithology/genesis categories for regional geologic maps for the entire globe. The scheme is presented for discussion and comment. Analysis of units on a variety of regional geologic maps indicates that units are defined based on assemblages of rock types, as well as their genetic type. In this compilation of continental geology, outcropping surface materials are dominantly sediment/sedimentary rock; major subdivisions of the sedimentary category include clastic sediment, carbonate sedimentary rocks, clastic sedimentary rocks, mixed carbonate and clastic sedimentary rock, colluvium and residuum. Significant areas of mixed igneous and metamorphic rock are also present. A system of global categories to characterize the lithology of regional geologic units is important for Earth System models of matter fluxes to soils, ecosystems, rivers and oceans, and for regional analysis of Earth surface processes at global scale. Because different applications of the classification scheme will focus on different lithologic constituents in mixed units, an ontology-type representation of the scheme that assigns properties to the units in an analyzable manner will be pursued. The OneGeology project is promoting deployment of geologic map services at million scale for all nations. Although initial efforts are commonly simple scanned map WMS services, the intention is to move towards data-based map services that categorize map units with standard vocabularies to allow use of a common map legend for better visual integration of the maps (e.g. see OneGeology Europe, http://onegeology-europe.brgm.fr/ geoportal/ viewer.jsp). Current categorization of regional units with a single lithology from the CGI SimpleLithology (http://resource.geosciml.org/201202/ Vocab2012html/ SimpleLithology201012.html) vocabulary poorly captures the lithologic character of such units in a meaningful way. A lithogenetic unit category scheme accessible as a GeoSciML-portrayal-based OGC Styled Layer Description resource is key to enabling OneGeology (http://oneGeology.org) geologic map services to achieve a high degree of visual harmonization.

The digital global geologic map of Mars: chronostratigraphic ages, topographic and crater morphologic characteristics, and updated resurfacing history

USGS Publications Warehouse

Tanaka, K.L.; Robbins, S.J.; Fortezzo, C.M.; Skinner, J.A.; Hare, T.M.

2014-01-01

A new global geologic map of Mars has been completed in a digital, geographic information system (GIS) format using geospatially controlled altimetry and image data sets. The map reconstructs the geologic history of Mars, which includes many new findings collated in the quarter century since the previous, Viking-based global maps were published, as well as other discoveries that were made during the course of the mapping using new data sets. The technical approach enabled consistent and regulated mapping that is appropriate not only for the map's 1:20,000,000 scale but also for its widespread use by diverse audiences. Each geologic unit outcrop includes basic attributes regarding identity, location, area, crater densities, and chronostratigraphic age. In turn, units are grouped by geographic and lithologic types, which provide synoptic global views of material ages and resurfacing character for the Noachian, Hesperian, and Amazonian periods. As a consequence of more precise and better quality topographic and morphologic data and more complete crater-density dating, our statistical comparisons identify significant refinements for how Martian geologic terrains are characterized. Unit groups show trends in mean elevation and slope that relate to geographic occurrence and geologic origin. In comparison with the previous global geologic map series based on Viking data, the new mapping consists of half the number of units due to simpler, more conservative and globally based approaches to discriminating units. In particular, Noachian highland surfaces overall have high percentages of their areas now dated as an epoch older than in the Viking mapping. Minimally eroded (i.e., pristine) impact craters ≥3 km in diameter occur in greater proportion on Hesperian surfaces. This observation contrasts with a deficit of similarly sized craters on heavily cratered and otherwise degraded Noachian terrain as well as on young Amazonian surfaces. We interpret these as reflecting the relatively stronger, lava-rich, yet less-impacted materials making up much of the younger units. Reconstructions of resurfacing of Mars by its eight geologic epochs using the Hartmann and Neukum chronology models indicate high rates of highland resurfacing during the Noachian (peaking at 0.3 km2/yr during the Middle Noachian), modest rates of volcanism and transition zone and lowland resurfacing during the Hesperian (∼0.1 km2/yr), and low rates of mainly volcanic and polar resurfacing (∼0.01 km2/yr) for most of the Amazonian. Apparent resurfacing increased in the Late Amazonian (∼0.03 km2/yr), perhaps due to better preservation of this latest record.

THE ABRF MARG MICROARRAY SURVEY 2005: TAKING THE PULSE ON THE MICROARRAY FIELD

EPA Science Inventory

Over the past several years microarray technology has evolved into a critical component of any discovery based program. Since 1999, the Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) has conducted biennial surveys designed to generate a pr...

A global map of urban extent from nightlights

DOE PAGES

Zhou, Yuyu; Smith, Steven J.; Zhao, Kaiguang; ...

2015-05-13

Urbanization, one of the major human induced land-cover and land-use changes, has a profound impact on the Earth system including biodiversity, the cycling of water and carbon and exchange of energy and water between Earth’s surface and atmosphere, all affecting weather and climate. Accurate information on urban areas and their spatial distribution at the regional and global scales is important for scientific understanding of their contribution to the changing Earth system, and for practical management and policy decisions. We developed a method to map the urban extent from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime stable-light data atmore » the global level and derived a new global map of 1-km urban extent for year 2000. Based on this map, we found that globally, urban land area is about 0.5% of total land area but ranges widely at regional level from 0.1% in Oceania to 2.3% in Europe. At the country level, urban land area varies from lower than 0.01% to higher than 10%, but is lower than 1% for most (70%) countries. Urbanization follows land mass distribution, as anticipated, with the highest concentration found between 30°N to 45°N latitude and the largest longitudinal peak around 80°W. Based on a sensitivity analysis and comparison with other global urban area products, we found that our global product of urban area provides a reliable estimate of global urban areas and offer the potential of capturing more accurately their spatial and temporal dynamics.« less

The Improved Locating Algorithm of Particle Filter Based on ROS Robot

NASA Astrophysics Data System (ADS)

Fang, Xun; Fu, Xiaoyang; Sun, Ming

2018-03-01

This paperanalyzes basic theory and primary algorithm of the real-time locating system and SLAM technology based on ROS system Robot. It proposes improved locating algorithm of particle filter effectively reduces the matching time of laser radar and map, additional ultra-wideband technology directly accelerates the global efficiency of FastSLAM algorithm, which no longer needs searching on the global map. Meanwhile, the re-sampling has been largely reduced about 5/6 that directly cancels the matching behavior on Roboticsalgorithm.

Anthropogenic Transformation of the Biomes, 1700 to 2000

NASA Astrophysics Data System (ADS)

Ellis, E. C.; Lightman, D.; Klein Goldewijk, K.; Ramankutty, N.

2008-12-01

Current global patterns of terrestrial ecosystem form and process are now predominantly anthropogenic as a result of land use and other direct human interactions with ecosystems. This study investigates anthropogenic transformation of the terrestrial biosphere over the course of the industrial revolution by mapping and characterizing global transitions between wild and anthropogenic biomes between 1700 and 2000. A global map of potential natural vegetation was used to represent wild biomes. Anthropogenic biomes were mapped for 1700, 1800, 1900 and 2000 using rule-based classification of current and historical global data for human population density, urban area and percent land cover by cultivated crops (rainfed, irrigated, and rice) and pastures. By assuming that wild, climate-driven, biome patterns have been relatively constant since 1700, transitions between wild and anthropogenic biomes were characterized between 1700 and 2000 at century intervals. Historical analysis of wild to anthropogenic biome transitions reveal the global transition from a primarily wild to a primarily anthropogenic terrestrial biosphere. Moreover, by mapping and examining global transitions between wild and anthropogenic biome classes, we provide a simple framework for assessing and modeling both past and future global biotic and ecological patterns in the light of the extent, intensity and duration of their modification by humans.

High-Resolution SNP/CGH Microarrays Reveal the Accumulation of Loss of Heterozygosity in Commonly Used Candida albicans Strains

PubMed Central

Abbey, Darren; Hickman, Meleah; Gresham, David; Berman, Judith

2011-01-01

Phenotypic diversity can arise rapidly through loss of heterozygosity (LOH) or by the acquisition of copy number variations (CNV) spanning whole chromosomes or shorter contiguous chromosome segments. In Candida albicans, a heterozygous diploid yeast pathogen with no known meiotic cycle, homozygosis and aneuploidy alter clinical characteristics, including drug resistance. Here, we developed a high-resolution microarray that simultaneously detects ∼39,000 single nucleotide polymorphism (SNP) alleles and ∼20,000 copy number variation loci across the C. albicans genome. An important feature of the array analysis is a computational pipeline that determines SNP allele ratios based upon chromosome copy number. Using the array and analysis tools, we constructed a haplotype map (hapmap) of strain SC5314 to assign SNP alleles to specific homologs, and we used it to follow the acquisition of loss of heterozygosity (LOH) and copy number changes in a series of derived laboratory strains. This high-resolution SNP/CGH microarray and the associated hapmap facilitated the phasing of alleles in lab strains and revealed detrimental genome changes that arose frequently during molecular manipulations of laboratory strains. Furthermore, it provided a useful tool for rapid, high-resolution, and cost-effective characterization of changes in allele diversity as well as changes in chromosome copy number in new C. albicans isolates. PMID:22384363

Global Maps of Lunar Neutron Fluxes from the LEND Instrument

NASA Technical Reports Server (NTRS)

Litvak, M. L.; Mitrofanov, I. G.; Sanin, A.; Malakhov, A.; Boynton, W. V.; Chin, G.; Droege, G.; Evans, L. G.; Garvin, J.; Golovin, D. V.;

Study on Mobile Object Positioning and Alarming System Based on the “Map World” in the Core Area of the Silk Road Economic Belt

NASA Astrophysics Data System (ADS)

Mu, Kai

2017-02-01

The established “Map World” on the National Geographic Information Public Service Platform offers free access to many geographic information in the Core Area of the Silk Road Economic Belt. Considering the special security situation and severe splittism and anti-splittism struggles in the Core Area of the Silk Road Economic Belt, a set of moving target positioning and alarming platform based on J2EE platform and B/S structure was designed and realized by combining the “Map World” data and global navigation satellite system. This platform solves various problems, such as effective combination of Global Navigation Satellite System (GNSS) and “Map World” resources, moving target alarming setting, inquiry of historical routes, system management, etc.

Deciphering the Epigenetic Code: An Overview of DNA Methylation Analysis Methods

PubMed Central

Umer, Muhammad

2013-01-01

Abstract Significance: Methylation of cytosine in DNA is linked with gene regulation, and this has profound implications in development, normal biology, and disease conditions in many eukaryotic organisms. A wide range of methods and approaches exist for its identification, quantification, and mapping within the genome. While the earliest approaches were nonspecific and were at best useful for quantification of total methylated cytosines in the chunk of DNA, this field has seen considerable progress and development over the past decades. Recent Advances: Methods for DNA methylation analysis differ in their coverage and sensitivity, and the method of choice depends on the intended application and desired level of information. Potential results include global methyl cytosine content, degree of methylation at specific loci, or genome-wide methylation maps. Introduction of more advanced approaches to DNA methylation analysis, such as microarray platforms and massively parallel sequencing, has brought us closer to unveiling the whole methylome. Critical Issues: Sensitive quantification of DNA methylation from degraded and minute quantities of DNA and high-throughput DNA methylation mapping of single cells still remain a challenge. Future Directions: Developments in DNA sequencing technologies as well as the methods for identification and mapping of 5-hydroxymethylcytosine are expected to augment our current understanding of epigenomics. Here we present an overview of methodologies available for DNA methylation analysis with special focus on recent developments in genome-wide and high-throughput methods. While the application focus relates to cancer research, the methods are equally relevant to broader issues of epigenetics and redox science in this special forum. Antioxid. Redox Signal. 18, 1972–1986. PMID:23121567

Transcriptional analysis of the Arabidopsis ovule by massively parallel signature sequencing

PubMed Central

Sánchez-León, Nidia; Arteaga-Vázquez, Mario; Alvarez-Mejía, César; Mendiola-Soto, Javier; Durán-Figueroa, Noé; Rodríguez-Leal, Daniel; Rodríguez-Arévalo, Isaac; García-Campayo, Vicenta; García-Aguilar, Marcelina; Olmedo-Monfil, Vianey; Arteaga-Sánchez, Mario; Martínez de la Vega, Octavio; Nobuta, Kan; Vemaraju, Kalyan; Meyers, Blake C.; Vielle-Calzada, Jean-Philippe

2012-01-01

The life cycle of flowering plants alternates between a predominant sporophytic (diploid) and an ephemeral gametophytic (haploid) generation that only occurs in reproductive organs. In Arabidopsis thaliana, the female gametophyte is deeply embedded within the ovule, complicating the study of the genetic and molecular interactions involved in the sporophytic to gametophytic transition. Massively parallel signature sequencing (MPSS) was used to conduct a quantitative large-scale transcriptional analysis of the fully differentiated Arabidopsis ovule prior to fertilization. The expression of 9775 genes was quantified in wild-type ovules, additionally detecting >2200 new transcripts mapping to antisense or intergenic regions. A quantitative comparison of global expression in wild-type and sporocyteless (spl) individuals resulted in 1301 genes showing 25-fold reduced or null activity in ovules lacking a female gametophyte, including those encoding 92 signalling proteins, 75 transcription factors, and 72 RNA-binding proteins not reported in previous studies based on microarray profiling. A combination of independent genetic and molecular strategies confirmed the differential expression of 28 of them, showing that they are either preferentially active in the female gametophyte, or dependent on the presence of a female gametophyte to be expressed in sporophytic cells of the ovule. Among 18 genes encoding pentatricopeptide-repeat proteins (PPRs) that show transcriptional activity in wild-type but not spl ovules, CIHUATEOTL (At4g38150) is specifically expressed in the female gametophyte and necessary for female gametogenesis. These results expand the nature of the transcriptional universe present in the ovule of Arabidopsis, and offer a large-scale quantitative reference of global expression for future genomic and developmental studies. PMID:22442422

Transcriptional analysis of the Arabidopsis ovule by massively parallel signature sequencing.

PubMed

Sánchez-León, Nidia; Arteaga-Vázquez, Mario; Alvarez-Mejía, César; Mendiola-Soto, Javier; Durán-Figueroa, Noé; Rodríguez-Leal, Daniel; Rodríguez-Arévalo, Isaac; García-Campayo, Vicenta; García-Aguilar, Marcelina; Olmedo-Monfil, Vianey; Arteaga-Sánchez, Mario; de la Vega, Octavio Martínez; Nobuta, Kan; Vemaraju, Kalyan; Meyers, Blake C; Vielle-Calzada, Jean-Philippe

2012-06-01

The life cycle of flowering plants alternates between a predominant sporophytic (diploid) and an ephemeral gametophytic (haploid) generation that only occurs in reproductive organs. In Arabidopsis thaliana, the female gametophyte is deeply embedded within the ovule, complicating the study of the genetic and molecular interactions involved in the sporophytic to gametophytic transition. Massively parallel signature sequencing (MPSS) was used to conduct a quantitative large-scale transcriptional analysis of the fully differentiated Arabidopsis ovule prior to fertilization. The expression of 9775 genes was quantified in wild-type ovules, additionally detecting >2200 new transcripts mapping to antisense or intergenic regions. A quantitative comparison of global expression in wild-type and sporocyteless (spl) individuals resulted in 1301 genes showing 25-fold reduced or null activity in ovules lacking a female gametophyte, including those encoding 92 signalling proteins, 75 transcription factors, and 72 RNA-binding proteins not reported in previous studies based on microarray profiling. A combination of independent genetic and molecular strategies confirmed the differential expression of 28 of them, showing that they are either preferentially active in the female gametophyte, or dependent on the presence of a female gametophyte to be expressed in sporophytic cells of the ovule. Among 18 genes encoding pentatricopeptide-repeat proteins (PPRs) that show transcriptional activity in wild-type but not spl ovules, CIHUATEOTL (At4g38150) is specifically expressed in the female gametophyte and necessary for female gametogenesis. These results expand the nature of the transcriptional universe present in the ovule of Arabidopsis, and offer a large-scale quantitative reference of global expression for future genomic and developmental studies.

Predicting features of breast cancer with gene expression patterns.

PubMed

Lu, Xuesong; Lu, Xin; Wang, Zhigang C; Iglehart, J Dirk; Zhang, Xuegong; Richardson, Andrea L

2008-03-01

Data from gene expression arrays hold an enormous amount of biological information. We sought to determine if global gene expression in primary breast cancers contained information about biologic, histologic, and anatomic features of the disease in individual patients. Microarray data from the tumors of 129 patients were analyzed for the ability to predict biomarkers [estrogen receptor (ER) and HER2], histologic features [grade and lymphatic-vascular invasion (LVI)], and stage parameters (tumor size and lymph node metastasis). Multiple statistical predictors were used and the prediction accuracy was determined by cross-validation error rate; multidimensional scaling (MDS) allowed visualization of the predicted states under study. Models built from gene expression data accurately predict ER and HER2 status, and divide tumor grade into high-grade and low-grade clusters; intermediate-grade tumors are not a unique group. In contrast, gene expression data is inaccurate at predicting tumor size, lymph node status or LVI. The best model for prediction of nodal status included tumor size, LVI status and pathologically defined tumor subtype (based on combinations of ER, HER2, and grade); the addition of microarray-based prediction to this model failed to improve the prediction accuracy. Global gene expression supports a binary division of ER, HER2, and grade, clearly separating tumors into two categories; intermediate values for these bio-indicators do not define intermediate tumor subsets. Results are consistent with a model of regional metastasis that depends on inherent biologic differences in metastatic propensity between breast cancer subtypes, upon which time and chance then operate.

Procedures for woody vegetation surveys in the Kazgail rural council area, Kordofan, Sudan

USGS Publications Warehouse

Falconer, Allan; Cross, Matthew D.; Orr, Donald G.

1990-01-01

Efforts to reforest parts of the Kordofan Province of Sudan are receiving support from international development agencies. These efforts include planning and implementing reforestation activities that require the collection of natural resources and socioeconomic data, and the preparation of base maps. A combination of remote sensing, geographic information system and global positioning systems procedures are used in this study to meet these requirements.Remote sensing techniques were used to provide base maps and to guide the compilation of vegetation resources maps. These techniques provided a rapid and efficient method for documenting available resources. Pocket‐sized global positioning system units were used to establish the location of field data collected for mapping and resource analysis. A microcomputer data management system tabulated and displayed the field data. The resulting system for data analysis, management, and planning has been adopted for the mapping and inventory of the Gum Belt of Sudan.

The Updating of Geospatial Base Data

NASA Astrophysics Data System (ADS)

Alrajhi, Muhamad N.; Konecny, Gottfried

2018-04-01

Topopographic mapping issues concern the area coverage at different scales and their age. The age of the map is determined by the system of updating. The United Nations (UNGGIM) have attempted to track the global map coverage at various scale ranges, which has greatly improved in recent decades. However the poor state of updating of base maps is still a global problem. In Saudi Arabia large scale mapping is carried out for all urban, suburban and rural areas by aerial surveys. Updating is carried out by remapping every 5 to 10 years. Due to the rapid urban development this is not satisfactory, but faster update methods are forseen by use of high resolution satellite imagery and the improvement of object oriented geodatabase structures, which will permit to utilize various survey technologies to update the photogrammetry established geodatabases. The longterm goal is to create an geodata infrastructure, which exists in Great Britain or Germany.

Global mapping of binding sites for Nrf2 identifies novel targets in cell survival response through ChIP-Seq profiling and network analysis

PubMed Central

Malhotra, Deepti; Portales-Casamar, Elodie; Singh, Anju; Srivastava, Siddhartha; Arenillas, David; Happel, Christine; Shyr, Casper; Wakabayashi, Nobunao; Kensler, Thomas W.; Wasserman, Wyeth W.; Biswal, Shyam

2010-01-01

The Nrf2 (nuclear factor E2 p45-related factor 2) transcription factor responds to diverse oxidative and electrophilic environmental stresses by circumventing repression by Keap1, translocating to the nucleus, and activating cytoprotective genes. Nrf2 responses provide protection against chemical carcinogenesis, chronic inflammation, neurodegeneration, emphysema, asthma and sepsis in murine models. Nrf2 regulates the expression of a plethora of genes that detoxify oxidants and electrophiles and repair or remove damaged macromolecules, such as through proteasomal processing. However, many direct targets of Nrf2 remain undefined. Here, mouse embryonic fibroblasts (MEF) with either constitutive nuclear accumulation (Keap1−/−) or depletion (Nrf2−/−) of Nrf2 were utilized to perform chromatin-immunoprecipitation with parallel sequencing (ChIP-Seq) and global transcription profiling. This unique Nrf2 ChIP-Seq dataset is highly enriched for Nrf2-binding motifs. Integrating ChIP-Seq and microarray analyses, we identified 645 basal and 654 inducible direct targets of Nrf2, with 244 genes at the intersection. Modulated pathways in stress response and cell proliferation distinguish the inducible and basal programs. Results were confirmed in an in vivo stress model of cigarette smoke-exposed mice. This study reveals global circuitry of the Nrf2 stress response emphasizing Nrf2 as a central node in cell survival response. PMID:20460467

Genomic Approach to Study Floral Development Genes in Rosa sp.

PubMed Central

Chauvet, Aurélie; Maene, Marion; Pécrix, Yann; Yang, Shu-Hua; Jeauffre, Julien; Thouroude, Tatiana; Boltz, Véronique; Martin-Magniette, Marie-Laure; Janczarski, Stéphane; Legeai, Fabrice; Renou, Jean-Pierre; Vergne, Philippe; Le Bris, Manuel; Foucher, Fabrice; Bendahmane, Mohammed

2011-01-01

Cultivated for centuries, the varieties of rose have been selected based on a number of flower traits. Understanding the genetic and molecular basis that contributes to these traits will impact on future improvements for this economically important ornamental plant. In this study, we used scanning electron microscopy and sections of meristems and flowers to establish a precise morphological calendar from early rose flower development stages to senescing flowers. Global gene expression was investigated from floral meristem initiation up to flower senescence in three rose genotypes exhibiting contrasted floral traits including continuous versus once flowering and simple versus double flower architecture, using a newly developed Affymetrix microarray (Rosa1_Affyarray) tool containing sequences representing 4765 unigenes expressed during flower development. Data analyses permitted the identification of genes associated with floral transition, floral organs initiation up to flower senescence. Quantitative real time PCR analyses validated the mRNA accumulation changes observed in microarray hybridizations for a selection of 24 genes expressed at either high or low levels. Our data describe the early flower development stages in Rosa sp, the production of a rose microarray and demonstrate its usefulness and reliability to study gene expression during extensive development phases, from the vegetative meristem to the senescent flower. PMID:22194838

Analysis of Protein Expression in Cell Microarrays: A Tool for Antibody-based Proteomics

PubMed Central

Andersson, Ann-Catrin; Strömberg, Sara; Bäckvall, Helena; Kampf, Caroline; Uhlen, Mathias; Wester, Kenneth; Pontén, Fredrik

2006-01-01

Tissue microarray (TMA) technology provides a possibility to explore protein expression patterns in a multitude of normal and disease tissues in a high-throughput setting. Although TMAs have been used for analysis of tissue samples, robust methods for studying in vitro cultured cell lines and cell aspirates in a TMA format have been lacking. We have adopted a technique to homogeneously distribute cells in an agarose gel matrix, creating an artificial tissue. This enables simultaneous profiling of protein expression in suspension- and adherent-grown cell samples assembled in a microarray. In addition, the present study provides an optimized strategy for the basic laboratory steps to efficiently produce TMAs. Presented modifications resulted in an improved quality of specimens and a higher section yield compared with standard TMA production protocols. Sections from the generated cell TMAs were tested for immunohistochemical staining properties using 20 well-characterized antibodies. Comparison of immunoreactivity in cultured dispersed cells and corresponding cells in tissue samples showed congruent results for all tested antibodies. We conclude that a modified TMA technique, including cell samples, provides a valuable tool for high-throughput analysis of protein expression, and that this technique can be used for global approaches to explore the human proteome. PMID:16957166

Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles

PubMed Central

Thaden, Joshua T; Mogno, Ilaria; Wierzbowski, Jamey; Cottarel, Guillaume; Kasif, Simon; Collins, James J; Gardner, Timothy S

2007-01-01

Machine learning approaches offer the potential to systematically identify transcriptional regulatory interactions from a compendium of microarray expression profiles. However, experimental validation of the performance of these methods at the genome scale has remained elusive. Here we assess the global performance of four existing classes of inference algorithms using 445 Escherichia coli Affymetrix arrays and 3,216 known E. coli regulatory interactions from RegulonDB. We also developed and applied the context likelihood of relatedness (CLR) algorithm, a novel extension of the relevance networks class of algorithms. CLR demonstrates an average precision gain of 36% relative to the next-best performing algorithm. At a 60% true positive rate, CLR identifies 1,079 regulatory interactions, of which 338 were in the previously known network and 741 were novel predictions. We tested the predicted interactions for three transcription factors with chromatin immunoprecipitation, confirming 21 novel interactions and verifying our RegulonDB-based performance estimates. CLR also identified a regulatory link providing central metabolic control of iron transport, which we confirmed with real-time quantitative PCR. The compendium of expression data compiled in this study, coupled with RegulonDB, provides a valuable model system for further improvement of network inference algorithms using experimental data. PMID:17214507

Surface invasive cleavage assay on a maskless light-directed diamond DNA microarray for genome-wide human SNP mapping.

PubMed

Nie, Bei; Yang, Min; Fu, Weiling; Liang, Zhiqing

2015-07-07

The surface invasive cleavage assay, because of its innate accuracy and ability for self-signal amplification, provides a potential route for the mapping of hundreds of thousands of human SNP sites. However, its performance on a high density DNA array has not yet been established, due to the unusual "hairpin" probe design on the microarray and the lack of chemical stability of commercially available substrates. Here we present an applicable method to implement a nanocrystalline diamond thin film as an alternative substrate for fabricating an addressable DNA array using maskless light-directed photochemistry, producing the most chemically stable and biocompatible system for genetic analysis and enzymatic reactions. The surface invasive cleavage reaction, followed by degenerated primer ligation and post-rolling circle amplification is consecutively performed on the addressable diamond DNA array, accurately mapping SNP sites from PCR-amplified human genomic target DNA. Furthermore, a specially-designed DNA array containing dual probes in the same pixel is fabricated by following a reverse light-directed DNA synthesis protocol. This essentially enables us to decipher thousands of SNP alleles in a single-pot reaction by the simple addition of enzyme, target and reaction buffers.

Comparative Analysis of Phenolic Compound Characterization and Their Biosynthesis Genes between Two Diverse Bread Wheat (Triticum aestivum) Varieties Differing for Chapatti (Unleavened Flat Bread) Quality.

PubMed

Sharma, Monica; Sandhir, Rajat; Singh, Anuradha; Kumar, Pankaj; Mishra, Ankita; Jachak, Sanjay; Singh, Sukhvinder P; Singh, Jagdeep; Roy, Joy

2016-01-01

Phenolic compounds (PCs) affect the bread quality and can also affect the other types of end-use food products such as chapatti (unleavened flat bread), now globally recognized wheat-based food product. The detailed analysis of PCs and their biosynthesis genes in diverse bread wheat ( Triticum aestivum ) varieties differing for chapatti quality have not been studied. In this study, the identification and quantification of PCs using UPLC-QTOF-MS and/or MS/MS and functional genomics techniques such as microarrays and qRT-PCR of their biosynthesis genes have been studied in a good chapatti variety, "C 306" and a poor chapatti variety, "Sonalika." About 80% (69/87) of plant phenolic compounds were tentatively identified in these varieties. Nine PCs (hinokinin, coutaric acid, fertaric acid, p-coumaroylqunic acid, kaempferide, isorhamnetin, epigallocatechin gallate, methyl isoorientin-2'-O-rhamnoside, and cyanidin-3-rutinoside) were identified only in the good chapatti variety and four PCs (tricin, apigenindin, quercetin-3-O-glucuronide, and myricetin-3-glucoside) in the poor chapatti variety. Therefore, about 20% of the identified PCs are unique to each other and may be "variety or genotype" specific PCs. Fourteen PCs used for quantification showed high variation between the varieties. The microarray data of 44 phenolic compound biosynthesis genes and 17 of them on qRT-PCR showed variation in expression level during seed development and majority of them showed low expression in the good chapatti variety. The expression pattern in the good chapatti variety was largely in agreement with that of phenolic compounds. The level of variation of 12 genes was high between the good and poor chapatti quality varieties and has potential in development of markers. The information generated in this study can be extended onto a larger germplasm set for development of molecular markers using QTL and/or association mapping approaches for their application in wheat breeding.

Comparative Analysis of Phenolic Compound Characterization and Their Biosynthesis Genes between Two Diverse Bread Wheat (Triticum aestivum) Varieties Differing for Chapatti (Unleavened Flat Bread) Quality

PubMed Central

Sharma, Monica; Sandhir, Rajat; Singh, Anuradha; Kumar, Pankaj; Mishra, Ankita; Jachak, Sanjay; Singh, Sukhvinder P.; Singh, Jagdeep; Roy, Joy

2016-01-01

Phenolic compounds (PCs) affect the bread quality and can also affect the other types of end-use food products such as chapatti (unleavened flat bread), now globally recognized wheat-based food product. The detailed analysis of PCs and their biosynthesis genes in diverse bread wheat (Triticum aestivum) varieties differing for chapatti quality have not been studied. In this study, the identification and quantification of PCs using UPLC-QTOF-MS and/or MS/MS and functional genomics techniques such as microarrays and qRT-PCR of their biosynthesis genes have been studied in a good chapatti variety, “C 306” and a poor chapatti variety, “Sonalika.” About 80% (69/87) of plant phenolic compounds were tentatively identified in these varieties. Nine PCs (hinokinin, coutaric acid, fertaric acid, p-coumaroylqunic acid, kaempferide, isorhamnetin, epigallocatechin gallate, methyl isoorientin-2′-O-rhamnoside, and cyanidin-3-rutinoside) were identified only in the good chapatti variety and four PCs (tricin, apigenindin, quercetin-3-O-glucuronide, and myricetin-3-glucoside) in the poor chapatti variety. Therefore, about 20% of the identified PCs are unique to each other and may be “variety or genotype” specific PCs. Fourteen PCs used for quantification showed high variation between the varieties. The microarray data of 44 phenolic compound biosynthesis genes and 17 of them on qRT-PCR showed variation in expression level during seed development and majority of them showed low expression in the good chapatti variety. The expression pattern in the good chapatti variety was largely in agreement with that of phenolic compounds. The level of variation of 12 genes was high between the good and poor chapatti quality varieties and has potential in development of markers. The information generated in this study can be extended onto a larger germplasm set for development of molecular markers using QTL and/or association mapping approaches for their application in wheat breeding. PMID:28018403

The tissue microarray OWL schema: An open-source tool for sharing tissue microarray data

PubMed Central

Kang, Hyunseok P.; Borromeo, Charles D.; Berman, Jules J.; Becich, Michael J.

2010-01-01

Background: Tissue microarrays (TMAs) are enormously useful tools for translational research, but incompatibilities in database systems between various researchers and institutions prevent the efficient sharing of data that could help realize their full potential. Resource Description Framework (RDF) provides a flexible method to represent knowledge in triples, which take the form Subject-Predicate-Object. All data resources are described using Uniform Resource Identifiers (URIs), which are global in scope. We present an OWL (Web Ontology Language) schema that expands upon the TMA data exchange specification to address this issue and assist in data sharing and integration. Methods: A minimal OWL schema was designed containing only concepts specific to TMA experiments. More general data elements were incorporated from predefined ontologies such as the NCI thesaurus. URIs were assigned using the Linked Data format. Results: We present examples of files utilizing the schema and conversion of XML data (similar to the TMA DES) to OWL. Conclusion: By utilizing predefined ontologies and global unique identifiers, this OWL schema provides a solution to the limitations of XML, which represents concepts defined in a localized setting. This will help increase the utilization of tissue resources, facilitating collaborative translational research efforts. PMID:20805954

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies.

PubMed

Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

2006-09-20

High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option.GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike.

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies

PubMed Central

Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

2006-01-01

Background High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option. GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. Results MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. Conclusion MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike. PMID:16987406

The prevalence of chromosomal deletions relating to developmental delay and/or intellectual disability in human euploid blastocysts.

PubMed

He, Wenyin; Sun, Xiaofang; Liu, Lian; Li, Man; Jin, Hua; Wang, Wei-Hua

2014-01-01

Chromosomal anomalies in human embryos produced by in vitro fertilization are very common, which include numerical (aneuploidy) and structural (deletion, duplication or others) anomalies. Our previous study indicated that chromosomal deletion(s) is the most common structural anomaly accounting for approximately 8% of euploid blastocysts. It is still unknown if these deletions in human euploid blastocysts have clinical significance. In this study, we analyzed 15 previously diagnosed euploid blastocysts that had chromosomal deletion(s) using Agilent oligonucleotide DNA microarray platform and localized the gene location in each deletion. Then, we used OMIM gene map and phenotype database to investigate if these deletions are related with some important genes that cause genetic diseases, especially developmental delay or intellectual disability. As results, we found that the detectable chromosomal deletion size with Agilent microarray is above 2.38 Mb, while the deletions observed in human blastocysts are between 11.6 to 103 Mb. With OMIM gene map and phenotype database information, we found that deletions can result in loss of 81-464 genes. Out of these genes, 34-149 genes are related with known genetic problems. Furthermore, we found that 5 out of 15 samples lost genes in the deleted region, which were related to developmental delay and/or intellectual disability. In conclusion, our data indicates that all human euploid blastocysts with chromosomal deletion(s) are abnormal and transfer of these embryos may cause birth defects and/or developmental and intellectual disabilities. Therefore, the embryos with chromosomal deletion revealed by DNA microarray should not be transferred to the patients, or further gene map and/or phenotype seeking is necessary before making a final decision.

Mapping Tree Density at the Global Scale

NASA Astrophysics Data System (ADS)

Covey, K. R.; Crowther, T. W.; Glick, H.; Bettigole, C.; Bradford, M.

2015-12-01

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global-scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical regions, with 0.74, and 0.61 trillion in boreal and temperate regions, respectively. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming impact of humans across most of the world. Based on our projected tree densities, we estimate that deforestation is currently responsible for removing over 15 billion trees each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Mapping tree density at a global scale

NASA Astrophysics Data System (ADS)

Crowther, T. W.; Glick, H. B.; Covey, K. R.; Bettigole, C.; Maynard, D. S.; Thomas, S. M.; Smith, J. R.; Hintler, G.; Duguid, M. C.; Amatulli, G.; Tuanmu, M.-N.; Jetz, W.; Salas, C.; Stam, C.; Piotto, D.; Tavani, R.; Green, S.; Bruce, G.; Williams, S. J.; Wiser, S. K.; Huber, M. O.; Hengeveld, G. M.; Nabuurs, G.-J.; Tikhonova, E.; Borchardt, P.; Li, C.-F.; Powrie, L. W.; Fischer, M.; Hemp, A.; Homeier, J.; Cho, P.; Vibrans, A. C.; Umunay, P. M.; Piao, S. L.; Rowe, C. W.; Ashton, M. S.; Crane, P. R.; Bradford, M. A.

2015-09-01

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical forests, with 0.74 trillion in boreal regions and 0.61 trillion in temperate regions. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming effect of humans across most of the world. Based on our projected tree densities, we estimate that over 15 billion trees are cut down each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Mapping tree density at a global scale.

PubMed

Crowther, T W; Glick, H B; Covey, K R; Bettigole, C; Maynard, D S; Thomas, S M; Smith, J R; Hintler, G; Duguid, M C; Amatulli, G; Tuanmu, M-N; Jetz, W; Salas, C; Stam, C; Piotto, D; Tavani, R; Green, S; Bruce, G; Williams, S J; Wiser, S K; Huber, M O; Hengeveld, G M; Nabuurs, G-J; Tikhonova, E; Borchardt, P; Li, C-F; Powrie, L W; Fischer, M; Hemp, A; Homeier, J; Cho, P; Vibrans, A C; Umunay, P M; Piao, S L; Rowe, C W; Ashton, M S; Crane, P R; Bradford, M A

2015-09-10

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical forests, with 0.74 trillion in boreal regions and 0.61 trillion in temperate regions. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming effect of humans across most of the world. Based on our projected tree densities, we estimate that over 15 billion trees are cut down each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Photogrammetric portrayal of Mars topography.

USGS Publications Warehouse

Wu, S.S.C.

1979-01-01

Special photogrammetric techniques have been developed to portray Mars topography, using Mariner and Viking imaging and nonimaging topographic information and earth-based radar data. Topography is represented by the compilation of maps at three scales: global, intermediate, and very large scale. The global map is a synthesis of topographic information obtained from Mariner 9 and earth-based radar, compiled at a scale of 1:25,000,000 with a contour interval of 1 km; it gives a broad quantitative view of the planet. At intermediate scales, Viking Orbiter photographs of various resolutions are used to compile detailed contour maps of a broad spectrum of prominent geologic features; a contour interval as small as 20 m has been obtained from very high resolution orbital photography. Imagery from the Viking lander facsimile cameras permits construction of detailed, very large scale (1:10) topographic maps of the terrain surrounding the two landers; these maps have a contour interval of 1 cm. This paper presents several new detailed topographic maps of Mars.-Author

Photogrammetric portrayal of Mars topography

NASA Technical Reports Server (NTRS)

Wu, S. S. C.

1979-01-01

Special photogrammetric techniques have been developed to portray Mars topography, using Mariner and Viking imaging and nonimaging topographic information and earth-based radar data. Topography is represented by the compilation of maps at three scales: global, intermediate, and very large scale. The global map is a synthesis of topographic information obtained from Mariner 9 and earth-based radar, compiled at a scale of 1:25,000,000 with a contour interval of 1 km; it gives a broad quantitative view of the planet. At intermediate scales, Viking Orbiter photographs of various resolutions are used to compile detailed contour maps of a broad spectrum of prominent geologic features; a contour interval as small as 20 m has been obtained from very high resolution orbital photography. Imagery from the Viking lander facsimile cameras permits construction of detailed, very large scale (1:10) topographic maps of the terrain surrounding the two landers; these maps have a contour interval of 1 cm. This paper presents several new detailed topographic maps of Mars.

Map of Life - A Dashboard for Monitoring Planetary Species Distributions

NASA Astrophysics Data System (ADS)

Jetz, W.

2016-12-01

Geographic information about biodiversity is vital for understanding the many services nature provides and their potential changes, yet remains unreliable and often insufficient. By integrating a wide range of knowledge about species distributions and their dynamics over time, Map of Life supports global biodiversity education, monitoring, research and decision-making. Built on a scalable web platform geared for large biodiversity and environmental data, Map of Life endeavors provides species range information globally and species lists for any area. With data and technology provided by NASA and Google Earth Engine, tools under development use remote sensing-based environmental layers to enable on-the-fly predictions of species distributions, range changes, and early warning signals for threatened species. The ultimate vision is a globally connected, collaborative knowledge- and tool-base for regional and local biodiversity decision-making, education, monitoring, and projection. For currently available tools, more information and to follow progress, go to MOL.org.

Spot detection and image segmentation in DNA microarray data.

PubMed

Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune

2005-01-01

Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

Microarray platform for omics analysis

NASA Astrophysics Data System (ADS)

Mecklenburg, Michael; Xie, Bin

2001-09-01

Microarray technology has revolutionized genetic analysis. However, limitations in genome analysis has lead to renewed interest in establishing 'omic' strategies. As we enter the post-genomic era, new microarray technologies are needed to address these new classes of 'omic' targets, such as proteins, as well as lipids and carbohydrates. We have developed a microarray platform that combines self- assembling monolayers with the biotin-streptavidin system to provide a robust, versatile immobilization scheme. A hydrophobic film is patterned on the surface creating an array of tension wells that eliminates evaporation effects thereby reducing the shear stress to which biomolecules are exposed to during immobilization. The streptavidin linker layer makes it possible to adapt and/or develop microarray based assays using virtually any class of biomolecules including: carbohydrates, peptides, antibodies, receptors, as well as them ore traditional DNA based arrays. Our microarray technology is designed to furnish seamless compatibility across the various 'omic' platforms by providing a common blueprint for fabricating and analyzing arrays. The prototype microarray uses a microscope slide footprint patterned with 2 by 96 flat wells. Data on the microarray platform will be presented.

Global map of heat flow on a 2 degree grid - digitally available

NASA Astrophysics Data System (ADS)

Davies, J. Huw

2014-05-01

A global map of surface heat flow is developed on a 2° by 2° equal area grid, and is made available digitally. It is based on a global heat flow data set of over 38,000 measurements, very similar to that used in Davies & Davies (2010). The map consists of three components. Firstly, in regions of young ocean crust (<67.7Ma) the model estimate uses a half-space conduction model based on the age of the oceanic crust, using parameters of Jaupart et al., (2007). This is done since it is well known that raw data measurements are frequently influenced by significant hydrothermal circulation. Secondly in other regions of data coverage the estimate is based on data measurements. At the map resolution these two categories (young ocean, data covered) cover 65% of Earth's surface. The estimate has been developed in two different ways. In one way the mean value is used and in the second the median is used. The median estimate might be expected to be less sensitive to outliers. Thirdly, for all other regions the estimate is based on the assumption that there is a correlation between heat-flow and geology. This is undertaken using the CCGM (2000) digital geology map. This assumption is assessed and the correlation is found to provide a minor improvement over assuming that heat flow would be represented by the global average. The estimate for Antarctica is guided by proxy measurements. All the work is undertaken using GIS methods. Estimates are made of the errors for all components. The results have been made available as digital files, including shapefiles and tab-delimited and csv ASCII files. In addition to the equal area grid, the results are also available on an equal longitude grid. The map has been published -Davies (2013). The digital files are available in the supplementary information of the publication. Commission for the Geological Map of the World (2000), Geological Map of the World at 1:25000000, UNESCO/CCGM, Paris. Davies, JH, (2013) A global map of solid Earth surface heat flow, Geochemistry, Geophysics and Geosystems, 14, 4608-4622, doi 10.1002/ggge.20271. Davies JH & Davies DR, (2010) Earth's surface heat flux, Solid Earth, 1, 5-24, www.solid-earth.net/1/5/2010/. Jaupart C, Labrosse S, Mareschal J-C, (2007) Temperatures, heat and energy in the mantle of the Earth, in Treatise on Geophysics, v7 Mantle Convection, ed D. Bercovici, 253-303, Elsevier, Amsterdam

Development and assessment of whole-genome oligonucleotide microarrays to analyze an anaerobic microbial community and its responses to oxidative stress.

PubMed

Scholten, Johannes C M; Culley, David E; Nie, Lei; Munn, Kyle J; Chow, Lely; Brockman, Fred J; Zhang, Weiwen

2007-06-29

The application of DNA microarray technology to investigate multiple-species microbial communities presents great challenges. In this study, we reported the design and quality assessment of four whole genome oligonucleotide microarrays for two syntroph bacteria, Desulfovibrio vulgaris and Syntrophobacter fumaroxidans, and two archaeal methanogens, Methanosarcina barkeri, and Methanospirillum hungatei, and their application to analyze global gene expression in a four-species microbial community in response to oxidative stress. In order to minimize the possibility of cross-hybridization, cross-genome comparison was performed to assure all probes unique to each genome so that the microarrays could provide species-level resolution. Microarray quality was validated by the good reproducibility of experimental measurements of multiple biological and analytical replicates. This study showed that S. fumaroxidans and M. hungatei responded to the oxidative stress with up-regulation of several genes known to be involved in reactive oxygen species (ROS) detoxification, such as catalase and rubrerythrin in S. fumaroxidans and thioredoxin and heat shock protein Hsp20 in M. hungatei. However, D. vulgaris seemed to be less sensitive to the oxidative stress as a member of a four-species community, since no gene involved in ROS detoxification was up-regulated. Our work demonstrated the successful application of microarrays to a multiple-species microbial community, and our preliminary results indicated that this approach could provide novel insights on the metabolism within microbial communities.

Systematic evaluation of RNA quality, microarray data reliability and pathway analysis in fresh, fresh frozen and formalin-fixed paraffin-embedded tissue samples.

PubMed

Wimmer, Isabella; Tröscher, Anna R; Brunner, Florian; Rubino, Stephen J; Bien, Christian G; Weiner, Howard L; Lassmann, Hans; Bauer, Jan

2018-04-20

Formalin-fixed paraffin-embedded (FFPE) tissues are valuable resources commonly used in pathology. However, formalin fixation modifies nucleic acids challenging the isolation of high-quality RNA for genetic profiling. Here, we assessed feasibility and reliability of microarray studies analysing transcriptome data from fresh, fresh-frozen (FF) and FFPE tissues. We show that reproducible microarray data can be generated from only 2 ng FFPE-derived RNA. For RNA quality assessment, fragment size distribution (DV200) and qPCR proved most suitable. During RNA isolation, extending tissue lysis time to 10 hours reduced high-molecular-weight species, while additional incubation at 70 °C markedly increased RNA yields. Since FF- and FFPE-derived microarrays constitute different data entities, we used indirect measures to investigate gene signal variation and relative gene expression. Whole-genome analyses revealed high concordance rates, while reviewing on single-genes basis showed higher data variation in FFPE than FF arrays. Using an experimental model, gene set enrichment analysis (GSEA) of FFPE-derived microarrays and fresh tissue-derived RNA-Seq datasets yielded similarly affected pathways confirming the applicability of FFPE tissue in global gene expression analysis. Our study provides a workflow comprising RNA isolation, quality assessment and microarray profiling using minimal RNA input, thus enabling hypothesis-generating pathway analyses from limited amounts of precious, pathologically significant FFPE tissues.

A Synthetic Glycan Microarray Enables Epitope Mapping of Plant Cell Wall Glycan-Directed Antibodies.

PubMed

Ruprecht, Colin; Bartetzko, Max P; Senf, Deborah; Dallabernadina, Pietro; Boos, Irene; Andersen, Mathias C F; Kotake, Toshihisa; Knox, J Paul; Hahn, Michael G; Clausen, Mads H; Pfrengle, Fabian

2017-11-01

In the last three decades, more than 200 monoclonal antibodies have been raised against most classes of plant cell wall polysaccharides by different laboratories worldwide. These antibodies are widely used to identify differences in plant cell wall components in mutants, organ and tissue types, and developmental stages. Despite their importance and broad use, the precise binding epitope has been determined for only a few of these antibodies. Here, we use a plant glycan microarray equipped with 88 synthetic oligosaccharides to comprehensively map the epitopes of plant cell wall glycan-directed antibodies. Our results reveal the binding epitopes for 78 arabinogalactan-, rhamnogalacturonan-, xylan-, and xyloglucan-directed antibodies. We demonstrate that, with knowledge of the exact epitopes recognized by individual antibodies, specific glycosyl hydrolases can be implemented into immunological cell wall analyses, providing a framework to obtain structural information on plant cell wall glycans with unprecedented molecular precision. © 2017 American Society of Plant Biologists. All Rights Reserved.

Spaceflight Alters Bacterial Gene Expression and Virulence and Reveals Role for Global Regulator Hfq

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Ott, C. M.; zuBentrup, K. Honer; Ramamurthy R.; Quick, L.; Porwollik, S.; Cheng, P.; McClellan, M.; Tsaprailis, G.; Radabaugh, T.;

A global tectonic activity map with orbital photographic supplement

NASA Technical Reports Server (NTRS)

Lowman, P. D., Jr.

1981-01-01

A three part map showing equatorial and polar regions was compiled showing tectonic and volcanic activity of the past one million years, including the present. Features shown include actively spreading ridges, spreading rates, major active faults, subduction zones, well defined plates, and volcanic areas active within the past one million years. Activity within this period was inferred from seismicity (instrumental and historic), physiography, and published literature. The tectonic activity map was used for planning global geodetic programs of satellite laser ranging and very long base line interferometry and for geologic education.

Linear model for fast background subtraction in oligonucleotide microarrays.

PubMed

Kroll, K Myriam; Barkema, Gerard T; Carlon, Enrico

2009-11-16

One important preprocessing step in the analysis of microarray data is background subtraction. In high-density oligonucleotide arrays this is recognized as a crucial step for the global performance of the data analysis from raw intensities to expression values. We propose here an algorithm for background estimation based on a model in which the cost function is quadratic in a set of fitting parameters such that minimization can be performed through linear algebra. The model incorporates two effects: 1) Correlated intensities between neighboring features in the chip and 2) sequence-dependent affinities for non-specific hybridization fitted by an extended nearest-neighbor model. The algorithm has been tested on 360 GeneChips from publicly available data of recent expression experiments. The algorithm is fast and accurate. Strong correlations between the fitted values for different experiments as well as between the free-energy parameters and their counterparts in aqueous solution indicate that the model captures a significant part of the underlying physical chemistry.

caCORRECT2: Improving the accuracy and reliability of microarray data in the presence of artifacts

PubMed Central

2011-01-01

Background In previous work, we reported the development of caCORRECT, a novel microarray quality control system built to identify and correct spatial artifacts commonly found on Affymetrix arrays. We have made recent improvements to caCORRECT, including the development of a model-based data-replacement strategy and integration with typical microarray workflows via caCORRECT's web portal and caBIG grid services. In this report, we demonstrate that caCORRECT improves the reproducibility and reliability of experimental results across several common Affymetrix microarray platforms. caCORRECT represents an advance over state-of-art quality control methods such as Harshlighting, and acts to improve gene expression calculation techniques such as PLIER, RMA and MAS5.0, because it incorporates spatial information into outlier detection as well as outlier information into probe normalization. The ability of caCORRECT to recover accurate gene expressions from low quality probe intensity data is assessed using a combination of real and synthetic artifacts with PCR follow-up confirmation and the affycomp spike in data. The caCORRECT tool can be accessed at the website: http://cacorrect.bme.gatech.edu. Results We demonstrate that (1) caCORRECT's artifact-aware normalization avoids the undesirable global data warping that happens when any damaged chips are processed without caCORRECT; (2) When used upstream of RMA, PLIER, or MAS5.0, the data imputation of caCORRECT generally improves the accuracy of microarray gene expression in the presence of artifacts more than using Harshlighting or not using any quality control; (3) Biomarkers selected from artifactual microarray data which have undergone the quality control procedures of caCORRECT are more likely to be reliable, as shown by both spike in and PCR validation experiments. Finally, we present a case study of the use of caCORRECT to reliably identify biomarkers for renal cell carcinoma, yielding two diagnostic biomarkers with potential clinical utility, PRKAB1 and NNMT. Conclusions caCORRECT is shown to improve the accuracy of gene expression, and the reproducibility of experimental results in clinical application. This study suggests that caCORRECT will be useful to clean up possible artifacts in new as well as archived microarray data. PMID:21957981

Calibration and assessment of channel-specific biases in microarray data with extended dynamical range.

PubMed

Bengtsson, Henrik; Jönsson, Göran; Vallon-Christersson, Johan

2004-11-12

Non-linearities in observed log-ratios of gene expressions, also known as intensity dependent log-ratios, can often be accounted for by global biases in the two channels being compared. Any step in a microarray process may introduce such offsets and in this article we study the biases introduced by the microarray scanner and the image analysis software. By scanning the same spotted oligonucleotide microarray at different photomultiplier tube (PMT) gains, we have identified a channel-specific bias present in two-channel microarray data. For the scanners analyzed it was in the range of 15-25 (out of 65,535). The observed bias was very stable between subsequent scans of the same array although the PMT gain was greatly adjusted. This indicates that the bias does not originate from a step preceding the scanner detector parts. The bias varies slightly between arrays. When comparing estimates based on data from the same array, but from different scanners, we have found that different scanners introduce different amounts of bias. So do various image analysis methods. We propose a scanning protocol and a constrained affine model that allows us to identify and estimate the bias in each channel. Backward transformation removes the bias and brings the channels to the same scale. The result is that systematic effects such as intensity dependent log-ratios are removed, but also that signal densities become much more similar. The average scan, which has a larger dynamical range and greater signal-to-noise ratio than individual scans, can then be obtained. The study shows that microarray scanners may introduce a significant bias in each channel. Such biases have to be calibrated for, otherwise systematic effects such as intensity dependent log-ratios will be observed. The proposed scanning protocol and calibration method is simple to use and is useful for evaluating scanner biases or for obtaining calibrated measurements with extended dynamical range and better precision. The cross-platform R package aroma, which implements all described methods, is available for free from http://www.maths.lth.se/bioinformatics/.

Global Ionospheric and Plasmaspheric Monitoring With FORMOSAT-3/COSMIC and Ground GPS Observables

NASA Astrophysics Data System (ADS)

Tsai, H.; Ho, T.; Cheng, M.; Hsu, B.; Liu, J. G.

2011-12-01

The global ionosphere map (GIM) provides instantaneous "snapshots" of the global total electron content (TEC) distribution by interpolating the ground-based GPS observables, which include the ionospheric and plasmaspheric content. The increasing use of the FORMOSAT-3/COSMIC (F3/C) satellites provides a change to monitor the global ionospheric and plasmaspheric content individually. The global plasmasphere map (GPM) is constructed by the F3/C non-radio occultation (RO) data in 3-hour snapshot, while the re-defined GIM in narrow sense is contructed with the blending of F3/C RO, the ground GPS observables, and the GPM. The result can be used to study the interaction between ionosphere and plasmasphere.

Accuracy Assessment of Satellite Derived Forest Cover Products in South and Southeast Asia

NASA Astrophysics Data System (ADS)

Gilani, H.; Xu, X.; Jain, A. K.

2017-12-01

South and Southeast Asia (SSEA) region occupies 16 % of worlds land area. It is home to over 50% of the world's population. The SSEA's countries are experiencing significant land-use and land-cover changes (LULCCs), primarily in agriculture, forest, and urban land. For this study, we compiled four existing global forest cover maps for year 2010 by Gong et al.(2015), Hansen et al. (2013), Sexton et al.(2013) and Shimada et al. (2014), which were all medium resolution (≤30 m) products based on Landsat and/or PALSAR satellite images. To evaluate the accuracy of these forest products, we used three types of information: (1) ground measurements, (2) high resolution satellite images and (3) forest cover maps produced at the national scale. The stratified random sampling technique was used to select a set of validation data points from the ground and high-resolution satellite images. Then the confusion matrix method was used to assess and rank the accuracy of the forest cover products for the entire SSEA region. We analyzed the spatial consistency of different forest cover maps, and further evaluated the consistency with terrain characteristics. Our study suggests that global forest cover mapping algorithms are trained and tested using limited ground measurement data. We found significant uncertainties in mountainous areas due to the topographical shadow effect and the dense tree canopies effects. The findings of this study will facilitate to improve our understanding of the forest cover dynamics and their impacts on the quantities and pathways of terrestrial carbon and nitrogen fluxes. Gong, P., et al. (2012). "Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data." International Journal of Remote Sensing 34(7): 2607-2654. Hansen, M. C., et al. (2013). "High-Resolution Global Maps of 21st-Century Forest Cover Change." Science 342(6160): 850-853. Sexton, J. O., et al. (2013). "Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error." International Journal of Digital Earth: 1-22. Shimada, M., et al. (2014). "New global forest/non-forest maps from ALOS PALSAR data (2007-2010)." Remote Sensing of Environment 155: 13-31.

Tiled Microarray Identification of Novel Viral Transcript Structures and Distinct Transcriptional Profiles during Two Modes of Productive Murine Gammaherpesvirus 68 Infection

PubMed Central

Cheng, Benson Yee Hin; Zhi, Jizu; Santana, Alexis; Khan, Sohail; Salinas, Eduardo; Forrest, J. Craig; Zheng, Yueting; Jaggi, Shirin; Leatherwood, Janet

2012-01-01

We applied a custom tiled microarray to examine murine gammaherpesvirus 68 (MHV68) polyadenylated transcript expression in a time course of de novo infection of fibroblast cells and following phorbol ester-mediated reactivation from a latently infected B cell line. During de novo infection, all open reading frames (ORFs) were transcribed and clustered into four major temporal groups that were overlapping yet distinct from clusters based on the phorbol ester-stimulated B cell reactivation time course. High-density transcript analysis at 2-h intervals during de novo infection mapped gene boundaries with a 20-nucleotide resolution, including a previously undefined ORF73 transcript and the MHV68 ORF63 homolog of Kaposi's sarcoma-associated herpesvirus vNLRP1. ORF6 transcript initiation was mapped by tiled array and confirmed by 5′ rapid amplification of cDNA ends. The ∼1.3-kb region upstream of ORF6 was responsive to lytic infection and MHV68 RTA, identifying a novel RTA-responsive promoter. Transcription in intergenic regions consistent with the previously defined expressed genomic regions was detected during both types of productive infection. We conclude that the MHV68 transcriptome is dynamic and distinct during de novo fibroblast infection and upon phorbol ester-stimulated B cell reactivation, highlighting the need to evaluate further transcript structure and the context-dependent molecular events that govern viral gene expression during chronic infection. PMID:22318145

A web-based system for supporting global land cover data production

NASA Astrophysics Data System (ADS)

Han, Gang; Chen, Jun; He, Chaoying; Li, Songnian; Wu, Hao; Liao, Anping; Peng, Shu

2015-05-01

Global land cover (GLC) data production and verification process is very complicated, time consuming and labor intensive, requiring huge amount of imagery data and ancillary data and involving many people, often from different geographic locations. The efficient integration of various kinds of ancillary data and effective collaborative classification in large area land cover mapping requires advanced supporting tools. This paper presents the design and development of a web-based system for supporting 30-m resolution GLC data production by combining geo-spatial web-service and Computer Support Collaborative Work (CSCW) technology. Based on the analysis of the functional and non-functional requirements from GLC mapping, a three tiers system model is proposed with four major parts, i.e., multisource data resources, data and function services, interactive mapping and production management. The prototyping and implementation of the system have been realised by a combination of Open Source Software (OSS) and commercially available off-the-shelf system. This web-based system not only facilitates the integration of heterogeneous data and services required by GLC data production, but also provides online access, visualization and analysis of the images, ancillary data and interim 30 m global land-cover maps. The system further supports online collaborative quality check and verification workflows. It has been successfully applied to China's 30-m resolution GLC mapping project, and has improved significantly the efficiency of GLC data production and verification. The concepts developed through this study should also benefit other GLC or regional land-cover data production efforts.

Probabilistic atlas-based segmentation of combined T1-weighted and DUTE MRI for calculation of head attenuation maps in integrated PET/MRI scanners

PubMed Central

Poynton, Clare B; Chen, Kevin T; Chonde, Daniel B; Izquierdo-Garcia, David; Gollub, Randy L; Gerstner, Elizabeth R; Batchelor, Tracy T; Catana, Ciprian

2014-01-01

We present a new MRI-based attenuation correction (AC) approach for integrated PET/MRI systems that combines both segmentation- and atlas-based methods by incorporating dual-echo ultra-short echo-time (DUTE) and T1-weighted (T1w) MRI data and a probabilistic atlas. Segmented atlases were constructed from CT training data using a leave-one-out framework and combined with T1w, DUTE, and CT data to train a classifier that computes the probability of air/soft tissue/bone at each voxel. This classifier was applied to segment the MRI of the subject of interest and attenuation maps (μ-maps) were generated by assigning specific linear attenuation coefficients (LACs) to each tissue class. The μ-maps generated with this “Atlas-T1w-DUTE” approach were compared to those obtained from DUTE data using a previously proposed method. For validation of the segmentation results, segmented CT μ-maps were considered to the “silver standard”; the segmentation accuracy was assessed qualitatively and quantitatively through calculation of the Dice similarity coefficient (DSC). Relative change (RC) maps between the CT and MRI-based attenuation corrected PET volumes were also calculated for a global voxel-wise assessment of the reconstruction results. The μ-maps obtained using the Atlas-T1w-DUTE classifier agreed well with those derived from CT; the mean DSCs for the Atlas-T1w-DUTE-based μ-maps across all subjects were higher than those for DUTE-based μ-maps; the atlas-based μ-maps also showed a lower percentage of misclassified voxels across all subjects. RC maps from the atlas-based technique also demonstrated improvement in the PET data compared to the DUTE method, both globally as well as regionally. PMID:24753982

Transcriptome analysis of salinity stress responses in common wheat using a 22k oligo-DNA microarray.

PubMed

Kawaura, Kanako; Mochida, Keiichi; Yamazaki, Yukiko; Ogihara, Yasunari

2006-04-01

In this study, we constructed a 22k wheat oligo-DNA microarray. A total of 148,676 expressed sequence tags of common wheat were collected from the database of the Wheat Genomics Consortium of Japan. These were grouped into 34,064 contigs, which were then used to design an oligonucleotide DNA microarray. Following a multistep selection of the sense strand, 21,939 60-mer oligo-DNA probes were selected for attachment on the microarray slide. This 22k oligo-DNA microarray was used to examine the transcriptional response of wheat to salt stress. More than 95% of the probes gave reproducible hybridization signals when targeted with RNAs extracted from salt-treated wheat shoots and roots. With the microarray, we identified 1,811 genes whose expressions changed more than 2-fold in response to salt. These included genes known to mediate response to salt, as well as unknown genes, and they were classified into 12 major groups by hierarchical clustering. These gene expression patterns were also confirmed by real-time reverse transcription-PCR. Many of the genes with unknown function were clustered together with genes known to be involved in response to salt stress. Thus, analysis of gene expression patterns combined with gene ontology should help identify the function of the unknown genes. Also, functional analysis of these wheat genes should provide new insight into the response to salt stress. Finally, these results indicate that the 22k oligo-DNA microarray is a reliable method for monitoring global gene expression patterns in wheat.

15 maps merged in one data structure - GIS-based template for Dawn at Ceres

NASA Astrophysics Data System (ADS)

Naß, A.; Dawn Mapping Team

2017-09-01

Derive regional and global valid statements out of the map (quadrangles) is already a very time intensive task. However, another challenge is how individual mappers can generate one homogenous GIS-based project (w.r.t. geometrical and visual character) representing one geologically-consistent final map. Within this contribution a template will be presented which was generated for the process of the interpretative mapping project of Ceres to accomplish the requirement of unifying and merging individual quadrangle.

Vision-based mapping with cooperative robots

NASA Astrophysics Data System (ADS)

Little, James J.; Jennings, Cullen; Murray, Don

1998-10-01

Two stereo-vision-based mobile robots navigate and autonomously explore their environment safely while building occupancy grid maps of the environment. The robots maintain position estimates within a global coordinate frame using landmark recognition. This allows them to build a common map by sharing position information and stereo data. Stereo vision processing and map updates are done at 3 Hz and the robots move at speeds of 200 cm/s. Cooperative mapping is achieved through autonomous exploration of unstructured and dynamic environments. The map is constructed conservatively, so as to be useful for collision-free path planning. Each robot maintains a separate copy of a shared map, and then posts updates to the common map when it returns to observe a landmark at home base. Issues include synchronization, mutual localization, navigation, exploration, registration of maps, merging repeated views (fusion), centralized vs decentralized maps.

Mapping local and global variability in plant trait distributions

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

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc

2017-12-01

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusingmore » on a set of plant traits closely coupled to photosynthesis and foliar respiration—specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (N m) and phosphorus (P m), we characterize how traits vary within and among over 50,000 ~50×50-km cells across the entire vegetated land surface. We do this in several ways—without defining the PFT of each grid cell and using 4 or 14 PFTs; each model’s predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps further reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.« less

Mapping local and global variability in plant trait distributions.

PubMed

Butler, Ethan E; Datta, Abhirup; Flores-Moreno, Habacuc; Chen, Ming; Wythers, Kirk R; Fazayeli, Farideh; Banerjee, Arindam; Atkin, Owen K; Kattge, Jens; Amiaud, Bernard; Blonder, Benjamin; Boenisch, Gerhard; Bond-Lamberty, Ben; Brown, Kerry A; Byun, Chaeho; Campetella, Giandiego; Cerabolini, Bruno E L; Cornelissen, Johannes H C; Craine, Joseph M; Craven, Dylan; de Vries, Franciska T; Díaz, Sandra; Domingues, Tomas F; Forey, Estelle; González-Melo, Andrés; Gross, Nicolas; Han, Wenxuan; Hattingh, Wesley N; Hickler, Thomas; Jansen, Steven; Kramer, Koen; Kraft, Nathan J B; Kurokawa, Hiroko; Laughlin, Daniel C; Meir, Patrick; Minden, Vanessa; Niinemets, Ülo; Onoda, Yusuke; Peñuelas, Josep; Read, Quentin; Sack, Lawren; Schamp, Brandon; Soudzilovskaia, Nadejda A; Spasojevic, Marko J; Sosinski, Enio; Thornton, Peter E; Valladares, Fernando; van Bodegom, Peter M; Williams, Mathew; Wirth, Christian; Reich, Peter B

2017-12-19

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.

Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.

PubMed

Saberkari, Hamidreza; Bahrami, Sheyda; Shamsi, Mousa; Amoshahy, Mohammad Javad; Ghavifekr, Habib Badri; Sedaaghi, Mohammad Hossein

2015-01-01

DNA microarray is a powerful approach to study simultaneously, the expression of 1000 of genes in a single experiment. The average value of the fluorescent intensity could be calculated in a microarray experiment. The calculated intensity values are very close in amount to the levels of expression of a particular gene. However, determining the appropriate position of every spot in microarray images is a main challenge, which leads to the accurate classification of normal and abnormal (cancer) cells. In this paper, first a preprocessing approach is performed to eliminate the noise and artifacts available in microarray cells using the nonlinear anisotropic diffusion filtering method. Then, the coordinate center of each spot is positioned utilizing the mathematical morphology operations. Finally, the position of each spot is exactly determined through applying a novel hybrid model based on the principle component analysis and the spatial fuzzy c-means clustering (SFCM) algorithm. Using a Gaussian kernel in SFCM algorithm will lead to improving the quality in complementary DNA microarray segmentation. The performance of the proposed algorithm has been evaluated on the real microarray images, which is available in Stanford Microarray Databases. Results illustrate that the accuracy of microarray cells segmentation in the proposed algorithm reaches to 100% and 98% for noiseless/noisy cells, respectively.

Microarray-based screening of heat shock protein inhibitors.

PubMed

Schax, Emilia; Walter, Johanna-Gabriela; Märzhäuser, Helene; Stahl, Frank; Scheper, Thomas; Agard, David A; Eichner, Simone; Kirschning, Andreas; Zeilinger, Carsten

2014-06-20

Based on the importance of heat shock proteins (HSPs) in diseases such as cancer, Alzheimer's disease or malaria, inhibitors of these chaperons are needed. Today's state-of-the-art techniques to identify HSP inhibitors are performed in microplate format, requiring large amounts of proteins and potential inhibitors. In contrast, we have developed a miniaturized protein microarray-based assay to identify novel inhibitors, allowing analysis with 300 pmol of protein. The assay is based on competitive binding of fluorescence-labeled ATP and potential inhibitors to the ATP-binding site of HSP. Therefore, the developed microarray enables the parallel analysis of different ATP-binding proteins on a single microarray. We have demonstrated the possibility of multiplexing by immobilizing full-length human HSP90α and HtpG of Helicobacter pylori on microarrays. Fluorescence-labeled ATP was competed by novel geldanamycin/reblastatin derivatives with IC50 values in the range of 0.5 nM to 4 μM and Z(*)-factors between 0.60 and 0.96. Our results demonstrate the potential of a target-oriented multiplexed protein microarray to identify novel inhibitors for different members of the HSP90 family. Copyright © 2014 Elsevier B.V. All rights reserved.

The Holdridge life zones of the conterminous United States in relation to ecosystem mapping

Treesearch

A.E. Lugo; S. L. Brown; R. Dodson; T. S Smith; H. H. Shugart

1999-01-01

Aim Our main goals were to develop a map of the life zones for the conterminous United States, based on the Holdridge Life Zone system, as a tool for ecosystem mapping, and to compare the map of Holdridge life zones with other global vegetation classification and mapping efforts. Location The area of interest is the forty-eight contiguous states of the United States....

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

PubMed Central

2011-01-01

Background Mutual information is a measure of similarity between two variables. It has been widely used in various application domains including computational biology, machine learning, statistics, image processing, and financial computing. Previously used simple histogram based mutual information estimators lack the precision in quality compared to kernel based methods. The recently introduced B-spline function based mutual information estimation method is competitive to the kernel based methods in terms of quality but at a lower computational complexity. Results We present a new approach to accelerate the B-spline function based mutual information estimation algorithm with commodity graphics hardware. To derive an efficient mapping onto this type of architecture, we have used the Compute Unified Device Architecture (CUDA) programming model to design and implement a new parallel algorithm. Our implementation, called CUDA-MI, can achieve speedups of up to 82 using double precision on a single GPU compared to a multi-threaded implementation on a quad-core CPU for large microarray datasets. We have used the results obtained by CUDA-MI to infer gene regulatory networks (GRNs) from microarray data. The comparisons to existing methods including ARACNE and TINGe show that CUDA-MI produces GRNs of higher quality in less time. Conclusions CUDA-MI is publicly available open-source software, written in CUDA and C++ programming languages. It obtains significant speedup over sequential multi-threaded implementation by fully exploiting the compute capability of commonly used CUDA-enabled low-cost GPUs. PMID:21672264

Integrating Socioeconomic and Earth Science Data Using Geobrowsers and Web Services: A Demonstration

NASA Astrophysics Data System (ADS)

Schumacher, J. A.; Yetman, G. G.

2007-12-01

The societal benefit areas identified as the focus for the Global Earth Observing System of Systems (GEOSS) 10- year implementation plan are an indicator of the importance of integrating socioeconomic data with earth science data to support decision makers. To aid this integration, CIESIN is delivering its global and U.S. demographic data to commercial and open source Geobrowsers and providing open standards based services for data access. Currently, data on population distribution, poverty, and detailed census data for the U.S. are available for visualization and access in Google Earth, NASA World Wind, and a browser-based 2-dimensional mapping client. The mapping client allows for the creation of web map documents that pull together layers from distributed servers and can be saved and shared. Visualization tools with Geobrowsers, user-driven map creation and sharing via browser-based clients, and a prototype for characterizing populations at risk to predicted precipitation deficits will be demonstrated.

Brain in situ hybridization maps as a source for reverse-engineering transcriptional regulatory networks: Alzheimer's disease insights

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

Acquaah-Mensah, George K.; Taylor, Ronald C.

Microarray data have been a valuable resource for identifying transcriptional regulatory relationships among genes. As an example, brain region-specific transcriptional regulatory events have the potential of providing etiological insights into Alzheimer Disease (AD). However, there is often a paucity of suitable brain-region specific expression data obtained via microarrays or other high throughput means. The Allen Brain Atlas in situ hybridization (ISH) data sets (Jones et al., 2009) represent a potentially valuable alternative source of high-throughput brain region-specific gene expression data for such purposes. In this study, Allen BrainAtlasmouse ISH data in the hippocampal fields were extracted, focusing on 508 genesmore » relevant to neurodegeneration. Transcriptional regulatory networkswere learned using three high-performing network inference algorithms. Only 17% of regulatory edges from a network reverse-engineered based on brain region-specific ISH data were also found in a network constructed upon gene expression correlations inmousewhole brain microarrays, thus showing the specificity of gene expression within brain sub-regions. Furthermore, the ISH data-based networks were used to identify instructive transcriptional regulatory relationships. Ncor2, Sp3 and Usf2 form a unique three-party regulatory motif, potentially affecting memory formation pathways. Nfe2l1, Egr1 and Usf2 emerge among regulators of genes involved in AD (e.g. Dhcr24, Aplp2, Tia1, Pdrx1, Vdac1, andSyn2). Further, Nfe2l1, Egr1 and Usf2 are sensitive to dietary factors and could be among links between dietary influences and genes in the AD etiology. Thus, this approach of harnessing brain region-specific ISH data represents a rare opportunity for gleaning unique etiological insights for diseases such as AD.« less

A comparison of the IGBP DISCover and University of Maryland 1 km global land cover products

USGS Publications Warehouse

Hansen, M.C.; Reed, B.

2000-01-01

Two global 1 km land cover data sets derived from 1992-1993 Advanced Very High Resolution Radiometer (AVHRR) data are currently available, the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) DISCover and the University of Maryland (UMd) 1 km land cover maps. This paper makes a preliminary comparison of the methodologies and results of the two products. The DISCover methodology employed an unsupervised clustering classification scheme on a per-continent basis using 12 monthly maximum NDVI composites as inputs. The UMd approach employed a supervised classification tree method in which temporal metrics derived from all AVHRR bands and the NDVI were used to predict class membership across the entire globe. The DISCover map uses the IGBP classification scheme, while the UMd map employs a modified IGBP scheme minus the classes of permanent wetlands, cropland/natural vegetation mosaic and ice and snow. Global area totals of aggregated vegetation types are very similar and have a per-pixel agreement of 74%. For tall versus short/no vegetation, the per-pixel agreement is 84%. For broad vegetation types, core areas map similarly, while transition zones around core areas differ significantly. This results in high regional variability between the maps. Individual class agreement between the two 1 km maps is 49%. Comparison of the maps at a nominal 0.5 resolution with two global ground-based maps shows an improvement of thematic concurrency of 46% when viewing average class agreement. The absence of the cropland mosaic class creates a difficulty in comparing the maps, due to its significant extent in the DISCover map. The DISCover map, in general, has more forest, while the UMd map has considerably more area in the intermediate tree cover classes of woody savanna/ woodland and savanna/wooded grassland.

Comparative transcriptional and translational analysis of leptospiral outer membrane protein expression in response to temperature.

PubMed

Lo, Miranda; Cordwell, Stuart J; Bulach, Dieter M; Adler, Ben

2009-12-08

Leptospirosis is a global zoonosis affecting millions of people annually. Transcriptional changes in response to temperature were previously investigated using microarrays to identify genes potentially expressed upon host entry. Past studies found that various leptospiral outer membrane proteins are differentially expressed at different temperatures. However, our microarray studies highlighted a divergence between protein abundance and transcript levels for some proteins. Given the abundance of post-transcriptional expression control mechanisms, this finding highlighted the importance of global protein analysis systems. To complement our previous transcription study, we evaluated differences in the proteins of the leptospiral outer membrane fraction in response to temperature upshift. Outer membrane protein-enriched fractions from Leptospira interrogans grown at 30 degrees C or overnight upshift to 37 degrees C were isolated and the relative abundance of each protein was determined by iTRAQ analysis coupled with two-dimensional liquid chromatography and tandem mass spectrometry (2-DLC/MS-MS). We identified 1026 proteins with 99% confidence; 27 and 66 were present at elevated and reduced abundance respectively. Protein abundance changes were compared with transcriptional differences determined from the microarray studies. While there was some correlation between the microarray and iTRAQ data, a subset of genes that showed no differential expression by microarray was found to encode temperature-regulated proteins. This set of genes is of particular interest as it is likely that regulation of their expression occurs post-transcriptionally, providing an opportunity to develop hypotheses about the molecular dynamics of the outer membrane of Leptospira in response to changing environments. This is the first study to compare transcriptional and translational responses to temperature shift in L. interrogans. The results thus provide an insight into the mechanisms used by L. interrogans to adapt to conditions encountered in the host and to cause disease. Our results suggest down-regulation of protein expression in response to temperature, and decreased expression of outer membrane proteins may facilitate minimal interaction with host immune mechanisms.

The Global Error Assessment (GEA) model for the selection of differentially expressed genes in microarray data.

PubMed

Mansourian, Robert; Mutch, David M; Antille, Nicolas; Aubert, Jerome; Fogel, Paul; Le Goff, Jean-Marc; Moulin, Julie; Petrov, Anton; Rytz, Andreas; Voegel, Johannes J; Roberts, Matthew-Alan

2004-11-01

Microarray technology has become a powerful research tool in many fields of study; however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed; however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure. The present study describes a Global Error Assessment (GEA) methodology to select differentially expressed genes in microarray datasets, and was developed using an in vitro experiment that compared control and interferon-gamma treated skin cells. In this experiment, up to nine replicates were used to confidently estimate error, thereby enabling methods of different statistical power to be compared. Gene expression results of a similar absolute expression are binned, so as to enable a highly accurate local estimate of the mean squared error within conditions. The model then relates variability of gene expression in each bin to absolute expression levels and uses this in a test derived from the classical ANOVA. The GEA selection method is compared with both the classical and permutational ANOVA tests, and demonstrates an increased stability, robustness and confidence in gene selection. A subset of the selected genes were validated by real-time reverse transcription-polymerase chain reaction (RT-PCR). All these results suggest that GEA methodology is (i) suitable for selection of differentially expressed genes in microarray data, (ii) intuitive and computationally efficient and (iii) especially advantageous under conditions of low k. The GEA code for R software is freely available upon request to authors.

A global, 30-m resolution land-surface water body dataset for 2000

NASA Astrophysics Data System (ADS)

Feng, M.; Sexton, J. O.; Huang, C.; Song, D. X.; Song, X. P.; Channan, S.; Townshend, J. R.

2014-12-01

Inland surface water is essential to terrestrial ecosystems and human civilization. The distribution of surface water in space and its change over time are related to many agricultural, environmental and ecological issues, and are important factors that must be considered in human socioeconomic development. Accurate mapping of surface water is essential for both scientific research and policy-driven applications. Satellite-based remote sensing provides snapshots of Earth's surface and can be used as the main input for water mapping, especially in large areas. Global water areas have been mapped with coarse resolution remotely sensed data (e.g., the Moderate Resolution Imaging Spectroradiometer (MODIS)). However, most inland rivers and water bodies, as well as their changes, are too small to map at such coarse resolutions. Landsat TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus) imagery has a 30m spatial resolution and provides decades of records (~40 years). Since 2008, the opening of the Landsat archive, coupled with relatively lower costs associated with computing and data storage, has made comprehensive study of the dynamic changes of surface water over large even global areas more feasible. Although Landsat images have been used for regional and even global water mapping, the method can hardly be automated due to the difficulties on distinguishing inland surface water with variant degrees of impurities and mixing of soil background with only Landsat data. The spectral similarities to other land cover types, e.g., shadow and glacier remnants, also cause misidentification. We have developed a probabilistic based automatic approach for mapping inland surface water bodies. Landsat surface reflectance in multiple bands, derived water indices, and data from other sources are integrated to maximize the ability of identifying water without human interference. The approach has been implemented with open-source libraries to facilitate processing large amounts of Landsat images on high-performance computing machines. It has been applied to the ~9,000 Landsat scenes of the Global Land Survey (GLS) 2000 data collection to produce a global, 30m resolution inland surface water body data set, which will be made available on the Global Land Cover Facility (GLCF) website (http://www.landcover.org).

Mycobacterium avium subspecies induce differential expression of pro-inflammatory mediators in a murine macrophage model: evidence for enhanced pathogenicity of Mycobacterium avium subspecies paratuberculosis.

PubMed

Basler, Tina; Geffers, Robert; Weiss, Siegfried; Valentin-Weigand, Peter; Goethe, Ralph

2008-01-01

Mycobacterium avium subspecies (ssp.) paratuberculosis (MAP) is the etiological agent of paratuberculosis, a chronic, non-treatable granulomatous enteritis of ruminants. MAP is the only mycobacterium affecting the intestinal tract, which is of interest since it is presently the most favoured pathogen linked to Crohn's disease (CD) in humans due to its frequent detection in CD tissues. MAP is genetically closely related to other M. avium ssp. such as M. avium ssp. avium (MAA) and M. avium ssp. hominissuis (MAH) which can cause mycobacteriosis in animals and immunocompromised humans. We have recently shown that murine macrophage cell lines represent suitable systems to analyse M. avium ssp. patho-mechanisms and could show that MAP, but not MAA, specifically inhibited the antigen-specific stimulatory capacity for CD4(+) T-cells. In the present study, we compared gene expression profiles of murine RAW264.7 macrophages in response to infections with MAP or MAA using murine high-density oligonucleotide Affymetrix microarrays. A comparison of MAP and MAA infection revealed 17 differentially expressed genes. They were expressed at a much lower level in MAP-infected macrophages than in MAA-infected macrophages. Among these were the genes for IL-1beta, IL-1alpha, CXCL2, PTGS2 (COX2), lipocalin (LCN2) and TNF, which are important pro-inflammatory factors. The microarray data were confirmed for selected genes by quantitative real-time reverse transcription PCR and, by protein array analyses and ELISA. Similar to MAA, infection with MAH also showed robust induction of IL-1beta, CXCL2, COX2, LCN2 and TNF. Taken together, our results from M. avium ssp.-infected murine macrophages provide evidence that MAP in contrast to MAA and MAH specifically suppresses the pro-inflammatory defence mechanisms of infected macrophages.

DNA Microarray-based Ecotoxicological Biomarker Discovery in a Small Fish Model Species

EPA Science Inventory

This paper addresses several issues critical to use of zebrafish oligonucleotide microarrays for computational toxicology research on endocrine disrupting chemicals using small fish models, and more generally, the use of microarrays in aquatic toxicology.

IMPROVING THE RELIABILITY OF MICROARRAYS FOR TOXICOLOGY RESEARCH: A COLLABORATIVE APPROACH

EPA Science Inventory

Microarray-based gene expression profiling is a critical tool to identify molecular biomarkers of specific chemical stressors. Although current microarray technologies have progressed from their infancy, biological and technical repeatability and reliability are often still limit...

Local search for optimal global map generation using mid-decadal landsat images

USGS Publications Warehouse

Khatib, L.; Gasch, J.; Morris, Robert; Covington, S.

2007-01-01

NASA and the US Geological Survey (USGS) are seeking to generate a map of the entire globe using Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor data from the "mid-decadal" period of 2004 through 2006. The global map is comprised of thousands of scene locations and, for each location, tens of different images of varying quality to chose from. Furthermore, it is desirable for images of adjacent scenes be close together in time of acquisition, to avoid obvious discontinuities due to seasonal changes. These characteristics make it desirable to formulate an automated solution to the problem of generating the complete map. This paper formulates a Global Map Generator problem as a Constraint Optimization Problem (GMG-COP) and describes an approach to solving it using local search. Preliminary results of running the algorithm on image data sets are summarized. The results suggest a significant improvement in map quality using constraint-based solutions. Copyright ?? 2007, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Global-scale surface spectral variations on Titan seen from Cassini/VIMS

USGS Publications Warehouse

Barnes, J.W.; Brown, R.H.; Soderblom, L.; Buratti, B.J.; Sotin, Christophe; Rodriguez, S.; Le, Mouelic S.; Baines, K.H.; Clark, R.; Nicholson, P.

2007-01-01

We present global-scale maps of Titan from the Visual and Infrared Mapping Spectrometer (VIMS) instrument on Cassini. We map at 64 near-infrared wavelengths simultaneously, covering the atmospheric windows at 0.94, 1.08, 1.28, 1.6, 2.0, 2.8, and 5 ??m with a typical resolution of 50 km/pixel or a typical total integration time of 1 s. Our maps have five to ten times the resolution of ground-based maps, better spectral resolution across most windows, coverage in multiple atmospheric windows, and represent the first spatially resolved maps of Titan at 5 ??m. The VIMS maps provide context and surface spectral information in support of other Cassini instruments. We note a strong latitudinal dependence in the spectral character of Titan's surface, and partition the surface into 9 spectral units that we describe in terms of spectral and spatial characteristics. ?? 2006 Elsevier Inc. All rights reserved.

EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

PubMed Central

Zhu, Yuerong; Zhu, Yuelin; Xu, Wei

2008-01-01

Background Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand. Results EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data. Conclusion EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from . PMID:18218103

Interactive Geophysical Mapping on the Web

NASA Astrophysics Data System (ADS)

Meertens, C.; Hamburger, M.; Estey, L.; Weingroff, M.; Deardorff, R.; Holt, W.

2002-12-01

We have developed a set of interactive, web-based map utilities that make geophysical results accessible to a large number and variety of users. These tools provide access to pre-determined map regions via a simple Html/JavaScript interface or to user-selectable areas using a Java interface to a Generic Mapping Tools (GMT) engine. Users can access a variety of maps, satellite images, and geophysical data at a range of spatial scales for the earth and other planets of the solar system. Developed initially by UNAVCO for study of global-scale geodynamic processes, users can choose from a variety of base maps (satellite mosaics, global topography, geoid, sea-floor age, strain rate and seismic hazard maps, and others) and can then add a number of geographic and geophysical overlays for example coastlines, political boundaries, rivers and lakes, NEIC earthquake and volcano locations, stress axes, and observed and model plate motion and deformation velocity vectors representing a compilation of 2933 geodetic measurements from around the world. The software design is flexible allowing for construction of special editions for different target audiences. Custom maps been implemented for UNAVCO as the "Jules Verne Voyager" and "Voyager Junior", for the International Lithosphere Project's "Global Strain Rate Map", and for EarthScope Education and Outreach as "EarthScope Voyager Jr.". For the later, a number of EarthScope-specific features have been added, including locations of proposed USArray (seismic), Plate Boundary Observatory (geodetic), and San Andreas Fault Observatory at Depth sites plus detailed maps and geographically referenced examples of EarthScope-related scientific investigations. In addition, we are developing a website that incorporates background materials and curricular activities that encourage users to explore Earth processes. A cluster of map processing computers and nearly a terabyte of disk storage has been assembled to power the generation of interactive maps and provide space for a very large collection of map data. A portal to these map tools can be found at: http://jules.unavco.ucar.edu.

Positional Accuracy of Airborne Integrated Global Positioning and Inertial Navigation Systems for Mapping in Glen Canyon, Arizona

USGS Publications Warehouse

Sanchez, Richard D.; Hothem, Larry D.

2002-01-01

High-resolution airborne and satellite image sensor systems integrated with onboard data collection based on the Global Positioning System (GPS) and inertial navigation systems (INS) may offer a quick and cost-effective way to gather accurate topographic map information without ground control or aerial triangulation. The Applanix Corporation?s Position and Orientation Solutions for Direct Georeferencing of aerial photography was used in this project to examine the positional accuracy of integrated GPS/INS for terrain mapping in Glen Canyon, Arizona. The research application in this study yielded important information on the usefulness and limits of airborne integrated GPS/INS data-capture systems for mapping.

Use of Satellite Remote Sensing Data in the Mapping of Global Landslide Susceptibility

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Huffman, George J.

2007-01-01

Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIs-based weighted linear combination method. First , six relevant landslide-controlling factors are derived from geospatial remote sensing data and coded into a GIS system. Next, continuous susceptibility values from low to high are assigned to each of the six factors. Second, a continuous scale of a global landslide susceptibility index is derived using GIS weighted linear combination based on each factor's relative significance to the process of landslide occurrence (e.g., slope is the most important factor, soil types and soil texture are also primary-level parameters, while elevation, land cover types, and drainage density are secondary in importance). Finally, the continuous index map is further classified into six susceptibility categories. Results show the hot spots of landslide-prone regions include the Pacific Rim, the Himalayas and South Asia, Rocky Mountains, Appalachian Mountains, Alps, and parts of the Middle East and Africa. India, China, Nepal, Japan, the USA, and Peru are shown to have landslide-prone areas. This first-cut global landslide susceptibility map forms a starting point to provide a global view of landslide risks and may be used in conjunction with satellite-based precipitation information to potentially detect areas with significant landslide potential due to heavy rainfall. 1

Development of a chip-based multiplexed immunoassay using liposomal nanovesicles and its application in the detection of pathogens causing female lower genital tract infections.

PubMed

Su, Wen-Hsiang; Ho, Tien-Yu; Tsou, Tsung-Shan; Lee, Wen-Ling; Wang, Kuan-Chin; Yu, Yuan-Yi; Chen, Tien-Jui; Tan, Chia-Hsuan; Kuo, Cheng-Deng; Chen, Chien-Sheng; Wang, Peng-Hui

2013-03-01

Cervicovaginitis is a highly prevalent disease that is a burden on healthcare globally. Immediate and adequate treatment can eradicate the infection and block subsequent complications. The feasibility of achip-based multiplexed immunoassay using liposomal nanovesicles was tested. A multiplexed immunoassay chip containing five antibodies for five pathogens (Chlamydia trachomatis, Escherichia coli, Neisseria gonorrhoeae, Streptococcus agalactiae, and Candida albicans) was established and tested. Four patients with spiking of candidiasis were enrolled. The difference between positive and negative readings was evaluated using the paired Student t test. The detection threshold of Candida in this microarray was 100,000 CFU/mL in a vaginal sample, and the time required for the whole procedure was 3 hours. The testing of the four patients showed 100% for both sensitivity and specificity. This microarray chip was a rapid, easy, inexpensive and sensitive tool for detecting female lower genital tract Candida infection in a one-time vaginal sampling process, although the data on the four other pathogens were still unavailable. A larger population study is encouraged to test the validity of this multiplexed immunoassay chip. Copyright © 2013. Published by Elsevier B.V.

EDGE3: A web-based solution for management and analysis of Agilent two color microarray experiments

PubMed Central

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-01-01

Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE3 provides a means for managing RNA samples and arrays during the hybridization process. EDGE3 is freely available for download at . PMID:19732451

EDGE(3): a web-based solution for management and analysis of Agilent two color microarray experiments.

PubMed

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-09-04

The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE(3) was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. EDGE(3) has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE(3) is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Here, we present EDGE(3), an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE(3) provides a means for managing RNA samples and arrays during the hybridization process. EDGE(3) is freely available for download at http://edge.oncology.wisc.edu/.

Arabidopsis Gene Family Profiler (aGFP)--user-oriented transcriptomic database with easy-to-use graphic interface.

PubMed

Dupl'áková, Nikoleta; Renák, David; Hovanec, Patrik; Honysová, Barbora; Twell, David; Honys, David

2007-07-23

Microarray technologies now belong to the standard functional genomics toolbox and have undergone massive development leading to increased genome coverage, accuracy and reliability. The number of experiments exploiting microarray technology has markedly increased in recent years. In parallel with the rapid accumulation of transcriptomic data, on-line analysis tools are being introduced to simplify their use. Global statistical data analysis methods contribute to the development of overall concepts about gene expression patterns and to query and compose working hypotheses. More recently, these applications are being supplemented with more specialized products offering visualization and specific data mining tools. We present a curated gene family-oriented gene expression database, Arabidopsis Gene Family Profiler (aGFP; http://agfp.ueb.cas.cz), which gives the user access to a large collection of normalised Affymetrix ATH1 microarray datasets. The database currently contains NASC Array and AtGenExpress transcriptomic datasets for various tissues at different developmental stages of wild type plants gathered from nearly 350 gene chips. The Arabidopsis GFP database has been designed as an easy-to-use tool for users needing an easily accessible resource for expression data of single genes, pre-defined gene families or custom gene sets, with the further possibility of keyword search. Arabidopsis Gene Family Profiler presents a user-friendly web interface using both graphic and text output. Data are stored at the MySQL server and individual queries are created in PHP script. The most distinguishable features of Arabidopsis Gene Family Profiler database are: 1) the presentation of normalized datasets (Affymetrix MAS algorithm and calculation of model-based gene-expression values based on the Perfect Match-only model); 2) the choice between two different normalization algorithms (Affymetrix MAS4 or MAS5 algorithms); 3) an intuitive interface; 4) an interactive "virtual plant" visualizing the spatial and developmental expression profiles of both gene families and individual genes. Arabidopsis GFP gives users the possibility to analyze current Arabidopsis developmental transcriptomic data starting with simple global queries that can be expanded and further refined to visualize comparative and highly selective gene expression profiles.

Challenges for circumpolar landcover mapping with remotely sensed data

NASA Astrophysics Data System (ADS)

Bartsch, A.; Widhalm, B.; Höfler, A.; Kroisleitner, C.; Trofaier, A. M.

2016-12-01

The European Space Agency has launched the GlobPermafrost initiative (2016-2019) to develop, validate and implement information products to support the research communities and related international organizations in their work on understanding permafrost better by integration of Earth Observation data. One of the challenges is to develop a land cover map which can be used to address permafrost related questions. Many applications in the Arctic require higher thematic detail than available in global maps to date. There exist a range of regional land cover maps which have been developed for e.g. upscaling of methane fluxes or soil organic carbon content in permafrost regions and demonstrate the suitability of satellite data. Widely used is the CAVM (Circum Arctic Vegetation map, Walker et al. 2005) as it offers a for many applications sufficient thematic detail. It is however confined to areas north of the tree line. Global land cover maps have been assessed based on the CAVM. Shrub and dwarf-shrub tundra are mostly classified as `Sparse vegetation'. Usually 50-60% of the area north of the tree line are represented by this class. Wetland areas are in general not well represented. This cannot only be explained with the insufficient spatial resolution since the CAVM is also based on medium resolution (1km) data. Required thematic detail and weaknesses of existing global landcover maps are discussed in the context of permafrost related processes across scales and the potential for improvement with/ added information of SAR data for this purpose is assessed.

FANSe2: a robust and cost-efficient alignment tool for quantitative next-generation sequencing applications.

PubMed

Xiao, Chuan-Le; Mai, Zhi-Biao; Lian, Xin-Lei; Zhong, Jia-Yong; Jin, Jing-Jie; He, Qing-Yu; Zhang, Gong

2014-01-01

Correct and bias-free interpretation of the deep sequencing data is inevitably dependent on the complete mapping of all mappable reads to the reference sequence, especially for quantitative RNA-seq applications. Seed-based algorithms are generally slow but robust, while Burrows-Wheeler Transform (BWT) based algorithms are fast but less robust. To have both advantages, we developed an algorithm FANSe2 with iterative mapping strategy based on the statistics of real-world sequencing error distribution to substantially accelerate the mapping without compromising the accuracy. Its sensitivity and accuracy are higher than the BWT-based algorithms in the tests using both prokaryotic and eukaryotic sequencing datasets. The gene identification results of FANSe2 is experimentally validated, while the previous algorithms have false positives and false negatives. FANSe2 showed remarkably better consistency to the microarray than most other algorithms in terms of gene expression quantifications. We implemented a scalable and almost maintenance-free parallelization method that can utilize the computational power of multiple office computers, a novel feature not present in any other mainstream algorithm. With three normal office computers, we demonstrated that FANSe2 mapped an RNA-seq dataset generated from an entire Illunima HiSeq 2000 flowcell (8 lanes, 608 M reads) to masked human genome within 4.1 hours with higher sensitivity than Bowtie/Bowtie2. FANSe2 thus provides robust accuracy, full indel sensitivity, fast speed, versatile compatibility and economical computational utilization, making it a useful and practical tool for deep sequencing applications. FANSe2 is freely available at http://bioinformatics.jnu.edu.cn/software/fanse2/.

Ontology-based meta-analysis of global collections of high-throughput public data.

PubMed

Kupershmidt, Ilya; Su, Qiaojuan Jane; Grewal, Anoop; Sundaresh, Suman; Halperin, Inbal; Flynn, James; Shekar, Mamatha; Wang, Helen; Park, Jenny; Cui, Wenwu; Wall, Gregory D; Wisotzkey, Robert; Alag, Satnam; Akhtari, Saeid; Ronaghi, Mostafa

2010-09-29

The investigation of the interconnections between the molecular and genetic events that govern biological systems is essential if we are to understand the development of disease and design effective novel treatments. Microarray and next-generation sequencing technologies have the potential to provide this information. However, taking full advantage of these approaches requires that biological connections be made across large quantities of highly heterogeneous genomic datasets. Leveraging the increasingly huge quantities of genomic data in the public domain is fast becoming one of the key challenges in the research community today. We have developed a novel data mining framework that enables researchers to use this growing collection of public high-throughput data to investigate any set of genes or proteins. The connectivity between molecular states across thousands of heterogeneous datasets from microarrays and other genomic platforms is determined through a combination of rank-based enrichment statistics, meta-analyses, and biomedical ontologies. We address data quality concerns through dataset replication and meta-analysis and ensure that the majority of the findings are derived using multiple lines of evidence. As an example of our strategy and the utility of this framework, we apply our data mining approach to explore the biology of brown fat within the context of the thousands of publicly available gene expression datasets. Our work presents a practical strategy for organizing, mining, and correlating global collections of large-scale genomic data to explore normal and disease biology. Using a hypothesis-free approach, we demonstrate how a data-driven analysis across very large collections of genomic data can reveal novel discoveries and evidence to support existing hypothesis.

MapReduce Algorithms for Inferring Gene Regulatory Networks from Time-Series Microarray Data Using an Information-Theoretic Approach.

PubMed

Abduallah, Yasser; Turki, Turki; Byron, Kevin; Du, Zongxuan; Cervantes-Cervantes, Miguel; Wang, Jason T L

2017-01-01

Gene regulation is a series of processes that control gene expression and its extent. The connections among genes and their regulatory molecules, usually transcription factors, and a descriptive model of such connections are known as gene regulatory networks (GRNs). Elucidating GRNs is crucial to understand the inner workings of the cell and the complexity of gene interactions. To date, numerous algorithms have been developed to infer gene regulatory networks. However, as the number of identified genes increases and the complexity of their interactions is uncovered, networks and their regulatory mechanisms become cumbersome to test. Furthermore, prodding through experimental results requires an enormous amount of computation, resulting in slow data processing. Therefore, new approaches are needed to expeditiously analyze copious amounts of experimental data resulting from cellular GRNs. To meet this need, cloud computing is promising as reported in the literature. Here, we propose new MapReduce algorithms for inferring gene regulatory networks on a Hadoop cluster in a cloud environment. These algorithms employ an information-theoretic approach to infer GRNs using time-series microarray data. Experimental results show that our MapReduce program is much faster than an existing tool while achieving slightly better prediction accuracy than the existing tool.

Global monitoring of autumn gene expression within and among phenotypically divergent populations of Sitka spruce (Picea sitchensis).

PubMed

Holliday, Jason A; Ralph, Steven G; White, Richard; Bohlmann, Jörg; Aitken, Sally N

2008-01-01

Cold acclimation in conifers is a complex process, the timing and extent of which reflects local adaptation and varies widely along latitudinal gradients for many temperate and boreal tree species. Despite their ecological and economic importance, little is known about the global changes in gene expression that accompany autumn cold acclimation in conifers. Using three populations of Sitka spruce (Picea sitchensis) spanning the species range, and a Picea cDNA microarray with 21,840 unique elements, within- and among-population gene expression was monitored during the autumn. Microarray data were validated for selected genes using real-time PCR. Similar numbers of genes were significantly twofold upregulated (1257) and downregulated (967) between late summer and early winter. Among those upregulated were dehydrins, pathogenesis-related/antifreeze genes, carbohydrate and lipid metabolism genes, and genes involved in signal transduction and transcriptional regulation. Among-population microarray hybridizations at early and late autumn time points revealed substantial variation in the autumn transcriptome, some of which may reflect local adaptation. These results demonstrate the complexity of cold acclimation in conifers, highlight similarities and differences to cold tolerance in annual plants, and provide a solid foundation for functional and genetic studies of this important adaptive process.

A new global interior ocean mapped climatology: the 1° × 1° GLODAP version 2

NASA Astrophysics Data System (ADS)

Lauvset, Siv K.; Key, Robert M.; Olsen, Are; van Heuven, Steven; Velo, Anton; Lin, Xiaohua; Schirnick, Carsten; Kozyr, Alex; Tanhua, Toste; Hoppema, Mario; Jutterström, Sara; Steinfeldt, Reiner; Jeansson, Emil; Ishii, Masao; Perez, Fiz F.; Suzuki, Toru; Watelet, Sylvain

2016-08-01

We present a mapped climatology (GLODAPv2.2016b) of ocean biogeochemical variables based on the new GLODAP version 2 data product (Olsen et al., 2016; Key et al., 2015), which covers all ocean basins over the years 1972 to 2013. The quality-controlled and internally consistent GLODAPv2 was used to create global 1° × 1° mapped climatologies of salinity, temperature, oxygen, nitrate, phosphate, silicate, total dissolved inorganic carbon (TCO2), total alkalinity (TAlk), pH, and CaCO3 saturation states using the Data-Interpolating Variational Analysis (DIVA) mapping method. Improving on maps based on an earlier but similar dataset, GLODAPv1.1, this climatology also covers the Arctic Ocean. Climatologies were created for 33 standard depth surfaces. The conceivably confounding temporal trends in TCO2 and pH due to anthropogenic influence were removed prior to mapping by normalizing these data to the year 2002 using first-order calculations of anthropogenic carbon accumulation rates. We additionally provide maps of accumulated anthropogenic carbon in the year 2002 and of preindustrial TCO2. For all parameters, all data from the full 1972-2013 period were used, including data that did not receive full secondary quality control. The GLODAPv2.2016b global 1° × 1° mapped climatologies, including error fields and ancillary information, are available at the GLODAPv2 web page at the Carbon Dioxide Information Analysis Center (CDIAC; doi:10.3334/CDIAC/OTG.NDP093_GLODAPv2).

Development of a rapid microarray-based DNA subtyping assay for the alleles of Shiga toxins 1 and 2 of Escherichia coli.

PubMed

Geue, Lutz; Stieber, Bettina; Monecke, Stefan; Engelmann, Ines; Gunzer, Florian; Slickers, Peter; Braun, Sascha D; Ehricht, Ralf

2014-08-01

In this study, we developed a new rapid, economic, and automated microarray-based genotyping test for the standardized subtyping of Shiga toxins 1 and 2 of Escherichia coli. The microarrays from Alere Technologies can be used in two different formats, the ArrayTube and the ArrayStrip (which enables high-throughput testing in a 96-well format). One microarray chip harbors all the gene sequences necessary to distinguish between all Stx subtypes, facilitating the identification of single and multiple subtypes within a single isolate in one experiment. Specific software was developed to automatically analyze all data obtained from the microarray. The assay was validated with 21 Shiga toxin-producing E. coli (STEC) reference strains that were previously tested by the complete set of conventional subtyping PCRs. The microarray results showed 100% concordance with the PCR results. Essentially identical results were detected when the standard DNA extraction method was replaced by a time-saving heat lysis protocol. For further validation of the microarray, we identified the Stx subtypes or combinations of the subtypes in 446 STEC field isolates of human and animal origin. In summary, this oligonucleotide array represents an excellent diagnostic tool that provides some advantages over standard PCR-based subtyping. The number of the spotted probes on the microarrays can be increased by additional probes, such as for novel alleles, species markers, or resistance genes, should the need arise. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

USGS ShakeMap Developments, Implementation, and Derivative Tools

NASA Astrophysics Data System (ADS)

Wald, D. J.; Lin, K.; Quitoriano, V.; Worden, B.

2007-12-01

We discuss ongoing development and enhancements of ShakeMap, a system for automatically generating maps of ground shaking and intensity in the minutes following an earthquake. The rapid availability of these maps is of particular value to emergency response organizations, utilities, insurance companies, government decision- makers, the media, and the general public. ShakeMap Version 3.2 was released in March, 2007, on a download site which allows ShakeMap developers to track operators' updates and provide follow-up information; V3.2 has now been downloaded in 15 countries. The V3.2 release supports LINUX in addition to other UNIX operating systems and adds enhancements to XML, KML, metadata, and other products. We have also added an uncertainty measure, quantified as a function of spatial location. Uncertainty is essential for evaluating the range of possible losses. Though not released in V3.2, we will describe a new quantitative uncertainty letter grading for each ShakeMap produced, allowing users to gauge the appropriate level of confidence when using rapidly produced ShakeMaps as part of their post-earthquake critical decision-making process. Since the V3.2 release, several new ground motion predictions equations have also been added to the prediction equation modules. ShakeMap is implemented in several new regions as reported in this Session. Within the U.S., robust systems serve California, Nevada, Utah, Washington and Oregon, Hawaii, and Anchorage. Additional systems are in development and efforts to provide backup capabilities for all Advanced National Seismic System (ANSS) regions at the National Earthquake Information Center are underway. Outside the U.S., this Session has descriptions of ShakeMap systems in Italy, Switzerland, Romania, and Turkey, among other countries. We also describe our predictive global ShakeMap system for the rapid evaluation of significant earthquakes globally for the Prompt Assessment of Global Earthquakes for Response (PAGER) system. These global ShakeMaps are constrained by rapidly gathered intensity data via the Internet and by finite fault and aftershock analyses for portraying fault rupture dimensions. As part of the PAGER loss calibration process we have produced an Atlas of ShakeMaps for significant earthquakes around the globe since 1973 (Allen and others, this Session); these Atlas events have additional constraints provided by archival strong motion, faulting dimensions, and macroseismic intensity data. We also describe derivative tools for further utilizing ShakeMap including ShakeCast, a fully automated system for delivering specific ShakeMap products to critical users and triggering established post-earthquake response protocols. We have released ShakeCast Version 2.0 (Lin and others, this Session), which allows RSS feeds for automatically receiving ShakeMap files, auto-launching of post-download processing scripts, and delivering notifications based on users' likely facility damage states derived from ShakeMap shaking parameters. As part of our efforts to produce estimated ShakeMaps globally, we have developed a procedure for deriving Vs30 estimates from correlations with topographic slope, and we have now implemented a global Vs30 Server, allowing users to generate Vs30 maps for custom user-selected regions around the globe (Allen and Wald, this Session). Finally, as a further derivative product of the ShakeMap Atlas project, we will present a shaking hazard Map for the past 30 years based on approximately 3,900 earthquake ShakeMaps of historic earthquakes.

Interim Report on SNP analysis and forensic microarray probe design for South American hemorrhagic fever viruses, tick-borne encephalitis virus, henipaviruses, Old World Arenaviruses, filoviruses, Crimean-Congo hemorrhagic fever viruses, Rift Valley fever

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

Jaing, C; Gardner, S

The goal of this project is to develop forensic genotyping assays for select agent viruses, enhancing the current capabilities for the viral bioforensics and law enforcement community. We used a multipronged approach combining bioinformatics analysis, PCR-enriched samples, microarrays and TaqMan assays to develop high resolution and cost effective genotyping methods for strain level forensic discrimination of viruses. We have leveraged substantial experience and efficiency gained through year 1 on software development, SNP discovery, TaqMan signature design and phylogenetic signature mapping to scale up the development of forensics signatures in year 2. In this report, we have summarized the whole genomemore » wide SNP analysis and microarray probe design for forensics characterization of South American hemorrhagic fever viruses, tick-borne encephalitis viruses and henipaviruses, Old World Arenaviruses, filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus and Japanese encephalitis virus.« less

The Global Hidden Hunger Indices and Maps: An Advocacy Tool for Action

PubMed Central

Muthayya, Sumithra; Rah, Jee Hyun; Sugimoto, Jonathan D.; Roos, Franz F.; Kraemer, Klaus; Black, Robert E.

2013-01-01

The unified global efforts to mitigate the high burden of vitamin and mineral deficiency, known as hidden hunger, in populations around the world are crucial to the achievement of most of the Millennium Development Goals (MDGs). We developed indices and maps of global hidden hunger to help prioritize program assistance, and to serve as an evidence-based global advocacy tool. Two types of hidden hunger indices and maps were created based on i) national prevalence data on stunting, anemia due to iron deficiency, and low serum retinol levels among preschool-aged children in 149 countries; and ii) estimates of Disability Adjusted Life Years (DALYs) attributed to micronutrient deficiencies in 136 countries. A number of countries in sub-Saharan Africa, as well as India and Afghanistan, had an alarmingly high level of hidden hunger, with stunting, iron deficiency anemia, and vitamin A deficiency all being highly prevalent. The total DALY rates per 100,000 population, attributed to micronutrient deficiencies, were generally the highest in sub-Saharan African countries. In 36 countries, home to 90% of the world’s stunted children, deficiencies of micronutrients were responsible for 1.5-12% of the total DALYs. The pattern and magnitude of iodine deficiency did not conform to that of other micronutrients. The greatest proportions of children with iodine deficiency were in the Eastern Mediterranean (46.6%), European (44.2%), and African (40.4%) regions. The current indices and maps provide crucial data to optimize the prioritization of program assistance addressing global multiple micronutrient deficiencies. Moreover, the indices and maps serve as a useful advocacy tool in the call for increased commitments to scale up effective nutrition interventions. PMID:23776712

The spatial data and knowledge gateways at the International Water Management Institute (IWMI)

NASA Astrophysics Data System (ADS)

Thenkabail, P. S.; Biradar, C. M.; Noojipady, P.; Islam, A.; Velpuri, M.; Vithanage, J.; Kulawardhana, W.; Li, Yuan Jie; Dheeravath, V.; Gunasinghe, S.; Alankara, R.

2006-10-01

In this paper we discuss spatial data and knowledge base (SDKB) gateway portals developed by the International Water Management Institute (IWMI). Our vision is to generate and/or facilitate easy and free access to state-of-art SDKB of excellence globally. Our mission is to make SDKB accessible online, globally, for free. The IWMI data storehouse pathway (IWMIDSP; http://www.iwmidsp.org) is a pathfinder global public good (GPG) portal on remote sensing and GIS (RS/GIS) data and products with specific emphasis on river basin data, but also storing valuable data on Nations, Regions, and the World. A number of other specialty GPG portals have also been released. These include Global map of irrigated area (http://www.iwmigiam.org), Drought monitoring system for southwest Asia (http://dms.iwmi.org), Tsunami satellite sensor data catalogue (http://tsdc.iwmi.org), and Knowledge base system (KBS) for Sri Lanka (http://www.iwmikbs.org). The IWMIDSP has been the backbone of several other projects such as global irrigated area mapping, drought monitoring system, wetlands, and knowledge base systems. A discussion on these pathfinder web portals follow.

DISC-BASED IMMUNOASSAY MICROARRAYS. (R825433)

EPA Science Inventory

Microarray technology as applied to areas that include genomics, diagnostics, environmental, and drug discovery, is an interesting research topic for which different chip-based devices have been developed. As an alternative, we have explored the principle of compact disc-based...

Genomic paradigms for food-borne enteric pathogen analysis at the USFDA: case studies highlighting method utility, integration and resolution.

PubMed

Elkins, C A; Kotewicz, M L; Jackson, S A; Lacher, D W; Abu-Ali, G S; Patel, I R

2013-01-01

Modern risk control and food safety practices involving food-borne bacterial pathogens are benefiting from new genomic technologies for rapid, yet highly specific, strain characterisations. Within the United States Food and Drug Administration (USFDA) Center for Food Safety and Applied Nutrition (CFSAN), optical genome mapping and DNA microarray genotyping have been used for several years to quickly assess genomic architecture and gene content, respectively, for outbreak strain subtyping and to enhance retrospective trace-back analyses. The application and relative utility of each method varies with outbreak scenario and the suspect pathogen, with comparative analytical power enhanced by database scale and depth. Integration of these two technologies allows high-resolution scrutiny of the genomic landscapes of enteric food-borne pathogens with notable examples including Shiga toxin-producing Escherichia coli (STEC) and Salmonella enterica serovars from a variety of food commodities. Moreover, the recent application of whole genome sequencing technologies to food-borne pathogen outbreaks and surveillance has enhanced resolution to the single nucleotide scale. This new wealth of sequence data will support more refined next-generation custom microarray designs, targeted re-sequencing and "genomic signature recognition" approaches involving a combination of genes and single nucleotide polymorphism detection to distil strain-specific fingerprinting to a minimised scale. This paper examines the utility of microarrays and optical mapping in analysing outbreaks, reviews best practices and the limits of these technologies for pathogen differentiation, and it considers future integration with whole genome sequencing efforts.

Distributional fold change test – a statistical approach for detecting differential expression in microarray experiments

PubMed Central

2012-01-01

Background Because of the large volume of data and the intrinsic variation of data intensity observed in microarray experiments, different statistical methods have been used to systematically extract biological information and to quantify the associated uncertainty. The simplest method to identify differentially expressed genes is to evaluate the ratio of average intensities in two different conditions and consider all genes that differ by more than an arbitrary cut-off value to be differentially expressed. This filtering approach is not a statistical test and there is no associated value that can indicate the level of confidence in the designation of genes as differentially expressed or not differentially expressed. At the same time the fold change by itself provide valuable information and it is important to find unambiguous ways of using this information in expression data treatment. Results A new method of finding differentially expressed genes, called distributional fold change (DFC) test is introduced. The method is based on an analysis of the intensity distribution of all microarray probe sets mapped to a three dimensional feature space composed of average expression level, average difference of gene expression and total variance. The proposed method allows one to rank each feature based on the signal-to-noise ratio and to ascertain for each feature the confidence level and power for being differentially expressed. The performance of the new method was evaluated using the total and partial area under receiver operating curves and tested on 11 data sets from Gene Omnibus Database with independently verified differentially expressed genes and compared with the t-test and shrinkage t-test. Overall the DFC test performed the best – on average it had higher sensitivity and partial AUC and its elevation was most prominent in the low range of differentially expressed features, typical for formalin-fixed paraffin-embedded sample sets. Conclusions The distributional fold change test is an effective method for finding and ranking differentially expressed probesets on microarrays. The application of this test is advantageous to data sets using formalin-fixed paraffin-embedded samples or other systems where degradation effects diminish the applicability of correlation adjusted methods to the whole feature set. PMID:23122055

Developing Land Surface Type Map with Biome Classification Scheme Using Suomi NPP/JPSS VIIRS Data

NASA Astrophysics Data System (ADS)

Zhang, Rui; Huang, Chengquan; Zhan, Xiwu; Jin, Huiran

2016-08-01

Accurate representation of actual terrestrial surface types at regional to global scales is an important element for a wide range of applications, such as land surface parameterization, modeling of biogeochemical cycles, and carbon cycle studies. In this study, in order to meet the requirement of the retrieval of global leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by the vegetation (fPAR) and other studies, a global map generated from Suomi National Polar- orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) surface reflectance data in six major biome classes based on their canopy structures, which include: Grass/Cereal Crops, Shrubs, Broadleaf Crops, Savannas, Broadleaf Forests, and Needleleaf Forests, was created. The primary biome classes were converted from an International Geosphere-Biosphere Program (IGBP) legend global surface type data that was created in previous study, and the separation of two crop types are based on a secondary classification.

A Platform for Combined DNA and Protein Microarrays Based on Total Internal Reflection Fluorescence

PubMed Central

Asanov, Alexander; Zepeda, Angélica; Vaca, Luis

2012-01-01

We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax. PMID:22438738

Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

PubMed Central

Biyani, Manish; Ichiki, Takanori

2015-01-01

Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA)-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing) a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density), ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era. PMID:27600226

Cloudy Earth

NASA Image and Video Library

2015-05-08

Decades of satellite observations and astronaut photographs show that clouds dominate space-based views of Earth. One study based on nearly a decade of satellite data estimated that about 67 percent of Earth’s surface is typically covered by clouds. This is especially the case over the oceans, where other research shows less than 10 percent of the sky is completely clear of clouds at any one time. Over land, 30 percent of skies are completely cloud free. Earth’s cloudy nature is unmistakable in this global cloud fraction map, based on data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite. While MODIS collects enough data to make a new global map of cloudiness every day, this version of the map shows an average of all of the satellite’s cloud observations between July 2002 and April 2015. Colors range from dark blue (no clouds) to light blue (some clouds) to white (frequent clouds).

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

PubMed

Choi, Jae-Seok; Kim, Munchurl

2017-03-01

Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower computational complexity when compared with a super-resolution method based on convolutional neural nets (SRCNN15). Compared with the previous SI method that is limited with a scale factor of 2, GLM-SI shows superior performance with average 0.79 dB higher in PSNR, and can be used for scale factors of 3 or higher.

Multiplex cDNA quantification method that facilitates the standardization of gene expression data

PubMed Central

Gotoh, Osamu; Murakami, Yasufumi; Suyama, Akira

2011-01-01

Microarray-based gene expression measurement is one of the major methods for transcriptome analysis. However, current microarray data are substantially affected by microarray platforms and RNA references because of the microarray method can provide merely the relative amounts of gene expression levels. Therefore, valid comparisons of the microarray data require standardized platforms, internal and/or external controls and complicated normalizations. These requirements impose limitations on the extensive comparison of gene expression data. Here, we report an effective approach to removing the unfavorable limitations by measuring the absolute amounts of gene expression levels on common DNA microarrays. We have developed a multiplex cDNA quantification method called GEP-DEAN (Gene expression profiling by DCN-encoding-based analysis). The method was validated by using chemically synthesized DNA strands of known quantities and cDNA samples prepared from mouse liver, demonstrating that the absolute amounts of cDNA strands were successfully measured with a sensitivity of 18 zmol in a highly multiplexed manner in 7 h. PMID:21415008

Chemiluminescence microarrays in analytical chemistry: a critical review.

PubMed

Seidel, Michael; Niessner, Reinhard

2014-09-01

Multi-analyte immunoassays on microarrays and on multiplex DNA microarrays have been described for quantitative analysis of small organic molecules (e.g., antibiotics, drugs of abuse, small molecule toxins), proteins (e.g., antibodies or protein toxins), and microorganisms, viruses, and eukaryotic cells. In analytical chemistry, multi-analyte detection by use of analytical microarrays has become an innovative research topic because of the possibility of generating several sets of quantitative data for different analyte classes in a short time. Chemiluminescence (CL) microarrays are powerful tools for rapid multiplex analysis of complex matrices. A wide range of applications for CL microarrays is described in the literature dealing with analytical microarrays. The motivation for this review is to summarize the current state of CL-based analytical microarrays. Combining analysis of different compound classes on CL microarrays reduces analysis time, cost of reagents, and use of laboratory space. Applications are discussed, with examples from food safety, water safety, environmental monitoring, diagnostics, forensics, toxicology, and biosecurity. The potential and limitations of research on multiplex analysis by use of CL microarrays are discussed in this review.

Equalizer reduces SNP bias in Affymetrix microarrays.

PubMed

Quigley, David

2015-07-30

Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a reference genome for the relevant species. However, most model organisms and all humans have genomes that deviate from their reference. These variations, which include single nucleotide polymorphisms, insertions of additional nucleotides, and nucleotide deletions, can affect the microarray's performance. Genetic experiments comparing individuals bearing different population-associated single nucleotide polymorphisms that intersect microarray probes are therefore subject to systemic bias, as the reduction in binding efficiency due to a technical artifact is confounded with genetic differences between parental strains. This problem has been recognized for some time, and earlier methods of compensation have attempted to identify probes affected by genome variants using statistical models. These methods may require replicate microarray measurement of gene expression in the relevant tissue in inbred parental samples, which are not always available in model organisms and are never available in humans. By using sequence information for the genomes of organisms under investigation, potentially problematic probes can now be identified a priori. However, there is no published software tool that makes it easy to eliminate these probes from an annotation. I present equalizer, a software package that uses genome variant data to modify annotation files for the commonly used Affymetrix IVT and Gene/Exon platforms. These files can be used by any microarray normalization method for subsequent analysis. I demonstrate how use of equalizer on experiments mapping germline influence on gene expression in a genetic cross between two divergent mouse species and in human samples significantly reduces probe hybridization-induced bias, reducing false positive and false negative findings. The equalizer package reduces probe hybridization bias from experiments performed on the Affymetrix microarray platform, allowing accurate assessment of germline influence on gene expression.

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

Zhou, Yuyu; Smith, Steven J.; Zhao, Kaiguang

Urbanization, one of the major human induced land-cover and land-use changes, has a profound impact on the Earth system including biodiversity, the cycling of water and carbon and exchange of energy and water between Earth’s surface and atmosphere, all affecting weather and climate. Accurate information on urban areas and their spatial distribution at the regional and global scales is important for scientific understanding of their contribution to the changing Earth system, and for practical management and policy decisions. We developed a method to map the urban extent from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime stable-light data atmore » the global level and derived a new global map of 1-km urban extent for year 2000. Based on this map, we found that globally, urban land area is about 0.5% of total land area but ranges widely at regional level from 0.1% in Oceania to 2.3% in Europe. At the country level, urban land area varies from lower than 0.01% to higher than 10%, but is lower than 1% for most (70%) countries. Urbanization follows land mass distribution, as anticipated, with the highest concentration found between 30°N to 45°N latitude and the largest longitudinal peak around 80°W. Based on a sensitivity analysis and comparison with other global urban area products, we found that our global product of urban area provides a reliable estimate of global urban areas and offer the potential of capturing more accurately their spatial and temporal dynamics.« less

Towards a Global Land Subsidence Map

NASA Astrophysics Data System (ADS)

Erkens, G.; Kooi, H.; Sutanudjaja, E.

2017-12-01

Land subsidence is a global problem, but a global land subsidence map is not available yet. Such map is crucial to raise global awareness of land subsidence, as land subsidence causes extensive damage (probably in the order of billions of dollars annually). Insights in the rates of subsidence are particularly relevant for low lying deltas and coastal zones, for which any further loss in elevation is unwanted. With the global land subsidence map relative sea level rise predictions may be improved, contributing to global flood risk calculations. In this contribution, we discuss the approach and progress we have made so far in making a global land subsidence map. The first results will be presented and discussed, and we give an outlook on the work needed to derive a global land subsidence map.

16S rRNA gene-based phylogenetic microarray for simultaneous identification of members of the genus Burkholderia.

PubMed

Schönmann, Susan; Loy, Alexander; Wimmersberger, Céline; Sobek, Jens; Aquino, Catharine; Vandamme, Peter; Frey, Beat; Rehrauer, Hubert; Eberl, Leo

2009-04-01

For cultivation-independent and highly parallel analysis of members of the genus Burkholderia, an oligonucleotide microarray (phylochip) consisting of 131 hierarchically nested 16S rRNA gene-targeted oligonucleotide probes was developed. A novel primer pair was designed for selective amplification of a 1.3 kb 16S rRNA gene fragment of Burkholderia species prior to microarray analysis. The diagnostic performance of the microarray for identification and differentiation of Burkholderia species was tested with 44 reference strains of the genera Burkholderia, Pandoraea, Ralstonia and Limnobacter. Hybridization patterns based on presence/absence of probe signals were interpreted semi-automatically using the novel likelihood-based strategy of the web-tool Phylo- Detect. Eighty-eight per cent of the reference strains were correctly identified at the species level. The evaluated microarray was applied to investigate shifts in the Burkholderia community structure in acidic forest soil upon addition of cadmium, a condition that selected for Burkholderia species. The microarray results were in agreement with those obtained from phylogenetic analysis of Burkholderia 16S rRNA gene sequences recovered from the same cadmiumcontaminated soil, demonstrating the value of the Burkholderia phylochip for determinative and environmental studies.

Setting the scene for SWOT: global maps of river reach hydrodynamic variables

NASA Astrophysics Data System (ADS)

Schumann, Guy J.-P.; Durand, Michael; Pavelsky, Tamlin; Lion, Christine; Allen, George

2017-04-01

Credible and reliable characterization of discharge from the Surface Water and Ocean Topography (SWOT) mission using the Manning-based algorithms needs a prior estimate constraining reach-scale channel roughness, base flow and river bathymetry. For some places, any one of those variables may exist locally or even regionally as a measurement, which is often only at a station, or sometimes as a basin-wide model estimate. However, to date none of those exist at the scale required for SWOT and thus need to be mapped at a continental scale. The prior estimates will be employed for producing initial discharge estimates, which will be used as starting-guesses for the various Manning-based algorithms, to be refined using the SWOT measurements themselves. A multitude of reach-scale variables were derived, including Landsat-based width, SRTM slope and accumulation area. As a possible starting point for building the prior database of low flow, river bathymetry and channel roughness estimates, we employed a variety of sources, including data from all GRDC records, simulations from the long-time runs of the global water balance model (WBM), and reach-based calculations from hydraulic geometry relationships as well as Manning's equation. Here, we present the first global maps of this prior database with some initial validation, caveats and prospective uses.

Global soil-climate-biome diagram: linking soil properties to climate and biota

NASA Astrophysics Data System (ADS)

Zhao, X.; Yang, Y.; Fang, J.

2017-12-01

As a critical component of the Earth system, soils interact strongly with both climate and biota and provide fundamental ecosystem services that maintain food, climate, and human security. Despite significant progress in digital soil mapping techniques and the rapidly growing quantity of observed soil information, quantitative linkages between soil properties, climate and biota at the global scale remain unclear. By compiling a large global soil database, we mapped seven major soil properties (bulk density [BD]; sand, silt and clay fractions; soil pH; soil organic carbon [SOC] density [SOCD]; and soil total nitrogen [STN] density [STND]) based on machine learning algorithms (regional random forest [RF] model) and quantitatively assessed the linkage between soil properties, climate and biota at the global scale. Our results demonstrated a global soil-climate-biome diagram, which improves our understanding of the strong correspondence between soils, climate and biomes. Soil pH decreased with greater mean annual precipitation (MAP) and lower mean annual temperature (MAT), and the critical MAP for the transition from alkaline to acidic soil pH decreased with decreasing MAT. Specifically, the critical MAP ranged from 400-500 mm when the MAT exceeded 10 °C but could decrease to 50-100 mm when the MAT was approximately 0 °C. SOCD and STND were tightly linked; both increased in accordance with lower MAT and higher MAP across terrestrial biomes. Global stocks of SOC and STN were estimated to be 788 ± 39.4 Pg (1015 g, or billion tons) and 63 ± 3.3 Pg in the upper 30-cm soil layer, respectively, but these values increased to 1654 ± 94.5 Pg and 133 ± 7.8 Pg in the upper 100-cm soil layer, respectively. These results reveal quantitative linkages between soil properties, climate and biota at the global scale, suggesting co-evolution of the soil, climate and biota under conditions of global environmental change.

A DNA microarray-based methylation-sensitive (MS)-AFLP hybridization method for genetic and epigenetic analyses.

PubMed

Yamamoto, F; Yamamoto, M

2004-07-01

We previously developed a PCR-based DNA fingerprinting technique named the Methylation Sensitive (MS)-AFLP method, which permits comparative genome-wide scanning of methylation status with a manageable number of fingerprinting experiments. The technique uses the methylation sensitive restriction enzyme NotI in the context of the existing Amplified Fragment Length Polymorphism (AFLP) method. Here we report the successful conversion of this gel electrophoresis-based DNA fingerprinting technique into a DNA microarray hybridization technique (DNA Microarray MS-AFLP). By performing a total of 30 (15 x 2 reciprocal labeling) DNA Microarray MS-AFLP hybridization experiments on genomic DNA from two breast and three prostate cancer cell lines in all pairwise combinations, and Southern hybridization experiments using more than 100 different probes, we have demonstrated that the DNA Microarray MS-AFLP is a reliable method for genetic and epigenetic analyses. No statistically significant differences were observed in the number of differences between the breast-prostate hybridization experiments and the breast-breast or prostate-prostate comparisons.

Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs.

PubMed

Jouffe, Vincent; Rowe, Suzanne; Liaubet, Laurence; Buitenhuis, Bart; Hornshøj, Henrik; SanCristobal, Magali; Mormède, Pierre; de Koning, D J

2009-07-16

Microarray studies can supplement QTL studies by suggesting potential candidate genes in the QTL regions, which by themselves are too large to provide a limited selection of candidate genes. Here we provide a case study where we explore ways to integrate QTL data and microarray data for the pig, which has only a partial genome sequence. We outline various procedures to localize differentially expressed genes on the pig genome and link this with information on published QTL. The starting point is a set of 237 differentially expressed cDNA clones in adrenal tissue from two pig breeds, before and after treatment with adrenocorticotropic hormone (ACTH). Different approaches to localize the differentially expressed (DE) genes to the pig genome showed different levels of success and a clear lack of concordance for some genes between the various approaches. For a focused analysis on 12 genes, overlapping QTL from the public domain were presented. Also, differentially expressed genes underlying QTL for ACTH response were described. Using the latest version of the draft sequence, the differentially expressed genes were mapped to the pig genome. This enabled co-location of DE genes and previously studied QTL regions, but the draft genome sequence is still incomplete and will contain many errors. A further step to explore links between DE genes and QTL at the pathway level was largely unsuccessful due to the lack of annotation of the pig genome. This could be improved by further comparative mapping analyses but this would be time consuming. This paper provides a case study for the integration of QTL data and microarray data for a species with limited genome sequence information and annotation. The results illustrate the challenges that must be addressed but also provide a roadmap for future work that is applicable to other non-model species.

Analysis of large-scale gene expression data.

PubMed

Sherlock, G

2000-04-01

The advent of cDNA and oligonucleotide microarray technologies has led to a paradigm shift in biological investigation, such that the bottleneck in research is shifting from data generation to data analysis. Hierarchical clustering, divisive clustering, self-organizing maps and k-means clustering have all been recently used to make sense of this mass of data.

Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system

PubMed Central

Sunkin, Susan M.; Ng, Lydia; Lau, Chris; Dolbeare, Tim; Gilbert, Terri L.; Thompson, Carol L.; Hawrylycz, Michael; Dang, Chinh

2013-01-01

The Allen Brain Atlas (http://www.brain-map.org) provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate. Here, we review the resources available at the Allen Brain Atlas, describing each product and data type [such as in situ hybridization (ISH) and supporting histology, microarray, RNA sequencing, reference atlases, projection mapping and magnetic resonance imaging]. In addition, standardized and unique features in the web applications are described that enable users to search and mine the various data sets. Features include both simple and sophisticated methods for gene searches, colorimetric and fluorescent ISH image viewers, graphical displays of ISH, microarray and RNA sequencing data, Brain Explorer software for 3D navigation of anatomy and gene expression, and an interactive reference atlas viewer. In addition, cross data set searches enable users to query multiple Allen Brain Atlas data sets simultaneously. All of the Allen Brain Atlas resources can be accessed through the Allen Brain Atlas data portal. PMID:23193282

Cell-Based Microarrays for In Vitro Toxicology

NASA Astrophysics Data System (ADS)

Wegener, Joachim

2015-07-01

DNA/RNA and protein microarrays have proven their outstanding bioanalytical performance throughout the past decades, given the unprecedented level of parallelization by which molecular recognition assays can be performed and analyzed. Cell microarrays (CMAs) make use of similar construction principles. They are applied to profile a given cell population with respect to the expression of specific molecular markers and also to measure functional cell responses to drugs and chemicals. This review focuses on the use of cell-based microarrays for assessing the cytotoxicity of drugs, toxins, or chemicals in general. It also summarizes CMA construction principles with respect to the cell types that are used for such microarrays, the readout parameters to assess toxicity, and the various formats that have been established and applied. The review ends with a critical comparison of CMAs and well-established microtiter plate (MTP) approaches.

A ground truth based comparative study on clustering of gene expression data.

PubMed

Zhu, Yitan; Wang, Zuyi; Miller, David J; Clarke, Robert; Xuan, Jianhua; Hoffman, Eric P; Wang, Yue

2008-05-01

Given the variety of available clustering methods for gene expression data analysis, it is important to develop an appropriate and rigorous validation scheme to assess the performance and limitations of the most widely used clustering algorithms. In this paper, we present a ground truth based comparative study on the functionality, accuracy, and stability of five data clustering methods, namely hierarchical clustering, K-means clustering, self-organizing maps, standard finite normal mixture fitting, and a caBIG toolkit (VIsual Statistical Data Analyzer--VISDA), tested on sample clustering of seven published microarray gene expression datasets and one synthetic dataset. We examined the performance of these algorithms in both data-sufficient and data-insufficient cases using quantitative performance measures, including cluster number detection accuracy and mean and standard deviation of partition accuracy. The experimental results showed that VISDA, an interactive coarse-to-fine maximum likelihood fitting algorithm, is a solid performer on most of the datasets, while K-means clustering and self-organizing maps optimized by the mean squared compactness criterion generally produce more stable solutions than the other methods.

Automated daily processing of more than 1000 ground-based GPS receivers for studying intense ionospheric storms

NASA Astrophysics Data System (ADS)

Komjathy, Attila; Sparks, Lawrence; Wilson, Brian D.; Mannucci, Anthony J.

2005-12-01

As the number of ground-based and space-based receivers tracking the Global Positioning System (GPS) satellites steadily increases, it is becoming possible to monitor changes in the ionosphere continuously and on a global scale with unprecedented accuracy and reliability. As of August 2005, there are more than 1000 globally distributed dual-frequency GPS receivers available using publicly accessible networks including, for example, the International GPS Service and the continuously operating reference stations. To take advantage of the vast amount of GPS data, researchers use a number of techniques to estimate satellite and receiver interfrequency biases and the total electron content (TEC) of the ionosphere. Most techniques estimate vertical ionospheric structure and, simultaneously, hardware-related biases treated as nuisance parameters. These methods often are limited to 200 GPS receivers and use a sequential least squares or Kalman filter approach. The biases are later removed from the measurements to obtain unbiased TEC. In our approach to calibrating GPS receiver and transmitter interfrequency biases we take advantage of all available GPS receivers using a new processing algorithm based on the Global Ionospheric Mapping (GIM) software developed at the Jet Propulsion Laboratory. This new capability is designed to estimate receiver biases for all stations. We solve for the instrumental biases by modeling the ionospheric delay and removing it from the observation equation using precomputed GIM maps. The precomputed GIM maps rely on 200 globally distributed GPS receivers to establish the "background" used to model the ionosphere at the remaining 800 GPS sites.

The Diagnostic Yield of Array Comparative Genomic Hybridization Is High Regardless of Severity of Intellectual Disability/Developmental Delay in Children.

PubMed

D'Arrigo, Stefano; Gavazzi, Francesco; Alfei, Enrico; Zuffardi, Orsetta; Montomoli, Cristina; Corso, Barbara; Buzzi, Erika; Sciacca, Francesca L; Bulgheroni, Sara; Riva, Daria; Pantaleoni, Chiara

2016-05-01

Microarray-based comparative genomic hybridization is a method of molecular analysis that identifies chromosomal anomalies (or copy number variants) that correlate with clinical phenotypes. The aim of the present study was to apply a clinical score previously designated by de Vries to 329 patients with intellectual disability/developmental disorder (intellectual disability/developmental delay) referred to our tertiary center and to see whether the clinical factors are associated with a positive outcome of aCGH analyses. Another goal was to test the association between a positive microarray-based comparative genomic hybridization result and the severity of intellectual disability/developmental delay. Microarray-based comparative genomic hybridization identified structural chromosomal alterations responsible for the intellectual disability/developmental delay phenotype in 16% of our sample. Our study showed that causative copy number variants are frequently found even in cases of mild intellectual disability (30.77%). We want to emphasize the need to conduct microarray-based comparative genomic hybridization on all individuals with intellectual disability/developmental delay, regardless of the severity, because the degree of intellectual disability/developmental delay does not predict the diagnostic yield of microarray-based comparative genomic hybridization. © The Author(s) 2015.

Global Urban Mapping and Modeling for Sustainable Urban Development

NASA Astrophysics Data System (ADS)

Zhou, Y.; Li, X.; Asrar, G.; Yu, S.; Smith, S.; Eom, J.; Imhoff, M. L.

2016-12-01

In the past several decades, the world has experienced fast urbanization, and this trend is expected to continue for decades to come. Urbanization, one of the major land cover and land use changes (LCLUC), is becoming increasingly important in global environmental changes, such as urban heat island (UHI) growth and vegetation phenology change. Better scientific insights and effective decision-making unarguably require reliable science-based information on spatiotemporal changes in urban extent and their environmental impacts. In this study, we developed a globally consistent 20-year urban map series to evaluate the time-reactive nature of global urbanization from the nighttime lights remote sensing data, and projected future urban expansion in the 21st century by employing an integrated modeling framework (Zhou et al. 2014, Zhou et al. 2015). We then evaluated the impacts of urbanization on building energy use and vegetation phenology that affect both ecosystem services and human health. We extended the modeling capability of building energy use in the Global Change Assessment Model (GCAM) with consideration of UHI effects by coupling the remote sensing based urbanization modeling and explored the impact of UHI on building energy use. We also investigated the impact of urbanization on vegetation phenology by using an improved phenology detection algorithm. The derived spatiotemporal information on historical and potential future urbanization and its implications in building energy use and vegetation phenology will be of great value in sustainable urban design and development for building energy use and human health (e.g., pollen allergy), especially when considered together with other factors such as climate variability and change. Zhou, Y., S. J. Smith, C. D. Elvidge, K. Zhao, A. Thomson & M. Imhoff (2014) A cluster-based method to map urban area from DMSP/OLS nightlights. Remote Sensing of Environment, 147, 173-185. Zhou, Y., S. J. Smith, K. Zhao, M. Imhoff, A. Thomson, B. Bond-Lamberty, G. R. Asrar, X. Zhang, C. He & C. D. Elvidge (2015) A global map of urban extent from nightlights. Environmental Research Letters, 10, 054011.

Classification of Microarray Data Using Kernel Fuzzy Inference System

PubMed Central

Kumar Rath, Santanu

2014-01-01

The DNA microarray classification technique has gained more popularity in both research and practice. In real data analysis, such as microarray data, the dataset contains a huge number of insignificant and irrelevant features that tend to lose useful information. Classes with high relevance and feature sets with high significance are generally referred for the selected features, which determine the samples classification into their respective classes. In this paper, kernel fuzzy inference system (K-FIS) algorithm is applied to classify the microarray data (leukemia) using t-test as a feature selection method. Kernel functions are used to map original data points into a higher-dimensional (possibly infinite-dimensional) feature space defined by a (usually nonlinear) function ϕ through a mathematical process called the kernel trick. This paper also presents a comparative study for classification using K-FIS along with support vector machine (SVM) for different set of features (genes). Performance parameters available in the literature such as precision, recall, specificity, F-measure, ROC curve, and accuracy are considered to analyze the efficiency of the classification model. From the proposed approach, it is apparent that K-FIS model obtains similar results when compared with SVM model. This is an indication that the proposed approach relies on kernel function. PMID:27433543

A globally complete map of supraglacial debris cover and a new toolkit for debris cover research

NASA Astrophysics Data System (ADS)

Herreid, Sam; Pellicciotti, Francesca

2017-04-01

A growing canon of literature is focused on resolving the processes and implications of debris cover on glaciers. However, this work is often confined to a handful of glaciers that were likely selected based on criteria optimizing their suitability to test a specific hypothesis or logistical ease. The role of debris cover in a glacier system is likely to not go overlooked in forthcoming research, yet the magnitude of this role at a global scale has not yet been fully described. Here, we present a map of debris cover for all glacierized regions on Earth including the Greenland Ice Sheet using 30 m Landsat data. This dataset will begin to open a wider context to the high quality, localized findings from the debris-covered glacier research community and help inform large-scale modeling efforts. A global map of debris cover also facilitates analysis attempting to isolate first order geomorphological and climate controls of supraglacial debris production. Furthering the objective of expanding the inclusion of debris cover in forthcoming research, we also present an under development suite of open-source, Python based tools. Requiring minimal and often freely available input data, we have automated the mapping of: i) debris cover, ii) ice cliffs, iii) debris cover evolution over the Landsat era and iv) glacier flow instabilities from altered debris structures. At the present time, debris extent is the only globally complete quantity but with the expanding repository of high quality global datasets and further tool development minimizing manual tasks and computational cost, we foresee all of these tools being applied globally in the near future.

Geologic mapping of the Amirani-Gish Bar region of Io: Implications for the global geologic mapping of Io

USGS Publications Warehouse

Williams, D.A.; Keszthelyi, L.P.; Crown, D.A.; Jaeger, W.L.; Schenk, P.M.

2007-01-01

We produced the first geologic map of the Amirani-Gish Bar region of Io, the last of four regional maps generated from Galileo mission data. The Amirani-Gish Bar region has five primary types of geologic materials: plains, mountains, patera floors, flows, and diffuse deposits. The flows and patera floors are thought to be compositionally similar, but are subdivided based on interpretations regarding their emplacement environments and mechanisms. Our mapping shows that volcanic activity in the Amirani-Gish Bar region is dominated by the Amirani Eruptive Center (AEC), now recognized to be part of an extensive, combined Amirani-Maui flow field. A mappable flow connects Amirani and Maui, suggesting that Maui is fed from Amirani, such that the post-Voyager designation "Maui Eruptive Center" should be revised. Amirani contains at least four hot spots detected by Galileo, and is the source of widespread bright (sulfur?) flows and active dark (silicate?) flows being emplaced in the Promethean style (slowly emplaced, compound flow fields). The floor of Gish Bar Patera has been partially resurfaced by dark lava flows, although other parts of its floor are bright and appeared unchanged during the Galileo mission. This suggests that the floor did not undergo complete resurfacing as a lava lake as proposed for other ionian paterae. There are several other hot spots in the region that are the sources of both active dark flows (confined within paterae), and SO2- and S2-rich diffuse deposits. Mapped diffuse deposits around fractures on mountains and in the plains appear to serve as the source for gas venting without the release of magma, an association previously unrecognized in this region. The six mountains mapped in this region exhibit various states of degradation. In addition to gaining insight into this region of Io, all four maps are studied to assess the best methodology to use to produce a new global geologic map of Io based on the newly released, combined Galileo-Voyager global mosaics. To convey the complexity of ionian surface geology, we find that a new global geologic map of Io should include a map sheet displaying the global abundances and types of surface features as well as a complementary GIS database as a means to catalog the record of surface changes observed since the Voyager flybys and during the Galileo mission. ?? 2006 Elsevier Inc. All rights reserved.

Data visualization in interactive maps and time series

NASA Astrophysics Data System (ADS)

Maigne, Vanessa; Evano, Pascal; Brockmann, Patrick; Peylin, Philippe; Ciais, Philippe

2014-05-01

State-of-the-art data visualization has nothing to do with plots and maps we used few years ago. Many opensource tools are now available to provide access to scientific data and implement accessible, interactive, and flexible web applications. Here we will present a web site opened November 2013 to create custom global and regional maps and time series from research models and datasets. For maps, we explore and get access to data sources from a THREDDS Data Server (TDS) with the OGC WMS protocol (using the ncWMS implementation) then create interactive maps with the OpenLayers javascript library and extra information layers from a GeoServer. Maps become dynamic, zoomable, synchroneaously connected to each other, and exportable to Google Earth. For time series, we extract data from a TDS with the Netcdf Subset Service (NCSS) then display interactive graphs with a custom library based on the Data Driven Documents javascript library (D3.js). This time series application provides dynamic functionalities such as interpolation, interactive zoom on different axes, display of point values, and export to different formats. These tools were implemented for the Global Carbon Atlas (http://www.globalcarbonatlas.org): a web portal to explore, visualize, and interpret global and regional carbon fluxes from various model simulations arising from both human activities and natural processes, a work led by the Global Carbon Project.

Comparison between Proteome and Transcriptome Response in Potato (Solanum tuberosum L.) Leaves Following Potato Virus Y (PVY) Infection.

PubMed

Stare, Tjaša; Stare, Katja; Weckwerth, Wolfram; Wienkoop, Stefanie; Gruden, Kristina

2017-07-06

Plant diseases caused by viral infection are affecting all major crops. Being an obligate intracellular organisms, chemical control of these pathogens is so far not applied in the field except to control the insect vectors of the viruses. Understanding of molecular responses of plant immunity is therefore economically important, guiding the enforcement of crop resistance. To disentangle complex regulatory mechanisms of the plant immune responses, understanding system as a whole is a must. However, integrating data from different molecular analysis (transcriptomics, proteomics, metabolomics, smallRNA regulation etc.) is not straightforward. We evaluated the response of potato ( Solanum tuberosum L.) following the infection with potato virus Y (PVY). The response has been analyzed on two molecular levels, with microarray transcriptome analysis and mass spectroscopy-based proteomics. Within this report, we performed detailed analysis of the results on both levels and compared two different approaches for analysis of proteomic data (spectral count versus MaxQuant). To link the data on different molecular levels, each protein was mapped to the corresponding potato transcript according to StNIB paralogue grouping. Only 33% of the proteins mapped to microarray probes in a one-to-one relation and additionally many showed discordance in detected levels of proteins with corresponding transcripts. We discussed functional importance of true biological differences between both levels and showed that the reason for the discordance between transcript and protein abundance lies partly in complexity and structure of biological regulation of proteome and transcriptome and partly in technical issues contributing to it.

Comparison between Proteome and Transcriptome Response in Potato (Solanum tuberosum L.) Leaves Following Potato Virus Y (PVY) Infection

PubMed Central

Stare, Tjaša; Stare, Katja; Weckwerth, Wolfram; Wienkoop, Stefanie

2017-01-01

Plant diseases caused by viral infection are affecting all major crops. Being an obligate intracellular organisms, chemical control of these pathogens is so far not applied in the field except to control the insect vectors of the viruses. Understanding of molecular responses of plant immunity is therefore economically important, guiding the enforcement of crop resistance. To disentangle complex regulatory mechanisms of the plant immune responses, understanding system as a whole is a must. However, integrating data from different molecular analysis (transcriptomics, proteomics, metabolomics, smallRNA regulation etc.) is not straightforward. We evaluated the response of potato (Solanum tuberosum L.) following the infection with potato virus Y (PVY). The response has been analyzed on two molecular levels, with microarray transcriptome analysis and mass spectroscopy-based proteomics. Within this report, we performed detailed analysis of the results on both levels and compared two different approaches for analysis of proteomic data (spectral count versus MaxQuant). To link the data on different molecular levels, each protein was mapped to the corresponding potato transcript according to StNIB paralogue grouping. Only 33% of the proteins mapped to microarray probes in a one-to-one relation and additionally many showed discordance in detected levels of proteins with corresponding transcripts. We discussed functional importance of true biological differences between both levels and showed that the reason for the discordance between transcript and protein abundance lies partly in complexity and structure of biological regulation of proteome and transcriptome and partly in technical issues contributing to it. PMID:28684682

Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results.

PubMed

Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu

2012-06-08

Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

Geology, structure, and statistics of multi-ring basins on Mars

NASA Technical Reports Server (NTRS)

Schultz, Richard A.; Frey, Herbert V.

1990-01-01

Available data on Martian multi-ring basins were compiled and evaluated using the new 1:15 million scale geologic maps of Mars and global topography was revised as base maps. Published center coordinates and ring diameters of Martian basins were plotted by computer and superimposed onto the base maps. In many cases basin centers or ring diameters or both had to be adjusted to achieve a better fit to the revised maps. It was also found that additional basins can explain subcircular topographic lows as well as map patterns of old Noachian materials, volcanic plains units, and channels in the Tharsis region.

Radar Based Navigation in Unknown Terrain

DTIC Science & Technology

2012-12-31

localization and mapping ( SLAM ) approach. The radar processing algorithms detect strong, persistent, and stationary reflectors embedded in the...Global System for Mobile Communications . . . . . . . . . 2 LIDAR Light Detection and Ranging . . . . . . . . . . . . . . . . 2 SAR Synthetic Aperture...22 SLAM Simultaneous Localization and Mapping . . . . . . . . . . 25 FDM Frequency Division Multiplexing

Validation of Satellite Snow Cover Maps in North America and Norway

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Solberg, Rune; Riggs, George A.

2002-01-01

Satellite-derived snow maps from NASA's Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) have been produced since February of 2000. The global maps are available daily at 500-m resolution, and at a climate-modeling grid (CMG) resolution of 1/20 deg (approximately 5.6 km). We compared the 8-day composite CMG MODIS-derived global maps from November 1,2001, through March 21,2002, and daily CMG maps from February 26 - March 5,2002, with National Oceanic and Atmospheric Administration (NOAA) Interactive Multisensor Snow and Ice Mapping System (IMS) 25-km resolution maps for North America. For the Norwegian study area, national snow maps, based on synoptic measurements as well as visual interpretation of AVHRR images, published by the Det Norske Meteorologiske Institutt (Norwegian Meteorological Institute) (MI) maps, as well as Landsat ETM+ images were compared with the MODIS maps. The MODIS-derived maps agreed over most areas with the IMS or MI maps, however, there are important areas of disagreement between the maps, especially when the 8-day composite maps were used. It is concluded that MODIS daily CMG maps should be studied for validation purposes rather than the 8-day composite maps, despite the limitations imposed by cloud obscuration when using the daily maps.

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

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.

Role of OSGIN1 in mediating smoking-induced autophagy in the human airway epithelium.

PubMed

Wang, Guoqing; Zhou, Haixia; Strulovici-Barel, Yael; Al-Hijji, Mohammed; Ou, Xuemei; Salit, Jacqueline; Walters, Matthew S; Staudt, Michelle R; Kaner, Robert J; Crystal, Ronald G

2017-07-03

Enhanced macroautophagy/autophagy is recognized as a component of the pathogenesis of smoking-induced airway disease. Based on the knowledge that enhanced autophagy is linked to oxidative stress and the DNA damage response, both of which are linked to smoking, we used microarray analysis of the airway epithelium to identify smoking upregulated genes known to respond to oxidative stress and the DNA damage response. This analysis identified OSGIN1 (oxidative stress induced growth inhibitor 1) as significantly upregulated by smoking, in both the large and small airway epithelium, an observation confirmed by an independent small airway microarray cohort, TaqMan PCR of large and small airway samples and RNA-Seq of small airway samples. High and low OSGIN1 expressors have different autophagy gene expression patterns in vivo. Genome-wide correlation of RNAseq analysis of airway basal/progenitor cells showed a direct correlation of OSGIN1 mRNA levels to multiple classic autophagy genes. In vitro cigarette smoke extract exposure of primary airway basal/progenitor cells was accompanied by a dose-dependent upregulation of OSGIN1 and autophagy induction. Lentivirus-mediated expression of OSGIN1 in human primary basal/progenitor cells induced puncta-like staining of MAP1LC3B and upregulation of MAP1LC3B mRNA and protein and SQSTM1 mRNA expression level in a dose and time-dependent manner. OSGIN1-induction of autophagosome, amphisome and autolysosome formation was confirmed by colocalization of MAP1LC3B with SQSTM1 or CD63 (endosome marker) and LAMP1 (lysosome marker). Both OSGIN1 overexpression and knockdown enhanced the smoking-evoked autophagic response. Together, these observations support the concept that smoking-induced upregulation of OSGIN1 is one link between smoking-induced stress and enhanced-autophagy in the human airway epithelium.

A fisheye viewer for microarray-based gene expression data

PubMed Central

Wu, Min; Thao, Cheng; Mu, Xiangming; Munson, Ethan V

2006-01-01

Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface – an electronic table (E-table) that uses fisheye distortion technology. Results The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site . The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. Conclusion This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table. PMID:17038193

Firefly algorithm with chaos

NASA Astrophysics Data System (ADS)

Gandomi, A. H.; Yang, X.-S.; Talatahari, S.; Alavi, A. H.

2013-01-01

A recently developed metaheuristic optimization algorithm, firefly algorithm (FA), mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies. In the present study, we will introduce chaos into FA so as to increase its global search mobility for robust global optimization. Detailed studies are carried out on benchmark problems with different chaotic maps. Here, 12 different chaotic maps are utilized to tune the attractive movement of the fireflies in the algorithm. The results show that some chaotic FAs can clearly outperform the standard FA.

Biologically relevant effects of mRNA amplification on gene expression profiles.

PubMed

van Haaften, Rachel I M; Schroen, Blanche; Janssen, Ben J A; van Erk, Arie; Debets, Jacques J M; Smeets, Hubert J M; Smits, Jos F M; van den Wijngaard, Arthur; Pinto, Yigal M; Evelo, Chris T A

2006-04-11

Gene expression microarray technology permits the analysis of global gene expression profiles. The amount of sample needed limits the use of small excision biopsies and/or needle biopsies from human or animal tissues. Linear amplification techniques have been developed to increase the amount of sample derived cDNA. These amplified samples can be hybridised on microarrays. However, little information is available whether microarrays based on amplified and unamplified material yield comparable results. In the present study we compared microarray data obtained from amplified mRNA derived from biopsies of rat cardiac left ventricle and non-amplified mRNA derived from the same organ. Biopsies were linearly amplified to acquire enough material for a microarray experiment. Both amplified and unamplified samples were hybridized to the Rat Expression Set 230 Array of Affymetrix. Analysis of the microarray data showed that unamplified material of two different left ventricles had 99.6% identical gene expression. Gene expression patterns of two biopsies obtained from the same parental organ were 96.3% identical. Similarly, gene expression pattern of two biopsies from dissimilar organs were 92.8% identical to each other.Twenty-one percent of reporters called present in parental left ventricular tissue disappeared after amplification in the biopsies. Those reporters were predominantly seen in the low intensity range. Sequence analysis showed that reporters that disappeared after amplification had a GC-content of 53.7+/-4.0%, while reporters called present in biopsy- and whole LV-samples had an average GC content of 47.8+/-5.5% (P <0.001). Those reporters were also predicted to form significantly more (0.76+/-0.07 versus 0.38+/-0.1) and longer (9.4+/-0.3 versus 8.4+/-0.4) hairpins as compared to representative control reporters present before and after amplification. This study establishes that the gene expression profile obtained after amplification of mRNA of left ventricular biopsies is representative for the whole left ventricle of the rat heart. However, specific gene transcripts present in parental tissues were undetectable in the minute left ventricular biopsies. Transcripts that were lost due to the amplification process were not randomly distributed, but had higher GC-content and hairpins in the sequence and were mainly found in the lower intensity range which includes many transcription factors from specific signalling pathways.

Biologically relevant effects of mRNA amplification on gene expression profiles

PubMed Central

van Haaften, Rachel IM; Schroen, Blanche; Janssen, Ben JA; van Erk, Arie; Debets, Jacques JM; Smeets, Hubert JM; Smits, Jos FM; van den Wijngaard, Arthur; Pinto, Yigal M; Evelo, Chris TA

2006-01-01

Background Gene expression microarray technology permits the analysis of global gene expression profiles. The amount of sample needed limits the use of small excision biopsies and/or needle biopsies from human or animal tissues. Linear amplification techniques have been developed to increase the amount of sample derived cDNA. These amplified samples can be hybridised on microarrays. However, little information is available whether microarrays based on amplified and unamplified material yield comparable results. In the present study we compared microarray data obtained from amplified mRNA derived from biopsies of rat cardiac left ventricle and non-amplified mRNA derived from the same organ. Biopsies were linearly amplified to acquire enough material for a microarray experiment. Both amplified and unamplified samples were hybridized to the Rat Expression Set 230 Array of Affymetrix. Results Analysis of the microarray data showed that unamplified material of two different left ventricles had 99.6% identical gene expression. Gene expression patterns of two biopsies obtained from the same parental organ were 96.3% identical. Similarly, gene expression pattern of two biopsies from dissimilar organs were 92.8% identical to each other. Twenty-one percent of reporters called present in parental left ventricular tissue disappeared after amplification in the biopsies. Those reporters were predominantly seen in the low intensity range. Sequence analysis showed that reporters that disappeared after amplification had a GC-content of 53.7+/-4.0%, while reporters called present in biopsy- and whole LV-samples had an average GC content of 47.8+/-5.5% (P <0.001). Those reporters were also predicted to form significantly more (0.76+/-0.07 versus 0.38+/-0.1) and longer (9.4+/-0.3 versus 8.4+/-0.4) hairpins as compared to representative control reporters present before and after amplification. Conclusion This study establishes that the gene expression profile obtained after amplification of mRNA of left ventricular biopsies is representative for the whole left ventricle of the rat heart. However, specific gene transcripts present in parental tissues were undetectable in the minute left ventricular biopsies. Transcripts that were lost due to the amplification process were not randomly distributed, but had higher GC-content and hairpins in the sequence and were mainly found in the lower intensity range which includes many transcription factors from specific signalling pathways. PMID:16608515

Online, automatic, ionospheric maps: IRI-PLAS-MAP

NASA Astrophysics Data System (ADS)

Arikan, F.; Sezen, U.; Gulyaeva, T. L.; Cilibas, O.

2015-04-01

Global and regional behavior of the ionosphere is an important component of space weather. The peak height and critical frequency of ionospheric layer for the maximum ionization, namely, hmF2 and foF2, and the total number of electrons on a ray path, Total Electron Content (TEC), are the most investigated and monitored values of ionosphere in capturing and observing ionospheric variability. Typically ionospheric models such as International Reference Ionosphere (IRI) can provide electron density profile, critical parameters of ionospheric layers and Ionospheric electron content for a given location, date and time. Yet, IRI model is limited by only foF2 STORM option in reflecting the dynamics of ionospheric/plasmaspheric/geomagnetic storms. Global Ionospheric Maps (GIM) are provided by IGS analysis centers for global TEC distribution estimated from ground-based GPS stations that can capture the actual dynamics of ionosphere and plasmasphere, but this service is not available for other ionospheric observables. In this study, a unique and original space weather service is introduced as IRI-PLAS-MAP from http://www.ionolab.org

Transfection microarray and the applications.

PubMed

Miyake, Masato; Yoshikawa, Tomohiro; Fujita, Satoshi; Miyake, Jun

2009-05-01

Microarray transfection has been extensively studied for high-throughput functional analysis of mammalian cells. However, control of efficiency and reproducibility are the critical issues for practical use. By using solid-phase transfection accelerators and nano-scaffold, we provide a highly efficient and reproducible microarray-transfection device, "transfection microarray". The device would be applied to the limited number of available primary cells and stem cells not only for large-scale functional analysis but also reporter-based time-lapse cellular event analysis.

Improving global paleogeography since the late Paleozoic using paleobiology

NASA Astrophysics Data System (ADS)

Cao, Wenchao; Zahirovic, Sabin; Flament, Nicolas; Williams, Simon; Golonka, Jan; Dietmar Müller, R.

2017-12-01

Paleogeographic reconstructions are important to understand Earth's tectonic evolution, past eustatic and regional sea level change, paleoclimate and ocean circulation, deep Earth resources and to constrain and interpret the dynamic topography predicted by mantle convection models. Global paleogeographic maps have been compiled and published, but they are generally presented as static maps with varying map projections, different time intervals represented by the maps and different plate motion models that underlie the paleogeographic reconstructions. This makes it difficult to convert the maps into a digital form and link them to alternative digital plate tectonic reconstructions. To address this limitation, we develop a workflow to restore global paleogeographic maps to their present-day coordinates and enable them to be linked to a different tectonic reconstruction. We use marine fossil collections from the Paleobiology Database to identify inconsistencies between their indicative paleoenvironments and published paleogeographic maps, and revise the locations of inferred paleo-coastlines that represent the estimated maximum transgression surfaces by resolving these inconsistencies. As a result, the consistency ratio between the paleogeography and the paleoenvironments indicated by the marine fossil collections is increased from an average of 75 % to nearly full consistency (100 %). The paleogeography in the main regions of North America, South America, Europe and Africa is significantly revised, especially in the Late Carboniferous, Middle Permian, Triassic, Jurassic, Late Cretaceous and most of the Cenozoic. The global flooded continental areas since the Early Devonian calculated from the revised paleogeography in this study are generally consistent with results derived from other paleoenvironment and paleo-lithofacies data and with the strontium isotope record in marine carbonates. We also estimate the terrestrial areal change over time associated with transferring reconstruction, filling gaps and modifying the paleogeographic geometries based on the paleobiology test. This indicates that the variation of the underlying plate reconstruction is the main factor that contributes to the terrestrial areal change, and the effect of revising paleogeographic geometries based on paleobiology is secondary.

Space flight alters bacterial gene expression and virulence and reveals a role for global regulator Hfq

PubMed Central

Wilson, J. W.; Ott, C. M.; zu Bentrup, K. Höner; Ramamurthy, R.; Quick, L.; Porwollik, S.; Cheng, P.; McClelland, M.; Tsaprailis, G.; Radabaugh, T.; Hunt, A.; Fernandez, D.; Richter, E.; Shah, M.; Kilcoyne, M.; Joshi, L.; Nelman-Gonzalez, M.; Hing, S.; Parra, M.; Dumars, P.; Norwood, K.; Bober, R.; Devich, J.; Ruggles, A.; Goulart, C.; Rupert, M.; Stodieck, L.; Stafford, P.; Catella, L.; Schurr, M. J.; Buchanan, K.; Morici, L.; McCracken, J.; Allen, P.; Baker-Coleman, C.; Hammond, T.; Vogel, J.; Nelson, R.; Pierson, D. L.; Stefanyshyn-Piper, H. M.; Nickerson, C. A.

2007-01-01

A comprehensive analysis of both the molecular genetic and phenotypic responses of any organism to the space flight environment has never been accomplished because of significant technological and logistical hurdles. Moreover, the effects of space flight on microbial pathogenicity and associated infectious disease risks have not been studied. The bacterial pathogen Salmonella typhimurium was grown aboard Space Shuttle mission STS-115 and compared with identical ground control cultures. Global microarray and proteomic analyses revealed that 167 transcripts and 73 proteins changed expression with the conserved RNA-binding protein Hfq identified as a likely global regulator involved in the response to this environment. Hfq involvement was confirmed with a ground-based microgravity culture model. Space flight samples exhibited enhanced virulence in a murine infection model and extracellular matrix accumulation consistent with a biofilm. Strategies to target Hfq and related regulators could potentially decrease infectious disease risks during space flight missions and provide novel therapeutic options on Earth. PMID:17901201

Global gene expression analysis by combinatorial optimization.

PubMed

Ameur, Adam; Aurell, Erik; Carlsson, Mats; Westholm, Jakub Orzechowski

2004-01-01

Generally, there is a trade-off between methods of gene expression analysis that are precise but labor-intensive, e.g. RT-PCR, and methods that scale up to global coverage but are not quite as quantitative, e.g. microarrays. In the present paper, we show how how a known method of gene expression profiling (K. Kato, Nucleic Acids Res. 23, 3685-3690 (1995)), which relies on a fairly small number of steps, can be turned into a global gene expression measurement by advanced data post-processing, with potentially little loss of accuracy. Post-processing here entails solving an ancillary combinatorial optimization problem. Validation is performed on in silico experiments generated from the FANTOM data base of full-length mouse cDNA. We present two variants of the method. One uses state-of-the-art commercial software for solving problems of this kind, the other a code developed by us specifically for this purpose, released in the public domain under GPL license.

Auditory Evidence Grids

DTIC Science & Technology

2006-01-01

information of the robot (Figure 1) acquired via laser-based localization techniques. The results are maps of the global soundscape . The algorithmic...environments than noise maps. Furthermore, provided the acoustic localization algorithm can detect the sources, the soundscape can be mapped with many...gathering information about the auditory soundscape in which it is working. In addition to robustness in the presence of noise, it has also been

Anorganic bovine bone and a silicate-based synthetic bone activate different microRNAs.

PubMed

Annalisa, Palmieri; Furio, Pezzetti; Ilaria, Zollino; Anna, Avantaggiato; Luca, Scapoli; Marcella, Martinelli; Marzia, Arlotti; Elena, Masiero; Carinci, Francesco

2008-09-01

Bio-Oss (BO), composed of anorganic bovine bone, is widely used in several bone regeneration procedures in oral surgery. PerioGlas (PG) is an alloplastic material that has been used for grafting of periodontal osseous defects since the 1990s. However, how these biomaterials alter osteoblast activity to promote bone formation is poorly understood. We attempted to address this question by using microRNA microarray techniques to investigate differences in translational regulation in osteoblasts exposed to BO and PG. By using miRNA microarrays containing 329 probes designed from human miRNA sequences, we investigated miRNAs whose expression was significantly modified in an osteoblast-like cell line (MG-63) cultured with BO vs PG. Three up-regulated miRNAs (mir-337, mir-200b, mir-377) and 4 down-regulated miRNAs (mir-130a, mir-214, mir-27a, mir-93) were identified. Our results indicated that BO and PG act on different miRNAs. Globally, PG causes activation of bone-forming signaling, whereas BO also activates cartilage-related pathways.

Computational, Integrative, and Comparative Methods for the Elucidation of Genetic Coexpression Networks

DOE PAGES

Baldwin, Nicole E.; Chesler, Elissa J.; Kirov, Stefan; ...

2005-01-01

Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively co-regulated genes and their annotation using gene ontology analysis and cis -regulatory element discovery. Themore » causal basis for co-regulation is detected through the use of quantitative trait locus mapping.« less

Evaluation of prognostic and predictive value of microtubule associated protein tau in two independent cohorts.

PubMed

Baquero, Maria T; Lostritto, Karen; Gustavson, Mark D; Bassi, Kimberly A; Appia, Franck; Camp, Robert L; Molinaro, Annette M; Harris, Lyndsay N; Rimm, David L

2011-11-02

Microtubule associated proteins (MAPs) endogenously regulate microtubule stabilization and have been reported as prognostic and predictive markers for taxane response. The microtubule stabilizer, MAP-tau, has shown conflicting results. We quantitatively assessed MAP-tau expression in two independent breast cancer cohorts to determine prognostic and predictive value of this biomarker. MAP-tau expression was evaluated in the retrospective Yale University breast cancer cohort (n = 651) using tissue microarrays and also in the TAX 307 cohort, a clinical trial randomized for TAC versus FAC chemotherapy (n = 140), using conventional whole tissue sections. Expression was measured using the AQUA method for quantitative immunofluorescence. Scores were correlated with clinicopathologic variables, survival, and response to therapy. Assessment of the Yale cohort using Cox univariate analysis indicated an improved overall survival (OS) in tumors with a positive correlation between high MAP-tau expression and overall survival (OS) (HR = 0.691, 95% CI = 0.489-0.974; P = 0.004). Kaplan Meier analysis showed 10-year survival for 65% of patients with high MAP-tau expression compared to 52% with low expression (P = .006). In TAX 307, high expression was associated with significantly longer median time to tumor progression (TTP) regardless of treatment arm (33.0 versus 23.4 months, P = 0.010) with mean TTP of 31.2 months. Response rates did not differ by MAP-tau expression (P = 0.518) or by treatment arm (P = 0.584). Quantitative measurement of MAP-tau expression has prognostic value in both cohorts, with high expression associated with longer TTP and OS. Differences by treatment arm or response rate in low versus high MAP-tau groups were not observed, indicating that MAP-tau is not associated with response to taxanes and is not a useful predictive marker for taxane-based chemotherapy.

Identifier mapping performance for integrating transcriptomics and proteomics experimental results

PubMed Central

2011-01-01

Background Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms. However, this kind of analysis is well known to be hampered by lack of standardization of identifier nomenclature among proteins, genes, and microarray probe sets. Therefore data integration may also play a role in critiquing the fallible gene identifications that both platforms emit. Results We compared three freely available internet-based identifier mapping resources for mapping UniProt accessions (ACCs) to Affymetrix probesets identifications (IDs): DAVID, EnVision, and NetAffx. Liquid chromatography-tandem mass spectrometry analyses of 91 endometrial cancer and 7 noncancer samples generated 11,879 distinct ACCs. For each ACC, we compared the retrieval sets of probeset IDs from each mapping resource. We confirmed a high level of discrepancy among the mapping resources. On the same samples, mRNA expression was available. Therefore, to evaluate the quality of each ACC-to-probeset match, we calculated proteome-transcriptome correlations, and compared the resources presuming that better mapping of identifiers should generate a higher proportion of mapped pairs with strong inter-platform correlations. A mixture model for the correlations fitted well and supported regression analysis, providing a window into the performance of the mapping resources. The resources have added and dropped matches over two years, but their overall performance has not changed. Conclusions The methods presented here serve to achieve concrete context-specific insight, to support well-informed decisions in choosing an ID mapping strategy for "omic" data merging. PMID:21619611

The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area

Treesearch

Ronald E. McRoberts

2010-01-01

Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing...

Seeing the forest beyond the trees

Treesearch

Sassan Saatchi; Joseph Mascaro; Liang Xu; Michael Keller; Yan Yang; Paul Duffy; Fernando Espirito-Santo; Alessandro Baccini; Jeffery Chambers; David Schimel

2014-01-01

In a recent paper (Mitchard et al. 2014, Global Ecology and Biogeography, 23,935-946) a new map of forest biomass based on a geostatistical model of field data for the Amazon (and surrounding forests) was presented and contrasted with two earlier maps based on remote sensing data Saatchi et al. (2011; RS1) and Baccini et al. (2012; RS2). Mitchard et al....

Global hierarchical classification of deepwater and wetland environments from remote sensing products

NASA Astrophysics Data System (ADS)

Fluet-Chouinard, E.; Lehner, B.; Aires, F.; Prigent, C.; McIntyre, P. B.

2017-12-01

Global surface water maps have improved in spatial and temporal resolutions through various remote sensing methods: open water extents with compiled Landsat archives and inundation with topographically downscaled multi-sensor retrievals. These time-series capture variations through time of open water and inundation without discriminating between hydrographic features (e.g. lakes, reservoirs, river channels and wetland types) as other databases have done as static representation. Available data sources present the opportunity to generate a comprehensive map and typology of aquatic environments (deepwater and wetlands) that improves on earlier digitized inventories and maps. The challenge of classifying surface waters globally is to distinguishing wetland types with meaningful characteristics or proxies (hydrology, water chemistry, soils, vegetation) while accommodating limitations of remote sensing data. We present a new wetland classification scheme designed for global application and produce a map of aquatic ecosystem types globally using state-of-the-art remote sensing products. Our classification scheme combines open water extent and expands it with downscaled multi-sensor inundation data to capture the maximal vegetated wetland extent. The hierarchical structure of the classification is modified from the Cowardin Systems (1979) developed for the USA. The first level classification is based on a combination of landscape positions and water source (e.g. lacustrine, riverine, palustrine, coastal and artificial) while the second level represents the hydrologic regime (e.g. perennial, seasonal, intermittent and waterlogged). Class-specific descriptors can further detail the wetland types with soils and vegetation cover. Our globally consistent nomenclature and top-down mapping allows for direct comparison across biogeographic regions, to upscale biogeochemical fluxes as well as other landscape level functions.

Development of a Digital Microarray with Interferometric Reflectance Imaging

NASA Astrophysics Data System (ADS)

Sevenler, Derin

This dissertation describes a new type of molecular assay for nucleic acids and proteins. We call this technique a digital microarray since it is conceptually similar to conventional fluorescence microarrays, yet it performs enumerative ('digital') counting of the number captured molecules. Digital microarrays are approximately 10,000-fold more sensitive than fluorescence microarrays, yet maintain all of the strengths of the platform including low cost and high multiplexing (i.e., many different tests on the same sample simultaneously). Digital microarrays use gold nanorods to label the captured target molecules. Each gold nanorod on the array is individually detected based on its light scattering, with an interferometric microscopy technique called SP-IRIS. Our optimized high-throughput version of SP-IRIS is able to scan a typical array of 500 spots in less than 10 minutes. Digital DNA microarrays may have utility in applications where sequencing is prohibitively expensive or slow. As an example, we describe a digital microarray assay for gene expression markers of bacterial drug resistance.

Comparison of global brain gene expression profiles between inbred long-sleep and inbred short-sleep mice by high-density gene array hybridization.

PubMed

Xu, Y; Ehringer, M; Yang, F; Sikela, J M

2001-06-01

Inbred long-sleep (ILS) and short-sleep (ISS) mice show significant central nervous system-mediated differences in sleep time for sedative dose of ethanol and are frequently used as a rodent model for ethanol sensitivity. In this study, we have used complementary DNA (cDNA) array hybridization methodology to identify genes that are differentially expressed between the brains of ILS and ISS mice. To carry out this analysis, we used both the gene discovery array (GDA) and the Mouse GEM 1 Microarray. GDA consists of 18,378 nonredundant mouse cDNA clones on a single nylon filter. Complex probes were prepared from total brain mRNA of ILS or ISS mice by using reverse transcription and 33P labeling. The labeled probes were hybridized in parallel to the gene array filters. Data from GDA experiments were analyzed with SQL-Plus and Oracle 8. The GEM microarray includes 8,730 sequence-verified clones on a glass chip. Two fluorescently labeled probes were used to hybridize a microarray simultaneously. Data from GEM experiments were analyzed by using the GEMTools software package (Incyte). Differentially expressed genes identified from each method were confirmed by relative quantitative reverse transcription-polymerase chain reaction (RT-PCR). A total of 41 genes or expressed sequence tags (ESTs) display significant expression level differences between brains of ILS and ISS mice after GDA, GEM1 hybridization, and quantitative RT-PCR confirmation. Among them, 18 clones were expressed higher in ILS mice, and 23 clones were expressed higher in ISS mice. The individual gene or EST's function and mapping information have been analyzed. This study identified 41 genes that are differentially expressed between brains of ILS and ISS mice. Some of them may have biological relevance in mediation of phenotypic variation between ILS and ISS mice for ethanol sensitivity. This study also demonstrates that parallel gene expression comparison with high-density cDNA arrays is a rapid and efficient way to discover potential genes and pathways involved in alcoholism and alcohol-related physiologic processes.

Controlling false-negative errors in microarray differential expression analysis: a PRIM approach.

PubMed

Cole, Steve W; Galic, Zoran; Zack, Jerome A

2003-09-22

Theoretical considerations suggest that current microarray screening algorithms may fail to detect many true differences in gene expression (Type II analytic errors). We assessed 'false negative' error rates in differential expression analyses by conventional linear statistical models (e.g. t-test), microarray-adapted variants (e.g. SAM, Cyber-T), and a novel strategy based on hold-out cross-validation. The latter approach employs the machine-learning algorithm Patient Rule Induction Method (PRIM) to infer minimum thresholds for reliable change in gene expression from Boolean conjunctions of fold-induction and raw fluorescence measurements. Monte Carlo analyses based on four empirical data sets show that conventional statistical models and their microarray-adapted variants overlook more than 50% of genes showing significant up-regulation. Conjoint PRIM prediction rules recover approximately twice as many differentially expressed transcripts while maintaining strong control over false-positive (Type I) errors. As a result, experimental replication rates increase and total analytic error rates decline. RT-PCR studies confirm that gene inductions detected by PRIM but overlooked by other methods represent true changes in mRNA levels. PRIM-based conjoint inference rules thus represent an improved strategy for high-sensitivity screening of DNA microarrays. Freestanding JAVA application at http://microarray.crump.ucla.edu/focus

MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes.

PubMed

Huerta, Mario; Munyi, Marc; Expósito, David; Querol, Enric; Cedano, Juan

2014-06-15

The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Marker-gene database tool: http://ibb.uab.es/mgdb © The Author 2014. Published by Oxford University Press.

Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

PubMed

Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

2009-11-01

Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

Joint mapping of genes and conditions via multidimensional unfolding analysis

PubMed Central

Van Deun, Katrijn; Marchal, Kathleen; Heiser, Willem J; Engelen, Kristof; Van Mechelen, Iven

2007-01-01

Background Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions based on their similarity in overall expression over profiles but also to gain information on more subtle relations between genes and conditions. Getting a clear visual overview of all these patterns in a single easy-to-grasp representation is a useful preliminary analysis step: We propose to use for this purpose an advanced exploratory method, called multidimensional unfolding. Results We present a novel algorithm for multidimensional unfolding that overcomes both general problems and problems that are specific for the analysis of gene expression data sets. Applying the algorithm to two publicly available microarray compendia illustrates its power as a tool for exploratory data analysis: The unfolding analysis of a first data set resulted in a two-dimensional representation which clearly reveals temporal regulation patterns for the genes and a meaningful structure for the time points, while the analysis of a second data set showed the algorithm's ability to go beyond a mere identification of those genes that discriminate between different patient or tissue types. Conclusion Multidimensional unfolding offers a useful tool for preliminary explorations of microarray data: By relying on an easy-to-grasp low-dimensional geometric framework, relations among genes, among conditions and between genes and conditions are simultaneously represented in an accessible way which may reveal interesting patterns in the data. An additional advantage of the method is that it can be applied to the raw data without necessitating the choice of suitable genewise transformations of the data. PMID:17550582

Global Agricultural Monitoring (GLAM) using MODAPS and LANCE Data Products

NASA Astrophysics Data System (ADS)

Anyamba, A.; Pak, E. E.; Majedi, A. H.; Small, J. L.; Tucker, C. J.; Reynolds, C. A.; Pinzon, J. E.; Smith, M. M.

2012-12-01

The Global Inventory Modeling and Mapping Studies / Global Agricultural Monitoring (GIMMS GLAM) system is a web-based geographic application that offers Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and user interface tools to data query and plot MODIS NDVI time series. The system processes near real-time and science quality Terra and Aqua MODIS 8-day composited datasets. These datasets are derived from the MOD09 and MYD09 surface reflectance products which are generated and provided by NASA/GSFC Land and Atmosphere Near Real-time Capability for EOS (LANCE) and NASA/GSFC MODIS Adaptive Processing System (MODAPS). The GIMMS GLAM system is developed and provided by the NASA/GSFC GIMMS group for the U.S. Department of Agriculture / Foreign Agricultural Service / International Production Assessment Division (USDA/FAS/IPAD) Global Agricultural Monitoring project (GLAM). The USDA/FAS/IPAD mission is to provide objective, timely, and regular assessment of the global agricultural production outlook and conditions affecting global food security. This system was developed to improve USDA/FAS/IPAD capabilities for making operational quantitative estimates for crop production and yield estimates based on satellite-derived data. The GIMMS GLAM system offers 1) web map imagery including Terra & Aqua MODIS 8-day composited NDVI, NDVI percent anomaly, and SWIR-NIR-Red band combinations, 2) web map overlays including administrative and 0.25 degree Land Information System (LIS) shape boundaries, and crop land cover masks, and 3) user interface tools to select features, data query, plot, and download MODIS NDVI time series.

A functional genomics tool for the Pacific bluefin tuna: Development of a 44K oligonucleotide microarray from whole-genome sequencing data for global transcriptome analysis.

PubMed

Yasuike, Motoshige; Fujiwara, Atushi; Nakamura, Yoji; Iwasaki, Yuki; Nishiki, Issei; Sugaya, Takuma; Shimizu, Akio; Sano, Motohiko; Kobayashi, Takanori; Ototake, Mitsuru

2016-02-01

Bluefin tunas are one of the most important fishery resources worldwide. Because of high market values, bluefin tuna farming has been rapidly growing during recent years. At present, the most common form of the tuna farming is based on the stocking of wild-caught fish. Therefore, concerns have been raised about the negative impact of the tuna farming on wild stocks. Recently, the Pacific bluefin tuna (PBT), Thunnus orientalis, has succeeded in completing the reproduction cycle under aquaculture conditions, but production bottlenecks remain to be solved because of very little biological information on bluefin tunas. Functional genomics approaches promise to rapidly increase our knowledge on biological processes in the bluefin tuna. Here, we describe the development of the first 44K PBT oligonucleotide microarray (oligo-array), based on whole-genome shotgun (WGS) sequencing and large-scale expressed sequence tags (ESTs) data. In addition, we also introduce an initial 44K PBT oligo-array experiment using in vitro grown peripheral blood leukocytes (PBLs) stimulated with immunostimulants such as lipopolysaccharide (LPS: a cell wall component of Gram-negative bacteria) or polyinosinic:polycytidylic acid (poly I:C: a synthetic mimic of viral infection). This pilot 44K PBT oligo-array analysis successfully addressed distinct immune processes between LPS- and poly I:C- stimulated PBLs. Thus, we expect that this oligo-array will provide an excellent opportunity to analyze global gene expression profiles for a better understanding of diseases and stress, as well as for reproduction, development and influence of nutrition on tuna aquaculture production. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Screening Mammalian Cells on a Hydrogel: Functionalized Small Molecule Microarray.

PubMed

Zhu, Biwei; Jiang, Bo; Na, Zhenkun; Yao, Shao Q

2017-01-01

Mammalian cell-based microarray technology has gained wide attention, for its plethora of promising applications. The platform is able to provide simultaneous information on multiple parameters for a given target, or even multiple target proteins, in a complex biological system. Here we describe the preparation of mammalian cell-based microarrays using selectively captured of human prostate cancer cells (PC-3). This platform was then used in controlled drug release and measuring the associated drug effects on these cancer cells.

Profiling In Situ Microbial Community Structure with an Amplification Microarray

PubMed Central

Knickerbocker, Christopher; Bryant, Lexi; Golova, Julia; Wiles, Cory; Williams, Kenneth H.; Peacock, Aaron D.; Long, Philip E.

2013-01-01

The objectives of this study were to unify amplification, labeling, and microarray hybridization chemistries within a single, closed microfluidic chamber (an amplification microarray) and verify technology performance on a series of groundwater samples from an in situ field experiment designed to compare U(VI) mobility under conditions of various alkalinities (as HCO3−) during stimulated microbial activity accompanying acetate amendment. Analytical limits of detection were between 2 and 200 cell equivalents of purified DNA. Amplification microarray signatures were well correlated with 16S rRNA-targeted quantitative PCR results and hybridization microarray signatures. The succession of the microbial community was evident with and consistent between the two microarray platforms. Amplification microarray analysis of acetate-treated groundwater showed elevated levels of iron-reducing bacteria (Flexibacter, Geobacter, Rhodoferax, and Shewanella) relative to the average background profile, as expected. Identical molecular signatures were evident in the transect treated with acetate plus NaHCO3, but at much lower signal intensities and with a much more rapid decline (to nondetection). Azoarcus, Thaurea, and Methylobacterium were responsive in the acetate-only transect but not in the presence of bicarbonate. Observed differences in microbial community composition or response to bicarbonate amendment likely had an effect on measured rates of U reduction, with higher rates probable in the part of the field experiment that was amended with bicarbonate. The simplification in microarray-based work flow is a significant technological advance toward entirely closed-amplicon microarray-based tests and is generally extensible to any number of environmental monitoring applications. PMID:23160129

Modeling Global Urbanization Supported by Nighttime Light Remote Sensing

NASA Astrophysics Data System (ADS)

Zhou, Y.

2015-12-01

Urbanization, a major driver of global change, profoundly impacts our physical and social world, for example, altering carbon cycling and climate. Understanding these consequences for better scientific insights and effective decision-making unarguably requires accurate information on urban extent and its spatial distributions. In this study, we developed a cluster-based method to estimate the optimal thresholds and map urban extents from the nighttime light remote sensing data, extended this method to the global domain by developing a computational method (parameterization) to estimate the key parameters in the cluster-based method, and built a consistent 20-year global urban map series to evaluate the time-reactive nature of global urbanization (e.g. 2000 in Fig. 1). Supported by urban maps derived from nightlights remote sensing data and socio-economic drivers, we developed an integrated modeling framework to project future urban expansion by integrating a top-down macro-scale statistical model with a bottom-up urban growth model. With the models calibrated and validated using historical data, we explored urban growth at the grid level (1-km) over the next two decades under a number of socio-economic scenarios. The derived spatiotemporal information of historical and potential future urbanization will be of great value with practical implications for developing adaptation and risk management measures for urban infrastructure, transportation, energy, and water systems when considered together with other factors such as climate variability and change, and high impact weather events.

Basin boundaries and focal points in a map coming from Bairstow's method.

PubMed

Gardini, Laura; Bischi, Gian-Italo; Fournier-Prunaret, Daniele

1999-06-01

This paper is devoted to the study of the global dynamical properties of a two-dimensional noninvertible map, with a denominator which can vanish, obtained by applying Bairstow's method to a cubic polynomial. It is shown that the complicated structure of the basins of attraction of the fixed points is due to the existence of singularities such as sets of nondefinition, focal points, and prefocal curves, which are specific to maps with a vanishing denominator, and have been recently introduced in the literature. Some global bifurcations that change the qualitative structure of the basin boundaries, are explained in terms of contacts among these singularities. The techniques used in this paper put in evidence some new dynamic behaviors and bifurcations, which are peculiar of maps with denominator; hence they can be applied to the analysis of other classes of maps coming from iterative algorithms (based on Newton's method, or others). (c) 1999 American Institute of Physics.

Specific Discrimination of Three Pathogenic Salmonella enterica subsp. enterica Serotypes by carB-Based Oligonucleotide Microarray

PubMed Central

Shin, Hwa Hui; Hwang, Byeong Hee; Seo, Jeong Hyun

2014-01-01

It is important to rapidly and selectively detect and analyze pathogenic Salmonella enterica subsp. enterica in contaminated food to reduce the morbidity and mortality of Salmonella infection and to guarantee food safety. In the present work, we developed an oligonucleotide microarray containing duplicate specific capture probes based on the carB gene, which encodes the carbamoyl phosphate synthetase large subunit, as a competent biomarker evaluated by genetic analysis to selectively and efficiently detect and discriminate three S. enterica subsp. enterica serotypes: Choleraesuis, Enteritidis, and Typhimurium. Using the developed microarray system, three serotype targets were successfully analyzed in a range as low as 1.6 to 3.1 nM and were specifically discriminated from each other without nonspecific signals. In addition, the constructed microarray did not have cross-reactivity with other common pathogenic bacteria and even enabled the clear discrimination of the target Salmonella serotype from a bacterial mixture. Therefore, these results demonstrated that our novel carB-based oligonucleotide microarray can be used as an effective and specific detection system for S. enterica subsp. enterica serotypes. PMID:24185846

Specific discrimination of three pathogenic Salmonella enterica subsp. enterica serotypes by carB-based oligonucleotide microarray.

PubMed

Shin, Hwa Hui; Hwang, Byeong Hee; Seo, Jeong Hyun; Cha, Hyung Joon

2014-01-01

It is important to rapidly and selectively detect and analyze pathogenic Salmonella enterica subsp. enterica in contaminated food to reduce the morbidity and mortality of Salmonella infection and to guarantee food safety. In the present work, we developed an oligonucleotide microarray containing duplicate specific capture probes based on the carB gene, which encodes the carbamoyl phosphate synthetase large subunit, as a competent biomarker evaluated by genetic analysis to selectively and efficiently detect and discriminate three S. enterica subsp. enterica serotypes: Choleraesuis, Enteritidis, and Typhimurium. Using the developed microarray system, three serotype targets were successfully analyzed in a range as low as 1.6 to 3.1 nM and were specifically discriminated from each other without nonspecific signals. In addition, the constructed microarray did not have cross-reactivity with other common pathogenic bacteria and even enabled the clear discrimination of the target Salmonella serotype from a bacterial mixture. Therefore, these results demonstrated that our novel carB-based oligonucleotide microarray can be used as an effective and specific detection system for S. enterica subsp. enterica serotypes.

Advantages of RNA-seq compared to RNA microarrays for transcriptome profiling of anterior cruciate ligament tears.

PubMed

Rai, Muhammad Farooq; Tycksen, Eric D; Sandell, Linda J; Brophy, Robert H

2018-01-01

Microarrays and RNA-seq are at the forefront of high throughput transcriptome analyses. Since these methodologies are based on different principles, there are concerns about the concordance of data between the two techniques. The concordance of RNA-seq and microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed in clinically derived ligament tissues. To demonstrate the concordance between RNA-seq and microarrays and to assess potential benefits of RNA-seq over microarrays, we assessed differences in transcript expression in anterior cruciate ligament (ACL) tissues based on time-from-injury. ACL remnants were collected from patients with an ACL tear at the time of ACL reconstruction. RNA prepared from torn ACL remnants was subjected to Agilent microarrays (N = 24) and RNA-seq (N = 8). The correlation of biological replicates in RNA-seq and microarrays data was similar (0.98 vs. 0.97), demonstrating that each platform has high internal reproducibility. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarrays values were moderate. The cross-platform concordance for differentially expressed transcripts or enriched pathways was linearly correlated (r = 0.64). RNA-Seq was superior in detecting low abundance transcripts and differentiating biologically critical isoforms. Additional independent validation of transcript expression was undertaken using microfluidic PCR for selected genes. PCR data showed 100% concordance (in expression pattern) with RNA-seq and microarrays data. These findings demonstrate that RNA-seq has advantages over microarrays for transcriptome profiling of ligament tissues when available and affordable. Furthermore, these findings are likely transferable to other musculoskeletal tissues where tissue collection is challenging and cells are in low abundance. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:484-497, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

The 'PUCE CAFE' Project: the First 15K Coffee Microarray, a New Tool for Discovering Candidate Genes correlated to Agronomic and Quality Traits

PubMed Central

2011-01-01

Background Understanding the genetic elements that contribute to key aspects of coffee biology will have an impact on future agronomical improvements for this economically important tree. During the past years, EST collections were generated in Coffee, opening the possibility to create new tools for functional genomics. Results The "PUCE CAFE" Project, organized by the scientific consortium NESTLE/IRD/CIRAD, has developed an oligo-based microarray using 15,721 unigenes derived from published coffee EST sequences mostly obtained from different stages of fruit development and leaves in Coffea Canephora (Robusta). Hybridizations for two independent experiments served to compare global gene expression profiles in three types of tissue matter (mature beans, leaves and flowers) in C. canephora as well as in the leaves of three different coffee species (C. canephora, C. eugenoides and C. arabica). Microarray construction, statistical analyses and validation by Q-PCR analysis are presented in this study. Conclusion We have generated the first 15 K coffee array during this PUCE CAFE project, granted by Génoplante (the French consortium for plant genomics). This new tool will help study functional genomics in a wide range of experiments on various plant tissues, such as analyzing bean maturation or resistance to pathogens or drought. Furthermore, the use of this array has proven to be valid in different coffee species (diploid or tetraploid), drastically enlarging its impact for high-throughput gene expression in the community of coffee research. PMID:21208403

Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

NASA Technical Reports Server (NTRS)

Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.

2002-01-01

The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 x g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies.

The 'PUCE CAFE' Project: the first 15K coffee microarray, a new tool for discovering candidate genes correlated to agronomic and quality traits.

PubMed

Privat, Isabelle; Bardil, Amélie; Gomez, Aureliano Bombarely; Severac, Dany; Dantec, Christelle; Fuentes, Ivanna; Mueller, Lukas; Joët, Thierry; Pot, David; Foucrier, Séverine; Dussert, Stéphane; Leroy, Thierry; Journot, Laurent; de Kochko, Alexandre; Campa, Claudine; Combes, Marie-Christine; Lashermes, Philippe; Bertrand, Benoit

2011-01-05

Understanding the genetic elements that contribute to key aspects of coffee biology will have an impact on future agronomical improvements for this economically important tree. During the past years, EST collections were generated in Coffee, opening the possibility to create new tools for functional genomics. The "PUCE CAFE" Project, organized by the scientific consortium NESTLE/IRD/CIRAD, has developed an oligo-based microarray using 15,721 unigenes derived from published coffee EST sequences mostly obtained from different stages of fruit development and leaves in Coffea Canephora (Robusta). Hybridizations for two independent experiments served to compare global gene expression profiles in three types of tissue matter (mature beans, leaves and flowers) in C. canephora as well as in the leaves of three different coffee species (C. canephora, C. eugenoides and C. arabica). Microarray construction, statistical analyses and validation by Q-PCR analysis are presented in this study. We have generated the first 15 K coffee array during this PUCE CAFE project, granted by Génoplante (the French consortium for plant genomics). This new tool will help study functional genomics in a wide range of experiments on various plant tissues, such as analyzing bean maturation or resistance to pathogens or drought. Furthermore, the use of this array has proven to be valid in different coffee species (diploid or tetraploid), drastically enlarging its impact for high-throughput gene expression in the community of coffee research.

Transcriptomic Studies of the Effect of nod Gene-Inducing Molecules in Rhizobia: Different Weapons, One Purpose

PubMed Central

Jiménez-Guerrero, Irene; Acosta-Jurado, Sebastián; Navarro-Gómez, Pilar; López-Baena, Francisco Javier; Ollero, Francisco Javier

2017-01-01

Simultaneous quantification of transcripts of the whole bacterial genome allows the analysis of the global transcriptional response under changing conditions. RNA-seq and microarrays are the most used techniques to measure these transcriptomic changes, and both complement each other in transcriptome profiling. In this review, we exhaustively compiled the symbiosis-related transcriptomic reports (microarrays and RNA sequencing) carried out hitherto in rhizobia. This review is specially focused on transcriptomic changes that takes place when five rhizobial species, Bradyrhizobium japonicum (=diazoefficiens) USDA 110, Rhizobium leguminosarum biovar viciae 3841, Rhizobium tropici CIAT 899, Sinorhizobium (=Ensifer) meliloti 1021 and S. fredii HH103, recognize inducing flavonoids, plant-exuded phenolic compounds that activate the biosynthesis and export of Nod factors (NF) in all analysed rhizobia. Interestingly, our global transcriptomic comparison also indicates that each rhizobial species possesses its own arsenal of molecular weapons accompanying the set of NF in order to establish a successful interaction with host legumes. PMID:29267254

Selection of optimal oligonucleotide probes for microarrays usingmultiple criteria, global alignment and parameter estimation.

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

Li, Xingyuan; He, Zhili; Zhou, Jizhong

2005-10-30

The oligonucleotide specificity for microarray hybridizationcan be predicted by its sequence identity to non-targets, continuousstretch to non-targets, and/or binding free energy to non-targets. Mostcurrently available programs only use one or two of these criteria, whichmay choose 'false' specific oligonucleotides or miss 'true' optimalprobes in a considerable proportion. We have developed a software tool,called CommOligo using new algorithms and all three criteria forselection of optimal oligonucleotide probes. A series of filters,including sequence identity, free energy, continuous stretch, GC content,self-annealing, distance to the 3'-untranslated region (3'-UTR) andmelting temperature (Tm), are used to check each possibleoligonucleotide. A sequence identity is calculated based onmore » gapped globalalignments. A traversal algorithm is used to generate alignments for freeenergy calculation. The optimal Tm interval is determined based on probecandidates that have passed all other filters. Final probes are pickedusing a combination of user-configurable piece-wise linear functions andan iterative process. The thresholds for identity, stretch and freeenergy filters are automatically determined from experimental data by anaccessory software tool, CommOligo_PE (CommOligo Parameter Estimator).The program was used to design probes for both whole-genome and highlyhomologous sequence data. CommOligo and CommOligo_PE are freely availableto academic users upon request.« less

Global maps of streamflow characteristics based on observations from several thousand catchments

NASA Astrophysics Data System (ADS)

Beck, Hylke; van Dijk, Albert; de Roo, Ad

2015-04-01

Streamflow (Q) estimation in ungauged catchments is one of the greatest challenges facing hydrologists. Observed Q from three to four thousand small-to-medium sized catchments (10-10000 km2) around the globe were used to train neural network ensembles to estimate Q characteristics based on climate and physiographic characteristics of the catchments. In total 17 Q characteristics were selected, including mean annual Q, baseflow index, and a number of flow percentiles. Testing coefficients of determination for the estimation of the Q characteristics ranged from 0.55 for the baseflow recession constant to 0.93 for the Q timing. Overall, climate indices dominated among the predictors. Predictors related to soils and geology were relatively unimportant, perhaps due to their data quality. The trained neural network ensembles were subsequently applied spatially over the entire ice-free land surface, resulting in global maps of the Q characteristics (0.125° resolution). These maps possess several unique features: they represent observation-driven estimates; are based on an unprecedentedly large set of catchments; and have associated uncertainty estimates. The maps can be used for various hydrological applications, including the diagnosis of macro-scale hydrological models. To demonstrate this, the produced maps were compared to equivalent maps derived from the simulated daily Q of four macro-scale hydrological models, highlighting various opportunities for improvement in model Q behavior. The produced dataset is available via http://water.jrc.ec.europa.eu.

Data-based estimates of the ocean carbon sink variability - first results of the Surface Ocean pCO2 Mapping intercomparison (SOCOM)

NASA Astrophysics Data System (ADS)

Rödenbeck, C.; Bakker, D. C. E.; Gruber, N.; Iida, Y.; Jacobson, A. R.; Jones, S.; Landschützer, P.; Metzl, N.; Nakaoka, S.; Olsen, A.; Park, G.-H.; Peylin, P.; Rodgers, K. B.; Sasse, T. P.; Schuster, U.; Shutler, J. D.; Valsala, V.; Wanninkhof, R.; Zeng, J.

2015-12-01

Using measurements of the surface-ocean CO2 partial pressure (pCO2) and 14 different pCO2 mapping methods recently collated by the Surface Ocean pCO2 Mapping intercomparison (SOCOM) initiative, variations in regional and global sea-air CO2 fluxes are investigated. Though the available mapping methods use widely different approaches, we find relatively consistent estimates of regional pCO2 seasonality, in line with previous estimates. In terms of interannual variability (IAV), all mapping methods estimate the largest variations to occur in the eastern equatorial Pacific. Despite considerable spread in the detailed variations, mapping methods that fit the data more closely also tend to agree more closely with each other in regional averages. Encouragingly, this includes mapping methods belonging to complementary types - taking variability either directly from the pCO2 data or indirectly from driver data via regression. From a weighted ensemble average, we find an IAV amplitude of the global sea-air CO2 flux of 0.31 PgC yr-1 (standard deviation over 1992-2009), which is larger than simulated by biogeochemical process models. From a decadal perspective, the global ocean CO2 uptake is estimated to have gradually increased since about 2000, with little decadal change prior to that. The weighted mean net global ocean CO2 sink estimated by the SOCOM ensemble is -1.75 PgC yr-1 (1992-2009), consistent within uncertainties with estimates from ocean-interior carbon data or atmospheric oxygen trends.

Generating Multi-Destination Maps.

PubMed

Zhang, Junsong; Fan, Jiepeng; Luo, Zhenshan

2017-08-01

Multi-destination maps are a kind of navigation maps aimed to guide visitors to multiple destinations within a region, which can be of great help to urban visitors. However, they have not been developed in the current online map service. To address this issue, we introduce a novel layout model designed especially for generating multi-destination maps, which considers the global and local layout of a multi-destination map. We model the layout problem as a graph drawing that satisfies a set of hard and soft constraints. In the global layout phase, we balance the scale factor between ROIs. In the local layout phase, we make all edges have good visibility and optimize the map layout to preserve the relative length and angle of roads. We also propose a perturbation-based optimization method to find an optimal layout in the complex solution space. The multi-destination maps generated by our system are potential feasible on the modern mobile devices and our result can show an overview and a detail view of the whole map at the same time. In addition, we perform a user study to evaluate the effectiveness of our method, and the results prove that the multi-destination maps achieve our goals well.

Lunar Reconnaissance Orbiter Camera (LROC) instrument overview

USGS Publications Warehouse

Robinson, M.S.; Brylow, S.M.; Tschimmel, M.; Humm, D.; Lawrence, S.J.; Thomas, P.C.; Denevi, B.W.; Bowman-Cisneros, E.; Zerr, J.; Ravine, M.A.; Caplinger, M.A.; Ghaemi, F.T.; Schaffner, J.A.; Malin, M.C.; Mahanti, P.; Bartels, A.; Anderson, J.; Tran, T.N.; Eliason, E.M.; McEwen, A.S.; Turtle, E.; Jolliff, B.L.; Hiesinger, H.

2010-01-01

The Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) and Narrow Angle Cameras (NACs) are on the NASA Lunar Reconnaissance Orbiter (LRO). The WAC is a 7-color push-frame camera (100 and 400 m/pixel visible and UV, respectively), while the two NACs are monochrome narrow-angle linescan imagers (0.5 m/pixel). The primary mission of LRO is to obtain measurements of the Moon that will enable future lunar human exploration. The overarching goals of the LROC investigation include landing site identification and certification, mapping of permanently polar shadowed and sunlit regions, meter-scale mapping of polar regions, global multispectral imaging, a global morphology base map, characterization of regolith properties, and determination of current impact hazards.

A high-resolution physically-based global flood hazard map

NASA Astrophysics Data System (ADS)

Kaheil, Y.; Begnudelli, L.; McCollum, J.

2016-12-01

We present the results from a physically-based global flood hazard model. The model uses a physically-based hydrologic model to simulate river discharges, and 2D hydrodynamic model to simulate inundation. The model is set up such that it allows the application of large-scale flood hazard through efficient use of parallel computing. For hydrology, we use the Hillslope River Routing (HRR) model. HRR accounts for surface hydrology using Green-Ampt parameterization. The model is calibrated against observed discharge data from the Global Runoff Data Centre (GRDC) network, among other publicly-available datasets. The parallel-computing framework takes advantage of the river network structure to minimize cross-processor messages, and thus significantly increases computational efficiency. For inundation, we implemented a computationally-efficient 2D finite-volume model with wetting/drying. The approach consists of simulating flood along the river network by forcing the hydraulic model with the streamflow hydrographs simulated by HRR, and scaled up to certain return levels, e.g. 100 years. The model is distributed such that each available processor takes the next simulation. Given an approximate criterion, the simulations are ordered from most-demanding to least-demanding to ensure that all processors finalize almost simultaneously. Upon completing all simulations, the maximum envelope of flood depth is taken to generate the final map. The model is applied globally, with selected results shown from different continents and regions. The maps shown depict flood depth and extent at different return periods. These maps, which are currently available at 3 arc-sec resolution ( 90m) can be made available at higher resolutions where high resolution DEMs are available. The maps can be utilized by flood risk managers at the national, regional, and even local levels to further understand their flood risk exposure, exercise certain measures of mitigation, and/or transfer the residual risk financially through flood insurance programs.

Robust Kalman filtering cooperated Elman neural network learning for vision-sensing-based robotic manipulation with global stability.

PubMed

Zhong, Xungao; Zhong, Xunyu; Peng, Xiafu

2013-10-08

In this paper, a global-state-space visual servoing scheme is proposed for uncalibrated model-independent robotic manipulation. The scheme is based on robust Kalman filtering (KF), in conjunction with Elman neural network (ENN) learning techniques. The global map relationship between the vision space and the robotic workspace is learned using an ENN. This learned mapping is shown to be an approximate estimate of the Jacobian in global space. In the testing phase, the desired Jacobian is arrived at using a robust KF to improve the ENN learning result so as to achieve robotic precise convergence of the desired pose. Meanwhile, the ENN weights are updated (re-trained) using a new input-output data pair vector (obtained from the KF cycle) to ensure robot global stability manipulation. Thus, our method, without requiring either camera or model parameters, avoids the corrupted performances caused by camera calibration and modeling errors. To demonstrate the proposed scheme's performance, various simulation and experimental results have been presented using a six-degree-of-freedom robotic manipulator with eye-in-hand configurations.

Towards the Redefinition of the Global Stratigraphy of Mercury: The Case of Intermediate Plains

NASA Astrophysics Data System (ADS)

Galluzzi, V.; Rothery, D. A.; Massironi, M.; Ferranti, L.; Mercury Mapping Team

2018-05-01

Observations based on an average mapping scale of 1:400k provide context for the redefinition of the global stratigraphy of Mercury. Results show that the Intermediate Plains unit should be re-introduced as an official mappable terrain.

Thermodynamically optimal whole-genome tiling microarray design and validation.

PubMed

Cho, Hyejin; Chou, Hui-Hsien

2016-06-13

Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations. Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome. This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.

Identification of sero-reactive antigens for the early diagnosis of Johne’s disease in cattle

PubMed Central

Randall, Arlo; Grohn, Yrjo T.; Katani, Robab; Schilling, Megan; Radzio-Basu, Jessica

2017-01-01

Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of Johne’s disease (JD), a chronic intestinal inflammatory disease of cattle and other ruminants. JD has a high herd prevalence and causes serious animal health problems and significant economic loss in domesticated ruminants throughout the world. Since serological detection of MAP infected animals during the early stages of infection remains challenging due to the low sensitivity of extant assays, we screened 180 well-characterized serum samples using a whole proteome microarray from Mycobacterium tuberculosis (MTB), a close relative of MAP. Based on extensive testing of serum and milk samples, fecal culture and qPCR for direct detection of MAP, the samples were previously assigned to one of 4 groups: negative low exposure (n = 30, NL); negative high exposure (n = 30, NH); fecal positive, ELISA negative (n = 60, F+E-); and fecal positive, ELISA positive (n = 60, F+E+). Of the 740 reactive proteins, several antigens were serologically recognized early but not late in infection, suggesting a complex and dynamic evolution of the MAP humoral immune response during disease progression. Ordinal logistic regression models identified a subset of 47 candidate proteins with significantly different normalized intensity values (p<0.05), including 12 in the NH and 23 in F+E- groups, suggesting potential utility for the early detection of MAP infected animals. Next, the diagnostic utility of four MAP orthologs (MAP1569, MAP2942c, MAP2609, and MAP1272c) was assessed and reveal moderate to high diagnostic sensitivities (range 48.3% to 76.7%) and specificity (range 96.7% to 100%), with a combined 88.3% sensitivity and 96.7% specificity. Taken together, the results of our analyses have identified several candidate MAP proteins of potential utility for the early detection of MAP infection, as well individual MAP proteins that may serve as the foundation for the next generation of well-defined serological diagnosis of JD in cattle. PMID:28863177

On the use of Schwarz-Christoffel conformal mappings to the grid generation for global ocean models

NASA Astrophysics Data System (ADS)

Xu, S.; Wang, B.; Liu, J.

2015-02-01

In this article we propose two conformal mapping based grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithms are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the basic grid design problem of pole relocation, these new algorithms also address more advanced issues such as smoothed scaling factor, or the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling where complex land-ocean distribution is present.

Mars: Detaching of the Free Water Signature (FWS) Presence Regions on the Base of HEND/ODYSSEY Data and Their Correlation with Some Permafrost Features from MOC Data

NASA Technical Reports Server (NTRS)

Kuzmin, R. O.; Mitrofanov, I. G.; Litvak, M. L.; Boynton, M. V.; Saunders, R. S.

2003-01-01

The first results from global mapping of the neutron albedo from Mars by HEND instrument have shown the noticeable deficit of both the epithermal (EN) and the fast (FN) neutrons counts rate in the high latitudes regions of both hemispheres of the planet. The deficit is indicative for high enriching of the surface regolith by hydrogen, which may correspond to amount of any water phases and forms. The objectives of our study are the spatial and temporal variations of the free water (ice) signature in the Martian surface layer on the base of HEND/ODYSSEY data and their correlation with spatial spreading of some permafrost features, mapped on the base of MOC images. For the study we used the results of the global mapping (pixel 5 x5 ) of EN and FN albedo, realized by HEND/ODYSSEY in the period from 17 February to 10 December 2002 year.

BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

PubMed Central

2010-01-01

Background The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems'-level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log2- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets. PMID:20128918

Mapping the Future Today: The Community College of Baltimore County Geospatial Applications Program

ERIC Educational Resources Information Center

Jeffrey, Scott; Alvarez, Jaime

2010-01-01

The Geospatial Applications Program at the Community College of Baltimore County (CCBC), located five miles west of downtown Baltimore, Maryland, provides comprehensive instruction in geographic information systems (GIS), remote sensing and global positioning systems (GPS). Geospatial techniques, which include computer-based mapping and remote…

Satellite-based peatland mapping: potential of the MODIS sensor.

Treesearch

D. Pflugmacher; O.N. Krankina; W.B. Cohen

2006-01-01

Peatlands play a major role in the global carbon cycle but are largely overlooked in current large-scale vegetation mapping efforts. In this study, we investigated the potential of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to capture extent and distribution of peatlands in the St. Petersburg region of Russia.

Event-Based Tone Mapping for Asynchronous Time-Based Image Sensor

PubMed Central

Simon Chane, Camille; Ieng, Sio-Hoi; Posch, Christoph; Benosman, Ryad B.

2016-01-01

The asynchronous time-based neuromorphic image sensor ATIS is an array of autonomously operating pixels able to encode luminance information with an exceptionally high dynamic range (>143 dB). This paper introduces an event-based methodology to display data from this type of event-based imagers, taking into account the large dynamic range and high temporal accuracy that go beyond available mainstream display technologies. We introduce an event-based tone mapping methodology for asynchronously acquired time encoded gray-level data. A global and a local tone mapping operator are proposed. Both are designed to operate on a stream of incoming events rather than on time frame windows. Experimental results on real outdoor scenes are presented to evaluate the performance of the tone mapping operators in terms of quality, temporal stability, adaptation capability, and computational time. PMID:27642275

Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

PubMed

Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter

2014-01-01

A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

Comparison of Global Transcriptional Responses of Chicken Following Primary and Secondary Eimeria acervulina Infections

USDA-ARS?s Scientific Manuscript database

In the current study, we compared chicken gene transcriptional profiles following primary and secondary infections with Eimeria acervulina using a 9.6K avian intestinal intraepithelial lymphocyte cDNA microarray (AVIELA). Gene Ontology analysis showed that primary infection significantly modulated ...

Human population, urban settlement patterns and their impact on Plasmodium falciparum malaria endemicity.

PubMed

Tatem, Andrew J; Guerra, Carlos A; Kabaria, Caroline W; Noor, Abdisalan M; Hay, Simon I

2008-10-27

The efficient allocation of financial resources for malaria control and the optimal distribution of appropriate interventions require accurate information on the geographic distribution of malaria risk and of the human populations it affects. Low population densities in rural areas and high population densities in urban areas can influence malaria transmission substantially. Here, the Malaria Atlas Project (MAP) global database of Plasmodium falciparum parasite rate (PfPR) surveys, medical intelligence and contemporary population surfaces are utilized to explore these relationships and other issues involved in combining malaria risk maps with those of human population distribution in order to define populations at risk more accurately. First, an existing population surface was examined to determine if it was sufficiently detailed to be used reliably as a mask to identify areas of very low and very high population density as malaria free regions. Second, the potential of international travel and health guidelines (ITHGs) for identifying malaria free cities was examined. Third, the differences in PfPR values between surveys conducted in author-defined rural and urban areas were examined. Fourth, the ability of various global urban extent maps to reliably discriminate these author-based classifications of urban and rural in the PfPR database was investigated. Finally, the urban map that most accurately replicated the author-based classifications was analysed to examine the effects of urban classifications on PfPR values across the entire MAP database. Masks of zero population density excluded many non-zero PfPR surveys, indicating that the population surface was not detailed enough to define areas of zero transmission resulting from low population densities. In contrast, the ITHGs enabled the identification and mapping of 53 malaria free urban areas within endemic countries. Comparison of PfPR survey results showed significant differences between author-defined 'urban' and 'rural' designations in Africa, but not for the remainder of the malaria endemic world. The Global Rural Urban Mapping Project (GRUMP) urban extent mask proved most accurate for mapping these author-defined rural and urban locations, and further sub-divisions of urban extents into urban and peri-urban classes enabled the effects of high population densities on malaria transmission to be mapped and quantified. The availability of detailed, contemporary census and urban extent data for the construction of coherent and accurate global spatial population databases is often poor. These known sources of uncertainty in population surfaces and urban maps have the potential to be incorporated into future malaria burden estimates. Currently, insufficient spatial information exists globally to identify areas accurately where population density is low enough to impact upon transmission. Medical intelligence does however exist to reliably identify malaria free cities. Moreover, in Africa, urban areas that have a significant effect on malaria transmission can be mapped.

High resolution global flood hazard map from physically-based hydrologic and hydraulic models.

NASA Astrophysics Data System (ADS)

Begnudelli, L.; Kaheil, Y.; McCollum, J.

2017-12-01

The global flood map published online at http://www.fmglobal.com/research-and-resources/global-flood-map at 90m resolution is being used worldwide to understand flood risk exposure, exercise certain measures of mitigation, and/or transfer the residual risk financially through flood insurance programs. The modeling system is based on a physically-based hydrologic model to simulate river discharges, and 2D shallow-water hydrodynamic model to simulate inundation. The model can be applied to large-scale flood hazard mapping thanks to several solutions that maximize its efficiency and the use of parallel computing. The hydrologic component of the modeling system is the Hillslope River Routing (HRR) hydrologic model. HRR simulates hydrological processes using a Green-Ampt parameterization, and is calibrated against observed discharge data from several publicly-available datasets. For inundation mapping, we use a 2D Finite-Volume Shallow-Water model with wetting/drying. We introduce here a grid Up-Scaling Technique (UST) for hydraulic modeling to perform simulations at higher resolution at global scale with relatively short computational times. A 30m SRTM is now available worldwide along with higher accuracy and/or resolution local Digital Elevation Models (DEMs) in many countries and regions. UST consists of aggregating computational cells, thus forming a coarser grid, while retaining the topographic information from the original full-resolution mesh. The full-resolution topography is used for building relationships between volume and free surface elevation inside cells and computing inter-cell fluxes. This approach almost achieves computational speed typical of the coarse grids while preserving, to a significant extent, the accuracy offered by the much higher resolution available DEM. The simulations are carried out along each river of the network by forcing the hydraulic model with the streamflow hydrographs generated by HRR. Hydrographs are scaled so that the peak corresponds to the return period corresponding to the hazard map being produced (e.g. 100 years, 500 years). Each numerical simulation models one river reach, except for the longest reaches which are split in smaller parts. Here we show results for selected river basins worldwide.

SimArray: a user-friendly and user-configurable microarray design tool

PubMed Central

Auburn, Richard P; Russell, Roslin R; Fischer, Bettina; Meadows, Lisa A; Sevillano Matilla, Santiago; Russell, Steven

2006-01-01

Background Microarrays were first developed to assess gene expression but are now also used to map protein-binding sites and to assess allelic variation between individuals. Regardless of the intended application, efficient production and appropriate array design are key determinants of experimental success. Inefficient production can make larger-scale studies prohibitively expensive, whereas poor array design makes normalisation and data analysis problematic. Results We have developed a user-friendly tool, SimArray, which generates a randomised spot layout, computes a maximum meta-grid area, and estimates the print time, in response to user-specified design decisions. Selected parameters include: the number of probes to be printed; the microtitre plate format; the printing pin configuration, and the achievable spot density. SimArray is compatible with all current robotic spotters that employ 96-, 384- or 1536-well microtitre plates, and can be configured to reflect most production environments. Print time and maximum meta-grid area estimates facilitate evaluation of each array design for its suitability. Randomisation of the spot layout facilitates correction of systematic biases by normalisation. Conclusion SimArray is intended to help both established researchers and those new to the microarray field to develop microarray designs with randomised spot layouts that are compatible with their specific production environment. SimArray is an open-source program and is available from . PMID:16509966

Microtiter plate-based antibody microarrays for bacteria and toxins

USDA-ARS?s Scientific Manuscript database

Research has focused on the development of rapid biosensor-based, high-throughput, and multiplexed detection of pathogenic bacteria in foods. Specifically, antibody microarrays in 96-well microtiter plates have been generated for the purpose of selective detection of Shiga toxin-producing E. coli (...

Microarray-based Comparative Genomic Indexing of the Cronobacter genus (Enterobacter sakazakii)

USDA-ARS?s Scientific Manuscript database

Cronobacter is a recently defined genus synonymous with Enterobacter sakazakii. This new genus currently comprises 6 genomospecies. To extend our understanding of the genetic relationship between Cronobacter sakazakii BAA-894 and the other species of this genus, microarray-based comparative genomi...

Towards large-scale mapping of urban three-dimensional structure using Landsat imagery and global elevation datasets

NASA Astrophysics Data System (ADS)

Wang, P.; Huang, C.

2017-12-01

The three-dimensional (3D) structure of buildings and infrastructures is fundamental to understanding and modelling of the impacts and challenges of urbanization in terms of energy use, carbon emissions, and earthquake vulnerabilities. However, spatially detailed maps of urban 3D structure have been scarce, particularly in fast-changing developing countries. We present here a novel methodology to map the volume of buildings and infrastructures at 30 meter resolution using a synergy of Landsat imagery and openly available global digital surface models (DSMs), including the Shuttle Radar Topography Mission (SRTM), ASTER Global Digital Elevation Map (GDEM), ALOS World 3D - 30m (AW3D30), and the recently released global DSM from the TanDEM-X mission. Our method builds on the concept of object-based height profile to extract height metrics from the DSMs and use a machine learning algorithm to predict height and volume from the height metrics. We have tested this algorithm in the entire England and assessed our result using Lidar measurements in 25 England cities. Our initial assessments achieved a RMSE of 1.4 m (R2 = 0.72) for building height and a RMSE of 1208.7 m3 (R2 = 0.69) for building volume, demonstrating the potential of large-scale applications and fully automated mapping of urban structure.

Competency-Based Objectives in Global Underserved Women's Health for Medical Trainees.

PubMed

Chen, Chi Chiung Grace; Dougherty, Anne; Whetstone, Sara; Mama, Saifuddin T; Larkins-Pettigrew, Margaret; Raine, Susan P; Autry, Amy M

2017-10-01

The Association of Professors of Gynecology and Obstetrics Committee on Global Health developed an inclusive definition of global women's health and competency-based objectives that reflected work internationally, as well as with U.S. vulnerable and underserved populations, such as refugee and immigrant populations or those who would otherwise have compromised access to health care. The knowledge, skill, and attitude-based competencies required to fulfill each learning objective were mapped to the Accreditation Council for Graduate Medical Education Outcomes Project's educational domains and the Consortium of Universities for Global Health competency domains. The proposed global women's health definition and competency-based learning objective framework is a first step in ensuring quality standards for educating trainees to address global women's health needs. By proposing these objectives, we hope to guide future program development and spark a broader conversation that will improve health for vulnerable women and shape educational, ethical, and equitable global health experiences for medical trainees.

Effects of Temperature on the Meiotic Recombination Landscape of the Yeast Saccharomyces cerevisiae

PubMed Central

Zhang, Ke; Wu, Xue-Chang

2017-01-01

ABSTRACT Although meiosis in warm-blooded organisms takes place in a narrow temperature range, meiosis in many organisms occurs over a wide variety of temperatures. We analyzed the properties of meiosis in the yeast Saccharomyces cerevisiae in cells sporulated at 14°C, 30°C, or 37°C. Using comparative-genomic-hybridization microarrays, we examined the distribution of Spo11-generated meiosis-specific double-stranded DNA breaks throughout the genome. Although there were between 300 and 400 regions of the genome with high levels of recombination (hot spots) observed at each temperature, only about 20% of these hot spots were found to have occurred independently of the temperature. In S. cerevisiae, regions near the telomeres and centromeres tend to have low levels of meiotic recombination. This tendency was observed in cells sporulated at 14°C and 30°C, but not at 37°C. Thus, the temperature of sporulation in yeast affects some global property of chromosome structure relevant to meiotic recombination. Using single-nucleotide polymorphism (SNP)-specific whole-genome microarrays, we also examined crossovers and their associated gene conversion events as well as gene conversion events that were unassociated with crossovers in all four spores of tetrads obtained by sporulation of diploids at 14°C, 30°C, or 37°C. Although tetrads from cells sporulated at 30°C had slightly (20%) more crossovers than those derived from cells sporulated at the other two temperatures, spore viability was good at all three temperatures. Thus, despite temperature-induced variation in the genetic maps, yeast cells produce viable haploid products at a wide variety of sporulation temperatures. PMID:29259092

A reconnaissance method for delineation of tracts for regional-scale mineral-resource assessment based on geologic-map data

USGS Publications Warehouse

Raines, G.L.; Mihalasky, M.J.

2002-01-01

The U.S. Geological Survey (USGS) is proposing to conduct a global mineral-resource assessment using geologic maps, significant deposits, and exploration history as minimal data requirements. Using a geologic map and locations of significant pluton-related deposits, the pluton-related-deposit tract maps from the USGS national mineral-resource assessment have been reproduced with GIS-based analysis and modeling techniques. Agreement, kappa, and Jaccard's C correlation statistics between the expert USGS and calculated tract maps of 87%, 40%, and 28%, respectively, have been achieved using a combination of weights-of-evidence and weighted logistic regression methods. Between the experts' and calculated maps, the ranking of states measured by total permissive area correlates at 84%. The disagreement between the experts and calculated results can be explained primarily by tracts defined by geophysical evidence not considered in the calculations, generalization of tracts by the experts, differences in map scales, and the experts' inclusion of large tracts that are arguably not permissive. This analysis shows that tracts for regional mineral-resource assessment approximating those delineated by USGS experts can be calculated using weights of evidence and weighted logistic regression, a geologic map, and the location of significant deposits. Weights of evidence and weighted logistic regression applied to a global geologic map could provide quickly a useful reconnaissance definition of tracts for mineral assessment that is tied to the data and is reproducible. ?? 2002 International Association for Mathematical Geology.

New global hydrography derived from spaceborne elevation data

USGS Publications Warehouse

Lehner, B.; Verdin, K.; Jarvis, A.

2008-01-01

In response to these limitations, a team of scientists has developed data and created maps of the world's rivers that provide the research community with more reliable information about where streams and watersheds occur on the Earth's surface and how water drains the landscape. The new product, known as HydroSHEDS (Hydrological Data and Maps Based on Shuttle Elevation Derivatives at Multiple Scales), provides this information at a resolution and quality unachieved by previous global data sets, such as HYDRO1k [U.S. Geological Survey (USGS), 2000].

Tree-centric mapping of forest carbon density from airborne laser scanning and hyperspectral data.

PubMed

Dalponte, Michele; Coomes, David A

2016-10-01

Forests are a major component of the global carbon cycle, and accurate estimation of forest carbon stocks and fluxes is important in the context of anthropogenic global change. Airborne laser scanning (ALS) data sets are increasingly recognized as outstanding data sources for high-fidelity mapping of carbon stocks at regional scales.We develop a tree-centric approach to carbon mapping, based on identifying individual tree crowns (ITCs) and species from airborne remote sensing data, from which individual tree carbon stocks are calculated. We identify ITCs from the laser scanning point cloud using a region-growing algorithm and identifying species from airborne hyperspectral data by machine learning. For each detected tree, we predict stem diameter from its height and crown-width estimate. From that point on, we use well-established approaches developed for field-based inventories: above-ground biomasses of trees are estimated using published allometries and summed within plots to estimate carbon density.We show this approach is highly reliable: tests in the Italian Alps demonstrated a close relationship between field- and ALS-based estimates of carbon stocks ( r 2  = 0·98). Small trees are invisible from the air, and a correction factor is required to accommodate this effect.An advantage of the tree-centric approach over existing area-based methods is that it can produce maps at any scale and is fundamentally based on field-based inventory methods, making it intuitive and transparent. Airborne laser scanning, hyperspectral sensing and computational power are all advancing rapidly, making it increasingly feasible to use ITC approaches for effective mapping of forest carbon density also inside wider carbon mapping programs like REDD++.

Rapid Spoligotyping of Mycobacterium tuberculosis Complex Bacteria by Use of a Microarray System with Automatic Data Processing and Assignment

PubMed Central

Ruettger, Anke; Nieter, Johanna; Skrypnyk, Artem; Engelmann, Ines; Ziegler, Albrecht; Moser, Irmgard; Monecke, Stefan; Ehricht, Ralf

2012-01-01

Membrane-based spoligotyping has been converted to DNA microarray format to qualify it for high-throughput testing. We have shown the assay's validity and suitability for direct typing from tissue and detecting new spoligotypes. Advantages of the microarray methodology include rapidity, ease of operation, automatic data processing, and affordability. PMID:22553239

Rapid spoligotyping of Mycobacterium tuberculosis complex bacteria by use of a microarray system with automatic data processing and assignment.

PubMed

Ruettger, Anke; Nieter, Johanna; Skrypnyk, Artem; Engelmann, Ines; Ziegler, Albrecht; Moser, Irmgard; Monecke, Stefan; Ehricht, Ralf; Sachse, Konrad

2012-07-01

Membrane-based spoligotyping has been converted to DNA microarray format to qualify it for high-throughput testing. We have shown the assay's validity and suitability for direct typing from tissue and detecting new spoligotypes. Advantages of the microarray methodology include rapidity, ease of operation, automatic data processing, and affordability.

Identification and handling of artifactual gene expression profiles emerging in microarray hybridization experiments

PubMed Central

Brodsky, Leonid; Leontovich, Andrei; Shtutman, Michael; Feinstein, Elena

2004-01-01

Mathematical methods of analysis of microarray hybridizations deal with gene expression profiles as elementary units. However, some of these profiles do not reflect a biologically relevant transcriptional response, but rather stem from technical artifacts. Here, we describe two technically independent but rationally interconnected methods for identification of such artifactual profiles. Our diagnostics are based on detection of deviations from uniformity, which is assumed as the main underlying principle of microarray design. Method 1 is based on detection of non-uniformity of microarray distribution of printed genes that are clustered based on the similarity of their expression profiles. Method 2 is based on evaluation of the presence of gene-specific microarray spots within the slides’ areas characterized by an abnormal concentration of low/high differential expression values, which we define as ‘patterns of differentials’. Applying two novel algorithms, for nested clustering (method 1) and for pattern detection (method 2), we can make a dual estimation of the profile’s quality for almost every printed gene. Genes with artifactual profiles detected by method 1 may then be removed from further analysis. Suspicious differential expression values detected by method 2 may be either removed or weighted according to the probabilities of patterns that cover them, thus diminishing their input in any further data analysis. PMID:14999086

AccuTyping: new algorithms for automated analysis of data from high-throughput genotyping with oligonucleotide microarrays

PubMed Central

Hu, Guohong; Wang, Hui-Yun; Greenawalt, Danielle M.; Azaro, Marco A.; Luo, Minjie; Tereshchenko, Irina V.; Cui, Xiangfeng; Yang, Qifeng; Gao, Richeng; Shen, Li; Li, Honghua

2006-01-01

Microarray-based analysis of single nucleotide polymorphisms (SNPs) has many applications in large-scale genetic studies. To minimize the influence of experimental variation, microarray data usually need to be processed in different aspects including background subtraction, normalization and low-signal filtering before genotype determination. Although many algorithms are sophisticated for these purposes, biases are still present. In the present paper, new algorithms for SNP microarray data analysis and the software, AccuTyping, developed based on these algorithms are described. The algorithms take advantage of a large number of SNPs included in each assay, and the fact that the top and bottom 20% of SNPs can be safely treated as homozygous after sorting based on their ratios between the signal intensities. These SNPs are then used as controls for color channel normalization and background subtraction. Genotype calls are made based on the logarithms of signal intensity ratios using two cutoff values, which were determined after training the program with a dataset of ∼160 000 genotypes and validated by non-microarray methods. AccuTyping was used to determine >300 000 genotypes of DNA and sperm samples. The accuracy was shown to be >99%. AccuTyping can be downloaded from . PMID:16982644

A novel DFNB31 mutation associated with Usher type 2 syndrome showing variable degrees of auditory loss in a consanguineous Portuguese family.

PubMed

Audo, Isabelle; Bujakowska, Kinga; Mohand-Saïd, Saddek; Tronche, Sophie; Lancelot, Marie-Elise; Antonio, Aline; Germain, Aurore; Lonjou, Christine; Carpentier, Wassila; Sahel, José-Alain; Bhattacharya, Shomi; Zeitz, Christina

2011-01-01

To identify the genetic defect of a consanguineous Portuguese family with rod-cone dystrophy and varying degrees of decreased audition. A detailed ophthalmic and auditory examination was performed on a Portuguese patient with severe autosomal recessive rod-cone dystrophy. Known genetic defects were excluded by performing autosomal recessive retinitis pigmentosa (arRP) genotyping microarray analysis and by Sanger sequencing of the coding exons and flanking intronic regions of eyes shut homolog-drosophila (EYS) and chromosome 2 open reading frame 71 (C2orf71). Subsequently, genome-wide homozygosity mapping was performed in DNA samples from available family members using a 700K single nucleotide polymorphism (SNP) microarray. Candidate genes present in the significantly large homozygous regions were screened for mutations using Sanger sequencing. The largest homozygous region (~11 Mb) in the affected family members was mapped to chromosome 9, which harbors deafness, autosomal recessive 31 (DFNB31; a gene previously associated with Usher syndrome). Mutation analysis of DFNB31 in the index patient identified a novel one-base-pair deletion (c.737delC), which is predicted to lead to a truncated protein (p.Pro246HisfsX13) and co-segregated with the disease in the family. Ophthalmic examination of the index patient and the affected siblings showed severe rod-cone dystrophy. Pure tone audiometry revealed a moderate hearing loss in the index patient, whereas the affected siblings were reported with more profound and early onset hearing impairment. We report a novel truncating mutation in DFNB31 associated with severe rod-cone dystrophy and varying degrees of hearing impairment in a consanguineous family of Portuguese origin. This is the second report of DFNB31 implication in Usher type 2.

High Quality Genomic Copy Number Data from Archival Formalin-Fixed Paraffin-Embedded Leiomyosarcoma: Optimisation of Universal Linkage System Labelling

PubMed Central

Salawu, Abdulazeez; Ul-Hassan, Aliya; Hammond, David; Fernando, Malee; Reed, Malcolm; Sisley, Karen

2012-01-01

Most soft tissue sarcomas are characterized by genetic instability and frequent genomic copy number aberrations that are not subtype-specific. Oligonucleotide microarray-based Comparative Genomic Hybridisation (array CGH) is an important technique used to map genome-wide copy number aberrations, but the traditional requirement for high-quality DNA typically obtained from fresh tissue has limited its use in sarcomas. Although large archives of Formalin-fixed Paraffin-embedded (FFPE) tumour samples are available for research, the degradative effects of formalin on DNA from these tissues has made labelling and analysis by array CGH technically challenging. The Universal Linkage System (ULS) may be used for a one-step chemical labelling of such degraded DNA. We have optimised the ULS labelling protocol to perform aCGH on archived FFPE leiomyosarcoma tissues using the 180k Agilent platform. Preservation age of samples ranged from a few months to seventeen years and the DNA showed a wide range of degradation (when visualised on agarose gels). Consistently high DNA labelling efficiency and low microarray probe-to-probe variation (as measured by the derivative log ratio spread) was seen. Comparison of paired fresh and FFPE samples from identical tumours showed good correlation of CNAs detected. Furthermore, the ability to macro-dissect FFPE samples permitted the detection of CNAs that were masked in fresh tissue. Aberrations were visually confirmed using Fluorescence in situ Hybridisation. These results suggest that archival FFPE tissue, with its relative abundance and attendant clinical data may be used for effective mapping for genomic copy number aberrations in such rare tumours as leiomyosarcoma and potentially unravel clues to tumour origins, progression and ultimately, targeted treatment. PMID:23209738

A DNA microarray-based assay to detect dual infection with two dengue virus serotypes.

PubMed

Díaz-Badillo, Alvaro; Muñoz, María de Lourdes; Perez-Ramirez, Gerardo; Altuzar, Victor; Burgueño, Juan; Mendoza-Alvarez, Julio G; Martínez-Muñoz, Jorge P; Cisneros, Alejandro; Navarrete-Espinosa, Joel; Sanchez-Sinencio, Feliciano

2014-04-25

Here; we have described and tested a microarray based-method for the screening of dengue virus (DENV) serotypes. This DNA microarray assay is specific and sensitive and can detect dual infections with two dengue virus serotypes and single-serotype infections. Other methodologies may underestimate samples containing more than one serotype. This technology can be used to discriminate between the four DENV serotypes. Single-stranded DNA targets were covalently attached to glass slides and hybridised with specific labelled probes. DENV isolates and dengue samples were used to evaluate microarray performance. Our results demonstrate that the probes hybridized specifically to DENV serotypes; with no detection of unspecific signals. This finding provides evidence that specific probes can effectively identify single and double infections in DENV samples.

A DNA Microarray-Based Assay to Detect Dual Infection with Two Dengue Virus Serotypes

PubMed Central

Díaz-Badillo, Alvaro; de Lourdes Muñoz, María; Perez-Ramirez, Gerardo; Altuzar, Victor; Burgueño, Juan; Mendoza-Alvarez, Julio G.; Martínez-Muñoz, Jorge P.; Cisneros, Alejandro; Navarrete-Espinosa, Joel; Sanchez-Sinencio, Feliciano

2014-01-01

Here; we have described and tested a microarray based-method for the screening of dengue virus (DENV) serotypes. This DNA microarray assay is specific and sensitive and can detect dual infections with two dengue virus serotypes and single-serotype infections. Other methodologies may underestimate samples containing more than one serotype. This technology can be used to discriminate between the four DENV serotypes. Single-stranded DNA targets were covalently attached to glass slides and hybridised with specific labelled probes. DENV isolates and dengue samples were used to evaluate microarray performance. Our results demonstrate that the probes hybridized specifically to DENV serotypes; with no detection of unspecific signals. This finding provides evidence that specific probes can effectively identify single and double infections in DENV samples. PMID:24776933

A Topographic Image Map of The Mc-18 Quadrangle "coprates" At 1: 2,000,000 Using Data Obtained From The Mars Orbiter Camera and The Mars Orbiter Laser Altimeter of Mars Global Surveyor

NASA Astrophysics Data System (ADS)

Niedermaier, G.; Wählisch, M.; van Gasselt, S.; Scholten, F.; Wewel, F.; Roatsch, T.; Matz, K.-D.; Jaumann, R.

We present a new topographic image map of Mars using 8 bit data obtained from the Mars Orbiter Camera (MOC) of the Mars Global Surveyor (MGS) [1]. The new map covers the Mars surface from 270 E (90 W) to 315 E (45 W) and from 0 North to 30 South with a resolution of 231.529 m/pixel (256 pixel/degree). For map creation, digital image processing methods have been applied. Furthermore, we managed to de- velop a general processing method for creating image mosaics based on MOC data. From a total amount of 66,081 images, 4,835 images (4,339 Context and 496 Geodesy images [3]) were finally used for the creation of the mosaic. After radiometric and brightness corrections, the images were Mars referenced [5], geometrically [6] cor- rected and sinusoidal map projected [4] using a global Martian Digital Terrain Model (DTM), developed by the DLR and based on MGS Mars Orbiter Laser Altimeter (MOLA) topographic datasets [2]. Three layers of MOC mosaics were created, which were stacked afterwards. The upper layer contains the context images with a resolution < 250 m/pixel. The middle layer contains the images of the Geodesy Campaign with a resolution < 250 m/pixel. The bottom layer consists of the Geodesy Campaign im- ages with a resolution > 250 m/pixel and < 435 m/pixel. The contour lines have been extracted from the global Martian DTM, developed at DLR. The contour data were imported as vector data into Macromedia Freehand as separate layer and corrected interactively. The map format of 1,15 m × 1,39 m represents the western part of the MDIM2 j quadrangle. The map is used for geological and morphological interpreta- tions in order to review and improve our current Viking-based knowledge about the Martian surface. References: [1] www.msss.com [2] wufs.wustl.edu [3] Caplinger, M. and M. Malin, The Mars Orbiter Camera Geodesy Campaign, JGR, in press. [4] Scholten, F., Vol XXXI, Part B2, Wien, 1996, p.351-356 [5] naif.jpl.nasa.gov [6] Kirk, R.L. et al., Geometric Calibration of the Mars Orbiter Cameras and Coalignment with Mars Orbiter Laser Altimeter, (abstract #1863), LPSC XXXII, 2001

Methods for transcriptomic analyses of the porcine host immune response: application to Salmonella infection using microarrays

USDA-ARS?s Scientific Manuscript database

Technological developments in both the collection and analysis of molecular genetic data over the past few years have provided new opportunities for an improved understanding of the global response to pathogen exposure. Such developments are particularly dramatic for scientists studying the pig, whe...

Evaluation of Montanide ISA 71 VG adjuvant during profilin vaccination against experimental coccidiosis

USDA-ARS?s Scientific Manuscript database

Chickens were immunized subcutaneously with an Eimeria recombinant profilin protein plus ISA 70 VG (ISA 70) or ISA 71 VG (ISA 71) water-in-oil adjuvants, or with profilin alone, and comparative RNA microarray hybridizations were performed to ascertain global transcriptome changes induced by profilin...

Optimized Probe Masking for Comparative Transcriptomics of Closely Related Species

PubMed Central

Poeschl, Yvonne; Delker, Carolin; Trenner, Jana; Ullrich, Kristian Karsten; Quint, Marcel; Grosse, Ivo

2013-01-01

Microarrays are commonly applied to study the transcriptome of specific species. However, many available microarrays are restricted to model organisms, and the design of custom microarrays for other species is often not feasible. Hence, transcriptomics approaches of non-model organisms as well as comparative transcriptomics studies among two or more species often make use of cost-intensive RNAseq studies or, alternatively, by hybridizing transcripts of a query species to a microarray of a closely related species. When analyzing these cross-species microarray expression data, differences in the transcriptome of the query species can cause problems, such as the following: (i) lower hybridization accuracy of probes due to mismatches or deletions, (ii) probes binding multiple transcripts of different genes, and (iii) probes binding transcripts of non-orthologous genes. So far, methods for (i) exist, but these neglect (ii) and (iii). Here, we propose an approach for comparative transcriptomics addressing problems (i) to (iii), which retains only transcript-specific probes binding transcripts of orthologous genes. We apply this approach to an Arabidopsis lyrata expression data set measured on a microarray designed for Arabidopsis thaliana, and compare it to two alternative approaches, a sequence-based approach and a genomic DNA hybridization-based approach. We investigate the number of retained probe sets, and we validate the resulting expression responses by qRT-PCR. We find that the proposed approach combines the benefit of sequence-based stringency and accuracy while allowing the expression analysis of much more genes than the alternative sequence-based approach. As an added benefit, the proposed approach requires probes to detect transcripts of orthologous genes only, which provides a superior base for biological interpretation of the measured expression responses. PMID:24260119

Reuse of imputed data in microarray analysis increases imputation efficiency

PubMed Central

Kim, Ki-Yeol; Kim, Byoung-Jin; Yi, Gwan-Su

2004-01-01

Background The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked. Results We developed a new cluster-based imputation method called sequential K-nearest neighbor (SKNN) method. This imputes the missing values sequentially from the gene having least missing values, and uses the imputed values for the later imputation. Although it uses the imputed values, the efficiency of this new method is greatly improved in its accuracy and computational complexity over the conventional KNN-based method and other methods based on maximum likelihood estimation. The performance of SKNN was in particular higher than other imputation methods for the data with high missing rates and large number of experiments. Application of Expectation Maximization (EM) to the SKNN method improved the accuracy, but increased computational time proportional to the number of iterations. The Multiple Imputation (MI) method, which is well known but not applied previously to microarray data, showed a similarly high accuracy as the SKNN method, with slightly higher dependency on the types of data sets. Conclusions Sequential reuse of imputed data in KNN-based imputation greatly increases the efficiency of imputation. The SKNN method should be practically useful to save the data of some microarray experiments which have high amounts of missing entries. The SKNN method generates reliable imputed values which can be used for further cluster-based analysis of microarray data. PMID:15504240

TOPSAT: Global space topographic mission

NASA Technical Reports Server (NTRS)

Vetrella, Sergio

1993-01-01

Viewgraphs on TOPSAT Global Space Topographic Mission are presented. Topics covered include: polar region applications; terrestrial ecosystem applications; stereo electro-optical sensors; space-based stereoscopic missions; optical stereo approach; radar interferometry; along track interferometry; TOPSAT-VISTA system approach; ISARA system approach; topographic mapping laser altimeter; and role of multi-beam laser altimeter.

Microarray Meta-Analysis of RNA-Binding Protein Functions in Alternative Polyadenylation

PubMed Central

Hu, Wenchao; Liu, Yuting; Yan, Jun

2014-01-01

Alternative polyadenylation (APA) is a post-transcriptional mechanism to generate diverse mRNA transcripts with different 3′UTRs from the same gene. In this study, we systematically searched for the APA events with differential expression in public mouse microarray data. Hundreds of genes with over-represented differential APA events and the corresponding experiments were identified. We further revealed that global APA differential expression occurred prevalently in tissues such as brain comparing to peripheral tissues, and biological processes such as development, differentiation and immune responses. Interestingly, we also observed widespread differential APA events in RNA-binding protein (RBP) genes such as Rbm3, Eif4e2 and Elavl1. Given the fact that RBPs are considered as the main regulators of differential APA expression, we constructed a co-expression network between APAs and RBPs using the microarray data. Further incorporation of CLIP-seq data of selected RBPs showed that Nova2 represses and Mbnl1 promotes the polyadenylation of closest poly(A) sites respectively. Altogether, our study is the first microarray meta-analysis in a mammal on the regulation of APA by RBPs that integrated massive mRNA expression data under a wide-range of biological conditions. Finally, we present our results as a comprehensive resource in an online website for the research community. PMID:24622240

Hematopoietic Lineage Transcriptome Stability and Representation in PAXgene™ Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray

PubMed Central

Kennedy, Laura; Vass, J. Keith; Haggart, D. Ross; Moore, Steve; Burczynski, Michael E.; Crowther, Dan; Miele, Gino

2008-01-01

Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgene™ RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2™ enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgene™ blood samples also advocate a short, fixed room temperature storage time for all PAXgene™ blood samples collected for the purposes of global transcriptional profiling in clinical studies. PMID:19578521

A microarray analysis of potential genes underlying the neurosensitivity of mice to propofol.

PubMed

Lowes, Damon A; Galley, Helen F; Lowe, Peter R; Rikke, Brad A; Johnson, Thomas E; Webster, Nigel R

2005-09-01

Establishing the mechanism of action of general anesthetics at the molecular level is difficult because of the multiple targets with which these drugs are associated. Inbred short sleep (ISS) and long sleep (ILS) mice are differentially sensitive in response to ethanol and other sedative hypnotics and contain a single quantitative trait locus (Lorp1) that accounts for the genetic variance of loss-of-righting reflex in response to propofol (LORP). In this study, we used high-density oligonucleotide microarrays to identify global gene expression and candidate genes differentially expressed within the Lorp1 region that may give insight into the molecular mechanism underlying LORP. Microarray analysis was performed using Affymetrix MG-U74Av2 Genechips and a selection of differentially expressed genes was confirmed by semiquantitative reverse transcription-polymerase chain reaction. Global expression in the brains of ILS and ISS mice revealed 3423 genes that were significantly expressed, of which 139 (4%) were differentially expressed. Analysis of genes located within the Lorp1 region showed that 26 genes were significantly expressed and that just 2 genes (7%) were differentially expressed. These genes encoded for the proteins AWP1 (associated with protein kinase 1) and "BTB (POZ) domain containing 1," whose functions are largely uncharacterized. Genes differentially expressed outside Lorp1 included seven genes with previously characterized neuronal functions and thus stand out as additional candidate genes that may be involved in mediating the neurosensitivity differences between ISS and ILS.

A potential global soils data base

NASA Technical Reports Server (NTRS)

Stoner, E. R.; Joyce, A. T.; Hogg, H. C.

1984-01-01

A general procedure is outlined for refining the existing world soil maps from the existing 1:1 million scale to 1:250,000 through the interpretation of Landsat MSS and TM images, and the use of a Geographic Information System to relate the soils maps to available information on climate, topography, geology, and vegetation.

ValWorkBench: an open source Java library for cluster validation, with applications to microarray data analysis.

PubMed

Giancarlo, R; Scaturro, D; Utro, F

2015-02-01

The prediction of the number of clusters in a dataset, in particular microarrays, is a fundamental task in biological data analysis, usually performed via validation measures. Unfortunately, it has received very little attention and in fact there is a growing need for software tools/libraries dedicated to it. Here we present ValWorkBench, a software library consisting of eleven well known validation measures, together with novel heuristic approximations for some of them. The main objective of this paper is to provide the interested researcher with the full software documentation of an open source cluster validation platform having the main features of being easily extendible in a homogeneous way and of offering software components that can be readily re-used. Consequently, the focus of the presentation is on the architecture of the library, since it provides an essential map that can be used to access the full software documentation, which is available at the supplementary material website [1]. The mentioned main features of ValWorkBench are also discussed and exemplified, with emphasis on software abstraction design and re-usability. A comparison with existing cluster validation software libraries, mainly in terms of the mentioned features, is also offered. It suggests that ValWorkBench is a much needed contribution to the microarray software development/algorithm engineering community. For completeness, it is important to mention that previous accurate algorithmic experimental analysis of the relative merits of each of the implemented measures [19,23,25], carried out specifically on microarray data, gives useful insights on the effectiveness of ValWorkBench for cluster validation to researchers in the microarray community interested in its use for the mentioned task. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

cDNA Microarray Screening in Food Safety

PubMed Central

ROY, SASHWATI; SEN, CHANDAN K

2009-01-01

The cDNA microarray technology and related bioinformatics tools presents a wide range of novel application opportunities. The technology may be productively applied to address food safety. In this mini-review article, we present an update highlighting the late breaking discoveries that demonstrate the vitality of cDNA microarray technology as a tool to analyze food safety with reference to microbial pathogens and genetically modified foods. In order to bring the microarray technology to mainstream food safety, it is important to develop robust user-friendly tools that may be applied in a field setting. In addition, there needs to be a standardized process for regulatory agencies to interpret and act upon microarray-based data. The cDNA microarray approach is an emergent technology in diagnostics. Its values lie in being able to provide complimentary molecular insight when employed in addition to traditional tests for food safety, as part of a more comprehensive battery of tests. PMID:16466843

ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.

PubMed

Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B

2016-01-01

Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. © 2016 Elsevier Inc. All rights reserved.

Integrated Microfluidic Devices for Automated Microarray-Based Gene Expression and Genotyping Analysis

NASA Astrophysics Data System (ADS)

Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew

Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed that the device identified influenza A hemagglutinin and neuraminidase subtypes and sequenced portions of both genes, demonstrating the potential of integrated microfluidic and microarray technology for multiple virus detection. The device provides a cost-effective solution to eliminate labor-intensive and time-consuming fluidic handling steps and allows microarray-based DNA analysis in a rapid and automated fashion.

DNA Microarray Wet Lab Simulation Brings Genomics into the High School Curriculum

ERIC Educational Resources Information Center

Campbell, A. Malcolm; Zanta, Carolyn A.; Heyer, Laurie J.; Kittinger, Ben; Gabric, Kathleen M.; Adler, Leslie

2006-01-01

We have developed a wet lab DNA microarray simulation as part of a complete DNA microarray module for high school students. The wet lab simulation has been field tested with high school students in Illinois and Maryland as well as in workshops with high school teachers from across the nation. Instead of using DNA, our simulation is based on pH…

VMF3/GPT3: refined discrete and empirical troposphere mapping functions

NASA Astrophysics Data System (ADS)

Landskron, Daniel; Böhm, Johannes

2018-04-01

Incorrect modeling of troposphere delays is one of the major error sources for space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). Over the years, many approaches have been devised which aim at mapping the delay of radio waves from zenith direction down to the observed elevation angle, so-called mapping functions. This paper contains a new approach intended to refine the currently most important discrete mapping function, the Vienna Mapping Functions 1 (VMF1), which is successively referred to as Vienna Mapping Functions 3 (VMF3). It is designed in such a way as to eliminate shortcomings in the empirical coefficients b and c and in the tuning for the specific elevation angle of 3°. Ray-traced delays of the ray-tracer RADIATE serve as the basis for the calculation of new mapping function coefficients. Comparisons of modeled slant delays demonstrate the ability of VMF3 to approximate the underlying ray-traced delays more accurately than VMF1 does, in particular at low elevation angles. In other words, when requiring highest precision, VMF3 is to be preferable to VMF1. Aside from revising the discrete form of mapping functions, we also present a new empirical model named Global Pressure and Temperature 3 (GPT3) on a 5°× 5° as well as a 1°× 1° global grid, which is generally based on the same data. Its main components are hydrostatic and wet empirical mapping function coefficients derived from special averaging techniques of the respective (discrete) VMF3 data. In addition, GPT3 also contains a set of meteorological quantities which are adopted as they stand from their predecessor, Global Pressure and Temperature 2 wet. Thus, GPT3 represents a very comprehensive troposphere model which can be used for a series of geodetic as well as meteorological and climatological purposes and is fully consistent with VMF3.

Global maps of streamflow characteristics based on observations from several thousand catchments

NASA Astrophysics Data System (ADS)

Beck, Hylke; de Roo, Ad; van Dijk, Albert

2016-04-01

Streamflow (Q) estimation in ungauged catchments is one of the greatest challenges facing hydrologists. Observed Q from three to four thousand small-to-medium sized catchments (10--10 000~km^2) around the globe were used to train neural network ensembles to estimate Q characteristics based on climate and physiographic characteristics of the catchments. In total 17 Q characteristics were selected, including mean annual Q, baseflow index, and a number of flow percentiles. Testing coefficients of determination for the estimation of the Q characteristics ranged from 0.55 for the baseflow recession constant to 0.93 for the Q timing. Overall, climate indices dominated among the predictors. Predictors related to soils and geology were relatively unimportant, perhaps due to their data quality. The trained neural network ensembles were subsequently applied spatially over the entire ice-free land surface, resulting in global maps of the Q characteristics (0.125° resolution). These maps possess several unique features: they represent observation-driven estimates; are based on an unprecedentedly large set of catchments; and have associated uncertainty estimates. The maps can be used for various hydrological applications, including the diagnosis of macro-scale hydrological models. To demonstrate this, the produced maps were compared to equivalent maps derived from the simulated daily Q of four macro-scale hydrological models, highlighting various opportunities for improvement in model Q behavior. The produced dataset is available via http://water.jrc.ec.europa.eu.

H1N1 viral proteome peptide microarray predicts individuals at risk for H1N1 infection and segregates infection versus Pandemrix® vaccination

PubMed Central

Ambati, Aditya; Valentini, Davide; Montomoli, Emanuele; Lapini, Guilia; Biuso, Fabrizio; Wenschuh, Holger; Magalhaes, Isabelle; Maeurer, Markus

2015-01-01

A high content peptide microarray containing the entire influenza A virus [A/California/08/2009(H1N1)] proteome and haemagglutinin proteins from 12 other influenza A subtypes, including the haemagglutinin from the [A/South Carolina/1/1918(H1N1)] strain, was used to gauge serum IgG epitope signatures before and after Pandemrix® vaccination or H1N1 infection in a Swedish cohort during the pandemic influenza season 2009. A very narrow pattern of pandemic flu-specific IgG epitope recognition was observed in the serum from individuals who later contracted H1N1 infection. Moreover, the pandemic influenza infection generated IgG reactivity to two adjacent epitopes of the neuraminidase protein. The differential serum IgG recognition was focused on haemagglutinin 1 (H1) and restricted to classical antigenic sites (Cb) in both the vaccinated controls and individuals with flu infections. We further identified a novel epitope VEPGDKITFEATGNL on the Ca antigenic site (251–265) of the pandemic flu haemagglutinin, which was exclusively recognized in serum from individuals with previous vaccinations and never in serum from individuals with H1N1 infection (confirmed by RNA PCR analysis from nasal swabs). This epitope was mapped to the receptor-binding domain of the influenza haemagglutinin and could serve as a correlate of immune protection in the context of pandemic flu. The study shows that unbiased epitope mapping using peptide microarray technology leads to the identification of biologically and clinically relevant target structures. Most significantly an H1N1 infection induced a different footprint of IgG epitope recognition patterns compared with the pandemic H1N1 vaccine. PMID:25639813

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

Kaplow, Irene M.; MacIsaac, Julia L.; Mah, Sarah M.

DNA methylation is an epigenetic modification that plays a key role in gene regulation. Previous studies have investigated its genetic basis by mapping genetic variants that are associated with DNA methylation at specific sites, but these have been limited to microarrays that cover <2% of the genome and cannot account for allele-specific methylation (ASM). Other studies have performed whole-genome bisulfite sequencing on a few individuals, but these lack statistical power to identify variants associated with DNA methylation. We present a novel approach in which bisulfite-treated DNA from many individuals is sequenced together in a single pool, resulting in a trulymore » genome-wide map of DNA methylation. Compared to methods that do not account for ASM, our approach increases statistical power to detect associations while sharply reducing cost, effort, and experimental variability. As a proof of concept, we generated deep sequencing data from a pool of 60 human cell lines; we evaluated almost twice as many CpGs as the largest microarray studies and identified more than 2000 genetic variants associated with DNA methylation. Here we found that these variants are highly enriched for associations with chromatin accessibility and CTCF binding but are less likely to be associated with traits indirectly linked to DNA, such as gene expression and disease phenotypes. In summary, our approach allows genome-wide mapping of genetic variants associated with DNA methylation in any tissue of any species, without the need for individual-level genotype or methylation data.« less

Comparative genomics in chicken and Pekin duck using FISH mapping and microarray analysis

PubMed Central

2009-01-01

Background The availability of the complete chicken (Gallus gallus) genome sequence as well as a large number of chicken probes for fluorescent in-situ hybridization (FISH) and microarray resources facilitate comparative genomic studies between chicken and other bird species. In a previous study, we provided a comprehensive cytogenetic map for the turkey (Meleagris gallopavo) and the first analysis of copy number variants (CNVs) in birds. Here, we extend this approach to the Pekin duck (Anas platyrhynchos), an obvious target for comparative genomic studies due to its agricultural importance and resistance to avian flu. Results We provide a detailed molecular cytogenetic map of the duck genome through FISH assignment of 155 chicken clones. We identified one inter- and six intrachromosomal rearrangements between chicken and duck macrochromosomes and demonstrated conserved synteny among all microchromosomes analysed. Array comparative genomic hybridisation revealed 32 CNVs, of which 5 overlap previously designated "hotspot" regions between chicken and turkey. Conclusion Our results suggest extensive conservation of avian genomes across 90 million years of evolution in both macro- and microchromosomes. The data on CNVs between chicken and duck extends previous analyses in chicken and turkey and supports the hypotheses that avian genomes contain fewer CNVs than mammalian genomes and that genomes of evolutionarily distant species share regions of copy number variation ("CNV hotspots"). Our results will expedite duck genomics, assist marker development and highlight areas of interest for future evolutionary and functional studies. PMID:19656363

CGI: Java Software for Mapping and Visualizing Data from Array-based Comparative Genomic Hybridization and Expression Profiling

PubMed Central

Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H.; Lau, Ching C.; Behl, Sanjiv; Man, Tsz-Kwong

2007-01-01

With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License. PMID:19936083

CGI: Java software for mapping and visualizing data from array-based comparative genomic hybridization and expression profiling.

PubMed

Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H; Lau, Ching C; Behl, Sanjiv; Man, Tsz-Kwong

2007-10-06

With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License.

Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping.

PubMed

Chang, Meiping; Smith, Sarah; Thorpe, Andrew; Barratt, Michael J; Karim, Farzana

2010-09-16

We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potential of compounds based on their own gene expression profiles using the Connectivity Map approach. Using microarrays, we identified differentially expressed genes in L4 and L5 dorsal root ganglia (DRG) from rats that had received intraplantar CFA for 4 days compared to matched, untreated control animals. Analysis of these data indicated that the two groups were distinguishable by differences in genes important in immune responses, nerve growth and regeneration. This list of differentially expressed genes defined a "CFA signature". We used the Connectivity Map approach to identify pharmacologic agents in the Broad Institute Build02 database that had gene expression signatures that were inversely related ('negatively connected') with our CFA signature. To test the predictive nature of the Connectivity Map methodology, we tested phenoxybenzamine (an alpha adrenergic receptor antagonist) - one of the most negatively connected compounds identified in this database - for analgesic activity in the CFA model. Our results indicate that at 10 mg/kg, phenoxybenzamine demonstrated analgesia comparable to that of Naproxen in this model. Evaluation of phenoxybenzamine-induced analgesia in the current study lends support to the utility of the Connectivity Map approach for identifying compounds with analgesic properties in the CFA model.

Advances in cell-free protein array methods.

PubMed

Yu, Xiaobo; Petritis, Brianne; Duan, Hu; Xu, Danke; LaBaer, Joshua

2018-01-01

Cell-free protein microarrays represent a special form of protein microarray which display proteins made fresh at the time of the experiment, avoiding storage and denaturation. They have been used increasingly in basic and translational research over the past decade to study protein-protein interactions, the pathogen-host relationship, post-translational modifications, and antibody biomarkers of different human diseases. Their role in the first blood-based diagnostic test for early stage breast cancer highlights their value in managing human health. Cell-free protein microarrays will continue to evolve to become widespread tools for research and clinical management. Areas covered: We review the advantages and disadvantages of different cell-free protein arrays, with an emphasis on the methods that have been studied in the last five years. We also discuss the applications of each microarray method. Expert commentary: Given the growing roles and impact of cell-free protein microarrays in research and medicine, we discuss: 1) the current technical and practical limitations of cell-free protein microarrays; 2) the biomarker discovery and verification pipeline using protein microarrays; and 3) how cell-free protein microarrays will advance over the next five years, both in their technology and applications.

Enhancing Results of Microarray Hybridizations Through Microagitation

PubMed Central

Toegl, Andreas; Kirchner, Roland; Gauer, Christoph; Wixforth, Achim

2003-01-01

Protein and DNA microarrays have become a standard tool in proteomics/genomics research. In order to guarantee fast and reproducible hybridization results, the diffusion limit must be overcome. Surface acoustic wave (SAW) micro-agitation chips efficiently agitate the smallest sample volumes (down to 10 μL and below) without introducing any dead volume. The advantages are reduced reaction time, increased signal-to-noise ratio, improved homogeneity across the microarray, and better slide-to-slide reproducibility. The SAW micromixer chips are the heart of the Advalytix ArrayBooster, which is compatible with all microarrays based on the microscope slide format. PMID:13678150

Profiling protein function with small molecule microarrays

PubMed Central

Winssinger, Nicolas; Ficarro, Scott; Schultz, Peter G.; Harris, Jennifer L.

2002-01-01

The regulation of protein function through posttranslational modification, local environment, and protein–protein interaction is critical to cellular function. The ability to analyze on a genome-wide scale protein functional activity rather than changes in protein abundance or structure would provide important new insights into complex biological processes. Herein, we report the application of a spatially addressable small molecule microarray to an activity-based profile of proteases in crude cell lysates. The potential of this small molecule-based profiling technology is demonstrated by the detection of caspase activation upon induction of apoptosis, characterization of the activated caspase, and inhibition of the caspase-executed apoptotic phenotype using the small molecule inhibitor identified in the microarray-based profile. PMID:12167675

Comparison of next generation sequencing technologies for transcriptome characterization

PubMed Central

2009-01-01

Background We have developed a simulation approach to help determine the optimal mixture of sequencing methods for most complete and cost effective transcriptome sequencing. We compared simulation results for traditional capillary sequencing with "Next Generation" (NG) ultra high-throughput technologies. The simulation model was parameterized using mappings of 130,000 cDNA sequence reads to the Arabidopsis genome (NCBI Accession SRA008180.19). We also generated 454-GS20 sequences and de novo assemblies for the basal eudicot California poppy (Eschscholzia californica) and the magnoliid avocado (Persea americana) using a variety of methods for cDNA synthesis. Results The Arabidopsis reads tagged more than 15,000 genes, including new splice variants and extended UTR regions. Of the total 134,791 reads (13.8 MB), 119,518 (88.7%) mapped exactly to known exons, while 1,117 (0.8%) mapped to introns, 11,524 (8.6%) spanned annotated intron/exon boundaries, and 3,066 (2.3%) extended beyond the end of annotated UTRs. Sequence-based inference of relative gene expression levels correlated significantly with microarray data. As expected, NG sequencing of normalized libraries tagged more genes than non-normalized libraries, although non-normalized libraries yielded more full-length cDNA sequences. The Arabidopsis data were used to simulate additional rounds of NG and traditional EST sequencing, and various combinations of each. Our simulations suggest a combination of FLX and Solexa sequencing for optimal transcriptome coverage at modest cost. We have also developed ESTcalc http://fgp.huck.psu.edu/NG_Sims/ngsim.pl, an online webtool, which allows users to explore the results of this study by specifying individualized costs and sequencing characteristics. Conclusion NG sequencing technologies are a highly flexible set of platforms that can be scaled to suit different project goals. In terms of sequence coverage alone, the NG sequencing is a dramatic advance over capillary-based sequencing, but NG sequencing also presents significant challenges in assembly and sequence accuracy due to short read lengths, method-specific sequencing errors, and the absence of physical clones. These problems may be overcome by hybrid sequencing strategies using a mixture of sequencing methodologies, by new assemblers, and by sequencing more deeply. Sequencing and microarray outcomes from multiple experiments suggest that our simulator will be useful for guiding NG transcriptome sequencing projects in a wide range of organisms. PMID:19646272

RDFBuilder: a tool to automatically build RDF-based interfaces for MAGE-OM microarray data sources.

PubMed

Anguita, Alberto; Martin, Luis; Garcia-Remesal, Miguel; Maojo, Victor

2013-07-01

This paper presents RDFBuilder, a tool that enables RDF-based access to MAGE-ML-compliant microarray databases. We have developed a system that automatically transforms the MAGE-OM model and microarray data stored in the ArrayExpress database into RDF format. Additionally, the system automatically enables a SPARQL endpoint. This allows users to execute SPARQL queries for retrieving microarray data, either from specific experiments or from more than one experiment at a time. Our system optimizes response times by caching and reusing information from previous queries. In this paper, we describe our methods for achieving this transformation. We show that our approach is complementary to other existing initiatives, such as Bio2RDF, for accessing and retrieving data from the ArrayExpress database. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Autoregressive-model-based missing value estimation for DNA microarray time series data.

PubMed

Choong, Miew Keen; Charbit, Maurice; Yan, Hong

2009-01-01

Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.

Emotional state and local versus global spatial memory.

PubMed

Brunyé, Tad T; Mahoney, Caroline R; Augustyn, Jason S; Taylor, Holly A

2009-02-01

The present work investigated the effects of participant emotional state on global versus local memory for map-based information. Participants were placed into one of four emotion induction groups, crossing high and low arousal with positive and negative valence, or a control group. They then studied a university campus map and completed two memory tests, free recall and spatial statement verification. Converging evidence from these two tasks demonstrated that arousal amplifies symbolic distance effects and leads to a globally-focused spatial mental representation, partially at the expense of local knowledge. These results were found for both positively- and negatively-valenced affective states. The present study is the first investigation of emotional effects on spatial memory, and has implications for theories of emotion and spatial cognition.

Bistatic LIDAR experiment proposed for the shuttle/tethered satellite system missions

NASA Technical Reports Server (NTRS)

Mccomas, D. J.; Spense, H. E.; Karl, R. R.; Horak, H. G.; Wilkerson, T. D.

1986-01-01

A new experiment concept has been proposed for the shuttle/tethered satellite system missions, which can provide high resolution, global density mappings of certain ionospheric species. The technique utilizes bistatic LIDAR to take advantage of the unique dual platform configuration offered by these missions. A tuned, shuttle-based laser is used to excite a column of the atmosphere adjacent to the tethered satellite, while triangulating photometic detectors on the satellite are employed to measure the fluorescence from sections of the column. The fluorescent intensity at the detectors is increased about six decades over both ground-based and monostatic shuttle-based LIDAR sounding of the same region. In addition, the orbital motion of the Shuttle provides for quasi-global mapping unattainable with ground-based observations. Since this technique provides such vastly improved resolution on a synoptic scale, many important middle atmospheric studies, heretofore untenable, may soon be addressed.

Analysis of developmental gene conservation in the Actinomycetales using DNA/DNA microarray comparisons.

PubMed

Kirby, Ralph; Herron, Paul; Hoskisson, Paul

2011-02-01

Based on available genome sequences, Actinomycetales show significant gene synteny across a wide range of species and genera. In addition, many genera show varying degrees of complex morphological development. Using the presence of gene synteny as a basis, it is clear that an analysis of gene conservation across the Streptomyces and various other Actinomycetales will provide information on both the importance of genes and gene clusters and the evolution of morphogenesis in these bacteria. Genome sequencing, although becoming cheaper, is still relatively expensive for comparing large numbers of strains. Thus, a heterologous DNA/DNA microarray hybridization dataset based on a Streptomyces coelicolor microarray allows a cheaper and greater depth of analysis of gene conservation. This study, using both bioinformatical and microarray approaches, was able to classify genes previously identified as involved in morphogenesis in Streptomyces into various subgroups in terms of conservation across species and genera. This will allow the targeting of genes for further study based on their importance at the species level and at higher evolutionary levels.

Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

PubMed Central

Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.

2002-01-01

The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 × g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies. PMID:12370447

Ewing's Sarcoma: An Analysis of miRNA Expression Profiles and Target Genes in Paraffin-Embedded Primary Tumor Tissue.

PubMed

Parafioriti, Antonina; Bason, Caterina; Armiraglio, Elisabetta; Calciano, Lucia; Daolio, Primo Andrea; Berardocco, Martina; Di Bernardo, Andrea; Colosimo, Alessia; Luksch, Roberto; Berardi, Anna C

2016-04-30

The molecular mechanism responsible for Ewing's Sarcoma (ES) remains largely unknown. MicroRNAs (miRNAs), a class of small non-coding RNAs able to regulate gene expression, are deregulated in tumors and may serve as a tool for diagnosis and prediction. However, the status of miRNAs in ES has not yet been thoroughly investigated. This study compared global miRNAs expression in paraffin-embedded tumor tissue samples from 20 ES patients, affected by primary untreated tumors, with miRNAs expressed in normal human mesenchymal stromal cells (MSCs) by microarray analysis. A miRTarBase database was used to identify the predicted target genes for differentially expressed miRNAs. The miRNAs microarray analysis revealed distinct patterns of miRNAs expression between ES samples and normal MSCs. 58 of the 954 analyzed miRNAs were significantly differentially expressed in ES samples compared to MSCs. Moreover, the qRT-PCR analysis carried out on three selected miRNAs showed that miR-181b, miR-1915 and miR-1275 were significantly aberrantly regulated, confirming the microarray results. Bio-database analysis identified BCL-2 as a bona fide target gene of the miR-21, miR-181a, miR-181b, miR-29a, miR-29b, miR-497, miR-195, miR-let-7a, miR-34a and miR-1915. Using paraffin-embedded tissues from ES patients, this study has identified several potential target miRNAs and one gene that might be considered a novel critical biomarker for ES pathogenesis.

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Sand, Olivier; Janky, Rekin's; Vanderstocken, Gilles; Deville, Yves; van Helden, Jacques

2008-07-01

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources.

Position Estimation and Local Mapping Using Omnidirectional Images and Global Appearance Descriptors

PubMed Central

Berenguer, Yerai; Payá, Luis; Ballesta, Mónica; Reinoso, Oscar

2015-01-01

This work presents some methods to create local maps and to estimate the position of a mobile robot, using the global appearance of omnidirectional images. We use a robot that carries an omnidirectional vision system on it. Every omnidirectional image acquired by the robot is described only with one global appearance descriptor, based on the Radon transform. In the work presented in this paper, two different possibilities have been considered. In the first one, we assume the existence of a map previously built composed of omnidirectional images that have been captured from previously-known positions. The purpose in this case consists of estimating the nearest position of the map to the current position of the robot, making use of the visual information acquired by the robot from its current (unknown) position. In the second one, we assume that we have a model of the environment composed of omnidirectional images, but with no information about the location of where the images were acquired. The purpose in this case consists of building a local map and estimating the position of the robot within this map. Both methods are tested with different databases (including virtual and real images) taking into consideration the changes of the position of different objects in the environment, different lighting conditions and occlusions. The results show the effectiveness and the robustness of both methods. PMID:26501289

APPLICATION OF CDNA MICROARRAY TECHNOLOGY TO IN VITRO TOXICOLOGY AND THE SELECTION OF GENES FOR A REAL TIME RT-PCR-BASED SCREEN FOR OXIDATIVE STRESS IN HEP-G2 CELLS

EPA Science Inventory

Large-scale analysis of gene expression using cDNA microarrays promises the
rapid detection of the mode of toxicity for drugs and other chemicals. cDNA
microarrays were used to examine chemically-induced alterations of gene
expression in HepG2 cells exposed to oxidative ...

Nanotechnology: moving from microarrays toward nanoarrays.

PubMed

Chen, Hua; Li, Jun

2007-01-01

Microarrays are important tools for high-throughput analysis of biomolecules. The use of microarrays for parallel screening of nucleic acid and protein profiles has become an industry standard. A few limitations of microarrays are the requirement for relatively large sample volumes and elongated incubation time, as well as the limit of detection. In addition, traditional microarrays make use of bulky instrumentation for the detection, and sample amplification and labeling are quite laborious, which increase analysis cost and delays the time for obtaining results. These problems limit microarray techniques from point-of-care and field applications. One strategy for overcoming these problems is to develop nanoarrays, particularly electronics-based nanoarrays. With further miniaturization, higher sensitivity, and simplified sample preparation, nanoarrays could potentially be employed for biomolecular analysis in personal healthcare and monitoring of trace pathogens. In this chapter, it is intended to introduce the concept and advantage of nanotechnology and then describe current methods and protocols for novel nanoarrays in three aspects: (1) label-free nucleic acids analysis using nanoarrays, (2) nanoarrays for protein detection by conventional optical fluorescence microscopy as well as by novel label-free methods such as atomic force microscopy, and (3) nanoarray for enzymatic-based assay. These nanoarrays will have significant applications in drug discovery, medical diagnosis, genetic testing, environmental monitoring, and food safety inspection.

Self-directed student research through analysis of microarray datasets: a computer-based functional genomics practical class for masters-level students.

PubMed

Grenville-Briggs, Laura J; Stansfield, Ian

2011-01-01

This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate active learning through experience of current research methods in bioinformatics and functional genomics. They seek to closely mimic a realistic research environment, and require the students first to propose research hypotheses, then test those hypotheses using specific sections of the microarray dataset. The complexity of the microarray data provides students with the freedom to propose their own unique hypotheses, tested using appropriate sections of the microarray data. This research latitude was highly regarded by students and is a strength of this practical. In addition, the focus on DNA damage by radiation and mutagenic chemicals allows them to place their results in a human medical context, and successfully sparks broad interest in the subject material. In evaluation, 79% of students scored the practical workshops on a five-point scale as 4 or 5 (totally effective) for student learning. More broadly, the general use of microarray data as a "student research playground" is also discussed. Copyright © 2011 Wiley Periodicals, Inc.

Microarray platform affords improved product analysis in mammalian cell growth studies

PubMed Central

Li, Lingyun; Migliore, Nicole; Schaefer, Eugene; Sharfstein, Susan T.; Dordick, Jonathan S.; Linhardt, Robert J.

2014-01-01

High throughput (HT) platforms serve as cost-efficient and rapid screening method for evaluating the effect of cell culture conditions and screening of chemicals. The aim of the current study was to develop a high-throughput cell-based microarray platform to assess the effect of culture conditions on Chinese hamster ovary (CHO) cells. Specifically, growth, transgene expression and metabolism of a GS/MSX CHO cell line, which produces a therapeutic monoclonal antibody, was examined using microarray system in conjunction with conventional shake flask platform in a non-proprietary medium. The microarray system consists of 60 nl spots of cells encapsulated in alginate and separated in groups via an 8-well chamber system attached to the chip. Results show the non-proprietary medium developed allows cell growth, production and normal glycosylation of recombinant antibody and metabolism of the recombinant CHO cells in both the microarray and shake flask platforms. In addition, 10.3 mM glutamate addition to the defined base media results in lactate metabolism shift in the recombinant GS/MSX CHO cells in the shake flask platform. Ultimately, the results demonstrate that the high-throughput microarray platform has the potential to be utilized for evaluating the impact of media additives on cellular processes, such as, cell growth, metabolism and productivity. PMID:24227746

High-Resolution Global Geologic Map of Ceres from NASA Dawn Mission

NASA Astrophysics Data System (ADS)

Williams, D. A.; Buczkowski, D. L.; Crown, D. A.; Frigeri, A.; Hughson, K.; Kneissl, T.; Krohn, K.; Mest, S. C.; Pasckert, J. H.; Platz, T.; Ruesch, O.; Schulzeck, F.; Scully, J. E. C.; Sizemore, H. G.; Nass, A.; Jaumann, R.; Raymond, C. A.; Russell, C. T.

2018-06-01

This presentation will discuss the completed 1:4,000,000 global geologic map of dwarf planet Ceres derived from Dawn Framing Camera Low Altitude Mapping Orbit (LAMo) images, combining 15 quadrangle maps.

Data-based estimates of the ocean carbon sink variability - first results of the Surface Ocean pCO2 Mapping intercomparison (SOCOM)

NASA Astrophysics Data System (ADS)

Rödenbeck, C.; Bakker, D. C. E.; Gruber, N.; Iida, Y.; Jacobson, A. R.; Jones, S.; Landschützer, P.; Metzl, N.; Nakaoka, S.; Olsen, A.; Park, G.-H.; Peylin, P.; Rodgers, K. B.; Sasse, T. P.; Schuster, U.; Shutler, J. D.; Valsala, V.; Wanninkhof, R.; Zeng, J.

2015-08-01

Using measurements of the surface-ocean CO2 partial pressure (pCO2) and 14 different pCO2 mapping methods recently collated by the Surface Ocean pCO2 Mapping intercomparison (SOCOM) initiative, variations in regional and global sea-air CO2 fluxes have been investigated. Though the available mapping methods use widely different approaches, we find relatively consistent estimates of regional pCO2 seasonality, in line with previous estimates. In terms of interannual variability (IAV), all mapping methods estimate the largest variations to occur in the Eastern equatorial Pacific. Despite considerable spead in the detailed variations, mapping methods with closer match to the data also tend to be more consistent with each other. Encouragingly, this includes mapping methods belonging to complementary types - taking variability either directly from the pCO2 data or indirectly from driver data via regression. From a weighted ensemble average, we find an IAV amplitude of the global sea-air CO2 flux of 0.31 PgC yr-1 (standard deviation over 1992-2009), which is larger than simulated by biogeochemical process models. On a decadal perspective, the global CO2 uptake is estimated to have gradually increased since about 2000, with little decadal change prior to 2000. The weighted mean total ocean CO2 sink estimated by the SOCOM ensemble is consistent within uncertainties with estimates from ocean-interior carbon data or atmospheric oxygen trends.

Broad spectrum microarray for fingerprint-based bacterial species identification

PubMed Central

2010-01-01

Background Microarrays are powerful tools for DNA-based molecular diagnostics and identification of pathogens. Most target a limited range of organisms and are based on only one or a very few genes for specific identification. Such microarrays are limited to organisms for which specific probes are available, and often have difficulty discriminating closely related taxa. We have developed an alternative broad-spectrum microarray that employs hybridisation fingerprints generated by high-density anonymous markers distributed over the entire genome for identification based on comparison to a reference database. Results A high-density microarray carrying 95,000 unique 13-mer probes was designed. Optimized methods were developed to deliver reproducible hybridisation patterns that enabled confident discrimination of bacteria at the species, subspecies, and strain levels. High correlation coefficients were achieved between replicates. A sub-selection of 12,071 probes, determined by ANOVA and class prediction analysis, enabled the discrimination of all samples in our panel. Mismatch probe hybridisation was observed but was found to have no effect on the discriminatory capacity of our system. Conclusions These results indicate the potential of our genome chip for reliable identification of a wide range of bacterial taxa at the subspecies level without laborious prior sequencing and probe design. With its high resolution capacity, our proof-of-principle chip demonstrates great potential as a tool for molecular diagnostics of broad taxonomic groups. PMID:20163710

Multiple biomarkers in molecular oncology. II. Molecular diagnostics applications in breast cancer management.

PubMed

Malinowski, Douglas P

2007-05-01

In recent years, the application of genomic and proteomic technologies to the problem of breast cancer prognosis and the prediction of therapy response have begun to yield encouraging results. Independent studies employing transcriptional profiling of primary breast cancer specimens using DNA microarrays have identified gene expression profiles that correlate with clinical outcome in primary breast biopsy specimens. Recent advances in microarray technology have demonstrated reproducibility, making clinical applications more achievable. In this regard, one such DNA microarray device based upon a 70-gene expression signature was recently cleared by the US FDA for application to breast cancer prognosis. These DNA microarrays often employ at least 70 gene targets for transcriptional profiling and prognostic assessment in breast cancer. The use of PCR-based methods utilizing a small subset of genes has recently demonstrated the ability to predict the clinical outcome in early-stage breast cancer. Furthermore, protein-based immunohistochemistry methods have progressed from using gene clusters and gene expression profiling to smaller subsets of expressed proteins to predict prognosis in early-stage breast cancer. Beyond prognostic applications, DNA microarray-based transcriptional profiling has demonstrated the ability to predict response to chemotherapy in early-stage breast cancer patients. In this review, recent advances in the use of multiple markers for prognosis of disease recurrence in early-stage breast cancer and the prediction of therapy response will be discussed.

Compiling and Mapping Global Permeability of the Unconsolidated and Consolidated Earth: GLobal HYdrogeology MaPS 2.0 (GLHYMPS 2.0)

NASA Astrophysics Data System (ADS)

Huscroft, Jordan; Gleeson, Tom; Hartmann, Jens; Börker, Janine

2018-02-01

The spatial distribution of subsurface parameters such as permeability are increasingly relevant for regional to global climate, land surface, and hydrologic models that are integrating groundwater dynamics and interactions. Despite the large fraction of unconsolidated sediments on Earth's surface with a wide range of permeability values, current global, high-resolution permeability maps distinguish solely fine-grained and coarse-grained unconsolidated sediments. Representative permeability values are derived for a wide variety of unconsolidated sediments and applied to a new global map of unconsolidated sediments to produce the first geologically constrained, two-layer global map of shallower and deeper permeability. The new mean logarithmic permeability of the Earth's surface is -12.7 ± 1.7 m2 being 1 order of magnitude higher than that derived from previous maps, which is consistent with the dominance of the coarser sediments. The new data set will benefit a variety of scientific applications including the next generation of climate, land surface, and hydrology models at regional to global scales.

GeneXplorer: an interactive web application for microarray data visualization and analysis.

PubMed

Rees, Christian A; Demeter, Janos; Matese, John C; Botstein, David; Sherlock, Gavin

2004-10-01

When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.

Global Map of Pluto

NASA Image and Video Library

2015-07-27

The science team of NASA's New Horizons mission has produced an updated global map of the dwarf planet Pluto. The map includes all resolved images of the surface acquired between July 7-14, 2015, at pixel resolutions ranging from 40 kilometers (24 miles) on the Charon-facing hemisphere (left and right sides of the map) to 400 meters (1,250 feet) on the anti-Charon facing hemisphere (map center). Many additional images are expected in fall of 2015 and these will be used to complete the global map. http://photojournal.jpl.nasa.gov/catalog/PIA19858

A new world malaria map: Plasmodium falciparum endemicity in 2010.

PubMed

Gething, Peter W; Patil, Anand P; Smith, David L; Guerra, Carlos A; Elyazar, Iqbal R F; Johnston, Geoffrey L; Tatem, Andrew J; Hay, Simon I

2011-12-20

Transmission intensity affects almost all aspects of malaria epidemiology and the impact of malaria on human populations. Maps of transmission intensity are necessary to identify populations at different levels of risk and to evaluate objectively options for disease control. To remain relevant operationally, such maps must be updated frequently. Following the first global effort to map Plasmodium falciparum malaria endemicity in 2007, this paper describes the generation of a new world map for the year 2010. This analysis is extended to provide the first global estimates of two other metrics of transmission intensity for P. falciparum that underpin contemporary questions in malaria control: the entomological inoculation rate (PfEIR) and the basic reproductive number (PfR). Annual parasite incidence data for 13,449 administrative units in 43 endemic countries were sourced to define the spatial limits of P. falciparum transmission in 2010 and 22,212 P. falciparum parasite rate (PfPR) surveys were used in a model-based geostatistical (MBG) prediction to create a continuous contemporary surface of malaria endemicity within these limits. A suite of transmission models were developed that link PfPR to PfEIR and PfR and these were fitted to field data. These models were combined with the PfPR map to create new global predictions of PfEIR and PfR. All output maps included measured uncertainty. An estimated 1.13 and 1.44 billion people worldwide were at risk of unstable and stable P. falciparum malaria, respectively. The majority of the endemic world was predicted with a median PfEIR of less than one and a median PfRc of less than two. Values of either metric exceeding 10 were almost exclusive to Africa. The uncertainty described in both PfEIR and PfR was substantial in regions of intense transmission. The year 2010 has a particular significance as an evaluation milestone for malaria global health policy. The maps presented here contribute to a rational basis for control and elimination decisions and can serve as a baseline assessment as the global health community looks ahead to the next series of milestones targeted at 2015.

PExFInS: An Integrative Post-GWAS Explorer for Functional Indels and SNPs

PubMed Central

Cheng, Zhongshan; Chu, Hin; Fan, Yanhui; Li, Cun; Song, You-Qiang; Zhou, Jie; Yuen, Kwok-Yung

2015-01-01

Expression quantitative trait loci (eQTLs) mapping and linkage disequilibrium (LD) analysis have been widely employed to interpret findings of genome-wide association studies (GWAS). With the availability of deep sequencing data of 423 lymphoblastoid cell lines (LCLs) from six global populations and the microarray expression data, we performed eQTL analysis, identified more than 228 K SNP cis-eQTLs and 21 K indel cis-eQTLs and generated a LCL cis-eQTL database. We demonstrate that the percentages of population-shared and population-specific cis-eQTLs are comparable; while indel cis-eQTLs in the population-specific subsection make more contribution to gene expression variations than those in the population-shared subsection. We found cis-eQTLs, especially the population-shared cis-eQTLs are significantly enriched toward transcription start site. Moreover, the National Human Genome Research Institute cataloged GWAS SNPs are enriched for LCL cis-eQTLs. Specifically, 32.8% GWAS SNPs are LCL cis-eQTLs, among which 12.5% can be tagged by indel cis-eQTLs, suggesting the fundamental contribution of indel cis-eQTLs to GWAS association signals. To search for functional indels and SNPs tagging GWAS SNPs, a pipeline Post-GWAS Explorer for Functional Indels and SNPs (PExFInS) has been developed, integrating LD analysis, functional annotation from public databases, cis-eQTL mapping with our LCL cis-eQTL database and other published cis-eQTL datasets. PMID:26612672

Decadal trends in global pelagic ocean chlorophyll: A new assessment integrating multiple satellites, in situ data, and models.

PubMed

Gregg, Watson W; Rousseaux, Cécile S

2014-09-01

Quantifying change in ocean biology using satellites is a major scientific objective. We document trends globally for the period 1998-2012 by integrating three diverse methodologies: ocean color data from multiple satellites, bias correction methods based on in situ data, and data assimilation to provide a consistent and complete global representation free of sampling biases. The results indicated no significant trend in global pelagic ocean chlorophyll over the 15 year data record. These results were consistent with previous findings that were based on the first 6 years and first 10 years of the SeaWiFS mission. However, all of the Northern Hemisphere basins (north of 10° latitude), as well as the Equatorial Indian basin, exhibited significant declines in chlorophyll. Trend maps showed the local trends and their change in percent per year. These trend maps were compared with several other previous efforts using only a single sensor (SeaWiFS) and more limited time series, showing remarkable consistency. These results suggested the present effort provides a path forward to quantifying global ocean trends using multiple satellite missions, which is essential if we are to understand the state, variability, and possible changes in the global oceans over longer time scales.

Globes from global data: Charting international research networks with the GRASS GIS r.out.polycones add-on module.

NASA Astrophysics Data System (ADS)

Löwe, Peter

2015-04-01

Many Free and Open Source Software (FOSS) tools have been created for the various application fields within geoscience. While FOSS allows re-implementation of functionalities in new environments by access to the original codebase, the easiest approach to build new software solutions for new problems is the combination or merging of existing software tools. Such mash-ups are implemented by embedding and encapsulating FOSS tools within each another, effectively focusing the use of the embedded software to the specific role it needs to perform in the given scenario, while ignoring all its other capabilities. GRASS GIS is a powerful and established FOSS GIS for raster, vector and volume data processing while the Generic Mapping Tools (GMT) are a suite of powerful Open Source mapping tools, which exceed the mapping capabilities of GRASS GIS. This poster reports on the new GRASS GIS add-on module r.out.polycones. It enables users to utilize non-continuous projections for map production within the GRASS production environment. This is implemented on the software level by encapsulating a subset of GMT mapping capabilities into a GRASS GIS (Version 6.x) add-on module. The module was developed at the German National Library of Science and Technology (TIB) to provide custom global maps of scientific collaboration networks, such as the DataCite consortium, the registration agency for Digital Object Identifiers (DOI) for research data. The GRASS GIS add-on module can be used for global mapping of raster data into a variety of non continuous sinosoidal projections, allowing the creation of printable biangles (gores) to be used for globe making. Due to the well structured modular nature of GRASS modules, technical follow-up work will focus on API-level Python-based integration in GRASS 7 [1]. Based on this, GMT based mapping capabilities in GRASS will be extended beyond non-continuous sinosoidal maps and advanced from raster-layers to content GRASS display monitors. References: [1] Petras, V., Petrasova, A., Chemin, Y., Zambelli, P., Landa, M., Gebbert, S., Neteler, N., Löwe, P.: Analyzing rasters, vectors and time series using new Python interfaces in GRASS GIS 7, Geophysical Research Abstracts Vol. 17, EGU2015-8142, 2015 (in preparation)

R Script Approach to Infer Toxoplasma Infection Mechanisms From Microarrays and Domain-Domain Protein Interactions

PubMed Central

Arenas, Ailan F; Salcedo, Gladys E; Gomez-Marin, Jorge E

2017-01-01

Pathogen-host protein-protein interaction systems examine the interactions between the protein repertoires of 2 distinct organisms. Some of these pathogen proteins interact with the host protein system and may manipulate it for their own advantages. In this work, we designed an R script by concatenating 2 functions called rowDM and rowCVmed to infer pathogen-host interaction using previously reported microarray data, including host gene enrichment analysis and the crossing of interspecific domain-domain interactions. We applied this script to the Toxoplasma-host system to describe pathogen survival mechanisms from human, mouse, and Toxoplasma Gene Expression Omnibus series. Our outcomes exhibited similar results with previously reported microarray analyses, but we found other important proteins that could contribute to toxoplasma pathogenesis. We observed that Toxoplasma ROP38 is the most differentially expressed protein among toxoplasma strains. Enrichment analysis and KEGG mapping indicated that the human retinal genes most affected by Toxoplasma infections are those related to antiapoptotic mechanisms. We suggest that proteins PIK3R1, PRKCA, PRKCG, PRKCB, HRAS, and c-JUN could be the possible substrates for differentially expressed Toxoplasma kinase ROP38. Likewise, we propose that Toxoplasma causes overexpression of apoptotic suppression human genes. PMID:29317802

Mutagen Structure and Transcriptional Response: Induction of Distinct Transcriptional Profiles in Salmonella TA100 by the Drinking-Water Mutagen MX and Its Homologues

EPA Science Inventory

The relationship between chemical structure and biological activity has been examined for various compounds and endpoints for decades. To explore this question relative to global gene expression, we performed microarray analysis of Salmonella TA100 after treatment under condition...

Transcriptome profiling and expression analyses of genes critical to wheat adaptation to low temperature

USDA-ARS?s Scientific Manuscript database

Background: To identify the genes involved in the development of low temperature (LT) tolerance in hexaploid wheat, we examined the global changes in expression in response to cold of the 55,052 potentially unique genes represented in the Affymetrix Wheat Genome microarray. We compared the expressi...

Evaluation of Montanide TM ISA 71 VG adjuvant during profilin vaccination against experimental coccidiosis

USDA-ARS?s Scientific Manuscript database

Chickens were immunized subcutaneously with an Eimeria recombinant profilin protein plus MontanideTM ISA 70 VG (ISA 70) or MontanideTM ISA 71 VG (ISA 71) water-in-oil adjuvants, or with profilin alone, and comparative RNA microarray analyses were performed to ascertain global transcriptomic changes ...

Satellite Maps Deliver More Realistic Gaming

NASA Technical Reports Server (NTRS)

2013-01-01

When Redwood City, California-based Electronic Arts (EA) decided to make SSX, its latest snowboarding video game, it faced challenges in creating realistic-looking mountains. The solution was NASA's ASTER Global Digital Elevation Map, made available by the Jet Propulsion Laboratory, which EA used to create 28 real-life mountains from 9 different ranges for its award-winning game.

Identification and validation of differentially expressed transcripts by RNA-sequencing of formalin-fixed, paraffin-embedded (FFPE) lung tissue from patients with Idiopathic Pulmonary Fibrosis.

PubMed

Vukmirovic, Milica; Herazo-Maya, Jose D; Blackmon, John; Skodric-Trifunovic, Vesna; Jovanovic, Dragana; Pavlovic, Sonja; Stojsic, Jelena; Zeljkovic, Vesna; Yan, Xiting; Homer, Robert; Stefanovic, Branko; Kaminski, Naftali

2017-01-12

Idiopathic Pulmonary Fibrosis (IPF) is a lethal lung disease of unknown etiology. A major limitation in transcriptomic profiling of lung tissue in IPF has been a dependence on snap-frozen fresh tissues (FF). In this project we sought to determine whether genome scale transcript profiling using RNA Sequencing (RNA-Seq) could be applied to archived Formalin-Fixed Paraffin-Embedded (FFPE) IPF tissues. We isolated total RNA from 7 IPF and 5 control FFPE lung tissues and performed 50 base pair paired-end sequencing on Illumina 2000 HiSeq. TopHat2 was used to map sequencing reads to the human genome. On average ~62 million reads (53.4% of ~116 million reads) were mapped per sample. 4,131 genes were differentially expressed between IPF and controls (1,920 increased and 2,211 decreased (FDR < 0.05). We compared our results to differentially expressed genes calculated from a previously published dataset generated from FF tissues analyzed on Agilent microarrays (GSE47460). The overlap of differentially expressed genes was very high (760 increased and 1,413 decreased, FDR < 0.05). Only 92 differentially expressed genes changed in opposite directions. Pathway enrichment analysis performed using MetaCore confirmed numerous IPF relevant genes and pathways including extracellular remodeling, TGF-beta, and WNT. Gene network analysis of MMP7, a highly differentially expressed gene in both datasets, revealed the same canonical pathways and gene network candidates in RNA-Seq and microarray data. For validation by NanoString nCounter® we selected 35 genes that had a fold change of 2 in at least one dataset (10 discordant, 10 significantly differentially expressed in one dataset only and 15 concordant genes). High concordance of fold change and FDR was observed for each type of the samples (FF vs FFPE) with both microarrays (r = 0.92) and RNA-Seq (r = 0.90) and the number of discordant genes was reduced to four. Our results demonstrate that RNA sequencing of RNA obtained from archived FFPE lung tissues is feasible. The results obtained from FFPE tissue are highly comparable to FF tissues. The ability to perform RNA-Seq on archived FFPE IPF tissues should greatly enhance the availability of tissue biopsies for research in IPF.

Model-based redesign of global transcription regulation

PubMed Central

Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso

2009-01-01

Synthetic biology aims to the design or redesign of biological systems. In particular, one possible goal could be the rewiring of the transcription regulation network by exchanging the endogenous promoters. To achieve this objective, we have adapted current methods to the inference of a model based on ordinary differential equations that is able to predict the network response after a major change in its topology. Our procedure utilizes microarray data for training. We have experimentally validated our inferred global regulatory model in Escherichia coli by predicting transcriptomic profiles under new perturbations. We have also tested our methodology in silico by providing accurate predictions of the underlying networks from expression data generated with artificial genomes. In addition, we have shown the predictive power of our methodology by obtaining the gene profile in experimental redesigns of the E. coli genome, where rewiring the transcriptional network by means of knockouts of master regulators or by upregulating transcription factors controlled by different promoters. Our approach is compatible with most network inference methods, allowing to explore computationally future genome-wide redesign experiments in synthetic biology. PMID:19188257

Global climate change and local land subsidence exacerbate inundation risk to the San Francisco Bay Area

PubMed Central

Shirzaei, Manoochehr; Bürgmann, Roland

2018-01-01

The current global projections of future sea level rise are the basis for developing inundation hazard maps. However, contributions from spatially variable coastal subsidence have generally not been considered in these projections. We use synthetic aperture radar interferometric measurements and global navigation satellite system data to show subsidence rates of less than 2 mm/year along most of the coastal areas along San Francisco Bay. However, rates exceed 10 mm/year in some areas underlain by compacting artificial landfill and Holocene mud deposits. The maps estimating 100-year inundation hazards solely based on the projection of sea level rise from various emission scenarios underestimate the area at risk of flooding by 3.7 to 90.9%, compared with revised maps that account for the contribution of local land subsidence. Given ongoing land subsidence, we project that an area of 125 to 429 km2 will be vulnerable to inundation, as opposed to 51 to 413 km2 considering sea level rise alone. PMID:29536042

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.

PubMed

Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana

2011-01-01

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.

A detailed transcript-level probe annotation reveals alternative splicing based microarray platform differences

PubMed Central

Lee, Joseph C; Stiles, David; Lu, Jun; Cam, Margaret C

2007-01-01

Background Microarrays are a popular tool used in experiments to measure gene expression levels. Improving the reproducibility of microarray results produced by different chips from various manufacturers is important to create comparable and combinable experimental results. Alternative splicing has been cited as a possible cause of differences in expression measurements across platforms, though no study to this point has been conducted to show its influence in cross-platform differences. Results Using probe sequence data, a new microarray probe/transcript annotation was created based on the AceView Aug05 release that allowed for the categorization of genes based on their expression measurements' susceptibility to alternative splicing differences across microarray platforms. Examining gene expression data from multiple platforms in light of the new categorization, genes unsusceptible to alternative splicing differences showed higher signal agreement than those genes most susceptible to alternative splicing differences. The analysis gave rise to a different probe-level visualization method that can highlight probe differences according to transcript specificity. Conclusion The results highlight the need for detailed probe annotation at the transcriptome level. The presence of alternative splicing within a given sample can affect gene expression measurements and is a contributing factor to overall technical differences across platforms. PMID:17708771

Novel calibration tools and validation concepts for microarray-based platforms used in molecular diagnostics and food safety control.

PubMed

Brunner, C; Hoffmann, K; Thiele, T; Schedler, U; Jehle, H; Resch-Genger, U

2015-04-01

Commercial platforms consisting of ready-to-use microarrays printed with target-specific DNA probes, a microarray scanner, and software for data analysis are available for different applications in medical diagnostics and food analysis, detecting, e.g., viral and bacteriological DNA sequences. The transfer of these tools from basic research to routine analysis, their broad acceptance in regulated areas, and their use in medical practice requires suitable calibration tools for regular control of instrument performance in addition to internal assay controls. Here, we present the development of a novel assay-adapted calibration slide for a commercialized DNA-based assay platform, consisting of precisely arranged fluorescent areas of various intensities obtained by incorporating different concentrations of a "green" dye and a "red" dye in a polymer matrix. These dyes present "Cy3" and "Cy5" analogues with improved photostability, chosen based upon their spectroscopic properties closely matching those of common labels for the green and red channel of microarray scanners. This simple tool allows to efficiently and regularly assess and control the performance of the microarray scanner provided with the biochip platform and to compare different scanners. It will be eventually used as fluorescence intensity scale for referencing of assays results and to enhance the overall comparability of diagnostic tests.

Analysis of host response to bacterial infection using error model based gene expression microarray experiments

PubMed Central

Stekel, Dov J.; Sarti, Donatella; Trevino, Victor; Zhang, Lihong; Salmon, Mike; Buckley, Chris D.; Stevens, Mark; Pallen, Mark J.; Penn, Charles; Falciani, Francesco

2005-01-01

A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples. PMID:15800204

Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass gene expression data.

PubMed

Ooi, Chia Huey; Chetty, Madhu; Teng, Shyh Wei

2006-06-23

Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gene expression-based tissue classification while improving accuracy at the same time. Surprisingly, this does not appear to be the case for all multiclass microarray datasets. The reason is that many feature selection techniques applied on microarray datasets are either rank-based and hence do not take into account correlations between genes, or are wrapper-based, which require high computational cost, and often yield difficult-to-reproduce results. In studies where correlations between genes are considered, attempts to establish the merit of the proposed techniques are hampered by evaluation procedures which are less than meticulous, resulting in overly optimistic estimates of accuracy. We present two realistically evaluated correlation-based feature selection techniques which incorporate, in addition to the two existing criteria involved in forming a predictor set (relevance and redundancy), a third criterion called the degree of differential prioritization (DDP). DDP functions as a parameter to strike the balance between relevance and redundancy, providing our techniques with the novel ability to differentially prioritize the optimization of relevance against redundancy (and vice versa). This ability proves useful in producing optimal classification accuracy while using reasonably small predictor set sizes for nine well-known multiclass microarray datasets. For multiclass microarray datasets, especially the GCM and NCI60 datasets, DDP enables our filter-based techniques to produce accuracies better than those reported in previous studies which employed similarly realistic evaluation procedures.

How well do we succeed in modeling the global soil carbon pools?

NASA Astrophysics Data System (ADS)

Viskari, T.; Liski, J.

2017-12-01

Terrestrial carbon pools are a crucial part of the global carbon cycle. Carbon from vegetation is deposited to the soil, which in turn releases carbon dioxide back to the atmosphere through heterotrophic respiration. The resulting soil carbon storage in the largest on land. While there are continuous efforts to improve the modeling of global soil carbon and how this storage is affected by climate change, this research requires still a more reliable baseline on how well the models estimate the current global soil carbon pools. Especially such comparisons are important for identifying the major challenges in the current soil carbon models. Here, we used the Yasso soil carbon model to create a global soil carbon map at a 0.5 degree resolution based on the available climate, land cover and vegetation productivity information. Yasso model describes the soil carbon cycling by pools that represent the breaking down of dead organic matter. We compared the model results to a measurement based projection of global soil carbon pools, and we examined the differences and spatial correlations between the two maps. In our findings, the modelled predictions captured the overall soil carbon distributions within 5 kgCm-2 on 63 % of the land area. The spatial distributions fit each other as well. The average soil carbon is smaller with the Yasso prediction ( 8.5 kg m-2) than with the measurement map ( 10 kg m-2) and there are notable areas, such as Siberia and Southern North America, where there are large differences between the model predictions and measurements. These results not only encourage future development of soil carbon models, but also highlight problem areas to focus and improve upon.

Estimating Global Impervious Surface based on Social-economic Data and Satellite Observations

NASA Astrophysics Data System (ADS)

Zeng, Z.; Zhang, K.; Xue, X.; Hong, Y.

2016-12-01

Impervious surface areas around the globe are expanding and significantly altering the surface energy balance, hydrology cycle and ecosystem services. Many studies have underlined the importance of impervious surface, r from hydrological modeling to contaminant transport monitoring and urban development estimation. Therefore accurate estimation of the global impervious surface is important for both physical and social sciences. Given the limited coverage of high spatial resolution imagery and ground survey, using satellite remote sensing and geospatial data to estimate global impervious areas is a practical approach. Based on the previous work of area-weighted imperviousness for north branch of the Chicago River provided by HDR, this study developed a method to determine the percentage of impervious surface using latest global land cover categories from multi-source satellite observations, population density and gross domestic product (GDP) data. Percent impervious surface at 30-meter resolution were mapped. We found that 1.33% of the CONUS (105,814 km2) and 0.475% of the land surface (640,370km2) are impervious surfaces. To test the utility and practicality of the proposed method, National Land Cover Database (NLCD) 2011 percent developed imperviousness for the conterminous United States was used to evaluate our results. The average difference between the derived imperviousness from our method and the NLCD data across CONUS is 1.14%, while difference between our results and the NLCD data are within ±1% over 81.63% of the CONUS. The distribution of global impervious surface map indicates that impervious surfaces are primarily concentrated in China, India, Japan, USA and Europe where are highly populated and/or developed. This study proposes a straightforward way of mapping global imperviousness, which can provide useful information for hydrologic modeling and other applications.

Optimal consistency in microRNA expression analysis using reference-gene-based normalization.

PubMed

Wang, Xi; Gardiner, Erin J; Cairns, Murray J

2015-05-01

Normalization of high-throughput molecular expression profiles secures differential expression analysis between samples of different phenotypes or biological conditions, and facilitates comparison between experimental batches. While the same general principles apply to microRNA (miRNA) normalization, there is mounting evidence that global shifts in their expression patterns occur in specific circumstances, which pose a challenge for normalizing miRNA expression data. As an alternative to global normalization, which has the propensity to flatten large trends, normalization against constitutively expressed reference genes presents an advantage through their relative independence. Here we investigated the performance of reference-gene-based (RGB) normalization for differential miRNA expression analysis of microarray expression data, and compared the results with other normalization methods, including: quantile, variance stabilization, robust spline, simple scaling, rank invariant, and Loess regression. The comparative analyses were executed using miRNA expression in tissue samples derived from subjects with schizophrenia and non-psychiatric controls. We proposed a consistency criterion for evaluating methods by examining the overlapping of differentially expressed miRNAs detected using different partitions of the whole data. Based on this criterion, we found that RGB normalization generally outperformed global normalization methods. Thus we recommend the application of RGB normalization for miRNA expression data sets, and believe that this will yield a more consistent and useful readout of differentially expressed miRNAs, particularly in biological conditions characterized by large shifts in miRNA expression.

Global Maps of Temporal Streamflow Characteristics Based on Observations from Many Small Catchments

NASA Astrophysics Data System (ADS)

Beck, H.; van Dijk, A.; de Roo, A.

2014-12-01

Streamflow (Q) estimation in ungauged catchments is one of the greatest challenges facing hydrologists. We used observed Q from approximately 7500 small catchments (<10,000 km2) around the globe to train neural network ensembles to estimate temporal Q distribution characteristics from climate and physiographic characteristics of the catchments. In total 17 Q characteristics were selected, including mean annual Q, baseflow index, and a number of flow percentiles. Training coefficients of determination for the estimation of the Q characteristics ranged from 0.56 for the baseflow recession constant to 0.93 for the Q timing. Overall, climate indices dominated among the predictors. Predictors related to soils and geology were the least important, perhaps due to data quality. The trained neural network ensembles were subsequently applied spatially over the ice-free land surface including ungauged regions, resulting in global maps of the Q characteristics (0.125° spatial resolution). These maps possess several unique features: 1) they represent purely observation-driven estimates; 2) are based on an unprecedentedly large set of catchments; and 3) have associated uncertainty estimates. The maps can be used for various hydrological applications, including the diagnosis of macro-scale hydrological models. To demonstrate this, the produced maps were compared to equivalent maps derived from the simulated daily Q of five macro-scale hydrological models, highlighting various opportunities for improvement in model Q behavior. The produced dataset is available for download.