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.

Construction and Validation of the Rhodobacter sphaeroides 2.4.1 DNA Microarray: Transcriptome Flexibility at Diverse Growth Modes

PubMed Central

Pappas, Christopher T.; Sram, Jakub; Moskvin, Oleg V.; Ivanov, Pavel S.; Mackenzie, R. Christopher; Choudhary, Madhusudan; Land, Miriam L.; Larimer, Frank W.; Kaplan, Samuel; Gomelsky, Mark

2004-01-01

A high-density oligonucleotide DNA microarray, a genechip, representing the 4.6-Mb genome of the facultative phototrophic proteobacterium, Rhodobacter sphaeroides 2.4.1, was custom-designed and manufactured by Affymetrix, Santa Clara, Calif. The genechip contains probe sets for 4,292 open reading frames (ORFs), 47 rRNA and tRNA genes, and 394 intergenic regions. The probe set sequences were derived from the genome annotation generated by Oak Ridge National Laboratory after extensive revision, which was based primarily upon codon usage characteristic of this GC-rich bacterium. As a result of the revision, numerous missing ORFs were uncovered, nonexistent ORFs were deleted, and misidentified start codons were corrected. To evaluate R. sphaeroides transcriptome flexibility, expression profiles for three diverse growth modes—aerobic respiration, anaerobic respiration in the dark, and anaerobic photosynthesis—were generated. Expression levels of one-fifth to one-third of the R. sphaeroides ORFs were significantly different in cells under any two growth modes. Pathways involved in energy generation and redox balance maintenance under three growth modes were reconstructed. Expression patterns of genes involved in these pathways mirrored known functional changes, suggesting that massive changes in gene expression are the major means used by R. sphaeroides in adaptation to diverse conditions. Differential expression was observed for genes encoding putative new participants in these pathways (additional photosystem genes, duplicate NADH dehydrogenase, ATP synthases), whose functionality has yet to be investigated. The DNA microarray data correlated well with data derived from quantitative reverse transcription-PCR, as well as with data from the literature, thus validating the R. sphaeroides genechip as a powerful and reliable tool for studying unprecedented metabolic versatility of this bacterium. PMID:15231807

New Insights into the RNA-Based Mechanism of Action of the Anticancer Drug 5′-Fluorouracil in Eukaryotic Cells

PubMed Central

Mojardín, Laura; Botet, Javier; Quintales, Luis; Moreno, Sergio; Salas, Margarita

2013-01-01

5-Fluorouracil (5FU) is a chemotherapeutic drug widely used in treating a range of advanced, solid tumours and, in particular, colorectal cancer. Here, we used high-density tiling DNA microarray technology to obtain the specific transcriptome-wide response induced by 5FU in the eukaryotic model Schizosaccharomyces pombe. This approach combined with real-time quantitative PCR analysis allowed us to detect splicing defects of a significant number of intron-containing mRNA, in addition to identify some rRNA and tRNA processing defects after 5FU treatment. Interestingly, our studies also revealed that 5FU specifically induced the expression of certain genes implicated in the processing of mRNA, tRNA and rRNA precursors, and in the post-transcriptional modification of uracil residues in RNA. The transcription of several tRNA genes was also significantly induced after drug exposure. These transcriptional changes might represent a cellular response mechanism to counteract 5FU damage since deletion strains for some of these up-regulated genes were hypersensitive to 5FU. Moreover, most of these RNA processing genes have human orthologs that participate in conserved pathways, suggesting that they could be novel targets to improve the efficacy of 5FU-based treatments. PMID:24223771

Parallel characterization of anaerobic toluene- and ethylbenzene-degrading microbial consortia by PCR-denaturing gradient gel electrophoresis, RNA-DNA membrane hybridization, and DNA microarray technology

NASA Technical Reports Server (NTRS)

Koizumi, Yoshikazu; Kelly, John J.; Nakagawa, Tatsunori; Urakawa, Hidetoshi; El-Fantroussi, Said; Al-Muzaini, Saleh; Fukui, Manabu; Urushigawa, Yoshikuni; Stahl, David A.

2002-01-01

A mesophilic toluene-degrading consortium (TDC) and an ethylbenzene-degrading consortium (EDC) were established under sulfate-reducing conditions. These consortia were first characterized by denaturing gradient gel electrophoresis (DGGE) fingerprinting of PCR-amplified 16S rRNA gene fragments, followed by sequencing. The sequences of the major bands (T-1 and E-2) belonging to TDC and EDC, respectively, were affiliated with the family Desulfobacteriaceae. Another major band from EDC (E-1) was related to an uncultured non-sulfate-reducing soil bacterium. Oligonucleotide probes specific for the 16S rRNAs of target organisms corresponding to T-1, E-1, and E-2 were designed, and hybridization conditions were optimized for two analytical formats, membrane and DNA microarray hybridization. Both formats were used to characterize the TDC and EDC, and the results of both were consistent with DGGE analysis. In order to assess the utility of the microarray format for analysis of environmental samples, oil-contaminated sediments from the coast of Kuwait were analyzed. The DNA microarray successfully detected bacterial nucleic acids from these samples, but probes targeting specific groups of sulfate-reducing bacteria did not give positive signals. The results of this study demonstrate the limitations and the potential utility of DNA microarrays for microbial community analysis.

Parallel Characterization of Anaerobic Toluene- and Ethylbenzene-Degrading Microbial Consortia by PCR-Denaturing Gradient Gel Electrophoresis, RNA-DNA Membrane Hybridization, and DNA Microarray Technology

PubMed Central

Koizumi, Yoshikazu; Kelly, John J.; Nakagawa, Tatsunori; Urakawa, Hidetoshi; El-Fantroussi, Saïd; Al-Muzaini, Saleh; Fukui, Manabu; Urushigawa, Yoshikuni; Stahl, David A.

2002-01-01

A mesophilic toluene-degrading consortium (TDC) and an ethylbenzene-degrading consortium (EDC) were established under sulfate-reducing conditions. These consortia were first characterized by denaturing gradient gel electrophoresis (DGGE) fingerprinting of PCR-amplified 16S rRNA gene fragments, followed by sequencing. The sequences of the major bands (T-1 and E-2) belonging to TDC and EDC, respectively, were affiliated with the family Desulfobacteriaceae. Another major band from EDC (E-1) was related to an uncultured non-sulfate-reducing soil bacterium. Oligonucleotide probes specific for the 16S rRNAs of target organisms corresponding to T-1, E-1, and E-2 were designed, and hybridization conditions were optimized for two analytical formats, membrane and DNA microarray hybridization. Both formats were used to characterize the TDC and EDC, and the results of both were consistent with DGGE analysis. In order to assess the utility of the microarray format for analysis of environmental samples, oil-contaminated sediments from the coast of Kuwait were analyzed. The DNA microarray successfully detected bacterial nucleic acids from these samples, but probes targeting specific groups of sulfate-reducing bacteria did not give positive signals. The results of this study demonstrate the limitations and the potential utility of DNA microarrays for microbial community analysis. PMID:12088997

Microbial community analysis of an Alabama coastal salt marsh impacted by the Deepwater Horizon Oil Spill

NASA Astrophysics Data System (ADS)

Beazley, M. J.; Martinez, R.; Rajan, S.; Powell, J.; Piceno, Y.; Tom, L.; Andersen, G. L.; Hazen, T. C.; Van Nostrand, J. D.; Zhou, J.; Mortazavi, B.; Sobecky, P. A.

2011-12-01

Microbial community responses of an Alabama coastal salt marsh environment to the Deepwater Horizon oil spill were studied by 16S rRNA (PhyloChip) and functional gene (GeoChip) microarray-based analysis. Oil and tar balls associated with the oil spill arrived along the Alabama coast in June 2010. Marsh and inlet sediment samples collected in June, July, and September 2010 from a salt marsh ecosystem at Point Aux Pines Alabama were analyzed to determine if bacterial community structure changed as a result of oil perturbation. Sediment total petroleum hydrocarbon (TPH) concentrations ranged from below detection to 189 mg kg-1 and were randomly dispersed throughout the salt marsh sediments. Total DNA extracted from sediment and particulates were used for PhyloChip and GeoChip hybridization. A total of 4000 to 8000 operational taxonomic units (OTUs) were detected in marsh and inlet samples. Distinctive changes in the number of detectable OTUs were observed between June, July, and September 2010. Surficial inlet sediments demonstrated a significant increase in the total number of OTUs between June and September that correlated with TPH concentrations. The most significant increases in bacterial abundance were observed in the phyla Actinobacteria, Firmicutes, Gemmatimonadetes, Proteobacteria, and Verrucomicrobia. Bacterial richness in marsh sediments also correlated with TPH concentrations with significant changes primarily in Acidobacteria, Actinobacteria, Firmicutes, Fusobacteria, Nitrospirae, and Proteobacteria. GeoChip microarray analysis detected 5000 to 8300 functional genes in marsh and inlet samples. Surficial inlet sediments demonstrated distinctive increases in the number of detectable genes and gene signal intensities in July samples compared to June. Signal intensities increased (> 1.5-fold) in genes associated with petroleum degradation. Genes related to metal resistance, stress, and carbon cycling also demonstrated increases in oiled sediments. This study demonstrates the value of applying phylogenetic and functional gene microarray technology to characterize the extensive microbial diversity of marsh environments. Moreover, this technology provides significant insight into bacterial community responses to anthropogenic oil events.

Effect of storage time on gene expression data acquired from unfrozen archived newborn blood spots.

PubMed

Ho, Nhan T; Busik, Julia V; Resau, James H; Paneth, Nigel; Khoo, Sok Kean

2016-11-01

Unfrozen archived newborn blood spots (NBS) have been shown to retain sufficient messenger RNA (mRNA) for gene expression profiling. However, the effect of storage time at ambient temperature for NBS samples in relation to the quality of gene expression data is relatively unknown. Here, we evaluated mRNA expression from quantitative real-time PCR (qRT-PCR) and microarray data obtained from NBS samples stored at ambient temperature to determine the effect of storage time on the quality of gene expression. These data were generated in a previous case-control study examining NBS in 53 children with cerebral palsy (CP) and 53 matched controls. NBS sample storage period ranged from 3 to 16years at ambient temperature. We found persistently low RNA integrity numbers (RIN=2.3±0.71) and 28S/18S rRNA ratios (~0) across NBS samples for all storage periods. In both qRT-PCR and microarray data, the expression of three common housekeeping genes-beta cytoskeletal actin (ACTB), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), and peptidylprolyl isomerase A (PPIA)-decreased with increased storage time. Median values of each microarray probe intensity at log 2 scale also decreased over time. After eight years of storage, probe intensity values were largely reduced to background intensity levels. Of 21,500 genes tested, 89% significantly decreased in signal intensity, with 13,551, 10,730, and 9925 genes detected within 5years, > 5 to <10years, and >10years of storage, respectively. We also examined the expression of two gender-specific genes (X inactivation-specific transcript, XIST and lysine-specific demethylase 5D, KDM5D) and seven gene sets representing the inflammatory, hypoxic, coagulative, and thyroidal pathways hypothesized to be related to CP risk to determine the effect of storage time on the detection of these biologically relevant genes. We found the gender-specific genes and CP-related gene sets detectable in all storage periods, but exhibited differential expression (between male vs. female or CP vs. control) only within the first six years of storage. We concluded that gene expression data quality deteriorates in unfrozen archived NBS over time and that differential gene expression profiling and analysis is recommended for those NBS samples collected and stored within six years at ambient temperature. Copyright © 2016 Elsevier Inc. All rights reserved.

Peatland succession induces a shift in the community composition of Sphagnum-associated active methanotrophs.

PubMed

Putkinen, Anuliina; Larmola, Tuula; Tuomivirta, Tero; Siljanen, Henri M P; Bodrossy, Levente; Tuittila, Eeva-Stiina; Fritze, Hannu

2014-06-01

Sphagnum-associated methanotrophs (SAM) are an important sink for the methane (CH4) formed in boreal peatlands. We aimed to reveal how peatland succession, which entails a directional change in several environmental variables, affects SAM and their activity. Based on the pmoA microarray results, SAM community structure changes when a peatland develops from a minerotrophic fen to an ombrotrophic bog. Methanotroph subtypes Ia, Ib, and II showed slightly contrasting patterns during succession, suggesting differences in their ecological niche adaptation. Although the direct DNA-based analysis revealed a high diversity of type Ib and II methanotrophs throughout the studied peatland chronosequence, stable isotope probing (SIP) of the pmoA gene indicated they were active mainly during the later stages of succession. In contrast, type Ia methanotrophs showed active CH4 consumption in all analyzed samples. SIP-derived (13)C-labeled 16S rRNA gene clone libraries revealed a high diversity of SAM in every succession stage including some putative Methylocella/Methyloferula methanotrophs that are not detectable with the pmoA-based approach. In addition, a high diversity of 16S rRNA gene sequences likely representing cross-labeled nonmethanotrophs was discovered, including a significant proportion of Verrucomicrobia-related sequences. These results help to predict the effects of changing environmental conditions on SAM communities and activity. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Multiple independent insertions of 5S rRNA genes in the spliced-leader gene family of trypanosome species.

PubMed

Beauparlant, Marc A; Drouin, Guy

2014-02-01

Analyses of the 5S rRNA genes found in the spliced-leader (SL) gene repeat units of numerous trypanosome species suggest that such linkages were not inherited from a common ancestor, but were the result of independent 5S rRNA gene insertions. In trypanosomes, 5S rRNA genes are found either in the tandemly repeated units coding for SL genes or in independent tandemly repeated units. Given that trypanosome species where 5S rRNA genes are within the tandemly repeated units coding for SL genes are phylogenetically related, one might hypothesize that this arrangement is the result of an ancestral insertion of 5S rRNA genes into the tandemly repeated SL gene family of trypanosomes. Here, we use the types of 5S rRNA genes found associated with SL genes, the flanking regions of the inserted 5S rRNA genes and the position of these insertions to show that most of the 5S rRNA genes found within SL gene repeat units of trypanosome species were not acquired from a common ancestor but are the results of independent insertions. These multiple 5S rRNA genes insertion events in trypanosomes are likely the result of frequent founder events in different hosts and/or geographical locations in species having short generation times.

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.

Electrochemical detection of synthetic DNA and native 16S rRNA fragments on a microarray using a biotinylated intercalator as coupling site for an enzyme label.

PubMed

Zimdars, Andreas; Gebala, Magdalena; Hartwich, Gerhard; Neugebauer, Sebastian; Schuhmann, Wolfgang

2015-10-01

The direct electrochemical detection of synthetic DNA and native 16S rRNA fragments isolated from Escherichia coli is described. Oligonucleotides are detected via selective post-labeling of double stranded DNA and DNA-RNA duplexes with a biotinylated intercalator that enables high-specific binding of a streptavidin/alkaline phosphatase conjugate. The alkaline phosphatase catalyzes formation of p-aminophenol that is subsequently oxidized at the underlying gold electrode and hence enables the detection of complementary hybridization of the DNA capture strands due to the enzymatic signal amplification. The hybridization assay was performed on microarrays consisting of 32 individually addressable gold microelectrodes. Synthetic DNA strands with sequences representing six different pathogens which are important for the diagnosis of urinary tract infections could be detected at concentrations of 60 nM. Native 16S rRNA isolated from the different pathogens could be detected at a concentration of 30 fM. Optimization of the sensing surface is described and influences on the assay performance are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

Two distinct extracellular RNA signatures released by a single cell type identified by microarray and next-generation sequencing

PubMed Central

Lässer, Cecilia; Shelke, Ganesh Vilas; Yeri, Ashish; Kim, Dae-Kyum; Crescitelli, Rossella; Raimondo, Stefania; Sjöstrand, Margareta; Gho, Yong Song; Van Keuren Jensen, Kendall; Lötvall, Jan

2017-01-01

ABSTRACT Cells secrete extracellular RNA (exRNA) to their surrounding environment and exRNA has been found in many body fluids such as blood, breast milk and cerebrospinal fluid. However, there are conflicting results regarding the nature of exRNA. Here, we have separated 2 distinct exRNA profiles released by mast cells, here termed high-density (HD) and low-density (LD) exRNA. The exRNA in both fractions was characterized by microarray and next-generation sequencing. Both exRNA fractions contained mRNA and miRNA, and the mRNAs in the LD exRNA correlated closely with the cellular mRNA, whereas the HD mRNA did not. Furthermore, the HD exRNA was enriched in lincRNA, antisense RNA, vault RNA, snoRNA, and snRNA with little or no evidence of full-length 18S and 28S rRNA. The LD exRNA was enriched in mitochondrial rRNA, mitochondrial tRNA, tRNA, piRNA, Y RNA, and full-length 18S and 28S rRNA. The proteomes of the HD and LD exRNA-containing fractions were determined with LC-MS/MS and analyzed with Gene Ontology term finder, which showed that both proteomes were associated with the term extracellular vesicles and electron microscopy suggests that at least a part of the exRNA is associated with exosome-like extracellular vesicles. Additionally, the proteins in the HD fractions tended to be associated with the nucleus and ribosomes, whereas the LD fraction proteome tended to be associated with the mitochondrion. We show that the 2 exRNA signatures released by a single cell type can be separated by floatation on a density gradient. These results show that cells can release multiple types of exRNA with substantial differences in RNA species content. This is important for any future studies determining the nature and function of exRNA released from different cells under different conditions. PMID:27791479

Phylogenetic Analysis of Shewanella Strains by DNA Relatedness Derived from Whole Genome Microarray DNA-DNA Hybridization and Comparison with Other Methods

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

Wu, Liyou; Yi, T. Y.; Van Nostrand, Joy

Phylogenetic analyses were done for the Shewanella strains isolated from Baltic Sea (38 strains), US DOE Hanford Uranium bioremediation site [Hanford Reach of the Columbia River (HRCR), 11 strains], Pacific Ocean and Hawaiian sediments (8 strains), and strains from other resources (16 strains) with three out group strains, Rhodopseudomonas palustris, Clostridium cellulolyticum, and Thermoanaerobacter ethanolicus X514, using DNA relatedness derived from WCGA-based DNA-DNA hybridizations, sequence similarities of 16S rRNA gene and gyrB gene, and sequence similarities of 6 loci of Shewanella genome selected from a shared gene list of the Shewanella strains with whole genome sequenced based on the averagemore » nucleotide identity of them (ANI). The phylogenetic trees based on 16S rRNA and gyrB gene sequences, and DNA relatedness derived from WCGA hybridizations of the tested Shewanella strains share exactly the same sub-clusters with very few exceptions, in which the strains were basically grouped by species. However, the phylogenetic analysis based on DNA relatedness derived from WCGA hybridizations dramatically increased the differentiation resolution at species and strains level within Shewanella genus. When the tree based on DNA relatedness derived from WCGA hybridizations was compared to the tree based on the combined sequences of the selected functional genes (6 loci), we found that the resolutions of both methods are similar, but the clustering of the tree based on DNA relatedness derived from WMGA hybridizations was clearer. These results indicate that WCGA-based DNA-DNA hybridization is an idea alternative of conventional DNA-DNA hybridization methods and it is superior to the phylogenetics methods based on sequence similarities of single genes. Detailed analysis is being performed for the re-classification of the strains examined.« less

Dramatic Increases of Soil Microbial Functional Gene Diversity at the Treeline Ecotone of Changbai Mountain.

PubMed

Shen, Congcong; Shi, Yu; Ni, Yingying; Deng, Ye; Van Nostrand, Joy D; He, Zhili; Zhou, Jizhong; Chu, Haiyan

2016-01-01

The elevational and latitudinal diversity patterns of microbial taxa have attracted great attention in the past decade. Recently, the distribution of functional attributes has been in the spotlight. Here, we report a study profiling soil microbial communities along an elevation gradient (500-2200 m) on Changbai Mountain. Using a comprehensive functional gene microarray (GeoChip 5.0), we found that microbial functional gene richness exhibited a dramatic increase at the treeline ecotone, but the bacterial taxonomic and phylogenetic diversity based on 16S rRNA gene sequencing did not exhibit such a similar trend. However, the β-diversity (compositional dissimilarity among sites) pattern for both bacterial taxa and functional genes was similar, showing significant elevational distance-decay patterns which presented increased dissimilarity with elevation. The bacterial taxonomic diversity/structure was strongly influenced by soil pH, while the functional gene diversity/structure was significantly correlated with soil dissolved organic carbon (DOC). This finding highlights that soil DOC may be a good predictor in determining the elevational distribution of microbial functional genes. The finding of significant shifts in functional gene diversity at the treeline ecotone could also provide valuable information for predicting the responses of microbial functions to climate change.

Molecular characterization of 5S ribosomal RNA genes and transcripts in the protozoan parasite Leishmania major.

PubMed

Moreno-Campos, Rodrigo; Florencio-Martínez, Luis E; Nepomuceno-Mejía, Tomás; Rojas-Sánchez, Saúl; Vélez-Ramírez, Daniel E; Padilla-Mejía, Norma E; Figueroa-Angulo, Elisa; Manning-Cela, Rebeca; Martínez-Calvillo, Santiago

2016-12-01

Eukaryotic 5S rRNA, synthesized by RNA polymerase III (Pol III), is an essential component of the large ribosomal subunit. Most organisms contain hundreds of 5S rRNA genes organized into tandem arrays. However, the genome of the protozoan parasite Leishmania major contains only 11 copies of the 5S rRNA gene, which are interspersed and associated with other Pol III-transcribed genes. Here we report that, in general, the number and order of the 5S rRNA genes is conserved between different species of Leishmania. While in most organisms 5S rRNA genes are normally associated with the nucleolus, combined fluorescent in situ hybridization and indirect immunofluorescence experiments showed that 5S rRNA genes are mainly located at the nuclear periphery in L. major. Similarly, the tandemly repeated 5S rRNA genes in Trypanosoma cruzi are dispersed throughout the nucleus. In contrast, 5S rRNA transcripts in L. major were localized within the nucleolus, and scattered throughout the cytoplasm, where mature ribosomes are located. Unlike other rRNA species, stable antisense RNA complementary to 5S rRNA is not detected in L. major.

Microarray and Real-Time PCR Analyses of the Responses of High-Arctic Soil Bacteria to Hydrocarbon Pollution and Bioremediation Treatments▿

PubMed Central

Yergeau, Etienne; Arbour, Mélanie; Brousseau, Roland; Juck, David; Lawrence, John R.; Masson, Luke; Whyte, Lyle G.; Greer, Charles W.

2009-01-01

High-Arctic soils have low nutrient availability, low moisture content, and very low temperatures and, as such, they pose a particular problem in terms of hydrocarbon bioremediation. An in-depth knowledge of the microbiology involved in this process is likely to be crucial to understand and optimize the factors most influencing bioremediation. Here, we compared two distinct large-scale field bioremediation experiments, located at the Canadian high-Arctic stations of Alert (ex situ approach) and Eureka (in situ approach). Bacterial community structure and function were assessed using microarrays targeting the 16S rRNA genes of bacteria found in cold environments and hydrocarbon degradation genes as well as quantitative reverse transcriptase PCR targeting key functional genes. The results indicated a large difference between sampling sites in terms of both soil microbiology and decontamination rates. A rapid reorganization of the bacterial community structure and functional potential as well as rapid increases in the expression of alkane monooxygenases and polyaromatic hydrocarbon-ring-hydroxylating dioxygenases were observed 1 month after the bioremediation treatment commenced in the Alert soils. In contrast, no clear changes in community structure were observed in Eureka soils, while key gene expression increased after a relatively long lag period (1 year). Such discrepancies are likely caused by differences in bioremediation treatments (i.e., ex situ versus in situ), weathering of the hydrocarbons, indigenous microbial communities, and environmental factors such as soil humidity and temperature. In addition, this study demonstrates the value of molecular tools for the monitoring of polar bacteria and their associated functions during bioremediation. PMID:19684169

Tandem repeats of the 5' non-transcribed spacer of Tetrahymena rDNA function as high copy number autonomous replicons in the macronucleus but do not prevent rRNA gene dosage regulation.

PubMed Central

Pan, W J; Blackburn, E H

1995-01-01

The rRNA genes in the somatic macronucleus of Tetrahymena thermophila are normally on 21 kb linear palindromic molecules (rDNA). We examined the effect on rRNA gene dosage of transforming T.thermophila macronuclei with plasmid constructs containing a pair of tandemly repeated rDNA replication origin regions unlinked to the rRNA gene. A significant proportion of the plasmid sequences were maintained as high copy circular molecules, eventually consisting solely of tandem arrays of origin regions. As reported previously for cells transformed by a construct in which the same tandem rDNA origins were linked to the rRNA gene [Yu, G.-L. and Blackburn, E. H. (1990) Mol. Cell. Biol., 10, 2070-2080], origin sequences recombined to form linear molecules bearing several tandem repeats of the origin region, as well as rRNA genes. The total number of rDNA origin sequences eventually exceeded rRNA gene copies by approximately 20- to 40-fold and the number of circular replicons carrying only rDNA origin sequences exceeded rRNA gene copies by 2- to 3-fold. However, the rRNA gene dosage was unchanged. Hence, simply monitoring the total number of rDNA origin regions is not sufficient to regulate rRNA gene copy number. Images PMID:7784211

Microarray Analysis of Microbiota of Gingival Lesions in Noma Patients

PubMed Central

Huyghe, Antoine; François, Patrice; Mombelli, Andrea; Tangomo, Manuela; Girard, Myriam; Baratti-Mayer, Denise; Bolivar, Ignacio; Pittet, Didier; Schrenzel, Jacques

2013-01-01

Noma (cancrum oris) is a gangrenous disease of unknown etiology affecting the maxillo-facial region of young children in extremely limited resource countries. In an attempt to better understand the microbiological events occurring during this disease, we used phylogenetic and low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis (ANG) lesions, and compared them to healthy control subjects of the same geographical and social background. Our observations raise doubts about Fusobacterium necrophorum, a previously suspected causative agent of noma, as this species was not associated with noma lesions. Various oral pathogens were more abundant in noma lesions, notably Atopobium spp., Prevotella intermedia, Peptostreptococcus spp., Streptococcus pyogenes and Streptococcus anginosus. On the other hand, pathogens associated with periodontal diseases such as Aggregatibacter actinomycetemcomitans, Capnocytophaga spp., Porphyromonas spp. and Fusobacteriales were more abundant in healthy controls. Importantly, the overall loss of bacterial diversity observed in noma samples as well as its homology to that of ANG microbiota supports the hypothesis that ANG might be the immediate step preceding noma. PMID:24086784

FunGene: the functional gene pipeline and repository.

PubMed

Fish, Jordan A; Chai, Benli; Wang, Qiong; Sun, Yanni; Brown, C Titus; Tiedje, James M; Cole, James R

2013-01-01

Ribosomal RNA genes have become the standard molecular markers for microbial community analysis for good reasons, including universal occurrence in cellular organisms, availability of large databases, and ease of rRNA gene region amplification and analysis. As markers, however, rRNA genes have some significant limitations. The rRNA genes are often present in multiple copies, unlike most protein-coding genes. The slow rate of change in rRNA genes means that multiple species sometimes share identical 16S rRNA gene sequences, while many more species share identical sequences in the short 16S rRNA regions commonly analyzed. In addition, the genes involved in many important processes are not distributed in a phylogenetically coherent manner, potentially due to gene loss or horizontal gene transfer. While rRNA genes remain the most commonly used markers, key genes in ecologically important pathways, e.g., those involved in carbon and nitrogen cycling, can provide important insights into community composition and function not obtainable through rRNA analysis. However, working with ecofunctional gene data requires some tools beyond those required for rRNA analysis. To address this, our Functional Gene Pipeline and Repository (FunGene; http://fungene.cme.msu.edu/) offers databases of many common ecofunctional genes and proteins, as well as integrated tools that allow researchers to browse these collections and choose subsets for further analysis, build phylogenetic trees, test primers and probes for coverage, and download aligned sequences. Additional FunGene tools are specialized to process coding gene amplicon data. For example, FrameBot produces frameshift-corrected protein and DNA sequences from raw reads while finding the most closely related protein reference sequence. These tools can help provide better insight into microbial communities by directly studying key genes involved in important ecological processes.

Genome-Wide Characterization of Light-Regulated Genes in Neurospora crassa

PubMed Central

Wu, Cheng; Yang, Fei; Smith, Kristina M.; Peterson, Matthew; Dekhang, Rigzin; Zhang, Ying; Zucker, Jeremy; Bredeweg, Erin L.; Mallappa, Chandrashekara; Zhou, Xiaoying; Lyubetskaya, Anna; Townsend, Jeffrey P.; Galagan, James E.; Freitag, Michael; Dunlap, Jay C.; Bell-Pedersen, Deborah; Sachs, Matthew S.

2014-01-01

The filamentous fungus Neurospora crassa responds to light in complex ways. To thoroughly study the transcriptional response of this organism to light, RNA-seq was used to analyze capped and polyadenylated mRNA prepared from mycelium grown for 24 hr in the dark and then exposed to light for 0 (control) 15, 60, 120, and 240 min. More than three-quarters of all defined protein coding genes (79%) were expressed in these cells. The increased sensitivity of RNA-seq compared with previous microarray studies revealed that the RNA levels for 31% of expressed genes were affected two-fold or more by exposure to light. Additionally, a large class of mRNAs, enriched for transcripts specifying products involved in rRNA metabolism, showed decreased expression in response to light, indicating a heretofore undocumented effect of light on this pathway. Based on measured changes in mRNA levels, light generally increases cellular metabolism and at the same time causes significant oxidative stress to the organism. To deal with this stress, protective photopigments are made, antioxidants are produced, and genes involved in ribosome biogenesis are transiently repressed. PMID:25053707

Folate deficiency facilitates recruitment of upstream binding factor to hot spots of DNA double-strand breaks of rRNA genes and promotes its transcription.

PubMed

Xie, Qiu; Li, Caihua; Song, Xiaozhen; Wu, Lihua; Jiang, Qian; Qiu, Zhiyong; Cao, Haiyan; Yu, Kaihui; Wan, Chunlei; Li, Jianting; Yang, Feng; Huang, Zebing; Niu, Bo; Jiang, Zhengwen; Zhang, Ting

2017-03-17

The biogenesis of ribosomes in vivo is an essential process for cellular functions. Transcription of ribosomal RNA (rRNA) genes is the rate-limiting step in ribosome biogenesis controlled by environmental conditions. Here, we investigated the role of folate antagonist on changes of DNA double-strand breaks (DSBs) landscape in mouse embryonic stem cells. A significant DSB enhancement was detected in the genome of these cells and a large majority of these DSBs were found in rRNA genes. Furthermore, spontaneous DSBs in cells under folate deficiency conditions were located exclusively within the rRNA gene units, representing a H3K4me1 hallmark. Enrichment H3K4me1 at the hot spots of DSB regions enhanced the recruitment of upstream binding factor (UBF) to rRNA genes, resulting in the increment of rRNA genes transcription. Supplement of folate resulted in a restored UBF binding across DNA breakage sites of rRNA genes, and normal rRNA gene transcription. In samples from neural tube defects (NTDs) with low folate level, up-regulation of rRNA gene transcription was observed, along with aberrant UBF level. Our results present a new view by which alterations in folate levels affects DNA breakage through epigenetic control leading to the regulation of rRNA gene transcription during the early stage of development. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identifying Fishes through DNA Barcodes and Microarrays.

PubMed

Kochzius, Marc; Seidel, Christian; Antoniou, Aglaia; Botla, Sandeep Kumar; Campo, Daniel; Cariani, Alessia; Vazquez, Eva Garcia; Hauschild, Janet; Hervet, Caroline; Hjörleifsdottir, Sigridur; Hreggvidsson, Gudmundur; Kappel, Kristina; Landi, Monica; Magoulas, Antonios; Marteinsson, Viggo; Nölte, Manfred; Planes, Serge; Tinti, Fausto; Turan, Cemal; Venugopal, Moleyur N; Weber, Hannes; Blohm, Dietmar

2010-09-07

International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection. This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S), cytochrome b (cyt b), and cytochrome oxidase subunit I (COI) for the identification of 50 European marine fish species by combining techniques of "DNA barcoding" and microarrays. In a DNA barcoding approach, neighbour Joining (NJ) phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the "position of label" effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (>90%) renders the DNA barcoding marker as rather unsuitable for this high-throughput technology. Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products.

Leuconostoc pseudomesenteroides WCFur3 partial 16S rRNA gene

USDA-ARS?s Scientific Manuscript database

This study used a partial 535 base pair 16S rRNA gene sequence to identify a bacterial isolate. Fatty acid profiles are consistent with the 16S rRNA gene sequence identification of this bacterium. The isolate was obtained from a compost bin in Fort Collins, Colorado, USA. The 16S rRNA gene sequen...

Characterization of a novel Lactobacillus species closely related to Lactobacillus johnsonii using a combination of molecular and comparative genomics methods.

PubMed

Sarmiento-Rubiano, Luz-Adriana; Berger, Bernard; Moine, Déborah; Zúñiga, Manuel; Pérez-Martínez, Gaspar; Yebra, María J

2010-09-17

Comparative genomic hybridization (CGH) constitutes a powerful tool for identification and characterization of bacterial strains. In this study we have applied this technique for the characterization of a number of Lactobacillus strains isolated from the intestinal content of rats fed with a diet supplemented with sorbitol. Phylogenetic analysis based on 16S rRNA gene, recA, pheS, pyrG and tuf sequences identified five bacterial strains isolated from the intestinal content of rats as belonging to the recently described Lactobacillus taiwanensis species. DNA-DNA hybridization experiments confirmed that these five strains are distinct but closely related to Lactobacillus johnsonii and Lactobacillus gasseri. A whole genome DNA microarray designed for the probiotic L. johnsonii strain NCC533 was used for CGH analysis of L. johnsonii ATCC 33200T, L. johnsonii BL261, L. gasseri ATCC 33323T and L. taiwanensis BL263. In these experiments, the fluorescence ratio distributions obtained with L. taiwanensis and L. gasseri showed characteristic inter-species profiles. The percentage of conserved L. johnsonii NCC533 genes was about 83% in the L. johnsonii strains comparisons and decreased to 51% and 47% for L. taiwanensis and L. gasseri, respectively. These results confirmed the separate status of L. taiwanensis from L. johnsonii at the level of species, and also that L. taiwanensis is closer to L. johnsonii than L. gasseri is to L. johnsonii. Conventional taxonomic analyses and microarray-based CGH analysis have been used for the identification and characterization of the newly species L. taiwanensis. The microarray-based CGH technology has been shown as a remarkable tool for the identification and fine discrimination between phylogenetically close species, and additionally provided insight into the adaptation of the strain L. taiwanensis BL263 to its ecological niche.

High-Density 16S Microarray and Clone Library-Based Microbial Community Composition of the Phoenix Spacecraft Assembly Clean Room

NASA Astrophysics Data System (ADS)

Vaishampayan, Parag; Osman, Shariff; Andersen, Gary; Venkateswaran, Kasthuri

2010-06-01

The bacterial diversity and comparative community structure of a clean room used for assembling the Phoenix spacecraft was characterized throughout the spacecraft assembly process by using 16S rRNA gene cloning/sequencing and DNA microarray (PhyloChip) technologies. Samples were collected from several locations of the clean room at three time points: before Phoenix's arrival (PHX-B), during hardware assembly (PHX-D), and after the spacecraft was removed for launch (PHX-A). Bacterial diversity comprised of all major bacterial phyla of PHX-B was found to be statistically different from PHX-D and PHX-A samples. Due to stringent cleaning and decontamination protocols during assembly, PHX-D bacterial diversity was dramatically reduced when compared to PHX-B and PHX-A samples. Comparative community analysis based on PhyloChip results revealed similar overall trends as were seen in clone libraries, but the high-density phylogenetic microarray detected larger diversity in all sampling events. The decrease in community complexity in PHX-D compared to PHX-B, and the subsequent recurrence of these organisms in PHX-A, speaks to the effectiveness of NASA cleaning protocols. However, the persistence of a subset of bacterial signatures throughout all spacecraft assembly phases underscores the need for continued refinement of sterilization technologies and the implementation of safeguards that monitor and inventory microbial contaminants.

High-density 16S microarray and clone library-based microbial community composition of the Phoenix spacecraft assembly clean room.

PubMed

Vaishampayan, Parag; Osman, Shariff; Andersen, Gary; Venkateswaran, Kasthuri

2010-06-01

The bacterial diversity and comparative community structure of a clean room used for assembling the Phoenix spacecraft was characterized throughout the spacecraft assembly process by using 16S rRNA gene cloning/sequencing and DNA microarray (PhyloChip) technologies. Samples were collected from several locations of the clean room at three time points: before Phoenix's arrival (PHX-B), during hardware assembly (PHX-D), and after the spacecraft was removed for launch (PHX-A). Bacterial diversity comprised of all major bacterial phyla of PHX-B was found to be statistically different from PHX-D and PHX-A samples. Due to stringent cleaning and decontamination protocols during assembly, PHX-D bacterial diversity was dramatically reduced when compared to PHX-B and PHX-A samples. Comparative community analysis based on PhyloChip results revealed similar overall trends as were seen in clone libraries, but the high-density phylogenetic microarray detected larger diversity in all sampling events. The decrease in community complexity in PHX-D compared to PHX-B, and the subsequent recurrence of these organisms in PHX-A, speaks to the effectiveness of NASA cleaning protocols. However, the persistence of a subset of bacterial signatures throughout all spacecraft assembly phases underscores the need for continued refinement of sterilization technologies and the implementation of safeguards that monitor and inventory microbial contaminants.

Direct profiling of environmental microbial populations by thermal dissociation analysis of native rRNAs hybridized to oligonucleotide microarrays

NASA Technical Reports Server (NTRS)

El Fantroussi, Said; Urakawa, Hidetoshi; Bernhard, Anne E.; Kelly, John J.; Noble, Peter A.; Smidt, H.; Yershov, G. M.; Stahl, David A.

2003-01-01

Oligonucleotide microarrays were used to profile directly extracted rRNA from environmental microbial populations without PCR amplification. In our initial inspection of two distinct estuarine study sites, the hybridization patterns were reproducible and varied between estuarine sediments of differing salinities. The determination of a thermal dissociation curve (i.e., melting profile) for each probe-target duplex provided information on hybridization specificity, which is essential for confirming adequate discrimination between target and nontarget sequences.

Dramatic Increases of Soil Microbial Functional Gene Diversity at the Treeline Ecotone of Changbai Mountain

PubMed Central

Shen, Congcong; Shi, Yu; Ni, Yingying; Deng, Ye; Van Nostrand, Joy D.; He, Zhili; Zhou, Jizhong; Chu, Haiyan

2016-01-01

The elevational and latitudinal diversity patterns of microbial taxa have attracted great attention in the past decade. Recently, the distribution of functional attributes has been in the spotlight. Here, we report a study profiling soil microbial communities along an elevation gradient (500–2200 m) on Changbai Mountain. Using a comprehensive functional gene microarray (GeoChip 5.0), we found that microbial functional gene richness exhibited a dramatic increase at the treeline ecotone, but the bacterial taxonomic and phylogenetic diversity based on 16S rRNA gene sequencing did not exhibit such a similar trend. However, the β-diversity (compositional dissimilarity among sites) pattern for both bacterial taxa and functional genes was similar, showing significant elevational distance-decay patterns which presented increased dissimilarity with elevation. The bacterial taxonomic diversity/structure was strongly influenced by soil pH, while the functional gene diversity/structure was significantly correlated with soil dissolved organic carbon (DOC). This finding highlights that soil DOC may be a good predictor in determining the elevational distribution of microbial functional genes. The finding of significant shifts in functional gene diversity at the treeline ecotone could also provide valuable information for predicting the responses of microbial functions to climate change. PMID:27524983

Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

PubMed

Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

2014-01-01

Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

Gene selection for microarray data classification via subspace learning and manifold regularization.

PubMed

Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

2017-12-19

With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

Contributions to Statistical Problems Related to Microarray Data

ERIC Educational Resources Information Center

Hong, Feng

2009-01-01

Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…

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

Interactions between Snow Chemistry, Mercury Inputs and Microbial Population Dynamics in an Arctic Snowpack

PubMed Central

Larose, Catherine; Prestat, Emmanuel; Cecillon, Sébastien; Berger, Sibel; Malandain, Cédric; Lyon, Delina; Ferrari, Christophe; Schneider, Dominique; Dommergue, Aurélien; Vogel, Timothy M.

2013-01-01

We investigated the interactions between snowpack chemistry, mercury (Hg) contamination and microbial community structure and function in Arctic snow. Snowpack chemistry (inorganic and organic ions) including mercury (Hg) speciation was studied in samples collected during a two-month field study in a high Arctic site, Svalbard, Norway (79°N). Shifts in microbial community structure were determined by using a 16S rRNA gene phylogenetic microarray. We linked snowpack and meltwater chemistry to changes in microbial community structure by using co-inertia analyses (CIA) and explored changes in community function due to Hg contamination by q-PCR quantification of Hg-resistance genes in metagenomic samples. Based on the CIA, chemical and microbial data were linked (p = 0.006) with bioavailable Hg (BioHg) and methylmercury (MeHg) contributing significantly to the ordination of samples. Mercury was shown to influence community function with increases in merA gene copy numbers at low BioHg levels. Our results show that snowpacks can be considered as dynamic habitats with microbial and chemical components responding rapidly to environmental changes. PMID:24282515

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/.

Detection and identification of bacteria in clinical samples by 16S rRNA gene sequencing: comparison of two different approaches in clinical practice.

PubMed

Jenkins, Claire; Ling, Clare L; Ciesielczuk, Holly L; Lockwood, Julianne; Hopkins, Susan; McHugh, Timothy D; Gillespie, Stephen H; Kibbler, Christopher C

2012-04-01

Amplification and sequence analysis of the 16S rRNA gene can be applied to detect and identify bacteria in clinical samples. We examined 75 clinical samples (17 culture-positive, 58 culture-negative) prospectively by two different PCR protocols, amplifying either a single fragment (1343 bp) or two fragments (762/598 bp) of the 16S rRNA gene. The 1343 bp PCR and 762/598 bp PCRs detected and identified the bacterial 16S rRNA gene in 23 (31 %) and 38 (51 %) of the 75 samples, respectively. The 1343 bp PCR identified 19 of 23 (83 %) PCR-positive samples to species level while the 762/598 bp PCR identified 14 of 38 (37 %) bacterial 16S rRNA gene fragments to species level and 24 to the genus level only. Amplification of shorter fragments of the bacterial 16S rRNA gene (762 and 598 bp) resulted in a more sensitive assay; however, analysis of a large fragment (1343 bp) improved species discrimination. Although not statistically significant, the 762/598 bp PCR detected the bacterial 16S rRNA gene in more samples than the 1343 bp PCR, making it more likely to be a more suitable method for the primary detection of the bacterial 16S rRNA gene in the clinical setting. The 1343 bp PCR may be used in combination with the 762/598 bp PCR when identification of the bacterial rRNA gene to species level is required.

Detection of Verrucomicrobia in a Pasture Soil by PCR-Mediated Amplification of 16S rRNA Genes

PubMed Central

O’Farrell, Katrina A.; Janssen, Peter H.

1999-01-01

Oligonucleotide primers were designed and used to amplify, by PCR, partial 16S rRNA genes of members of the bacterial division Verrucomicrobia in DNA extracted from a pasture soil. By applying most-probable-number theory to the assay, verrucomicrobia appeared to contribute some 0.2% of the soil DNA. Amplified ribosomal DNA restriction analysis of 53 cloned PCR-amplified partial 16S rRNA gene fragments and comparative sequence analysis of 21 nonchimeric partial 16S rRNA genes showed that these primers amplified only 16S rRNA genes of members of the Verrucomicrobia in DNA extracted from the soil. PMID:10473454

Importing MAGE-ML format microarray data into BioConductor.

PubMed

Durinck, Steffen; Allemeersch, Joke; Carey, Vincent J; Moreau, Yves; De Moor, Bart

2004-12-12

The microarray gene expression markup language (MAGE-ML) is a widely used XML (eXtensible Markup Language) standard for describing and exchanging information about microarray experiments. It can describe microarray designs, microarray experiment designs, gene expression data and data analysis results. We describe RMAGEML, a new Bioconductor package that provides a link between cDNA microarray data stored in MAGE-ML format and the Bioconductor framework for preprocessing, visualization and analysis of microarray experiments. http://www.bioconductor.org. Open Source.

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...

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.

Transcriptional analysis of nucleolar dominance in polyploid plants: Biased expression/silencing of progenitor rRNA genes is developmentally regulated in Brassica

PubMed Central

Chen, Z. Jeffrey; Pikaard, Craig S.

1997-01-01

Nucleolar dominance is an epigenetic phenomenon that describes the formation of nucleoli around rRNA genes inherited from only one parent in the progeny of an interspecific hybrid. Despite numerous cytogenetic studies, little is known about nucleolar dominance at the level of rRNA gene expression in plants. We used S1 nuclease protection and primer extension assays to define nucleolar dominance at a molecular level in the plant genus Brassica. rRNA transcription start sites were mapped in three diploids and in three allotetraploids (amphidiploids) and one allohexaploid species derived from these diploid progenitors. rRNA transcripts of only one progenitor were detected in vegetative tissues of each polyploid. Dominance was independent of maternal effect, ploidy, or rRNA gene dosage. Natural and newly synthesized amphidiploids yielded the same results, arguing against substantial evolutionary effects. The hypothesis that nucleolar dominance in plants is correlated with physical characteristics of rRNA gene intergenic spacers is not supported in Brassica. Furthermore, in Brassica napus, rRNA genes silenced in vegetative tissues were found to be expressed in all floral organs, including sepals and petals, arguing against the hypothesis that passage through meiosis is needed to reactivate suppressed genes. Instead, the transition of inflorescence to floral meristem appears to be a developmental stage when silenced genes can be derepressed. PMID:9096413

Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.

PubMed

Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu

2015-01-01

Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.

A New Oligonucleotide Microarray for Detection of Pathogenic and Non-Pathogenic Legionella spp.

PubMed Central

Cao, Boyang; Liu, Xiangqian; Yu, Xiang; Chen, Min; Feng, Lu; Wang, Lei

2014-01-01

Legionella pneumophila has been recognized as the major cause of legionellosis since the discovery of the deadly disease. Legionella spp. other than L. pneumophila were later found to be responsible to many non-pneumophila infections. The non-L. pneumophila infections are likely under-detected because of a lack of effective diagnosis. In this report, we have sequenced the 16S-23S rRNA gene internal transcribed spacer (ITS) of 10 Legionella species and subspecies, including L. anisa, L. bozemanii, L. dumoffii, L. fairfieldensis, L. gormanii, L. jordanis, L. maceachernii, L. micdadei, L. pneumophila subspp. fraseri and L. pneumophila subspp. pasculleii, and developed a rapid oligonucleotide microarray detection technique accordingly to identify 12 most common Legionella spp., which consist of 11 pathogenic species of L. anisa, L. bozemanii, L. dumoffii, L. gormanii, L. jordanis, L. longbeachae, L. maceachernii, L. micdadei, and L. pneumophila (including subspp. pneumophila, subspp. fraseri, and subspp. pasculleii) and one non-pathogenic species, L. fairfieldensis. Twenty-nine probes that reproducibly detected multiple Legionella species with high specificity were included in the array. A total of 52 strains, including 30 target pathogens and 22 non-target bacteria, were used to verify the oligonucleotide microarray assay. The sensitivity of the detection was at 1.0 ng with genomic DNA or 13 CFU/100 mL with Legionella cultures. The microarray detected seven samples of air conditioner-condensed water with 100% accuracy, validating the technique as a promising method for applications in basic microbiology, clinical diagnosis, food safety, and epidemiological surveillance. The phylogenetic study based on the ITS has also revealed that the non-pathogenic L. fairfieldensis is the closest to L. pneumophila than the nine other pathogenic Legionella spp. PMID:25469776

A new oligonucleotide microarray for detection of pathogenic and non-pathogenic Legionella spp.

PubMed

Cao, Boyang; Liu, Xiangqian; Yu, Xiang; Chen, Min; Feng, Lu; Wang, Lei

2014-01-01

Legionella pneumophila has been recognized as the major cause of legionellosis since the discovery of the deadly disease. Legionella spp. other than L. pneumophila were later found to be responsible to many non-pneumophila infections. The non-L. pneumophila infections are likely under-detected because of a lack of effective diagnosis. In this report, we have sequenced the 16S-23S rRNA gene internal transcribed spacer (ITS) of 10 Legionella species and subspecies, including L. anisa, L. bozemanii, L. dumoffii, L. fairfieldensis, L. gormanii, L. jordanis, L. maceachernii, L. micdadei, L. pneumophila subspp. fraseri and L. pneumophila subspp. pasculleii, and developed a rapid oligonucleotide microarray detection technique accordingly to identify 12 most common Legionella spp., which consist of 11 pathogenic species of L. anisa, L. bozemanii, L. dumoffii, L. gormanii, L. jordanis, L. longbeachae, L. maceachernii, L. micdadei, and L. pneumophila (including subspp. pneumophila, subspp. fraseri, and subspp. pasculleii) and one non-pathogenic species, L. fairfieldensis. Twenty-nine probes that reproducibly detected multiple Legionella species with high specificity were included in the array. A total of 52 strains, including 30 target pathogens and 22 non-target bacteria, were used to verify the oligonucleotide microarray assay. The sensitivity of the detection was at 1.0 ng with genomic DNA or 13 CFU/100 mL with Legionella cultures. The microarray detected seven samples of air conditioner-condensed water with 100% accuracy, validating the technique as a promising method for applications in basic microbiology, clinical diagnosis, food safety, and epidemiological surveillance. The phylogenetic study based on the ITS has also revealed that the non-pathogenic L. fairfieldensis is the closest to L. pneumophila than the nine other pathogenic Legionella spp.

rrndb: the Ribosomal RNA Operon Copy Number Database

PubMed Central

Klappenbach, Joel A.; Saxman, Paul R.; Cole, James R.; Schmidt, Thomas M.

2001-01-01

The Ribosomal RNA Operon Copy Number Database (rrndb) is an Internet-accessible database containing annotated information on rRNA operon copy number among prokaryotes. Gene redundancy is uncommon in prokaryotic genomes, yet the rRNA genes can vary from one to as many as 15 copies. Despite the widespread use of 16S rRNA gene sequences for identification of prokaryotes, information on the number and sequence of individual rRNA genes in a genome is not readily accessible. In an attempt to understand the evolutionary implications of rRNA operon redundancy, we have created a phylogenetically arranged report on rRNA gene copy number for a diverse collection of prokaryotic microorganisms. Each entry (organism) in the rrndb contains detailed information linked directly to external websites including the Ribosomal Database Project, GenBank, PubMed and several culture collections. Data contained in the rrndb will be valuable to researchers investigating microbial ecology and evolution using 16S rRNA gene sequences. The rrndb web site is directly accessible on the WWW at http://rrndb.cme.msu.edu. PMID:11125085

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

Horizontal Transfer of Segments of the 16S rRNA Genes between Species of the Streptococcus anginosus Group

PubMed Central

Schouls, Leo M.; Schot, Corrie S.; Jacobs, Jan A.

2003-01-01

The nature in variation of the 16S rRNA gene of members of the Streptococcus anginosus group was investigated by hybridization and DNA sequencing. A collection of 708 strains was analyzed by reverse line blot hybridization. This revealed the presence of distinct reaction patterns representing 11 different hybridization groups. The 16S rRNA genes of two strains of each hybridization group were sequenced to near-completion, and the sequence data confirmed the reverse line blot hybridization results. Closer inspection of the sequences revealed mosaic-like structures, strongly suggesting horizontal transfer of segments of the 16S rRNA gene between different species belonging to the Streptococcus anginosus group. Southern blot hybridization further showed that within a single strain all copies of the 16S rRNA gene had the same composition, indicating that the apparent mosaic structures were not PCR-induced artifacts. These findings indicate that the highly conserved rRNA genes are also subject to recombination and that these events may be fixed in the population. Such recombination may lead to the construction of incorrect phylogenetic trees based on the 16S rRNA genes. PMID:14645285

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.

[Differentially expressed genes of cell signal transduction associated with benzene poisoning by cDNA microarray].

PubMed

Wang, Hong; Bi, Yongyi; Tao, Ning; Wang, Chunhong

2005-08-01

To detect the differential expression of cell signal transduction genes associated with benzene poisoning, and to explore the pathogenic mechanisms of blood system damage induced by benzene. Peripheral white blood cell gene expression profile of 7 benzene poisoning patients, including one aplastic anemia, was determined by cDNA microarray. Seven chips from normal workers were served as controls. Cluster analysis of gene expression profile was performed. Among the 4265 target genes, 176 genes associated with cell signal transduction were differentially expressed. 35 up-regulated genes including PTPRC, STAT4, IFITM1 etc were found in at least 6 pieces of microarray; 45 down-regulated genes including ARHB, PPP3CB, CDC37 etc were found in at least 5 pieces of microarray. cDNA microarray technology is an effective technique for screening the differentially expressed genes of cell signal transduction. Disorder in cell signal transduction may play certain role in the pathogenic mechanism of benzene poisoning.

[Phylogenetic analysis of closely related Leuconostoc citreum species based on partial housekeeping genes].

PubMed

Lv, Qiang; Chen, Ming; Xu, Haiyan; Song, Yuqin; Sun, Zhihong; Dan, Tong; Sun, Tiansong

2013-07-04

Using the 16S rRNA, dnaA, murC and pyrG gene sequences, we identified the phylogenetic relationship among closely related Leuconostoc citreum species. Seven Leu. citreum strains originally isolated from sourdough were characterized by PCR methods to amplify the dnaA, murC and pyrG gene sequences, which were determined to assess the suitability as phylogenetic markers. Then, we estimated the genetic distance and constructed the phylogenetic trees including 16S rRNA and above mentioned three housekeeping genes combining with published corresponding sequences. By comparing the phylogenetic trees, the topology of three housekeeping genes trees were consistent with that of 16S rRNA gene. The homology of closely related Leu. citreum species among dnaA, murC, pyrG and 16S rRNA gene sequences were different, ranged from75.5% to 97.2%, 50.2% to 99.7%, 65.0% to 99.8% and 98.5% 100%, respectively. The phylogenetic relationship of three housekeeping genes sequences were highly consistent with the results of 16S rRNA gene sequence, while the genetic distance of these housekeeping genes were extremely high than 16S rRNA gene. Consequently, the dnaA, murC and pyrG gene are suitable for classification and identification closely related Leu. citreum species.

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

PubMed

Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

2014-08-04

Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

Use of Microarray to Analyze Gene Expression Profiles of Acute Effects of Prochloraz on Fathead Minnows Pimephales promelas

EPA Science Inventory

Microarray technology is a powerful tool to investigate the gene expression profiles for thousands of genes simultaneously. In recent years, microarrays have been used to characterize environmental pollutants and identify molecular mode(s) of action of chemicals including endocri...

Phylogenetic comparisons of a coastal bacterioplankton community with its counterparts in open ocean and freshwater systems.

PubMed

Rappé; Vergin; Giovannoni

2000-09-01

In order to extend previous comparisons between coastal marine bacterioplankton communities and their open ocean and freshwater counterparts, here we summarize and provide new data on a clone library of 105 SSU rRNA genes recovered from seawater collected over the western continental shelf of the USA in the Pacific Ocean. Comparisons to previously published data revealed that this coastal bacterioplankton clone library was dominated by SSU rRNA gene phylotypes originally described from surface waters of the open ocean, but also revealed unique SSU rRNA gene lineages of beta Proteobacteria related to those found in clone libraries from freshwater habitats. beta Proteobacteria lineages common to coastal and freshwater samples included members of a clade of obligately methylotrophic bacteria, SSU rRNA genes affiliated with Xylophilus ampelinus, and a clade related to the genus Duganella. In addition, SSU rRNA genes were recovered from such previously recognized marine bacterioplankton SSU rRNA gene clone clusters as the SAR86, SAR11, and SAR116 clusters within the class Proteobacteria, the Roseobacter clade of the alpha subclass of the Proteobacteria, the marine group A/SAR406 cluster, and the marine Actinobacteria clade. Overall, these results support and extend previous observations concerning the global distribution of several marine planktonic prokaryote SSU rRNA gene phylotypes, but also show that coastal bacterioplankton communities contain SSU rRNA gene lineages (and presumably bacterioplankton) shown previously to be prevalent in freshwater habitats.

Principles of gene microarray data analysis.

PubMed

Mocellin, Simone; Rossi, Carlo Riccardo

2007-01-01

The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

Application of Molecular Techniques To Elucidate the Influence of Cellulosic Waste on the Bacterial Community Structure at a Simulated Low-Level-Radioactive-Waste Site▿ †

PubMed Central

Field, Erin K.; D'Imperio, Seth; Miller, Amber R.; VanEngelen, Michael R.; Gerlach, Robin; Lee, Brady D.; Apel, William A.; Peyton, Brent M.

2010-01-01

Low-level-radioactive-waste (low-level-waste) sites, including those at various U.S. Department of Energy sites, frequently contain cellulosic waste in the form of paper towels, cardboard boxes, or wood contaminated with heavy metals and radionuclides such as chromium and uranium. To understand how the soil microbial community is influenced by the presence of cellulosic waste products, multiple soil samples were obtained from a nonradioactive model low-level-waste test pit at the Idaho National Laboratory. Samples were analyzed using 16S rRNA gene clone libraries and 16S rRNA gene microarray (PhyloChip) analyses. Both methods revealed changes in the bacterial community structure with depth. In all samples, the PhyloChip detected significantly more operational taxonomic units, and therefore relative diversity, than the clone libraries. Diversity indices suggest that diversity is lowest in the fill and fill-waste interface (FW) layers and greater in the wood waste and waste-clay interface layers. Principal-coordinate analysis and lineage-specific analysis determined that the Bacteroidetes and Actinobacteria phyla account for most of the significant differences observed between the layers. The decreased diversity in the FW layer and increased members of families containing known cellulose-degrading microorganisms suggest that the FW layer is an enrichment environment for these organisms. These results suggest that the presence of the cellulosic material significantly influences the bacterial community structure in a stratified soil system. PMID:20305022

The repeat organizer, a specialized insulator element within the intergenic spacer of the Xenopus rRNA genes.

PubMed Central

Robinett, C C; O'Connor, A; Dunaway, M

1997-01-01

We have identified a novel activity for the region of the intergenic spacer of the Xenopus laevis rRNA genes that contains the 35- and 100-bp repeats. We devised a new assay for this region by constructing DNA plasmids containing a tandem repeat of rRNA reporter genes that were separated by the 35- and 100-bp repeat region and a rRNA gene enhancer. When the 35- and 100-bp repeat region is present in its normal position and orientation at the 3' end of the rRNA reporter genes, the enhancer activates the adjacent downstream promoter but not the upstream rRNA promoter on the same plasmid. Because this element can restrict the range of an enhancer's activity in the context of tandem genes, we have named it the repeat organizer (RO). The ability to restrict enhancer action is a feature of insulator elements, but unlike previously described insulator elements the RO does not block enhancer action in a simple enhancer-blocking assay. Instead, the activity of the RO requires that it be in its normal position and orientation with respect to the other sequence elements of the rRNA genes. The enhancer-binding transcription factor xUBF also binds to the repetitive sequences of the RO in vitro, but these sequences do not activate transcription in vivo. We propose that the RO is a specialized insulator element that organizes the tandem array of rRNA genes into single-gene expression units by promoting activation of a promoter by its proximal enhancers. PMID:9111359

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.

Drosophila mitochondrial DNA: a novel gene order.

PubMed Central

Clary, D O; Goddard, J M; Martin, S C; Fauron, C M; Wolstenholme, D R

1982-01-01

Part of the replication origin-containing A+T-rich region of the Drosophila yakuba mtDNA molecule and segments on either side of this region have been sequenced, and the genes within them identified. The data confirm that the small and large rRNA genes lie in tandem adjacent to that side of the A+T-rich region which is replicated first, and establish that a tRNAval gene lies between the two rRNA genes and that URF1 follows the large rRNA gene. The data further establish that the genes for tRNAile, tRNAgln, tRNAf-met and URF2 lie in the order given, on the opposite side of the A+T-rich region to the rRNA genes and, except for tRNAgln, are contained in the opposite strand to the rRNA, tRNAval and URF1 genes. This is in contrast to mammalian mtDNAs where all of these genes are located on the side of the replication origin which is replicated last, within the order tRNAphe, small (12S) rRNA, tRNAval, large (16S) rRNA, tRNAleu, URF1, tRNAile, tRNAgln, tRNAf-met and URF2, and, except tRNAgln, are all contained in the same (H) strand. In D. yakuba URF1 and URF2, the triplet AGA appears to specify an amino acid, which is again different from the situation found in mammalian mtDNAs, where AGA is used only as a rare termination codon. PMID:6294611

DEVELOPMENT AND VALIDATION OF A 2,000 GENE MICROARRAY FOR THE FATHEAD MINNOW, PIMEPHALES PROMELAS

EPA Science Inventory

The development of the gene microarray has provided the field of ecotoxicology a new tool to identify modes of action (MOA) of chemicals and chemical mixtures. Herein we describe the development and application of a 2,000 gene oligonucleotide microarray for the fathead minnow (P...

RNA polymerase I transcription in a Brassica interspecific hybrid and its progenitors: Tests of transcription factor involvement in nucleolar dominance.

PubMed Central

Frieman, M; Chen, Z J; Saez-Vasquez, J; Shen, L A; Pikaard, C S

1999-01-01

In interspecific hybrids or allopolyploids, often one parental set of ribosomal RNA genes is transcribed and the other is silent, an epigenetic phenomenon known as nucleolar dominance. Silencing is enforced by cytosine methylation and histone deacetylation, but the initial discrimination mechanism is unknown. One hypothesis is that a species-specific transcription factor is inactivated, thereby silencing one set of rRNA genes. Another is that dominant rRNA genes have higher binding affinities for limiting transcription factors. A third suggests that selective methylation of underdominant rRNA genes blocks transcription factor binding. We tested these hypotheses using Brassica napus (canola), an allotetraploid derived from B. rapa and B. oleracea in which only B. rapa rRNA genes are transcribed. B. oleracea and B. rapa rRNA genes were active when transfected into protoplasts of the other species, which argues against the species-specific transcription factor model. B. oleracea and B. rapa rRNA genes also competed equally for the pol I transcription machinery in vitro and in vivo. Cytosine methylation had no effect on rRNA gene transcription in vitro, which suggests that transcription factor binding was unimpaired. These data are inconsistent with the prevailing models and point to discrimination mechanisms that are likely to act at a chromosomal level. PMID:10224274

Theileria sp. Infections Associated with Bovine Fatalities in the United States Confirmed by Small-Subunit rRNA Gene Analyses of Blood and Tick Samples

PubMed Central

Chae, Joon-seok; Levy, Michael; Hunt, John; Schlater, Jack; Snider, Glen; Waghela, Suryakant D.; Holman, Patricia J.; Wagner, G. Gale

1999-01-01

Theileria sp.-specific small subunit (SSU) rRNA gene amplification confirmed the presence of the organism in cattle and in Amblyomma americanum and Dermacentor variabilis ticks collected from a cattle herd in Missouri. Blood from the index animal had type A and type D Theileria SSU rRNA genes. The type D gene was also found in blood from two cohort cattle and tick tissues. The type A SSU rRNA gene was previously reported from bovine Theileria isolates from Texas and North Carolina; the type D gene was reported from a Texas cow with theileriosis. PMID:10449501

Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

PubMed Central

2012-01-01

Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO). MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA) with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO) correctly identified (p < 0.05) microarray data in which genes annotated to differentially expressed GO terms are upregulated. We found that GSEA + MIMGO was slightly less effective than, or comparable to, GSEA (Pearson), a method that uses Pearson’s correlation as a metric, at detecting true differentially expressed GO terms. However, unlike other methods including GSEA (Pearson), GSEA + MIMGO can comprehensively identify the microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively. PMID:23232071

5S rRNA gene arrangements in protists: a case of nonadaptive evolution.

PubMed

Drouin, Guy; Tsang, Corey

2012-06-01

Given their high copy number and high level of expression, one might expect that both the sequence and organization of eukaryotic ribosomal RNA genes would be conserved during evolution. Although the organization of 18S, 5.8S and 28S ribosomal RNA genes is indeed relatively well conserved, that of 5S rRNA genes is much more variable. Here, we review the different types of 5S rRNA gene arrangements which have been observed in protists. This includes linkages to the other ribosomal RNA genes as well as linkages to ubiquitin, splice-leader, snRNA and tRNA genes. Mapping these linkages to independently derived phylogenies shows that these diverse linkages have repeatedly been gained and lost during evolution. This argues against such linkages being the primitive condition not only in protists but also in other eukaryote species. Because the only characteristic the diverse genes with which 5S rRNA genes are found linked with is that they are tandemly repeated, these arrangements are unlikely to provide any selective advantage. Rather, the observed high variability in 5S rRNA genes arrangements is likely the result of the fact that 5S rRNA genes contain internal promoters, that these genes are often transposed by diverse recombination mechanisms and that these new gene arrangements are rapidly homogenized by unequal crossingovers and/or by gene conversions events in species with short generation times and frequent founder events.

Selective Phylogenetic Analysis Targeted at 16S rRNA Genes of Thermophiles and Hyperthermophiles in Deep-Subsurface Geothermal Environments

PubMed Central

Kimura, Hiroyuki; Sugihara, Maki; Kato, Kenji; Hanada, Satoshi

2006-01-01

Deep-subsurface samples obtained by deep drilling are likely to be contaminated with mesophilic microorganisms in the drilling fluid, and this could affect determination of the community structure of the geothermal microflora using 16S rRNA gene clone library analysis. To eliminate possible contamination by PCR-amplified 16S rRNA genes from mesophiles, a combined thermal denaturation and enzyme digestion method, based on a strong correlation between the G+C content of the 16S rRNA gene and the optimum growth temperatures of most known prokaryotic cultures, was used prior to clone library construction. To validate this technique, hot spring fluid (76°C) and river water (14°C) were used to mimic a deep-subsurface sample contaminated with drilling fluid. After DNA extraction and PCR amplification of the 16S rRNA genes from individual samples separately, the amplified products from river water were observed to be denatured at 82°C and completely digested by exonuclease I (Exo I), while the amplified products from hot spring fluid remained intact after denaturation at 84°C and enzyme digestion with Exo I. DNAs extracted from the two samples were mixed and used as a template for amplification of the 16S rRNA genes. The amplified rRNA genes were denatured at 84°C and digested with Exo I before clone library construction. The results indicated that the 16S rRNA gene sequences from the river water were almost completely eliminated, whereas those from the hot spring fluid remained. PMID:16391020

Microbialite response to an anthropogenic salinity gradient in Great Salt Lake, Utah.

PubMed

Lindsay, M R; Anderson, C; Fox, N; Scofield, G; Allen, J; Anderson, E; Bueter, L; Poudel, S; Sutherland, K; Munson-McGee, J H; Van Nostrand, J D; Zhou, J; Spear, J R; Baxter, B K; Lageson, D R; Boyd, E S

2017-01-01

A railroad causeway across Great Salt Lake, Utah (GSL), has restricted water flow since its construction in 1959, resulting in a more saline North Arm (NA; 24%-31% salinity) and a less saline South Arm (SA; 11%-14% salinity). Here, we characterized microbial carbonates collected from the SA and the NA to evaluate the effect of increased salinity on community composition and abundance and to determine whether the communities present in the NA are still actively precipitating carbonate or if they are remnant features from prior to causeway construction. SSU rRNA gene abundances associated with the NA microbialite were three orders of magnitude lower than those associated with the SA microbialite, indicating that the latter community is more productive. SSU rRNA gene sequencing and functional gene microarray analyses indicated that SA and NA microbialite communities are distinct. In particular, abundant sequences affiliated with photoautotrophic taxa including cyanobacteria and diatoms that may drive carbonate precipitation and thus still actively form microbialites were identified in the SA microbialite; sequences affiliated with photoautotrophic taxa were in low abundance in the NA microbialite. SA and NA microbialites comprise smooth prismatic aragonite crystals. However, the SA microbialite also contained micritic aragonite, which can be formed as a result of biological activity. Collectively, these observations suggest that NA microbialites are likely to be remnant features from prior to causeway construction and indicate a strong decrease in the ability of NA microbialite communities to actively precipitate carbonate minerals. Moreover, the results suggest a role for cyanobacteria and diatoms in carbonate precipitation and microbialite formation in the SA of GSL. © 2016 John Wiley & Sons Ltd.

MALDI-TOF mass spectrometry for quantitative gene expression analysis of acid responses in Staphylococcus aureus.

PubMed

Rode, Tone Mari; Berget, Ingunn; Langsrud, Solveig; Møretrø, Trond; Holck, Askild

2009-07-01

Microorganisms are constantly exposed to new and altered growth conditions, and respond by changing gene expression patterns. Several methods for studying gene expression exist. During the last decade, the analysis of microarrays has been one of the most common approaches applied for large scale gene expression studies. A relatively new method for gene expression analysis is MassARRAY, which combines real competitive-PCR and MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry. In contrast to microarray methods, MassARRAY technology is suitable for analysing a larger number of samples, though for a smaller set of genes. In this study we compare the results from MassARRAY with microarrays on gene expression responses of Staphylococcus aureus exposed to acid stress at pH 4.5. RNA isolated from the same stress experiments was analysed using both the MassARRAY and the microarray methods. The MassARRAY and microarray methods showed good correlation. Both MassARRAY and microarray estimated somewhat lower fold changes compared with quantitative real-time PCR (qRT-PCR). The results confirmed the up-regulation of the urease genes in acidic environments, and also indicated the importance of metal ion regulation. This study shows that the MassARRAY technology is suitable for gene expression analysis in prokaryotes, and has advantages when a set of genes is being analysed for an organism exposed to many different environmental conditions.

The application of DNA microarrays in gene expression analysis.

PubMed

van Hal, N L; Vorst, O; van Houwelingen, A M; Kok, E J; Peijnenburg, A; Aharoni, A; van Tunen, A J; Keijer, J

2000-03-31

DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed. These comprise array manufacturing and design, array hybridisation, scanning, and data handling. Furthermore, it is discussed how DNA microarrays can be applied in the working fields of: safety, functionality and health of food and gene discovery and pathway engineering in plants.

Epigenetic regulation of TTF-I-mediated promoter–terminator interactions of rRNA genes

PubMed Central

Németh, Attila; Guibert, Sylvain; Tiwari, Vijay Kumar; Ohlsson, Rolf; Längst, Gernot

2008-01-01

Ribosomal RNA synthesis is the eukaryotic cell's main transcriptional activity, but little is known about the chromatin domain organization and epigenetics of actively transcribed rRNA genes. Here, we show epigenetic and spatial organization of mouse rRNA genes at the molecular level. TTF-I-binding sites subdivide the rRNA transcription unit into functional chromatin domains and sharply delimit transcription factor occupancy. H2A.Z-containing nucleosomes occupy the spacer promoter next to a newly characterized TTF-I-binding site. The spacer and the promoter proximal TTF-I-binding sites demarcate the enhancer. DNA from both the enhancer and the coding region is hypomethylated in actively transcribed repeats. 3C analysis revealed an interaction between promoter and terminator regions, which brings the beginning and end of active rRNA genes into close contact. Reporter assays show that TTF-I mediates this interaction, thereby linking topology and epigenetic regulation of the rRNA genes. PMID:18354495

Sequence heterogeneity in the two 16S rRNA genes of Phormium yellow leaf phytoplasma.

PubMed Central

Liefting, L W; Andersen, M T; Beever, R E; Gardner, R C; Forster, R L

1996-01-01

Phormium yellow leaf (PYL) phytoplasma causes a lethal disease of the monocotyledon, New Zealand flax (Phormium tenax). The 16S rRNA genes of PYL phytoplasma were amplified from infected flax by PCR and cloned, and the nucleotide sequences were determined. DNA sequencing and Southern hybridization analysis of genomic DNA indicated the presence of two copies of the 16S rRNA gene. The two 16S rRNA genes exhibited sequence heterogeneity in 4 nucleotide positions and could be distinguished by the restriction enzymes BpmI and BsrI. This is the first record in which sequence heterogeneity in the 16S rRNA genes of a phytoplasma has been determined by sequence analysis. A phylogenetic tree based on 16S rRNA gene sequences showed that PYL phytoplasma is most closely related to the stolbur and German grapevine yellows phytoplasmas, which form the stolbur subgroup of the aster yellows group. This phylogenetic position of PYL phytoplasma was supported by 16S/23S spacer region sequence data. PMID:8795200

Prevalence of 16S rRNA methylase genes among β-lactamase-producing Enterobacteriaceae clinical isolates in Saudi Arabia

PubMed Central

Al Sheikh, Yazeed A.; Marie, Mohammed Ali M.; John, James; Krishnappa, Lakshmana Gowda; Dabwab, Khaled Homoud M.

2014-01-01

Background Co production of 16S rRNA methylases gene and β-Lactamase gene among Enterobacteriaceae isolates conferring resistance to both therapeutic options has serious implications for clinicians worldwide. Methods To study co existence of 16S rRNA methylases (armA, rmtA, rmtB, rmtC, rmtD, and npmA) and β-Lactamase (blaTEM-1, blaSHV-12, blaCTX-M-14) genes, we screened all phenotypic positive β-Lactamase producing enterobacteriaceae by polymerase chain reaction (PCR) targeting above genes. A total of 330 enterobacteriaceae strains were collected during study period out of that 218 isolates were identified phenotypically as β-Lactamase producers, which include 50 (22.9%) Escherichia coli; 92 (42.2%) Klebsiella pneumoniae, 44 (20.2%), Citrobactor freundii and 32 (14.7%) Enterobacter spp. Results Among this 218, only 188 isolates harbored the resistant gene for β-Lactamase production. Major β-Lactamase producing isolates were bla TEM-1 type. 122 (56 %) isolates were found to produce any one of the 16S rRNA methylase genes. A total of 116 isolates co produced β-Lactamase and at least one 16S rRNA methylases gene Co production of armA gene was found in 26 isolates with rmtB and in 4 isolates with rmtC. The rmtA and rmtD genes were not detected in any of the tested isolates. Six isolates were positive for a 16S rRNA methylase gene alone. Conclusion β-Lactamase producing isolates appears to coexist with 16S rRNA methylase predominantly armA and rmtB genes in the same isolate. We conclude the major β-Lactamase and 16S rRNA methylases co-producer was K. pneumoniae followed by E. coli. We suggest further work on evaluating other β-lactamases types and novel antibiotic resistance mechanisms among Enterobacteriaceae. PMID:25005152

Studying modification of aminoglycoside antibiotics by resistance-causing enzymes via microarray.

PubMed

Disney, Matthew D

2012-01-01

Widespread bacterial resistance to antibiotics is a significant public health concern. To remain a step ahead of evolving bacteria, new methods to study resistance to antibacterials and to uncover novel antibiotics that evade resistance are urgently needed. Herein, microarray-based methods that have been developed to study aminoglycoside modification by resistance-causing enzymes are reviewed. These arrays can also be used to study the binding of aminoglycoside antibiotics to a mimic of their therapeutic target, the rRNA aminoacyl site (A-site), and how modification by resistance-causing enzymes affects their abilities to bind RNA.

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data.

PubMed

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R; Del Río-Navarro, Blanca E; Mendoza-Vargas, Alfredo; Sánchez, Filiberto; Ochoa-Leyva, Adrian

2017-01-01

In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6-10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.

Strategies for comparing gene expression profiles from different microarray platforms: application to a case-control experiment.

PubMed

Severgnini, Marco; Bicciato, Silvio; Mangano, Eleonora; Scarlatti, Francesca; Mezzelani, Alessandra; Mattioli, Michela; Ghidoni, Riccardo; Peano, Clelia; Bonnal, Raoul; Viti, Federica; Milanesi, Luciano; De Bellis, Gianluca; Battaglia, Cristina

2006-06-01

Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.

Phytoplasma phylogenetics based on analysis of secA and 23S rRNA gene sequences for improved resolution of candidate species of 'Candidatus Phytoplasma'.

PubMed

Hodgetts, Jennifer; Boonham, Neil; Mumford, Rick; Harrison, Nigel; Dickinson, Matthew

2008-08-01

Phytoplasma phylogenetics has focused primarily on sequences of the non-coding 16S rRNA gene and the 16S-23S rRNA intergenic spacer region (16-23S ISR), and primers that enable amplification of these regions from all phytoplasmas by PCR are well established. In this study, primers based on the secA gene have been developed into a semi-nested PCR assay that results in a sequence of the expected size (about 480 bp) from all 34 phytoplasmas examined, including strains representative of 12 16Sr groups. Phylogenetic analysis of secA gene sequences showed similar clustering of phytoplasmas when compared with clusters resolved by similar sequence analyses of a 16-23S ISR-23S rRNA gene contig or of the 16S rRNA gene alone. The main differences between trees were in the branch lengths, which were elongated in the 16-23S ISR-23S rRNA gene tree when compared with the 16S rRNA gene tree and elongated still further in the secA gene tree, despite this being a shorter sequence. The improved resolution in the secA gene-derived phylogenetic tree resulted in the 16SrII group splitting into two distinct clusters, while phytoplasmas associated with coconut lethal yellowing-type diseases split into three distinct groups, thereby supporting past proposals that they represent different candidate species within 'Candidatus Phytoplasma'. The ability to differentiate 16Sr groups and subgroups by virtual RFLP analysis of secA gene sequences suggests that this gene may provide an informative alternative molecular marker for pathogen identification and diagnosis of phytoplasma diseases.

Characterization of a novel Lactobacillus species closely related to Lactobacillus johnsonii using a combination of molecular and comparative genomics methods

PubMed Central

2010-01-01

Background Comparative genomic hybridization (CGH) constitutes a powerful tool for identification and characterization of bacterial strains. In this study we have applied this technique for the characterization of a number of Lactobacillus strains isolated from the intestinal content of rats fed with a diet supplemented with sorbitol. Results Phylogenetic analysis based on 16S rRNA gene, recA, pheS, pyrG and tuf sequences identified five bacterial strains isolated from the intestinal content of rats as belonging to the recently described Lactobacillus taiwanensis species. DNA-DNA hybridization experiments confirmed that these five strains are distinct but closely related to Lactobacillus johnsonii and Lactobacillus gasseri. A whole genome DNA microarray designed for the probiotic L. johnsonii strain NCC533 was used for CGH analysis of L. johnsonii ATCC 33200T, L. johnsonii BL261, L. gasseri ATCC 33323T and L. taiwanensis BL263. In these experiments, the fluorescence ratio distributions obtained with L. taiwanensis and L. gasseri showed characteristic inter-species profiles. The percentage of conserved L. johnsonii NCC533 genes was about 83% in the L. johnsonii strains comparisons and decreased to 51% and 47% for L. taiwanensis and L. gasseri, respectively. These results confirmed the separate status of L. taiwanensis from L. johnsonii at the level of species, and also that L. taiwanensis is closer to L. johnsonii than L. gasseri is to L. johnsonii. Conclusion Conventional taxonomic analyses and microarray-based CGH analysis have been used for the identification and characterization of the newly species L. taiwanensis. The microarray-based CGH technology has been shown as a remarkable tool for the identification and fine discrimination between phylogenetically close species, and additionally provided insight into the adaptation of the strain L. taiwanensis BL263 to its ecological niche. PMID:20849602

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

Comparison of potential diatom 'barcode' genes (the 18S rRNA gene and ITS, COI, rbcL) and their effectiveness in discriminating and determining species taxonomy in the Bacillariophyta.

PubMed

Guo, Liliang; Sui, Zhenghong; Zhang, Shu; Ren, Yuanyuan; Liu, Yuan

2015-04-01

Diatoms form an enormous group of photoautotrophic micro-eukaryotes and play a crucial role in marine ecology. In this study, we evaluated typical genes to determine whether they were effective at different levels of diatom clustering analysis to assess the potential of these regions for barcoding taxa. Our test genes included nuclear rRNA genes (the nuclear small-subunit rRNA gene and the 5.8S rRNA gene+ITS-2), a mitochondrial gene (cytochrome c-oxidase subunit 1, COI), a chloroplast gene [ribulose-1,5-biphosphate carboxylase/oxygenase large subunit (rbcL)] and the universal plastid amplicon (UPA). Calculated genetic divergence was highest for the internal transcribed spacer (ITS; 5.8S+ITS-2) (p-distance of 1.569, 85.84% parsimony-informative sites) and COI (6.084, 82.14%), followed by the 18S rRNA gene (0.139, 57.69%), rbcL (0.120, 42.01%) and UPA (0.050, 14.97%), which indicated that ITS and COI were highly divergent compared with the other tested genes, and that their nucleotide compositions were variable within the whole group of diatoms. Bayesian inference (BI) analysis showed that the phylogenetic trees generated from each gene clustered diatoms at different phylogenetic levels. The 18S rRNA gene was better than the other genes in clustering higher diatom taxa, and both the 18S rRNA gene and rbcL performed well in clustering some lower taxa. The COI region was able to barcode species of some genera within the Bacillariophyceae. ITS was a potential marker for DNA based-taxonomy and DNA barcoding of Thalassiosirales, while species of Cyclotella, Skeletonema and Stephanodiscus gathered in separate clades, and were paraphyletic with those of Thalassiosira. Finally, UPA was too conserved to serve as a diatom barcode. © 2015 IUMS.

Functional Analyses of NSF1 in Wine Yeast Using Interconnected Correlation Clustering and Molecular Analyses

PubMed Central

Bessonov, Kyrylo; Walkey, Christopher J.; Shelp, Barry J.; van Vuuren, Hennie J. J.; Chiu, David; van der Merwe, George

2013-01-01

Analyzing time-course expression data captured in microarray datasets is a complex undertaking as the vast and complex data space is represented by a relatively low number of samples as compared to thousands of available genes. Here, we developed the Interdependent Correlation Clustering (ICC) method to analyze relationships that exist among genes conditioned on the expression of a specific target gene in microarray data. Based on Correlation Clustering, the ICC method analyzes a large set of correlation values related to gene expression profiles extracted from given microarray datasets. ICC can be applied to any microarray dataset and any target gene. We applied this method to microarray data generated from wine fermentations and selected NSF1, which encodes a C2H2 zinc finger-type transcription factor, as the target gene. The validity of the method was verified by accurate identifications of the previously known functional roles of NSF1. In addition, we identified and verified potential new functions for this gene; specifically, NSF1 is a negative regulator for the expression of sulfur metabolism genes, the nuclear localization of Nsf1 protein (Nsf1p) is controlled in a sulfur-dependent manner, and the transcription of NSF1 is regulated by Met4p, an important transcriptional activator of sulfur metabolism genes. The inter-disciplinary approach adopted here highlighted the accuracy and relevancy of the ICC method in mining for novel gene functions using complex microarray datasets with a limited number of samples. PMID:24130853

Ultrafiltration and Microarray for Detection of Microbial Source Tracking Marker and Pathogen Genes in Riverine and Marine Systems

PubMed Central

Li, Xiang; Harwood, Valerie J.; Nayak, Bina

2016-01-01

Pathogen identification and microbial source tracking (MST) to identify sources of fecal pollution improve evaluation of water quality. They contribute to improved assessment of human health risks and remediation of pollution sources. An MST microarray was used to simultaneously detect genes for multiple pathogens and indicators of fecal pollution in freshwater, marine water, sewage-contaminated freshwater and marine water, and treated wastewater. Dead-end ultrafiltration (DEUF) was used to concentrate organisms from water samples, yielding a recovery efficiency of >95% for Escherichia coli and human polyomavirus. Whole-genome amplification (WGA) increased gene copies from ultrafiltered samples and increased the sensitivity of the microarray. Viruses (adenovirus, bocavirus, hepatitis A virus, and human polyomaviruses) were detected in sewage-contaminated samples. Pathogens such as Legionella pneumophila, Shigella flexneri, and Campylobacter fetus were detected along with genes conferring resistance to aminoglycosides, beta-lactams, and tetracycline. Nonmetric dimensional analysis of MST marker genes grouped sewage-spiked freshwater and marine samples with sewage and apart from other fecal sources. The sensitivity (percent true positives) of the microarray probes for gene targets anticipated in sewage was 51 to 57% and was lower than the specificity (percent true negatives; 79 to 81%). A linear relationship between gene copies determined by quantitative PCR and microarray fluorescence was found, indicating the semiquantitative nature of the MST microarray. These results indicate that ultrafiltration coupled with WGA provides sufficient nucleic acids for detection of viruses, bacteria, protozoa, and antibiotic resistance genes by the microarray in applications ranging from beach monitoring to risk assessment. PMID:26729716

Challenges of microarray applications for microbial detection and gene expression profiling in food

USDA-ARS?s Scientific Manuscript database

Microarray technology represents one of the latest advances in molecular biology. The diverse types of microarrays have been applied to clinical and environmental microbiology, microbial ecology, and in human, veterinary, and plant diagnostics. Since multiple genes can be analyzed simultaneously, ...

PhyloChip™ microarray comparison of sampling methods used for coral microbial ecology

USGS Publications Warehouse

Kellogg, Christina A.; Piceno, Yvette M.; Tom, Lauren M.; DeSantis, Todd Z.; Zawada, David G.; Andersen, Gary L.

2012-01-01

Interest in coral microbial ecology has been increasing steadily over the last decade, yet standardized methods of sample collection still have not been defined. Two methods were compared for their ability to sample coral-associated microbial communities: tissue punches and foam swabs, the latter being less invasive and preferred by reef managers. Four colonies of star coral, Montastraea annularis, were sampled in the Dry Tortugas National Park (two healthy and two with white plague disease). The PhyloChip™ G3 microarray was used to assess microbial community structure of amplified 16S rRNA gene sequences. Samples clustered based on methodology rather than coral colony. Punch samples from healthy and diseased corals were distinct. All swab samples clustered closely together with the seawater control and did not group according to the health state of the corals. Although more microbial taxa were detected by the swab method, there is a much larger overlap between the water control and swab samples than punch samples, suggesting some of the additional diversity is due to contamination from water absorbed by the swab. While swabs are useful for noninvasive studies of the coral surface mucus layer, these results show that they are not optimal for studies of coral disease.

PhyloChip™ microarray comparison of sampling methods used for coral microbial ecology.

PubMed

Kellogg, Christina A; Piceno, Yvette M; Tom, Lauren M; DeSantis, Todd Z; Zawada, David G; Andersen, Gary L

2012-01-01

Interest in coral microbial ecology has been increasing steadily over the last decade, yet standardized methods of sample collection still have not been defined. Two methods were compared for their ability to sample coral-associated microbial communities: tissue punches and foam swabs, the latter being less invasive and preferred by reef managers. Four colonies of star coral, Montastraea annularis, were sampled in the Dry Tortugas National Park (two healthy and two with white plague disease). The PhyloChip™ G3 microarray was used to assess microbial community structure of amplified 16S rRNA gene sequences. Samples clustered based on methodology rather than coral colony. Punch samples from healthy and diseased corals were distinct. All swab samples clustered closely together with the seawater control and did not group according to the health state of the corals. Although more microbial taxa were detected by the swab method, there is a much larger overlap between the water control and swab samples than punch samples, suggesting some of the additional diversity is due to contamination from water absorbed by the swab. While swabs are useful for noninvasive studies of the coral surface mucus layer, these results show that they are not optimal for studies of coral disease. Published by Elsevier B.V.

Changes in the Composition of Drinking Water Bacterial Clone Libraries Introduced by Using Two Different 16S rRna Gene PCR Primers

EPA Science Inventory

Sequence analysis of 16S rRNA gene clone libraries is a popular tool used to describe the composition of natural microbial communities. Commonly, clone libraries are developed by direct cloning of 16S rRNA gene PCR products. Different primers are often employed in the initial amp...

Changes in the Composition of Drinking Water Bacterial Clone Libraries Introduced by Using Two Different 16S rRNA Gene PCR Primers

EPA Science Inventory

Sequence analysis of 16S rRNA gene clone libraries is a popular tool used to describe the composition of natural microbial communities. Commonly, clone libraries are developed by direct cloning of 16S rRNA gene PCR products. Different primers are often employed in the initial amp...

Recognition of chimeric small-subunit ribosomal DNAs composed of genes from uncultivated microorganisms

NASA Technical Reports Server (NTRS)

Kopczynski, E. D.; Bateson, M. M.; Ward, D. M.

1994-01-01

When PCR was used to recover small-subunit (SSU) rRNA genes from a hot spring cyanobacterial mat community, chimeric SSU rRNA sequences which exhibited little or no secondary structural abnormality were recovered. They were revealed as chimeras of SSU rRNA genes of uncultivated species through separate phylogenetic analysis of short sequence domains.

Morphometric and molecular data on two mitochondrial genes of a newly discovered chimaeran fish ( Hydrolagus melanophasma, Chondrichthyes)

NASA Astrophysics Data System (ADS)

De La Cruz-Agüero, José; García-Rodríguez, Francisco Javier; Cota-Gómez, Víctor Manuel; Melo-Barrera, Felipe Neri; González-Armas, Rogelio

2012-06-01

Fresh and preserved (type material) specimens of the black ghost chimaera Hydrolagus melanophasma were compared for morphometric characteristics. A molecular comparison was also performed on two mitochondrial gene sequences (12S rRNA and 16S rRNA gene sequences). While significant differences in measurements were found, the differences were not attributable to sexual dimorphism or the quality of the specimens, but to the sample size and the type of statistical tests. The result of the genetic characterization showed that 12S rRNA and 16S rRNA genes represented robust molecular markers that characterized the species.

Gene response profiles for Daphnia pulex exposed to the environmental stressor cadmium reveals novel crustacean metallothioneins.

PubMed

Shaw, Joseph R; Colbourne, John K; Davey, Jennifer C; Glaholt, Stephen P; Hampton, Thomas H; Chen, Celia Y; Folt, Carol L; Hamilton, Joshua W

2007-12-21

Genomic research tools such as microarrays are proving to be important resources to study the complex regulation of genes that respond to environmental perturbations. A first generation cDNA microarray was developed for the environmental indicator species Daphnia pulex, to identify genes whose regulation is modulated following exposure to the metal stressor cadmium. Our experiments revealed interesting changes in gene transcription that suggest their biological roles and their potentially toxicological features in responding to this important environmental contaminant. Our microarray identified genes reported in the literature to be regulated in response to cadmium exposure, suggested functional attributes for genes that share no sequence similarity to proteins in the public databases, and pointed to genes that are likely members of expanded gene families in the Daphnia genome. Genes identified on the microarray also were associated with cadmium induced phenotypes and population-level outcomes that we experimentally determined. A subset of genes regulated in response to cadmium exposure was independently validated using quantitative-realtime (Q-RT)-PCR. These microarray studies led to the discovery of three genes coding for the metal detoxication protein metallothionein (MT). The gene structures and predicted translated sequences of D. pulex MTs clearly place them in this gene family. Yet, they share little homology with previously characterized MTs. The genomic information obtained from this study represents an important first step in characterizing microarray patterns that may be diagnostic to specific environmental contaminants and give insights into their toxicological mechanisms, while also providing a practical tool for evolutionary, ecological, and toxicological functional gene discovery studies. Advances in Daphnia genomics will enable the further development of this species as a model organism for the environmental sciences.

Gene response profiles for Daphnia pulex exposed to the environmental stressor cadmium reveals novel crustacean metallothioneins

PubMed Central

Shaw, Joseph R; Colbourne, John K; Davey, Jennifer C; Glaholt, Stephen P; Hampton, Thomas H; Chen, Celia Y; Folt, Carol L; Hamilton, Joshua W

2007-01-01

Background Genomic research tools such as microarrays are proving to be important resources to study the complex regulation of genes that respond to environmental perturbations. A first generation cDNA microarray was developed for the environmental indicator species Daphnia pulex, to identify genes whose regulation is modulated following exposure to the metal stressor cadmium. Our experiments revealed interesting changes in gene transcription that suggest their biological roles and their potentially toxicological features in responding to this important environmental contaminant. Results Our microarray identified genes reported in the literature to be regulated in response to cadmium exposure, suggested functional attributes for genes that share no sequence similarity to proteins in the public databases, and pointed to genes that are likely members of expanded gene families in the Daphnia genome. Genes identified on the microarray also were associated with cadmium induced phenotypes and population-level outcomes that we experimentally determined. A subset of genes regulated in response to cadmium exposure was independently validated using quantitative-realtime (Q-RT)-PCR. These microarray studies led to the discovery of three genes coding for the metal detoxication protein metallothionein (MT). The gene structures and predicted translated sequences of D. pulex MTs clearly place them in this gene family. Yet, they share little homology with previously characterized MTs. Conclusion The genomic information obtained from this study represents an important first step in characterizing microarray patterns that may be diagnostic to specific environmental contaminants and give insights into their toxicological mechanisms, while also providing a practical tool for evolutionary, ecological, and toxicological functional gene discovery studies. Advances in Daphnia genomics will enable the further development of this species as a model organism for the environmental sciences. PMID:18154678

The use of open source bioinformatics tools to dissect transcriptomic data.

PubMed

Nitsche, Benjamin M; Ram, Arthur F J; Meyer, Vera

2012-01-01

Microarrays are a valuable technology to study fungal physiology on a transcriptomic level. Various microarray platforms are available comprising both single and two channel arrays. Despite different technologies, preprocessing of microarray data generally includes quality control, background correction, normalization, and summarization of probe level data. Subsequently, depending on the experimental design, diverse statistical analysis can be performed, including the identification of differentially expressed genes and the construction of gene coexpression networks.We describe how Bioconductor, a collection of open source and open development packages for the statistical programming language R, can be used for dissecting microarray data. We provide fundamental details that facilitate the process of getting started with R and Bioconductor. Using two publicly available microarray datasets from Aspergillus niger, we give detailed protocols on how to identify differentially expressed genes and how to construct gene coexpression networks.

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data

PubMed Central

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R.; del Río-Navarro, Blanca E.; Mendoza-Vargas, Alfredo; Sánchez, Filiberto

2017-01-01

Background In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. Methods We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6–10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). Results From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Discussion Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments. PMID:29230367

Comprehensive Census of Bacteria in Clean Rooms by Using DNA Microarray and Cloning Methods▿ †

PubMed Central

La Duc, Myron T.; Osman, Shariff; Vaishampayan, Parag; Piceno, Yvette; Andersen, Gary; Spry, J. A.; Venkateswaran, Kasthuri

2009-01-01

A census of clean room surface-associated bacterial populations was derived from the results of both the cloning and sequencing of 16S rRNA genes and DNA microarray (PhyloChip) analyses. Samples from the Lockheed Martin Aeronautics Multiple Testing Facility (LMA-MTF), the Kennedy Space Center Payload Hazard and Servicing Facility (KSC-PHSF), and the Jet Propulsion Laboratory Spacecraft Assembly Facility (JPL-SAF) clean rooms were collected during the various assembly phases of the Phoenix and Mars Science Laboratory (MSL) spacecraft. Clone library-derived analyses detected a larger bacterial diversity prior to the arrival of spacecraft hardware in these clean room facilities. PhyloChip results were in agreement with this trend but also unveiled the presence of anywhere from 9- to 70-fold more bacterial taxa than cloning approaches. Among the facilities sampled, the JPL-SAF (MSL mission) housed a significantly less diverse bacterial population than either the LMA-MTF or KSC-PHSF (Phoenix mission). Bacterial taxa known to thrive in arid conditions were frequently detected in MSL-associated JPL-SAF samples, whereas proteobacterial lineages dominated Phoenix-associated KSC-PHSF samples. Comprehensive bacterial censuses, such as that reported here, will help space-faring nations preemptively identify contaminant biomatter that may compromise extraterrestrial life detection experiments. The robust nature and high sensitivity of DNA microarray technologies should prove beneficial to a wide range of scientific, electronic, homeland security, medical, and pharmaceutical applications and to any other ventures with a vested interest in monitoring and controlling contamination in exceptionally clean environments. PMID:19700540

Comprehensive census of bacteria in clean rooms by using DNA microarray and cloning methods.

PubMed

La Duc, Myron T; Osman, Shariff; Vaishampayan, Parag; Piceno, Yvette; Andersen, Gary; Spry, J A; Venkateswaran, Kasthuri

2009-10-01

A census of clean room surface-associated bacterial populations was derived from the results of both the cloning and sequencing of 16S rRNA genes and DNA microarray (PhyloChip) analyses. Samples from the Lockheed Martin Aeronautics Multiple Testing Facility (LMA-MTF), the Kennedy Space Center Payload Hazard and Servicing Facility (KSC-PHSF), and the Jet Propulsion Laboratory Spacecraft Assembly Facility (JPL-SAF) clean rooms were collected during the various assembly phases of the Phoenix and Mars Science Laboratory (MSL) spacecraft. Clone library-derived analyses detected a larger bacterial diversity prior to the arrival of spacecraft hardware in these clean room facilities. PhyloChip results were in agreement with this trend but also unveiled the presence of anywhere from 9- to 70-fold more bacterial taxa than cloning approaches. Among the facilities sampled, the JPL-SAF (MSL mission) housed a significantly less diverse bacterial population than either the LMA-MTF or KSC-PHSF (Phoenix mission). Bacterial taxa known to thrive in arid conditions were frequently detected in MSL-associated JPL-SAF samples, whereas proteobacterial lineages dominated Phoenix-associated KSC-PHSF samples. Comprehensive bacterial censuses, such as that reported here, will help space-faring nations preemptively identify contaminant biomatter that may compromise extraterrestrial life detection experiments. The robust nature and high sensitivity of DNA microarray technologies should prove beneficial to a wide range of scientific, electronic, homeland security, medical, and pharmaceutical applications and to any other ventures with a vested interest in monitoring and controlling contamination in exceptionally clean environments.

Variable Copy Number, Intra-Genomic Heterogeneities and Lateral Transfers of the 16S rRNA Gene in Pseudomonas

PubMed Central

Bodilis, Josselin; Nsigue-Meilo, Sandrine; Besaury, Ludovic; Quillet, Laurent

2012-01-01

Even though the 16S rRNA gene is the most commonly used taxonomic marker in microbial ecology, its poor resolution is still not fully understood at the intra-genus level. In this work, the number of rRNA gene operons, intra-genomic heterogeneities and lateral transfers were investigated at a fine-scale resolution, throughout the Pseudomonas genus. In addition to nineteen sequenced Pseudomonas strains, we determined the 16S rRNA copy number in four other Pseudomonas strains by Southern hybridization and Pulsed-Field Gel Electrophoresis, and studied the intra-genomic heterogeneities by Denaturing Gradient Gel Electrophoresis and sequencing. Although the variable copy number (from four to seven) seems to be correlated with the evolutionary distance, some close strains in the P. fluorescens lineage showed a different number of 16S rRNA genes, whereas all the strains in the P. aeruginosa lineage displayed the same number of genes (four copies). Further study of the intra-genomic heterogeneities revealed that most of the Pseudomonas strains (15 out of 19 strains) had at least two different 16S rRNA alleles. A great difference (5 or 19 nucleotides, essentially grouped near the V1 hypervariable region) was observed only in two sequenced strains. In one of our strains studied (MFY30 strain), we found a difference of 12 nucleotides (grouped in the V3 hypervariable region) between copies of the 16S rRNA gene. Finally, occurrence of partial lateral transfers of the 16S rRNA gene was further investigated in 1803 full-length sequences of Pseudomonas available in the databases. Remarkably, we found that the two most variable regions (the V1 and V3 hypervariable regions) had probably been laterally transferred from another evolutionary distant Pseudomonas strain for at least 48.3 and 41.6% of the 16S rRNA sequences, respectively. In conclusion, we strongly recommend removing these regions of the 16S rRNA gene during the intra-genus diversity studies. PMID:22545126

Conserved Curvature of RNA Polymerase I Core Promoter Beyond rRNA Genes: The Case of the Tritryps

PubMed Central

Smircich, Pablo; Duhagon, María Ana; Garat, Beatriz

2015-01-01

In trypanosomatids, the RNA polymerase I (RNAPI)-dependent promoters controlling the ribosomal RNA (rRNA) genes have been well identified. Although the RNAPI transcription machinery recognizes the DNA conformation instead of the DNA sequence of promoters, no conformational study has been reported for these promoters. Here we present the in silico analysis of the intrinsic DNA curvature of the rRNA gene core promoters in Trypanosoma brucei, Trypanosoma cruzi, and Leishmania major. We found that, in spite of the absence of sequence conservation, these promoters hold conformational properties similar to other eukaryotic rRNA promoters. Our results also indicated that the intrinsic DNA curvature pattern is conserved within the Leishmania genus and also among strains of T. cruzi and T. brucei. Furthermore, we analyzed the impact of point mutations on the intrinsic curvature and their impact on the promoter activity. Furthermore, we found that the core promoters of protein-coding genes transcribed by RNAPI in T. brucei show the same conserved conformational characteristics. Overall, our results indicate that DNA intrinsic curvature of the rRNA gene core promoters is conserved in these ancient eukaryotes and such conserved curvature might be a requirement of RNAPI machinery for transcription of not only rRNA genes but also protein-coding genes. PMID:26718450

Selective progressive response of soil microbial community to wild oat roots.

PubMed

DeAngelis, Kristen M; Brodie, Eoin L; DeSantis, Todd Z; Andersen, Gary L; Lindow, Steven E; Firestone, Mary K

2009-02-01

Roots moving through soil induce physical and chemical changes that differentiate rhizosphere from bulk soil, and the effects of these changes on soil microorganisms have long been a topic of interest. The use of a high-density 16S rRNA microarray (PhyloChip) for bacterial and archaeal community analysis has allowed definition of the populations that respond to the root within the complex grassland soil community; this research accompanies compositional changes reported earlier, including increases in chitinase- and protease-specific activity, cell numbers and quorum sensing signal. PhyloChip results showed a significant change compared with bulk soil in relative abundance for 7% of the total rhizosphere microbial community (147 of 1917 taxa); the 7% response value was confirmed by16S rRNA terminal restriction fragment length polymorphism analysis. This PhyloChip-defined dynamic subset was comprised of taxa in 17 of the 44 phyla detected in all soil samples. Expected rhizosphere-competent phyla, such as Proteobacteria and Firmicutes, were well represented, as were less-well-documented rhizosphere colonizers including Actinobacteria, Verrucomicrobia and Nitrospira. Richness of Bacteroidetes and Actinobacteria decreased in soil near the root tip compared with bulk soil, but then increased in older root zones. Quantitative PCR revealed rhizosphere abundance of beta-Proteobacteria and Actinobacteria at about 10(8) copies of 16S rRNA genes per g soil, with Nitrospira having about 10(5) copies per g soil. This report demonstrates that changes in a relatively small subset of the soil microbial community are sufficient to produce substantial changes in functions observed earlier in progressively more mature rhizosphere zones.

Hybrid genetic algorithm-neural network: feature extraction for unpreprocessed microarray data.

PubMed

Tong, Dong Ling; Schierz, Amanda C

2011-09-01

Suitable techniques for microarray analysis have been widely researched, particularly for the study of marker genes expressed to a specific type of cancer. Most of the machine learning methods that have been applied to significant gene selection focus on the classification ability rather than the selection ability of the method. These methods also require the microarray data to be preprocessed before analysis takes place. The objective of this study is to develop a hybrid genetic algorithm-neural network (GANN) model that emphasises feature selection and can operate on unpreprocessed microarray data. The GANN is a hybrid model where the fitness value of the genetic algorithm (GA) is based upon the number of samples correctly labelled by a standard feedforward artificial neural network (ANN). The model is evaluated by using two benchmark microarray datasets with different array platforms and differing number of classes (a 2-class oligonucleotide microarray data for acute leukaemia and a 4-class complementary DNA (cDNA) microarray dataset for SRBCTs (small round blue cell tumours)). The underlying concept of the GANN algorithm is to select highly informative genes by co-evolving both the GA fitness function and the ANN weights at the same time. The novel GANN selected approximately 50% of the same genes as the original studies. This may indicate that these common genes are more biologically significant than other genes in the datasets. The remaining 50% of the significant genes identified were used to build predictive models and for both datasets, the models based on the set of genes extracted by the GANN method produced more accurate results. The results also suggest that the GANN method not only can detect genes that are exclusively associated with a single cancer type but can also explore the genes that are differentially expressed in multiple cancer types. The results show that the GANN model has successfully extracted statistically significant genes from the unpreprocessed microarray data as well as extracting known biologically significant genes. We also show that assessing the biological significance of genes based on classification accuracy may be misleading and though the GANN's set of extra genes prove to be more statistically significant than those selected by other methods, a biological assessment of these genes is highly recommended to confirm their functionality. Copyright © 2011 Elsevier B.V. All rights reserved.

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

EPA Science Inventory

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, ...

Rearing Water Treatment Induces Microbial Selection Influencing the Microbiota and Pathogen Associated Transcripts of Cod (Gadus morhua) Larvae.

PubMed

Vestrum, Ragnhild I; Attramadal, Kari J K; Winge, Per; Li, Keshuai; Olsen, Yngvar; Bones, Atle M; Vadstein, Olav; Bakke, Ingrid

2018-01-01

We have previously shown that K-selection and microbial stability in the rearing water increases survival and growth of Atlantic cod ( Gadus morhua ) larvae, and that recirculating aquaculture systems (RAS) are compatible with this. Here, we have assessed how water treatment influenced the larval microbiota and host responses at the gene expression level. Cod larvae were reared with two different rearing water systems: a RAS and a flow-through system (FTS). The water microbiota was examined using a 16S rDNA PCR/DGGE strategy. RNA extracted from larvae at 8, 13, and 17 days post hatching was used for microbiota and microarray gene expression analysis. Bacterial cDNA was synthesized and used for 16S rRNA amplicon 454 pyrosequencing of larval microbiota. Both water and larval microbiota differed significantly between the systems, and the larval microbiota appeared to become more dissimilar between systems with time. In total 4 phyla were identified for all larvae: Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. The most profound difference in larval microbiota was a high abundance of Arcobacter (Epsilonproteobacteria) in FTS larvae (34 ± 9% of total reads). Arcobacter includes several species that are known pathogens for humans and animals. Cod larval transcriptome responses were investigated using an oligonucleotide gene expression microarray covering approximately 24,000 genes. Interestingly, FTS larvae transcriptional profiles revealed an overrepresentation of upregulated transcripts associated with responses to pathogens and infections, such as c1ql3-like , pglyrp-2-like and zg16, compared to RAS larvae. In conclusion, distinct water treatment systems induced differences in the larval microbiota. FTS larvae showed up-regulation of transcripts associated with responses to microbial stress. These results are consistent with the hypothesis that RAS promotes K-selection and microbial stability by maintaining a microbial load close to the carrying capacity of the system, and ensuring long retention times for both bacteria and water in the system.

Metagenomic and metabolic profiling of nonlithifying and lithifying stromatolitic mats of Highborne Cay, The Bahamas.

PubMed

Khodadad, Christina L M; Foster, Jamie S

2012-01-01

Stromatolites are laminated carbonate build-ups formed by the metabolic activity of microbial mats and represent one of the oldest known ecosystems on Earth. In this study, we examined a living stromatolite located within the Exuma Sound, The Bahamas and profiled the metagenome and metabolic potential underlying these complex microbial communities. The metagenomes of the two dominant stromatolitic mat types, a nonlithifying (Type 1) and lithifying (Type 3) microbial mat, were partially sequenced and compared. This deep-sequencing approach was complemented by profiling the substrate utilization patterns of the mats using metabolic microarrays. Taxonomic assessment of the protein-encoding genes confirmed previous SSU rRNA analyses that bacteria dominate the metagenome of both mat types. Eukaryotes comprised less than 13% of the metagenomes and were rich in sequences associated with nematodes and heterotrophic protists. Comparative genomic analyses of the functional genes revealed extensive similarities in most of the subsystems between the nonlithifying and lithifying mat types. The one exception was an increase in the relative abundance of certain genes associated with carbohydrate metabolism in the lithifying Type 3 mats. Specifically, genes associated with the degradation of carbohydrates commonly found in exopolymeric substances, such as hexoses, deoxy- and acidic sugars were found. The genetic differences in carbohydrate metabolisms between the two mat types were confirmed using metabolic microarrays. Lithifying mats had a significant increase in diversity and utilization of carbon, nitrogen, phosphorus and sulfur substrates. The two stromatolitic mat types retained similar microbial communities, functional diversity and many genetic components within their metagenomes. However, there were major differences detected in the activity and genetic pathways of organic carbon utilization. These differences provide a strong link between the metagenome and the physiology of the mats, as well as new insights into the biological processes associated with carbonate precipitation in modern marine stromatolites.

Rearing Water Treatment Induces Microbial Selection Influencing the Microbiota and Pathogen Associated Transcripts of Cod (Gadus morhua) Larvae

PubMed Central

Vestrum, Ragnhild I.; Attramadal, Kari J. K.; Winge, Per; Li, Keshuai; Olsen, Yngvar; Bones, Atle M.; Vadstein, Olav; Bakke, Ingrid

2018-01-01

We have previously shown that K-selection and microbial stability in the rearing water increases survival and growth of Atlantic cod (Gadus morhua) larvae, and that recirculating aquaculture systems (RAS) are compatible with this. Here, we have assessed how water treatment influenced the larval microbiota and host responses at the gene expression level. Cod larvae were reared with two different rearing water systems: a RAS and a flow-through system (FTS). The water microbiota was examined using a 16S rDNA PCR/DGGE strategy. RNA extracted from larvae at 8, 13, and 17 days post hatching was used for microbiota and microarray gene expression analysis. Bacterial cDNA was synthesized and used for 16S rRNA amplicon 454 pyrosequencing of larval microbiota. Both water and larval microbiota differed significantly between the systems, and the larval microbiota appeared to become more dissimilar between systems with time. In total 4 phyla were identified for all larvae: Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. The most profound difference in larval microbiota was a high abundance of Arcobacter (Epsilonproteobacteria) in FTS larvae (34 ± 9% of total reads). Arcobacter includes several species that are known pathogens for humans and animals. Cod larval transcriptome responses were investigated using an oligonucleotide gene expression microarray covering approximately 24,000 genes. Interestingly, FTS larvae transcriptional profiles revealed an overrepresentation of upregulated transcripts associated with responses to pathogens and infections, such as c1ql3-like, pglyrp-2-like and zg16, compared to RAS larvae. In conclusion, distinct water treatment systems induced differences in the larval microbiota. FTS larvae showed up-regulation of transcripts associated with responses to microbial stress. These results are consistent with the hypothesis that RAS promotes K-selection and microbial stability by maintaining a microbial load close to the carrying capacity of the system, and ensuring long retention times for both bacteria and water in the system. PMID:29765364

Conditional Inactivation of Upstream Binding Factor Reveals Its Epigenetic Functions and the Existence of a Somatic Nucleolar Precursor Body

PubMed Central

Hamdane, Nourdine; Stefanovsky, Victor Y.; Tremblay, Michel G.; Németh, Attila; Paquet, Eric; Lessard, Frédéric; Sanij, Elaine; Hannan, Ross; Moss, Tom

2014-01-01

Upstream Binding Factor (UBF) is a unique multi-HMGB-box protein first identified as a co-factor in RNA polymerase I (RPI/PolI) transcription. However, its poor DNA sequence selectivity and its ability to generate nucleosome-like nucleoprotein complexes suggest a more generalized role in chromatin structure. We previously showed that extensive depletion of UBF reduced the number of actively transcribed ribosomal RNA (rRNA) genes, but had little effect on rRNA synthesis rates or cell proliferation, leaving open the question of its requirement for RPI transcription. Using gene deletion in mouse, we now show that UBF is essential for embryo development beyond morula. Conditional deletion in cell cultures reveals that UBF is also essential for transcription of the rRNA genes and that it defines the active chromatin conformation of both gene and enhancer sequences. Loss of UBF prevents formation of the SL1/TIF1B pre-initiation complex and recruitment of the RPI-Rrn3/TIF1A complex. It is also accompanied by recruitment of H3K9me3, canonical histone H1 and HP1α, but not by de novo DNA methylation. Further, genes retain penta-acetyl H4 and H2A.Z, suggesting that even in the absence of UBF the rRNA genes can maintain a potentially active state. In contrast to canonical histone H1, binding of H1.4 is dependent on UBF, strongly suggesting that it plays a positive role in gene activity. Unexpectedly, arrest of rRNA synthesis does not suppress transcription of the 5S, tRNA or snRNA genes, nor expression of the several hundred mRNA genes implicated in ribosome biogenesis. Thus, rRNA gene activity does not coordinate global gene expression for ribosome biogenesis. Loss of UBF also unexpectedly induced the formation in cells of a large sub-nuclear structure resembling the nucleolar precursor body (NPB) of oocytes and early embryos. These somatic NPBs contain rRNA synthesis and processing factors but do not associate with the rRNA gene loci (NORs). PMID:25121932

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.

Phylogenetic relatedness determined between antibiotic resistance and 16S rRNA genes in actinobacteria.

PubMed

Sagova-Mareckova, Marketa; Ulanova, Dana; Sanderova, Petra; Omelka, Marek; Kamenik, Zdenek; Olsovska, Jana; Kopecky, Jan

2015-04-01

Distribution and evolutionary history of resistance genes in environmental actinobacteria provide information on intensity of antibiosis and evolution of specific secondary metabolic pathways at a given site. To this day, actinobacteria producing biologically active compounds were isolated mostly from soil but only a limited range of soil environments were commonly sampled. Consequently, soil remains an unexplored environment in search for novel producers and related evolutionary questions. Ninety actinobacteria strains isolated at contrasting soil sites were characterized phylogenetically by 16S rRNA gene, for presence of erm and ABC transporter resistance genes and antibiotic production. An analogous analysis was performed in silico with 246 and 31 strains from Integrated Microbial Genomes (JGI_IMG) database selected by the presence of ABC transporter genes and erm genes, respectively. In the isolates, distances of erm gene sequences were significantly correlated to phylogenetic distances based on 16S rRNA genes, while ABC transporter gene distances were not. The phylogenetic distance of isolates was significantly correlated to soil pH and organic matter content of isolation sites. In the analysis of JGI_IMG datasets the correlation between phylogeny of resistance genes and the strain phylogeny based on 16S rRNA genes or five housekeeping genes was observed for both the erm genes and ABC transporter genes in both actinobacteria and streptomycetes. However, in the analysis of sequences from genomes where both resistance genes occurred together the correlation was observed for both ABC transporter and erm genes in actinobacteria but in streptomycetes only in the erm gene. The type of erm resistance gene sequences was influenced by linkage to 16S rRNA gene sequences and site characteristics. The phylogeny of ABC transporter gene was correlated to 16S rRNA genes mainly above the genus level. The results support the concept of new specific secondary metabolite scaffolds occurring more likely in taxonomically distant producers but suggest that the antibiotic selection of gene pools is also influenced by site conditions.

Anaplasma phagocytophilum in questing Ixodes ricinus ticks: comparison of prevalences and partial 16S rRNA gene variants in urban, pasture, and natural habitats.

PubMed

Overzier, Evelyn; Pfister, Kurt; Thiel, Claudia; Herb, Ingrid; Mahling, Monia; Silaghi, Cornelia

2013-03-01

Urban, natural, and pasture areas were investigated for prevalences and 16S rRNA gene variants of Anaplasma phagocytophilum in questing Ixodes ricinus ticks. The prevalences differed significantly between habitat types, and year-to-year variations in prevalence and habitat-dependent occurrence of 16S rRNA gene variants were detected.

Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

USDA-ARS?s Scientific Manuscript database

The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

Microarrays Made Simple: "DNA Chips" Paper Activity

ERIC Educational Resources Information Center

Barnard, Betsy

2006-01-01

DNA microarray technology is revolutionizing biological science. DNA microarrays (also called DNA chips) allow simultaneous screening of many genes for changes in expression between different cells. Now researchers can obtain information about genes in days or weeks that used to take months or years. The paper activity described in this article…

MICROARRAY QUALITY CONTROL PROJECT: A COMPREHENSIVE GENE EXPRESSION TECHNOLOGY SURVEY DEMONSTRATES MEASURABLE CONSISTENCY AND CONCORDANT RESULTS BETWEEN PLATFORMS

EPA Science Inventory

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, h...

Structure of the human gastric bacterial community in relation to Helicobacter pylori status.

PubMed

Maldonado-Contreras, Ana; Goldfarb, Kate C; Godoy-Vitorino, Filipa; Karaoz, Ulas; Contreras, Mónica; Blaser, Martin J; Brodie, Eoin L; Dominguez-Bello, Maria G

2011-04-01

The human stomach is naturally colonized by Helicobacter pylori, which, when present, dominates the gastric bacterial community. In this study, we aimed to characterize the structure of the bacterial community in the stomach of patients of differing H. pylori status. We used a high-density 16S rRNA gene microarray (PhyloChip, Affymetrix, Inc.) to hybridize 16S rRNA gene amplicons from gastric biopsy DNA of 10 rural Amerindian patients from Amazonas, Venezuela, and of two immigrants to the United States (from South Asia and Africa, respectively). H. pylori status was determined by PCR amplification of H. pylori glmM from gastric biopsy samples. Of the 12 patients, 8 (6 of the 10 Amerindians and the 2 non-Amerindians) were H. pylori glmM positive. Regardless of H. pylori status, the PhyloChip detected Helicobacteriaceae DNA in all patients, although with lower relative abundance in patients who were glmM negative. The G2-chip taxonomy analysis of PhyloChip data indicated the presence of 44 bacterial phyla (of which 16 are unclassified by the Taxonomic Outline of the Bacteria and Archaea taxonomy) in a highly uneven community dominated by only four phyla: Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. Positive H. pylori status was associated with increased relative abundance of non-Helicobacter bacteria from the Proteobacteria, Spirochetes and Acidobacteria, and with decreased abundance of Actinobacteria, Bacteroidetes and Firmicutes. The PhyloChip detected richness of low abundance phyla, and showed marked differences in the structure of the gastric bacterial community according to H. pylori status.

Comparative analyses of the bacterial microbiota of the human nostril and oropharynx.

PubMed

Lemon, Katherine P; Klepac-Ceraj, Vanja; Schiffer, Hilary K; Brodie, Eoin L; Lynch, Susan V; Kolter, Roberto

2010-06-22

The nose and throat are important sites of pathogen colonization, yet the microbiota of both is relatively unexplored by culture-independent approaches. We examined the bacterial microbiota of the nostril and posterior wall of the oropharynx from seven healthy adults using two culture-independent methods, a 16S rRNA gene microarray (PhyloChip) and 16S rRNA gene clone libraries. While the bacterial microbiota of the oropharynx was richer than that of the nostril, the oropharyngeal microbiota varied less among participants than did nostril microbiota. A few phyla accounted for the majority of the bacteria detected at each site: Firmicutes and Actinobacteria in the nostril and Firmicutes, Proteobacteria, and Bacteroidetes in the oropharynx. Compared to culture-independent surveys of microbiota from other body sites, the microbiota of the nostril and oropharynx show distinct phylum-level distribution patterns, supporting niche-specific colonization at discrete anatomical sites. In the nostril, the distribution of Actinobacteria and Firmicutes was reminiscent of that of skin, though Proteobacteria were much less prevalent. The distribution of Firmicutes, Proteobacteria, and Bacteroidetes in the oropharynx was most similar to that in saliva, with more Proteobacteria than in the distal esophagus or mouth. While Firmicutes were prevalent at both sites, distinct families within this phylum dominated numerically in each. At both sites there was an inverse correlation between the prevalences of Firmicutes and another phylum: in the oropharynx, Firmicutes and Proteobacteria, and in the nostril, Firmicutes and Actinobacteria. In the nostril, this inverse correlation existed between the Firmicutes family Staphylococcaceae and Actinobacteria families, suggesting potential antagonism between these groups.

Structure of the human gastric bacterial community in relation to Helicobacter pylori status

PubMed Central

Maldonado-Contreras, Ana; Goldfarb, Kate C; Godoy-Vitorino, Filipa; Karaoz, Ulas; Contreras, Mónica; Blaser, Martin J; Brodie, Eoin L; Dominguez-Bello, Maria G

2011-01-01

The human stomach is naturally colonized by Helicobacter pylori, which, when present, dominates the gastric bacterial community. In this study, we aimed to characterize the structure of the bacterial community in the stomach of patients of differing H. pylori status. We used a high-density 16S rRNA gene microarray (PhyloChip, Affymetrix, Inc.) to hybridize 16S rRNA gene amplicons from gastric biopsy DNA of 10 rural Amerindian patients from Amazonas, Venezuela, and of two immigrants to the United States (from South Asia and Africa, respectively). H. pylori status was determined by PCR amplification of H. pylori glmM from gastric biopsy samples. Of the 12 patients, 8 (6 of the 10 Amerindians and the 2 non-Amerindians) were H. pylori glmM positive. Regardless of H. pylori status, the PhyloChip detected Helicobacteriaceae DNA in all patients, although with lower relative abundance in patients who were glmM negative. The G2-chip taxonomy analysis of PhyloChip data indicated the presence of 44 bacterial phyla (of which 16 are unclassified by the Taxonomic Outline of the Bacteria and Archaea taxonomy) in a highly uneven community dominated by only four phyla: Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. Positive H. pylori status was associated with increased relative abundance of non-Helicobacter bacteria from the Proteobacteria, Spirochetes and Acidobacteria, and with decreased abundance of Actinobacteria, Bacteroidetes and Firmicutes. The PhyloChip detected richness of low abundance phyla, and showed marked differences in the structure of the gastric bacterial community according to H. pylori status. PMID:20927139

Phylogenetic Network Analysis Revealed the Occurrence of Horizontal Gene Transfer of 16S rRNA in the Genus Enterobacter

PubMed Central

Sato, Mitsuharu; Miyazaki, Kentaro

2017-01-01

Horizontal gene transfer (HGT) is a ubiquitous genetic event in bacterial evolution, but it seldom occurs for genes involved in highly complex supramolecules (or biosystems), which consist of many gene products. The ribosome is one such supramolecule, but several bacteria harbor dissimilar and/or chimeric 16S rRNAs in their genomes, suggesting the occurrence of HGT of this gene. However, we know little about whether the genes actually experience HGT and, if so, the frequency of such a transfer. This is primarily because the methods currently employed for phylogenetic analysis (e.g., neighbor-joining, maximum likelihood, and maximum parsimony) of 16S rRNA genes assume point mutation-driven tree-shape evolution as an evolutionary model, which is intrinsically inappropriate to decipher the evolutionary history for genes driven by recombination. To address this issue, we applied a phylogenetic network analysis, which has been used previously for detection of genetic recombination in homologous alleles, to the 16S rRNA gene. We focused on the genus Enterobacter, whose phylogenetic relationships inferred by multi-locus sequence alignment analysis and 16S rRNA sequences are incompatible. All 10 complete genomic sequences were retrieved from the NCBI database, in which 71 16S rRNA genes were included. Neighbor-joining analysis demonstrated that the genes residing in the same genomes clustered, indicating the occurrence of intragenomic recombination. However, as suggested by the low bootstrap values, evolutionary relationships between the clusters were uncertain. We then applied phylogenetic network analysis to representative sequences from each cluster. We found three ancestral 16S rRNA groups; the others were likely created through recursive recombination between the ancestors and chimeric descendants. Despite the large sequence changes caused by the recombination events, the RNA secondary structures were conserved. Successive intergenomic and intragenomic recombination thus shaped the evolution of 16S rRNA genes in the genus Enterobacter. PMID:29180992

Intra-Genomic Heterogeneity in 16S rRNA Genes in Strictly Anaerobic Clinical Isolates from Periodontal Abscesses.

PubMed

Chen, Jiazhen; Miao, Xinyu; Xu, Meng; He, Junlin; Xie, Yi; Wu, Xingwen; Chen, Gang; Yu, Liying; Zhang, Wenhong

2015-01-01

Members of the genera Prevotella, Veillonella and Fusobacterium are the predominant culturable obligate anaerobic bacteria isolated from periodontal abscesses. When determining the cumulative number of clinical anaerobic isolates from periodontal abscesses, ambiguous or overlapping signals were frequently encountered in 16S rRNA gene sequencing chromatograms, resulting in ambiguous identifications. With the exception of the genus Veillonella, the high intra-chromosomal heterogeneity of rrs genes has not been reported. The 16S rRNA genes of 138 clinical, strictly anaerobic isolates and one reference strain were directly sequenced, and the chromatograms were carefully examined. Gene cloning was performed for 22 typical isolates with doublet sequencing signals for the 16S rRNA genes, and four copies of the rrs-ITS genes of 9 Prevotella intermedia isolates were separately amplified by PCR, sequenced and compared. Five conserved housekeeping genes, hsp60, recA, dnaJ, gyrB1 and rpoB from 89 clinical isolates of Prevotella were also amplified by PCR and sequenced for identification and phylogenetic analysis along with 18 Prevotella reference strains. Heterogeneity of 16S rRNA genes was apparent in clinical, strictly anaerobic oral bacteria, particularly in the genera Prevotella and Veillonella. One hundred out of 138 anaerobic strains (72%) had intragenomic nucleotide polymorphisms (SNPs) in multiple locations, and 13 strains (9.4%) had intragenomic insertions or deletions in the 16S rRNA gene. In the genera Prevotella and Veillonella, 75% (67/89) and 100% (19/19) of the strains had SNPs in the 16S rRNA gene, respectively. Gene cloning and separate amplifications of four copies of the rrs-ITS genes confirmed that 2 to 4 heterogeneous 16S rRNA copies existed. Sequence alignment of five housekeeping genes revealed that intra-species nucleotide similarities were very high in the genera Prevotella, ranging from 94.3-100%. However, the inter-species similarities were relatively low, ranging from 68.7-97.9%. The housekeeping genes rpoB and gyrB1 were demonstrated to be alternative classification markers to the species level based on intra- and inter-species comparisons, whereas based on phylogenetic tree rpoB proved to be reliable phylogenetic marker for the genus Prevotella.

Intra-Genomic Heterogeneity in 16S rRNA Genes in Strictly Anaerobic Clinical Isolates from Periodontal Abscesses

PubMed Central

Chen, Jiazhen; Miao, Xinyu; Xu, Meng; He, Junlin; Xie, Yi; Wu, Xingwen; Chen, Gang; Yu, Liying; Zhang, Wenhong

2015-01-01

Background Members of the genera Prevotella, Veillonella and Fusobacterium are the predominant culturable obligate anaerobic bacteria isolated from periodontal abscesses. When determining the cumulative number of clinical anaerobic isolates from periodontal abscesses, ambiguous or overlapping signals were frequently encountered in 16S rRNA gene sequencing chromatograms, resulting in ambiguous identifications. With the exception of the genus Veillonella, the high intra-chromosomal heterogeneity of rrs genes has not been reported. Methods The 16S rRNA genes of 138 clinical, strictly anaerobic isolates and one reference strain were directly sequenced, and the chromatograms were carefully examined. Gene cloning was performed for 22 typical isolates with doublet sequencing signals for the 16S rRNA genes, and four copies of the rrs-ITS genes of 9 Prevotella intermedia isolates were separately amplified by PCR, sequenced and compared. Five conserved housekeeping genes, hsp60, recA, dnaJ, gyrB1 and rpoB from 89 clinical isolates of Prevotella were also amplified by PCR and sequenced for identification and phylogenetic analysis along with 18 Prevotella reference strains. Results Heterogeneity of 16S rRNA genes was apparent in clinical, strictly anaerobic oral bacteria, particularly in the genera Prevotella and Veillonella. One hundred out of 138 anaerobic strains (72%) had intragenomic nucleotide polymorphisms (SNPs) in multiple locations, and 13 strains (9.4%) had intragenomic insertions or deletions in the 16S rRNA gene. In the genera Prevotella and Veillonella, 75% (67/89) and 100% (19/19) of the strains had SNPs in the 16S rRNA gene, respectively. Gene cloning and separate amplifications of four copies of the rrs-ITS genes confirmed that 2 to 4 heterogeneous 16S rRNA copies existed. Conclusion Sequence alignment of five housekeeping genes revealed that intra-species nucleotide similarities were very high in the genera Prevotella, ranging from 94.3–100%. However, the inter-species similarities were relatively low, ranging from 68.7–97.9%. The housekeeping genes rpoB and gyrB1 were demonstrated to be alternative classification markers to the species level based on intra- and inter-species comparisons, whereas based on phylogenetic tree rpoB proved to be reliable phylogenetic marker for the genus Prevotella. PMID:26103050

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 ...

An efficient method to identify differentially expressed genes in microarray experiments

PubMed Central

Qin, Huaizhen; Feng, Tao; Harding, Scott A.; Tsai, Chung-Jui; Zhang, Shuanglin

2013-01-01

Motivation Microarray experiments typically analyze thousands to tens of thousands of genes from small numbers of biological replicates. The fact that genes are normally expressed in functionally relevant patterns suggests that gene-expression data can be stratified and clustered into relatively homogenous groups. Cluster-wise dimensionality reduction should make it feasible to improve screening power while minimizing information loss. Results We propose a powerful and computationally simple method for finding differentially expressed genes in small microarray experiments. The method incorporates a novel stratification-based tight clustering algorithm, principal component analysis and information pooling. Comprehensive simulations show that our method is substantially more powerful than the popular SAM and eBayes approaches. We applied the method to three real microarray datasets: one from a Populus nitrogen stress experiment with 3 biological replicates; and two from public microarray datasets of human cancers with 10 to 40 biological replicates. In all three analyses, our method proved more robust than the popular alternatives for identification of differentially expressed genes. Availability The C++ code to implement the proposed method is available upon request for academic use. PMID:18453554

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.

An Advanced Approach to Simultaneous Monitoring of Multiple Bacteria in Space

NASA Technical Reports Server (NTRS)

Eggers, M.

1998-01-01

The utility of a novel microarray-based microbial analyzer was demonstrated by the rapid detection, imaging, and identification of a mixture of microorganisms found in a waste water sample from the Lunar-Mars Life Support Test Project through the synergistic combination of: (1) judicious RNA probe selection via algorithms developed by University of Houston scientists; (2) tuned surface chemistries developed by Baylor College of Medicine scientists to facilitate hybridization of rRNA targets to DNA probes under very low salt conditions, thereby minimizing secondary structure; and (3) integration of the microarray printing and detection/imaging instrumentation by Genometrix to complete the quantitative analysis of microorganism mixtures.

A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.

PubMed

Ogunnaike, Babatunde A; Gelmi, Claudio A; Edwards, Jeremy S

2010-05-21

Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

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

Functional comparison of microarray data across multiple platforms using the method of percentage of overlapping functions.

PubMed

Li, Zhiguang; Kwekel, Joshua C; Chen, Tao

2012-01-01

Functional comparison across microarray platforms is used to assess the comparability or similarity of the biological relevance associated with the gene expression data generated by multiple microarray platforms. Comparisons at the functional level are very important considering that the ultimate purpose of microarray technology is to determine the biological meaning behind the gene expression changes under a specific condition, not just to generate a list of genes. Herein, we present a method named percentage of overlapping functions (POF) and illustrate how it is used to perform the functional comparison of microarray data generated across multiple platforms. This method facilitates the determination of functional differences or similarities in microarray data generated from multiple array platforms across all the functions that are presented on these platforms. This method can also be used to compare the functional differences or similarities between experiments, projects, or laboratories.

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.

Gene expression profiling in gill tissues of White spot syndrome virus infected black tiger shrimp Penaeus monodon by DNA microarray.

PubMed

Shekhar, M S; Gomathi, A; Gopikrishna, G; Ponniah, A G

2015-06-01

White spot syndrome virus (WSSV) continues to be the most devastating viral pathogen infecting penaeid shrimp the world over. The genome of WSSV has been deciphered and characterized from three geographical isolates and significant progress has been made in developing various molecular diagnostic methods to detect the virus. However, the information on host immune gene response to WSSV pathogenesis is limited. Microarray analysis was carried out as an approach to analyse the gene expression in black tiger shrimp Penaeus monodon in response to WSSV infection. Gill tissues collected from the WSSV infected shrimp at 6, 24, 48 h and moribund stage were analysed for differential gene expression. Shrimp cDNAs of 40,059 unique sequences were considered for designing the microarray chip. The Cy3-labeled cRNA derived from healthy and WSSV-infected shrimp was subjected to hybridization with all the DNA spots in the microarray which revealed 8,633 and 11,147 as up- and down-regulated genes respectively at different time intervals post infection. The altered expression of these numerous genes represented diverse functions such as immune response, osmoregulation, apoptosis, nucleic acid binding, energy and metabolism, signal transduction, stress response and molting. The changes in gene expression profiles observed by microarray analysis provides molecular insights and framework of genes which are up- and down-regulated at different time intervals during WSSV infection in shrimp. The microarray data was validated by Real Time analysis of four differentially expressed genes involved in apoptosis (translationally controlled tumor protein, inhibitor of apoptosis protein, ubiquitin conjugated enzyme E2 and caspase) for gene expression levels. The role of apoptosis related genes in WSSV infected shrimp is discussed herein.

Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

PubMed Central

2014-01-01

Background Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. Results S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. Conclusions This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved. PMID:24444313

Suitability of partial 16S ribosomal RNA gene sequence analysis for the identification of dangerous bacterial pathogens.

PubMed

Ruppitsch, W; Stöger, A; Indra, A; Grif, K; Schabereiter-Gurtner, C; Hirschl, A; Allerberger, F

2007-03-01

In a bioterrorism event a rapid tool is needed to identify relevant dangerous bacteria. The aim of the study was to assess the usefulness of partial 16S rRNA gene sequence analysis and the suitability of diverse databases for identifying dangerous bacterial pathogens. For rapid identification purposes a 500-bp fragment of the 16S rRNA gene of 28 isolates comprising Bacillus anthracis, Brucella melitensis, Burkholderia mallei, Burkholderia pseudomallei, Francisella tularensis, Yersinia pestis, and eight genus-related and unrelated control strains was amplified and sequenced. The obtained sequence data were submitted to three public and two commercial sequence databases for species identification. The most frequent reason for incorrect identification was the lack of the respective 16S rRNA gene sequences in the database. Sequence analysis of a 500-bp 16S rDNA fragment allows the rapid identification of dangerous bacterial species. However, for discrimination of closely related species sequencing of the entire 16S rRNA gene, additional sequencing of the 23S rRNA gene or sequencing of the 16S-23S rRNA intergenic spacer is essential. This work provides comprehensive information on the suitability of partial 16S rDNA analysis and diverse databases for rapid and accurate identification of dangerous bacterial pathogens.

Pyrosequencing of mcrA and Archaeal 16S rRNA Genes Reveals Diversity and Substrate Preferences of Methanogen Communities in Anaerobic Digesters

PubMed Central

Wilkins, David; Lu, Xiao-Ying; Shen, Zhiyong; Chen, Jiapeng

2014-01-01

Methanogenic archaea play a key role in biogas-producing anaerobic digestion and yet remain poorly taxonomically characterized. This is in part due to the limitations of low-throughput Sanger sequencing of a single (16S rRNA) gene, which in the past may have undersampled methanogen diversity. In this study, archaeal communities from three sludge digesters in Hong Kong and one wastewater digester in China were examined using high-throughput pyrosequencing of the methyl coenzyme M reductase (mcrA) and 16S rRNA genes. Methanobacteriales, Methanomicrobiales, and Methanosarcinales were detected in each digester, indicating that both hydrogenotrophic and acetoclastic methanogenesis was occurring. Two sludge digesters had similar community structures, likely due to their similar design and feedstock. Taxonomic classification of the mcrA genes suggested that these digesters were dominated by acetoclastic methanogens, particularly Methanosarcinales, while the other digesters were dominated by hydrogenotrophic Methanomicrobiales. The proposed euryarchaeotal order Methanomassiliicoccales and the uncultured WSA2 group were detected with the 16S rRNA gene, and potential mcrA genes for these groups were identified. 16S rRNA gene sequencing also recovered several crenarchaeotal groups potentially involved in the initial anaerobic digestion processes. Overall, the two genes produced different taxonomic profiles for the digesters, while greater methanogen richness was detected using the mcrA gene, supporting the use of this functional gene as a complement to the 16S rRNA gene to better assess methanogen diversity. A significant positive correlation was detected between methane production and the abundance of mcrA transcripts in digesters treating sludge and wastewater samples, supporting the mcrA gene as a biomarker for methane yield. PMID:25381241

Prevalence of 16S rRNA methylase genes in Klebsiella pneumoniae isolates from a Chinese teaching hospital: coexistence of rmtB and armA genes in the same isolate.

PubMed

Yu, Fangyou; Wang, Liangxing; Pan, Jingye; Yao, Dan; Chen, Chan; Zhu, Tao; Lou, Qiang; Hu, Jian; Wu, Yang; Zhang, Xueqing; Chen, Zengqiang; Qu, Di

2009-05-01

16S rRNA methylase-mediated high-level resistance to aminoglycosides has been reported recently in clinical isolates of Gram-negative bacilli from several countries. Twenty-one (6.2%, 21/337) of 337 isolates of Klebsiella pneumoniae from a teaching hospital in Wenzhou, China, were positive for 16S rRNA methylase genes (3 for armA, 13 for rmtB, 5 for both armA and rmtB) and highly resistant to gentamicin, amikacin, and tobramycin (MICs, > or =256 microg/mL). Nineteen of 21 isolates harboring 16S rRNA methyalse genes were extended-spectrum beta-lactamase (ESBL) producers. The plasmids harboring 16S rRNA methylase genes from 14 of 21 donors were transferred into the recipients, Escherichia coli J53. The armA and the rmtB usually coexisted with ESBL genes in the same isolate in clinical isolates and cotransferred with ESBL genes on a self-transmissible conjugative plasmid to the recipients. Among 5 isolates harboring both armA and rmtB, the armA genes were located on the chromosomes, and the rmtB genes were located on the plasmids, as determined by Southern hybridization. The result of pulsed-field gel electrophoresis showed that horizontal gene transfer and clonal spread were responsible for the dissemination of the rmtB and the armA genes. 16S rRNA methylase-producing isolates of Klebsiella pneumoniae were commonly identified in the Chinese teaching hospital with coexistence of rmtB and armA genes in the same isolate.

CGO: utilizing and integrating gene expression microarray data in clinical research and data management.

PubMed

Bumm, Klaus; Zheng, Mingzhong; Bailey, Clyde; Zhan, Fenghuang; Chiriva-Internati, M; Eddlemon, Paul; Terry, Julian; Barlogie, Bart; Shaughnessy, John D

2002-02-01

Clinical GeneOrganizer (CGO) is a novel windows-based archiving, organization and data mining software for the integration of gene expression profiling in clinical medicine. The program implements various user-friendly tools and extracts data for further statistical analysis. This software was written for Affymetrix GeneChip *.txt files, but can also be used for any other microarray-derived data. The MS-SQL server version acts as a data mart and links microarray data with clinical parameters of any other existing database and therefore represents a valuable tool for combining gene expression analysis and clinical disease characteristics.

Genetic and functional properties of uncultivated thermophilic crenarchaeotes from a subsurface gold mine as revealed by analysis of genome fragments.

PubMed

Nunoura, Takuro; Hirayama, Hisako; Takami, Hideto; Oida, Hanako; Nishi, Shinro; Shimamura, Shigeru; Suzuki, Yohey; Inagaki, Fumio; Takai, Ken; Nealson, Kenneth H; Horikoshi, Koki

2005-12-01

Within a phylum Crenarchaeota, only some members of the hyperthermophilic class Thermoprotei, have been cultivated and characterized. In this study, we have constructed a metagenomic library from a microbial mat formation in a subsurface hot water stream of the Hishikari gold mine, Japan, and sequenced genome fragments of two different phylogroups of uncultivated thermophilic Crenarchaeota: (i) hot water crenarchaeotic group (HWCG) I (41.2 kb), and (ii) HWCG III (49.3 kb). The genome fragment of HWCG I contained a 16S rRNA gene, two tRNA genes and 35 genes encoding proteins but no 23S rRNA gene. Among the genes encoding proteins, several genes for putative aerobic-type carbon monoxide dehydrogenase represented a potential clue with regard to the yet unknown metabolism of HWCG I Archaea. The genome fragment of HWCG III contained a 16S/23S rRNA operon and 44 genes encoding proteins. In the 23S rRNA gene, we detected a homing-endonuclease encoding a group I intron similar to those detected in hyperthermophilic Crenarchaeota and Bacteria, as well as eukaryotic organelles. The reconstructed phylogenetic tree based on the 23S rRNA gene sequence reinforced the intermediate phylogenetic affiliation of HWCG III bridging the hyperthermophilic and non-thermophilic uncultivated Crenarchaeota.

RNAi targeting GPR4 influences HMEC-1 gene expression by microarray analysis

PubMed Central

Ren, Juan; Zhang, Yuelang; Cai, Hui; Ma, Hongbing; Zhao, Dongli; Zhang, Xiaozhi; Li, Zongfang; Wang, Shufeng; Wang, Jiangsheng; Liu, Rui; Li, Yi; Qian, Jiansheng; Wei, Hongxia; Niu, Liying; Liu, Yan; Xiao, Lisha; Ding, Muyang; Jiang, Shiwen

2014-01-01

G-protein coupled receptor 4 (GPR4) belongs to a protein family comprised of 3 closely related G protein-coupled receptors. Recent studies have shown that GPR4 plays important roles in angiogenesis, proton sensing, and regulating tumor cells as an oncogenic gene. How GPR4 conducts its functions? Rare has been known. In order to detect the genes related to GPR4, microarray technology was employed. GPR4 is highly expressed in human vascular endothelial cell HMEC-1. Small interfering RNA against GPR4 was used to knockdown GPR4 expression in HMEC-1. Then RNA from the GPR4 knockdown cells and control cells were analyzed through genome microarray. Microarray results shown that among the whole genes and expressed sequence tags, 447 differentially expressed genes were identified, containing 318 up-regulated genes and 129 down-regulated genes. These genes whose expression dramatically changed may be involved in the GPR4 functions. These genes were related to cell apoptosis, cytoskeleton and signal transduction, cell proliferation, differentiation and cell-cycle regulation, gene transcription and translation and cell material and energy metabolism. PMID:24753754

Taxonomic resolutions based on 18S rRNA genes: a case study of subclass copepoda.

PubMed

Wu, Shu; Xiong, Jie; Yu, Yuhe

2015-01-01

Biodiversity studies are commonly conducted using 18S rRNA genes. In this study, we compared the inter-species divergence of variable regions (V1-9) within the copepod 18S rRNA gene, and tested their taxonomic resolutions at different taxonomic levels. Our results indicate that the 18S rRNA gene is a good molecular marker for the study of copepod biodiversity, and our conclusions are as follows: 1) 18S rRNA genes are highly conserved intra-species (intra-species similarities are close to 100%); and could aid in species-level analyses, but with some limitations; 2) nearly-whole-length sequences and some partial regions (around V2, V4, and V9) of the 18S rRNA gene can be used to discriminate between samples at both the family and order levels (with a success rate of about 80%); 3) compared with other regions, V9 has a higher resolution at the genus level (with an identification success rate of about 80%); and 4) V7 is most divergent in length, and would be a good candidate marker for the phylogenetic study of Acartia species. This study also evaluated the correlation between similarity thresholds and the accuracy of using nuclear 18S rRNA genes for the classification of organisms in the subclass Copepoda. We suggest that sample identification accuracy should be considered when a molecular sequence divergence threshold is used for taxonomic identification, and that the lowest similarity threshold should be determined based on a pre-designated level of acceptable accuracy.

Taxonomic Resolutions Based on 18S rRNA Genes: A Case Study of Subclass Copepoda

PubMed Central

Wu, Shu; Xiong, Jie; Yu, Yuhe

2015-01-01

Biodiversity studies are commonly conducted using 18S rRNA genes. In this study, we compared the inter-species divergence of variable regions (V1–9) within the copepod 18S rRNA gene, and tested their taxonomic resolutions at different taxonomic levels. Our results indicate that the 18S rRNA gene is a good molecular marker for the study of copepod biodiversity, and our conclusions are as follows: 1) 18S rRNA genes are highly conserved intra-species (intra-species similarities are close to 100%); and could aid in species-level analyses, but with some limitations; 2) nearly-whole-length sequences and some partial regions (around V2, V4, and V9) of the 18S rRNA gene can be used to discriminate between samples at both the family and order levels (with a success rate of about 80%); 3) compared with other regions, V9 has a higher resolution at the genus level (with an identification success rate of about 80%); and 4) V7 is most divergent in length, and would be a good candidate marker for the phylogenetic study of Acartia species. This study also evaluated the correlation between similarity thresholds and the accuracy of using nuclear 18S rRNA genes for the classification of organisms in the subclass Copepoda. We suggest that sample identification accuracy should be considered when a molecular sequence divergence threshold is used for taxonomic identification, and that the lowest similarity threshold should be determined based on a pre-designated level of acceptable accuracy. PMID:26107258

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.

International interlaboratory study comparing single organism 16S rRNA gene sequencing data: Beyond consensus sequence comparisons

PubMed Central

Olson, Nathan D.; Lund, Steven P.; Zook, Justin M.; Rojas-Cornejo, Fabiola; Beck, Brian; Foy, Carole; Huggett, Jim; Whale, Alexandra S.; Sui, Zhiwei; Baoutina, Anna; Dobeson, Michael; Partis, Lina; Morrow, Jayne B.

2015-01-01

This study presents the results from an interlaboratory sequencing study for which we developed a novel high-resolution method for comparing data from different sequencing platforms for a multi-copy, paralogous gene. The combination of PCR amplification and 16S ribosomal RNA gene (16S rRNA) sequencing has revolutionized bacteriology by enabling rapid identification, frequently without the need for culture. To assess variability between laboratories in sequencing 16S rRNA, six laboratories sequenced the gene encoding the 16S rRNA from Escherichia coli O157:H7 strain EDL933 and Listeria monocytogenes serovar 4b strain NCTC11994. Participants performed sequencing methods and protocols available in their laboratories: Sanger sequencing, Roche 454 pyrosequencing®, or Ion Torrent PGM®. The sequencing data were evaluated on three levels: (1) identity of biologically conserved position, (2) ratio of 16S rRNA gene copies featuring identified variants, and (3) the collection of variant combinations in a set of 16S rRNA gene copies. The same set of biologically conserved positions was identified for each sequencing method. Analytical methods using Bayesian and maximum likelihood statistics were developed to estimate variant copy ratios, which describe the ratio of nucleotides at each identified biologically variable position, as well as the likely set of variant combinations present in 16S rRNA gene copies. Our results indicate that estimated variant copy ratios at biologically variable positions were only reproducible for high throughput sequencing methods. Furthermore, the likely variant combination set was only reproducible with increased sequencing depth and longer read lengths. We also demonstrate novel methods for evaluating variable positions when comparing multi-copy gene sequence data from multiple laboratories generated using multiple sequencing technologies. PMID:27077030

The nucleotide sequence of the intergenic region between the 5.8S and 26S rRNA genes of the yeast ribosomal RNA operon. Possible implications for the interaction between 5.8S and 26S rRNA and the processing of the primary transcript.

PubMed Central

Veldman, G M; Klootwijk, J; van Heerikhuizen, H; Planta, R J

1981-01-01

We have determined the nucleotide sequence of part of a cloned yeast ribosomal RNA operon extending from the 5.8S RNA gene downstream into the 5' -terminal region of the 26S RNA gene. We mapped the pertinent processing sites, viz. the 5' end of 26S rRNA and the 3'ends of 5.8S rRNA and its immediate precursor, 7S RNA. At the 3' end of 7S RNA we find the sequence UCGUUU which is very similar to the type I consensus sequence UCAUUA/U present at the 3' ends of 17S, 5.8S and 26S rRNA as well as 18S precursor rRNA in yeast. At the 5' end of the 26S RNA gene we find a sequence of thirteen nucleotides which is homologous to the type II sequence present at the 5' termini of both the 17S and the 5.8S RNA gene. These findings further support the suggestion put forward earlier (G.M. Veldman et al. (1980) Nucl. Acids Res. 8, 2907-2920) that both consensus sequences are involved in the recognition of precursor rRNA by the processing nuclease(s). We discuss a model for the processing of yeast rRNA in which a processing enzyme sequentially recognizes several combinations of a type I and a type II consensus sequence. We also describe the existence of a significant base complementarity between sequences in the 5' -terminal region of 26S rRNA and the 3' -terminal region of 5.8S rRNA. We suggest that base pairing between these sequences contributes to the binding between 5.8S and 26S rRNA. Images PMID:7312619

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

Microbiology of aquatic environments: Characterizations of the microbiotas of municipal water supplies, the International Space Station Internal Active Thermal Control System's heat transport fluid, and US Space Shuttle drinking water

NASA Astrophysics Data System (ADS)

Bernardini, James Nicholas, III

An understanding of the microbiota within life support systems is essential for the prolonged presence of humans in space. This is because microbes may cause disease or induce biofouling and/or corrosion within spacecraft water systems. It is imperative that we develop effective high-throughput technologies for characterizing microbial populations that can eventually be used in the space environment. This dissertation describes testing and development of such methodologies, targeting both bacteria and viruses in water, and examines the bacterial and viral diversity within two spacecraft life support systems. The bacterial community of the International Space Station Internal Active Thermal Control System (IATCS) was examined using conventional culture-based and advanced molecular techniques including adenosine triphosphate (ATP) and Limulus Amebocyte Lysate (LAL) assays, direct microscopic examination, and analyses of 16S rRNA gene libraries from the community metagenome. The cultivable heterotrophs of the IATCS fluids ranged from below detection limit to 1.1x10 5/100 ml, and viable cells, measured by ATP, ranged from 1.4x10 3/100 ml to 7.7x105/100 ml. DNA extraction, cloning, sequencing, and bioinformatic analysis of the clones from 16S RNA gene libraries showed members of the firmicutes, alpha, beta, and gamma-proteobacteria to be present in the fluids. This persistent microbial bioburden and the presence of probable metal reducers, biofilm formers, and opportunistic pathogens illustrate the need for better characterization of bacterial communities present within spacecraft fluids. A new methodology was developed for detection of viruses in water using microarrays. Samples were concentrated by lyophilization, resuspended and filtered (0.22microm). Viral nucleic acids were then extracted, amplified, fluorescently labeled and hybridized onto a custom microarray with probes for ˜1000 known viruses. Numerous virus signatures were observed. Human Adenovirus C and Influenza A viruses were used to verify positive microarray hybridizations by quantitative polymerase chain reaction (PCR), reverse transcriptase PCR, and conventional PCR. Experiments were performed using municipal drinking water, IATCS fluids, and Shuttle drinking water. Thus, this dissertation describes what we believe is the first molecular analysis of the IATCS bacterial ecology and the first use and validation of a microarray-based assay for the detection of viral genetic signatures within drinking waters.

IDENTIFICATION OF BIOLOGICALLY RELEVANT GENES USING A DATABASE OF RAT LIVER AND KIDNEY BASELINE GENE EXPRESSION

EPA Science Inventory

Microarray data from independent labs and studies can be compared to potentially identify toxicologically and biologically relevant genes. The Baseline Animal Database working group of HESI was formed to assess baseline gene expression from microarray data derived from control or...

Pseudomonas sp. strain CA5 (a selenite-reducing bacterium) 16S rRNA gene complete sequence. National Institute of Health, National Center for Biotechnology Information, GenBank sequence. Accession FJ422810.1.

USDA-ARS?s Scientific Manuscript database

This study used 1321 base pair 16S rRNA gene sequence methods to confirm the phylogenetic position of a soil isolate as a bacterium belonging to the genus Pesudomonas sp. Morphological, biochemical characteristics, and fatty acid profiles are consistent with the 16S rRNA gene sequence identification...

Detection of a mixed infection in a culture-negative brain abscess by broad-spectrum bacterial 16S rRNA gene PCR.

PubMed

Keller, Peter M; Rampini, Silvana K; Bloemberg, Guido V

2010-06-01

We describe the identification of two bacterial pathogens from a culture-negative brain abscess by the use of broad-spectrum 16S rRNA gene PCR. Simultaneous detection of Fusobacterium nucleatum and Porphyromonas endodontalis was possible due to a 24-bp length difference of their partially amplified 16S rRNA genes, which allowed separation by high-resolution polyacrylamide gel electrophoresis.

Mode of inheritance and evidence for cistron heterogeneity of chloroplast 16S ribosomal RNA genes in Nicotiana.

PubMed

Vacek, A T; Bourque, D P

1980-09-01

Oligonucleotide maps (fingerprints) of T1 RNase digests of 125I-labeled 16 S chloroplast rRNA of Nicotiana tabacum and N. gossei revealed the presence of T1 oligonucleotide fragment 100 in the 16 S rRNA of N. gossei while N. tabacum 16 S rRNA had a unique T1 oligonucleotide (fragment 101) as well as some fragment 100. From the positions in the fingerprints and from fingerprints of secondary enzymatic digestion of the fragments, we conclude that fragments 100 and 101 are similar in sequence and size, but fragment 100 probably contains an extra uracil residue. This difference is shown to be maternally inherited, thus confirming the location of 16 S chloroplast rRNA genes on chloroplast DNA and ruling out the possibility of genetically active chloroplast rRNA genes in the nucleus. The presence of both fragments 100 and 101 in N. tabacum may indicate sequence heterogeneity between the two cistrons for 16 S chloroplast rRNA. These results demonstrate the feasibility of determining the inheritance of organelle genes by genetic analysis of their primary transcripts.

A novel universal DNA labeling and amplification system for rapid microarray-based detection of 117 antibiotic resistance genes in Gram-positive bacteria.

PubMed

Strauss, Christian; Endimiani, Andrea; Perreten, Vincent

2015-01-01

A rapid and simple DNA labeling system has been developed for disposable microarrays and has been validated for the detection of 117 antibiotic resistance genes abundant in Gram-positive bacteria. The DNA was fragmented and amplified using phi-29 polymerase and random primers with linkers. Labeling and further amplification were then performed by classic PCR amplification using biotinylated primers specific for the linkers. The microarray developed by Perreten et al. (Perreten, V., Vorlet-Fawer, L., Slickers, P., Ehricht, R., Kuhnert, P., Frey, J., 2005. Microarray-based detection of 90 antibiotic resistance genes of gram-positive bacteria. J.Clin.Microbiol. 43, 2291-2302.) was improved by additional oligonucleotides. A total of 244 oligonucleotides (26 to 37 nucleotide length and with similar melting temperatures) were spotted on the microarray, including genes conferring resistance to clinically important antibiotic classes like β-lactams, macrolides, aminoglycosides, glycopeptides and tetracyclines. Each antibiotic resistance gene is represented by at least 2 oligonucleotides designed from consensus sequences of gene families. The specificity of the oligonucleotides and the quality of the amplification and labeling were verified by analysis of a collection of 65 strains belonging to 24 species. Association between genotype and phenotype was verified for 6 antibiotics using 77 Staphylococcus strains belonging to different species and revealed 95% test specificity and a 93% predictive value of a positive test. The DNA labeling and amplification is independent of the species and of the target genes and could be used for different types of microarrays. This system has also the advantage to detect several genes within one bacterium at once, like in Staphylococcus aureus strain BM3318, in which up to 15 genes were detected. This new microarray-based detection system offers a large potential for applications in clinical diagnostic, basic research, food safety and surveillance programs for antimicrobial resistance. Copyright © 2014 Elsevier B.V. All rights reserved.

Moving Toward Integrating Gene Expression Profiling into High-throughput Testing:A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

EPA Science Inventory

Microarray profiling of chemical-induced effects is being increasingly used in medium and high-throughput formats. In this study, we describe computational methods to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), ...

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards.

PubMed

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Laegreid, Astrid

2007-10-18

The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish.

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards

PubMed Central

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Lægreid, Astrid

2007-01-01

Background The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. Results We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. Conclusion The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish. PMID:17949480

Evaluation of two main RNA-seq approaches for gene quantification in clinical RNA sequencing: polyA+ selection versus rRNA depletion.

PubMed

Zhao, Shanrong; Zhang, Ying; Gamini, Ramya; Zhang, Baohong; von Schack, David

2018-03-19

To allow efficient transcript/gene detection, highly abundant ribosomal RNAs (rRNA) are generally removed from total RNA either by positive polyA+ selection or by rRNA depletion (negative selection) before sequencing. Comparisons between the two methods have been carried out by various groups, but the assessments have relied largely on non-clinical samples. In this study, we evaluated these two RNA sequencing approaches using human blood and colon tissue samples. Our analyses showed that rRNA depletion captured more unique transcriptome features, whereas polyA+ selection outperformed rRNA depletion with higher exonic coverage and better accuracy of gene quantification. For blood- and colon-derived RNAs, we found that 220% and 50% more reads, respectively, would have to be sequenced to achieve the same level of exonic coverage in the rRNA depletion method compared with the polyA+ selection method. Therefore, in most cases we strongly recommend polyA+ selection over rRNA depletion for gene quantification in clinical RNA sequencing. Our evaluation revealed that a small number of lncRNAs and small RNAs made up a large fraction of the reads in the rRNA depletion RNA sequencing data. Thus, we recommend that these RNAs are specifically depleted to improve the sequencing depth of the remaining RNAs.

A preliminary result of three-dimensional microarray technology to gene analysis with endoscopic ultrasound-guided fine-needle aspiration specimens and pancreatic juices

PubMed Central

2010-01-01

Background Analysis of gene expression and gene mutation may add information to be different from ordinary pathological tissue diagnosis. Since samples obtained endoscopically are very small, it is desired that more sensitive technology is developed for gene analysis. We investigated whether gene expression and gene mutation analysis by newly developed ultra-sensitive three-dimensional (3D) microarray is possible using small amount samples from endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) specimens and pancreatic juices. Methods Small amount samples from 17 EUS-FNA specimens and 16 pancreatic juices were obtained. After nucleic acid extraction, the samples were amplified with labeling and analyzed by the 3D microarray. Results The analyzable rate with the microarray was 46% (6/13) in EUS-FNA specimens of RNAlater® storage, and RNA degradations were observed in all the samples of frozen storage. In pancreatic juices, the analyzable rate was 67% (4/6) in frozen storage samples and 20% (2/10) in RNAlater® storage. EUS-FNA specimens were classified into cancer and non-cancer by gene expression analysis and K-ras codon 12 mutations were also detected using the 3D microarray. Conclusions Gene analysis from small amount samples obtained endoscopically was possible by newly developed 3D microarray technology. High quality RNA from EUS-FNA samples were obtained and remained in good condition only using RNA stabilizer. In contrast, high quality RNA from pancreatic juice samples were obtained only in frozen storage without RNA stabilizer. PMID:20416107

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

PubMed

Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

How Much Do rRNA Gene Surveys Underestimate Extant Bacterial Diversity?

PubMed

Rodriguez-R, Luis M; Castro, Juan C; Kyrpides, Nikos C; Cole, James R; Tiedje, James M; Konstantinidis, Konstantinos T

2018-03-15

The most common practice in studying and cataloguing prokaryotic diversity involves the grouping of sequences into operational taxonomic units (OTUs) at the 97% 16S rRNA gene sequence identity level, often using partial gene sequences, such as PCR-generated amplicons. Due to the high sequence conservation of rRNA genes, organisms belonging to closely related yet distinct species may be grouped under the same OTU. However, it remains unclear how much diversity has been underestimated by this practice. To address this question, we compared the OTUs of genomes defined at the 97% or 98.5% 16S rRNA gene identity level against OTUs of the same genomes defined at the 95% whole-genome average nucleotide identity (ANI), which is a much more accurate proxy for species. Our results show that OTUs resulting from a 98.5% 16S rRNA gene identity cutoff are more accurate than 97% compared to 95% ANI (90.5% versus 89.9% accuracy) but indistinguishable from any other threshold in the 98.29 to 98.78% range. Even with the more stringent thresholds, however, the 16S rRNA gene-based approach commonly underestimates the number of OTUs by ∼12%, on average, compared to the ANI-based approach (∼14% underestimation when using the 97% identity threshold). More importantly, the degree of underestimation can become 50% or more for certain taxa, such as the genera Pseudomonas , Burkholderia , Escherichia , Campylobacter , and Citrobacter These results provide a quantitative view of the degree of underestimation of extant prokaryotic diversity by 16S rRNA gene-defined OTUs and suggest that genomic resolution is often necessary. IMPORTANCE Species diversity is one of the most fundamental pieces of information for community ecology and conservational biology. Therefore, employing accurate proxies for what a species or the unit of diversity is are cornerstones for a large set of microbial ecology and diversity studies. The most common proxies currently used rely on the clustering of 16S rRNA gene sequences at some threshold of nucleotide identity, typically 97% or 98.5%. Here, we explore how well this strategy reflects the more accurate whole-genome-based proxies and determine the frequency with which the high conservation of 16S rRNA sequences masks substantial species-level diversity. Copyright © 2018 American Society for Microbiology.

Mining microarray data at NCBI's Gene Expression Omnibus (GEO)*.

PubMed

Barrett, Tanya; Edgar, Ron

2006-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

Parallel human genome analysis: microarray-based expression monitoring of 1000 genes.

PubMed Central

Schena, M; Shalon, D; Heller, R; Chai, A; Brown, P O; Davis, R W

1996-01-01

Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm2 DNA "chips" were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. Array elements that displayed differential expression patterns under given experimental conditions were characterized by sequencing. The identification of known and novel heat shock and phorbol ester-regulated genes in human T cells demonstrates the sensitivity of the assay. Parallel gene analysis with microarrays provides a rapid and efficient method for large-scale human gene discovery. Images Fig. 1 Fig. 2 Fig. 3 PMID:8855227

Mining microarrays for metabolic meaning: nutritional regulation of hypothalamic gene expression.

PubMed

Mobbs, Charles V; Yen, Kelvin; Mastaitis, Jason; Nguyen, Ha; Watson, Elizabeth; Wurmbach, Elisa; Sealfon, Stuart C; Brooks, Andrew; Salton, Stephen R J

2004-06-01

DNA microarray analysis has been used to investigate relative changes in the level of gene expression in the CNS, including changes that are associated with disease, injury, psychiatric disorders, drug exposure or withdrawal, and memory formation. We have used oligonucleotide microarrays to identify hypothalamic genes that respond to nutritional manipulation. In addition to commonly used microarray analysis based on criteria such as fold-regulation, we have also found that simply carrying out multiple t tests then sorting by P value constitutes a highly reliable method to detect true regulation, as assessed by real-time polymerase chain reaction (PCR), even for relatively low abundance genes or relatively low magnitude of regulation. Such analyses directly suggested novel mechanisms that mediate effects of nutritional state on neuroendocrine function and are being used to identify regulated gene products that may elucidate the metabolic pathology of obese ob/ob, lean Vgf-/Vgf-, and other models with profound metabolic impairments.

Punctual mutations in 23S rRNA gene of clarithromycin-resistant Helicobacter pylori in Colombian populations.

PubMed

Matta, Andrés Jenuer; Zambrano, Diana Carolina; Pazos, Alvaro Jairo

2018-04-14

To characterize punctual mutations in 23S rRNA gene of clarithromycin-resistant Helicobacter pylori ( H. pylori ) and determine their association with therapeutic failure. PCR products of 23S rRNA gene V domain of 74 H. pylori isolates; 34 resistant to clarithromycin (29 from a low-risk gastric cancer (GC) population: Tumaco-Colombia, and 5 from a high-risk population: Tuquerres-Colombia) and 40 from a susceptible population (28 from Tumaco and 12 from Túquerres) were sequenced using capillary electrophoresis. The concordance between mutations of V domain 23S rRNA gene of H. pylori and therapeutic failure was determined using the Kappa coefficient and McNemar's test was performed to determine the relationship between H. pylori mutations and clarithromycin resistance. 23S rRNA gene from H. pylori was amplified in 56/74 isolates, of which 25 were resistant to clarithromycin (20 from Tumaco and 5 from Túquerres, respectively). In 17 resistant isolates (13 from Tumaco and 4 from Túquerres) the following mutations were found: A1593T1, A1653G2, C1770T, C1954T1, and G1827C in isolates from Tumaco, and A2144G from Túquerres. The mutations T2183C, A2144G and C2196T in H. pylori isolates resistant to clarithromycin from Colombia are reported for the first time. No association between the H. pylori mutations and in vitro clarithromycin resistance was found. However, therapeutic failure of eradication treatment was associated with mutations of 23S rRNA gene in clarithromycin-resistant H. pylori ( κ = 0.71). The therapeutic failure of eradication treatment in the two populations from Colombia was associated with mutations of the 23S rRNA gene in clarithromycin-resistant H. pylori .

Multiclass classification of microarray data samples with a reduced number of genes

PubMed Central

2011-01-01

Background Multiclass classification of microarray data samples with a reduced number of genes is a rich and challenging problem in Bioinformatics research. The problem gets harder as the number of classes is increased. In addition, the performance of most classifiers is tightly linked to the effectiveness of mandatory gene selection methods. Critical to gene selection is the availability of estimates about the maximum number of genes that can be handled by any classification algorithm. Lack of such estimates may lead to either computationally demanding explorations of a search space with thousands of dimensions or classification models based on gene sets of unrestricted size. In the former case, unbiased but possibly overfitted classification models may arise. In the latter case, biased classification models unable to support statistically significant findings may be obtained. Results A novel bound on the maximum number of genes that can be handled by binary classifiers in binary mediated multiclass classification algorithms of microarray data samples is presented. The bound suggests that high-dimensional binary output domains might favor the existence of accurate and sparse binary mediated multiclass classifiers for microarray data samples. Conclusions A comprehensive experimental work shows that the bound is indeed useful to induce accurate and sparse multiclass classifiers for microarray data samples. PMID:21342522

Microarray labeling extension values: laboratory signatures for Affymetrix GeneChips

PubMed Central

Lee, Yun-Shien; Chen, Chun-Houh; Tsai, Chi-Neu; Tsai, Chia-Lung; Chao, Angel; Wang, Tzu-Hao

2009-01-01

Interlaboratory comparison of microarray data, even when using the same platform, imposes several challenges to scientists. RNA quality, RNA labeling efficiency, hybridization procedures and data-mining tools can all contribute variations in each laboratory. In Affymetrix GeneChips, about 11–20 different 25-mer oligonucleotides are used to measure the level of each transcript. Here, we report that ‘labeling extension values (LEVs)’, which are correlation coefficients between probe intensities and probe positions, are highly correlated with the gene expression levels (GEVs) on eukayotic Affymetrix microarray data. By analyzing LEVs and GEVs in the publicly available 2414 cel files of 20 Affymetrix microarray types covering 13 species, we found that correlations between LEVs and GEVs only exist in eukaryotic RNAs, but not in prokaryotic ones. Surprisingly, Affymetrix results of the same specimens that were analyzed in different laboratories could be clearly differentiated only by LEVs, leading to the identification of ‘laboratory signatures’. In the examined dataset, GSE10797, filtering out high-LEV genes did not compromise the discovery of biological processes that are constructed by differentially expressed genes. In conclusion, LEVs provide a new filtering parameter for microarray analysis of gene expression and it may improve the inter- and intralaboratory comparability of Affymetrix GeneChips data. PMID:19295132

Microarray-based identification of differentially expressed genes in extramammary Paget’s disease

PubMed Central

Lin, Jin-Ran; Liang, Jun; Zhang, Qiao-An; Huang, Qiong; Wang, Shang-Shang; Qin, Hai-Hong; Chen, Lian-Jun; Xu, Jin-Hua

2015-01-01

Extramammary Paget’s disease (EMPD) is a rare cutaneous malignancy accounting for approximately 1-2% of vulvar cancers. The rarity of this disease has caused difficulties in characterization and the molecular mechanism underlying EMPD development remains largely unclear. Here we used microarray analysis to identify differentially expressed genes in EMPD of the scrotum comparing with normal epithelium from healthy donors. Agilent single-channel microarray was used to compare the gene expression between 6 EMPD specimens and 6 normal scrotum epithelium samples. A total of 799 up-regulated genes and 723 down-regulated genes were identified in EMPD tissues. Real-time PCR was conducted to verify the differential expression of some representative genes, including ERBB4, TCF3, PAPSS2, PIK3R3, PRLR, SULT1A1, TCF7L1, and CREB3L4. Generally, the real-time PCR results were consistent with microarray data, and the expression of ERBB4, PRLR, TCF3, PIK3R3, SULT1A1, and TCF7L1 was significantly overexpressed in EMPD (P<0.05). Moreover, the overexpression of PRLR in EMPD, a receptor for the anterior pituitary hormone prolactin (PRL), was confirmed by immunohistochemistry. These data demonstrate that the differentially expressed genes from the microarray-based identification are tightly associated with EMPD occurrence. PMID:26221264

Detection of a Mixed Infection in a Culture-Negative Brain Abscess by Broad-Spectrum Bacterial 16S rRNA Gene PCR ▿ †

PubMed Central

Keller, Peter M.; Rampini, Silvana K.; Bloemberg, Guido V.

2010-01-01

We describe the identification of two bacterial pathogens from a culture-negative brain abscess by the use of broad-spectrum 16S rRNA gene PCR. Simultaneous detection of Fusobacterium nucleatum and Porphyromonas endodontalis was possible due to a 24-bp length difference of their partially amplified 16S rRNA genes, which allowed separation by high-resolution polyacrylamide gel electrophoresis. PMID:20392909

Genetic and epigenetic variation in 5S ribosomal RNA genes reveals genome dynamics in Arabidopsis thaliana

PubMed Central

Simon, Lauriane; Rabanal, Fernando A; Dubos, Tristan; Oliver, Cecilia; Lauber, Damien; Poulet, Axel; Vogt, Alexander; Mandlbauer, Ariane; Le Goff, Samuel; Sommer, Andreas; Duborjal, Hervé; Tatout, Christophe

2018-01-01

Abstract Organized in tandem repeat arrays in most eukaryotes and transcribed by RNA polymerase III, expression of 5S rRNA genes is under epigenetic control. To unveil mechanisms of transcriptional regulation, we obtained here in depth sequence information on 5S rRNA genes from the Arabidopsis thaliana genome and identified differential enrichment in epigenetic marks between the three 5S rDNA loci situated on chromosomes 3, 4 and 5. We reveal the chromosome 5 locus as the major source of an atypical, long 5S rRNA transcript characteristic of an open chromatin structure. 5S rRNA genes from this locus translocated in the Landsberg erecta ecotype as shown by linkage mapping and chromosome-specific FISH analysis. These variations in 5S rDNA locus organization cause changes in the spatial arrangement of chromosomes in the nucleus. Furthermore, 5S rRNA gene arrangements are highly dynamic with alterations in chromosomal positions through translocations in certain mutants of the RNA-directed DNA methylation pathway and important copy number variations among ecotypes. Finally, variations in 5S rRNA gene sequence, chromatin organization and transcripts indicate differential usage of 5S rDNA loci in distinct ecotypes. We suggest that both the usage of existing and new 5S rDNA loci resulting from translocations may impact neighboring chromatin organization. PMID:29518237

Genetic and epigenetic variation in 5S ribosomal RNA genes reveals genome dynamics in Arabidopsis thaliana.

PubMed

Simon, Lauriane; Rabanal, Fernando A; Dubos, Tristan; Oliver, Cecilia; Lauber, Damien; Poulet, Axel; Vogt, Alexander; Mandlbauer, Ariane; Le Goff, Samuel; Sommer, Andreas; Duborjal, Hervé; Tatout, Christophe; Probst, Aline V

2018-04-06

Organized in tandem repeat arrays in most eukaryotes and transcribed by RNA polymerase III, expression of 5S rRNA genes is under epigenetic control. To unveil mechanisms of transcriptional regulation, we obtained here in depth sequence information on 5S rRNA genes from the Arabidopsis thaliana genome and identified differential enrichment in epigenetic marks between the three 5S rDNA loci situated on chromosomes 3, 4 and 5. We reveal the chromosome 5 locus as the major source of an atypical, long 5S rRNA transcript characteristic of an open chromatin structure. 5S rRNA genes from this locus translocated in the Landsberg erecta ecotype as shown by linkage mapping and chromosome-specific FISH analysis. These variations in 5S rDNA locus organization cause changes in the spatial arrangement of chromosomes in the nucleus. Furthermore, 5S rRNA gene arrangements are highly dynamic with alterations in chromosomal positions through translocations in certain mutants of the RNA-directed DNA methylation pathway and important copy number variations among ecotypes. Finally, variations in 5S rRNA gene sequence, chromatin organization and transcripts indicate differential usage of 5S rDNA loci in distinct ecotypes. We suggest that both the usage of existing and new 5S rDNA loci resulting from translocations may impact neighboring chromatin organization.

Genes misregulated in C. elegans deficient in Dicer, RDE-4, or RDE-1 are enriched for innate immunity genes.

PubMed

Welker, Noah C; Habig, Jeffrey W; Bass, Brenda L

2007-07-01

We describe the first microarray analysis of a whole animal containing a mutation in the Dicer gene. We used adult Caenorhabditis elegans and, to distinguish among different roles of Dicer, we also performed microarray analyses of animals with mutations in rde-4 and rde-1, which are involved in silencing by siRNA, but not miRNA. Surprisingly, we find that the X chromosome is greatly enriched for genes regulated by Dicer. Comparison of all three microarray data sets indicates the majority of Dicer-regulated genes are not dependent on RDE-4 or RDE-1, including the X-linked genes. However, all three data sets are enriched in genes important for innate immunity and, specifically, show increased expression of innate immunity genes.

Genes misregulated in C. elegans deficient in Dicer, RDE-4, or RDE-1 are enriched for innate immunity genes

PubMed Central

Welker, Noah C.; Habig, Jeffrey W.; Bass, Brenda L.

2007-01-01

We describe the first microarray analysis of a whole animal containing a mutation in the Dicer gene. We used adult Caenorhabditis elegans and, to distinguish among different roles of Dicer, we also performed microarray analyses of animals with mutations in rde-4 and rde-1, which are involved in silencing by siRNA, but not miRNA. Surprisingly, we find that the X chromosome is greatly enriched for genes regulated by Dicer. Comparison of all three microarray data sets indicates the majority of Dicer-regulated genes are not dependent on RDE-4 or RDE-1, including the X-linked genes. However, all three data sets are enriched in genes important for innate immunity and, specifically, show increased expression of innate immunity genes. PMID:17526642

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

PubMed Central

2012-01-01

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings. PMID:16964229

Fragmentation of the large subunit ribosomal RNA gene in oyster mitochondrial genomes.

PubMed

Milbury, Coren A; Lee, Jung C; Cannone, Jamie J; Gaffney, Patrick M; Gutell, Robin R

2010-09-02

Discontinuous genes have been observed in bacteria, archaea, and eukaryotic nuclei, mitochondria and chloroplasts. Gene discontinuity occurs in multiple forms: the two most frequent forms result from introns that are spliced out of the RNA and the resulting exons are spliced together to form a single transcript, and fragmented gene transcripts that are not covalently attached post-transcriptionally. Within the past few years, fragmented ribosomal RNA (rRNA) genes have been discovered in bilateral metazoan mitochondria, all within a group of related oysters. In this study, we have characterized this fragmentation with comparative analysis and experimentation. We present secondary structures, modeled using comparative sequence analysis of the discontinuous mitochondrial large subunit rRNA genes of the cupped oysters C. virginica, C. gigas, and C. hongkongensis. Comparative structure models for the large subunit rRNA in each of the three oyster species are generally similar to those for other bilateral metazoans. We also used RT-PCR and analyzed ESTs to determine if the two fragmented LSU rRNAs are spliced together. The two segments are transcribed separately, and not spliced together although they still form functional rRNAs and ribosomes. Although many examples of discontinuous ribosomal genes have been documented in bacteria and archaea, as well as the nuclei, chloroplasts, and mitochondria of eukaryotes, oysters are some of the first characterized examples of fragmented bilateral animal mitochondrial rRNA genes. The secondary structures of the oyster LSU rRNA fragments have been predicted on the basis of previous comparative metazoan mitochondrial LSU rRNA structure models.

Identification of candidate genes in osteoporosis by integrated microarray analysis.

PubMed

Li, J J; Wang, B Q; Fei, Q; Yang, Y; Li, D

2016-12-01

In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation.Cite this article: J. J. Li, B. Q. Wang, Q. Fei, Y. Yang, D. Li. Identification of candidate genes in osteoporosis by integrated microarray analysis. Bone Joint Res 2016;5:594-601. DOI: 10.1302/2046-3758.512.BJR-2016-0073.R1. © 2016 Fei et al.

Chromatin structure and methylation of rat rRNA genes studied by formaldehyde fixation and psoralen cross-linking.

PubMed Central

Stancheva, I; Lucchini, R; Koller, T; Sogo, J M

1997-01-01

By using formaldehyde cross-linking of histones to DNA and gel retardation assays we show that formaldehyde fixation, similar to previously established psoralen photocross-linking, discriminates between nucleosome- packed (inactive) and nucleosome-free (active) fractions of ribosomal RNA genes. By both cross-linking techniques we were able to purify fragments from agarose gels, corresponding to coding, enhancer and promoter sequences of rRNA genes, which were further investigated with respect to DNA methylation. This approach allows us to analyse independently and in detail methylation patterns of active and inactive rRNA gene copies by the combination of Hpa II and Msp I restriction enzymes. We found CpG methylation mainly present in enhancer and promoter regions of inactive rRNA gene copies. The methylation of one single Hpa II site, located in the promoter region, showed particularly strong correlation with the transcriptional activity. PMID:9108154

An intron within the 16S ribosomal RNA gene of the archaeon Pyrobaculum aerophilum

NASA Technical Reports Server (NTRS)

Burggraf, S.; Larsen, N.; Woese, C. R.; Stetter, K. O.

1993-01-01

The 16S rRNA genes of Pyrobaculum aerophilum and Pyrobaculum islandicum were amplified by the polymerase chain reaction, and the resulting products were sequenced directly. The two organisms are closely related by this measure (over 98% similar). However, they differ in that the (lone) 16S rRNA gene of Pyrobaculum aerophilum contains a 713-bp intron not seen in the corresponding gene of Pyrobaculum islandicum. To our knowledge, this is the only intron so far reported in the small subunit rRNA gene of a prokaryote. Upon excision the intron is circularized. A secondary structure model of the intron-containing rRNA suggests a splicing mechanism of the same type as that invoked for the tRNA introns of the Archaea and Eucarya and 23S rRNAs of the Archaea. The intron contains an open reading frame whose protein translation shows no certain homology with any known protein sequence.

Phylogenetic Analysis of Ruminant Theileria spp. from China Based on 28S Ribosomal RNA Gene

PubMed Central

Gou, Huitian; Guan, Guiquan; Ma, Miling; Liu, Aihong; Liu, Zhijie; Xu, Zongke; Ren, Qiaoyun; Li, Youquan; Yang, Jifei; Chen, Ze

2013-01-01

Species identification using DNA sequences is the basis for DNA taxonomy. In this study, we sequenced the ribosomal large-subunit RNA gene sequences (3,037-3,061 bp) in length of 13 Chinese Theileria stocks that were infective to cattle and sheep. The complete 28S rRNA gene is relatively difficult to amplify and its conserved region is not important for phylogenetic study. Therefore, we selected the D2-D3 region from the complete 28S rRNA sequences for phylogenetic analysis. Our analyses of 28S rRNA gene sequences showed that the 28S rRNA was useful as a phylogenetic marker for analyzing the relationships among Theileria spp. in ruminants. In addition, the D2-D3 region was a short segment that could be used instead of the whole 28S rRNA sequence during the phylogenetic analysis of Theileria, and it may be an ideal DNA barcode. PMID:24327775

Phylogenetic analysis of ruminant Theileria spp. from China based on 28S ribosomal RNA gene.

PubMed

Gou, Huitian; Guan, Guiquan; Ma, Miling; Liu, Aihong; Liu, Zhijie; Xu, Zongke; Ren, Qiaoyun; Li, Youquan; Yang, Jifei; Chen, Ze; Yin, Hong; Luo, Jianxun

2013-10-01

Species identification using DNA sequences is the basis for DNA taxonomy. In this study, we sequenced the ribosomal large-subunit RNA gene sequences (3,037-3,061 bp) in length of 13 Chinese Theileria stocks that were infective to cattle and sheep. The complete 28S rRNA gene is relatively difficult to amplify and its conserved region is not important for phylogenetic study. Therefore, we selected the D2-D3 region from the complete 28S rRNA sequences for phylogenetic analysis. Our analyses of 28S rRNA gene sequences showed that the 28S rRNA was useful as a phylogenetic marker for analyzing the relationships among Theileria spp. in ruminants. In addition, the D2-D3 region was a short segment that could be used instead of the whole 28S rRNA sequence during the phylogenetic analysis of Theileria, and it may be an ideal DNA barcode.

Free-living and captive turtles and tortoises as carriers of new Chlamydia spp.

PubMed Central

Niemczuk, Krzysztof; Zaręba, Kinga; Zając, Magdalena; Laroucau, Karine; Szymańska-Czerwińska, Monika

2017-01-01

A variety of Chlamydia species belonging to the Chlamydiaceae family have been reported in reptilian hosts but scarce data about their occurrence in turtles and tortoises are available. In this study, research was conducted to acquire information on invasive alien species (IAS) of turtles and indigenous turtles and tortoises, living both free and in captivity, as possible reservoirs of Chlamydiaceae. Analysis of specimens (pharyngeal and cloacal swabs and tissues) from 204 turtles and tortoises revealed an overall Chlamydiaceae prevalence of 18.3% and 28.6% among free-living and captive animals respectively, with variable levels of shedding. Further testing conducted with a species-specific real-time PCR and microarray test was unsuccessful. Subsequently sequencing was applied to genotype the Chlamydiaceae-positive samples. Almost the full lengths of the 16S rRNA and ompA genes as well as the 16S-23S intergenic spacer (IGS) and 23S rRNA domain I were obtained for 14, 20 and 8 specimens respectively. Phylogenetic analysis of 16S rRNA amplicons revealed two distinct branches. Group 1 (10 specimens), specific to freshwater turtles and reported here for the first time, was most closely related to Chlamydia (C.) pneumoniae strains and the newly described Candidatus C. sanzinia. Group 2 (four specimens), detected in Testudo spp. samples, showed highest homology to C. pecorum strains but formed a separate sub-branch. Finally, molecular analysis conducted on positive samples together with their geographical distribution in places distant from each other strongly suggest that Group 1 specimens correspond to a new species in the Chlamydiaceae family. In-depth studies of Chlamydia spp. from turtles and tortoises are needed to further characterise these atypical strains and address arising questions about their pathogenicity and zoonotic potential. PMID:28950002

Free-living and captive turtles and tortoises as carriers of new Chlamydia spp.

PubMed

Mitura, Agata; Niemczuk, Krzysztof; Zaręba, Kinga; Zając, Magdalena; Laroucau, Karine; Szymańska-Czerwińska, Monika

2017-01-01

A variety of Chlamydia species belonging to the Chlamydiaceae family have been reported in reptilian hosts but scarce data about their occurrence in turtles and tortoises are available. In this study, research was conducted to acquire information on invasive alien species (IAS) of turtles and indigenous turtles and tortoises, living both free and in captivity, as possible reservoirs of Chlamydiaceae. Analysis of specimens (pharyngeal and cloacal swabs and tissues) from 204 turtles and tortoises revealed an overall Chlamydiaceae prevalence of 18.3% and 28.6% among free-living and captive animals respectively, with variable levels of shedding. Further testing conducted with a species-specific real-time PCR and microarray test was unsuccessful. Subsequently sequencing was applied to genotype the Chlamydiaceae-positive samples. Almost the full lengths of the 16S rRNA and ompA genes as well as the 16S-23S intergenic spacer (IGS) and 23S rRNA domain I were obtained for 14, 20 and 8 specimens respectively. Phylogenetic analysis of 16S rRNA amplicons revealed two distinct branches. Group 1 (10 specimens), specific to freshwater turtles and reported here for the first time, was most closely related to Chlamydia (C.) pneumoniae strains and the newly described Candidatus C. sanzinia. Group 2 (four specimens), detected in Testudo spp. samples, showed highest homology to C. pecorum strains but formed a separate sub-branch. Finally, molecular analysis conducted on positive samples together with their geographical distribution in places distant from each other strongly suggest that Group 1 specimens correspond to a new species in the Chlamydiaceae family. In-depth studies of Chlamydia spp. from turtles and tortoises are needed to further characterise these atypical strains and address arising questions about their pathogenicity and zoonotic potential.

[Design of primers to DNA of lactic acid bacteria].

PubMed

Lashchevskiĭ, V V; Kovalenko, N K

2003-01-01

Primers LP1-LP2 to the gene 16S rRNA have been developed, which permit to differentiate lactic acid bacteria: Lactobacillus plantarum, L. delbrueckii subsp. bulgaricus and Streptococcus salivarius subsp. thermophilus. The strain-specific and species-specific differentiations are possible under different annealing temperature. Additional fragments, which are synthesized outside the framework of gene 16S rRNA reading, provide for the strain-specific type of differentiation, and the fragment F864 read in the gene 16S rRNA permits identifying L. plantarum.

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/.

Microarray profiling of human white adipose tissue after exogenous leptin injection.

PubMed

Taleb, S; Van Haaften, R; Henegar, C; Hukshorn, C; Cancello, R; Pelloux, V; Hanczar, B; Viguerie, N; Langin, D; Evelo, C; Zucker, J; Clément, K; Saris, W H M

2006-03-01

Leptin is a secreted adipocyte hormone that plays a key role in the regulation of body weight homeostasis. The leptin effect on human white adipose tissue (WAT) is still debated. The aim of this study was to assess whether the administration of polyethylene glycol-leptin (PEG-OB) in a single supraphysiological dose has transcriptional effects on genes of WAT and to identify its target genes and functional pathways in WAT. Blood samples and WAT biopsies were obtained from 10 healthy nonobese men before treatment and 72 h after the PEG-OB injection, leading to an approximate 809-fold increase in circulating leptin. The WAT gene expression profile before and after the PEG-OB injection was compared using pangenomic microarrays. Functional gene annotations based on the gene ontology of the PEG-OB regulated genes were performed using both an 'in house' automated procedure and GenMAPP (Gene Microarray Pathway Profiler), designed for viewing and analyzing gene expression data in the context of biological pathways. Statistical analysis of microarray data revealed that PEG-OB had a major down-regulated effect on WAT gene expression, as we obtained 1,822 and 100 down- and up-regulated genes, respectively. Microarray data were validated using reverse transcription quantitative PCR. Functional gene annotations of PEG-OB regulated genes revealed that the functional class related to immunity and inflammation was among the most mobilized PEG-OB pathway in WAT. These genes are mainly expressed in the cell of the stroma vascular fraction in comparison with adipocytes. Our observations support the hypothesis that leptin could act on WAT, particularly on genes related to inflammation and immunity, which may suggest a novel leptin target pathway in human WAT.

Fiber-optic microarray for simultaneous detection of multiple harmful algal bloom species.

PubMed

Ahn, Soohyoun; Kulis, David M; Erdner, Deana L; Anderson, Donald M; Walt, David R

2006-09-01

Harmful algal blooms (HABs) are a serious threat to coastal resources, causing a variety of impacts on public health, regional economies, and ecosystems. Plankton analysis is a valuable component of many HAB monitoring and research programs, but the diversity of plankton poses a problem in discriminating toxic from nontoxic species using conventional detection methods. Here we describe a sensitive and specific sandwich hybridization assay that combines fiber-optic microarrays with oligonucleotide probes to detect and enumerate the HAB species Alexandrium fundyense, Alexandrium ostenfeldii, and Pseudo-nitzschia australis. Microarrays were prepared by loading oligonucleotide probe-coupled microspheres (diameter, 3 mum) onto the distal ends of chemically etched imaging fiber bundles. Hybridization of target rRNA from HAB cells to immobilized probes on the microspheres was visualized using Cy3-labeled secondary probes in a sandwich-type assay format. We applied these microarrays to the detection and enumeration of HAB cells in both cultured and field samples. Our study demonstrated a detection limit of approximately 5 cells for all three target organisms within 45 min, without a separate amplification step, in both sample types. We also developed a multiplexed microarray to detect the three HAB species simultaneously, which successfully detected the target organisms, alone and in combination, without cross-reactivity. Our study suggests that fiber-optic microarrays can be used for rapid and sensitive detection and potential enumeration of HAB species in the environment.

Prokaryotic diversity, distribution, and insights into their role in biogeochemical cycling in marine basalts

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

Mason, Olivia U.; Di Meo-Savoie, Carol A.; Van Nostrand, Joy D.

2008-09-30

We used molecular techniques to analyze basalts of varying ages that were collected from the East Pacific Rise, 9 oN, from the rift axis of the Juan de Fuca Ridge, and from neighboring seamounts. Cluster analysis of 16S rDNA Terminal Restriction Fragment Polymorphism data revealed that basalt endoliths are distinct from seawater and that communities clustered, to some degree, based on the age of the host rock. This age-based clustering suggests that alteration processes may affect community structure. Cloning and sequencing of bacterial and archaeal 16S rRNA genes revealed twelve different phyla and sub-phyla associated with basalts. These include themore » Gemmatimonadetes, Nitrospirae, the candidate phylum SBR1093 in the c, andin the Archaea Marine Benthic Group B, none of which have been previously reported in basalts. We delineated novel ocean crust clades in the gamma-Proteobacteria, Planctomycetes, and Actinobacteria that are composed entirely of basalt associated microflora, and may represent basalt ecotypes. Finally, microarray analysis of functional genes in basalt revealed that genes coding for previously unreported processes such as carbon fixation, methane-oxidation, methanogenesis, and nitrogen fixation are present, suggesting that basalts harbor previously unrecognized metabolic diversity. These novel processes could exert a profound influence on ocean chemistry.« less

Towards the integration, annotation and association of historical microarray experiments with RNA-seq.

PubMed

Chavan, Shweta S; Bauer, Michael A; Peterson, Erich A; Heuck, Christoph J; Johann, Donald J

2013-01-01

Transcriptome analysis by microarrays has produced important advances in biomedicine. For instance in multiple myeloma (MM), microarray approaches led to the development of an effective disease subtyping via cluster assignment, and a 70 gene risk score. Both enabled an improved molecular understanding of MM, and have provided prognostic information for the purposes of clinical management. Many researchers are now transitioning to Next Generation Sequencing (NGS) approaches and RNA-seq in particular, due to its discovery-based nature, improved sensitivity, and dynamic range. Additionally, RNA-seq allows for the analysis of gene isoforms, splice variants, and novel gene fusions. Given the voluminous amounts of historical microarray data, there is now a need to associate and integrate microarray and RNA-seq data via advanced bioinformatic approaches. Custom software was developed following a model-view-controller (MVC) approach to integrate Affymetrix probe set-IDs, and gene annotation information from a variety of sources. The tool/approach employs an assortment of strategies to integrate, cross reference, and associate microarray and RNA-seq datasets. Output from a variety of transcriptome reconstruction and quantitation tools (e.g., Cufflinks) can be directly integrated, and/or associated with Affymetrix probe set data, as well as necessary gene identifiers and/or symbols from a diversity of sources. Strategies are employed to maximize the annotation and cross referencing process. Custom gene sets (e.g., MM 70 risk score (GEP-70)) can be specified, and the tool can be directly assimilated into an RNA-seq pipeline. A novel bioinformatic approach to aid in the facilitation of both annotation and association of historic microarray data, in conjunction with richer RNA-seq data, is now assisting with the study of MM cancer biology.

Estimating gene function with least squares nonnegative matrix factorization.

PubMed

Wang, Guoli; Ochs, Michael F

2007-01-01

Nonnegative matrix factorization is a machine learning algorithm that has extracted information from data in a number of fields, including imaging and spectral analysis, text mining, and microarray data analysis. One limitation with the method for linking genes through microarray data in order to estimate gene function is the high variance observed in transcription levels between different genes. Least squares nonnegative matrix factorization uses estimates of the uncertainties on the mRNA levels for each gene in each condition, to guide the algorithm to a local minimum in normalized chi2, rather than a Euclidean distance or divergence between the reconstructed data and the data itself. Herein, application of this method to microarray data is demonstrated in order to predict gene function.

Microarray data mining using Bioconductor packages.

PubMed

Nie, Haisheng; Neerincx, Pieter B T; van der Poel, Jan; Ferrari, Francesco; Bicciato, Silvio; Leunissen, Jack A M; Groenen, Martien A M

2009-07-16

This paper describes the results of a Gene Ontology (GO) term enrichment analysis of chicken microarray data using the Bioconductor packages. By checking the enriched GO terms in three contrasts, MM8-PM8, MM8-MA8, and MM8-MM24, of the provided microarray data during this workshop, this analysis aimed to investigate the host reactions in chickens occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. The results of GO enrichment analysis using GO terms annotated to chicken genes and GO terms annotated to chicken-human orthologous genes were also compared. Furthermore, a locally adaptive statistical procedure (LAP) was performed to test differentially expressed chromosomal regions, rather than individual genes, in the chicken genome after Eimeria challenge. GO enrichment analysis identified significant (raw p-value < 0.05) GO terms for all three contrasts included in the analysis. Some of the GO terms linked to, generally, primary immune responses or secondary immune responses indicating the GO enrichment analysis is a useful approach to analyze microarray data. The comparisons of GO enrichment results using chicken gene information and chicken-human orthologous gene information showed more refined GO terms related to immune responses when using chicken-human orthologous gene information, this suggests that using chicken-human orthologous gene information has higher power to detect significant GO terms with more refined functionality. Furthermore, three chromosome regions were identified to be significantly up-regulated in contrast MM8-PM8 (q-value < 0.01). Overall, this paper describes a practical approach to analyze microarray data in farm animals where the genome information is still incomplete. For farm animals, such as chicken, with currently limited gene annotation, borrowing gene annotation information from orthologous genes in well-annotated species, such as human, will help improve the pathway analysis results substantially. Furthermore, LAP analysis approach is a relatively new and very useful way to be applied in microarray analysis.

Bacterial population dynamics during uranium reduction andre-oxidation: Application of a novel high density oligonucleotidemicroarray approach

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

Brodie, Eoin L.; DeSantis, Todd Z.; Joyner, Dominique C.

2006-01-30

Reduction of soluble uranium U(VI) to less-soluble uraniumU(IV) is a promising approach to minimize migration from contaminatedaquifers. It is generally assumed that, under constant reducingconditions, U(IV) is stable and immobile; however, in a previous study,we documented reoxidation of U(IV) under continuous reducing conditions(Wan et al., Environ. Sci. Technol. 2005, 39:6162 6169). To determine ifchanges in microbial community composition were a factor in U(IV)reoxidation, we employed a high-density phylogenetic DNA microarray (16Smicroarray) containing 500,000 probes to monitor changes in bacterialpopulations during this remediation process. Comparison of the 16Smicroarray with clone libraries demonstrated successful detection andclassification of most clone groups. Analysis ofmore » the most dynamic groupsof 16S rRNA gene amplicons detected by the 16S microarray identified fiveclusters of bacterial subfamilies responding in a similar manner. Thisapproach demonstrated that amplicons of known metal-reducing bacteriasuch as Geothrix fermentans (confirmed by quantitative PCR) and thosewithin the Geobacteraceae were abundant during U(VI) reduction and didnot decline during the U(IV) reoxidation phase. Significantly, it appearsthat the observed reoxidation of uranium under reducing conditionsoccurred despite elevated microbial activity and the consistent presenceof metal-reducing bacteria. High-density phylogenetic microarraysconstitute a powerful tool, enabling the detection and monitoring of asubstantial portion of the microbial population in a routine, accurate,and reproducible manner.« less

Mining Microarray Data at NCBI’s Gene Expression Omnibus (GEO)*

PubMed Central

Barrett, Tanya; Edgar, Ron

2006-01-01

Summary The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) has emerged as the leading fully public repository for gene expression data. This chapter describes how to use Web-based interfaces, applications, and graphics to effectively explore, visualize, and interpret the hundreds of microarray studies and millions of gene expression patterns stored in GEO. Data can be examined from both experiment-centric and gene-centric perspectives using user-friendly tools that do not require specialized expertise in microarray analysis or time-consuming download of massive data sets. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo. PMID:16888359

Chondrocyte channel transcriptomics

PubMed Central

Lewis, Rebecca; May, Hannah; Mobasheri, Ali; Barrett-Jolley, Richard

2013-01-01

To date, a range of ion channels have been identified in chondrocytes using a number of different techniques, predominantly electrophysiological and/or biomolecular; each of these has its advantages and disadvantages. Here we aim to compare and contrast the data available from biophysical and microarray experiments. This letter analyses recent transcriptomics datasets from chondrocytes, accessible from the European Bioinformatics Institute (EBI). We discuss whether such bioinformatic analysis of microarray datasets can potentially accelerate identification and discovery of ion channels in chondrocytes. The ion channels which appear most frequently across these microarray datasets are discussed, along with their possible functions. We discuss whether functional or protein data exist which support the microarray data. A microarray experiment comparing gene expression in osteoarthritis and healthy cartilage is also discussed and we verify the differential expression of 2 of these genes, namely the genes encoding large calcium-activated potassium (BK) and aquaporin channels. PMID:23995703

Microbiome Analysis of Stool Samples from African Americans with Colon Polyps

PubMed Central

Brim, Hassan; Yooseph, Shibu; Zoetendal, Erwin G.; Lee, Edward; Torralbo, Manolito; Laiyemo, Adeyinka O.; Shokrani, Babak; Nelson, Karen; Ashktorab, Hassan

2013-01-01

Background Colonic polyps are common tumors occurring in ~50% of Western populations with ~10% risk of malignant progression. Dietary agents have been considered the primary environmental exposure to promote colorectal cancer (CRC) development. However, the colonic mucosa is permanently in contact with the microbiota and its metabolic products including toxins that also have the potential to trigger oncogenic transformation. Aim To analyze fecal DNA for microbiota composition and functional potential in African Americans with pre-neoplastic lesions. Materials & Methods We analyzed the bacterial composition of stool samples from 6 healthy individuals and 6 patients with colon polyps using 16S ribosomal RNA-based phylogenetic microarray; the Human intestinal Tract Chip (HITChip) and 16S rRNA gene barcoded 454 pyrosequencing. The functional potential was determined by sequence-based metagenomics using 454 pyrosequencing. Results Fecal microbiota profiling of samples from the healthy and polyp patients using both a phylogenetic microarraying (HITChip) and barcoded 454 pyrosequencing generated similar results. A distinction between both sets of samples was only obtained when the analysis was performed at the sub-genus level. Most of the species leading to the dissociation were from the Bacteroides group. The metagenomic analysis did not reveal major differences in bacterial gene prevalence/abundances between the two groups even when the analysis and comparisons were restricted to available Bacteroides genomes. Conclusion This study reveals that at the pre-neoplastic stages, there is a trend showing microbiota changes between healthy and colon polyp patients at the sub-genus level. These differences were not reflected at the genome/functions levels. Bacteria and associated functions within the Bacteroides group need to be further analyzed and dissected to pinpoint potential actors in the early colon oncogenic transformation in a large sample size. PMID:24376500

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 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

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

APPLICATION OF DNA MICROARRAYS TO REPRODUCTIVE TOXICOLOGY AND THE DEVELOPMENT OF A TESTIS ARRAY

EPA Science Inventory

With the advent of sequence information for entire mammalian genomes, it is now possible to analyze gene expression and gene polymorphisms on a genomic scale. The primary tool for analysis of gene expression is the DNA microarray. We have used commercially available cDNA micro...

BIOMONITORING THE TOXICOGENOMIC RESPONSE TO ENDOCRINE DISRUPTING CHEMICALS IN HUMANS, LABORATORY SPECIES AND WILDLIFE

EPA Science Inventory

With the advent of sequence information for entire eukaryotic genomes, it is now possible to analyze gene expression on a genomic scale. The primary tool for genomic analysis of gene expression is the gene microarray. We have used commercially available and custom cDNA microarray...

Coupling Genetic and Chemical Microbiome Profiling Reveals Heterogeneity of Archaeome and Bacteriome in Subsurface Biofilms That Are Dominated by the Same Archaeal Species

PubMed Central

Holman, Hoi-Ying N.; DeSantis, Todd Z.; Wanner, Gerhard; Andersen, Gary L.; Perras, Alexandra K.; Meck, Sandra; Völkel, Jörg; Bechtel, Hans A.; Wirth, Reinhard; Moissl-Eichinger, Christine

2014-01-01

Earth harbors an enormous portion of subsurface microbial life, whose microbiome flux across geographical locations remains mainly unexplored due to difficult access to samples. Here, we investigated the microbiome relatedness of subsurface biofilms of two sulfidic springs in southeast Germany that have similar physical and chemical parameters and are fed by one deep groundwater current. Due to their unique hydrogeological setting these springs provide accessible windows to subsurface biofilms dominated by the same uncultivated archaeal species, called SM1 Euryarchaeon. Comparative analysis of infrared imaging spectra demonstrated great variations in archaeal membrane composition between biofilms of the two springs, suggesting different SM1 euryarchaeal strains of the same species at both aquifer outlets. This strain variation was supported by ultrastructural and metagenomic analyses of the archaeal biofilms, which included intergenic spacer region sequencing of the rRNA gene operon. At 16S rRNA gene level, PhyloChip G3 DNA microarray detected similar biofilm communities for archaea, but site-specific communities for bacteria. Both biofilms showed an enrichment of different deltaproteobacterial operational taxonomic units, whose families were, however, congruent as were their lipid spectra. Consequently, the function of the major proportion of the bacteriome appeared to be conserved across the geographic locations studied, which was confirmed by dsrB-directed quantitative PCR. Consequently, microbiome differences of these subsurface biofilms exist at subtle nuances for archaea (strain level variation) and at higher taxonomic levels for predominant bacteria without a substantial perturbation in bacteriome function. The results of this communication provide deep insight into the dynamics of subsurface microbial life and warrant its future investigation with regard to metabolic and genomic analyses. PMID:24971452

Nearly complete rRNA genes assembled from across the metazoan animals: effects of more taxa, a structure-based alignment, and paired-sites evolutionary models on phylogeny reconstruction.

PubMed

Mallatt, Jon; Craig, Catherine Waggoner; Yoder, Matthew J

2010-04-01

This study (1) uses nearly complete rRNA-gene sequences from across Metazoa (197 taxa) to reconstruct animal phylogeny; (2) presents a highly annotated, manual alignment of these sequences with special reference to rRNA features including paired sites (http://purl.oclc.org/NET/rRNA/Metazoan_alignment) and (3) tests, after eliminating as few disruptive, rogue sequences as possible, if a likelihood framework can recover the main metazoan clades. We found that systematic elimination of approximately 6% of the sequences, including the divergent or unstably placed sequences of cephalopods, arrowworm, symphylan and pauropod myriapods, and of myzostomid and nemertodermatid worms, led to a tree that supported Ecdysozoa, Lophotrochozoa, Protostomia, and Bilateria. Deuterostomia, however, was never recovered, because the rRNA of urochordates goes (nonsignificantly) near the base of the Bilateria. Counterintuitively, when we modeled the evolution of the paired sites, phylogenetic resolution was not increased over traditional tree-building models that assume all sites in rRNA evolve independently. The rRNA genes of non-bilaterians contain a higher % AT than do those of most bilaterians. The rRNA genes of Acoela and Myzostomida were found to be secondarily shortened, AT-enriched, and highly modified, throwing some doubt on the location of these worms at the base of Bilateria in the rRNA tree--especially myzostomids, which other evidence suggests are annelids instead. Other findings are marsupial-with-placental mammals, arrowworms in Ecdysozoa (well supported here but contradicted by morphology), and Placozoa as sister to Cnidaria. Finally, despite the difficulties, the rRNA-gene trees are in strong concordance with trees derived from multiple protein-coding genes in supporting the new animal phylogeny. (c) 2009 Elsevier Inc. All rights reserved.

Hierarchical Gene Selection and Genetic Fuzzy System for Cancer Microarray Data Classification

PubMed Central

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice. PMID:25823003

Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.

PubMed

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice.

Microarray analysis of genes differentially expressed in HepG2 cells cultured in simulated microgravity: preliminary report

NASA Technical Reports Server (NTRS)

Khaoustov, V. I.; Risin, D.; Pellis, N. R.; Yoffe, B.; McIntire, L. V. (Principal Investigator)

2001-01-01

Developed at NASA, the rotary cell culture system (RCCS) allows the creation of unique microgravity environment of low shear force, high-mass transfer, and enables three-dimensional (3D) cell culture of dissimilar cell types. Recently we demonstrated that a simulated microgravity is conducive for maintaining long-term cultures of functional hepatocytes and promote 3D cell assembly. Using deoxyribonucleic acid (DNA) microarray technology, it is now possible to measure the levels of thousands of different messenger ribonucleic acids (mRNAs) in a single hybridization step. This technique is particularly powerful for comparing gene expression in the same tissue under different environmental conditions. The aim of this research was to analyze gene expression of hepatoblastoma cell line (HepG2) during early stage of 3D-cell assembly in simulated microgravity. For this, mRNA from HepG2 cultured in the RCCS was analyzed by deoxyribonucleic acid microarray. Analyses of HepG2 mRNA by using 6K glass DNA microarray revealed changes in expression of 95 genes (overexpression of 85 genes and downregulation of 10 genes). Our preliminary results indicated that simulated microgravity modifies the expression of several genes and that microarray technology may provide new understanding of the fundamental biological questions of how gravity affects the development and function of individual cells.

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

DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data

PubMed Central

Glez-Peña, Daniel; Álvarez, Rodrigo; Díaz, Fernando; Fdez-Riverola, Florentino

2009-01-01

Background Expression profiling assays done by using DNA microarray technology generate enormous data sets that are not amenable to simple analysis. The greatest challenge in maximizing the use of this huge amount of data is to develop algorithms to interpret and interconnect results from different genes under different conditions. In this context, fuzzy logic can provide a systematic and unbiased way to both (i) find biologically significant insights relating to meaningful genes, thereby removing the need for expert knowledge in preliminary steps of microarray data analyses and (ii) reduce the cost and complexity of later applied machine learning techniques being able to achieve interpretable models. Results DFP is a new Bioconductor R package that implements a method for discretizing and selecting differentially expressed genes based on the application of fuzzy logic. DFP takes advantage of fuzzy membership functions to assign linguistic labels to gene expression levels. The technique builds a reduced set of relevant genes (FP, Fuzzy Pattern) able to summarize and represent each underlying class (pathology). A last step constructs a biased set of genes (DFP, Discriminant Fuzzy Pattern) by intersecting existing fuzzy patterns in order to detect discriminative elements. In addition, the software provides new functions and visualisation tools that summarize achieved results and aid in the interpretation of differentially expressed genes from multiple microarray experiments. Conclusion DFP integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It has the advantage that its parameters are highly configurable, facilitating the discovery of biologically relevant connections between sets of genes belonging to different pathologies. This information makes it possible to automatically filter irrelevant genes thereby reducing the large volume of data supplied by microarray experiments. Based on these contributions GENECBR, a successful tool for cancer diagnosis using microarray datasets, has recently been released. PMID:19178723

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.

DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data.

PubMed

Glez-Peña, Daniel; Alvarez, Rodrigo; Díaz, Fernando; Fdez-Riverola, Florentino

2009-01-29

Expression profiling assays done by using DNA microarray technology generate enormous data sets that are not amenable to simple analysis. The greatest challenge in maximizing the use of this huge amount of data is to develop algorithms to interpret and interconnect results from different genes under different conditions. In this context, fuzzy logic can provide a systematic and unbiased way to both (i) find biologically significant insights relating to meaningful genes, thereby removing the need for expert knowledge in preliminary steps of microarray data analyses and (ii) reduce the cost and complexity of later applied machine learning techniques being able to achieve interpretable models. DFP is a new Bioconductor R package that implements a method for discretizing and selecting differentially expressed genes based on the application of fuzzy logic. DFP takes advantage of fuzzy membership functions to assign linguistic labels to gene expression levels. The technique builds a reduced set of relevant genes (FP, Fuzzy Pattern) able to summarize and represent each underlying class (pathology). A last step constructs a biased set of genes (DFP, Discriminant Fuzzy Pattern) by intersecting existing fuzzy patterns in order to detect discriminative elements. In addition, the software provides new functions and visualisation tools that summarize achieved results and aid in the interpretation of differentially expressed genes from multiple microarray experiments. DFP integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It has the advantage that its parameters are highly configurable, facilitating the discovery of biologically relevant connections between sets of genes belonging to different pathologies. This information makes it possible to automatically filter irrelevant genes thereby reducing the large volume of data supplied by microarray experiments. Based on these contributions GENECBR, a successful tool for cancer diagnosis using microarray datasets, has recently been released.

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.

An Archaea 5S rRNA analog is stably expressed in Escherichia coli

NASA Technical Reports Server (NTRS)

Yang, Y.; Fox, G. E.

1996-01-01

Mini-genes for 5S-like rRNA were constructed. These genes had a sequence which largely resembles that of the naturally occurring 5S rRNA of a bacterium, Halococcus morrhuae, which phylogenetically belongs to the Archaea. Plasmids carrying the mini-genes were transformed into Escherichia coli (Ec). Ribosomal incorporation was not a prerequisite for stable accumulation of the RNA product. However, only those constructs with a well-base-paired helix I accumulated RNA product. This result strongly implies that this aspect of the structure is likely to be an important condition for stabilizing 5S rRNA-like products. The results are consistent with our current understanding of 5S rRNA processing in Ec. When used in conjunction with rRNA probe technology, the resulting chimeric RNA may be useful as a monitoring tool for genetically engineered microorganisms or naturally occurring organisms that are released into the environment.

Community structure and function of planktonic Crenarchaeota: changes with depth in the South China Sea.

PubMed

Hu, Anyi; Jiao, Nianzhi; Zhang, Chuanlun L

2011-10-01

Marine Crenarchaeota represent a widespread and abundant microbial group in marine ecosystems. Here, we investigated the abundance, diversity, and distribution of planktonic Crenarchaeota in the epi-, meso-, and bathypelagic zones at three stations in the South China Sea (SCS) by analysis of crenarchaeal 16S rRNA gene, ammonia monooxygenase gene amoA involved in ammonia oxidation, and biotin carboxylase gene accA putatively involved in archaeal CO(2) fixation. Quantitative PCR analyses indicated that crenarchaeal amoA and accA gene abundances varied similarly with archaeal and crenarchaeal 16S rRNA gene abundances at all stations, except that crenarchaeal accA genes were almost absent in the epipelagic zone. Ratios of the crenarchaeal amoA gene to 16S rRNA gene abundances decreased ~2.6 times from the epi- to bathypelagic zones, whereas the ratios of crenarchaeal accA gene to marine group I crenarchaeal 16S rRNA gene or to crenarchaeal amoA gene abundances increased with depth, suggesting that the metabolism of Crenarchaeota may change from the epi- to meso- or bathypelagic zones. Denaturing gradient gel electrophoresis profiling of the 16S rRNA genes revealed depth partitioning in archaeal community structures. Clone libraries of crenarchaeal amoA and accA genes showed two clusters: the "shallow" cluster was exclusively derived from epipelagic water and the "deep" cluster was from meso- and/or bathypelagic waters, suggesting that niche partitioning may take place between the shallow and deep marine Crenarchaeota. Overall, our results show strong depth partitioning of crenarchaeal populations in the SCS and suggest a shift in their community structure and ecological function with increasing depth.

sigReannot: an oligo-set re-annotation pipeline based on similarities with the Ensembl transcripts and Unigene clusters.

PubMed

Casel, Pierrot; Moreews, François; Lagarrigue, Sandrine; Klopp, Christophe

2009-07-16

Microarray is a powerful technology enabling to monitor tens of thousands of genes in a single experiment. Most microarrays are now using oligo-sets. The design of the oligo-nucleotides is time consuming and error prone. Genome wide microarray oligo-sets are designed using as large a set of transcripts as possible in order to monitor as many genes as possible. Depending on the genome sequencing state and on the assembly state the knowledge of the existing transcripts can be very different. This knowledge evolves with the different genome builds and gene builds. Once the design is done the microarrays are often used for several years. The biologists working in EADGENE expressed the need of up-to-dated annotation files for the oligo-sets they share including information about the orthologous genes of model species, the Gene Ontology, the corresponding pathways and the chromosomal location. The results of SigReannot on a chicken micro-array used in the EADGENE project compared to the initial annotations show that 23% of the oligo-nucleotide gene annotations were not confirmed, 2% were modified and 1% were added. The interest of this up-to-date annotation procedure is demonstrated through the analysis of real data previously published. SigReannot uses the oligo-nucleotide design procedure criteria to validate the probe-gene link and the Ensembl transcripts as reference for annotation. It therefore produces a high quality annotation based on reference gene sets.

Study of hepatitis B virus gene mutations with enzymatic colorimetry-based DNA microarray.

PubMed

Mao, Hailei; Wang, Huimin; Zhang, Donglei; Mao, Hongju; Zhao, Jianlong; Shi, Jian; Cui, Zhichu

2006-01-01

To establish a modified microarray method for detecting HBV gene mutations in the clinic. Site-specific oligonucleotide probes were immobilized to microarray slides and hybridized to biotin-labeled HBV gene fragments amplified from two-step PCR. Hybridized targets were transferred to nitrocellulose membranes, followed by intensity measurement using BCIP/NBT colorimetry. HBV genes from 99 Hepatitis B patients and 40 healthy blood donors were analyzed. Mutation frequencies of HBV pre-core/core and basic core promoter (BCP) regions were found to be significantly higher in the patient group (42%, 40% versus 2.5%, 5%, P < 0.01). Compared with a traditional fluorescence method, the colorimetry method exhibited the same level of sensitivity and reproducibility. An enzymatic colorimetry-based DNA microarray assay was successfully established to monitor HBV mutations. Pre-core/core and BCP mutations of HBV genes could be major causes of HBV infection in HBeAg-negative patients and could also be relevant to chronicity and aggravation of hepatitis B.

Clustering gene expression data based on predicted differential effects of GV interaction.

PubMed

Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

2005-02-01

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

The Role of 16S rRNA Gene Sequencing in Identification of Microorganisms Misidentified by Conventional Methods

PubMed Central

Petti, C. A.; Polage, C. R.; Schreckenberger, P.

2005-01-01

Traditional methods for microbial identification require the recognition of differences in morphology, growth, enzymatic activity, and metabolism to define genera and species. Full and partial 16S rRNA gene sequencing methods have emerged as useful tools for identifying phenotypically aberrant microorganisms. We report on three bacterial blood isolates from three different College of American Pathologists-certified laboratories that were referred to ARUP Laboratories for definitive identification. Because phenotypic identification suggested unusual organisms not typically associated with the submitted clinical diagnosis, consultation with the Medical Director was sought and further testing was performed including partial 16S rRNA gene sequencing. All three patients had endocarditis, and conventional methods identified isolates from patients A, B, and C as a Facklamia sp., Eubacterium tenue, and a Bifidobacterium sp. 16S rRNA gene sequencing identified the isolates as Enterococcus faecalis, Cardiobacterium valvarum, and Streptococcus mutans, respectively. We conclude that the initial identifications of these three isolates were erroneous, may have misled clinicians, and potentially impacted patient care. 16S rRNA gene sequencing is a more objective identification tool, unaffected by phenotypic variation or technologist bias, and has the potential to reduce laboratory errors. PMID:16333109

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

Identification of New Single Nucleotide Polymorphism-Based Markers for Inter- and Intraspecies Discrimination of Obligate Bacterial Parasites (Pasteuria spp.) of Invertebrates ▿ †

PubMed Central

Mauchline, Tim H.; Knox, Rachel; Mohan, Sharad; Powers, Stephen J.; Kerry, Brian R.; Davies, Keith G.; Hirsch, Penny R.

2011-01-01

Protein-encoding and 16S rRNA genes of Pasteuria penetrans populations from a wide range of geographic locations were examined. Most interpopulation single nucleotide polymorphisms (SNPs) were detected in the 16S rRNA gene. However, in order to fully resolve all populations, these were supplemented with SNPs from protein-encoding genes in a multilocus SNP typing approach. Examination of individual 16S rRNA gene sequences revealed the occurrence of “cryptic” SNPs which were not present in the consensus sequences of any P. penetrans population. Additionally, hierarchical cluster analysis separated P. penetrans 16S rRNA gene clones into four groups, and one of which contained sequences from the most highly passaged population, demonstrating that it is possible to manipulate the population structure of this fastidious bacterium. The other groups were made from representatives of the other populations in various proportions. Comparison of sequences among three Pasteuria species, namely, P. penetrans, P. hartismeri, and P. ramosa, showed that the protein-encoding genes provided greater discrimination than the 16S rRNA gene. From these findings, we have developed a toolbox for the discrimination of Pasteuria at both the inter- and intraspecies levels. We also provide a model to monitor genetic variation in other obligate hyperparasites and difficult-to-culture microorganisms. PMID:21803895

Identification of new single nucleotide polymorphism-based markers for inter- and intraspecies discrimination of obligate bacterial parasites (Pasteuria spp.) of invertebrates.

PubMed

Mauchline, Tim H; Knox, Rachel; Mohan, Sharad; Powers, Stephen J; Kerry, Brian R; Davies, Keith G; Hirsch, Penny R

2011-09-01

Protein-encoding and 16S rRNA genes of Pasteuria penetrans populations from a wide range of geographic locations were examined. Most interpopulation single nucleotide polymorphisms (SNPs) were detected in the 16S rRNA gene. However, in order to fully resolve all populations, these were supplemented with SNPs from protein-encoding genes in a multilocus SNP typing approach. Examination of individual 16S rRNA gene sequences revealed the occurrence of "cryptic" SNPs which were not present in the consensus sequences of any P. penetrans population. Additionally, hierarchical cluster analysis separated P. penetrans 16S rRNA gene clones into four groups, and one of which contained sequences from the most highly passaged population, demonstrating that it is possible to manipulate the population structure of this fastidious bacterium. The other groups were made from representatives of the other populations in various proportions. Comparison of sequences among three Pasteuria species, namely, P. penetrans, P. hartismeri, and P. ramosa, showed that the protein-encoding genes provided greater discrimination than the 16S rRNA gene. From these findings, we have developed a toolbox for the discrimination of Pasteuria at both the inter- and intraspecies levels. We also provide a model to monitor genetic variation in other obligate hyperparasites and difficult-to-culture microorganisms.

CYANOBACTERIA AND CYANOTOXINS IN WATER SUPPLY RESERVOIRS – TO DEVELOP AND VALIDATE A MICROARRAY TO TEST FOR CYANOBACTERIA AND CYANOTOXIN GENES IN DRINKING WATER RESERVOIRS AS AN AID TO RISK ASSESSMENT AND MANAGEMENT OF WATER SUPPLIES

EPA Science Inventory

The objective of this study is to develop a microarray to test for cyanobacteria and cyanotoxin genes in drinking water reservoirs as an aid to risk assessment and manages of water supplies. The microarray will include probes recognizing important freshwater cyanobacterial tax...

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

[Typing and subtyping avian influenza virus using DNA microarrays].

PubMed

Yang, Zhongping; Wang, Xiurong; Tian, Lina; Wang, Yu; Chen, Hualan

2008-07-01

Outbreaks of highly pathogenic avian influenza (HPAI) virus has caused great economic loss to the poultry industry and resulted in human deaths in Thailand and Vietnam since 2004. Rapid typing and subtyping of viruses, especially HPAI from clinical specimens, are desirable for taking prompt control measures to prevent spreading of the disease. We described a simultaneous approach using microarray to detect and subtype avian influenza virus (AIV). We designed primers of probe genes and used reverse transcriptase PCR to prepare cDNAs of AIV M gene, H5, H7, H9 subtypes haemagglutinin genes and N1, N2 subtypes neuraminidase genes. They were cloned, sequenced, reamplified and spotted to form a glass-bound microarrays. We labeled samples using Cy3-dUTP by RT-PCR, hybridized and scanned the microarrays to typing and subtyping AIV. The hybridization pattern agreed perfectly with the known grid location of each probe, no cross hybridization could be detected. Examinating of HA subtypes 1 through 15, 30 infected samples and 21 field samples revealed the DNA microarray assay was more sensitive and specific than RT-PCR test and chicken embryo inoculation. It can simultaneously detect and differentiate the main epidemic AIV. The results show that DNA microarray technology is a useful diagnostic method.

Microarray analysis identified Puccinia striiformis f. sp. tritici genes involved in infection and sporulation.

USDA-ARS?s Scientific Manuscript database

Puccinia striiformis f. sp. tritici (Pst) causes stripe rust, one of the most important diseases of wheat worldwide. To identify Pst genes involved in infection and sporulation, a custom oligonucleotide Genechip was made using sequences of 442 genes selected from Pst cDNA libraries. Microarray analy...

[Saccharomyces boulardii reduced intestinal inflammation in mice model of 2,4,6-trinitrobencene sulfonic acid induced colitis: based on microarray].

PubMed

Lee, Sang Kil; Kim, Hyo Jong; Chi, Sung Gil

2010-01-01

Saccharomyces boulardii has been reported to be beneficial in the treatment of inflammatory bowel disease. The aim of this work was to evaluate the effect of S. boulardii in a mice model of 2,4,6-trinitrobencene sulfonic acid (TNBS) induced colitis and analyze the expression of genes in S. boulardii treated mice by microarray. BALB/c mice received TNBS or TNBS and S. boulardii treatment for 4 days. Microarray was performed on total mRNA form colon, and histologic evaluation was also performed. In mice treated with S. boulardii, the histological appearance and mortality rate were significantly restored compared with rats receiving only TNBS. Among 330 genes which were altered by both S. boulardii and TNBS (>2 folds), 193 genes were down-regulated by S. boulardii in microarray. Most of genes which were down-regulated by S. bouardii were functionally classified as inflammatory and immune response related genes. S. boulardii may reduce colonic inflammation along with regulation of inflammatory and immune responsive genes in TNBS-induced colitis.

Implementation of plaid model biclustering method on microarray of carcinoma and adenoma tumor gene expression data

NASA Astrophysics Data System (ADS)

Ardaneswari, Gianinna; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

A Tumor is an abnormal growth of cells that serves no purpose. Carcinoma is a tumor that grows from the top of the cell membrane and the organ adenoma is a benign tumor of the gland-like cells or epithelial tissue. In the field of molecular biology, the development of microarray technology is used in the data store of disease genetic expression. For each of microarray gene, an amount of information is stored for each trait or condition. In gene expression data clustering can be done with a bicluster algorithm, thats clustering method which not only the objects to be clustered, but also the properties or condition of the object. This research proposed Plaid Model Biclustering as one of biclustering method. In this study, we discuss the implementation of Plaid Model Biclustering Method on microarray of Carcinoma and Adenoma tumor gene expression data. From the experimental results, we found three biclusters are formed by Carcinoma gene expression data and four biclusters are formed by Adenoma gene expression data.

Approximate geodesic distances reveal biologically relevant structures in microarray data.

PubMed

Nilsson, Jens; Fioretos, Thoas; Höglund, Mattias; Fontes, Magnus

2004-04-12

Genome-wide gene expression measurements, as currently determined by the microarray technology, can be represented mathematically as points in a high-dimensional gene expression space. Genes interact with each other in regulatory networks, restricting the cellular gene expression profiles to a certain manifold, or surface, in gene expression space. To obtain knowledge about this manifold, various dimensionality reduction methods and distance metrics are used. For data points distributed on curved manifolds, a sensible distance measure would be the geodesic distance along the manifold. In this work, we examine whether an approximate geodesic distance measure captures biological similarities better than the traditionally used Euclidean distance. We computed approximate geodesic distances, determined by the Isomap algorithm, for one set of lymphoma and one set of lung cancer microarray samples. Compared with the ordinary Euclidean distance metric, this distance measure produced more instructive, biologically relevant, visualizations when applying multidimensional scaling. This suggests the Isomap algorithm as a promising tool for the interpretation of microarray data. Furthermore, the results demonstrate the benefit and importance of taking nonlinearities in gene expression data into account.

Robust gene selection methods using weighting schemes for microarray data analysis.

PubMed

Kang, Suyeon; Song, Jongwoo

2017-09-02

A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.

PubMed

Feng, Yinling; Wang, Xuefeng

2017-03-01

In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co‑expression networks and clinical information was adopted, using weighted gene co‑expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co‑pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution‑based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD‑associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis.

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

Punctual mutations in 23S rRNA gene of clarithromycin-resistant Helicobacter pylori in Colombian populations

PubMed Central

Matta, Andrés Jenuer; Zambrano, Diana Carolina; Pazos, Alvaro Jairo

2018-01-01

AIM To characterize punctual mutations in 23S rRNA gene of clarithromycin-resistant Helicobacter pylori (H. pylori) and determine their association with therapeutic failure. METHODS PCR products of 23S rRNA gene V domain of 74 H. pylori isolates; 34 resistant to clarithromycin (29 from a low-risk gastric cancer (GC) population: Tumaco-Colombia, and 5 from a high-risk population: Tuquerres-Colombia) and 40 from a susceptible population (28 from Tumaco and 12 from Túquerres) were sequenced using capillary electrophoresis. The concordance between mutations of V domain 23S rRNA gene of H. pylori and therapeutic failure was determined using the Kappa coefficient and McNemar’s test was performed to determine the relationship between H. pylori mutations and clarithromycin resistance. RESULTS 23S rRNA gene from H. pylori was amplified in 56/74 isolates, of which 25 were resistant to clarithromycin (20 from Tumaco and 5 from Túquerres, respectively). In 17 resistant isolates (13 from Tumaco and 4 from Túquerres) the following mutations were found: A1593T1, A1653G2, C1770T, C1954T1, and G1827C in isolates from Tumaco, and A2144G from Túquerres. The mutations T2183C, A2144G and C2196T in H. pylori isolates resistant to clarithromycin from Colombia are reported for the first time. No association between the H. pylori mutations and in vitro clarithromycin resistance was found. However, therapeutic failure of eradication treatment was associated with mutations of 23S rRNA gene in clarithromycin-resistant H. pylori (κ = 0.71). CONCLUSION The therapeutic failure of eradication treatment in the two populations from Colombia was associated with mutations of the 23S rRNA gene in clarithromycin-resistant H. pylori. PMID:29662291

Diversity and community composition of methanogenic archaea in the rumen of Scottish upland sheep assessed by different methods.

PubMed

Snelling, Timothy J; Genç, Buğra; McKain, Nest; Watson, Mick; Waters, Sinéad M; Creevey, Christopher J; Wallace, R John

2014-01-01

Ruminal archaeomes of two mature sheep grazing in the Scottish uplands were analysed by different sequencing and analysis methods in order to compare the apparent archaeal communities. All methods revealed that the majority of methanogens belonged to the Methanobacteriales order containing the Methanobrevibacter, Methanosphaera and Methanobacteria genera. Sanger sequenced 1.3 kb 16S rRNA gene amplicons identified the main species of Methanobrevibacter present to be a SGMT Clade member Mbb. millerae (≥ 91% of OTUs); Methanosphaera comprised the remainder of the OTUs. The primers did not amplify ruminal Thermoplasmatales-related 16S rRNA genes. Illumina sequenced V6-V8 16S rRNA gene amplicons identified similar Methanobrevibacter spp. and Methanosphaera clades and also identified the Thermoplasmatales-related order as 13% of total archaea. Unusually, both methods concluded that Mbb. ruminantium and relatives from the same clade (RO) were almost absent. Sequences mapping to rumen 16S rRNA and mcrA gene references were extracted from Illumina metagenome data. Mapping of the metagenome data to 16S rRNA gene references produced taxonomic identification to Order level including 2-3% Thermoplasmatales, but was unable to discriminate to species level. Mapping of the metagenome data to mcrA gene references resolved 69% to unclassified Methanobacteriales. Only 30% of sequences were assigned to species level clades: of the sequences assigned to Methanobrevibacter, most mapped to SGMT (16%) and RO (10%) clades. The Sanger 16S amplicon and Illumina metagenome mcrA analyses showed similar species richness (Chao1 Index 19-35), while Illumina metagenome and amplicon 16S rRNA analysis gave lower richness estimates (10-18). The values of the Shannon Index were low in all methods, indicating low richness and uneven species distribution. Thus, although much information may be extracted from the other methods, Illumina amplicon sequencing of the V6-V8 16S rRNA gene would be the method of choice for studying rumen archaeal communities.

[Identification of Hydrocarbon-Oxidizing Dietzia Bacteria from Petroleum Reservoirs Based on Phenotypic Properties and Analysis of the 16S rRNA and gyrB Genes].

PubMed

Nazina, T N; Shumkova, E S; Sokolova, D Sh; Babich, T L; Zhurina, M V; Xue, Yan-Fen; Osipov, G A; Poltaraus, A B; Tourova, T P

2015-01-01

The taxonomic position of hydrocarbon-oxidizing bacterial strains 263 and 32d isolated from formation water of the Daqing petroleum reservoir (PRC) was determined by polyphasic taxonomy techniques, including analysis of the 16S rRNA and the gyrB genes. The major chemotaxonomic characteristics of both strains, including the IV type cell wall, composition of cell wall fatty acids, mycolic acids, and menaquinones, agreed with those typical of Dietzia strains. The DNA G+C content of strains 263 and 32d were 67.8 and 67.6 mol%, respectively. Phylogenetic analysis of the 16S rRNA gene of strain 32d revealed 99.7% similarity to the gene of D. maris, making it possible to identify strain 32d as belonging to this species. The 16S rRNA gene sequence of strain 263 exhibited 99.7 and 99.9% similarity to those of D. natronolimnaea and D. cercidiphylli YIM65002(T), respectively. Analysis of the gyrB genes of the subterranean isolates and of a number of Dietzia type strains confirmed classiffication of strain 32d as a D. maris strain and of strain 263, as a D. natronolimnaea strain. A conclusion was made concerning higher resolving power of phylogenetic analysis of the gyrB gene compared to the 16S rRNA gene analysis in the case of determination of the species position of Dietzia isolates.

The Microarray Revolution: Perspectives from Educators

ERIC Educational Resources Information Center

Brewster, Jay L.; Beason, K. Beth; Eckdahl, Todd T.; Evans, Irene M.

2004-01-01

In recent years, microarray analysis has become a key experimental tool, enabling the analysis of genome-wide patterns of gene expression. This review approaches the microarray revolution with a focus upon four topics: 1) the early development of this technology and its application to cancer diagnostics; 2) a primer of microarray research,…

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.

A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.

PubMed

Wolff, Alexander; Bayerlová, Michaela; Gaedcke, Jochen; Kube, Dieter; Beißbarth, Tim

2018-01-01

Pipeline comparisons for gene expression data are highly valuable for applied real data analyses, as they enable the selection of suitable analysis strategies for the dataset at hand. Such pipelines for RNA-Seq data should include mapping of reads, counting and differential gene expression analysis or preprocessing, normalization and differential gene expression in case of microarray analysis, in order to give a global insight into pipeline performances. Four commonly used RNA-Seq pipelines (STAR/HTSeq-Count/edgeR, STAR/RSEM/edgeR, Sailfish/edgeR, TopHat2/Cufflinks/CuffDiff)) were investigated on multiple levels (alignment and counting) and cross-compared with the microarray counterpart on the level of gene expression and gene ontology enrichment. For these comparisons we generated two matched microarray and RNA-Seq datasets: Burkitt Lymphoma cell line data and rectal cancer patient data. The overall mapping rate of STAR was 98.98% for the cell line dataset and 98.49% for the patient dataset. Tophat's overall mapping rate was 97.02% and 96.73%, respectively, while Sailfish had only an overall mapping rate of 84.81% and 54.44%. The correlation of gene expression in microarray and RNA-Seq data was moderately worse for the patient dataset (ρ = 0.67-0.69) than for the cell line dataset (ρ = 0.87-0.88). An exception were the correlation results of Cufflinks, which were substantially lower (ρ = 0.21-0.29 and 0.34-0.53). For both datasets we identified very low numbers of differentially expressed genes using the microarray platform. For RNA-Seq we checked the agreement of differentially expressed genes identified in the different pipelines and of GO-term enrichment results. In conclusion the combination of STAR aligner with HTSeq-Count followed by STAR aligner with RSEM and Sailfish generated differentially expressed genes best suited for the dataset at hand and in agreement with most of the other transcriptomics pipelines.

ArraySolver: an algorithm for colour-coded graphical display and Wilcoxon signed-rank statistics for comparing microarray gene expression data.

PubMed

Khan, Haseeb Ahmad

2004-01-01

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann-Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n < or = 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform.

ArraySolver: An Algorithm for Colour-Coded Graphical Display and Wilcoxon Signed-Rank Statistics for Comparing Microarray Gene Expression Data

PubMed Central

2004-01-01

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann–Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n ≤ 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform. PMID:18629036

Differential gene expression detection and sample classification using penalized linear regression models.

PubMed

Wu, Baolin

2006-02-15

Differential gene expression detection and sample classification using microarray data have received much research interest recently. Owing to the large number of genes p and small number of samples n (p > n), microarray data analysis poses big challenges for statistical analysis. An obvious problem owing to the 'large p small n' is over-fitting. Just by chance, we are likely to find some non-differentially expressed genes that can classify the samples very well. The idea of shrinkage is to regularize the model parameters to reduce the effects of noise and produce reliable inferences. Shrinkage has been successfully applied in the microarray data analysis. The SAM statistics proposed by Tusher et al. and the 'nearest shrunken centroid' proposed by Tibshirani et al. are ad hoc shrinkage methods. Both methods are simple, intuitive and prove to be useful in empirical studies. Recently Wu proposed the penalized t/F-statistics with shrinkage by formally using the (1) penalized linear regression models for two-class microarray data, showing good performance. In this paper we systematically discussed the use of penalized regression models for analyzing microarray data. We generalize the two-class penalized t/F-statistics proposed by Wu to multi-class microarray data. We formally derive the ad hoc shrunken centroid used by Tibshirani et al. using the (1) penalized regression models. And we show that the penalized linear regression models provide a rigorous and unified statistical framework for sample classification and differential gene expression detection.

A study of metaheuristic algorithms for high dimensional feature selection on microarray data

NASA Astrophysics Data System (ADS)

Dankolo, Muhammad Nasiru; Radzi, Nor Haizan Mohamed; Sallehuddin, Roselina; Mustaffa, Noorfa Haszlinna

2017-11-01

Microarray systems enable experts to examine gene profile at molecular level using machine learning algorithms. It increases the potentials of classification and diagnosis of many diseases at gene expression level. Though, numerous difficulties may affect the efficiency of machine learning algorithms which includes vast number of genes features comprised in the original data. Many of these features may be unrelated to the intended analysis. Therefore, feature selection is necessary to be performed in the data pre-processing. Many feature selection algorithms are developed and applied on microarray which including the metaheuristic optimization algorithms. This paper discusses the application of the metaheuristics algorithms for feature selection in microarray dataset. This study reveals that, the algorithms have yield an interesting result with limited resources thereby saving computational expenses of machine learning algorithms.

Cytokine-related genes and oxidation-related genes detected in preeclamptic placentas.

PubMed

Lee, Gui Se Ra; Joe, Yoon Seong; Kim, Sa Jin; Shin, Jong Chul

2010-10-01

To investigate cytokine- and oxidation-related genes for preeclampsia using DNA microarray analysis. Placentas were collected from 13 normal pregnancies and 13 patients with preeclampsia. Gene expression was studied using DNA microarray. Among significantly expressed genes, we focused on genes associated with cytokines and oxidation, and the results were confirmed using quantitative real time-polymerase chain reaction (QRT-PCR). 415 genes out of 30,940 genes were altered by > or =2-fold in the microarray analysis. 121 up-regulated genes and 294 down-regulated genes were found to be in preeclamptic placenta. Six cytokine-related genes and 5 oxidation-related genes were found from among the 121 up-regulated genes. The cytokine-related genes studied included oncostatin M (OSM), fms-related tyrosine kinase (FLT1) and vascular endothelial growth factor A (VEGFA), and the oxidation-related genes studied included spermine oxidase (SMOX), l cytochrome P450, family 26, subfamily A, polypeptide 1 (CYP26A1), acetate dehydrogenase A (LDHA). These six genes were also significantly higher in placentas from patients with preeclampsia than in those from women with normal pregnancies. The placental tissue of patients with preeclampsia showed significantly higher mRNA expression of these six genes than the normal group, using QRT-PCR. DNA microarray analysis is one of the great methods for simultaneously detecting the functionally associated genes of preeclampsia. The cytokine-related genes such as OSM, FLT1 and VEGFA, and the oxidation-related genes such as LDHA, CYP26A1 and SMOX might prove to be the starting point in the elucidation of the pathogenesis of preeclampsia.

Selective phylogenetic analysis targeting 16S rRNA genes of hyperthermophilic archaea in the deep-subsurface hot biosphere.

PubMed

Kimura, Hiroyuki; Ishibashi, Jun-Ichiro; Masuda, Harue; Kato, Kenji; Hanada, Satoshi

2007-04-01

International drilling projects for the study of microbial communities in the deep-subsurface hot biosphere have been expanded. Core samples obtained by deep drilling are commonly contaminated with mesophilic microorganisms in the drilling fluid, making it difficult to examine the microbial community by 16S rRNA gene clone library analysis. To eliminate mesophilic organism contamination, we previously developed a new method (selective phylogenetic analysis [SePA]) based on the strong correlation between the guanine-plus-cytosine (G+C) contents of the 16S rRNA genes and the optimal growth temperatures of prokaryotes, and we verified the method's effectiveness (H. Kimura, M. Sugihara, K. Kato, and S. Hanada, Appl. Environ. Microbiol. 72:21-27, 2006). In the present study we ascertained SePA's ability to eliminate contamination by archaeal rRNA genes, using deep-sea hydrothermal fluid (117 degrees C) and surface seawater (29.9 degrees C) as substitutes for deep-subsurface geothermal samples and drilling fluid, respectively. Archaeal 16S rRNA gene fragments, PCR amplified from the surface seawater, were denatured at 82 degrees C and completely digested with exonuclease I (Exo I), while gene fragments from the deep-sea hydrothermal fluid remained intact after denaturation at 84 degrees C because of their high G+C contents. An examination using mixtures of DNAs from the two environmental samples showed that denaturation at 84 degrees C and digestion with Exo I completely eliminated archaeal 16S rRNA genes from the surface seawater. Our method was quite useful for culture-independent community analysis of hyperthermophilic archaea in core samples recovered from deep-subsurface geothermal environments.

Best practices for hybridization design in two-colour microarray analysis.

PubMed

Knapen, Dries; Vergauwen, Lucia; Laukens, Kris; Blust, Ronny

2009-07-01

Two-colour microarrays are a popular platform of choice in gene expression studies. Because two different samples are hybridized on a single microarray, and several microarrays are usually needed in a given experiment, there are many possible ways to combine samples on different microarrays. The actual combination employed is commonly referred to as the 'hybridization design'. Different types of hybridization designs have been developed, all aimed at optimizing the experimental setup for the detection of differentially expressed genes while coping with technical noise. Here, we first provide an overview of the different classes of hybridization designs, discussing their advantages and limitations, and then we illustrate the current trends in the use of different hybridization design types in contemporary research.

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.

Archaeal community diversity and abundance changes along a natural salinity gradient in estuarine sediments

PubMed Central

Webster, Gordon; O'Sullivan, Louise A.; Meng, Yiyu; Williams, Angharad S.; Sass, Andrea M.; Watkins, Andrew J.; Parkes, R. John; Weightman, Andrew J.

2014-01-01

Archaea are widespread in marine sediments, but their occurrence and relationship with natural salinity gradients in estuarine sediments is not well understood. This study investigated the abundance and diversity of Archaea in sediments at three sites [Brightlingsea (BR), Alresford (AR) and Hythe (HY)] along the Colne Estuary, using quantitative real-time PCR (qPCR) of 16S rRNA genes, DNA hybridization, Archaea 16S rRNA and mcrA gene phylogenetic analyses. Total archaeal 16S rRNA abundance in sediments were higher in the low-salinity brackish sediments from HY (2–8 × 107 16S rRNA gene copies cm−3) than the high-salinity marine sites from BR and AR (2 × 104–2 × 107 and 4 × 106–2 × 107 16S rRNA gene copies cm−3, respectively), although as a proportion of the total prokaryotes Archaea were higher at BR than at AR or HY. Phylogenetic analysis showed that members of the ‘Bathyarchaeota’ (MCG), Thaumarchaeota and methanogenic Euryarchaeota were the dominant groups of Archaea. The composition of Thaumarchaeota varied with salinity, as only ‘marine’ group I.1a was present in marine sediments (BR). Methanogen 16S rRNA genes from low-salinity sediments at HY were dominated by acetotrophic Methanosaeta and putatively hydrogentrophic Methanomicrobiales, whereas the marine site (BR) was dominated by mcrA genes belonging to methylotrophic Methanococcoides, versatile Methanosarcina and methanotrophic ANME-2a. Overall, the results indicate that salinity and associated factors play a role in controlling diversity and distribution of Archaea in estuarine sediments. PMID:25764553

PhylArray: phylogenetic probe design algorithm for microarray.

PubMed

Militon, Cécile; Rimour, Sébastien; Missaoui, Mohieddine; Biderre, Corinne; Barra, Vincent; Hill, David; Moné, Anne; Gagne, Geneviève; Meier, Harald; Peyretaillade, Eric; Peyret, Pierre

2007-10-01

Microbial diversity is still largely unknown in most environments, such as soils. In order to get access to this microbial 'black-box', the development of powerful tools such as microarrays are necessary. However, the reliability of this approach relies on probe efficiency, in particular sensitivity, specificity and explorative power, in order to obtain an image of the microbial communities that is close to reality. We propose a new probe design algorithm that is able to select microarray probes targeting SSU rRNA at any phylogenetic level. This original approach, implemented in a program called 'PhylArray', designs a combination of degenerate and non-degenerate probes for each target taxon. Comparative experimental evaluations indicate that probes designed with PhylArray yield a higher sensitivity and specificity than those designed by conventional approaches. Applying the combined PhyArray/GoArrays strategy helps to optimize the hybridization performance of short probes. Finally, hybridizations with environmental targets have shown that the use of the PhylArray strategy can draw attention to even previously unknown bacteria.

Optimization of single-base-pair mismatch discrimination in oligonucleotide microarrays

NASA Technical Reports Server (NTRS)

Urakawa, Hidetoshi; El Fantroussi, Said; Smidt, Hauke; Smoot, James C.; Tribou, Erik H.; Kelly, John J.; Noble, Peter A.; Stahl, David A.

2003-01-01

The discrimination between perfect-match and single-base-pair-mismatched nucleic acid duplexes was investigated by using oligonucleotide DNA microarrays and nonequilibrium dissociation rates (melting profiles). DNA and RNA versions of two synthetic targets corresponding to the 16S rRNA sequences of Staphylococcus epidermidis (38 nucleotides) and Nitrosomonas eutropha (39 nucleotides) were hybridized to perfect-match probes (18-mer and 19-mer) and to a set of probes having all possible single-base-pair mismatches. The melting profiles of all probe-target duplexes were determined in parallel by using an imposed temperature step gradient. We derived an optimum wash temperature for each probe and target by using a simple formula to calculate a discrimination index for each temperature of the step gradient. This optimum corresponded to the output of an independent analysis using a customized neural network program. These results together provide an experimental and analytical framework for optimizing mismatch discrimination among all probes on a DNA microarray.

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.

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.

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

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

PubMed

Gusnanto, Arief; Calza, Stefano; Pawitan, Yudi

2007-04-01

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

Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

PubMed

Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar

2016-04-01

Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. Copyright © 2016 Elsevier Inc. All rights reserved.

APPLICATION OF GENE ARRAY TECHNOLOGY IN THE RESEARCH OF CARDIOPULMONARY TOXICITY INDUCED BY PARTICULATE MATTER (PM) AND ITS CONSTITUENTS.

EPA Science Inventory

Because of its ability to provide a "snap-shot" view of expression of large number of genes simultaneously, the microarray technology may be a useful tool to uncover new mechanisms of toxicity. This proposal will use the state-of-the-art gene microarrays and a new bioinformatic t...

Stochastic models for inferring genetic regulation from microarray gene expression data.

PubMed

Tian, Tianhai

2010-03-01

Microarray expression profiles are inherently noisy and many different sources of variation exist in microarray experiments. It is still a significant challenge to develop stochastic models to realize noise in microarray expression profiles, which has profound influence on the reverse engineering of genetic regulation. Using the target genes of the tumour suppressor gene p53 as the test problem, we developed stochastic differential equation models and established the relationship between the noise strength of stochastic models and parameters of an error model for describing the distribution of the microarray measurements. Numerical results indicate that the simulated variance from stochastic models with a stochastic degradation process can be represented by a monomial in terms of the hybridization intensity and the order of the monomial depends on the type of stochastic process. The developed stochastic models with multiple stochastic processes generated simulations whose variance is consistent with the prediction of the error model. This work also established a general method to develop stochastic models from experimental information. 2009 Elsevier Ireland Ltd. All rights reserved.

Toxicity phenotype does not correlate with phylogeny of Cylindrospermopsis raciborskii strains.

PubMed

Stucken, Karina; Murillo, Alejandro A; Soto-Liebe, Katia; Fuentes-Valdés, Juan J; Méndez, Marco A; Vásquez, Mónica

2009-02-01

Cylindrospermopsis raciborskii is a species of freshwater, bloom-forming cyanobacterium. C. raciborskii produces toxins, including cylindrospermopsin (hepatotoxin) and saxitoxin (neurotoxin), although non toxin-producing strains are also observed. In spite of differences in toxicity, C. raciborskii strains comprise a monophyletic group, based upon 16S rRNA gene sequence identities (greater than 99%). We performed phylogenetic analyses; 16S rRNA gene and 16S-23S rRNA gene internally transcribed spacer (ITS-1) sequence comparisons, and genomic DNA restriction fragment length polymorphism (RFLP), resolved by pulsed-field gel electrophoresis (PFGE), of strains of C. raciborskii, obtained mainly from the Australian phylogeographic cluster. Our results showed no correlation between toxic phenotype and phylogenetic association in the Australian strains. Analyses of the 16S rRNA gene and the respective ITS-1 sequences (long L, and short S) showed an independent evolution of each ribosomal operon. The genes putatively involved in the cylindrospermopsin biosynthetic pathway were present in one locus and only in the hepatotoxic strains, demonstrating a common genomic organization for these genes and the absence of mutated or inactivated biosynthetic genes in the non toxic strains. In summary, our results support the hypothesis that the genes involved in toxicity may have been transferred as an island by processes of gene lateral transfer, rather than convergent evolution.

Inference of sigma factor controlled networks by using numerical modeling applied to microarray time series data of the germinating prokaryote.

PubMed

Strakova, Eva; Zikova, Alice; Vohradsky, Jiri

2014-01-01

A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.

Nutrient control of gene expression in Drosophila: microarray analysis of starvation and sugar-dependent response

PubMed Central

Zinke, Ingo; Schütz, Christina S.; Katzenberger, Jörg D.; Bauer, Matthias; Pankratz, Michael J.

2002-01-01

We have identified genes regulated by starvation and sugar signals in Drosophila larvae using whole-genome microarrays. Based on expression profiles in the two nutrient conditions, they were organized into different categories that reflect distinct physiological pathways mediating sugar and fat metabolism, and cell growth. In the category of genes regulated in sugar-fed, but not in starved, animals, there is an upregulation of genes encoding key enzymes of the fat biosynthesis pathway and a downregulation of genes encoding lipases. The highest and earliest activated gene upon sugar ingestion is sugarbabe, a zinc finger protein that is induced in the gut and the fat body. Identification of potential targets using microarrays suggests that sugarbabe functions to repress genes involved in dietary fat breakdown and absorption. The current analysis provides a basis for studying the genetic mechanisms underlying nutrient signalling. PMID:12426388

Methyltransferase That Modifies Guanine 966 of the 16 S rRNA: FUNCTIONAL IDENTIFICATION AND TERTIARY STRUCTURE*

PubMed Central

Lesnyak, Dmitry V.; Osipiuk, Jerzy; Skarina, Tatiana; Sergiev, Petr V.; Bogdanov, Alexey A.; Edwards, Aled; Savchenko, Alexei; Joachimiak, Andrzej; Dontsova, Olga A.

2010-01-01

N2-Methylguanine 966 is located in the loop of Escherichia coli 16 S rRNA helix 31, forming a part of the P-site tRNA-binding pocket. We found yhhF to be a gene encoding for m2G966 specific 16 S rRNA methyltransferase. Disruption of the yhhF gene by kanamycin resistance marker leads to a loss of modification at G966. The modification could be rescued by expression of recombinant protein from the plasmid carrying the yhhF gene. Moreover, purified m2G966 methyltransferase, in the presence of S-adenosylomethionine (AdoMet), is able to methylate 30 S ribosomal subunits that were purified from yhhF knock-out strain in vitro. The methylation is specific for G966 base of the 16 S rRNA. The m2G966 methyltransferase was crystallized, and its structure has been determined and refined to 2.05 Å. The structure closely resembles RsmC rRNA methyltransferase, specific for m2G1207 of the 16 S rRNA. Structural comparisons and analysis of the enzyme active site suggest modes for binding AdoMet and rRNA to m2G966 methyltransferase. Based on the experimental data and current nomenclature the protein expressed from the yhhF gene was renamed to RsmD. A model for interaction of RsmD with ribosome has been proposed. PMID:17189261

Methyltransferase that modifies guanine 966 of the 16 S rRNA: functional identification and tertiary structure.

PubMed

Lesnyak, Dmitry V; Osipiuk, Jerzy; Skarina, Tatiana; Sergiev, Petr V; Bogdanov, Alexey A; Edwards, Aled; Savchenko, Alexei; Joachimiak, Andrzej; Dontsova, Olga A

2007-02-23

N(2)-Methylguanine 966 is located in the loop of Escherichia coli 16 S rRNA helix 31, forming a part of the P-site tRNA-binding pocket. We found yhhF to be a gene encoding for m(2)G966 specific 16 S rRNA methyltransferase. Disruption of the yhhF gene by kanamycin resistance marker leads to a loss of modification at G966. The modification could be rescued by expression of recombinant protein from the plasmid carrying the yhhF gene. Moreover, purified m(2)G966 methyltransferase, in the presence of S-adenosylomethionine (AdoMet), is able to methylate 30 S ribosomal subunits that were purified from yhhF knock-out strain in vitro. The methylation is specific for G966 base of the 16 S rRNA. The m(2)G966 methyltransferase was crystallized, and its structure has been determined and refined to 2.05A(.) The structure closely resembles RsmC rRNA methyltransferase, specific for m(2)G1207 of the 16 S rRNA. Structural comparisons and analysis of the enzyme active site suggest modes for binding AdoMet and rRNA to m(2)G966 methyltransferase. Based on the experimental data and current nomenclature the protein expressed from the yhhF gene was renamed to RsmD. A model for interaction of RsmD with ribosome has been proposed.

Fermented Milk Containing Lactobacillus casei Strain Shirota Preserves the Diversity of the Gut Microbiota and Relieves Abdominal Dysfunction in Healthy Medical Students Exposed to Academic Stress.

PubMed

Kato-Kataoka, Akito; Nishida, Kensei; Takada, Mai; Kawai, Mitsuhisa; Kikuchi-Hayakawa, Hiroko; Suda, Kazunori; Ishikawa, Hiroshi; Gondo, Yusuke; Shimizu, Kensuke; Matsuki, Takahiro; Kushiro, Akira; Hoshi, Ryoutaro; Watanabe, Osamu; Igarashi, Tomoki; Miyazaki, Kouji; Kuwano, Yuki; Rokutan, Kazuhito

2016-06-15

Stress-induced abdominal dysfunction is an attractive target for probiotics. To investigate the effects of the probiotic Lactobacillus casei strain Shirota on abdominal dysfunction, a double-blind, placebo-controlled trial was conducted with healthy medical students undertaking an authorized nationwide examination for academic advancement. For 8 weeks, until the day before the examination, 23 and 24 subjects consumed an L. casei strain Shirota-fermented milk and a placebo milk daily, respectively. In addition to assessments of abdominal symptoms, psychophysical state, and salivary stress markers, gene expression changes in peripheral blood leukocytes and composition of the gut microbiota were analyzed using DNA microarray analysis and 16S rRNA gene amplicon sequence analysis, respectively, before and after the intervention. Stress-induced increases in a visual analog scale measuring feelings of stress, the total score of abdominal dysfunction, and the number of genes with changes in expression of more than 2-fold in leukocytes were significantly suppressed in the L. casei strain Shirota group compared with those in the placebo group. A significant increase in salivary cortisol levels before the examination was observed only in the placebo group. The administration of L. casei strain Shirota, but not placebo, significantly reduced gastrointestinal symptoms. Moreover, 16S rRNA gene amplicon sequencing demonstrated that the L. casei strain Shirota group had significantly higher numbers of species, a marker of the alpha-diversity index, in their gut microbiota and a significantly lower percentage of Bacteroidaceae than the placebo group. Our findings indicate that the daily consumption of probiotics, such as L. casei strain Shirota, preserves the diversity of the gut microbiota and may relieve stress-associated responses of abdominal dysfunction in healthy subjects exposed to stressful situations. A novel clinical trial was conducted with healthy medical students under examination stress conditions. It was demonstrated that the daily consumption of lactic acid bacteria provided health benefits to prevent the onset of stress-associated abdominal symptoms and a good change of gut microbiota in healthy medical students. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Isolation of temperature-sensitive mutants of 16 S rRNA in Escherichia coli.

PubMed

Triman, K; Becker, E; Dammel, C; Katz, J; Mori, H; Douthwaite, S; Yapijakis, C; Yoast, S; Noller, H F

1989-10-20

Temperature-sensitive mutants have been isolated following hydroxylamine mutagenesis of a plasmid containing Escherichia coli rRNA genes carrying selectable markers for spectinomycin resistance (U1192 in 16 S rRNA) and erythromycin resistance (G2058 in 23 S rRNA). These antibiotic resistance alleles, originally identified by Morgan and co-workers, enable us to follow expression of cloned rRNA genes in vivo. Recessive mutations causing the loss of expression of the cloned 16 S rRNA gene were identified by the loss of the ability of cells to survive on media containing spectinomycin. The mutations were localized by in vitro restriction fragment replacement followed by in vivo marker rescue and were identified by DNA sequence analysis. We report here seven single-base alterations in 16 S rRNA (A146, U153, A350, A359, A538, A1292 and U1293), five of which produce temperature-sensitive spectinomycin resistance and two that produce unconditional loss of resistance. In each case, loss of ribosomal function can be accounted for by disruption of base-pairing in the secondary structure of 16 S rRNA. For the temperature-sensitive mutants, there is a lag period of about two generations between a shift to the restrictive temperature and cessation of growth, implying that the structural defects cause impairment of ribosome assembly.

Analysis and modelling of septic shock microarray data using Singular Value Decomposition.

PubMed

Allanki, Srinivas; Dixit, Madhulika; Thangaraj, Paul; Sinha, Nandan Kumar

2017-06-01

Being a high throughput technique, enormous amounts of microarray data has been generated and there arises a need for more efficient techniques of analysis, in terms of speed and accuracy. Finding the differentially expressed genes based on just fold change and p-value might not extract all the vital biological signals that occur at a lower gene expression level. Besides this, numerous mathematical models have been generated to predict the clinical outcome from microarray data, while very few, if not none, aim at predicting the vital genes that are important in a disease progression. Such models help a basic researcher narrow down and concentrate on a promising set of genes which leads to the discovery of gene-based therapies. In this article, as a first objective, we have used the lesser known and used Singular Value Decomposition (SVD) technique to build a microarray data analysis tool that works with gene expression patterns and intrinsic structure of the data in an unsupervised manner. We have re-analysed a microarray data over the clinical course of Septic shock from Cazalis et al. (2014) and have shown that our proposed analysis provides additional information compared to the conventional method. As a second objective, we developed a novel mathematical model that predicts a set of vital genes in the disease progression that works by generating samples in the continuum between health and disease, using a simple normal-distribution-based random number generator. We also verify that most of the predicted genes are indeed related to septic shock. Copyright © 2017 Elsevier Inc. All rights reserved.

Detection and Identification of Gastrointestinal Lactobacillus Species by Using Denaturing Gradient Gel Electrophoresis and Species-Specific PCR Primers

PubMed Central

Walter, J.; Tannock, G. W.; Tilsala-Timisjarvi, A.; Rodtong, S.; Loach, D. M.; Munro, K.; Alatossava, T.

2000-01-01

Denaturing gradient gel electrophoresis (DGGE) of DNA fragments obtained by PCR amplification of the V2-V3 region of the 16S rRNA gene was used to detect the presence of Lactobacillus species in the stomach contents of mice. Lactobacillus isolates cultured from human and porcine gastrointestinal samples were identified to the species level by using a combination of DGGE and species-specific PCR primers that targeted 16S-23S rRNA intergenic spacer region or 16S rRNA gene sequences. The identifications obtained by this approach were confirmed by sequencing the V2-V3 region of the 16S rRNA gene and by a BLAST search of the GenBank database. PMID:10618239

A comparative study of COI and 16 S rRNA genes for DNA barcoding of cultivable carps in India.

PubMed

Mohanty, Mausumee; Jayasankar, Pallipuram; Sahoo, Lakshman; Das, Paramananda

2015-02-01

The 5' region of the mitochondrial DNA gene cytochrome c oxidase subunit I (COI) is the standard marker for DNA barcoding. However, 16 S rRNA has also been advocated for DNA barcoding in many animal species. Herein, we directly compare the usefulness of COI and 16 S rRNA in discriminating six cultivable carp species: Labeo rohita, Catla catla, Cirrhinus mrigala, Labeo fimbriatus, Labeo bata and Cirrhinus reba from India. Analysis of partial sequences of these two gene fragments from 171 individuals indicated close genetic relationship between Catla catla and Labeo rohita. The results of the present study indicated COI to be more useful than 16 S rRNA for DNA barcoding of Indian carps.

Redescriptions of three trachelocercid ciliates (Protista, Ciliophora, Karyorelictea), with notes on their phylogeny based on small subunit rRNA gene sequences.

PubMed

Yan, Ying; Xu, Yuan; Yi, Zhenzhen; Warren, Alan

2013-09-01

Three trachelocercid ciliates, Kovalevaia sulcata (Kovaleva, 1966) Foissner, 1997, Trachelocerca sagitta (Müller, 1786) Ehrenberg, 1840 and Trachelocerca ditis (Wright, 1982) Foissner, 1996, isolated from two coastal habitats at Qingdao, China, were investigated using live observation and silver impregnation methods. Data on their infraciliature and morphology are supplied. The small subunit rRNA (SSU rRNA) genes of K. sulcata and Trachelocerca sagitta were sequenced for the first time. Phylogenetic analyses based on SSU rRNA gene sequence data indicate that both organisms, and the previously sequenced Trachelocerca ditis, are located within the trachelocercid assemblage and that K. sulcata is sister to an unidentified taxon forming a clade that is basal to the core trachelocercids.

Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

PubMed

Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

2017-08-07

High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Distinct classical and molecular cytogenetics of Astyanax marionae and A. fasciatus (Characiformes: Characidae): a comparative study of the organization of heterochromatin and repetitive genes.

PubMed

Piscor, Diovani; Centofante, Liano; Parise-Maltempi, Patricia Pasquali

2017-09-01

Genus Astyanax is well distributed in Neotropical freshwater environments and its taxonomic position is uncertain, as is the case with other Characidae genera allocated in the group incertae sedis. This study aimed to analyse the karyotype of different populations of Astyanax fasciatus (Corumbataí River basin) using Giemsa staining, C-band technique, and fluorescence in situ hybridization for the H3 histone and 5S rRNA genes, in addition we describe for the first time the chromosomal organization of H3 histone and 5S rRNAgenes in A. marionae (ParaguayRiver basin). Chromosomes of three A. fasciatus populations were analysed (two with 2n = 50 and one with 2n = 48) and the heterochromatin was organized in two forms (blocks with blurred boundaries and distinct blocks). H3 histone and 5S rRNA genes were observed in all the three populations of A. fasciatus on two chromosome pairs (one metacentric chromosome showing H3 histone and 5S rRNA gene clusters). In A. marionae (2n = 48), H3 histone and 5S rRNA genes were observed in one acrocentric chromosome pair (different pairs). Further, differences between karyotypes and heterochromatin, as well as the chromosomal organization of H3 histone and 5S rRNA genes in Astyanax species, focussing on chromosome evolution in the group are discussed.

Transformation of Chloroplast Ribosomal RNA Genes in Chlamydomonas: Molecular and Genetic Characterization of Integration Events

PubMed Central

Newman, S. M.; Boynton, J. E.; Gillham, N. W.; Randolph-Anderson, B. L.; Johnson, A. M.; Harris, E. H.

1990-01-01

Transformation of chloroplast ribosomal RNA (rRNA) genes in Chlamydomonas has been achieved by the biolistic process using cloned chloroplast DNA fragments carrying mutations that confer antibiotic resistance. The sites of exchange employed during the integration of the donor DNA into the recipient genome have been localized using a combination of antibiotic resistance mutations in the 16S and 23S rRNA genes and restriction fragment length polymorphisms that flank these genes. Complete or nearly complete replacement of a region of the chloroplast genome in the recipient cell by the corresponding sequence from the donor plasmid was the most common integration event. Exchange events between the homologous donor and recipient sequences occurred preferentially near the vector:insert junctions. Insertion of the donor rRNA genes and flanking sequences into one inverted repeat of the recipient genome was followed by intramolecular copy correction so that both copies of the inverted repeat acquired identical sequences. Increased frequencies of rRNA gene transformants were achieved by reducing the copy number of the chloroplast genome in the recipient cells and by decreasing the heterology between donor and recipient DNA sequences flanking the selectable markers. In addition to producing bona fide chloroplast rRNA transformants, the biolistic process induced mutants resistant to low levels of streptomycin, typical of nuclear mutations in Chlamydomonas. PMID:1981764

Complete mitochondrial genome of Cynopterus sphinx (Pteropodidae: Cynopterus).

PubMed

Li, Linmiao; Li, Min; Wu, Zhengjun; Chen, Jinping

2015-01-01

We have characterized the complete mitochondrial genome of Cynopterus sphinx (Pteropodidae: Cynopterus) and described its organization in this study. The total length of C. sphinx complete mitochondrial genome was 16,895 bp with the base composition of 32.54% A, 14.05% G, 25.82% T and 27.59% C. The complete mitochondrial genome included 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes (12S rRNA and 16S rRNA) and 1 control region (D-loop). The control region was 1435 bp long with the sequence CATACG repeat 64 times. Three protein-coding genes (ND1, COI and ND4) were ended with incomplete stop codon TA or T.

Investigation of histone H4 hyperacetylation dynamics in the 5S rRNA genes family by chromatin immunoprecipitation assay.

PubMed

Burlibașa, Liliana; Suciu, Ilinca

2015-12-01

Oogenesis is a critical event in the formation of female gamete, whose role in development is to transfer genomic information to the next generation. During this process, the gene expression pattern changes dramatically concomitant with genome remodelling, while genomic information is stably maintained. The aim of the present study was to investigate the presence of H4 acetylation of the oocyte and somatic 5S rRNA genes in Triturus cristatus, using chromatin immunoprecipitation assay (ChIP). Our findings suggest that some epigenetic mechanisms such as histone acetylation could be involved in the transcriptional regulation of 5S rRNA gene families.

SPERM RNA AMPLIFICATION FOR GENE EXPRESSION PROFILING BY DNA MICROARRAY TECHNOLOGY

EPA Science Inventory

Sperm RNA Amplification for Gene Expression Profiling by DNA Microarray Technology
Hongzu Ren, Kary E. Thompson, Judith E. Schmid and David J. Dix, Reproductive Toxicology Division, NHEERL, Office of Research and Development, US Environmental Protection Agency, Research Triang...

MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

EPA Science Inventory

MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

Dichloroacetic acid (DCA) is a major by-product of water disinfection by chlorination. Several studies have demonstrated the hepatocarcinogenicity of DCA in rodents when administered in dri...

Gene copy number variation and its significance in cyanobacterial phylogeny

PubMed Central

2012-01-01

Background In eukaryotes, variation in gene copy numbers is often associated with deleterious effects, but may also have positive effects. For prokaryotes, studies on gene copy number variation are rare. Previous studies have suggested that high numbers of rRNA gene copies can be advantageous in environments with changing resource availability, but further association of gene copies and phenotypic traits are not documented. We used one of the morphologically most diverse prokaryotic phyla to test whether numbers of gene copies are associated with levels of cell differentiation. Results We implemented a search algorithm that identified 44 genes with highly conserved copies across 22 fully sequenced cyanobacterial taxa. For two very basal cyanobacterial species, Gloeobacter violaceus and a thermophilic Synechococcus species, distinct phylogenetic positions previously found were supported by identical protein coding gene copy numbers. Furthermore, we found that increased ribosomal gene copy numbers showed a strong correlation to cyanobacteria capable of terminal cell differentiation. Additionally, we detected extremely low variation of 16S rRNA sequence copies within the cyanobacteria. We compared our results for 16S rRNA to three other eubacterial phyla (Chroroflexi, Spirochaetes and Bacteroidetes). Based on Bayesian phylogenetic inference and the comparisons of genetic distances, we could confirm that cyanobacterial 16S rRNA paralogs and orthologs show significantly stronger conservation than found in other eubacterial phyla. Conclusions A higher number of ribosomal operons could potentially provide an advantage to terminally differentiated cyanobacteria. Furthermore, we suggest that 16S rRNA gene copies in cyanobacteria are homogenized by both concerted evolution and purifying selection. In addition, the small ribosomal subunit in cyanobacteria appears to evolve at extraordinary slow evolutionary rates, an observation that has been made previously for morphological characteristics of cyanobacteria. PMID:22894826

Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

PubMed

Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

2009-10-27

The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a highly adaptable, integrative, yet flexible tool which can be used for automated quality control, analysis, annotation and visualization of microarray data, constituting a starting point for further data interpretation and integration with numerous other tools.

Diversity and distribution of 16S rRNA and phenol monooxygenase genes in the rhizosphere and endophytic bacteria isolated from PAH-contaminated sites

NASA Astrophysics Data System (ADS)

Peng, Anping; Liu, Juan; Ling, Wanting; Chen, Zeyou; Gao, Yanzheng

2015-07-01

This is the first investigation of the diversity and distribution of 16S rRNA and phenol monooxygenase (PHE) genes in endophytic and rhizosphere bacteria of plants at sites contaminated with different levels of PAHs. Ten PAHs at concentrations from 34.22 to 55.29 and 45.79 to 97.81 mg·kg-1 were measured in rhizosphere soils of Alopecurus aequalis Sobol and Oxalis corniculata L., respectively. The diversity of 16S rRNA and PHE genes in rhizosphere soils or plants changed with varying PAH pollution levels, as shown based on PCR-DGGE data. Generally, higher Shannon-Weiner indexes were found in mild or moderate contaminated areas. A total of 82 different bacterial 16S rRNA gene sequences belonging to five phyla; namely, Acfinobacteria, Proteobacteria, Chloroflexi, Cyanophyta, and Bacteroidetes, were obtained from rhizosphere soils. For the 57 identified PHE gene sequences, 18 were excised from rhizosphere bacteria and 39 from endophytic bacteria. The copy numbers of 16S rRNA and PHE genes in rhizosphere and endophytic bacteria varied from 3.83 × 103 to 2.28 × 106 and 4.17 × 102 to 1.99 × 105, respectively. The copy numbers of PHE genes in rhizosphere bacteria were significantly higher than in endophytic bacteria. Results increase our understanding of the diversity of rhizosphere and endophytic bacteria from plants grown in PAH-contaminated sites.

Nucleosome Translational Position, Not Histone Acetylation, Determines TFIIIA Binding to Nucleosomal Xenopus laevis 5S rRNA Genes

PubMed Central

Howe, LeAnn; Ausió, Juan

1998-01-01

We sought to study the binding constraints placed on the nine-zinc-finger protein transcription factor IIIA (TFIIIA) by a histone octamer. To this end, five overlapping fragments of the Xenopus laevis oocyte and somatic 5S rRNA genes were reconstituted into nucleosomes, and it was subsequently shown that nucleosome translational positioning is a major determinant of the binding of TFIIIA to the 5S rRNA genes. Furthermore, it was found that histone acetylation cannot override the TFIIIA binding constraints imposed by unfavorable translational positions. PMID:9488430

Molecular analysis of the rRNA genes of Babesia spp and Ehrlichia canis detected in dogs from RibeirÃo Preto, Brazil

PubMed Central

Oliveira, L.P.; Cardozo, G.P.; Santos, E.V.; Mansur, M.A.B.; Donini, I.A.N.; Zissou, V.G.; Roberto, P.G.; Marins, M.

2009-01-01

The partial DNA sequences of the 18S rRNA gene of Babesia canis and the 16S rRNA gene of Ehrlichia canis detected in dogs from Ribeirão Preto, Brazil, were compared to sequences from other strains deposited in GenBank. The E. canis strain circulating in Ribeirão Preto is identical to other strains previously detected in the region, whereas the subspecies Babesia canis vogeli is the main Babesia strain circulating in dogs from Ribeirão Preto. PMID:24031351

Characteristics of complete mitogenome of the lesser short-nosed fruit bat Cynopterus brachyotis (Chiroptera: Pteropodidae) in Malaysia.

PubMed

Yoon, Kwang Bae; Kim, Ji Young; Park, Yung Chul

2016-05-01

We describe the characteristics of complete mitogenome of C. brachyotis in this article. The complete mitogenome of C. brachyotis is 16,701 bp long with a total base composition of 32.4% A, 25.7% T, 27.7% C and 14.2% G. The mitogenome consists of 13 protein-coding genes (11,408 bp), (KM659865) two rRNA (12S rRNA and 16S rRNA) genes (2,539 bp), 22 tRNA genes (1518 bp) and one control region (1239 bp).

Comprehensive Analysis of Bacterial Flora in Postoperative Maxillary Cyst Fluid by 16S rRNA Gene and Culture Methods

PubMed Central

Sano, Naoto; Yamashita, Yoshio; Fukuda, Kazumasa; Taniguchi, Hatsumi; Goto, Masaaki; Miyamoto, Hiroshi

2012-01-01

Intracystic fluid was aseptically collected from 11 patients with postoperative maxillary cyst (POMC), and DNA was extracted from the POMC fluid. Bacterial species were identified by sequencing after cloning of approximately 580 bp of the 16S rRNA gene. Identification of pathogenic bacteria was also performed by culture methods. The phylogenetic identity was determined by sequencing 517–596 bp in each of the 1139 16S rRNA gene clones. A total of 1114 clones were classified while the remaining 25 clones were unclassified. A total of 103 bacterial species belonging to 42 genera were identified in POMC fluid samples by 16S rRNA gene analysis. Species of Prevotella (91%), Neisseria (73%), Fusobacterium (73%), Porphyromonas (73%), and Propionibacterium (73%) were found to be highly prevalent in all patients. Streptococcus mitis (64%), Fusobacterium nucleatum (55%), Propionibacterium acnes (55%), Staphylococcus capitis (55%), and Streptococcus salivarius (55%) were detected in more than 6 of the 11 patients. The results obtained by the culture method were different from those obtained by 16S rRNA gene analysis, but both approaches may be necessary for the identification of pathogens, especially of bacteria that are difficult to detect by culture methods, and the development of rational treatments for patients with POMC. PMID:22685668

Derivation of an artificial gene to improve classification accuracy upon gene selection.

PubMed

Seo, Minseok; Oh, Sejong

2012-02-01

Classification analysis has been developed continuously since 1936. This research field has advanced as a result of development of classifiers such as KNN, ANN, and SVM, as well as through data preprocessing areas. Feature (gene) selection is required for very high dimensional data such as microarray before classification work. The goal of feature selection is to choose a subset of informative features that reduces processing time and provides higher classification accuracy. In this study, we devised a method of artificial gene making (AGM) for microarray data to improve classification accuracy. Our artificial gene was derived from a whole microarray dataset, and combined with a result of gene selection for classification analysis. We experimentally confirmed a clear improvement of classification accuracy after inserting artificial gene. Our artificial gene worked well for popular feature (gene) selection algorithms and classifiers. The proposed approach can be applied to any type of high dimensional dataset. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

A proposed metric for assessing the measurement quality of individual microarrays

PubMed Central

Kim, Kyoungmi; Page, Grier P; Beasley, T Mark; Barnes, Stephen; Scheirer, Katherine E; Allison, David B

2006-01-01

Background High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that may introduce error and uncertainty in analyses. These steps include mRNA sample extraction, amplification and labeling, hybridization, and scanning. In some cases this may be manifested as systematic spatial variation on the surface of microarray in which expression measurements within an individual array may vary as a function of geographic position on the array surface. Results We hypothesized that an index of the degree of spatiality of gene expression measurements associated with their physical geographic locations on an array could indicate the summary of the physical reliability of the microarray. We introduced a novel way to formulate this index using a statistical analysis tool. Our approach regressed gene expression intensity measurements on a polynomial response surface of the microarray's Cartesian coordinates. We demonstrated this method using a fixed model and presented results from real and simulated datasets. Conclusion We demonstrated the potential of such a quantitative metric for assessing the reliability of individual arrays. Moreover, we showed that this procedure can be incorporated into laboratory practice as a means to set quality control specifications and as a tool to determine whether an array has sufficient quality to be retained in terms of spatial correlation of gene expression measurements. PMID:16430768

Identification of novel and known oocyte-specific genes using complementary DNA subtraction and microarray analysis in three different species.

PubMed

Vallée, Maud; Gravel, Catherine; Palin, Marie-France; Reghenas, Hélène; Stothard, Paul; Wishart, David S; Sirard, Marc-André

2005-07-01

The main objective of the present study was to identify novel oocyte-specific genes in three different species: bovine, mouse, and Xenopus laevis. To achieve this goal, two powerful technologies were combined: a polymerase chain reaction (PCR)-based cDNA subtraction, and cDNA microarrays. Three subtractive libraries consisting of 3456 clones were established and enriched for oocyte-specific transcripts. Sequencing analysis of the positive insert-containing clones resulted in the following classification: 53% of the clones corresponded to known cDNAs, 26% were classified as uncharacterized cDNAs, and a final 9% were classified as novel sequences. All these clones were used for cDNA microarray preparation. Results from these microarray analyses revealed that in addition to already known oocyte-specific genes, such as GDF9, BMP15, and ZP, known genes with unknown function in the oocyte were identified, such as a MLF1-interacting protein (MLF1IP), B-cell translocation gene 4 (BTG4), and phosphotyrosine-binding protein (xPTB). Furthermore, 15 novel oocyte-specific genes were validated by reverse transcription-PCR to confirm their preferential expression in the oocyte compared to somatic tissues. The results obtained in the present study confirmed that microarray analysis is a robust technique to identify true positives from the suppressive subtractive hybridization experiment. Furthermore, obtaining oocyte-specific genes from three species simultaneously allowed us to look at important genes that are conserved across species. Further characterization of these novel oocyte-specific genes will lead to a better understanding of the molecular mechanisms related to the unique functions found in the oocyte.

New PCR primers targeting hydrazine synthase and cytochrome c biogenesis proteins in anammox bacteria.

PubMed

Zhou, Zhichao; Chen, Jing; Meng, Han; Dvornyk, Volodymyr; Gu, Ji-Dong

2017-02-01

PCR primers targeting genes encoding the two proteins of anammox bacteria, hydrazine synthase and cytochrome c biogenesis protein, were designed and tested in this study. Three different ecotypes of samples, namely ocean sediments, coastal wetland sediments, and wastewater treatment plant (WWTP) samples, were used to assess the primer efficiency and the community structures of anammox bacteria retrieved by 16S ribosomal RNA (rRNA) and the functional genes. Abundances of hzsB gene of anammox bacteria in South China Sea (SCS) samples were significantly correlated with 16S rRNA gene by qPCR method. And hzsB and hzsC gene primer pair hzsB364f-hzsB640r and hzsC745f-hzsC862r in combination with anammox bacterial 16S rRNA gene primers were recommended for quantifying anammox bacteria. Congruent with 16S rRNA gene-based community study, functional gene hzsB could also delineate the coastal-ocean distributing pattern, and seawater depth was positively associated with the diversity and abundance of anammox bacteria from shallow- to deep-sea. Both hzsC and ccsA genes could differentiate marine samples between deep and shallow groups of the Scalindua sp. clades. As for WWTP samples, non-Scalindua anammox bacteria reflected by hzsB, hzsC, ccsA, and ccsB gene-based libraries showed a similar distribution pattern with that by 16S rRNA gene. NH 4 + and NH 4 + /Σ(NO 3 - + NO 2 - ) positively correlated with anammox bacteria gene diversity, but organic matter contents correlated negatively with anammox bacteria gene diversity in SCS. Salinity was positively associated with diversity indices of hzsC and ccsB gene-harboring anammox bacteria communities and could potentially differentiate the distribution patterns between shallow- and deep-sea sediment samples. SCS surface sediments harbored considerably diverse community of Scalindua. A new Mai Po clade representing coastal estuary wetland anammox bacteria group based on 16S rRNA gene phylogeny is proposed. Existence of anammox bacteria within wider coverage of genera in Mai Po wetland indicates this unique niche is very complex, and species of anammox bacteria are niche-specific with different physiological properties towards substrates competing and chemical tolerance capability.

A database for the analysis of immunity genes in Drosophila: PADMA database.

PubMed

Lee, Mark J; Mondal, Ariful; Small, Chiyedza; Paddibhatla, Indira; Kawaguchi, Akira; Govind, Shubha

2011-01-01

While microarray experiments generate voluminous data, discerning trends that support an existing or alternative paradigm is challenging. To synergize hypothesis building and testing, we designed the Pathogen Associated Drosophila MicroArray (PADMA) database for easy retrieval and comparison of microarray results from immunity-related experiments (www.padmadatabase.org). PADMA also allows biologists to upload their microarray-results and compare it with datasets housed within PADMA. We tested PADMA using a preliminary dataset from Ganaspis xanthopoda-infected fly larvae, and uncovered unexpected trends in gene expression, reshaping our hypothesis. Thus, the PADMA database will be a useful resource to fly researchers to evaluate, revise, and refine hypotheses.

Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray

PubMed Central

2010-01-01

Background Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties. Conclusion All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues. PMID:20964859

Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray.

PubMed

Fenart, Stéphane; Ndong, Yves-Placide Assoumou; Duarte, Jorge; Rivière, Nathalie; Wilmer, Jeroen; van Wuytswinkel, Olivier; Lucau, Anca; Cariou, Emmanuelle; Neutelings, Godfrey; Gutierrez, Laurent; Chabbert, Brigitte; Guillot, Xavier; Tavernier, Reynald; Hawkins, Simon; Thomasset, Brigitte

2010-10-21

Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties. All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues.

Influence of the stringent control system on the transcription of ribosomal ribonucleic acid and ribosomal protein genes in Escherichia coli.

PubMed Central

Dennis, P P

1977-01-01

The fraction of the total ribonucleic acid (RNA) synthesis rate that is messenger RNA (mRNA) for ribosomal protein (r-protein) and ribosomal RNA (rRNA) has been estimated in valS(Ts) rel+ stringent and valS(Ts) relA1 relaxed strains of Escherichia coli during a partial inhibition of valyl-transfer RNA aminoacylation. The partial inhibition was accomplished by shifting the strains from the permissive growth temperature of 29.5 degrees C to the semipermissive temperature of 35.5 degrees C. The RNA synthesized at the elevated temperature was pulse labeled with [3H]uracil. The fraction of the total incorpoarted 3H radioactivity in r-protein mRNA or in rRNA was estimated by specific hybridization to the transducing phages gammaspc1, which carries about 15 r-protein genes and lambdailv5, which carries an rRNA transcription unit. The results clearly demonstrate that the rel gene influences the fraction of the total RNA synthesis rate that is r protein mRNA and rRNA; in the rel+ strain they are significantly increased relative to control cultures. This indicates that the expression of the genes coding for the RNA and protein component of the ribosome are most likely regulated at the level of transcription. Furthermore, it appears that the distribution of functioning RNA polymerase between rRNA genes, r-protein genes, and other types of genes is influenced by the rel gene control system; presumably this influence is mediated through the unusual nucleotide guanosine tetraphosphate. PMID:320185

Microarray expression profiling in adhesion and normal peritoneal tissues.

PubMed

Ambler, Dana R; Golden, Alicia M; Gell, Jennifer S; Saed, Ghassan M; Carey, David J; Diamond, Michael P

2012-05-01

To identify molecular markers associated with adhesion and normal peritoneal tissue using microarray expression profiling. Comparative study. University hospital. Five premenopausal women. Adhesion and normal peritoneal tissue samples were obtained from premenopausal women. Ribonucleic acid was extracted using standard protocols and processed for hybridization to Affymetrix Whole Transcript Human Gene Expression Chips. Microarray data were obtained from five different patients, each with adhesion tissue and normal peritoneal samples. Real-time polymerase chain reaction was performed for confirmation using standard protocols. Gene expression in postoperative adhesion and normal peritoneal tissues. A total of 1,263 genes were differentially expressed between adhesion and normal tissues. One hundred seventy-three genes were found to be up-regulated and 56 genes were down-regulated in the adhesion tissues compared with normal peritoneal tissues. The genes were sorted into functional categories according to Gene Ontology annotations. Twenty-six up-regulated genes and 11 down-regulated genes were identified with functions potentially relevant to the pathophysiology of postoperative adhesions. We evaluated and confirmed expression of 12 of these specific genes via polymerase chain reaction. The pathogenesis, natural history, and optimal treatment of postoperative adhesive disease remains unanswered. Microarray analysis of adhesions identified specific genes with increased and decreased expression when compared with normal peritoneum. Knowledge of these genes and ontologic pathways with altered expression provide targets for new therapies to treat patients who have or are at risk for postoperative adhesions. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Multi-membership gene regulation in pathway based microarray analysis

PubMed Central

2011-01-01

Background Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. Results We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. Conclusions We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes. PMID:21939531

Multi-membership gene regulation in pathway based microarray analysis.

PubMed

Pavlidis, Stelios P; Payne, Annette M; Swift, Stephen M

2011-09-22

Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes.

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...

Estimation of gene induction enables a relevance-based ranking of gene sets.

PubMed

Bartholomé, Kilian; Kreutz, Clemens; Timmer, Jens

2009-07-01

In order to handle and interpret the vast amounts of data produced by microarray experiments, the analysis of sets of genes with a common biological functionality has been shown to be advantageous compared to single gene analyses. Some statistical methods have been proposed to analyse the differential gene expression of gene sets in microarray experiments. However, most of these methods either require threshhold values to be chosen for the analysis, or they need some reference set for the determination of significance. We present a method that estimates the number of differentially expressed genes in a gene set without requiring a threshold value for significance of genes. The method is self-contained (i.e., it does not require a reference set for comparison). In contrast to other methods which are focused on significance, our approach emphasizes the relevance of the regulation of gene sets. The presented method measures the degree of regulation of a gene set and is a useful tool to compare the induction of different gene sets and place the results of microarray experiments into the biological context. An R-package is available.

Phylogenetic relationships of Malassezia species based on multilocus sequence analysis.

PubMed

Castellá, Gemma; Coutinho, Selene Dall' Acqua; Cabañes, F Javier

2014-01-01

Members of the genus Malassezia are lipophilic basidiomycetous yeasts, which are part of the normal cutaneous microbiota of humans and other warm-blooded animals. Currently, this genus consists of 14 species that have been characterized by phenetic and molecular methods. Although several molecular methods have been used to identify and/or differentiate Malassezia species, the sequencing of the rRNA genes and the chitin synthase-2 gene (CHS2) are the most widely employed. There is little information about the β-tubulin gene in the genus Malassezia, a gene has been used for the analysis of complex species groups. The aim of the present study was to sequence a fragment of the β-tubulin gene of Malassezia species and analyze their phylogenetic relationship using a multilocus sequence approach based on two rRNA genes (ITS including 5.8S rRNA and D1/D2 region of 26S rRNA) together with two protein encoding genes (CHS2 and β-tubulin). The phylogenetic study of the partial β-tubulin gene sequences indicated that this molecular marker can be used to assess diversity and identify new species. The multilocus sequence analysis of the four loci provides robust support to delineate species at the terminal nodes and could help to estimate divergence times for the origin and diversification of Malassezia species.

A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes

PubMed Central

Seo, Minseok; Shin, Su-kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

2016-01-01

Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of data from experimental microarrays and simulation studies, the proposed model-based approach was shown to provide a more powerful result than the naïve approach and the hierarchical approach. Since our approach is model-based, it is very flexible and can easily handle different types of covariates. PMID:26964035

Automated detection and quantitation of bacterial RNA by using electrical microarrays.

PubMed

Elsholz, B; Wörl, R; Blohm, L; Albers, J; Feucht, H; Grunwald, T; Jürgen, B; Schweder, T; Hintsche, Rainer

2006-07-15

Low-density electrical 16S rRNA specific oligonucleotide microarrays and an automated analysis system have been developed for the identification and quantitation of pathogens. The pathogens are Escherichia coli, Pseudomonas aeruginosa, Enterococcus faecalis, Staphylococcus aureus, and Staphylococcus epidermidis, which are typically involved in urinary tract infections. Interdigitated gold array electrodes (IDA-electrodes), which have structures in the nanometer range, have been used for very sensitive analysis. Thiol-modified oligonucleotides are immobilized on the gold IDA as capture probes. They mediate the specific recognition of the target 16S rRNA by hybridization. Additionally three unlabeled oligonucleotides are hybridized in close proximity to the capturing site. They are supporting molecules, because they improve the RNA hybridization at the capturing site. A biotin labeled detector oligonucleotide is also allowed to hybridize to the captured RNA sequence. The biotin labels enable the binding of avidin alkaline phophatase conjugates. The phosphatase liberates the electrochemical mediator p-aminophenol from its electrically inactive phosphate derivative. The electrical signals were generated by amperometric redox cycling and detected by a unique multipotentiostat. The read out signals of the microarray are position specific current and change over time in proportion to the analyte concentration. If two additional biotins are introduced into the affinity binding complex via the supporting oligonucleotides, the sensitivity of the assays increase more than 60%. The limit of detection of Escherichia coli total RNA has been determined to be 0.5 ng/microL. The control of fluidics for variable assay formats as well as the multichannel electrical read out and data handling have all been fully automated. The fast and easy procedure does not require any amplification of the targeted nucleic acids by PCR.

MADGE: scalable distributed data management software for cDNA microarrays.

PubMed

McIndoe, Richard A; Lanzen, Aaron; Hurtz, Kimberly

2003-01-01

The human genome project and the development of new high-throughput technologies have created unparalleled opportunities to study the mechanism of diseases, monitor the disease progression and evaluate effective therapies. Gene expression profiling is a critical tool to accomplish these goals. The use of nucleic acid microarrays to assess the gene expression of thousands of genes simultaneously has seen phenomenal growth over the past five years. Although commercial sources of microarrays exist, investigators wanting more flexibility in the genes represented on the array will turn to in-house production. The creation and use of cDNA microarrays is a complicated process that generates an enormous amount of information. Effective data management of this information is essential to efficiently access, analyze, troubleshoot and evaluate the microarray experiments. We have developed a distributable software package designed to track and store the various pieces of data generated by a cDNA microarray facility. This includes the clone collection storage data, annotation data, workflow queues, microarray data, data repositories, sample submission information, and project/investigator information. This application was designed using a 3-tier client server model. The data access layer (1st tier) contains the relational database system tuned to support a large number of transactions. The data services layer (2nd tier) is a distributed COM server with full database transaction support. The application layer (3rd tier) is an internet based user interface that contains both client and server side code for dynamic interactions with the user. This software is freely available to academic institutions and non-profit organizations at http://www.genomics.mcg.edu/niddkbtc.

Microarray gene expression profiling analysis combined with bioinformatics in multiple sclerosis.

PubMed

Liu, Mingyuan; Hou, Xiaojun; Zhang, Ping; Hao, Yong; Yang, Yiting; Wu, Xiongfeng; Zhu, Desheng; Guan, Yangtai

2013-05-01

Multiple sclerosis (MS) is the most prevalent demyelinating disease and the principal cause of neurological disability in young adults. Recent microarray gene expression profiling studies have identified several genetic variants contributing to the complex pathogenesis of MS, however, expressional and functional studies are still required to further understand its molecular mechanism. The present study aimed to analyze the molecular mechanism of MS using microarray analysis combined with bioinformatics techniques. We downloaded the gene expression profile of MS from Gene Expression Omnibus (GEO) and analysed the microarray data using the differentially coexpressed genes (DCGs) and links package in R and Database for Annotation, Visualization and Integrated Discovery. The regulatory impact factor (RIF) algorithm was used to measure the impact factor of transcription factor. A total of 1,297 DCGs between MS patients and healthy controls were identified. Functional annotation indicated that these DCGs were associated with immune and neurological functions. Furthermore, the RIF result suggested that IKZF1, BACH1, CEBPB, EGR1, FOS may play central regulatory roles in controlling gene expression in the pathogenesis of MS. Our findings confirm the presence of multiple molecular alterations in MS and indicate the possibility for identifying prognostic factors associated with MS pathogenesis.

Homogeneous versus heterogeneous probes for microbial ecological microarrays.

PubMed

Bae, Jin-Woo; Park, Yong-Ha

2006-07-01

Microbial ecological microarrays have been developed for investigating the composition and functions of microorganism communities in environmental niches. These arrays include microbial identification microarrays, which use oligonucleotides, gene fragments or microbial genomes as probes. In this article, the advantages and disadvantages of each type of probe are reviewed. Oligonucleotide probes are currently useful for probing uncultivated bacteria that are not amenable to gene fragment probing, whereas the functional gene fragments amplified randomly from microbial genomes require phylogenetic and hierarchical categorization before use as microbial identification probes, despite their high resolution for both specificity and sensitivity. Until more bacteria are sequenced and gene fragment probes are thoroughly validated, heterogeneous bacterial genome probes will provide a simple, sensitive and quantitative tool for exploring the ecosystem structure.

Detection and characterization of Pasteuria 16S rRNA gene sequences from nematodes and soils.

PubMed

Duan, Y P; Castro, H F; Hewlett, T E; White, J H; Ogram, A V

2003-01-01

Various bacterial species in the genus Pasteuria have great potential as biocontrol agents against plant-parasitic nematodes, although study of this important genus is hampered by the current inability to cultivate Pasteuria species outside their host. To aid in the study of this genus, an extensive 16S rRNA gene sequence phylogeny was constructed and this information was used to develop cultivation-independent methods for detection of Pasteuria in soils and nematodes. Thirty new clones of Pasteuria 16S rRNA genes were obtained directly from nematodes and soil samples. These were sequenced and used to construct an extensive phylogeny of this genus. These sequences were divided into two deeply branching clades within the low-G + C, Gram-positive division; some sequences appear to represent novel species within the genus Pasteuria. In addition, a surprising degree of 16S rRNA gene sequence diversity was observed within what had previously been designated a single strain of Pasteuria penetrans (P-20). PCR primers specific to Pasteuria 16S rRNA for detection of Pasteuria in soils were also designed and evaluated. Detection limits for soil DNA were 100-10,000 Pasteuria endospores (g soil)(-1).

Microarray Meta-Analysis Identifies Acute Lung Injury Biomarkers in Donor Lungs That Predict Development of Primary Graft Failure in Recipients

PubMed Central

Haitsma, Jack J.; Furmli, Suleiman; Masoom, Hussain; Liu, Mingyao; Imai, Yumiko; Slutsky, Arthur S.; Beyene, Joseph; Greenwood, Celia M. T.; dos Santos, Claudia

2012-01-01

Objectives To perform a meta-analysis of gene expression microarray data from animal studies of lung injury, and to identify an injury-specific gene expression signature capable of predicting the development of lung injury in humans. Methods We performed a microarray meta-analysis using 77 microarray chips across six platforms, two species and different animal lung injury models exposed to lung injury with or/and without mechanical ventilation. Individual gene chips were classified and grouped based on the strategy used to induce lung injury. Effect size (change in gene expression) was calculated between non-injurious and injurious conditions comparing two main strategies to pool chips: (1) one-hit and (2) two-hit lung injury models. A random effects model was used to integrate individual effect sizes calculated from each experiment. Classification models were built using the gene expression signatures generated by the meta-analysis to predict the development of lung injury in human lung transplant recipients. Results Two injury-specific lists of differentially expressed genes generated from our meta-analysis of lung injury models were validated using external data sets and prospective data from animal models of ventilator-induced lung injury (VILI). Pathway analysis of gene sets revealed that both new and previously implicated VILI-related pathways are enriched with differentially regulated genes. Classification model based on gene expression signatures identified in animal models of lung injury predicted development of primary graft failure (PGF) in lung transplant recipients with larger than 80% accuracy based upon injury profiles from transplant donors. We also found that better classifier performance can be achieved by using meta-analysis to identify differentially-expressed genes than using single study-based differential analysis. Conclusion Taken together, our data suggests that microarray analysis of gene expression data allows for the detection of “injury" gene predictors that can classify lung injury samples and identify patients at risk for clinically relevant lung injury complications. PMID:23071521

Role of the Chemokine MCP-1 in Sensitization of PKC-Mediated Apoptosis in Prostate Cancer Cells

DTIC Science & Technology

2010-02-01

component. As phorbol esters are strong inducers of gene expression, we analyzed changes in gene expression using Affymetrix microarrays. These studies...were carried out at the UPenn Microarray Facility. We studied the dynamics of changes in gene expression by PMA at different times between 0 and 24 h...after PMA treatment. We identified ~ 5,000 PMA- genes up- or down-regulated by PMA (> 2-fold change), identified early and late genes , and classified

Automated Identification of Medically Important Bacteria by 16S rRNA Gene Sequencing Using a Novel Comprehensive Database, 16SpathDB▿

PubMed Central

Woo, Patrick C. Y.; Teng, Jade L. L.; Yeung, Juilian M. Y.; Tse, Herman; Lau, Susanna K. P.; Yuen, Kwok-Yung

2011-01-01

Despite the increasing use of 16S rRNA gene sequencing, interpretation of 16S rRNA gene sequence results is one of the most difficult problems faced by clinical microbiologists and technicians. To overcome the problems we encountered in the existing databases during 16S rRNA gene sequence interpretation, we built a comprehensive database, 16SpathDB (http://147.8.74.24/16SpathDB) based on the 16S rRNA gene sequences of all medically important bacteria listed in the Manual of Clinical Microbiology and evaluated its use for automated identification of these bacteria. Among 91 nonduplicated bacterial isolates collected in our clinical microbiology laboratory, 71 (78%) were reported by 16SpathDB as a single bacterial species having >98.0% nucleotide identity with the query sequence, 19 (20.9%) were reported as more than one bacterial species having >98.0% nucleotide identity with the query sequence, and 1 (1.1%) was reported as no match. For the 71 bacterial isolates reported as a single bacterial species, all results were identical to their true identities as determined by a polyphasic approach. For the 19 bacterial isolates reported as more than one bacterial species, all results contained their true identities as determined by a polyphasic approach and all of them had their true identities as the “best match in 16SpathDB.” For the isolate (Gordonibacter pamelaeae) reported as no match, the bacterium has never been reported to be associated with human disease and was not included in the Manual of Clinical Microbiology. 16SpathDB is an automated, user-friendly, efficient, accurate, and regularly updated database for 16S rRNA gene sequence interpretation in clinical microbiology laboratories. PMID:21389154

Archaeal community diversity and abundance changes along a natural salinity gradient in estuarine sediments.

PubMed

Webster, Gordon; O'Sullivan, Louise A; Meng, Yiyu; Williams, Angharad S; Sass, Andrea M; Watkins, Andrew J; Parkes, R John; Weightman, Andrew J

2015-02-01

Archaea are widespread in marine sediments, but their occurrence and relationship with natural salinity gradients in estuarine sediments is not well understood. This study investigated the abundance and diversity of Archaea in sediments at three sites [Brightlingsea (BR), Alresford (AR) and Hythe (HY)] along the Colne Estuary, using quantitative real-time PCR (qPCR) of 16S rRNA genes, DNA hybridization, Archaea 16S rRNA and mcrA gene phylogenetic analyses. Total archaeal 16S rRNA abundance in sediments were higher in the low-salinity brackish sediments from HY (2-8 × 10(7) 16S rRNA gene copies cm(-3)) than the high-salinity marine sites from BR and AR (2 × 10(4)-2 × 10(7) and 4 × 10(6)-2 × 10(7) 16S rRNA gene copies cm(-3), respectively), although as a proportion of the total prokaryotes Archaea were higher at BR than at AR or HY. Phylogenetic analysis showed that members of the 'Bathyarchaeota' (MCG), Thaumarchaeota and methanogenic Euryarchaeota were the dominant groups of Archaea. The composition of Thaumarchaeota varied with salinity, as only 'marine' group I.1a was present in marine sediments (BR). Methanogen 16S rRNA genes from low-salinity sediments at HY were dominated by acetotrophic Methanosaeta and putatively hydrogentrophic Methanomicrobiales, whereas the marine site (BR) was dominated by mcrA genes belonging to methylotrophic Methanococcoides, versatile Methanosarcina and methanotrophic ANME-2a. Overall, the results indicate that salinity and associated factors play a role in controlling diversity and distribution of Archaea in estuarine sediments. © The Author 2014. Published by Oxford University Press on behalf of Federation of European Microbiological Society.

Isolation and identification of multidrug-resistant Staphylococcus haemolyticus from a laboratory-breeding mouse.

PubMed

Huang, Fengying; Meng, Qiuping; Tan, Guanghong; Huang, Yonghao; Wang, Hua; Mei, Wenli; Dai, Haofu

2011-06-01

To analysis and identify a bacterium strain isolated from laboratory breeding mouse far away from a hospital. Phenotype of the isolate was investigated by conventional microbiological methods, including Gram-staining, colony morphology, tests for haemolysis, catalase, coagulase, and antimicrobial susceptibility test. The mecA and 16S rRNA genes were amplified by the polymerase chain reaction (PCR) and sequenced. The base sequence of the PCR product was compared with known 16S rRNA gene sequences in the GenBank database by phylogenetic analysis and multiple sequence alignment. The isolate in this study was a gram positive, coagulase negative, and catalase positive coccus. The isolate was resistant to oxacillin, methicillin, penicillin, ampicillin, cefazolin, ciprofloxacin erythromycin, et al. PCR results indicated that the isolate was mecA gene positive and its 16S rRNA was 1 465 bp. Phylogenetic analysis of the resultant 16S rRNA indicated the isolate belonged to genus Saphylococcus, and multiple sequence alignment showed that the isolate was Saphylococcus haemolyticus with only one base difference from the corresponding 16S rRNA deposited in the GenBank. 16S rRNA gene sequencing is a suitable technique for non-specialist researchers. Laboratory animals are possible sources of lethal pathogens, and researchers must adapt protective measures when they manipulate animals. Copyright © 2011 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline

PubMed Central

Rahmatallah, Yasir; Emmert-Streib, Frank

2016-01-01

Transcriptome sequencing (RNA-seq) is gradually replacing microarrays for high-throughput studies of gene expression. The main challenge of analyzing microarray data is not in finding differentially expressed genes, but in gaining insights into the biological processes underlying phenotypic differences. To interpret experimental results from microarrays, gene set analysis (GSA) has become the method of choice, in particular because it incorporates pre-existing biological knowledge (in a form of functionally related gene sets) into the analysis. Here we provide a brief review of several statistically different GSA approaches (competitive and self-contained) that can be adapted from microarrays practice as well as those specifically designed for RNA-seq. We evaluate their performance (in terms of Type I error rate, power, robustness to the sample size and heterogeneity, as well as the sensitivity to different types of selection biases) on simulated and real RNA-seq data. Not surprisingly, the performance of various GSA approaches depends only on the statistical hypothesis they test and does not depend on whether the test was developed for microarrays or RNA-seq data. Interestingly, we found that competitive methods have lower power as well as robustness to the samples heterogeneity than self-contained methods, leading to poor results reproducibility. We also found that the power of unsupervised competitive methods depends on the balance between up- and down-regulated genes in tested gene sets. These properties of competitive methods have been overlooked before. Our evaluation provides a concise guideline for selecting GSA approaches, best performing under particular experimental settings in the context of RNA-seq. PMID:26342128

In vitro study of the effects of ELF electric fields on gene expression in human epidermal cells.

PubMed

Collard, Jean-Francois; Mertens, Benjamin; Hinsenkamp, Maurice

2011-01-01

An acceleration of differentiation, at the expense of proliferation, is observed after exposure of various biological models to low frequency and low amplitude electric and electromagnetic fields. Following these results showing significant modifications, we try to identify the biological mechanism involved at the cell level through microarray screening. For this study, we use epidermis cultures harvested from human abdominoplasty. Two platinum electrodes are used to apply the electric signal. The gene expressions of 38,500 well-characterized human genes are analyzed using Affymetrix(®) microarray U133 Plus 2.0 chips. The protocol is repeated on three different patients. After three periods of exposure, a total of 24 chips have been processed. After the application of ELF electric fields, the microarray analysis confirms a modification of the gene expression of epidermis cells. Particularly, four up-regulated genes (DKK1, TXNRD1, ATF3, and MME) and one down-regulated gene (MACF1) are involved in the regulation of proliferation and differentiation. Expression of these five genes was also confirmed by real-time rtPCR in all samples used for microarray analysis. These results corroborate an acceleration of cell differentiation at the expense of cell proliferation. © 2010 Wiley-Liss, Inc.

First Report of cfr-Carrying Plasmids in the Pandemic Sequence Type 22 Methicillin-Resistant Staphylococcus aureus Staphylococcal Cassette Chromosome mec Type IV Clone

PubMed Central

Shore, Anna C.; Lazaris, Alexandros; Kinnevey, Peter M.; Brennan, Orla M.; Brennan, Gráinne I.; O'Connell, Brian; Feßler, Andrea T.; Schwarz, Stefan

2016-01-01

Linezolid is often the drug of last resort for serious methicillin-resistant Staphylococcus aureus (MRSA) infections. Linezolid resistance is mediated by mutations in 23S rRNA and genes for ribosomal proteins; cfr, encoding phenicol, lincosamide, oxazolidinone, pleuromutilin, and streptogramin A (PhLOPSA) resistance; its homologue cfr(B); or optrA, conferring oxazolidinone and phenicol resistance. Linezolid resistance is rare in S. aureus, and cfr is even rarer. This study investigated the clonality and linezolid resistance mechanisms of two MRSA isolates from patients in separate Irish hospitals. Isolates were subjected to cfr PCR, PhLOPSA susceptibility testing, 23S rRNA PCR and sequencing, DNA microarray profiling, spa typing, pulsed-field gel electrophoresis (PFGE), plasmid curing, and conjugative transfer. Whole-genome sequencing was used for single-nucleotide variant (SNV) analysis, multilocus sequence typing, L protein mutation identification, cfr plasmid sequence analysis, and optrA and cfr(B) detection. Isolates M12/0145 and M13/0401 exhibited linezolid MICs of 64 and 16 mg/liter, respectively, and harbored identical 23S rRNA and L22 mutations, but M12/0145 exhibited the mutation in 2/6 23S rRNA alleles, compared to 1/5 in M13/0401. Both isolates were sequence type 22 MRSA staphylococcal cassette chromosome mec type IV (ST22-MRSA-IV)/spa type t032 isolates, harbored cfr, exhibited the PhLOPSA phenotype, and lacked optrA and cfr(B). They differed by five PFGE bands and 603 SNVs. Isolate M12/0145 harbored cfr and fexA on a 41-kb conjugative pSCFS3-type plasmid, whereas M13/0401 harbored cfr and lsa(B) on a novel 27-kb plasmid. This is the first report of cfr in the pandemic ST22-MRSA-IV clone. Different cfr plasmids and mutations associated with linezolid resistance in genotypically distinct ST22-MRSA-IV isolates highlight that prudent management of linezolid use is essential. PMID:26953212

Quantitative real-time reverse transcription polymerase chain reaction: normalization to rRNA or single housekeeping genes is inappropriate for human tissue biopsies.

PubMed

Tricarico, Carmela; Pinzani, Pamela; Bianchi, Simonetta; Paglierani, Milena; Distante, Vito; Pazzagli, Mario; Bustin, Stephen A; Orlando, Claudio

2002-10-15

Careful normalization is essential when using quantitative reverse transcription polymerase chain reaction assays to compare mRNA levels between biopsies from different individuals or cells undergoing different treatment. Generally this involves the use of internal controls, such as mRNA specified by a housekeeping gene, ribosomal RNA (rRNA), or accurately quantitated total RNA. The aim of this study was to compare these methods and determine which one can provide the most accurate and biologically relevant quantitative results. Our results show significant variation in the expression levels of 10 commonly used housekeeping genes and 18S rRNA, both between individuals and between biopsies taken from the same patient. Furthermore, in 23 breast cancers samples mRNA and protein levels of a regulated gene, vascular endothelial growth factor (VEGF), correlated only when normalized to total RNA, as did microvessel density. Finally, mRNA levels of VEGF and the most popular housekeeping gene, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), were significantly correlated in the colon. Our results suggest that the use of internal standards comprising single housekeeping genes or rRNA is inappropriate for studies involving tissue biopsies.

[Expression of cell adhesion molecules in acute leukemia cell].

PubMed

Ju, Xiaoping; Peng, Min; Xu, Xiaoping; Lu, Shuqing; Li, Yao; Ying, Kang; Xie, Yi; Mao, Yumin; Xia, Fang

2002-11-01

To investigate the role of cell adhesion molecule in the development and extramedullary infiltration (EI) of acute leukemia. The expressions of neural cell adhesion molecule (NCAM) gene, intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule (VCAM-1) genes in 25 acute leukemia patients bone marrow cells were detected by microarray and reverse transcriptase-polymerase chain reaction (RT-PCR). The expressions of NCAM, ICAM-1 and VCAM-1 gene were significantly higher in acute leukemia cells and leukemia cells with EI than in normal tissues and leukemia cells without EI, respectively, both by cDNA microarray and by RT-PCR. The cDNA microarray is a powerful technique in analysis of acute leukemia cells associated genes. High expressions of cell adhesion molecule genes might be correlated with leukemia pathogenesis and infiltration of acute leukemia cell.

Comparison of 16S rRNA sequencing with biochemical testing for species-level identification of clinical isolates of Neisseria spp.

PubMed

Mechergui, Arij; Achour, Wafa; Ben Hassen, Assia

2014-08-01

We aimed to compare accuracy of genus and species level identification of Neisseria spp. using biochemical testing and 16S rRNA sequence analysis. These methods were evaluated using 85 Neisseria spp. clinical isolates initially identified to the genus level by conventional biochemical tests and API NH system (Bio-Mérieux(®)). In 34 % (29/85), more than one possibility was given by 16S rRNA sequence analysis. In 6 % (5/85), one of the possibilities offered by 16S rRNA gene sequencing, agreed with the result given by biochemical testing. In 4 % (3/85), the same species was given by both methods. 16S rRNA gene sequencing results did not correlate well with biochemical tests.

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.

Soil microbial community successional patterns during forest ecosystem restoration.

PubMed

Banning, Natasha C; Gleeson, Deirdre B; Grigg, Andrew H; Grant, Carl D; Andersen, Gary L; Brodie, Eoin L; Murphy, D V

2011-09-01

Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables.

Soil Microbial Community Successional Patterns during Forest Ecosystem Restoration ▿†

PubMed Central

Banning, Natasha C.; Gleeson, Deirdre B.; Grigg, Andrew H.; Grant, Carl D.; Andersen, Gary L.; Brodie, Eoin L.; Murphy, D. V.

2011-01-01

Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables. PMID:21724890

Microarray analysis of the rat lacrimal gland following the loss of parasympathetic control of secretion

PubMed Central

Nguyen, Doan H.; Toshida, Hiroshi; Schurr, Jill; Beuerman, Roger W.

2010-01-01

Previous studies showed that loss of muscarinic parasympathetic input to the lacrimal gland (LG) leads to a dramatic reduction in tear secretion and profound changes to LG structure. In this study, we used DNA microarrays to examine the regulation of the gene expression of the genes for secretory function and organization of the LG. Long-Evans rats anesthetized with a mixture of ketamine/xylazine (80:10 mg/kg) underwent unilateral sectioning of the greater superficial petrosal nerve, the input to the pterygopalatine ganglion. After 7 days, tear secretion was measured, the animals were killed, and structural changes in the LG were examined by light microscopy. Total RNA from control and experimental LGs (n = 5) was used for DNA microarray analysis employing the U34A GeneChip. Three statistical algorithms (detection, change call, and signal log ratio) were used to determine differential gene expression using the Microarray Suite (5.0) and Data Mining Tools (3.0). Tear secretion was significantly reduced and corneal ulcers developed in all experimental eyes. Light microscopy showed breakdown of the acinar structure of the LG. DNA microarray analysis showed downregulation of genes associated with the endoplasmic reticulum and Golgi, including genes involved in protein folding and processing. Conversely, transcripts for cytoskeleton and extracellular matrix components, inflammation, and apoptosis were upregulated. The number of significantly upregulated genes (116) was substantially greater than the number of downregulated genes (49). Removal of the main secretory input to the rat LG resulted in clinical symptoms associated with severe dry eye. Components of the secretory pathway were negatively affected, and the increase in cell proliferation and inflammation may lead to loss of organization in the parasympathectomized lacrimal gland. PMID:15084711

Structure and variation of the mitochondrial genome of fishes.

PubMed

Satoh, Takashi P; Miya, Masaki; Mabuchi, Kohji; Nishida, Mutsumi

2016-09-07

The mitochondrial (mt) genome has been used as an effective tool for phylogenetic and population genetic analyses in vertebrates. However, the structure and variability of the vertebrate mt genome are not well understood. A potential strategy for improving our understanding is to conduct a comprehensive comparative study of large mt genome data. The aim of this study was to characterize the structure and variability of the fish mt genome through comparative analysis of large datasets. An analysis of the secondary structure of proteins for 250 fish species (248 ray-finned and 2 cartilaginous fishes) illustrated that cytochrome c oxidase subunits (COI, COII, and COIII) and a cytochrome bc1 complex subunit (Cyt b) had substantial amino acid conservation. Among the four proteins, COI was the most conserved, as more than half of all amino acid sites were invariable among the 250 species. Our models identified 43 and 58 stems within 12S rRNA and 16S rRNA, respectively, with larger numbers than proposed previously for vertebrates. The models also identified 149 and 319 invariable sites in 12S rRNA and 16S rRNA, respectively, in all fishes. In particular, the present result verified that a region corresponding to the peptidyl transferase center in prokaryotic 23S rRNA, which is homologous to mt 16S rRNA, is also conserved in fish mt 16S rRNA. Concerning the gene order, we found 35 variations (in 32 families) that deviated from the common gene order in vertebrates. These gene rearrangements were mostly observed in the area spanning the ND5 gene to the control region as well as two tRNA gene cluster regions (IQM and WANCY regions). Although many of such gene rearrangements were unique to a specific taxon, some were shared polyphyletically between distantly related species. Through a large-scale comparative analysis of 250 fish species mt genomes, we elucidated various structural aspects of the fish mt genome and the encoded genes. The present results will be important for understanding functions of the mt genome and developing programs for nucleotide sequence analysis. This study demonstrated the significance of extensive comparisons for understanding the structure of the mt genome.

MicroRNA-integrated and network-embedded gene selection with diffusion distance.

PubMed

Huang, Di; Zhou, Xiaobo; Lyon, Christopher J; Hsueh, Willa A; Wong, Stephen T C

2010-10-29

Gene network information has been used to improve gene selection in microarray-based studies by selecting marker genes based both on their expression and the coordinate expression of genes within their gene network under a given condition. Here we propose a new network-embedded gene selection model. In this model, we first address the limitations of microarray data. Microarray data, although widely used for gene selection, measures only mRNA abundance, which does not always reflect the ultimate gene phenotype, since it does not account for post-transcriptional effects. To overcome this important (critical in certain cases) but ignored-in-almost-all-existing-studies limitation, we design a new strategy to integrate together microarray data with the information of microRNA, the major post-transcriptional regulatory factor. We also handle the challenges led by gene collaboration mechanism. To incorporate the biological facts that genes without direct interactions may work closely due to signal transduction and that two genes may be functionally connected through multi paths, we adopt the concept of diffusion distance. This concept permits us to simulate biological signal propagation and therefore to estimate the collaboration probability for all gene pairs, directly or indirectly-connected, according to multi paths connecting them. We demonstrate, using type 2 diabetes (DM2) as an example, that the proposed strategies can enhance the identification of functional gene partners, which is the key issue in a network-embedded gene selection model. More importantly, we show that our gene selection model outperforms related ones. Genes selected by our model 1) have improved classification capability; 2) agree with biological evidence of DM2-association; and 3) are involved in many well-known DM2-associated pathways.

Complete mitochondrial genome of a wild Siberian tiger.

PubMed

Sun, Yujiao; Lu, Taofeng; Sun, Zhaohui; Guan, Weijun; Liu, Zhensheng; Teng, Liwei; Wang, Shuo; Ma, Yuehui

2015-01-01

In this study, the complete mitochondrial genome of Siberian tiger (Panthera tigris altaica) was sequenced, using muscle tissue obtained from a male wild tiger. The total length of the mitochondrial genome is 16,996 bp. The genome structure of this tiger is in accordance with other Siberian tigers and it contains 12S rRNA gene, 16S rRNA gene, 22 tRNA genes, 13 protein-coding genes, and 1 control region.

mRNA-Seq and microarray development for the Grooved carpet shell clam, Ruditapes decussatus: a functional approach to unravel host -parasite interaction

PubMed Central

2013-01-01

Background The Grooved Carpet shell clam Ruditapes decussatus is the autochthonous European clam and the most appreciated from a gastronomic and economic point of view. The production is in decline due to several factors such as Perkinsiosis and habitat invasion and competition by the introduced exotic species, the manila clam Ruditapes philippinarum. After we sequenced R. decussatus transcriptome we have designed an oligo microarray capable of contributing to provide some clues on molecular response of the clam to Perkinsiosis. Results A database consisting of 41,119 unique transcripts was constructed, of which 12,479 (30.3%) were annotated by similarity. An oligo-DNA microarray platform was then designed and applied to profile gene expression in R. decussatus heavily infected by Perkinsus olseni. Functional annotation of differentially expressed genes between those two conditionswas performed by gene set enrichment analysis. As expected, microarrays unveil genes related with stress/infectious agents such as hydrolases, proteases and others. The extensive role of innate immune system was also analyzed and effect of parasitosis upon expression of important molecules such as lectins reviewed. Conclusions This study represents a first attempt to characterize Ruditapes decussatus transcriptome, an important marine resource for the European aquaculture. The trancriptome sequencing and consequent annotation will increase the available tools and resources for this specie, introducing the possibility of high throughput experiments such as microarrays analysis. In this specific case microarray approach was used to unveil some important aspects of host-parasite interaction between the Carpet shell clam and Perkinsus, two non-model species, highlighting some genes associated with this interaction. Ample information was obtained to identify biological processes significantly enriched among differentially expressed genes in Perkinsus infected versus non-infected gills. An overview on the genes related with the immune system on R. decussatus transcriptome is also reported. PMID:24168212

mRNA-Seq and microarray development for the Grooved Carpet shell clam, Ruditapes decussatus: a functional approach to unravel host-parasite interaction.

PubMed

Leite, Ricardo B; Milan, Massimo; Coppe, Alessandro; Bortoluzzi, Stefania; dos Anjos, António; Reinhardt, Richard; Saavedra, Carlos; Patarnello, Tomaso; Cancela, M Leonor; Bargelloni, Luca

2013-10-29

The Grooved Carpet shell clam Ruditapes decussatus is the autochthonous European clam and the most appreciated from a gastronomic and economic point of view. The production is in decline due to several factors such as Perkinsiosis and habitat invasion and competition by the introduced exotic species, the manila clam Ruditapes philippinarum. After we sequenced R. decussatus transcriptome we have designed an oligo microarray capable of contributing to provide some clues on molecular response of the clam to Perkinsiosis. A database consisting of 41,119 unique transcripts was constructed, of which 12,479 (30.3%) were annotated by similarity. An oligo-DNA microarray platform was then designed and applied to profile gene expression in R. decussatus heavily infected by Perkinsus olseni. Functional annotation of differentially expressed genes between those two conditionswas performed by gene set enrichment analysis. As expected, microarrays unveil genes related with stress/infectious agents such as hydrolases, proteases and others. The extensive role of innate immune system was also analyzed and effect of parasitosis upon expression of important molecules such as lectins reviewed. This study represents a first attempt to characterize Ruditapes decussatus transcriptome, an important marine resource for the European aquaculture. The trancriptome sequencing and consequent annotation will increase the available tools and resources for this specie, introducing the possibility of high throughput experiments such as microarrays analysis. In this specific case microarray approach was used to unveil some important aspects of host-parasite interaction between the Carpet shell clam and Perkinsus, two non-model species, highlighting some genes associated with this interaction. Ample information was obtained to identify biological processes significantly enriched among differentially expressed genes in Perkinsus infected versus non-infected gills. An overview on the genes related with the immune system on R. decussatus transcriptome is also reported.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

PubMed Central

McArt, Darragh G.; Dunne, Philip D.; Blayney, Jaine K.; Salto-Tellez, Manuel; Van Schaeybroeck, Sandra; Hamilton, Peter W.; Zhang, Shu-Dong

2013-01-01

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. PMID:23840550

Gene Expression Analyses of Subchondral Bone in Early Experimental Osteoarthritis by Microarray

PubMed Central

Chen, YuXian; Shen, Jun; Lu, HuaDing; Zeng, Chun; Ren, JianHua; Zeng, Hua; Li, ZhiFu; Chen, ShaoMing; Cai, DaoZhang; Zhao, Qing

2012-01-01

Osteoarthritis (OA) is a degenerative joint disease that affects both cartilage and bone. A better understanding of the early molecular changes in subchondral bone may help elucidate the pathogenesis of OA. We used microarray technology to investigate the time course of molecular changes in the subchondral bone in the early stages of experimental osteoarthritis in a rat model. We identified 2,234 differentially expressed (DE) genes at 1 week, 1,944 at 2 weeks and 1,517 at 4 weeks post-surgery. Further analyses of the dysregulated genes indicated that the events underlying subchondral bone remodeling occurred sequentially and in a time-dependent manner at the gene expression level. Some of the identified dysregulated genes that were identified have suspected roles in bone development or remodeling; these genes include Alp, Igf1, Tgf β1, Postn, Mmp3, Tnfsf11, Acp5, Bmp5, Aspn and Ihh. The differences in the expression of these genes were confirmed by real-time PCR, and the results indicated that our microarray data accurately reflected gene expression patterns characteristic of early OA. To validate the results of our microarray analysis at the protein level, immunohistochemistry staining was used to investigate the expression of Mmp3 and Aspn protein in tissue sections. These analyses indicate that Mmp3 protein expression completely matched the results of both the microarray and real-time PCR analyses; however, Aspn protein expression was not observed to differ at any time. In summary, our study demonstrated a simple method of separation of subchondral bone sample from the knee joint of rat, which can effectively avoid bone RNA degradation. These findings also revealed the gene expression profiles of subchondral bone in the rat OA model at multiple time points post-surgery and identified important DE genes with known or suspected roles in bone development or remodeling. These genes may be novel diagnostic markers or therapeutic targets for OA. PMID:22384228

A New Way to Introduce Microarray Technology in a Lecture/Laboratory Setting by Studying the Evolution of This Modern Technology

ERIC Educational Resources Information Center

Rowland-Goldsmith, Melissa

2009-01-01

DNA microarray is an ordered grid containing known sequences of DNA, which represent many of the genes in a particular organism. Each DNA sequence is unique to a specific gene. This technology enables the researcher to screen many genes from cells or tissue grown in different conditions. We developed an undergraduate lecture and laboratory…

Identification of Bacillus Probiotics Isolated from Soil Rhizosphere Using 16S rRNA, recA, rpoB Gene Sequencing and RAPD-PCR.

PubMed

Mohkam, Milad; Nezafat, Navid; Berenjian, Aydin; Mobasher, Mohammad Ali; Ghasemi, Younes

2016-03-01

Some Bacillus species, especially Bacillus subtilis and Bacillus pumilus groups, have highly similar 16S rRNA gene sequences, which are hard to identify based on 16S rDNA sequence analysis. To conquer this drawback, rpoB, recA sequence analysis along with randomly amplified polymorphic (RAPD) fingerprinting was examined as an alternative method for differentiating Bacillus species. The 16S rRNA, rpoB and recA genes were amplified via a polymerase chain reaction using their specific primers. The resulted PCR amplicons were sequenced, and phylogenetic analysis was employed by MEGA 6 software. Identification based on 16S rRNA gene sequencing was underpinned by rpoB and recA gene sequencing as well as RAPD-PCR technique. Subsequently, concatenation and phylogenetic analysis showed that extent of diversity and similarity were better obtained by rpoB and recA primers, which are also reinforced by RAPD-PCR methods. However, in one case, these approaches failed to identify one isolate, which in combination with the phenotypical method offsets this issue. Overall, RAPD fingerprinting, rpoB and recA along with concatenated genes sequence analysis discriminated closely related Bacillus species, which highlights the significance of the multigenic method in more precisely distinguishing Bacillus strains. This research emphasizes the benefit of RAPD fingerprinting, rpoB and recA sequence analysis superior to 16S rRNA gene sequence analysis for suitable and effective identification of Bacillus species as recommended for probiotic products.

Anaerobic Ammonium-Oxidizing Bacteria in Cow Manure Composting.

PubMed

Wang, Tingting; Cheng, Lijun; Zhang, Wenhao; Xu, Xiuhong; Meng, Qingxin; Sun, Xuewei; Liu, Huajing; Li, Hongtao; Sun, Yu

2017-07-28

Composting is widely used to transform waste into valuable agricultural organic fertilizer. Anaerobic ammonium-oxidizing (anammox) bacteria play an important role in the global nitrogen cycle, but their role in composting remains poorly understood. In the present study, the community structure, diversity, and abundance of anammox bacteria were analyzed using cloning and sequencing methods by targeting the 16S rRNA gene and the hydrazine oxidase gene ( hzo ) in samples isolated from compost produced from cow manure and rice straw. A total of 25 operational taxonomic units were classified based on 16S rRNA gene clone libraries, and 14 operational taxonomic units were classified based on hzo gene clone libraries. The phylogenetic tree analysis of the 16S rRNA gene and deduced HZO protein sequences from the corresponding encoding genes indicated that the majority of the obtained clones were related to the known anammox bacteria Candidatus "Brocadia," Candidatus "Kuenenia," and Candidatus "Scalindua." The abundances of anammox bacteria were determined by quantitative PCR, and between 2.13 × 10 5 and 1.15 × 10 6 16S rRNA gene copies per gram of compost were found. This study provides the first demonstration of the existence of anammox bacteria with limited diversity in cow manure composting.

Streptococcus oricebi sp. nov., isolated from the oral cavity of tufted capuchin.

PubMed

Saito, M; Shinozaki-Kuwahara, N; Hirasawa, M; Takada, K

2016-02-01

A Gram-stain-positive, catalase-negative, coccus-shaped organism was isolated from the oral cavity of tufted capuchin (Cebus apella). Comparative 16S rRNA gene sequence analysis suggested classification of the organism within the genus Streptococcus. Strain M8T was related most closely to Streptococcus oralis ATCC 35037T (96.17 % similarity) followed by Streptococcus massiliensis CCUG 49690T (95.90 %) based on the 16S rRNA gene. Strain M8T was related most closely to S. massiliensis CCUG 49690T (86.58 %) based on the RNA polymerase β subunit-encoding gene (rpoB), and to Streptococcus tigurinus AZ_3aT (81.26 %) followed by S. massiliensis CCUG 49690T (80.45 %) based on the 60 kDa heat-shock protein gene (groEL). The phylogenetic trees of 16S rRNA, rpoB and groEL gene sequences showed that strain M8T was most closely related to S. massiliensis. Based on phenotypic characterization as well as 16S rRNA gene and housekeeping gene (rpoB and groEL) sequence data, a novel taxon, Streptococcus oricebi sp. nov. (type strain M8T = JCM 30719T = DSM 100101T), is proposed.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

PubMed Central

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems. PMID:25961028

Insights into the degradation capacities of Amycolatopsis tucumanensis DSM 45259 guided by microarray data.

PubMed

Bourguignon, Natalia; Bargiela, Rafael; Rojo, David; Chernikova, Tatyana N; de Rodas, Sara A López; García-Cantalejo, Jesús; Näther, Daniela J; Golyshin, Peter N; Barbas, Coral; Ferrero, Marcela; Ferrer, Manuel

2016-12-01

The analysis of catabolic capacities of microorganisms is currently often achieved by cultivation approaches and by the analysis of genomic or metagenomic datasets. Recently, a microarray system designed from curated key aromatic catabolic gene families and key alkane degradation genes was designed. The collection of genes in the microarray can be exploited to indicate whether a given microbe or microbial community is likely to be functionally connected with certain degradative phenotypes, without previous knowledge of genome data. Herein, this microarray was applied to capture new insights into the catabolic capacities of copper-resistant actinomycete Amycolatopsis tucumanensis DSM 45259. The array data support the presumptive ability of the DSM 45259 strain to utilize single alkanes (n-decane and n-tetradecane) and aromatics such as benzoate, phthalate and phenol as sole carbon sources, which was experimentally validated by cultivation and mass spectrometry. Interestingly, while in strain DSM 45259 alkB gene encoding an alkane hydroxylase is most likely highly similar to that found in other actinomycetes, the genes encoding benzoate 1,2-dioxygenase, phthalate 4,5-dioxygenase and phenol hydroxylase were homologous to proteobacterial genes. This suggests that strain DSM 45259 contains catabolic genes distantly related to those found in other actinomycetes. Together, this study not only provided new insight into the catabolic abilities of strain DSM 45259, but also suggests that this strain contains genes uncommon within actinomycetes.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

PubMed

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

Microarray characterization of gene expression changes in blood during acute ethanol exposure

PubMed Central

2013-01-01

Background As part of the civil aviation safety program to define the adverse effects of ethanol on flying performance, we performed a DNA microarray analysis of human whole blood samples from a five-time point study of subjects administered ethanol orally, followed by breathalyzer analysis, to monitor blood alcohol concentration (BAC) to discover significant gene expression changes in response to the ethanol exposure. Methods Subjects were administered either orange juice or orange juice with ethanol. Blood samples were taken based on BAC and total RNA was isolated from PaxGene™ blood tubes. The amplified cDNA was used in microarray and quantitative real-time polymerase chain reaction (RT-qPCR) analyses to evaluate differential gene expression. Microarray data was analyzed in a pipeline fashion to summarize and normalize and the results evaluated for relative expression across time points with multiple methods. Candidate genes showing distinctive expression patterns in response to ethanol were clustered by pattern and further analyzed for related function, pathway membership and common transcription factor binding within and across clusters. RT-qPCR was used with representative genes to confirm relative transcript levels across time to those detected in microarrays. Results Microarray analysis of samples representing 0%, 0.04%, 0.08%, return to 0.04%, and 0.02% wt/vol BAC showed that changes in gene expression could be detected across the time course. The expression changes were verified by qRT-PCR. The candidate genes of interest (GOI) identified from the microarray analysis and clustered by expression pattern across the five BAC points showed seven coordinately expressed groups. Analysis showed function-based networks, shared transcription factor binding sites and signaling pathways for members of the clusters. These include hematological functions, innate immunity and inflammation functions, metabolic functions expected of ethanol metabolism, and pancreatic and hepatic function. Five of the seven clusters showed links to the p38 MAPK pathway. Conclusions The results of this study provide a first look at changing gene expression patterns in human blood during an acute rise in blood ethanol concentration and its depletion because of metabolism and excretion, and demonstrate that it is possible to detect changes in gene expression using total RNA isolated from whole blood. The analysis approach for this study serves as a workflow to investigate the biology linked to expression changes across a time course and from these changes, to identify target genes that could serve as biomarkers linked to pilot performance. PMID:23883607

Employing image processing techniques for cancer detection using microarray images.

PubMed

Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

2017-02-01

Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Genotyping microarray: Mutation screening in Spanish families with autosomal dominant retinitis pigmentosa

PubMed Central

García-Hoyos, María; Cortón, Marta; Ávila-Fernández, Almudena; Riveiro-Álvarez, Rosa; Giménez, Ascensión; Hernan, Inma; Carballo, Miguel; Ayuso, Carmen

2012-01-01

Purpose Presently, 22 genes have been described in association with autosomal dominant retinitis pigmentosa (adRP); however, they explain only 50% of all cases, making genetic diagnosis of this disease difficult and costly. The aim of this study was to evaluate a specific genotyping microarray for its application to the molecular diagnosis of adRP in Spanish patients. Methods We analyzed 139 unrelated Spanish families with adRP. Samples were studied by using a genotyping microarray (adRP). All mutations found were further confirmed with automatic sequencing. Rhodopsin (RHO) sequencing was performed in all negative samples for the genotyping microarray. Results The adRP genotyping microarray detected the mutation associated with the disease in 20 of the 139 families with adRP. As in other populations, RHO was found to be the most frequently mutated gene in these families (7.9% of the microarray genotyped families). The rate of false positives (microarray results not confirmed with sequencing) and false negatives (mutations in RHO detected with sequencing but not with the genotyping microarray) were established, and high levels of analytical sensitivity (95%) and specificity (100%) were found. Diagnostic accuracy was 15.1%. Conclusions The adRP genotyping microarray is a quick, cost-efficient first step in the molecular diagnosis of Spanish patients with adRP. PMID:22736939

Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.

PubMed Central

Galfalvy, Hanga C; Erraji-Benchekroun, Loubna; Smyrniotopoulos, Peggy; Pavlidis, Paul; Ellis, Steven P; Mann, J John; Sibille, Etienne; Arango, Victoria

2003-01-01

Background Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods. Results Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression. Conclusion In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects. PMID:12962547

Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.

PubMed

Galfalvy, Hanga C; Erraji-Benchekroun, Loubna; Smyrniotopoulos, Peggy; Pavlidis, Paul; Ellis, Steven P; Mann, J John; Sibille, Etienne; Arango, Victoria

2003-09-08

Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods. Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression. In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects.

Microarray analyses reveal distinct roles for Rel proteins in the Drosophila immune response

PubMed Central

Pal, Subhamoy; Wu, Junlin; Wu, Louisa P.

2007-01-01

The NF-κB group of transcription factors play an important role in mediating immune responses in organisms as diverse as insects and mammals. The fruit fly Drosophila melanogaster express three closely related NF-κB-like transcription factors: Dorsal, Dif, and Relish. To study their roles in vivo, we used microarrays to determine the effect of null mutations in individual Rel transcription factors on larval immune gene expression. Of the 188 genes that were significantly up-regulated in wildtype larvae upon bacterial challenge, overlapping but distinct groups of genes were affected in the Rel mutants. We also ectopically expressed Dorsal or Dif and used cDNA microarrays to determine the genes that were up-regulated in the presence of these transcription factors. This expression was sufficient to drive expression of some immune genes, suggesting redundancy in the regulation of these genes. Combining this data, we also identified novel genes that may be specific targets of Dif. PMID:17537510

Computerized system for recognition of autism on the basis of gene expression microarray data.

PubMed

Latkowski, Tomasz; Osowski, Stanislaw

2015-01-01

The aim of this paper is to provide a means to recognize a case of autism using gene expression microarrays. The crucial task is to discover the most important genes which are strictly associated with autism. The paper presents an application of different methods of gene selection, to select the most representative input attributes for an ensemble of classifiers. The set of classifiers is responsible for distinguishing autism data from the reference class. Simultaneous application of a few gene selection methods enables analysis of the ill-conditioned gene expression matrix from different points of view. The results of selection combined with a genetic algorithm and SVM classifier have shown increased accuracy of autism recognition. Early recognition of autism is extremely important for treatment of children and increases the probability of their recovery and return to normal social communication. The results of this research can find practical application in early recognition of autism on the basis of gene expression microarray analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fish and chips: Various methodologies demonstrate utility of a 16,006-gene salmonid microarray

PubMed Central

von Schalburg, Kristian R; Rise, Matthew L; Cooper, Glenn A; Brown, Gordon D; Gibbs, A Ross; Nelson, Colleen C; Davidson, William S; Koop, Ben F

2005-01-01

Background We have developed and fabricated a salmonid microarray containing cDNAs representing 16,006 genes. The genes spotted on the array have been stringently selected from Atlantic salmon and rainbow trout expressed sequence tag (EST) databases. The EST databases presently contain over 300,000 sequences from over 175 salmonid cDNA libraries derived from a wide variety of tissues and different developmental stages. In order to evaluate the utility of the microarray, a number of hybridization techniques and screening methods have been developed and tested. Results We have analyzed and evaluated the utility of a microarray containing 16,006 (16K) salmonid cDNAs in a variety of potential experimental settings. We quantified the amount of transcriptome binding that occurred in cross-species, organ complexity and intraspecific variation hybridization studies. We also developed a methodology to rapidly identify and confirm the contents of a bacterial artificial chromosome (BAC) library containing Atlantic salmon genomic DNA. Conclusion We validate and demonstrate the usefulness of the 16K microarray over a wide range of teleosts, even for transcriptome targets from species distantly related to salmonids. We show the potential of the use of the microarray in a variety of experimental settings through hybridization studies that examine the binding of targets derived from different organs and tissues. Intraspecific variation in transcriptome expression is evaluated and discussed. Finally, BAC hybridizations are demonstrated as a rapid and accurate means to identify gene content. PMID:16164747

Detecting novel genes with sparse arrays

PubMed Central

Haiminen, Niina; Smit, Bart; Rautio, Jari; Vitikainen, Marika; Wiebe, Marilyn; Martinez, Diego; Chee, Christine; Kunkel, Joe; Sanchez, Charles; Nelson, Mary Anne; Pakula, Tiina; Saloheimo, Markku; Penttilä, Merja; Kivioja, Teemu

2014-01-01

Species-specific genes play an important role in defining the phenotype of an organism. However, current gene prediction methods can only efficiently find genes that share features such as sequence similarity or general sequence characteristics with previously known genes. Novel sequencing methods and tiling arrays can be used to find genes without prior information and they have demonstrated that novel genes can still be found from extensively studied model organisms. Unfortunately, these methods are expensive and thus are not easily applicable, e.g., to finding genes that are expressed only in very specific conditions. We demonstrate a method for finding novel genes with sparse arrays, applying it on the 33.9 Mb genome of the filamentous fungus Trichoderma reesei. Our computational method does not require normalisations between arrays and it takes into account the multiple-testing problem typical for analysis of microarray data. In contrast to tiling arrays, that use overlapping probes, only one 25mer microarray oligonucleotide probe was used for every 100 b. Thus, only relatively little space on a microarray slide was required to cover the intergenic regions of a genome. The analysis was done as a by-product of a conventional microarray experiment with no additional costs. We found at least 23 good candidates for novel transcripts that could code for proteins and all of which were expressed at high levels. Candidate genes were found to neighbour ire1 and cre1 and many other regulatory genes. Our simple, low-cost method can easily be applied to finding novel species-specific genes without prior knowledge of their sequence properties. PMID:20691772

Supervised group Lasso with applications to microarray data analysis

PubMed Central

Ma, Shuangge; Song, Xiao; Huang, Jian

2007-01-01

Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods. PMID:17316436

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

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.

Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences.

PubMed

Ling, Zhi-Qiang; Wang, Yi; Mukaisho, Kenichi; Hattori, Takanori; Tatsuta, Takeshi; Ge, Ming-Hua; Jin, Li; Mao, Wei-Min; Sugihara, Hiroyuki

2010-06-01

Tests of differentially expressed genes (DEGs) from microarray experiments are based on the null hypothesis that genes that are irrelevant to the phenotype/stimulus are expressed equally in the target and control samples. However, this strict hypothesis is not always true, as there can be several transcriptomic background differences between target and control samples, including different cell/tissue types, different cell cycle stages and different biological donors. These differences lead to increased false positives, which have little biological/medical significance. In this article, we propose a statistical framework to identify DEGs between target and control samples from expression microarray data allowing transcriptomic background differences between these samples by introducing a modified null hypothesis that the gene expression background difference is normally distributed. We use an iterative procedure to perform robust estimation of the null hypothesis and identify DEGs as outliers. We evaluated our method using our own triplicate microarray experiment, followed by validations with reverse transcription-polymerase chain reaction (RT-PCR) and on the MicroArray Quality Control dataset. The evaluations suggest that our technique (i) results in less false positive and false negative results, as measured by the degree of agreement with RT-PCR of the same samples, (ii) can be applied to different microarray platforms and results in better reproducibility as measured by the degree of DEG identification concordance both intra- and inter-platforms and (iii) can be applied efficiently with only a few microarray replicates. Based on these evaluations, we propose that this method not only identifies more reliable and biologically/medically significant DEG, but also reduces the power-cost tradeoff problem in the microarray field. Source code and binaries freely available for download at http://comonca.org.cn/fdca/resources/softwares/deg.zip.

Identification by 16S rRNA gene sequencing of an Actinomyces hongkongensis isolate recovered from a patient with pelvic actinomycosis.

PubMed

Flynn, A N; Lyndon, C A; Church, D L

2013-08-01

A case of Actinomyces hongkongensis pelvic actinomycosis in an adult woman is described. Conventional phenotypic tests failed to identify the Gram-positive bacillus isolated from a fluid aspirate of a pelvic abscess. The bacterium was identified by 16S rRNA gene sequencing and analysis using the SmartGene Integrated Database Network System software.

Experimental Approaches to Microarray Analysis of Tumor Samples

ERIC Educational Resources Information Center

Furge, Laura Lowe; Winter, Michael B.; Meyers, Jacob I.; Furge, Kyle A.

2008-01-01

Comprehensive measurement of gene expression using high-density nucleic acid arrays (i.e. microarrays) has become an important tool for investigating the molecular differences in clinical and research samples. Consequently, inclusion of discussion in biochemistry, molecular biology, or other appropriate courses of microarray technologies has…

CEM-designer: design of custom expression microarrays in the post-ENCODE Era.

PubMed

Arnold, Christian; Externbrink, Fabian; Hackermüller, Jörg; Reiche, Kristin

2014-11-10

Microarrays are widely used in gene expression studies, and custom expression microarrays are popular to monitor expression changes of a customer-defined set of genes. However, the complexity of transcriptomes uncovered recently make custom expression microarray design a non-trivial task. Pervasive transcription and alternative processing of transcripts generate a wealth of interweaved transcripts that requires well-considered probe design strategies and is largely neglected in existing approaches. We developed the web server CEM-Designer that facilitates microarray platform independent design of custom expression microarrays for complex transcriptomes. CEM-Designer covers (i) the collection and generation of a set of unique target sequences from different sources and (ii) the selection of a set of sensitive and specific probes that optimally represents the target sequences. Probe design itself is left to third party software to ensure that probes meet provider-specific constraints. CEM-Designer is available at http://designpipeline.bioinf.uni-leipzig.de. Copyright © 2014 Elsevier B.V. All rights reserved.

Split-plot microarray experiments: issues of design, power and sample size.

PubMed

Tsai, Pi-Wen; Lee, Mei-Ling Ting

2005-01-01

This article focuses on microarray experiments with two or more factors in which treatment combinations of the factors corresponding to the samples paired together onto arrays are not completely random. A main effect of one (or more) factor(s) is confounded with arrays (the experimental blocks). This is called a split-plot microarray experiment. We utilise an analysis of variance (ANOVA) model to assess differentially expressed genes for between-array and within-array comparisons that are generic under a split-plot microarray experiment. Instead of standard t- or F-test statistics that rely on mean square errors of the ANOVA model, we use a robust method, referred to as 'a pooled percentile estimator', to identify genes that are differentially expressed across different treatment conditions. We illustrate the design and analysis of split-plot microarray experiments based on a case application described by Jin et al. A brief discussion of power and sample size for split-plot microarray experiments is also presented.

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.

Feasibility of the salivary transcriptome as a novel biomarker in determining disease susceptibility.

PubMed

Hidayat, M F H; Milne, T; Cullinan, M P; Seymour, G J

2018-06-01

The salivary transcriptome may present as a readily available and non-invasive source of potential biomarkers. The development of chronic periodontitis is determined by individual patient susceptibility; hence, the aim of this study was to determine the potential of the salivary transcriptome as a biomarker of disease susceptibility using chronic periodontitis as an example. Using an Oragene ® RNA kit, the total RNA was purified from the saliva of 10 patients with chronic periodontitis and 10 patients without chronic periodontitis. The quantity and quality of the total RNA was determined, and a measure of gene expression via cDNA was undertaken using the Affymetrix microarray system. The microarray profiling result was further validated by real-time quantitative polymerase chain reaction. Spectrophotometric analysis showed the total RNA purified from each participant ranged from 0.92 μg/500 μL to 62.85 μg/500 μL. There was great variability in the quantity of total RNA obtained from the 2 groups in the study with a mean of 10.21 ± 12.71 μg/500 μL for the periodontitis group and 15.97 ± 23.47 μg/500 μL for the control group. Further the RNA purity (based on the A 260 /A 280 ratio) for the majority of participants (9 periodontitis and 6 controls) were within the acceptable limits for downstream analysis (2.0 ± 0.1). The study samples, showed 2 distinct bands at 23S (3800 bp) and 16S (1500 bp) characteristic of bacterial rRNA. Preliminary microarray analysis was performed for 4 samples (P2, P6, H5 and H9). The percentage of genes present in each of the 4 samples was not consistent with about 1.8%-18.7% of genes being detected. Quantitative real-time polymerase chain reaction confirmed that the total RNA purified from each sample was mainly bacterial RNA (Uni 16S) with minimal human mRNA. This study showed that minimal amounts of human RNA were able to be isolated from the saliva of patients with periodontitis as well as controls. Further work is required to enhance the extraction process of human mRNA from saliva if the salivary transcriptome is to be used in determining individual patient susceptibility. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Gene expression profiling of two distinct neuronal populations in the rodent spinal cord.

PubMed

Ryge, Jesper; Westerdahl, Ann-Charlotte; Alstrøm, Preben; Kiehn, Ole

2008-01-01

In the field of neuroscience microarray gene expression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal populations can in combination with global gene expression profiling potentially increase the resolution and specificity of such studies to shed new light on neuronal functions at the cellular level. We examine the microarray gene expression profiles of two distinct neuronal populations in the spinal cord of the neonatal rat, the principal motor neurons and specific interneurons involved in motor control. The gene expression profiles of the respective cell populations were obtained from amplified mRNA originating from 50-250 fluorescently identified and laser microdissected cells. In the data analysis we combine a new microarray normalization procedure with a conglomerate measure of significant differential gene expression. Using our methodology we find 32 genes to be more expressed in the interneurons compared to the motor neurons that all except one have not previously been associated with this neuronal population. As a validation of our method we find 17 genes to be more expressed in the motor neurons than in the interneurons and of these only one had not previously been described in this population. We provide an optimized experimental protocol that allows isolation of gene transcripts from fluorescent retrogradely labeled cell populations in fresh tissue, which can be used to generate amplified aRNA for microarray hybridization from as few as 50 laser microdissected cells. Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressed genes between the motor neurons and the interneurons that reflect the functional differences between these two cell populations in generating and transmitting the motor output in the rodent spinal cord.

Gene Expression Profiling of Two Distinct Neuronal Populations in the Rodent Spinal Cord

PubMed Central

Alstrøm, Preben; Kiehn, Ole

2008-01-01

Background In the field of neuroscience microarray gene expression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal populations can in combination with global gene expression profiling potentially increase the resolution and specificity of such studies to shed new light on neuronal functions at the cellular level. Methodology/Principal Findings We examine the microarray gene expression profiles of two distinct neuronal populations in the spinal cord of the neonatal rat, the principal motor neurons and specific interneurons involved in motor control. The gene expression profiles of the respective cell populations were obtained from amplified mRNA originating from 50–250 fluorescently identified and laser microdissected cells. In the data analysis we combine a new microarray normalization procedure with a conglomerate measure of significant differential gene expression. Using our methodology we find 32 genes to be more expressed in the interneurons compared to the motor neurons that all except one have not previously been associated with this neuronal population. As a validation of our method we find 17 genes to be more expressed in the motor neurons than in the interneurons and of these only one had not previously been described in this population. Conclusions/Significance We provide an optimized experimental protocol that allows isolation of gene transcripts from fluorescent retrogradely labeled cell populations in fresh tissue, which can be used to generate amplified aRNA for microarray hybridization from as few as 50 laser microdissected cells. Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressed genes between the motor neurons and the interneurons that reflect the functional differences between these two cell populations in generating and transmitting the motor output in the rodent spinal cord. PMID:18923679

Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

PubMed Central

2010-01-01

Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions. PMID:20509979

Sequence of the chloroplast 16S rRNA gene and its surrounding regions of Chlamydomonas reinhardii.

PubMed Central

Dron, M; Rahire, M; Rochaix, J D

1982-01-01

The sequence of a 2 kb DNA fragment containing the chloroplast 16S ribosomal RNA gene from Chlamydomonas reinhardii and its flanking regions has been determined. The algal 16S rRNA sequence (1475 nucleotides) and secondary structure are highly related to those found in bacteria and in the chloroplasts of higher plants. In contrast, the flanking regions are very different. In C. reinhardii the 16S rRNA gene is surrounded by AT rich segments of about 180 bases, which are followed by a long stretch of complementary bases separated from each other by 1833 nucleotides. It is likely that these structures play an important role in the folding and processing of the precursor of 16S rRNA. The primary and secondary structures of the binding sites of two ribosomal proteins in the 16SrRNAs of E. coli and C. reinhardii are considerably related. Images PMID:6296784

Bioluminescent symbionts of the Caribbean flashlight fish (Kryptophanaron alfredi) have a single rRNA operon.

PubMed

Wolfe, C J; Haygood, M G

1993-08-01

Ribosomal RNA (rRNA) operon copy number and gene order were determined for the luminous bacterial symbiont of Kryptophanaron alfredi, an anomalopid (flashlight) fish, and estimated for the luminous symbionts of 3 other fish families and of 3 luminous seawater isolates. Compared with the seawater isolates and other fish symbionts, the copy number of rRNA genes in the K. alfredi symbiont was radically reduced, although gene order appeared conserved among all the strains. The K. alfredi symbiont possesses only a single rRNA operon, whereas the other strains examined have minimum copy numbers ranging from 8 to 11. No difference in copy number was observed between light organ and seawater isolates of the same species, or between isolates of the same species from the light organs of 2 different host families. Thus, the anomalopid symbiosis appears unique among characterized light organ symbioses.

Evaluation of the skin irritation using a DNA microarray on a reconstructed human epidermal model.

PubMed

Niwa, Makoto; Nagai, Kanji; Oike, Hideaki; Kobori, Masuko

2009-02-01

To avoid the need to use animals to test the skin irritancy potential of chemicals and cosmetics, it is important to establish an in vitro method based on the reconstructed human epidermal model. To evaluate skin irritancy efficiently and sensitively, we determined the gene expression induced by a topically-applied mild irritant sodium dodecyl sulfate (SDS) in a reconstructed human epidermal model LabCyte EPI-MODEL (LabCyte) using a DNA microarray carrying genes that were related to inflammation, immunity, stress and housekeeping. The expression and secretion of IL-1alpha in reconstructed human epidermal culture is known to be induced by irritation. We detected the induction of IL-1alpha expression and its secretion into the cell culture medium by treatment with 0.075% SDS for 18 h in LabCyte culture using DNA microarray, quantitative reverse-transcription polymerase chain reaction (RT-PCR) and ELISA. DNA microarray analysis indicated that the expression of 10 of the 205 genes carried on the DNA microarray was significantly induced in a LabCyte culture by 0.05% or 0.075% SDS irritation for 18 h. RT-PCR analysis confirmed that SDS treatment significantly induced the expressions of interleukin-1 receptor antagonist (IL-1RN), FOS-like antigen 1 (FOSL1), heat shock 70 kDa protein 1A (HSPA1) and myeloid differentiation primary response gene (88) (MYD88), as well as the known marker genes for irritation IL-1beta and IL-8 in a LabCyte culture. Our results showed that a DNA microarray is a useful tool for efficiently evaluating mild skin irritation using a reconstructed human epidermal model.

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

A Novel Plasmid-Based Microarray Screen Identifies Suppressors of rrp6Δ in Saccharomyces cerevisiae▿†

PubMed Central

Abruzzi, Katharine; Denome, Sylvia; Olsen, Jens Raabjerg; Assenholt, Jannie; Haaning, Line Lindegaard; Jensen, Torben Heick; Rosbash, Michael

2007-01-01

Genetic screens in Saccharomyces cerevisiae provide novel information about interacting genes and pathways. We screened for high-copy-number suppressors of a strain with the gene encoding the nuclear exosome component Rrp6p deleted, with either a traditional plate screen for suppressors of rrp6Δ temperature sensitivity or a novel microarray enhancer/suppressor screening (MES) strategy. MES combines DNA microarray technology with high-copy-number plasmid expression in liquid media. The plate screen and MES identified overlapping, but also different, suppressor genes. Only MES identified the novel mRNP protein Nab6p and the tRNA transporter Los1p, which could not have been identified in a traditional plate screen; both genes are toxic when overexpressed in rrp6Δ strains at 37°C. Nab6p binds poly(A)+ RNA, and the functions of Nab6p and Los1p suggest that mRNA metabolism and/or protein synthesis are growth rate limiting in rrp6Δ strains. Microarray analyses of gene expression in rrp6Δ strains and a number of suppressor strains support this hypothesis. PMID:17101774

Species-specific identification of Dekkera/Brettanomyces yeasts by fluorescently labeled DNA probes targeting the 26S rRNA.

PubMed

Röder, Christoph; König, Helmut; Fröhlich, Jürgen

2007-09-01

Sequencing of the complete 26S rRNA genes of all Dekkera/Brettanomyces species colonizing different beverages revealed the potential for a specific primer and probe design to support diagnostic PCR approaches and FISH. By analysis of the complete 26S rRNA genes of all five currently known Dekkera/Brettanomyces species (Dekkera bruxellensis, D. anomala, Brettanomyces custersianus, B. nanus and B. naardenensis), several regions with high nucleotide sequence variability yet distinct from the D1/D2 domains were identified. FISH species-specific probes targeting the 26S rRNA gene's most variable regions were designed. Accessibility of probe targets for hybridization was facilitated by the construction of partially complementary 'side'-labeled probes, based on secondary structure models of the rRNA sequences. The specificity and routine applicability of the FISH-based method for yeast identification were tested by analyzing different wine isolates. Investigation of the prevalence of Dekkera/Brettanomyces yeasts in the German viticultural regions Wonnegau, Nierstein and Bingen (Rhinehesse, Rhineland-Palatinate) resulted in the isolation of 37 D. bruxellensis strains from 291 wine samples.

Gene Expression Profiling of Gastric Cancer

PubMed Central

Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

2015-01-01

Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

The nucleotide sequence of the entire ribosomal DNA operon and the structure of the large subunit rRNA of Giardia muris.

PubMed

van Keulen, H; Gutell, R R; Campbell, S R; Erlandsen, S L; Jarroll, E L

1992-10-01

The total nucleotide sequence of the rDNA of Giardia muris, an intestinal protozoan parasite of rodents, has been determined. The repeat unit is 7668 basepairs (bp) in size and consists of a spacer of 3314 bp, a small-subunit rRNA (SSU-rRNA) gene of 1429, and a large-subunit rRNA (LSU-rRNA) gene of 2698 bp. The spacer contains long direct repeats and is heterogeneous in size. The LSU-rRNA of G. muris was compared to that of the human intestinal parasite Giardia duodenalis, to the bird parasite Giardia ardeae, and to that of Escherichia coli. The LSU-rRNA has a size comparable to the 23S rRNA of E. coli but shows structural features typical for eukaryotes. Some variable regions are typically small and account for the overall smaller size of this rRNA. The structure of the G. muris LSU-rRNA is similar to that of the other Giardia rRNA, but each rRNA has characteristic features residing in a number of variable regions.

LS Bound based gene selection for DNA microarray data.

PubMed

Zhou, Xin; Mao, K Z

2005-04-15

One problem with discriminant analysis of DNA microarray data is that each sample is represented by quite a large number of genes, and many of them are irrelevant, insignificant or redundant to the discriminant problem at hand. Methods for selecting important genes are, therefore, of much significance in microarray data analysis. In the present study, a new criterion, called LS Bound measure, is proposed to address the gene selection problem. The LS Bound measure is derived from leave-one-out procedure of LS-SVMs (least squares support vector machines), and as the upper bound for leave-one-out classification results it reflects to some extent the generalization performance of gene subsets. We applied this LS Bound measure for gene selection on two benchmark microarray datasets: colon cancer and leukemia. We also compared the LS Bound measure with other evaluation criteria, including the well-known Fisher's ratio and Mahalanobis class separability measure, and other published gene selection algorithms, including Weighting factor and SVM Recursive Feature Elimination. The strength of the LS Bound measure is that it provides gene subsets leading to more accurate classification results than the filter method while its computational complexity is at the level of the filter method. A companion website can be accessed at http://www.ntu.edu.sg/home5/pg02776030/lsbound/. The website contains: (1) the source code of the gene selection algorithm; (2) the complete set of tables and figures regarding the experimental study; (3) proof of the inequality (9). ekzmao@ntu.edu.sg.

geneCommittee: a web-based tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification.

PubMed

Reboiro-Jato, Miguel; Arrais, Joel P; Oliveira, José Luis; Fdez-Riverola, Florentino

2014-01-30

The diagnosis and prognosis of several diseases can be shortened through the use of different large-scale genome experiments. In this context, microarrays can generate expression data for a huge set of genes. However, to obtain solid statistical evidence from the resulting data, it is necessary to train and to validate many classification techniques in order to find the best discriminative method. This is a time-consuming process that normally depends on intricate statistical tools. geneCommittee is a web-based interactive tool for routinely evaluating the discriminative classification power of custom hypothesis in the form of biologically relevant gene sets. While the user can work with different gene set collections and several microarray data files to configure specific classification experiments, the tool is able to run several tests in parallel. Provided with a straightforward and intuitive interface, geneCommittee is able to render valuable information for diagnostic analyses and clinical management decisions based on systematically evaluating custom hypothesis over different data sets using complementary classifiers, a key aspect in clinical research. geneCommittee allows the enrichment of microarrays raw data with gene functional annotations, producing integrated datasets that simplify the construction of better discriminative hypothesis, and allows the creation of a set of complementary classifiers. The trained committees can then be used for clinical research and diagnosis. Full documentation including common use cases and guided analysis workflows is freely available at http://sing.ei.uvigo.es/GC/.

Use of a 15 k gene microarray to determine gene expression changes in response to acute and chronic methylmercury exposure in the fathead minnow Pimephales promelas Rafinesque

USGS Publications Warehouse

Klaper, R.; Carter, Barbara J.; Richter, C.A.; Drevnick, P.E.; Sandheinrich, M.B.; Tillitt, D.E.

2008-01-01

This study describes the use of a 15 000 gene microarray developed for the toxicological model species, Pimephales promelas, in investigating the impact of acute and chronic methylmercury exposures in male gonad and liver tissues. The results show significant differences in the individual genes that were differentially expressed in response to each treatment. In liver, a total of 650 genes exhibited significantly (P < 0.05) altered expression with greater than two-fold differences from the controls in response to acute exposure and a total of 267 genes were differentially expressed in response to chronic exposure. A majority of these genes were downregulated rather than upregulated. Fewer genes were altered in gonad than in liver at both timepoints. A total of 212 genes were differentially expressed in response to acute exposure and 155 genes were altered in response to chronic exposure. Despite the differences in individual genes expressed across treatments, the functional categories that altered genes were associated with showed some similarities. Of interest in light of other studies involving the effects of methylmercury on fish, several genes associated with apoptosis were upregulated in response to both acute and chronic exposures. Induction of apoptosis has been associated with effects on reproduction seen in the previous studies. This study demonstrates the utility of microarray analysis for investigations of the physiological effects of toxicants as well as the time-course of effects that may take place. In addition, it is the first publication to demonstrate the use of this new 15 000 gene microarray for fish biology and toxicology. ?? 2008 The Authors.

Near-isogenic cotton germplasm lines that differ in fiber-bundle strength have temporal differences in fiber gene expression patterns as revealed by comparative high-throughput profiling.

PubMed

Hinchliffe, Doug J; Meredith, William R; Yeater, Kathleen M; Kim, Hee Jin; Woodward, Andrew W; Chen, Z Jeffrey; Triplett, Barbara A

2010-05-01

Gene expression profiles of developing cotton (Gossypium hirsutum L.) fibers from two near-isogenic lines (NILs) that differ in fiber-bundle strength, short-fiber content, and in fewer than two genetic loci were compared using an oligonucleotide microarray. Fiber gene expression was compared at five time points spanning fiber elongation and secondary cell wall (SCW) biosynthesis. Fiber samples were collected from field plots in a randomized, complete block design, with three spatially distinct biological replications for each NIL at each time point. Microarray hybridizations were performed in a loop experimental design that allowed comparisons of fiber gene expression profiles as a function of time between the two NILs. Overall, developmental expression patterns revealed by the microarray experiment agreed with previously reported cotton fiber gene expression patterns for specific genes. Additionally, genes expressed coordinately with the onset of SCW biosynthesis in cotton fiber correlated with gene expression patterns of other SCW-producing plant tissues. Functional classification and enrichment analysis of differentially expressed genes between the two NILs revealed that genes associated with SCW biosynthesis were significantly up-regulated in fibers of the high-fiber quality line at the transition stage of cotton fiber development. For independent corroboration of the microarray results, 15 genes were selected for quantitative reverse transcription PCR analysis of fiber gene expression. These analyses, conducted over multiple field years, confirmed the temporal difference in fiber gene expression between the two NILs. We hypothesize that the loci conferring temporal differences in fiber gene expression between the NILs are important regulatory sequences that offer the potential for more targeted manipulation of cotton fiber quality.

Regulation of Plasmodium yoelii oocyst development by strain- and stage-specific small-subunit rRNA.

PubMed

Qi, Yanwei; Zhu, Feng; Eastman, Richard T; Fu, Young; Zilversmit, Martine; Pattaradilokrat, Sittiporn; Hong, Lingxian; Liu, Shengfa; McCutchan, Thomas F; Pan, Weiqing; Xu, Wenyue; Li, Jian; Huang, Fusheng; Su, Xin-zhuan

2015-03-10

One unique feature of malaria parasites is the differential transcription of structurally distinct rRNA (rRNA) genes at different developmental stages: the A-type genes are transcribed mainly in asexual stages, whereas the S-type genes are expressed mostly in sexual or mosquito stages. Conclusive functional evidence of different rRNAs in regulating stage-specific parasite development, however, is still absent. Here we performed genetic crosses of Plasmodium yoelii parasites with one parent having an oocyst development defect (ODD) phenotype and another producing normal oocysts to identify the gene(s) contributing to the ODD. The parent with ODD--characterized as having small oocysts and lacking infective sporozoites--was obtained after introduction of a plasmid with a green fluorescent protein gene into the parasite genome and subsequent passages in mice. Quantitative trait locus analysis of genome-wide microsatellite genotypes of 48 progeny from the crosses linked an ~200-kb segment on chromosome 6 containing one of the S-type genes (D-type small subunit rRNA gene [D-ssu]) to the ODD. Fine mapping of the plasmid integration site, gene expression pattern, and gene knockout experiments demonstrated that disruption of the D-ssu gene caused the ODD phenotype. Interestingly, introduction of the D-ssu gene into the same parasite strain (self), but not into a different subspecies, significantly affected or completely ablated oocyst development, suggesting a stage- and subspecies (strain)-specific regulation of oocyst development by D-ssu. This study demonstrates that P. yoelii D-ssu is essential for normal oocyst and sporozoite development and that variation in the D-ssu sequence can have dramatic effects on parasite development. Malaria parasites are the only known organisms that express structurally distinct rRNA genes at different developmental stages. The differential expression of these genes suggests that they play unique roles during the complex life cycle of the parasites. Conclusive functional proof of different rRNAs in regulating parasite development, however, is still absent or controversial. Here we functionally demonstrate for the first time that a stage-specifically expressed D-type small-subunit rRNA gene (D-ssu) is essential for oocyst development of the malaria parasite Plasmodium yoelii in the mosquito. This study also shows that variations in D-ssu sequence and/or the timing of transcription may have profound effects on parasite oocyst development. The results show that in addition to protein translation, rRNAs of malaria parasites also regulate parasite development and differentiation in a strain-specific manner, which can be explored for controlling parasite transmission. Copyright © 2015 Qi et al.

Microarray analysis of gene expression patterns in the leaf during potato tuberization in the potato somatic hybrid Solanum tuberosum and Solanum etuberosum.

PubMed

Tiwari, Jagesh Kumar; Devi, Sapna; Sundaresha, S; Chandel, Poonam; Ali, Nilofer; Singh, Brajesh; Bhardwaj, Vinay; Singh, Bir Pal

2015-06-01

Genes involved in photoassimilate partitioning and changes in hormonal balance are important for potato tuberization. In the present study, we investigated gene expression patterns in the tuber-bearing potato somatic hybrid (E1-3) and control non-tuberous wild species Solanum etuberosum (Etb) by microarray. Plants were grown under controlled conditions and leaves were collected at eight tuber developmental stages for microarray analysis. A t-test analysis identified a total of 468 genes (94 up-regulated and 374 down-regulated) that were statistically significant (p ≤ 0.05) and differentially expressed in E1-3 and Etb. Gene Ontology (GO) characterization of the 468 genes revealed that 145 were annotated and 323 were of unknown function. Further, these 145 genes were grouped based on GO biological processes followed by molecular function and (or) PGSC description into 15 gene sets, namely (1) transport, (2) metabolic process, (3) biological process, (4) photosynthesis, (5) oxidation-reduction, (6) transcription, (7) translation, (8) binding, (9) protein phosphorylation, (10) protein folding, (11) ubiquitin-dependent protein catabolic process, (12) RNA processing, (13) negative regulation of protein, (14) methylation, and (15) mitosis. RT-PCR analysis of 10 selected highly significant genes (p ≤ 0.01) confirmed the microarray results. Overall, we show that candidate genes induced in leaves of E1-3 were implicated in tuberization processes such as transport, carbohydrate metabolism, phytohormones, and transcription/translation/binding functions. Hence, our results provide an insight into the candidate genes induced in leaf tissues during tuberization in E1-3.

Comparison of sequencing the D2 region of the large subunit ribosomal RNA gene (MicroSEQ®) versus the internal transcribed spacer (ITS) regions using two public databases for identification of common and uncommon clinically relevant fungal species.

PubMed

Arbefeville, S; Harris, A; Ferrieri, P

2017-09-01

Fungal infections cause considerable morbidity and mortality in immunocompromised patients. Rapid and accurate identification of fungi is essential to guide accurately targeted antifungal therapy. With the advent of molecular methods, clinical laboratories can use new technologies to supplement traditional phenotypic identification of fungi. The aims of the study were to evaluate the sole commercially available MicroSEQ® D2 LSU rDNA Fungal Identification Kit compared to the in-house developed internal transcribed spacer (ITS) regions assay in identifying moulds, using two well-known online public databases to analyze sequenced data. 85 common and uncommon clinically relevant fungi isolated from clinical specimens were sequenced for the D2 region of the large subunit (LSU) of ribosomal RNA (rRNA) gene with the MicroSEQ® Kit and the ITS regions with the in house developed assay. The generated sequenced data were analyzed with the online GenBank and MycoBank public databases. The D2 region of the LSU rRNA gene identified 89.4% or 92.9% of the 85 isolates to the genus level and the full ITS region (f-ITS) 96.5% or 100%, using GenBank or MycoBank, respectively, when compared to the consensus ID. When comparing species-level designations to the consensus ID, D2 region of the LSU rRNA gene aligned with 44.7% (38/85) or 52.9% (45/85) of these isolates in GenBank or MycoBank, respectively. By comparison, f-ITS possessed greater specificity, followed by ITS1, then ITS2 regions using GenBank or MycoBank. Using GenBank or MycoBank, D2 region of the LSU rRNA gene outperformed phenotypic based ID at the genus level. Comparing rates of ID between D2 region of the LSU rRNA gene and the ITS regions in GenBank or MycoBank at the species level against the consensus ID, f-ITS and ITS2 exceeded performance of the D2 region of the LSU rRNA gene, but ITS1 had similar performance to the D2 region of the LSU rRNA gene using MycoBank. Our results indicated that the MicroSEQ® D2 LSU rDNA Fungal Identification Kit was equivalent to the in-house developed ITS regions assay to identify fungi at the genus level. The MycoBank database gave a better curated database and thus allowed a better genus and species identification for both D2 region of the LSU rRNA gene and ITS regions. Copyright © 2017 Elsevier B.V. All rights reserved.

Microarray analysis of gene expression profiles in ripening pineapple fruits.

PubMed

Koia, Jonni H; Moyle, Richard L; Botella, Jose R

2012-12-18

Pineapple (Ananas comosus) is a tropical fruit crop of significant commercial importance. Although the physiological changes that occur during pineapple fruit development have been well characterized, little is known about the molecular events that occur during the fruit ripening process. Understanding the molecular basis of pineapple fruit ripening will aid the development of new varieties via molecular breeding or genetic modification. In this study we developed a 9277 element pineapple microarray and used it to profile gene expression changes that occur during pineapple fruit ripening. Microarray analyses identified 271 unique cDNAs differentially expressed at least 1.5-fold between the mature green and mature yellow stages of pineapple fruit ripening. Among these 271 sequences, 184 share significant homology with genes encoding proteins of known function, 53 share homology with genes encoding proteins of unknown function and 34 share no significant homology with any database accession. Of the 237 pineapple sequences with homologs, 160 were up-regulated and 77 were down-regulated during pineapple fruit ripening. DAVID Functional Annotation Cluster (FAC) analysis of all 237 sequences with homologs revealed confident enrichment scores for redox activity, organic acid metabolism, metalloenzyme activity, glycolysis, vitamin C biosynthesis, antioxidant activity and cysteine peptidase activity, indicating the functional significance and importance of these processes and pathways during pineapple fruit development. Quantitative real-time PCR analysis validated the microarray expression results for nine out of ten genes tested. This is the first report of a microarray based gene expression study undertaken in pineapple. Our bioinformatic analyses of the transcript profiles have identified a number of genes, processes and pathways with putative involvement in the pineapple fruit ripening process. This study extends our knowledge of the molecular basis of pineapple fruit ripening and non-climacteric fruit ripening in general.

Microarray analysis of gene expression profiles in ripening pineapple fruits

PubMed Central

2012-01-01

Background Pineapple (Ananas comosus) is a tropical fruit crop of significant commercial importance. Although the physiological changes that occur during pineapple fruit development have been well characterized, little is known about the molecular events that occur during the fruit ripening process. Understanding the molecular basis of pineapple fruit ripening will aid the development of new varieties via molecular breeding or genetic modification. In this study we developed a 9277 element pineapple microarray and used it to profile gene expression changes that occur during pineapple fruit ripening. Results Microarray analyses identified 271 unique cDNAs differentially expressed at least 1.5-fold between the mature green and mature yellow stages of pineapple fruit ripening. Among these 271 sequences, 184 share significant homology with genes encoding proteins of known function, 53 share homology with genes encoding proteins of unknown function and 34 share no significant homology with any database accession. Of the 237 pineapple sequences with homologs, 160 were up-regulated and 77 were down-regulated during pineapple fruit ripening. DAVID Functional Annotation Cluster (FAC) analysis of all 237 sequences with homologs revealed confident enrichment scores for redox activity, organic acid metabolism, metalloenzyme activity, glycolysis, vitamin C biosynthesis, antioxidant activity and cysteine peptidase activity, indicating the functional significance and importance of these processes and pathways during pineapple fruit development. Quantitative real-time PCR analysis validated the microarray expression results for nine out of ten genes tested. Conclusions This is the first report of a microarray based gene expression study undertaken in pineapple. Our bioinformatic analyses of the transcript profiles have identified a number of genes, processes and pathways with putative involvement in the pineapple fruit ripening process. This study extends our knowledge of the molecular basis of pineapple fruit ripening and non-climacteric fruit ripening in general. PMID:23245313

Quantitative Proteomic and Microarray Analysis of the Archaeon Methanosarcina Acetivorans Grown with Acetate Versus Methanol*

PubMed Central

Li, Lingyun; Li, Qingbo; Rohlin, Lars; Kim, UnMi; Salmon, Kirsty; Rejtar, Tomas; Gunsalus, Robert P.; Karger, Barry L.; Ferry, James G.

2008-01-01

Summary Methanosarcina acetivorans strain C2A is an acetate- and methanol-utilizing methane-producing organism for which the genome, the largest yet sequenced among the Archaea, reveals extensive physiological diversity. LC linear ion trap-FTICR mass spectrometry was employed to analyze acetate- vs. methanol-grown cells metabolically labeled with 14N vs. 15N, respectively, to obtain quantitative protein abundance ratios. DNA microarray analyses of acetate- vs. methanol-grown cells was also performed to determine gene expression ratios. The combined approaches were highly complementary, extending the physiological understanding of growth and methanogenesis. Of the 1081 proteins detected, 255 were ≥ 3-fold differentially abundant. DNA microarray analysis revealed 410 genes that were ≥ 2.5-fold differentially expressed of 1972 genes with detected expression. The ratios of differentially abundant proteins were in good agreement with expression ratios of the encoding genes. Taken together, the results suggest several novel roles for electron transport components specific to acetate-grown cells, including two flavodoxins each specific for growth on acetate or methanol. Protein abundance ratios indicated that duplicate CO dehydrogenase/acetyl-CoA complexes function in the conversion of acetate to methane. Surprisingly, the protein abundance and gene expression ratios indicated a general stress response in acetate- vs. methanol-grown cells that included enzymes specific for polyphosphate accumulation and oxidative stress. The microarray analysis identified transcripts of several genes encoding regulatory proteins with identity to the PhoU, MarR, GlnK, and TetR families commonly found in the Bacteria domain. An analysis of neighboring genes suggested roles in controlling phosphate metabolism (PhoU), ammonia assimilation (GlnK), and molybdopterin cofactor biosynthesis (TetR). Finally, the proteomic and microarray results suggested roles for two-component regulatory systems specific for each growth substrate. PMID:17269732

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.

Microarray study of single nucleotide polymorphisms and expression of ATP-binding cassette genes in breast tumors

NASA Astrophysics Data System (ADS)

Tsyganov, M. M.; Ibragimova, M. K.; Karabut, I. V.; Freydin, M. B.; Choinzonov, E. L.; Litvyakov, N. V.

2015-11-01

Our previous research establishes that changes of expression of the ATP-binding cassette genes family is connected with the neoadjuvant chemotherapy effect. However, the mechanism of regulation of resistance gene expression remains unclear. As many researchers believe, single nucleotide polymorphisms can be involved in this process. Thereupon, microarray analysis is used to study polymorphisms in ATP-binding cassette genes. It is thus found that MDR gene expression is connected with 5 polymorphisms, i.e. rs241432, rs241429, rs241430, rs3784867, rs59409230, which participate in the regulation of expression of own genes.

Adaptable gene-specific dye bias correction for two-channel DNA microarrays.

PubMed

Margaritis, Thanasis; Lijnzaad, Philip; van Leenen, Dik; Bouwmeester, Diane; Kemmeren, Patrick; van Hooff, Sander R; Holstege, Frank C P

2009-01-01

DNA microarray technology is a powerful tool for monitoring gene expression or for finding the location of DNA-bound proteins. DNA microarrays can suffer from gene-specific dye bias (GSDB), causing some probes to be affected more by the dye than by the sample. This results in large measurement errors, which vary considerably for different probes and also across different hybridizations. GSDB is not corrected by conventional normalization and has been difficult to address systematically because of its variance. We show that GSDB is influenced by label incorporation efficiency, explaining the variation of GSDB across different hybridizations. A correction method (Gene- And Slide-Specific Correction, GASSCO) is presented, whereby sequence-specific corrections are modulated by the overall bias of individual hybridizations. GASSCO outperforms earlier methods and works well on a variety of publically available datasets covering a range of platforms, organisms and applications, including ChIP on chip. A sequence-based model is also presented, which predicts which probes will suffer most from GSDB, useful for microarray probe design and correction of individual hybridizations. Software implementing the method is publicly available.

Adaptable gene-specific dye bias correction for two-channel DNA microarrays

PubMed Central

Margaritis, Thanasis; Lijnzaad, Philip; van Leenen, Dik; Bouwmeester, Diane; Kemmeren, Patrick; van Hooff, Sander R; Holstege, Frank CP

2009-01-01

DNA microarray technology is a powerful tool for monitoring gene expression or for finding the location of DNA-bound proteins. DNA microarrays can suffer from gene-specific dye bias (GSDB), causing some probes to be affected more by the dye than by the sample. This results in large measurement errors, which vary considerably for different probes and also across different hybridizations. GSDB is not corrected by conventional normalization and has been difficult to address systematically because of its variance. We show that GSDB is influenced by label incorporation efficiency, explaining the variation of GSDB across different hybridizations. A correction method (Gene- And Slide-Specific Correction, GASSCO) is presented, whereby sequence-specific corrections are modulated by the overall bias of individual hybridizations. GASSCO outperforms earlier methods and works well on a variety of publically available datasets covering a range of platforms, organisms and applications, including ChIP on chip. A sequence-based model is also presented, which predicts which probes will suffer most from GSDB, useful for microarray probe design and correction of individual hybridizations. Software implementing the method is publicly available. PMID:19401678

A cDNA microarray gene expression data classifier for clinical diagnostics based on graph theory.

PubMed

Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco

2011-01-01

Despite great advances in discovering cancer molecular profiles, the proper application of microarray technology to routine clinical diagnostics is still a challenge. Current practices in the classification of microarrays' data show two main limitations: the reliability of the training data sets used to build the classifiers, and the classifiers' performances, especially when the sample to be classified does not belong to any of the available classes. In this case, state-of-the-art algorithms usually produce a high rate of false positives that, in real diagnostic applications, are unacceptable. To address this problem, this paper presents a new cDNA microarray data classification algorithm based on graph theory and is able to overcome most of the limitations of known classification methodologies. The classifier works by analyzing gene expression data organized in an innovative data structure based on graphs, where vertices correspond to genes and edges to gene expression relationships. To demonstrate the novelty of the proposed approach, the authors present an experimental performance comparison between the proposed classifier and several state-of-the-art classification algorithms.

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.

A Unique Procedure to Identify Cell Surface Markers Through a Spherical Self-Organizing Map Applied to DNA Microarray Analysis.

PubMed

Sugii, Yuh; Kasai, Tomonari; Ikeda, Masashi; Vaidyanath, Arun; Kumon, Kazuki; Mizutani, Akifumi; Seno, Akimasa; Tokutaka, Heizo; Kudoh, Takayuki; Seno, Masaharu

2016-01-01

To identify cell-specific markers, we designed a DNA microarray platform with oligonucleotide probes for human membrane-anchored proteins. Human glioma cell lines were analyzed using microarray and compared with normal and fetal brain tissues. For the microarray analysis, we employed a spherical self-organizing map, which is a clustering method suitable for the conversion of multidimensional data into two-dimensional data and displays the relationship on a spherical surface. Based on the gene expression profile, the cell surface characteristics were successfully mirrored onto the spherical surface, thereby distinguishing normal brain tissue from the disease model based on the strength of gene expression. The clustered glioma-specific genes were further analyzed by polymerase chain reaction procedure and immunocytochemical staining of glioma cells. Our platform and the following procedure were successfully demonstrated to categorize the genes coding for cell surface proteins that are specific to glioma cells. Our assessment demonstrates that a spherical self-organizing map is a valuable tool for distinguishing cell surface markers and can be employed in marker discovery studies for the treatment of cancer.

Marker genes that are less conserved in their sequences are useful for predicting genome-wide similarity levels between closely related prokaryotic strains

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

Lan, Yemin; Rosen, Gail; Hershberg, Ruth

The 16s rRNA gene is so far the most widely used marker for taxonomical classification and separation of prokaryotes. Since it is universally conserved among prokaryotes, it is possible to use this gene to classify a broad range of prokaryotic organisms. At the same time, it has often been noted that the 16s rRNA gene is too conserved to separate between prokaryotes at finer taxonomic levels. In this paper, we examine how well levels of similarity of 16s rRNA and 73 additional universal or nearly universal marker genes correlate with genome-wide levels of gene sequence similarity. We demonstrate that themore » percent identity of 16s rRNA predicts genome-wide levels of similarity very well for distantly related prokaryotes, but not for closely related ones. In closely related prokaryotes, we find that there are many other marker genes for which levels of similarity are much more predictive of genome-wide levels of gene sequence similarity. Finally, we show that the identities of the markers that are most useful for predicting genome-wide levels of similarity within closely related prokaryotic lineages vary greatly between lineages. However, the most useful markers are always those that are least conserved in their sequences within each lineage. In conclusion, our results show that by choosing markers that are less conserved in their sequences within a lineage of interest, it is possible to better predict genome-wide gene sequence similarity between closely related prokaryotes than is possible using the 16s rRNA gene. We point readers towards a database we have created (POGO-DB) that can be used to easily establish which markers show lowest levels of sequence conservation within different prokaryotic lineages.« less

Marker genes that are less conserved in their sequences are useful for predicting genome-wide similarity levels between closely related prokaryotic strains

DOE PAGES

Lan, Yemin; Rosen, Gail; Hershberg, Ruth

2016-05-03

The 16s rRNA gene is so far the most widely used marker for taxonomical classification and separation of prokaryotes. Since it is universally conserved among prokaryotes, it is possible to use this gene to classify a broad range of prokaryotic organisms. At the same time, it has often been noted that the 16s rRNA gene is too conserved to separate between prokaryotes at finer taxonomic levels. In this paper, we examine how well levels of similarity of 16s rRNA and 73 additional universal or nearly universal marker genes correlate with genome-wide levels of gene sequence similarity. We demonstrate that themore » percent identity of 16s rRNA predicts genome-wide levels of similarity very well for distantly related prokaryotes, but not for closely related ones. In closely related prokaryotes, we find that there are many other marker genes for which levels of similarity are much more predictive of genome-wide levels of gene sequence similarity. Finally, we show that the identities of the markers that are most useful for predicting genome-wide levels of similarity within closely related prokaryotic lineages vary greatly between lineages. However, the most useful markers are always those that are least conserved in their sequences within each lineage. In conclusion, our results show that by choosing markers that are less conserved in their sequences within a lineage of interest, it is possible to better predict genome-wide gene sequence similarity between closely related prokaryotes than is possible using the 16s rRNA gene. We point readers towards a database we have created (POGO-DB) that can be used to easily establish which markers show lowest levels of sequence conservation within different prokaryotic lineages.« less

Genome-wide gene order distances support clustering the gram-positive bacteria

PubMed Central

House, Christopher H.; Pellegrini, Matteo; Fitz-Gibbon, Sorel T.

2015-01-01

Initially using 143 genomes, we developed a method for calculating the pair-wise distance between prokaryotic genomes using a Monte Carlo method to estimate the conservation of gene order. The method was based on repeatedly selecting five or six non-adjacent random orthologs from each of two genomes and determining if the chosen orthologs were in the same order. The raw distances were then corrected for gene order convergence using an adaptation of the Jukes-Cantor model, as well as using the common distance correction D′ = −ln(1-D). First, we compared the distances found via the order of six orthologs to distances found based on ortholog gene content and small subunit rRNA sequences. The Jukes-Cantor gene order distances are reasonably well correlated with the divergence of rRNA (R2 = 0.24), especially at rRNA Jukes-Cantor distances of less than 0.2 (R2 = 0.52). Gene content is only weakly correlated with rRNA divergence (R2 = 0.04) over all distances, however, it is especially strongly correlated at rRNA Jukes-Cantor distances of less than 0.1 (R2 = 0.67). This initial work suggests that gene order may be useful in conjunction with other methods to help understand the relatedness of genomes. Using the gene order distances in 143 genomes, the relations of prokaryotes were studied using neighbor joining and agreement subtrees. We then repeated our study of the relations of prokaryotes using gene order in 172 complete genomes better representing a wider-diversity of prokaryotes. Consistently, our trees show the Actinobacteria as a sister group to the bulk of the Firmicutes. In fact, the robustness of gene order support was found to be considerably greater for uniting these two phyla than for uniting any of the proteobacterial classes together. The results are supportive of the idea that Actinobacteria and Firmicutes are closely related, which in turn implies a single origin for the gram-positive cell. PMID:25653643

The Complete Mitochondrial DNA Sequence of Scenedesmus obliquus Reflects an Intermediate Stage in the Evolution of the Green Algal Mitochondrial Genome

PubMed Central

Nedelcu, Aurora M.; Lee, Robert W.; Lemieux, Claude; Gray, Michael W.; Burger, Gertraud

2000-01-01

Two distinct mitochondrial genome types have been described among the green algal lineages investigated to date: a reduced–derived, Chlamydomonas-like type and an ancestral, Prototheca-like type. To determine if this unexpected dichotomy is real or is due to insufficient or biased sampling and to define trends in the evolution of the green algal mitochondrial genome, we sequenced and analyzed the mitochondrial DNA (mtDNA) of Scenedesmus obliquus. This genome is 42,919 bp in size and encodes 42 conserved genes (i.e., large and small subunit rRNA genes, 27 tRNA and 13 respiratory protein-coding genes), four additional free-standing open reading frames with no known homologs, and an intronic reading frame with endonuclease/maturase similarity. No 5S rRNA or ribosomal protein-coding genes have been identified in Scenedesmus mtDNA. The standard protein-coding genes feature a deviant genetic code characterized by the use of UAG (normally a stop codon) to specify leucine, and the unprecedented use of UCA (normally a serine codon) as a signal for termination of translation. The mitochondrial genome of Scenedesmus combines features of both green algal mitochondrial genome types: the presence of a more complex set of protein-coding and tRNA genes is shared with the ancestral type, whereas the lack of 5S rRNA and ribosomal protein-coding genes as well as the presence of fragmented and scrambled rRNA genes are shared with the reduced–derived type of mitochondrial genome organization. Furthermore, the gene content and the fragmentation pattern of the rRNA genes suggest that this genome represents an intermediate stage in the evolutionary process of mitochondrial genome streamlining in green algae. [The sequence data described in this paper have been submitted to the GenBank data library under accession no. AF204057.] PMID:10854413

Chicken interferome: avian interferon-stimulated genes identified by microarray and RNA-seq of primary chick embryo fibroblasts treated with a chicken type I interferon (IFN-α).

PubMed

Giotis, Efstathios S; Robey, Rebecca C; Skinner, Natalie G; Tomlinson, Christopher D; Goodbourn, Stephen; Skinner, Michael A

2016-08-05

Viruses that infect birds pose major threats-to the global supply of chicken, the major, universally-acceptable meat, and as zoonotic agents (e.g. avian influenza viruses H5N1 and H7N9). Controlling these viruses in birds as well as understanding their emergence into, and transmission amongst, humans will require considerable ingenuity and understanding of how different species defend themselves. The type I interferon-coordinated response constitutes the major antiviral innate defence. Although interferon was discovered in chicken cells, details of the response, particularly the identity of hundreds of stimulated genes, are far better described in mammals. Viruses induce interferon-stimulated genes but they also regulate the expression of many hundreds of cellular metabolic and structural genes to facilitate their replication. This study focusses on the potentially anti-viral genes by identifying those induced just by interferon in primary chick embryo fibroblasts. Three transcriptomic technologies were exploited: RNA-seq, a classical 3'-biased chicken microarray and a high density, "sense target", whole transcriptome chicken microarray, with each recognising 120-150 regulated genes (curated for duplication and incorrect assignment of some microarray probesets). Overall, the results are considered robust because 128 of the compiled, curated list of 193 regulated genes were detected by two, or more, of the technologies.

Alternative splicing of anciently exonized 5S rRNA regulates plant transcription factor TFIIIA

PubMed Central

Fu, Yan; Bannach, Oliver; Chen, Hao; Teune, Jan-Hendrik; Schmitz, Axel; Steger, Gerhard; Xiong, Liming; Barbazuk, W. Brad

2009-01-01

Identifying conserved alternative splicing (AS) events among evolutionarily distant species can prioritize AS events for functional characterization and help uncover relevant cis- and trans-regulatory factors. A genome-wide search for conserved cassette exon AS events in higher plants revealed the exonization of 5S ribosomal RNA (5S rRNA) within the gene of its own transcription regulator, TFIIIA (transcription factor for polymerase III A). The 5S rRNA-derived exon in TFIIIA gene exists in all representative land plant species but not in green algae and nonplant species, suggesting it is specific to land plants. TFIIIA is essential for RNA polymerase III-based transcription of 5S rRNA in eukaryotes. Integrating comparative genomics and molecular biology revealed that the conserved cassette exon derived from 5S rRNA is coupled with nonsense-mediated mRNA decay. Utilizing multiple independent Arabidopsis overexpressing TFIIIA transgenic lines under osmotic and salt stress, strong accordance between phenotypic and molecular evidence reveals the biological relevance of AS of the exonized 5S rRNA in quantitative autoregulation of TFIIIA homeostasis. Most significantly, this study provides the first evidence of ancient exaptation of 5S rRNA in plants, suggesting a novel gene regulation model mediated by the AS of an anciently exonized noncoding element. PMID:19211543

Cloning and restriction enzyme mapping of ribosomal DNA of Giardia duodenalis, Giardia ardeae and Giardia muris.

PubMed

van Keulen, H; Campbell, S R; Erlandsen, S L; Jarroll, E L

1991-06-01

In an attempt to study Giardia at the DNA sequence level, the rRNA genes of three species, Giardia duodenalis, Giardia ardeae and Giardia muris were cloned and restriction enzyme maps were constructed. The rDNA repeats of these Giardia show completely different restriction enzyme recognition patterns. The size of the rDNA repeat ranges from approximately 5.6 kb in G. duodenalis to 7.6 kb in both G. muris and G. ardeae. These size differences are mainly attributable to the variation in length of the spacer. Minor differences exist among these Giardia in the sizes of their small subunit rRNA and the internal transcribed spacer between small and large subunit rRNA. The genetic maps were constructed by sequence analysis of the DNA around the 5' and 3' ends of the mature rRNA genes and between the rRNA covering the 5.8S rRNA gene and internal transcribed spacer. Comparison of the 5.8S rDNA and 3' end of large subunit rDNA from these three Giardia species showed considerable sequence variation, but the rDNA sequences of G. duodenalis and G. ardeae appear more closely related to each other than to G. muris.

Identification of reference genes for quantitative expression analysis using large-scale RNA-seq data of Arabidopsis thaliana and model crop plants.

PubMed

Kudo, Toru; Sasaki, Yohei; Terashima, Shin; Matsuda-Imai, Noriko; Takano, Tomoyuki; Saito, Misa; Kanno, Maasa; Ozaki, Soichi; Suwabe, Keita; Suzuki, Go; Watanabe, Masao; Matsuoka, Makoto; Takayama, Seiji; Yano, Kentaro

2016-10-13

In quantitative gene expression analysis, normalization using a reference gene as an internal control is frequently performed for appropriate interpretation of the results. Efforts have been devoted to exploring superior novel reference genes using microarray transcriptomic data and to evaluating commonly used reference genes by targeting analysis. However, because the number of specifically detectable genes is totally dependent on probe design in the microarray analysis, exploration using microarray data may miss some of the best choices for the reference genes. Recently emerging RNA sequencing (RNA-seq) provides an ideal resource for comprehensive exploration of reference genes since this method is capable of detecting all expressed genes, in principle including even unknown genes. We report the results of a comprehensive exploration of reference genes using public RNA-seq data from plants such as Arabidopsis thaliana (Arabidopsis), Glycine max (soybean), Solanum lycopersicum (tomato) and Oryza sativa (rice). To select reference genes suitable for the broadest experimental conditions possible, candidates were surveyed by the following four steps: (1) evaluation of the basal expression level of each gene in each experiment; (2) evaluation of the expression stability of each gene in each experiment; (3) evaluation of the expression stability of each gene across the experiments; and (4) selection of top-ranked genes, after ranking according to the number of experiments in which the gene was expressed stably. Employing this procedure, 13, 10, 12 and 21 top candidates for reference genes were proposed in Arabidopsis, soybean, tomato and rice, respectively. Microarray expression data confirmed that the expression of the proposed reference genes under broad experimental conditions was more stable than that of commonly used reference genes. These novel reference genes will be useful for analyzing gene expression profiles across experiments carried out under various experimental conditions.

Ribosomal RNA and ribosomal proteins in corynebacteria.

PubMed

Martín, Juan F; Barreiro, Carlos; González-Lavado, Eva; Barriuso, Mónica

2003-09-04

Ribosomal RNAs (rRNAs) (16S, 23S, 5S) encoded by the rrn operons and ribosomal proteins play a very important role in the formation of ribosomes and in the control of translation. Five copies of the rrn operon were reported by hybridization studies in Brevibacterium (Corynebacterium) lactofermentum but the genome sequence of Corynebacterium glutamicum provided evidence for six rrn copies. All six copies of the C. glutamicum 16S rRNA have a size of 1523 bp and each of the six copies of the 5S contain 120 bp whereas size differences are found between the six copies of the 23S rRNA. The anti-Shine-Dalgarno sequence at the 3'-end of the 16S rRNA was 5'-CCUCCUUUC-3'. Each rrn operon is transcribed as a large precursor rRNA (pre-rRNA) that is processed by RNaseIII and other RNases at specific cleavage boxes that have been identified in the C. glutamicum pre-rRNA. A secondary structure of the C. glutamicum 16S rRNA is proposed. The 16S rRNA sequence has been used as a molecular evolution clock allowing the deduction of a phylogenetic tree of all Corynebacterium species. In C. glutamicum, there are 11 ribosomal protein gene clusters encoding 42 ribosomal proteins. The organization of some of the ribosomal protein gene cluster is identical to that of Escherichia coli whereas in other clusters the organization of the genes is rather different. Some specific ribosomal protein genes are located in a different cluster in C. glutamicum when compared with E. coli, indicating that the control of expression of these genes is different in E. coli and C. glutamicum.

Sequence heterogeneities of genes encoding 16S rRNAs in Paenibacillus polymyxa detected by temperature gradient gel electrophoresis.

PubMed Central

Nübel, U; Engelen, B; Felske, A; Snaidr, J; Wieshuber, A; Amann, R I; Ludwig, W; Backhaus, H

1996-01-01

Sequence heterogeneities in 16S rRNA genes from individual strains of Paenibacillus polymyxa were detected by sequence-dependent separation of PCR products by temperature gradient gel electrophoresis (TGGE). A fragment of the 16S rRNA genes, comprising variable regions V6 to V8, was used as a target sequence for amplifications. PCR products from P. polymyxa (type strain) emerged as a well-defined pattern of bands in the gradient gel. Six plasmids with different inserts, individually demonstrating the migration characteristics of single bands of the pattern, were obtained by cloning the PCR products. Their sequences were analyzed as a representative sample of the total heterogeneity. An amount of 10 variant nucleotide positions in the fragment of 347 bp was observed, with all substitutions conserving the relevant secondary structures of the V6 and V8 regions in the RNA molecules. Hybridizations with specifically designed probes demonstrated different chromosomal locations of the respective rRNA genes. Amplifications of reverse-transcribed rRNA from ribosome preparations, as well as whole-cell hybridizations, revealed a predominant representation of particular sequences in ribosomes of exponentially growing laboratory cultures. Different strains of P. polymyxa showed not only remarkably differing patterns of PCR products in TGGE analysis but also discriminative whole-cell labeling with the designed oligonucleotide probes, indicating the different representation of individual sequences in active ribosomes. Our results demonstrate the usefulness of TGGE for the structural analysis of heterogeneous rRNA genes together with their expression, stress problems of the generation of meaningful data for 16S rRNA sequences and probe designs, and might have consequences for evolutionary concepts. PMID:8824607

Identification of Novel Tissue-Specific Genes by Analysis of Microarray Databases: A Human and Mouse Model

PubMed Central

Suh, Yeunsu; Davis, Michael E.; Lee, Kichoon

2013-01-01

Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI′s Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved. PMID:23741331

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.

Microarray analysis of genes associated with cell surface NIS protein levels in breast cancer.

PubMed

Beyer, Sasha J; Zhang, Xiaoli; Jimenez, Rafael E; Lee, Mei-Ling T; Richardson, Andrea L; Huang, Kun; Jhiang, Sissy M

2011-10-11

Na+/I- symporter (NIS)-mediated iodide uptake allows radioiodine therapy for thyroid cancer. NIS is also expressed in breast tumors, raising potential for radionuclide therapy of breast cancer. However, NIS expression in most breast cancers is low and may not be sufficient for radionuclide therapy. We aimed to identify biomarkers associated with NIS expression such that mechanisms underlying NIS modulation in human breast tumors may be elucidated. Published oligonucleotide microarray data within the National Center for Biotechnology Information Gene Expression Omnibus database were analyzed to identify gene expression tightly correlated with NIS mRNA level among human breast tumors. NIS immunostaining was performed in a tissue microarray composed of 28 human breast tumors which had corresponding oligonucleotide microarray data available for each tumor such that gene expression associated with cell surface NIS protein level could be identified. NIS mRNA levels do not vary among breast tumors or when compared to normal breast tissues when detected by Affymetrix oligonucleotide microarray platforms. Cell surface NIS protein levels are much more variable than their corresponding NIS mRNA levels. Despite a limited number of breast tumors examined, our analysis identified cysteinyl-tRNA synthetase as a biomarker that is highly associated with cell surface NIS protein levels in the ER-positive breast cancer subtype. Further investigation on genes associated with cell surface NIS protein levels within each breast cancer molecular subtype may lead to novel targets for selectively increasing NIS expression/function in a subset of breast cancers patients.

BEND3 represses rDNA transcription by stabilizing a NoRC component via USP21 deubiquitinase

PubMed Central

Khan, Abid; Giri, Sumanprava; Wang, Yating; Chakraborty, Arindam; Ghosh, Archit K.; Anantharaman, Aparna; Aggarwal, Vasudha; Sathyan, Kizhakke M.; Ha, Taekjip; Prasanth, Kannanganattu V.; Prasanth, Supriya G.

2015-01-01

Ribosome biogenesis dictates the translational capacity of cells. Several mechanisms establish and maintain transcriptional output from eukaryotic ribosomal DNA (rDNA) loci. rDNA silencing is one such mechanism that ensures the inactivity and hence the maintenance of a silenced state of a subset of rRNA gene copies. Whereas oncogenic agents stimulate rRNA gene transcription, tumor suppressors decrease rRNA gene transcription. We demonstrate in mammalian cells that BANP, E5R, and Nac1 (BEN) domain 3 (BEND3), a quadruple BEN domain-containing protein, localizes in nucleoli and binds to ribosomal RNA gene promoters to help repress rRNA genes. Loss of BEND3 increases histone H3K4 trimethylation and, correspondingly, decreases rDNA promoter DNA methylation, consistent with a role for BEND3 in rDNA silencing. BEND3 associates with the nucleolar-remodeling complex (NoRC), and SUMOylated BEND3 stabilizes NoRC component TTF-1–interacting protein 5 via association with ubiquitin specific protease 21 (USP21) debiquitinase. Our results provide mechanistic insights into how the novel rDNA transcription repressor BEND3 acts together with NoRC to actively coordinate the establishment of rDNA silencing. PMID:26100909

BEND3 represses rDNA transcription by stabilizing a NoRC component via USP21 deubiquitinase.

PubMed

Khan, Abid; Giri, Sumanprava; Wang, Yating; Chakraborty, Arindam; Ghosh, Archit K; Anantharaman, Aparna; Aggarwal, Vasudha; Sathyan, Kizhakke M; Ha, Taekjip; Prasanth, Kannanganattu V; Prasanth, Supriya G

2015-07-07

Ribosome biogenesis dictates the translational capacity of cells. Several mechanisms establish and maintain transcriptional output from eukaryotic ribosomal DNA (rDNA) loci. rDNA silencing is one such mechanism that ensures the inactivity and hence the maintenance of a silenced state of a subset of rRNA gene copies. Whereas oncogenic agents stimulate rRNA gene transcription, tumor suppressors decrease rRNA gene transcription. We demonstrate in mammalian cells that BANP, E5R, and Nac1 (BEN) domain 3 (BEND3), a quadruple BEN domain-containing protein, localizes in nucleoli and binds to ribosomal RNA gene promoters to help repress rRNA genes. Loss of BEND3 increases histone H3K4 trimethylation and, correspondingly, decreases rDNA promoter DNA methylation, consistent with a role for BEND3 in rDNA silencing. BEND3 associates with the nucleolar-remodeling complex (NoRC), and SUMOylated BEND3 stabilizes NoRC component TTF-1-interacting protein 5 via association with ubiquitin specific protease 21 (USP21) debiquitinase. Our results provide mechanistic insights into how the novel rDNA transcription repressor BEND3 acts together with NoRC to actively coordinate the establishment of rDNA silencing.

Expression stability of two housekeeping genes (18S rRNA and G3PDH) during in vitro maturation of follicular oocytes in buffalo (Bubalus bubalis).

PubMed

Aswal, Ajay Pal Singh; Raghav, Sarvesh; De, Sachinandan; Thakur, Manish; Goswami, Surender Lal; Datta, Tirtha Kumar

2008-01-15

The present study was undertaken to evaluate the expression stability of two housekeeping genes (HKGs), 18S rRNA and G3PDH during in vitro maturation (IVM) of oocytes in buffalo, which qualifies their use as internal controls for valid qRT-PCR estimation of other oocyte transcripts. A semi quantitative RT-PCR system was used with optimised qRT-PCR parameters at exponential PCR cycle for evaluation of temporal expression pattern of these genes over 24 h of IVM. 18S rRNA was found more stable in its expression pattern than G3PDH.

The GermOnline cross-species systems browser provides comprehensive information on genes and gene products relevant for sexual reproduction.

PubMed

Gattiker, Alexandre; Niederhauser-Wiederkehr, Christa; Moore, James; Hermida, Leandro; Primig, Michael

2007-01-01

We report a novel release of the GermOnline knowledgebase covering genes relevant for the cell cycle, gametogenesis and fertility. GermOnline was extended into a cross-species systems browser including information on DNA sequence annotation, gene expression and the function of gene products. The database covers eight model organisms and Homo sapiens, for which complete genome annotation data are available. The database is now built around a sophisticated genome browser (Ensembl), our own microarray information management and annotation system (MIMAS) used to extensively describe experimental data obtained with high-density oligonucleotide microarrays (GeneChips) and a comprehensive system for online editing of database entries (MediaWiki). The RNA data include results from classical microarrays as well as tiling arrays that yield information on RNA expression levels, transcript start sites and lengths as well as exon composition. Members of the research community are solicited to help GermOnline curators keep database entries on genes and gene products complete and accurate. The database is accessible at http://www.germonline.org/.

Applying Multivariate Adaptive Splines to Identify Genes With Expressions Varying After Diagnosis in Microarray Experiments.

PubMed

Duan, Fenghai; Xu, Ye

2017-01-01

To analyze a microarray experiment to identify the genes with expressions varying after the diagnosis of breast cancer. A total of 44 928 probe sets in an Affymetrix microarray data publicly available on Gene Expression Omnibus from 249 patients with breast cancer were analyzed by the nonparametric multivariate adaptive splines. Then, the identified genes with turning points were grouped by K-means clustering, and their network relationship was subsequently analyzed by the Ingenuity Pathway Analysis. In total, 1640 probe sets (genes) were reliably identified to have turning points along with the age at diagnosis in their expression profiling, of which 927 expressed lower after turning points and 713 expressed higher after the turning points. K-means clustered them into 3 groups with turning points centering at 54, 62.5, and 72, respectively. The pathway analysis showed that the identified genes were actively involved in various cancer-related functions or networks. In this article, we applied the nonparametric multivariate adaptive splines method to a publicly available gene expression data and successfully identified genes with expressions varying before and after breast cancer diagnosis.

Characterization of regulatory pathways in Xylella fastidiosa: genes and phenotypes controlled by algU.

PubMed

Shi, Xiang Yang; Dumenyo, C Korsi; Hernandez-Martinez, Rufina; Azad, Hamid; Cooksey, Donald A

2007-11-01

Many virulence genes in plant bacterial pathogens are coordinately regulated by "global" regulatory genes. Conducting DNA microarray analysis of bacterial mutants of such genes, compared with the wild type, can help to refine the list of genes that may contribute to virulence in bacterial pathogens. The regulatory gene algU, with roles in stress response and regulation of the biosynthesis of the exopolysaccharide alginate in Pseudomonas aeruginosa and many other bacteria, has been extensively studied. The role of algU in Xylella fastidiosa, the cause of Pierce's disease of grapevines, was analyzed by mutation and whole-genome microarray analysis to define its involvement in aggregation, biofilm formation, and virulence. In this study, an algU::nptII mutant had reduced cell-cell aggregation, attachment, and biofilm formation and lower virulence in grapevines. Microarray analysis showed that 42 genes had significantly lower expression in the algU::nptII mutant than in the wild type. Among these are several genes that could contribute to cell aggregation and biofilm formation, as well as other physiological processes such as virulence, competition, and survival.

Identification by 16S rRNA Gene Sequencing of an Actinomyces hongkongensis Isolate Recovered from a Patient with Pelvic Actinomycosis

PubMed Central

Flynn, A. N.; Lyndon, C. A.

2013-01-01

A case of Actinomyces hongkongensis pelvic actinomycosis in an adult woman is described. Conventional phenotypic tests failed to identify the Gram-positive bacillus isolated from a fluid aspirate of a pelvic abscess. The bacterium was identified by 16S rRNA gene sequencing and analysis using the SmartGene Integrated Database Network System software. PMID:23698532

Comparison between rpoB and 16S rRNA Gene Sequencing for Molecular Identification of 168 Clinical Isolates of Corynebacterium

PubMed Central

Khamis, Atieh; Raoult, Didier; La Scola, Bernard

2005-01-01

Higher proportions (91%) of 168 corynebacterial isolates were positively identified by partial rpoB gene determination than by that based on 16S rRNA gene sequences. This method is thus a simple, molecular-analysis-based method for identification of corynebacteria, but it should be used in conjunction with other tests for definitive identification. PMID:15815024

Increased expression of LD1 genes transcribed by RNA polymerase I in Leishmania donovani as a result of duplication into the rRNA gene locus

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

Lodes, M.J.; Merlin, G.; DeVos, T.

1995-12-01

This report investigates the duplication of two LD1 genes into the rRNA locus and the resultant transcription by RNA polymerase I, which has a faster transcription rate than that of RNA polymerase II. This was conducted using a 2.2-Mb chromosome in Leishmania donovani. 55 refs., 6 figs.

Use of rpoB gene analysis for identification of nitrogen-fixing Paenibacillus species as an alternative to the 16S rRNA gene.

PubMed

da Mota, F F; Gomes, E A; Paiva, E; Rosado, A S; Seldin, L

2004-01-01

To avoid the limitations of 16S rRNA-based phylogenetic analysis for Paenibacillus species, the usefulness of the RNA polymerase beta-subunit encoding gene (rpoB) was investigated as an alternative to the 16S rRNA gene for taxonomic studies. Partial rpoB sequences were generated for the type strains of eight nitrogen-fixing Paenibacillus species. The presence of only one copy of rpoB in the genome of P. graminis strain RSA19(T) was demonstrated by denaturing gradient gel electrophoresis and hybridization assays. A comparative analysis of the sequences of the 16S rRNA and rpoB genes was performed and the eight species showed between 91.6-99.1% (16S rRNA) and 77.9-97.3% (rpoB) similarity, allowing a more accurate discrimination between the different species using the rpoB gene. Finally, 24 isolates from the rhizosphere of different cultivars of maize previously identified as Paenibacillus spp. were assigned correctly to one of the nitrogen-fixing species. The data obtained in this study indicate that rpoB is a powerful identification tool, which can be used for the correct discrimination of the nitrogen-fixing species of agricultural and industrial importance within the genus Paenibacillus.

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

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

Tholouli, Eleni; MacDermott, Sarah; Hoyland, Judith

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection inmore » archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.« less

Analysis of Temporal-spatial Co-variation within Gene Expression Microarray Data in an Organogenesis Model

NASA Astrophysics Data System (ADS)

Ehler, Martin; Rajapakse, Vinodh; Zeeberg, Barry; Brooks, Brian; Brown, Jacob; Czaja, Wojciech; Bonner, Robert F.

The gene networks underlying closure of the optic fissure during vertebrate eye development are poorly understood. We used a novel clustering method based on Laplacian Eigenmaps, a nonlinear dimension reduction method, to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure. Our new method provided greater biological specificity than classical clustering algorithms in terms of identifying more biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates. This new methodology builds on the advantages of LCM to isolate pure phenotypic populations within complex tissues and allows improved ability to identify critical gene products expressed at lower copy number. The combination of LCM of embryonic organs, gene expression microarrays, and extracting spatial and temporal co-variations appear to be a powerful approach to understanding the gene regulatory networks that specify mammalian organogenesis.

The complete mitochondrial genome sequence of the maned wolf (Chrysocyon brachyurus).

PubMed

Zhao, Chao; Yang, Xiufeng; Zhang, Honghai; Zhang, Jin; Chen, Lei; Sha, Weilai; Liu, Guangshuai

2016-01-01

In this study, the complete mitochondrial genome of the maned wolf (Chrysocyon brachyurus), the unique species in Chrysocyon, was sequenced and reported for the first time using blood samples obtained from a female individual in Shanghai Zoo, China. Sequence analysis showed that the genome structure was in accordance with other Canidae species and it contained 12 S rRNA gene, 16 S rRNA gene, 22 tRNA genes, 13 protein-coding genes and 1 control region.

Expression profiling and pathway analysis of Krüppel-like factor 4 in mouse embryonic fibroblasts

PubMed Central

Hagos, Engda G; Ghaleb, Amr M; Kumar, Amrita; Neish, Andrew S; Yang, Vincent W

2011-01-01

Background: Krüppel-like factor 4 (KLF4) is a zinc-finger transcription factor with diverse regulatory functions in proliferation, differentiation, and development. KLF4 also plays a role in inflammation, tumorigenesis, and reprogramming of somatic cells to induced pluripotent stem (iPS) cells. To gain insight into the mechanisms by which KLF4 regulates these processes, we conducted DNA microarray analyses to identify differentially expressed genes in mouse embryonic fibroblasts (MEFs) wild type and null for Klf4. Methods: Expression profiles of fibroblasts isolated from mouse embryos wild type or null for the Klf4 alleles were examined by DNA microarrays. Differentially expressed genes were subjected to the Database for Annotation, Visualization and Integrated Discovery (DAVID). The microarray data were also interrogated with the Ingenuity Pathway Analysis (IPA) and Gene Set Enrichment Analysis (GSEA) for pathway identification. Results obtained from the microarray analysis were confirmed by Western blotting for select genes with biological relevance to determine the correlation between mRNA and protein levels. Results: One hundred and sixty three up-regulated and 88 down-regulated genes were identified that demonstrated a fold-change of at least 1.5 and a P-value < 0.05 in Klf4-null MEFs compared to wild type MEFs. Many of the up-regulated genes in Klf4-null MEFs encode proto-oncogenes, growth factors, extracellular matrix, and cell cycle activators. In contrast, genes encoding tumor suppressors and those involved in JAK-STAT signaling pathways are down-regulated in Klf4-null MEFs. IPA and GSEA also identified various pathways that are regulated by KLF4. Lastly, Western blotting of select target genes confirmed the changes revealed by microarray data. Conclusions: These data are not only consistent with previous functional studies of KLF4's role in tumor suppression and somatic cell reprogramming, but also revealed novel target genes that mediate KLF4's functions. PMID:21892412

Environmental Shortcourse Final report [Joint US-EC Short Course on Environmental Biotechnology: Microbial Catalysts for the Environment

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

Zylstra, Gerben; van der Meer, Jan Roelof

The Joint US-EC Short Course on Environmental Biotechnology is designed for several purposes. One of the central tenets is to bring together young scientists (at the late Ph.D. or early postdoctoral stages of their careers) in a forum that will set the groundwork for future overseas collaborative interactions. The course is also designed to give the scientists hands-on experience in modern, up-to-date biotechnological methods for the analysis of microbes and their activities pertinent to the remediation of pollutants in the environment. The 2011 course covered multiple theoretical and practical topics in environmental biotechnology. The practical part was centered around amore » full concise experiment to demonstrate the possibility for targeted remediation of contaminated soil. Experiments included chemical, microbiological, and molecular analyses of sediments and/or waters, contaminant bioavailability assessment, seeded bioremediation, gene probing, PCR amplification, microbial community analysis based on 16S rRNA gene diversity, and microarray analyses. Each of these topics is explained in detail. The practical part of the course was complemented with two lectures per day, given by distinguished scientists from the US and from Europe, covering a research area related to what the students are doing in the course.« less

Integrated metagenomics and network analysis of soil microbial community of the forest timberline

PubMed Central

Ding, Junjun; Zhang, Yuguang; Deng, Ye; Cong, Jing; Lu, Hui; Sun, Xin; Yang, Caiyun; Yuan, Tong; Van Nostrand, Joy D.; Li, Diqiang; Zhou, Jizhong; Yang, Yunfeng

2015-01-01

The forest timberline responds quickly and markedly to climate changes, rendering it a ready indicator. Climate warming has caused an upshift of the timberline worldwide. However, the impact on belowground ecosystem and biogeochemical cycles remain elusive. To understand soil microbial ecology of the timberline, we analyzed microbial communities via 16s rRNA Illumina sequencing, a microarray-based tool named GeoChip 4.0 and a random matrix theory-based association network approach. We selected 24 sampling sites at two vegetation belts forming the timberline of Shennongjia Mountain in Hubei Province of China, a region with extraordinarily rich biodiversity. We found that temperature, among all of measured environmental parameters, showed the most significant and extensive linkages with microbial biomass, microbial diversity and composition at both taxonomic and functional gene levels, and microbial association network. Therefore, temperature was the best predictor for microbial community variations in the timberline. Furthermore, abundances of nitrogen cycle and phosphorus cycle genes were concomitant with NH4+-N, NO3−-N and total phosphorus, offering tangible clues to the underlying mechanisms of soil biogeochemical cycles. As the first glimpse at both taxonomic and functional compositions of soil microbial community of the timberline, our findings have major implications for predicting consequences of future timberline upshift. PMID:25613225

Characterization of the two intra-individual sequence variants in the 18S rRNA gene in the plant parasitic nematode, Rotylenchulus reniformis.

PubMed

Nyaku, Seloame T; Sripathi, Venkateswara R; Kantety, Ramesh V; Gu, Yong Q; Lawrence, Kathy; Sharma, Govind C

2013-01-01

The 18S rRNA gene is fundamental to cellular and organismal protein synthesis and because of its stable persistence through generations it is also used in phylogenetic analysis among taxa. Sequence variation in this gene within a single species is rare, but it has been observed in few metazoan organisms. More frequently it has mostly been reported in the non-transcribed spacer region. Here, we have identified two sequence variants within the near full coding region of 18S rRNA gene from a single reniform nematode (RN) Rotylenchulus reniformis labeled as reniform nematode variant 1 (RN_VAR1) and variant 2 (RN_VAR2). All sequences from three of the four isolates had both RN variants in their sequences; however, isolate 13B had only RN variant 2 sequence. Specific variable base sites (96 or 5.5%) were found within the 18S rRNA gene that can clearly distinguish the two 18S rDNA variants of RN, in 11 (25.0%) and 33 (75.0%) of the 44 RN clones, for RN_VAR1 and RN_VAR2, respectively. Neighbor-joining trees show that the RN_VAR1 is very similar to the previously existing R. reniformis sequence in GenBank, while the RN_VAR2 sequence is more divergent. This is the first report of the identification of two major variants of the 18S rRNA gene in the same single RN, and documents the specific base variation between the two variants, and hypothesizes on simultaneous co-existence of these two variants for this gene.

Characterization of the Two Intra-Individual Sequence Variants in the 18S rRNA Gene in the Plant Parasitic Nematode, Rotylenchulus reniformis

PubMed Central

Nyaku, Seloame T.; Sripathi, Venkateswara R.; Kantety, Ramesh V.; Gu, Yong Q.; Lawrence, Kathy; Sharma, Govind C.

2013-01-01

The 18S rRNA gene is fundamental to cellular and organismal protein synthesis and because of its stable persistence through generations it is also used in phylogenetic analysis among taxa. Sequence variation in this gene within a single species is rare, but it has been observed in few metazoan organisms. More frequently it has mostly been reported in the non-transcribed spacer region. Here, we have identified two sequence variants within the near full coding region of 18S rRNA gene from a single reniform nematode (RN) Rotylenchulus reniformis labeled as reniform nematode variant 1 (RN_VAR1) and variant 2 (RN_VAR2). All sequences from three of the four isolates had both RN variants in their sequences; however, isolate 13B had only RN variant 2 sequence. Specific variable base sites (96 or 5.5%) were found within the 18S rRNA gene that can clearly distinguish the two 18S rDNA variants of RN, in 11 (25.0%) and 33 (75.0%) of the 44 RN clones, for RN_VAR1 and RN_VAR2, respectively. Neighbor-joining trees show that the RN_VAR1 is very similar to the previously existing R. reniformis sequence in GenBank, while the RN_VAR2 sequence is more divergent. This is the first report of the identification of two major variants of the 18S rRNA gene in the same single RN, and documents the specific base variation between the two variants, and hypothesizes on simultaneous co-existence of these two variants for this gene. PMID:23593343

Microarrays

ERIC Educational Resources Information Center

Plomin, Robert; Schalkwyk, Leonard C.

2007-01-01

Microarrays are revolutionizing genetics by making it possible to genotype hundreds of thousands of DNA markers and to assess the expression (RNA transcripts) of all of the genes in the genome. Microarrays are slides the size of a postage stamp that contain millions of DNA sequences to which single-stranded DNA or RNA can hybridize. This…

Immune and inflammatory gene signature in rat cerebrum in subarachnoid hemorrhage with microarray analysis.

PubMed

Lee, Chu-I; Chou, An-Kuo; Lin, Ching-Chih; Chou, Chia-Hua; Loh, Joon-Khim; Lieu, Ann-Shung; Wang, Chih-Jen; Huang, Chi-Ying F; Howng, Shen-Long; Hong, Yi-Ren

2012-01-01

Cerebral vasospasm following subarachnoid hemorrhage (SAH) has been studied in terms of a contraction of the major cerebral arteries, but the effect of cerebrum tissue in SAH is not yet well understood. To gain insight into the biology of SAH-expressing cerebrum, we employed oligonucleotide microarrays to characterize the gene expression profiles of cerebrum tissue at the early stage of SAH. Functional gene expression in the cerebrum was analyzed 2 h following stage 1-hemorrhage in Sprague-Dawley rats. mRNA was investigated by performing microarray and quantitative real-time PCR analyses, and protein expression was determined by Western blot analysis. In this study, 18 upregulated and 18 downregulated genes displayed at least a 1.5-fold change. Five genes were verified by real-time PCR, including three upregulated genes [prostaglandin E synthase (PGES), CD14 antigen, and tissue inhibitor of metalloproteinase 1 (TIMP1)] as well as two downregulated genes [KRAB-zinc finger protein-2 (KZF-2) and γ-aminobutyric acid B receptor 1 (GABA B receptor)]. Notably, there were functional implications for the three upregulated genes involved in the inflammatory SAH process. However, the mechanisms leading to decreased KZF-2 and GABA B receptor expression in SAH have never been characterized. We conclude that oligonucleotide microarrays have the potential for use as a method to identify candidate genes associated with SAH and to provide novel investigational targets, including genes involved in the immune and inflammatory response. Furthermore, understanding the regulation of MMP9/TIMP1 during the early stages of SAH may elucidate the pathophysiological mechanisms in SAH rats.

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.

DigOut: viewing differential expression genes as outliers.

PubMed

Yu, Hui; Tu, Kang; Xie, Lu; Li, Yuan-Yuan

2010-12-01

With regards to well-replicated two-conditional microarray datasets, the selection of differentially expressed (DE) genes is a well-studied computational topic, but for multi-conditional microarray datasets with limited or no replication, the same task is not properly addressed by previous studies. This paper adopts multivariate outlier analysis to analyze replication-lacking multi-conditional microarray datasets, finding that it performs significantly better than the widely used limit fold change (LFC) model in a simulated comparative experiment. Compared with the LFC model, the multivariate outlier analysis also demonstrates improved stability against sample variations in a series of manipulated real expression datasets. The reanalysis of a real non-replicated multi-conditional expression dataset series leads to satisfactory results. In conclusion, a multivariate outlier analysis algorithm, like DigOut, is particularly useful for selecting DE genes from non-replicated multi-conditional gene expression dataset.

Taxonomic evaluation of Streptomyces albus and related species using multilocus sequence analysis

USDA-ARS?s Scientific Manuscript database

In phylogenetic analyses of the genus Streptomyces using 16S rRNA gene sequences, Streptomyces albus subsp. albus NRRL B-1811T formed a cluster with 5 other species having identical or nearly identical 16S rRNA gene sequences. Moreover, the morphological and physiological characteristics of these ot...

Recognition of Potentially Novel Human Disease-Associated Pathogens by Implementation of Systematic 16S rRNA Gene Sequencing in the Diagnostic Laboratory▿ †

PubMed Central

Keller, Peter M.; Rampini, Silvana K.; Büchler, Andrea C.; Eich, Gerhard; Wanner, Roger M.; Speck, Roberto F.; Böttger, Erik C.; Bloemberg, Guido V.

2010-01-01

Clinical isolates that are difficult to identify by conventional means form a valuable source of novel human pathogens. We report on a 5-year study based on systematic 16S rRNA gene sequence analysis. We found 60 previously unknown 16S rRNA sequences corresponding to potentially novel bacterial taxa. For 30 of 60 isolates, clinical relevance was evaluated; 18 of the 30 isolates analyzed were considered to be associated with human disease. PMID:20631113

Phylogenetic analysis of Fusobacterium prausnitzii based upon the 16S rRNA gene sequence and PCR confirmation.

PubMed

Wang, R F; Cao, W W; Cerniglia, C E

1996-01-01

In order to develop a PCR method to detect Fusobacterium prausnitzii in human feces and to clarify the phylogenetic position of this species, its 16S rRNA gene sequence was determined. The sequence described in this paper is different from the 16S rRNA gene sequence is specific for F. prausnitzii, and the results of this assay confirmed that F. prausnitzii is the most common species in human feces. However, a PCR assay based on the original GenBank sequence was negative when it was performed with two strains of F. prausnitzii obtained from the American Type Culture Collection. A phylogenetic tree based on the new 16S rRNA gene sequence was constructed. On this tree F. prausnitzii was not a member of the Fusobacterium group but was closer to some Eubacterium spp. and located between Clostridium "clusters III and IV" (M.D. Collins, P.A. Lawson, A. Willems, J.J. Cordoba, J. Fernandez-Garayzabal, P. Garcia, J. Cai, H. Hippe, and J.A.E. Farrow, Int. J. Syst. Bacteriol. 44:812-826, 1994).

Identification of Nucleolus-Associated Chromatin Domains Reveals a Role for the Nucleolus in 3D Organization of the A. thaliana Genome.

PubMed

Pontvianne, Frédéric; Carpentier, Marie-Christine; Durut, Nathalie; Pavlištová, Veronika; Jaške, Karin; Schořová, Šárka; Parrinello, Hugues; Rohmer, Marine; Pikaard, Craig S; Fojtová, Miloslava; Fajkus, Jiří; Sáez-Vásquez, Julio

2016-08-09

The nucleolus is the site of rRNA gene transcription, rRNA processing, and ribosome biogenesis. However, the nucleolus also plays additional roles in the cell. We isolated nucleoli using fluorescence-activated cell sorting (FACS) and identified nucleolus-associated chromatin domains (NADs) by deep sequencing, comparing wild-type plants and null mutants for the nucleolar protein NUCLEOLIN 1 (NUC1). NADs are primarily genomic regions with heterochromatic signatures and include transposable elements (TEs), sub-telomeric regions, and mostly inactive protein-coding genes. However, NADs also include active rRNA genes and the entire short arm of chromosome 4 adjacent to them. In nuc1 null mutants, which alter rRNA gene expression and overall nucleolar structure, NADs are altered, telomere association with the nucleolus is decreased, and telomeres become shorter. Collectively, our studies reveal roles for NUC1 and the nucleolus in the spatial organization of chromosomes as well as telomere maintenance. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Identification of candidate genes involved in neuroblastoma progression by combining genomic and expression microarrays with survival data.

PubMed

Łastowska, M; Viprey, V; Santibanez-Koref, M; Wappler, I; Peters, H; Cullinane, C; Roberts, P; Hall, A G; Tweddle, D A; Pearson, A D J; Lewis, I; Burchill, S A; Jackson, M S

2007-11-22

Identifying genes, whose expression is consistently altered by chromosomal gains or losses, is an important step in defining genes of biological relevance in a wide variety of tumour types. However, additional criteria are needed to discriminate further among the large number of candidate genes identified. This is particularly true for neuroblastoma, where multiple genomic copy number changes of proven prognostic value exist. We have used Affymetrix microarrays and a combination of fluorescent in situ hybridization and single nucleotide polymorphism (SNP) microarrays to establish expression profiles and delineate copy number alterations in 30 primary neuroblastomas. Correlation of microarray data with patient survival and analysis of expression within rodent neuroblastoma cell lines were then used to define further genes likely to be involved in the disease process. Using this approach, we identify >1000 genes within eight recurrent genomic alterations (loss of 1p, 3p, 4p, 10q and 11q, 2p gain, 17q gain, and the MYCN amplicon) whose expression is consistently altered by copy number change. Of these, 84 correlate with patient survival, with the minimal regions of 17q gain and 4p loss being enriched significantly for such genes. These include genes involved in RNA and DNA metabolism, and apoptosis. Orthologues of all but one of these genes on 17q are overexpressed in rodent neuroblastoma cell lines. A significant excess of SNPs whose copy number correlates with survival is also observed on proximal 4p in stage 4 tumours, and we find that deletion of 4p is associated with improved outcome in an extended cohort of tumours. These results define the major impact of genomic copy number alterations upon transcription within neuroblastoma, and highlight genes on distal 17q and proximal 4p for downstream analyses. They also suggest that integration of discriminators, such as survival and comparative gene expression, with microarray data may be useful in the identification of critical genes within regions of loss or gain in many human cancers.

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

Inhabitancy of active Nitrosopumilus-like ammonia-oxidizing archaea and Nitrospira nitrite-oxidizing bacteria in the sponge Theonella swinhoei

PubMed Central

Feng, Guofang; Sun, Wei; Zhang, Fengli; Karthik, Loganathan; Li, Zhiyong

2016-01-01

Nitrification directly contributes to the ammonia removal in sponges, and it plays an indispensable role in sponge-mediated nitrogen cycle. Previous studies have demonstrated genomic evidences of nitrifying lineages in the sponge Theonella swinhoei. However, little is known about the transcriptional activity of nitrifying community in this sponge. In this study, combined DNA- and transcript-based analyses were performed to reveal the composition and transcriptional activity of the nitrifiers in T. swinhoei from the South China Sea. Transcriptional activity of ammonia-oxidizing archaea (AOA) and nitrite-oxidizing bacteria (NOB) in this sponge were confirmed by targeting their nitrifying genes,16S rRNA genes and their transcripts. Phylogenetic analysis coupled with RDP rRNA classification indicated that archaeal 16S rRNA genes, amoA (the subunit of ammonia monooxygenase) genes and their transcripts were closely related to Nitrosopumilus-like AOA; whereas nitrifying bacterial 16S rRNA genes, nxrB (the subunit of nitrite oxidoreductase) genes and their transcripts were closely related to Nitrospira NOB. Quantitative assessment demonstrated relative higher abundances of nitrifying genes and transcripts of Nitrosopumilus-like AOA than those of Nitrospira NOB in this sponge. This study illustrated the transcriptional potentials of Nitrosopumilus-like archaea and Nitrospira bacteria that would predominantly contribute to the nitrification functionality in the South China Sea T. swinhoei. PMID:27113140

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.

Development of a Genome-Proxy Microarray for Profiling Marine Microbial Communities and its Application to a Time Series in Monterey Bay, California

DTIC Science & Technology

2008-09-01

community representation. 12 survey a complex microbial community. Community DNA or rRNA extracted from a sample may require amplification before...restricted to cultivated clades, since not only do many clades have sufficient database representation due to 16S environmental surveys , but such...well developed for standard and comprehensive surveys . Depending on the population being targeted and the identification method, FCM can be a

MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data

PubMed Central

2014-01-01

Background Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. Results We developed a workflow to facilitate and standardize Meta-Analysis of Affymetrix Microarray Data analysis (MAAMD) in Kepler. Two freely available stand-alone software tools, R and AltAnalyze were embedded in MAAMD. The inputs of MAAMD are user-editable csv files, which contain sample information and parameters describing the locations of input files and required tools. MAAMD was tested by analyzing 4 different GEO datasets from mice and drosophila. MAAMD automates data downloading, data organization, data quality control assesment, differential gene expression analysis, clustering analysis, pathway visualization, gene-set enrichment analysis, and cross-species orthologous-gene comparisons. MAAMD was utilized to identify gene orthologues responding to hypoxia or hyperoxia in both mice and drosophila. The entire set of analyses for 4 datasets (34 total microarrays) finished in ~ one hour. Conclusions MAAMD saves time, minimizes the required computer skills, and offers a standardized procedure for users to analyze microarray datasets and make new intra- and inter-dataset comparisons. PMID:24621103

[Preparation of the cDNA microarray on the differential expressed cDNA of senescence-accelerated mouse's hippocampus].

PubMed

Cheng, Xiao-Rui; Zhou, Wen-Xia; Zhang, Yong-Xiang

2006-05-01

Alzheimer' s disease (AD) is the most common form of dementia in the elderly. AD is an invariably fatal neurodegenerative disorder with no effective treatment. Senescence-accelerated mouse prone 8 (SAMP8) is a model for studying age-related cognitive impairments and also is a good model to study brain aging and one of mouse model of AD. The technique of cDNA microarray can monitor the expression levels of thousands of genes simultaneously and can be used to study AD with the character of multi-mechanism, multi-targets and multi-pathway. In order to disclose the mechanism of AD and find the drug targets of AD, cDNA microarray containing 3136 cDNAs amplified from the suppression subtracted cDNA library of hippocampus of SAMP8 and SAMR1 was prepared with 16 blocks and 14 x 14 pins, the housekeeping gene beta-actin and G3PDH as inner conference. The background of this microarray was low and unanimous, and dots divided evenly. The conditions of hybridization and washing were optimized during the hybridization of probe and target molecule. After the data of hybridization analysis, the differential expressed cDNAs were sequenced and analyzed by the bioinformatics, and some of genes were quantified by the real time RT-PCR and the reliability of this cDNA microarray were validated. This cDNA microarray may be the good means to select the differential expressed genes and disclose the molecular mechanism of SAMP8's brain aging and AD.

Detection and identification of Theileria infection in sika deer ( Cervus nippon ) in China.

PubMed

He, Lan; Khan, Muhanmad Kasib; Zhang, Wen-Jie; Zhang, Qing-Li; Zhou, Yan-Qin; Hu, Min; Zhao, Junlong

2012-06-01

The sika deer ( Cervus nippon ) is a first-grade state-protected animal in China and designated a threatened species by the World Conservation Union. To detect hemoparasite infection of sika deer, blood samples were collected from 24 animals in the Hubei Province Deer Center. Genomic DNA was extracted, and the V4 hypervariable region encoding 18S rRNA was analyzed by reverse line blot hybridization assay. PCR products hybridized with Babesia / Theileria genus-specific probes but failed to hybridize with any of the Babesia or Theileria species-specific probes, suggesting the presence of a novel, or variant, species. Here 18S rRNA and internal transcribed spacer (ITS) genes were amplified, cloned, and sequenced from 7 isolates. Alignment and BlastN of the cloned sequences revealed high similarities to the homologous 18S rRNA genes and ITS genes of Theileria cervi (AY735122), Theileria sp. CNY1A (AB012194), and Theileria sp. ex Yamaguchi (AF529272). Phylogenetic analysis based on the 18S rRNA gene and ITS sequences showed that all cloned sequences were grouped within the Theileria clade. Phylogeny based on the 18S rRNA gene divided the organisms into 2 groups. Group 1 was closest to Theileria sp. ex Yamaguchi (AF529272), and group 2 was distinct from all other identified Theileria and Babesia species. These results suggest the existence of Theileria sp. infection in sika deer in China. To our knowledge, this is the first report of cervine Theileria sp. in China.

Exploring internal features of 16S rRNA gene for identification of clinically relevant species of the genus Streptococcus

PubMed Central

2011-01-01

Background Streptococcus is an economically important genus as a number of species belonging to this genus are human and animal pathogens. The genus has been divided into different groups based on 16S rRNA gene sequence similarity. The variability observed among the members of these groups is low and it is difficult to distinguish them. The present study was taken up to explore 16S rRNA gene sequence to develop methods that can be used for preliminary identification and can supplement the existing methods for identification of clinically-relevant isolates of the genus Streptococcus. Methods 16S rRNA gene sequences belonging to the isolates of S. dysgalactiae, S. equi, S. pyogenes, S. agalactiae, S. bovis, S. gallolyticus, S. mutans, S. sobrinus, S. mitis, S. pneumoniae, S. thermophilus and S. anginosus were analyzed with the purpose to define genetic variability within each species to generate a phylogenetic framework, to identify species-specific signatures and in-silico restriction enzyme analysis. Results The framework based analysis was used to segregate Streptococcus spp. previously identified upto genus level. This segregation was validated using species-specific signatures and in-silico restriction enzyme analysis. 43 uncharacterized Streptococcus spp. could be identified using this approach. Conclusions The markers generated exploring 16S rRNA gene sequences provided useful tool that can be further used for identification of different species of the genus Streptococcus. PMID:21702978

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

PubMed

Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

2009-12-21

Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment.

Combined Analyses of the ITS Loci and the Corresponding 16S rRNA Genes Reveal High Micro- and Macrodiversity of SAR11 Populations in the Red Sea

PubMed Central

Ngugi, David Kamanda; Stingl, Ulrich

2012-01-01

Bacteria belonging to the SAR11 clade are among the most abundant prokaryotes in the pelagic zone of the ocean. 16S rRNA gene-based analyses indicate that they constitute up to 60% of the bacterioplankton community in the surface waters of the Red Sea. This extremely oligotrophic water body is further characterized by an epipelagic zone, which has a temperature above 24°C throughout the year, and a remarkable uniform temperature (∼22°C) and salinity (∼41 psu) from the mixed layer (∼200 m) to the bottom at over 2000 m depth. Despite these conditions that set it apart from other marine environments, the microbiology of this ecosystem is still vastly understudied. Prompted by the limited phylogenetic resolution of the 16S rRNA gene, we extended our previous study by sequencing the internal transcribed spacer (ITS) region of SAR11 in different depths of the Red Sea’s water column together with the respective 16S fragment. The overall diversity captured by the ITS loci was ten times higher than that of the corresponding 16S rRNA genes. Moreover, species estimates based on the ITS showed a highly diverse population of SAR11 in the mixed layer that became diminished in deep isothermal waters, which was in contrast to results of the related 16S rRNA genes. While the 16S rRNA gene-based sequences clustered into three phylogenetic subgroups, the related ITS fragments fell into several phylotypes that showed clear depth-dependent shifts in relative abundances. Blast-based analyses not only documented the observed vertical partitioning and universal co-occurrence of specific phylotypes in five other distinct oceanic provinces, but also highlighted the influence of ecosystem-specific traits (e.g., temperature, nutrient availability, and concentration of dissolved oxygen) on the population dynamics of this ubiquitous marine bacterium. PMID:23185592

Sequence variation identified in the 18S rRNA gene of Theileria mutans and Theileria velifera from the African buffalo (Syncerus caffer).

PubMed

Chaisi, Mamohale E; Collins, Nicola E; Potgieter, Fred T; Oosthuizen, Marinda C

2013-01-16

The African buffalo (Syncerus caffer) is a natural reservoir host for both pathogenic and non-pathogenic Theileria species. These often occur naturally as mixed infections in buffalo. Although the benign and mildly pathogenic forms do not have any significant economic importance, their presence could complicate the interpretation of diagnostic test results aimed at the specific diagnosis of the pathogenic Theileria parva in cattle and buffalo in South Africa. The 18S rRNA gene has been used as the target in a quantitative real-time PCR (qPCR) assay for the detection of T. parva infections. However, the extent of sequence variation within this gene in the non-pathogenic Theileria spp. of the Africa buffalo is not well known. The aim of this study was, therefore, to characterise the full-length 18S rRNA genes of Theileria mutans, Theileria sp. (strain MSD) and T. velifera and to determine the possible influence of any sequence variation on the specific detection of T. parva using the 18S rRNA qPCR. The reverse line blot (RLB) hybridization assay was used to select samples which either tested positive for several different Theileria spp., or which hybridised only with the Babesia/Theileria genus-specific probe and not with any of the Babesia or Theileria species-specific probes. The full-length 18S rRNA genes from 14 samples, originating from 13 buffalo and one bovine from different localities in South Africa, were amplified, cloned and the resulting recombinants sequenced. Variations in the 18S rRNA gene sequences were identified in T. mutans, Theileria sp. (strain MSD) and T. velifera, with the greatest diversity observed amongst the T. mutans variants. This variation possibly explained why the RLB hybridization assay failed to detect T. mutans and T. velifera in some of the analysed samples. Copyright © 2012 Elsevier B.V. All rights reserved.

A meta-data based method for DNA microarray imputation.

PubMed

Jörnsten, Rebecka; Ouyang, Ming; Wang, Hui-Yu

2007-03-29

DNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples under two or more conditions. Due to cost and design constraints of spotted cDNA microarray experiments, each logical set commonly includes only a small number of replicates per condition. Despite the vast improvement of the microarray technology in recent years, missing values are prevalent. Intuitively, imputation of missing values is best done using many replicates within the same logical set. In practice, there are few replicates and thus reliable imputation within logical sets is difficult. However, it is in the case of few replicates that the presence of missing values, and how they are imputed, can have the most profound impact on the outcome of downstream analyses (e.g. significance analysis and clustering). This study explores the feasibility of imputation across logical sets, using the vast amount of publicly available microarray data to improve imputation reliability in the small sample size setting. We download all cDNA microarray data of Saccharomyces cerevisiae, Arabidopsis thaliana, and Caenorhabditis elegans from the Stanford Microarray Database. Through cross-validation and simulation, we find that, for all three species, our proposed imputation using data from public databases is far superior to imputation within a logical set, sometimes to an astonishing degree. Furthermore, the imputation root mean square error for significant genes is generally a lot less than that of non-significant ones. Since downstream analysis of significant genes, such as clustering and network analysis, can be very sensitive to small perturbations of estimated gene effects, it is highly recommended that researchers apply reliable data imputation prior to further analysis. Our method can also be applied to cDNA microarray experiments from other species, provided good reference data are available.

USING DNA MICROARRAYS TO CHARACTERIZE GENE EXPRESSION IN TESTES OF FERTILE AND INFERTILE HUMANS AND MICE

EPA Science Inventory

USING DNA MICROARRAYS TO CHARACTERIZE GENE EXPRESSION
IN TESTES OF FERTILE AND INFERTILE HUMANS AND MICE

John C. Rockett1, J. Christopher Luft1, J. Brian Garges1, M. Stacey Ricci2, Pasquale Patrizio2, Norman B. Hecht2 and David J. Dix1
Reproductive Toxicology Divisio...

Comparison of dkgB-linked intergenic sequence ribotyping to DNA microarray hybridization for assigning serotype to Salmonella enterica

PubMed Central

Guard, Jean; Sanchez-Ingunza, Roxana; Morales, Cesar; Stewart, Tod; Liljebjelke, Karen; Kessel, JoAnn; Ingram, Kim; Jones, Deana; Jackson, Charlene; Fedorka-Cray, Paula; Frye, Jonathan; Gast, Richard; Hinton, Arthur

2012-01-01

Two DNA-based methods were compared for the ability to assign serotype to 139 isolates of Salmonella enterica ssp. I. Intergenic sequence ribotyping (ISR) evaluated single nucleotide polymorphisms occurring in a 5S ribosomal gene region and flanking sequences bordering the gene dkgB. A DNA microarray hybridization method that assessed the presence and the absence of sets of genes was the second method. Serotype was assigned for 128 (92.1%) of submissions by the two DNA methods. ISR detected mixtures of serotypes within single colonies and it cost substantially less than Kauffmann–White serotyping and DNA microarray hybridization. Decreasing the cost of serotyping S. enterica while maintaining reliability may encourage routine testing and research. PMID:22998607

Changes in the microbial community structure of bacteria, archaea and fungi in response to elevated CO(2) and warming in an Australian native grassland soil.

PubMed

Hayden, Helen L; Mele, Pauline M; Bougoure, Damian S; Allan, Claire Y; Norng, Sorn; Piceno, Yvette M; Brodie, Eoin L; Desantis, Todd Z; Andersen, Gary L; Williams, Amity L; Hovenden, Mark J

2012-12-01

The microbial community structure of bacteria, archaea and fungi is described in an Australian native grassland soil after more than 5 years exposure to different atmospheric CO2 concentrations ([CO2]) (ambient, +550 ppm) and temperatures (ambient, + 2°C) under different plant functional types (C3 and C4 grasses) and at two soil depths (0-5 cm and 5-10 cm). Archaeal community diversity was influenced by elevated [CO2], while under warming archaeal 16S rRNA gene copy numbers increased for C4 plant Themeda triandra and decreased for the C3 plant community (P < 0.05). Fungal community diversity resulted in three groups based upon elevated [CO2], elevated [CO2] plus warming and ambient [CO2]. Overall bacterial community diversity was influenced primarily by depth. Specific bacterial taxa changed in richness and relative abundance in response to climate change factors when assessed by a high-resolution 16S rRNA microarray (PhyloChip). Operational taxonomic unit signal intensities increased under elevated [CO2] for both Firmicutes and Bacteroidetes, and increased under warming for Actinobacteria and Alphaproteobacteria. For the interaction of elevated [CO2] and warming there were 103 significant operational taxonomic units (P < 0.01) representing 15 phyla and 30 classes. The majority of these operational taxonomic units increased in abundance for elevated [CO2] plus warming plots, while abundance declined in warmed or elevated [CO2] plots. Bacterial abundance (16S rRNA gene copy number) was significantly different for the interaction of elevated [CO2] and depth (P < 0.05) with decreased abundance under elevated [CO2] at 5-10 cm, and for Firmicutes under elevated [CO2] (P < 0.05). Bacteria, archaea and fungi in soil responded differently to elevated [CO2], warming and their interaction. Taxa identified as significantly climate-responsive could show differing trends in the direction of response ('+' or '-') under elevated CO2 or warming, which could then not be used to predict their interactive effects supporting the need to investigate interactive effects for climate change. The approach of focusing on specific taxonomic groups provides greater potential for understanding complex microbial community changes in ecosystems under climate change. © 2012 Society for Applied Microbiology and Blackwell Publishing Ltd.

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

Selection of the internal control gene for real-time quantitative rt-PCR assays in temperature treated Leptospira.

PubMed

Carrillo-Casas, Erika Margarita; Hernández-Castro, Rigoberto; Suárez-Güemes, Francisco; de la Peña-Moctezuma, Alejandro

2008-06-01

Analysis of gene expression requires sensitive, precise, and reproducible measurements for specific mRNA sequences. To avoid bias, real-time RT-PCR is referred to one or several internal control genes. Here, we sought to identify a gene to be used as normalizer by analyzing three functional distinct housekeeping genes (lipL41, flaB, and 16S rRNA) for their expression level and stability in temperature treated Leptospira cultures. Leptospira interrogans serovar Hardjo subtype Hardjoprajitno was cultured at 30 degrees C for 7 days until a density of 10(6) cells/ml was reached and then shifted to physiological temperatures (37 degrees C and 42 degrees C) and to environmental temperatures (25 degrees C and 30 degrees C) during a 24 h period. cDNA was amplified by quantitative PCR using SYBR Green I technology and gene-specific primers for lipL41, flaB, and 16S rRNA. Expression stability (M) was assessed by geNorm and Normfinder v.18. 16S rRNA registered an average expression stability of M = 1.1816, followed by flaB (M = 1.682) and lipL41 (M = 1.763). 16S rRNA was identified as the most stable gene and can be used as a normalizer, as it showed greater expression stability than lipL41 and flaB in the four temperature treatments. Hence, comparisons of gene expression will have a higher sensitivity and specificity.

Data-adaptive test statistics for microarray data.

PubMed

Mukherjee, Sach; Roberts, Stephen J; van der Laan, Mark J

2005-09-01

An important task in microarray data analysis is the selection of genes that are differentially expressed between different tissue samples, such as healthy and diseased. However, microarray data contain an enormous number of dimensions (genes) and very few samples (arrays), a mismatch which poses fundamental statistical problems for the selection process that have defied easy resolution. In this paper, we present a novel approach to the selection of differentially expressed genes in which test statistics are learned from data using a simple notion of reproducibility in selection results as the learning criterion. Reproducibility, as we define it, can be computed without any knowledge of the 'ground-truth', but takes advantage of certain properties of microarray data to provide an asymptotically valid guide to expected loss under the true data-generating distribution. We are therefore able to indirectly minimize expected loss, and obtain results substantially more robust than conventional methods. We apply our method to simulated and oligonucleotide array data. By request to the corresponding author.

Differential gene expression related to Nora virus infection of Drosophila melanogaster

PubMed Central

Cordes, Ethan J.; Licking-Murray, Kellie D; Carlson, Kimberly A.

2013-01-01

Nora virus is a recently discovered RNA picorna-like virus that produces a persistent infection in Drosophila melanogaster, but the antiviral pathway or change in gene expression is unknown. We performed cDNA microarray analysis comparing the gene expression profiles of Nora virus infected and uninfected wild-type D. melanogaster. This analysis yielded 58 genes exhibiting a 1.5-fold change or greater and p-value less than 0.01. Of these genes, 46 were up-regulated and 12 down-regulated in response to infection. To validate the microarray results, qRT-PCR was performed with probes for Chorion protein 16 and Troponin C isoform 4, which show good correspondence with cDNA microarray results. Differential regulation of genes associated with Toll and immune-deficient pathways, cytoskeletal development, Janus Kinase-Signal Transducer and Activator of Transcription interactions, and a potential gut-specific innate immune response were found. This genome-wide expression profile of Nora virus infection of D. melanogaster can pinpoint genes of interest for further investigation of antiviral pathways employed, genetic mechanisms, sites of replication, viral persistence, and developmental effects. PMID:23603562

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.

Microarray analysis of gene expression in West Nile virus–infected human retinal pigment epithelium

PubMed Central

Munoz-Erazo, Luis; Natoli, Ricardo; Provis, Jan Marie; Madigan, Michelle Catherine

2012-01-01

Purpose To identify key genes differentially expressed in the human retinal pigment epithelium (hRPE) following low-level West Nile virus (WNV) infection. Methods Primary hRPE and retinal pigment epithelium cell line (ARPE-19) cells were infected with WNV (multiplicity of infection 1). RNA extracted from mock-infected and WNV-infected cells was assessed for differential expression of genes using Affymetrix microarray. Quantitative real-time PCR analysis of 23 genes was used to validate the microarray results. Results Functional annotation clustering of the microarray data showed that gene clusters involved in immune and antiviral responses ranked highly, involving genes such as chemokine (C-C motif) ligand 2 (CCL2), chemokine (C-C motif) ligand 5 (CCL5), chemokine (C-X-C motif) ligand 10 (CXCL10), and toll like receptor 3 (TLR3). In conjunction with the quantitative real-time PCR analysis, other novel genes regulated by WNV infection included indoleamine 2,3-dioxygenase (IDO1), genes involved in the transforming growth factor–β pathway (bone morphogenetic protein and activin membrane-bound inhibitor homolog [BAMBI] and activating transcription factor 3 [ATF3]), and genes involved in apoptosis (tumor necrosis factor receptor superfamily, member 10d [TNFRSF10D]). WNV-infected RPE did not produce any interferon-γ, suggesting that IDO1 is induced by other soluble factors, by the virus alone, or both. Conclusions Low-level WNV infection of hRPE cells induced expression of genes that are typically associated with the host cell response to virus infection. We also identified other genes, including IDO1 and BAMBI, that may influence the RPE and therefore outer blood-retinal barrier integrity during ocular infection and inflammation, or are associated with degeneration, as seen for example in aging. PMID:22509103

A RNA-Seq Analysis of the Rat Supraoptic Nucleus Transcriptome: Effects of Salt Loading on Gene Expression

PubMed Central

Salinas, Yasmmyn D.; Shi, YiJun; Greenwood, Michael; Hoe, See Ziau; Murphy, David; Gainer, Harold

2015-01-01

Magnocellular neurons (MCNs) in the hypothalamo-neurohypophysial system (HNS) are highly specialized to release large amounts of arginine vasopressin (Avp) or oxytocin (Oxt) into the blood stream and play critical roles in the regulation of body fluid homeostasis. The MCNs are osmosensory neurons and are excited by exposure to hypertonic solutions and inhibited by hypotonic solutions. The MCNs respond to systemic hypertonic and hypotonic stimulation with large changes in the expression of their Avp and Oxt genes, and microarray studies have shown that these osmotic perturbations also cause large changes in global gene expression in the HNS. In this paper, we examine gene expression in the rat supraoptic nucleus (SON) under normosmotic and chronic salt-loading SL) conditions by the first time using “new-generation”, RNA sequencing (RNA-Seq) methods. We reliably detect 9,709 genes as present in the SON by RNA-Seq, and 552 of these genes were changed in expression as a result of chronic SL. These genes reflect diverse functions, and 42 of these are involved in either transcriptional or translational processes. In addition, we compare the SON transcriptomes resolved by RNA-Seq methods with the SON transcriptomes determined by Affymetrix microarray methods in rats under the same osmotic conditions, and find that there are 6,466 genes present in the SON that are represented in both data sets, although 1,040 of the expressed genes were found only in the microarray data, and 2,762 of the expressed genes are selectively found in the RNA-Seq data and not the microarray data. These data provide the research community a comprehensive view of the transcriptome in the SON under normosmotic conditions and the changes in specific gene expression evoked by salt loading. PMID:25897513

Identification of Common Differentially Expressed Genes in Urinary Bladder Cancer

PubMed Central

Zaravinos, Apostolos; Lambrou, George I.; Boulalas, Ioannis; Delakas, Dimitris; Spandidos, Demetrios A.

2011-01-01

Background Current diagnosis and treatment of urinary bladder cancer (BC) has shown great progress with the utilization of microarrays. Purpose Our goal was to identify common differentially expressed (DE) genes among clinically relevant subclasses of BC using microarrays. Methodology/Principal Findings BC samples and controls, both experimental and publicly available datasets, were analyzed by whole genome microarrays. We grouped the samples according to their histology and defined the DE genes in each sample individually, as well as in each tumor group. A dual analysis strategy was followed. First, experimental samples were analyzed and conclusions were formulated; and second, experimental sets were combined with publicly available microarray datasets and were further analyzed in search of common DE genes. The experimental dataset identified 831 genes that were DE in all tumor samples, simultaneously. Moreover, 33 genes were up-regulated and 85 genes were down-regulated in all 10 BC samples compared to the 5 normal tissues, simultaneously. Hierarchical clustering partitioned tumor groups in accordance to their histology. K-means clustering of all genes and all samples, as well as clustering of tumor groups, presented 49 clusters. K-means clustering of common DE genes in all samples revealed 24 clusters. Genes manifested various differential patterns of expression, based on PCA. YY1 and NFκB were among the most common transcription factors that regulated the expression of the identified DE genes. Chromosome 1 contained 32 DE genes, followed by chromosomes 2 and 11, which contained 25 and 23 DE genes, respectively. Chromosome 21 had the least number of DE genes. GO analysis revealed the prevalence of transport and binding genes in the common down-regulated DE genes; the prevalence of RNA metabolism and processing genes in the up-regulated DE genes; as well as the prevalence of genes responsible for cell communication and signal transduction in the DE genes that were down-regulated in T1-Grade III tumors and up-regulated in T2/T3-Grade III tumors. Combination of samples from all microarray platforms revealed 17 common DE genes, (BMP4, CRYGD, DBH, GJB1, KRT83, MPZ, NHLH1, TACR3, ACTC1, MFAP4, SPARCL1, TAGLN, TPM2, CDC20, LHCGR, TM9SF1 and HCCS) 4 of which participate in numerous pathways. Conclusions/Significance The identification of the common DE genes among BC samples of different histology can provide further insight into the discovery of new putative markers. PMID:21483740

Mining subspace clusters from DNA microarray data using large itemset techniques.

PubMed

Chang, Ye-In; Chen, Jiun-Rung; Tsai, Yueh-Chi

2009-05-01

Mining subspace clusters from the DNA microarrays could help researchers identify those genes which commonly contribute to a disease, where a subspace cluster indicates a subset of genes whose expression levels are similar under a subset of conditions. Since in a DNA microarray, the number of genes is far larger than the number of conditions, those previous proposed algorithms which compute the maximum dimension sets (MDSs) for any two genes will take a long time to mine subspace clusters. In this article, we propose the Large Itemset-Based Clustering (LISC) algorithm for mining subspace clusters. Instead of constructing MDSs for any two genes, we construct only MDSs for any two conditions. Then, we transform the task of finding the maximal possible gene sets into the problem of mining large itemsets from the condition-pair MDSs. Since we are only interested in those subspace clusters with gene sets as large as possible, it is desirable to pay attention to those gene sets which have reasonable large support values in the condition-pair MDSs. From our simulation results, we show that the proposed algorithm needs shorter processing time than those previous proposed algorithms which need to construct gene-pair MDSs.

Variation of gene expression in Bacillus subtilis samples of fermentation replicates.

PubMed

Zhou, Ying; Yu, Wen-Bang; Ye, Bang-Ce

2011-06-01

The application of comprehensive gene expression profiling technologies to compare wild and mutated microorganism samples or to assess molecular differences between various treatments has been widely used. However, little is known about the normal variation of gene expression in microorganisms. In this study, an Agilent customized microarray representing 4,106 genes was used to quantify transcript levels of five-repeated flasks to assess normal variation in Bacillus subtilis gene expression. CV analysis and analysis of variance were employed to investigate the normal variance of genes and the components of variance, respectively. The results showed that above 80% of the total variation was caused by biological variance. For the 12 replicates, 451 of 4,106 genes exhibited variance with CV values over 10%. The functional category enrichment analysis demonstrated that these variable genes were mainly involved in cell type differentiation, cell type localization, cell cycle and DNA processing, and spore or cyst coat. Using power analysis, the minimal biological replicate number for a B. subtilis microarray experiment was determined to be six. The results contribute to the definition of the baseline level of variability in B. subtilis gene expression and emphasize the importance of replicate microarray experiments.

Recursive feature selection with significant variables of support vectors.

PubMed

Tsai, Chen-An; Huang, Chien-Hsun; Chang, Ching-Wei; Chen, Chun-Houh

2012-01-01

The development of DNA microarray makes researchers screen thousands of genes simultaneously and it also helps determine high- and low-expression level genes in normal and disease tissues. Selecting relevant genes for cancer classification is an important issue. Most of the gene selection methods use univariate ranking criteria and arbitrarily choose a threshold to choose genes. However, the parameter setting may not be compatible to the selected classification algorithms. In this paper, we propose a new gene selection method (SVM-t) based on the use of t-statistics embedded in support vector machine. We compared the performance to two similar SVM-based methods: SVM recursive feature elimination (SVMRFE) and recursive support vector machine (RSVM). The three methods were compared based on extensive simulation experiments and analyses of two published microarray datasets. In the simulation experiments, we found that the proposed method is more robust in selecting informative genes than SVMRFE and RSVM and capable to attain good classification performance when the variations of informative and noninformative genes are different. In the analysis of two microarray datasets, the proposed method yields better performance in identifying fewer genes with good prediction accuracy, compared to SVMRFE and RSVM.

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.

Deletion of the transcriptional coactivator PGC1α in skeletal muscles is associated with reduced expression of genes related to oxidative muscle function

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

Hatazawa, Yukino; Research Fellow of Japan Society for the Promotion of Science, Tokyo; Minami, Kimiko

The expression of the transcriptional coactivator PGC1α is increased in skeletal muscles during exercise. Previously, we showed that increased PGC1α leads to prolonged exercise performance (the duration for which running can be continued) and, at the same time, increases the expression of branched-chain amino acid (BCAA) metabolism-related enzymes and genes that are involved in supplying substrates for the TCA cycle. We recently created mice with PGC1α knockout specifically in the skeletal muscles (PGC1α KO mice), which show decreased mitochondrial content. In this study, global gene expression (microarray) analysis was performed in the skeletal muscles of PGC1α KO mice compared withmore » that of wild-type control mice. As a result, decreased expression of genes involved in the TCA cycle, oxidative phosphorylation, and BCAA metabolism were observed. Compared with previously obtained microarray data on PGC1α-overexpressing transgenic mice, each gene showed the completely opposite direction of expression change. Bioinformatic analysis of the promoter region of genes with decreased expression in PGC1α KO mice predicted the involvement of several transcription factors, including a nuclear receptor, ERR, in their regulation. As PGC1α KO microarray data in this study show opposing findings to the PGC1α transgenic data, a loss-of-function experiment, as well as a gain-of-function experiment, revealed PGC1α’s function in the oxidative energy metabolism of skeletal muscles. - Highlights: • Microarray analysis was performed in the skeletal muscle of PGC1α KO mice. • Expression of genes in the oxidative energy metabolism was decreased. • Bioinformatic analysis of promoter region of the genes predicted involvement of ERR. • PGC1α KO microarray data in this study show the mirror image of transgenic data.« less

An integrated method for cancer classification and rule extraction from microarray data

PubMed Central

Huang, Liang-Tsung

2009-01-01

Different microarray techniques recently have been successfully used to investigate useful information for cancer diagnosis at the gene expression level due to their ability to measure thousands of gene expression levels in a massively parallel way. One important issue is to improve classification performance of microarray data. However, it would be ideal that influential genes and even interpretable rules can be explored at the same time to offer biological insight. Introducing the concepts of system design in software engineering, this paper has presented an integrated and effective method (named X-AI) for accurate cancer classification and the acquisition of knowledge from DNA microarray data. This method included a feature selector to systematically extract the relative important genes so as to reduce the dimension and retain as much as possible of the class discriminatory information. Next, diagonal quadratic discriminant analysis (DQDA) was combined to classify tumors, and generalized rule induction (GRI) was integrated to establish association rules which can give an understanding of the relationships between cancer classes and related genes. Two non-redundant datasets of acute leukemia were used to validate the proposed X-AI, showing significantly high accuracy for discriminating different classes. On the other hand, I have presented the abilities of X-AI to extract relevant genes, as well as to develop interpretable rules. Further, a web server has been established for cancer classification and it is freely available at . PMID:19272192

Improved analytical methods for microarray-based genome-composition analysis

PubMed Central

Kim, Charles C; Joyce, Elizabeth A; Chan, Kaman; Falkow, Stanley

2002-01-01

Background Whereas genome sequencing has given us high-resolution pictures of many different species of bacteria, microarrays provide a means of obtaining information on genome composition for many strains of a given species. Genome-composition analysis using microarrays, or 'genomotyping', can be used to categorize genes into 'present' and 'divergent' categories based on the level of hybridization signal. This typically involves selecting a signal value that is used as a cutoff to discriminate present (high signal) and divergent (low signal) genes. Current methodology uses empirical determination of cutoffs for classification into these categories, but this methodology is subject to several problems that can result in the misclassification of many genes. Results We describe a method that depends on the shape of the signal-ratio distribution and does not require empirical determination of a cutoff. Moreover, the cutoff is determined on an array-to-array basis, accounting for variation in strain composition and hybridization quality. The algorithm also provides an estimate of the probability that any given gene is present, which provides a measure of confidence in the categorical assignments. Conclusions Many genes previously classified as present using static methods are in fact divergent on the basis of microarray signal; this is corrected by our algorithm. We have reassigned hundreds of genes from previous genomotyping studies of Helicobacter pylori and Campylobacter jejuni strains, and expect that the algorithm should be widely applicable to genomotyping data. PMID:12429064

Fluctuations and synchrony of RNA synthesis in nucleoli.

PubMed

Pliss, Artem; Kuzmin, Andrey N; Kachynski, Aliaksandr V; Baev, Alexander; Berezney, Ronald; Prasad, Paras N

2015-06-01

Ribosomal RNA (rRNA) sequences are synthesized at exceptionally high rates and, together with ribosomal proteins (r-proteins), are utilized as building blocks for the assembly of pre-ribosomal particles. Although it is widely acknowledged that tight regulation and coordination of rRNA and r-protein production are fundamentally important for the maintenance of cellular homeostasis, still little is known about the real-time kinetics of the ribosome component synthesis in individual cells. In this communication we introduce a label-free MicroRaman spectrometric approach for monitoring rRNA synthesis in live cultured cells. Remarkably high and rapid fluctuations of rRNA production rates were revealed by this technique. Strikingly, the changes in the rRNA output were synchronous for ribosomal genes located in separate nucleoli of the same cell. Our findings call for the development of new concepts to elucidate the coordination of ribosomal components production. In this regard, numerical modeling further demonstrated that the production of rRNA and r-proteins can be coordinated, regardless of the fluctuations in rRNA synthesis. Overall, our quantitative data reveal a spectacular interplay of inherently stochastic rates of RNA synthesis and the coordination of gene expression.

[Archaeal diversity in permafrost deposits of Bunger Hills Oasis and King George Island (Antarctica) according to the 16S rRNA gene sequencing].

PubMed

Karaevskaia, E S; Demchenko, L S; Demidov, N É; Rivkina, E M; Bulat, S A; Gilichinskiĭ, D A

2014-01-01

Archaeal communities of permafrost deposits of King George Island and Bunger Hills Oasis (Antarctica) differing in the content of biogenic methane were analyzed using clone libraries of two 16S rRNA gene regions. Phylotypes belonging to methanogenic archaea were identified in all horizons.

Phylogenetic Analysis of Bacteroidales 16S rRNA Genes Unveils Sequences Specific to Diverse Swine Fecal Sources

EPA Science Inventory

Two of the currently available methods to assess swine fecal pollution (Bac1 and PF163) target Bacteroidales 16S rRNA genes. However, these assays have been shown to exhibit poor host-specificity and low detection limits in environmental waters, in part due to the limited number...

16S rRNA Gene Sequence Analysis of Drinking Water Using RNA and DNA Extracts as Targets for Clone Library Development

EPA Science Inventory

The bacterial composition of chlorinated drinking water was analyzed using 16S rRNA gene clone libraries derived from DNA extracts of 12 samples and compared to clone libraries previously generated using RNA extracts from the same samples. Phylogenetic analysis of 761 DNA-based ...

16S rRNA Gene Sequence Analysis of Drinking Water Using RNA and DNA Extracts as Targets for Clone Library Development

EPA Science Inventory

We examined the bacterial composition of chlorinated drinking water using 16S rRNA gene clone libraries derived from RNA and DNA extracted from twelve water samples collected in three different months (June, August, and September of 2007). Phylogenetic analysis of 1234 and 1117 ...

16S rRNA Gene Sequence Analysis of Drinking Water Using RNA and DNA Extracts as Targets for Clone Library Development - Poster

EPA Science Inventory

We examined the bacterial composition of chlorinated drinking water using 16S rRNA gene clone libraries derived from RNA and DNA extracted from twelve water samples collected in three different months (June, August, and September of 2007). Phylogenetic analysis of 1234 and 1117 ...

rRNA gene restriction patterns as an epidemiological marker in nosocomial outbreaks of Staphylococcus aureus infections.

PubMed

Meugnier, H; Fernandez, M P; Bes, M; Brun, Y; Bornstein, N; Freney, J; Fleurette, J

1993-01-01

rRNA gene restriction patterns (ribotyping) were compared with phage typing, serotyping, enterotoxins and exfoliatin production in the analysis of 26 Staphylococcus aureus strains isolated from two different nosocomial outbreaks. Total DNA was cleaved by EcoRI restriction endonuclease. After agarose gel electrophoresis and Southern transfer, the hybridization of the membranes was done with radiolabelled 16S rRNA gene from Bacillus subtilis inserted into a plasmid vector. Six to 13 fragments were visualized. A core of common fragments was discerned for all strains tested. A full correlation between ribotyping and conventional markers was observed in only one of the outbreaks studied. In both outbreaks, ribotyping proved helpful in characterizing otherwise untypable strains.

16S rRNA partial gene sequencing for the differentiation and molecular subtyping of Listeria species.

PubMed

Hellberg, Rosalee S; Martin, Keely G; Keys, Ashley L; Haney, Christopher J; Shen, Yuelian; Smiley, R Derike

2013-12-01

Use of 16S rRNA partial gene sequencing within the regulatory workflow could greatly reduce the time and labor needed for confirmation and subtyping of Listeria monocytogenes. The goal of this study was to build a 16S rRNA partial gene reference library for Listeria spp. and investigate the potential for 16S rRNA molecular subtyping. A total of 86 isolates of Listeria representing L. innocua, L. seeligeri, L. welshimeri, and L. monocytogenes were obtained for use in building the custom library. Seven non-Listeria species and three additional strains of Listeria were obtained for use in exclusivity and food spiking tests. Isolates were sequenced for the partial 16S rRNA gene using the MicroSeq ID 500 Bacterial Identification Kit (Applied Biosystems). High-quality sequences were obtained for 84 of the custom library isolates and 23 unique 16S sequence types were discovered for use in molecular subtyping. All of the exclusivity strains were negative for Listeria and the three Listeria strains used in food spiking were consistently recovered and correctly identified at the species level. The spiking results also allowed for differentiation beyond the species level, as 87% of replicates for one strain and 100% of replicates for the other two strains consistently matched the same 16S type. Copyright © 2013 Elsevier Ltd. All rights reserved.

A role for Dehalobacter spp. in the reductive dehalogenation of dichlorobenzenes and monochlorobenzene.

PubMed

Nelson, Jennifer L; Fung, Jennifer M; Cadillo-Quiroz, Hinsby; Cheng, Xu; Zinder, Stephen H

2011-08-15

Previously, we demonstrated the reductive dehalogenation of dichlorobenzene (DCB) isomers to monochlorobenzene (MCB), and MCB to benzene in sediment microcosms derived from a chlorobenzene-contaminated site. In this study, enrichment cultures were established for each DCB isomer and each produced MCB and trace amounts of benzene as end products. MCB dehalogenation activity could only be transferred in sediment microcosms. The 1,2-DCB-dehalogenating culture was studied the most intensively. Whereas Dehalococcoides spp. were not detected in any of the microcosms or cultures, Dehalobacter spp. were detected in 16S rRNA gene clone libraries from 1,2-DCB enrichment cultures, and by PCR using Dehalobacter-specific primers in 1,3-DCB and 1,4-DCB enrichments and MCB-dehalogenating microcosms. Quantitative PCR showed Dehalobacter 16S rRNA gene copies increased up to 3 orders of magnitude upon dehalogenation of DCBs or MCB, and that nearly all of bacterial 16S rRNA genes in a 1,2-DCB-dehalogenating culture belonged to Dehalobacter spp. Dehalobacter 16S rRNA genes from DCB enrichment cultures and MCB-dehalogenating microcosms showed considerable diversity, implying that 16S rRNA sequences do not predict dehalogenation-spectra of Dehalobacter spp. These studies support a role for Dehalobacter spp. in the reductive dehalogenation of DCBs and MCB, and this genus should be considered for its potential impact on chlorobenzene fate at contaminated sites.

The complete mitochondrial genome of Chrysopa pallens (Insecta, Neuroptera, Chrysopidae).

PubMed

He, Kun; Chen, Zhe; Yu, Dan-Na; Zhang, Jia-Yong

2012-10-01

The complete mitochondrial genome of Chrysopa pallens (Neuroptera, Chrysopidae) was sequenced. It consists of 13 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA (rRNA) genes, and a control region (AT-rich region). The total length of C. pallens mitogenome is 16,723 bp with 79.5% AT content, and the length of control region is 1905 bp with 89.1% AT content. The non-coding regions of C. pallens include control region between 12S rRNA and trnI genes, and a 75-bp space region between trnI and trnQ genes.

A general framework for optimization of probes for gene expression microarray and its application to the fungus Podospora anserina.

PubMed

Bidard, Frédérique; Imbeaud, Sandrine; Reymond, Nancie; Lespinet, Olivier; Silar, Philippe; Clavé, Corinne; Delacroix, Hervé; Berteaux-Lecellier, Véronique; Debuchy, Robert

2010-06-18

The development of new microarray technologies makes custom long oligonucleotide arrays affordable for many experimental applications, notably gene expression analyses. Reliable results depend on probe design quality and selection. Probe design strategy should cope with the limited accuracy of de novo gene prediction programs, and annotation up-dating. We present a novel in silico procedure which addresses these issues and includes experimental screening, as an empirical approach is the best strategy to identify optimal probes in the in silico outcome. We used four criteria for in silico probe selection: cross-hybridization, hairpin stability, probe location relative to coding sequence end and intron position. This latter criterion is critical when exon-intron gene structure predictions for intron-rich genes are inaccurate. For each coding sequence (CDS), we selected a sub-set of four probes. These probes were included in a test microarray, which was used to evaluate the hybridization behavior of each probe. The best probe for each CDS was selected according to three experimental criteria: signal-to-noise ratio, signal reproducibility, and representative signal intensities. This procedure was applied for the development of a gene expression Agilent platform for the filamentous fungus Podospora anserina and the selection of a single 60-mer probe for each of the 10,556 P. anserina CDS. A reliable gene expression microarray version based on the Agilent 44K platform was developed with four spot replicates of each probe to increase statistical significance of analysis.

Microarray analysis of differentially expressed genes engaged in fruit development between Prunus mume and Prunus armeniaca.

PubMed

Li, Xiaoying; Korir, Nicholas Kibet; Liu, Lili; Shangguan, Lingfei; Wang, Yuzhu; Han, Jian; Chen, Ming; Fang, Jinggui

2012-11-15

Microarray analysis is a technique that can be employed to provide expression profiles of single genes and new insights to elucidate the biological mechanisms responsible for fruit development. To evaluate expression of genes mostly engaged in fruit development between Prunus mume and Prunus armeniaca, we first identified differentially expressed transcripts along the entire fruit life cycle by using microarrays spotted with 10,641 ESTs collected from P. mume and other Prunus EST sequences. A total of 1418 ESTs were selected after quality control of microarray spots and analysis for differential gene expression patterns during fruit development of P. mume and P. Armeniaca. From these, 707 up-regulated and 711 down-regulated genes showing more than two-fold differences in expression level were annotated by GO based on biological processes, molecular functions and cellular components. These differentially expressed genes were found to be involved in several important pathways of carbohydrate, galactose, and starch and sucrose metabolism as well as in biosynthesis of other secondary metabolites via KEGG. This could provide detailed information on the fruit quality differences during development and ripening of these two species. With the results obtained, we provide a practical database for comprehensive understanding of molecular events during fruit development and also lay a theoretical foundation for the cloning of genes regulating in a series of important rate-limiting enzymes involved in vital metabolic pathways during fruit development. Copyright © 2012 Elsevier GmbH. All rights reserved.

BATS: a Bayesian user-friendly software for analyzing time series microarray experiments.

PubMed

Angelini, Claudia; Cutillo, Luisa; De Canditiis, Daniela; Mutarelli, Margherita; Pensky, Marianna

2008-10-06

Gene expression levels in a given cell can be influenced by different factors, namely pharmacological or medical treatments. The response to a given stimulus is usually different for different genes and may depend on time. One of the goals of modern molecular biology is the high-throughput identification of genes associated with a particular treatment or a biological process of interest. From methodological and computational point of view, analyzing high-dimensional time course microarray data requires very specific set of tools which are usually not included in standard software packages. Recently, the authors of this paper developed a fully Bayesian approach which allows one to identify differentially expressed genes in a 'one-sample' time-course microarray experiment, to rank them and to estimate their expression profiles. The method is based on explicit expressions for calculations and, hence, very computationally efficient. The software package BATS (Bayesian Analysis of Time Series) presented here implements the methodology described above. It allows an user to automatically identify and rank differentially expressed genes and to estimate their expression profiles when at least 5-6 time points are available. The package has a user-friendly interface. BATS successfully manages various technical difficulties which arise in time-course microarray experiments, such as a small number of observations, non-uniform sampling intervals and replicated or missing data. BATS is a free user-friendly software for the analysis of both simulated and real microarray time course experiments. The software, the user manual and a brief illustrative example are freely available online at the BATS website: http://www.na.iac.cnr.it/bats.

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.

Dancing together and separate again: gymnosperms exhibit frequent changes of fundamental 5S and 35S rRNA gene (rDNA) organisation

PubMed Central

Garcia, S; Kovařík, A

2013-01-01

In higher eukaryotes, the 5S rRNA genes occur in tandem units and are arranged either separately (S-type arrangement) or linked to other repeated genes, in most cases to rDNA locus encoding 18S–5.8S–26S genes (L-type arrangement). Here we used Southern blot hybridisation, PCR and sequencing approaches to analyse genomic organisation of rRNA genes in all large gymnosperm groups, including Coniferales, Ginkgoales, Gnetales and Cycadales. The data are provided for 27 species (21 genera). The 5S units linked to the 35S rDNA units occur in some but not all Gnetales, Coniferales and in Ginkgo (∼30% of the species analysed), while the remaining exhibit separate organisation. The linked 5S rRNA genes may occur as single-copy insertions or as short tandems embedded in the 26S–18S rDNA intergenic spacer (IGS). The 5S transcript may be encoded by the same (Ginkgo, Ephedra) or opposite (Podocarpus) DNA strand as the 18S–5.8S–26S genes. In addition, pseudogenised 5S copies were also found in some IGS types. Both L- and S-type units have been largely homogenised across the genomes. Phylogenetic relationships based on the comparison of 5S coding sequences suggest that the 5S genes independently inserted IGS at least three times in the course of gymnosperm evolution. Frequent transpositions and rearrangements of basic units indicate relatively relaxed selection pressures imposed on genomic organisation of 5S genes in plants. PMID:23512008

Dancing together and separate again: gymnosperms exhibit frequent changes of fundamental 5S and 35S rRNA gene (rDNA) organisation.

PubMed

Garcia, S; Kovařík, A

2013-07-01

In higher eukaryotes, the 5S rRNA genes occur in tandem units and are arranged either separately (S-type arrangement) or linked to other repeated genes, in most cases to rDNA locus encoding 18S-5.8S-26S genes (L-type arrangement). Here we used Southern blot hybridisation, PCR and sequencing approaches to analyse genomic organisation of rRNA genes in all large gymnosperm groups, including Coniferales, Ginkgoales, Gnetales and Cycadales. The data are provided for 27 species (21 genera). The 5S units linked to the 35S rDNA units occur in some but not all Gnetales, Coniferales and in Ginkgo (∼30% of the species analysed), while the remaining exhibit separate organisation. The linked 5S rRNA genes may occur as single-copy insertions or as short tandems embedded in the 26S-18S rDNA intergenic spacer (IGS). The 5S transcript may be encoded by the same (Ginkgo, Ephedra) or opposite (Podocarpus) DNA strand as the 18S-5.8S-26S genes. In addition, pseudogenised 5S copies were also found in some IGS types. Both L- and S-type units have been largely homogenised across the genomes. Phylogenetic relationships based on the comparison of 5S coding sequences suggest that the 5S genes independently inserted IGS at least three times in the course of gymnosperm evolution. Frequent transpositions and rearrangements of basic units indicate relatively relaxed selection pressures imposed on genomic organisation of 5S genes in plants.

PanFP: Pangenome-based functional profiles for microbial communities

DOE PAGES

Jun, Se -Ran; Hauser, Loren John; Schadt, Christopher Warren; ...

2015-09-26

For decades there has been increasing interest in understanding the relationships between microbial communities and ecosystem functions. Current DNA sequencing technologies allows for the exploration of microbial communities in two principle ways: targeted rRNA gene surveys and shotgun metagenomics. For large study designs, it is often still prohibitively expensive to sequence metagenomes at both the breadth and depth necessary to statistically capture the true functional diversity of a community. Although rRNA gene surveys provide no direct evidence of function, they do provide a reasonable estimation of microbial diversity, while being a very cost effective way to screen samples of interestmore » for later shotgun metagenomic analyses. However, there is a great deal of 16S rRNA gene survey data currently available from diverse environments, and thus a need for tools to infer functional composition of environmental samples based on 16S rRNA gene survey data. As a result, we present a computational method called pangenome based functional profiles (PanFP), which infers functional profiles of microbial communities from 16S rRNA gene survey data for Bacteria and Archaea. PanFP is based on pangenome reconstruction of a 16S rRNA gene operational taxonomic unit (OTU) from known genes and genomes pooled from the OTU s taxonomic lineage. From this lineage, we derive an OTU functional profile by weighting a pangenome s functional profile with the OTUs abundance observed in a given sample. We validated our method by comparing PanFP to the functional profiles obtained from the direct shotgun metagenomic measurement of 65 diverse communities via Spearman correlation coefficients. These correlations improved with increasing sequencing depth, within the range of 0.8 0.9 for the most deeply sequenced Human Microbiome Project mock community samples. PanFP is very similar in performance to another recently released tool, PICRUSt, for almost all of survey data analysed here. But, our method is unique in that any OTU building method can be used, as opposed to being limited to closed reference OTU picking strategies against specific reference sequence databases. In conclusion, we developed an automated computational method, which derives an inferred functional profile based on the 16S rRNA gene surveys of microbial communities. The inferred functional profile provides a cost effective way to study complex ecosystems through predicted comparative functional metagenomes and metadata analysis. All PanFP source code and additional documentation are freely available online at GitHub.« less

PanFP: pangenome-based functional profiles for microbial communities.

PubMed

Jun, Se-Ran; Robeson, Michael S; Hauser, Loren J; Schadt, Christopher W; Gorin, Andrey A

2015-09-26

For decades there has been increasing interest in understanding the relationships between microbial communities and ecosystem functions. Current DNA sequencing technologies allows for the exploration of microbial communities in two principle ways: targeted rRNA gene surveys and shotgun metagenomics. For large study designs, it is often still prohibitively expensive to sequence metagenomes at both the breadth and depth necessary to statistically capture the true functional diversity of a community. Although rRNA gene surveys provide no direct evidence of function, they do provide a reasonable estimation of microbial diversity, while being a very cost-effective way to screen samples of interest for later shotgun metagenomic analyses. However, there is a great deal of 16S rRNA gene survey data currently available from diverse environments, and thus a need for tools to infer functional composition of environmental samples based on 16S rRNA gene survey data. We present a computational method called pangenome-based functional profiles (PanFP), which infers functional profiles of microbial communities from 16S rRNA gene survey data for Bacteria and Archaea. PanFP is based on pangenome reconstruction of a 16S rRNA gene operational taxonomic unit (OTU) from known genes and genomes pooled from the OTU's taxonomic lineage. From this lineage, we derive an OTU functional profile by weighting a pangenome's functional profile with the OTUs abundance observed in a given sample. We validated our method by comparing PanFP to the functional profiles obtained from the direct shotgun metagenomic measurement of 65 diverse communities via Spearman correlation coefficients. These correlations improved with increasing sequencing depth, within the range of 0.8-0.9 for the most deeply sequenced Human Microbiome Project mock community samples. PanFP is very similar in performance to another recently released tool, PICRUSt, for almost all of survey data analysed here. But, our method is unique in that any OTU building method can be used, as opposed to being limited to closed-reference OTU picking strategies against specific reference sequence databases. We developed an automated computational method, which derives an inferred functional profile based on the 16S rRNA gene surveys of microbial communities. The inferred functional profile provides a cost effective way to study complex ecosystems through predicted comparative functional metagenomes and metadata analysis. All PanFP source code and additional documentation are freely available online at GitHub ( https://github.com/srjun/PanFP ).

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

Jun, Se -Ran; Hauser, Loren John; Schadt, Christopher Warren

For decades there has been increasing interest in understanding the relationships between microbial communities and ecosystem functions. Current DNA sequencing technologies allows for the exploration of microbial communities in two principle ways: targeted rRNA gene surveys and shotgun metagenomics. For large study designs, it is often still prohibitively expensive to sequence metagenomes at both the breadth and depth necessary to statistically capture the true functional diversity of a community. Although rRNA gene surveys provide no direct evidence of function, they do provide a reasonable estimation of microbial diversity, while being a very cost effective way to screen samples of interestmore » for later shotgun metagenomic analyses. However, there is a great deal of 16S rRNA gene survey data currently available from diverse environments, and thus a need for tools to infer functional composition of environmental samples based on 16S rRNA gene survey data. As a result, we present a computational method called pangenome based functional profiles (PanFP), which infers functional profiles of microbial communities from 16S rRNA gene survey data for Bacteria and Archaea. PanFP is based on pangenome reconstruction of a 16S rRNA gene operational taxonomic unit (OTU) from known genes and genomes pooled from the OTU s taxonomic lineage. From this lineage, we derive an OTU functional profile by weighting a pangenome s functional profile with the OTUs abundance observed in a given sample. We validated our method by comparing PanFP to the functional profiles obtained from the direct shotgun metagenomic measurement of 65 diverse communities via Spearman correlation coefficients. These correlations improved with increasing sequencing depth, within the range of 0.8 0.9 for the most deeply sequenced Human Microbiome Project mock community samples. PanFP is very similar in performance to another recently released tool, PICRUSt, for almost all of survey data analysed here. But, our method is unique in that any OTU building method can be used, as opposed to being limited to closed reference OTU picking strategies against specific reference sequence databases. In conclusion, we developed an automated computational method, which derives an inferred functional profile based on the 16S rRNA gene surveys of microbial communities. The inferred functional profile provides a cost effective way to study complex ecosystems through predicted comparative functional metagenomes and metadata analysis. All PanFP source code and additional documentation are freely available online at GitHub.« less

Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni

PubMed Central

Lockyer, Anne E; Spinks, Jenny; Kane, Richard A; Hoffmann, Karl F; Fitzpatrick, Jennifer M; Rollinson, David; Noble, Leslie R; Jones, Catherine S

2008-01-01

Background Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. Results We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs) libraries, suppression subtractive hybridization (SSH) libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO) terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7 and copine 1, cytoplasmic intermediate filament (IF) protein and transcription enzymes such as elongation factor 1α and EF-2. Conclusion Production of the first cDNA microarray for profiling gene expression in B. glabrata provides a foundation for expanding our understanding of pathways and genes involved in the snail internal defence system (IDS). We demonstrate resistant strain-specific expression of genes potentially associated with the snail IDS, ranging from signalling and inflammation responses through to lysis of proteinacous products (encapsulated sporocysts or phagocytosed parasite components) and processing/degradation of these targeted products by ubiquitination. PMID:19114004

Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni.

PubMed

Lockyer, Anne E; Spinks, Jenny; Kane, Richard A; Hoffmann, Karl F; Fitzpatrick, Jennifer M; Rollinson, David; Noble, Leslie R; Jones, Catherine S

2008-12-29

Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs) libraries, suppression subtractive hybridization (SSH) libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO) terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7 and copine 1, cytoplasmic intermediate filament (IF) protein and transcription enzymes such as elongation factor 1alpha and EF-2. Production of the first cDNA microarray for profiling gene expression in B. glabrata provides a foundation for expanding our understanding of pathways and genes involved in the snail internal defence system (IDS). We demonstrate resistant strain-specific expression of genes potentially associated with the snail IDS, ranging from signalling and inflammation responses through to lysis of proteinacous products (encapsulated sporocysts or phagocytosed parasite components) and processing/degradation of these targeted products by ubiquitination.

Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

PubMed Central

Thomas, E. V.; Phillippy, K. H.; Brahamsha, B.; Haaland, D. M.; Timlin, J. A.; Elbourne, L. D. H.; Palenik, B.; Paulsen, I. T.

2009-01-01

Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array) was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition. PMID:19404483

Gene Expression Omnibus (GEO): Microarray data storage, submission, retrieval, and analysis

PubMed Central

Barrett, Tanya

2006-01-01

The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely distributes high-throughput molecular abundance data, predominantly gene expression data generated by DNA microarray technology. The database has a flexible design that can handle diverse styles of both unprocessed and processed data in a MIAME- (Minimum Information About a Microarray Experiment) supportive infrastructure that promotes fully annotated submissions. GEO currently stores about a billion individual gene expression measurements, derived from over 100 organisms, submitted by over 1,500 laboratories, addressing a wide range of biological phenomena. To maximize the utility of these data, several user-friendly Web-based interfaces and applications have been implemented that enable effective exploration, query, and visualization of these data, at the level of individual genes or entire studies. This chapter describes how the data are stored, submission procedures, and mechanisms for data retrieval and query. GEO is publicly accessible at http://www.ncbi.nlm.nih.gov/projects/geo/. PMID:16939800

Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

DOE PAGES

Thomas, E. V.; Phillippy, K. H.; Brahamsha, B.; ...

2009-01-01

Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array) was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in partmore » to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.« less

Novel variants of the 5S rRNA genes in Eruca sativa.

PubMed

Singh, K; Bhatia, S; Lakshmikumaran, M

1994-02-01

The 5S ribosomal RNA (rRNA) genes of Eruca sativa were cloned and characterized. They are organized into clusters of tandemly repeated units. Each repeat unit consists of a 119-bp coding region followed by a noncoding spacer region that separates it from the coding region of the next repeat unit. Our study reports novel gene variants of the 5S rRNA genes in plants. Two families of the 5S rDNA, the 0.5-kb size family and the 1-kb size family, coexist in the E. sativa genome. The 0.5-kb size family consists of the 5S rRNA genes (S4) that have coding regions similar to those of other reported plant 5S rDNA sequences, whereas the 1-kb size family consists of the 5S rRNA gene variants (S1) that exist as 1-kb BamHI tandem repeats. S1 is made up of two variant units (V1 and V2) of 5S rDNA where the BamHI site between the two units is mutated. Sequence heterogeneity among S4, V1, and V2 units exists throughout the sequence and is not limited to the noncoding spacer region only. The coding regions of V1 and V2 show approximately 20% dissimilarity to the coding regions of S4 and other reported plant 5S rDNA sequences. Such a large variation in the coding regions of the 5S rDNA units within the same plant species has been observed for the first time. Restriction site variation is observed between the two size classes of 5S rDNA in E. sativa.(ABSTRACT TRUNCATED AT 250 WORDS)

Plastid 16S rRNA gene diversity among eukaryotic picophytoplankton sorted by flow cytometry from the South Pacific Ocean.

PubMed

Shi, Xiao Li; Lepère, Cécile; Scanlan, David J; Vaulot, Daniel

2011-04-28

The genetic diversity of photosynthetic picoeukaryotes was investigated in the South East Pacific Ocean. Genetic libraries of the plastid 16S rRNA gene were constructed on picoeukaryote populations sorted by flow cytometry, using two different primer sets, OXY107F/OXY1313R commonly used to amplify oxygenic organisms, and PLA491F/OXY1313R, biased towards plastids of marine algae. Surprisingly, the two sets revealed quite different photosynthetic picoeukaryote diversity patterns, which were moreover different from what we previously reported using the 18S rRNA nuclear gene as a marker. The first 16S primer set revealed many sequences related to Pelagophyceae and Dictyochophyceae, the second 16S primer set was heavily biased toward Prymnesiophyceae, while 18S sequences were dominated by Prasinophyceae, Chrysophyceae and Haptophyta. Primer mismatches with major algal lineages is probably one reason behind this discrepancy. However, other reasons, such as DNA accessibility or gene copy numbers, may be also critical. Based on plastid 16S rRNA gene sequences, the structure of photosynthetic picoeukaryotes varied along the BIOSOPE transect vertically and horizontally. In oligotrophic regions, Pelagophyceae, Chrysophyceae, and Prymnesiophyceae dominated. Pelagophyceae were prevalent at the DCM depth and Chrysophyceae at the surface. In mesotrophic regions Pelagophyceae were still important but Chlorophyta contribution increased. Phylogenetic analysis revealed a new clade of Prasinophyceae (clade 16S-IX), which seems to be restricted to hyper-oligotrophic stations. Our data suggest that a single gene marker, even as widely used as 18S rRNA, provides a biased view of eukaryotic communities and that the use of several markers is necessary to obtain a complete image.

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.

Leukemia-associated gene rearrangements in blood mononuclears of subjects in long terms after radiation exposure.

PubMed

Butenko, Z A; Smirnova, I A; Zak, K P; Kishinskaja, E G; Janok, E A

2000-03-01

The results of electron microscopy and molecular genetic study of blood mononuclears of 220 clean-up workers after 7-10 years since Chernobyl accident are presented. An increase of lymphocytes with altered ultrastructure of nuclei and membrane has been observed. Structural polymorphism of leukemia associated bcr and rRNA genes has been analyzed using Southern blot hybridization. Allelic polymorphism of bcr gene with allele distribution characteristic of myeloid leukemia and rearrangements of rRNA genes have been revealed in 11,5% of clean-up workers under study.

The 5S rDNA family evolves through concerted and birth-and-death evolution in fish genomes: an example from freshwater stingrays

PubMed Central

2011-01-01

Background Ribosomal 5S genes are well known for the critical role they play in ribosome folding and functionality. These genes are thought to evolve in a concerted fashion, with high rates of homogenization of gene copies. However, the majority of previous analyses regarding the evolutionary process of rDNA repeats were conducted in invertebrates and plants. Studies have also been conducted on vertebrates, but these analyses were usually restricted to the 18S, 5.8S and 28S rRNA genes. The recent identification of divergent 5S rRNA gene paralogs in the genomes of elasmobranches and teleost fishes indicate that the eukaryotic 5S rRNA gene family has a more complex genomic organization than previously thought. The availability of new sequence data from lower vertebrates such as teleosts and elasmobranches enables an enhanced evolutionary characterization of 5S rDNA among vertebrates. Results We identified two variant classes of 5S rDNA sequences in the genomes of Potamotrygonidae stingrays, similar to the genomes of other vertebrates. One class of 5S rRNA genes was shared only by elasmobranches. A broad comparative survey among 100 vertebrate species suggests that the 5S rRNA gene variants in fishes originated from rounds of genome duplication. These variants were then maintained or eliminated by birth-and-death mechanisms, under intense purifying selection. Clustered multiple copies of 5S rDNA variants could have arisen due to unequal crossing over mechanisms. Simultaneously, the distinct genome clusters were independently homogenized, resulting in the maintenance of clusters of highly similar repeats through concerted evolution. Conclusions We believe that 5S rDNA molecular evolution in fish genomes is driven by a mixed mechanism that integrates birth-and-death and concerted evolution. PMID:21627815

Genetic makeup of Shiga toxin-producing Escherichia coli in relation to clinical symptoms and duration of shedding: a microarray analysis of isolates from Swedish children.

PubMed

Matussek, A; Jernberg, C; Einemo, I-M; Monecke, S; Ehricht, R; Engelmann, I; Löfgren, S; Mernelius, S

2017-08-01

Shiga toxin (Stx)-producing Escherichia coli (STECs) cause non-bloody diarrhea, hemorrhagic colitis, and hemolytic uremic syndrome, and are the primary cause of acute renal failure in children worldwide. This study investigated the correlation of genetic makeup of STEC strains as revealed by DNA microarray to clinical symptoms and the duration of STEC shedding. All STEC isolated (n = 96) from patients <10 years of age in Jönköping County, Sweden from 2003 to 2015 were included. Isolates were characterized by DNA microarray, including almost 280 genes. Clinical data were collected through a questionnaire and by reviewing medical records. Of the 96 virulence genes (including stx) in the microarray, 62 genes were present in at least one isolate. Statistically significant differences in prevalence were observed for 21 genes when comparing patients with bloody diarrhea (BD) and with non-bloody stool (18 of 21 associated with BD). Most genes encode toxins (e.g., stx2 alleles, astA, toxB), adhesion factors (i.e. espB_O157, tir, eae), or secretion factors (e.g., espA, espF, espJ, etpD, nleA, nleB, nleC, tccP). Seven genes were associated with prolonged stx shedding; the presence of three genes (lpfA, senB, and stx1) and the absence of four genes (espB_O157, espF, astA, and intI1). We found STEC genes that might predict severe disease outcome already at diagnosis. This can be used to develop diagnostic tools for risk assessment of disease outcome. Furthermore, genes associated with the duration of stx shedding were detected, enabling a possible better prediction of length of STEC carriage after infection.

DNA microarrays of baculovirus genomes: differential expression of viral genes in two susceptible insect cell lines.

PubMed

Yamagishi, J; Isobe, R; Takebuchi, T; Bando, H

2003-03-01

We describe, for the first time, the generation of a viral DNA chip for simultaneous expression measurements of nearly all known open reading frames (ORFs) in the best-studied members of the family Baculoviridae, Autographa californica multiple nucleopolyhedrovirus (AcMNPV) and Bombyx mori nucleopolyhedrovirus (BmNPV). In this study, a viral DNA chip (Ac-BmNPV chip) was fabricated and used to characterize the viral gene expression profile for AcMNPV in different cell types. The viral chip is composed of microarrays of viral DNA prepared by robotic deposition of PCR-amplified viral DNA fragments on glass for ORFs in the NPV genome. Viral gene expression was monitored by hybridization to the DNA fragment microarrays with fluorescently labeled cDNAs prepared from infected Spodoptera frugiperda, Sf9 cells and Trichoplusia ni, TnHigh-Five cells, the latter a major producer of baculovirus and recombinant proteins. A comparison of expression profiles of known ORFs in AcMNPV elucidated six genes (ORF150, p10, pk2, and three late gene expression factor genes lef-3, p35 and lef- 6) the expression of each of which was regulated differently in the two cell lines. Most of these genes are known to be closely involved in the viral life cycle such as in DNA replication, late gene expression and the release of polyhedra from infected cells. These results imply that the differential expression of these viral genes accounts for the differences in viral replication between these two cell lines. Thus, these fabricated microarrays of NPV DNA which allow a rapid analysis of gene expression at the viral genome level should greatly speed the functional analysis of large genomes of NPV.

Gene expression profiling and pathway analysis in MCF-7 and MDA-MB-231 human breast cancer cell lines treated with dioscin

USDA-ARS?s Scientific Manuscript database

The long-term goal of our study is to understand the genetic and epigenetic mechanisms of breast cancer metastasis in human and to discover new possible genetic markers for use in clinical practice. We have used microarray technology (Human OneArray microarray, phylanxbiotech.com) to compare gene ex...

Evaluation of gene expression classification studies: factors associated with classification performance.

PubMed

Novianti, Putri W; Roes, Kit C B; Eijkemans, Marinus J C

2014-01-01

Classification methods used in microarray studies for gene expression are diverse in the way they deal with the underlying complexity of the data, as well as in the technique used to build the classification model. The MAQC II study on cancer classification problems has found that performance was affected by factors such as the classification algorithm, cross validation method, number of genes, and gene selection method. In this paper, we study the hypothesis that the disease under study significantly determines which method is optimal, and that additionally sample size, class imbalance, type of medical question (diagnostic, prognostic or treatment response), and microarray platform are potentially influential. A systematic literature review was used to extract the information from 48 published articles on non-cancer microarray classification studies. The impact of the various factors on the reported classification accuracy was analyzed through random-intercept logistic regression. The type of medical question and method of cross validation dominated the explained variation in accuracy among studies, followed by disease category and microarray platform. In total, 42% of the between study variation was explained by all the study specific and problem specific factors that we studied together.

NCBI GEO: archive for functional genomics data sets--10 years on.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Holko, Michelle; Ayanbule, Oluwabukunmi; Yefanov, Andrey; Soboleva, Alexandra

2011-01-01

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20,000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

Estimating differential expression from multiple indicators

PubMed Central

Ilmjärv, Sten; Hundahl, Christian Ansgar; Reimets, Riin; Niitsoo, Margus; Kolde, Raivo; Vilo, Jaak; Vasar, Eero; Luuk, Hendrik

2014-01-01

Regardless of the advent of high-throughput sequencing, microarrays remain central in current biomedical research. Conventional microarray analysis pipelines apply data reduction before the estimation of differential expression, which is likely to render the estimates susceptible to noise from signal summarization and reduce statistical power. We present a probe-level framework, which capitalizes on the high number of concurrent measurements to provide more robust differential expression estimates. The framework naturally extends to various experimental designs and target categories (e.g. transcripts, genes, genomic regions) as well as small sample sizes. Benchmarking in relation to popular microarray and RNA-sequencing data-analysis pipelines indicated high and stable performance on the Microarray Quality Control dataset and in a cell-culture model of hypoxia. Experimental-data-exhibiting long-range epigenetic silencing of gene expression was used to demonstrate the efficacy of detecting differential expression of genomic regions, a level of analysis not embraced by conventional workflows. Finally, we designed and conducted an experiment to identify hypothermia-responsive genes in terms of monotonic time-response. As a novel insight, hypothermia-dependent up-regulation of multiple genes of two major antioxidant pathways was identified and verified by quantitative real-time PCR. PMID:24586062

Mining microarray datasets in nutrition: expression of the GPR120 (n-3 fatty acid receptor/sensor) gene is down-regulated in human adipocytes by macrophage secretions.

PubMed

Trayhurn, Paul; Denyer, Gareth

2012-01-01

Microarray datasets are a rich source of information in nutritional investigation. Targeted mining of microarray data following initial, non-biased bioinformatic analysis can provide key insight into specific genes and metabolic processes of interest. Microarrays from human adipocytes were examined to explore the effects of macrophage secretions on the expression of the G-protein-coupled receptor (GPR) genes that encode fatty acid receptors/sensors. Exposure of the adipocytes to macrophage-conditioned medium for 4 or 24 h had no effect on GPR40 and GPR43 expression, but there was a marked stimulation of GPR84 expression (receptor for medium-chain fatty acids), the mRNA level increasing 13·5-fold at 24 h relative to unconditioned medium. Importantly, expression of GPR120, which encodes an n-3 PUFA receptor/sensor, was strongly inhibited by the conditioned medium (15-fold decrease in mRNA at 24 h). Macrophage secretions have major effects on the expression of fatty acid receptor/sensor genes in human adipocytes, which may lead to an augmentation of the inflammatory response in adipose tissue in obesity.

Mining microarray datasets in nutrition: expression of the GPR120 (n-3 fatty acid receptor/sensor) gene is down-regulated in human adipocytes by macrophage secretions

PubMed Central

Trayhurn, Paul; Denyer, Gareth

2012-01-01

Microarray datasets are a rich source of information in nutritional investigation. Targeted mining of microarray data following initial, non-biased bioinformatic analysis can provide key insight into specific genes and metabolic processes of interest. Microarrays from human adipocytes were examined to explore the effects of macrophage secretions on the expression of the G-protein-coupled receptor (GPR) genes that encode fatty acid receptors/sensors. Exposure of the adipocytes to macrophage-conditioned medium for 4 or 24 h had no effect on GPR40 and GPR43 expression, but there was a marked stimulation of GPR84 expression (receptor for medium-chain fatty acids), the mRNA level increasing 13·5-fold at 24 h relative to unconditioned medium. Importantly, expression of GPR120, which encodes an n-3 PUFA receptor/sensor, was strongly inhibited by the conditioned medium (15-fold decrease in mRNA at 24 h). Macrophage secretions have major effects on the expression of fatty acid receptor/sensor genes in human adipocytes, which may lead to an augmentation of the inflammatory response in adipose tissue in obesity. PMID:25191551

High density DNA microarrays: algorithms and biomedical applications.

PubMed

Liu, Wei-Min

2004-08-01

DNA microarrays are devices capable of detecting the identity and abundance of numerous DNA or RNA segments in samples. They are used for analyzing gene expressions, identifying genetic markers and detecting mutations on a genomic scale. The fundamental chemical mechanism of DNA microarrays is the hybridization between probes and targets due to the hydrogen bonds of nucleotide base pairing. Since the cross hybridization is inevitable, and probes or targets may form undesirable secondary or tertiary structures, the microarray data contain noise and depend on experimental conditions. It is crucial to apply proper statistical algorithms to obtain useful signals from noisy data. After we obtained the signals of a large amount of probes, we need to derive the biomedical information such as the existence of a transcript in a cell, the difference of expression levels of a gene in multiple samples, and the type of a genetic marker. Furthermore, after the expression levels of thousands of genes or the genotypes of thousands of single nucleotide polymorphisms are determined, it is usually important to find a small number of genes or markers that are related to a disease, individual reactions to drugs, or other phenotypes. All these applications need careful data analyses and reliable algorithms.

Development and validation of a microarray for the investigation of the CAZymes encoded by the human gut microbiome.

PubMed

El Kaoutari, Abdessamad; Armougom, Fabrice; Leroy, Quentin; Vialettes, Bernard; Million, Matthieu; Raoult, Didier; Henrissat, Bernard

2013-01-01

Distal gut bacteria play a pivotal role in the digestion of dietary polysaccharides by producing a large number of carbohydrate-active enzymes (CAZymes) that the host otherwise does not produce. We report here the design of a custom microarray that we used to spot non-redundant DNA probes for more than 6,500 genes encoding glycoside hydrolases and lyases selected from 174 reference genomes from distal gut bacteria. The custom microarray was tested and validated by the hybridization of bacterial DNA extracted from the stool samples of lean, obese and anorexic individuals. Our results suggest that a microarray-based study can detect genes from low-abundance bacteria better than metagenomic-based studies. A striking example was the finding that a gene encoding a GH6-family cellulase was present in all subjects examined, whereas metagenomic studies have consistently failed to detect this gene in both human and animal gut microbiomes. In addition, an examination of eight stool samples allowed the identification of a corresponding CAZome core containing 46 families of glycoside hydrolases and polysaccharide lyases, which suggests the functional stability of the gut microbiota despite large taxonomical variations between individuals.

Microarray Analysis of Gene Expression Alteration in Human Middle Ear Epithelial Cells Induced by Asian Sand Dust.

PubMed

Go, Yoon Young; Park, Moo Kyun; Kwon, Jee Young; Seo, Young Rok; Chae, Sung-Won; Song, Jae-Jun

2015-12-01

The primary aim of this study is to evaluate the gene expression profile of Asian sand dust (ASD)-treated human middle ear epithelial cell (HMEEC) using microarray analysis. The HMEEC was treated with ASD (400 µg/mL) and total RNA was extracted for microarray analysis. Molecular pathways among differentially expressed genes were further analyzed. For selected genes, the changes in gene expression were confirmed by real-time polymerase chain reaction. A total of 1,274 genes were differentially expressed by ASD. Among them, 1,138 genes were 2 folds up-regulated, whereas 136 genes were 2 folds down-regulated. Up-regulated genes were mainly involved in cellular processes, including apoptosis, cell differentiation, and cell proliferation. Down-regulated genes affected cellular processes, including apoptosis, cell cycle, cell differentiation, and cell proliferation. The 10 genes including ADM, CCL5, EDN1, EGR1, FOS, GHRL, JUN, SOCS3, TNF, and TNFSF10 were identified as main modulators in up-regulated genes. A total of 11 genes including CSF3, DKK1, FOSL1, FST, TERT, MMP13, PTHLH, SPRY2, TGFBR2, THBS1, and TIMP1 acted as main components of pathway associated with 2-fold down regulated genes. We identified the differentially expressed genes in ASD-treated HMEEC. Our work indicates that air pollutant like ASD, may play an important role in the pathogenesis of otitis media.

Oral microbiota species in acute apical endodontic abscesses.

PubMed

George, Noelle; Flamiatos, Erin; Kawasaki, Kellie; Kim, Namgu; Carriere, Charles; Phan, Brian; Joseph, Raphael; Strauss, Shay; Kohli, Richie; Choi, Dongseok; Baumgartner, J Craig; Sedgley, Christine; Maier, Tom; Machida, Curtis A

2016-01-01

Acute apical abscesses are serious endodontic diseases resulting from pulpal infection with opportunistic oral microorganisms. The objective of this study was to identify and compare the oral microbiota in patients (N=18) exhibiting acute apical abscesses, originating from the demographic region in Portland, Oregon. The study hypothesis is that abscesses obtained from this demographic region may contain unique microorganisms not identified in specimens from other regions. Endodontic abscesses were sampled from patients at the Oregon Health & Science University (OHSU) School of Dentistry. DNA from abscess specimens was subjected to polymerase chain reaction amplification using 16S rRNA gene-specific primers and Cy3-dCTP labeling. Labeled DNA was then applied to microbial microarrays (280 species) generated by the Human Oral Microbial Identification Microarray Laboratory (Forsyth Institute, Cambridge, MA). The most prevalent microorganisms, found across multiple abscess specimens, include Fusobacterium nucleatum, Parvimonas micra, Megasphaera species clone CS025, Prevotella multisaccharivorax, Atopobium rimae, and Porphyromonas endodontalis. The most abundant microorganisms, found in highest numbers within individual abscesses, include F. nucleatum, P. micra, Streptococcus Cluster III, Solobacterium moorei, Streptococcus constellatus, and Porphyromonas endodontalis. Strong bacterial associations were identified between Prevotella multisaccharivorax, Acidaminococcaceae species clone DM071, Megasphaera species clone CS025, Actinomyces species clone EP053, and Streptococcus cristatus (all with Spearman coefficients >0.9). Cultivable and uncultivable bacterial species have been identified in endodontic abscesses obtained from the Portland, Oregon demographic region, and taxa identifications correlated well with other published studies, with the exception of Treponema and Streptococcus cristae, which were not commonly identified in endodontic abscesses between the demographic region in Portland, Oregon and other regions.

Combinations of bacterial species associated with symptomatic endodontic infections in a Chinese population.

PubMed

Qi, Z; Cao, H; Jiang, H; Zhao, J; Tang, Z

2016-01-01

To use microarrays to detect 11 selected bacteria in infected root canals, revealing bacterial combinations that are associated with clinical symptoms and signs of primary endodontic infections in a Chinese population. DNA was extracted from 90 samples collected from the root canals of teeth with primary endodontic infections in a Chinese population, and the 16S rRNA gene was amplified by polymerase chain reaction (PCR). The PCR products were hybridized to microarrays containing specific oligonucleotide probes targeting 11 species, and the arrays were screened with a confocal laser scanner. Pearson's chi-squared test and cluster analysis were performed to investigate the associations between the bacterial combinations and clinical symptoms and signs using SAS 8.02. Seventy-seven samples (86%) yielded at least one of the 11 target species. Parvimonas micra (56%), Porphyromonas endodontalis (51%), Tannerella forsythia (48%), Prevotella intermedia (44%) and Porphyromonas gingivalis (37%) were the most prevalent taxa and were often concomitant. The following positive associations were found between the bacterial combinations and clinical features: P. endodontalis and T. forsythia with abscess; P. gingivalis and P. micra with sinus tract; P. gingivalis and P. endodontalis or P. micra and P. endodontalis with abscess and sinus tract; and the combination of P. endodontalis, P. micra, T. forsythia and P. gingivalis with sinus tract (P < 0.05). Various combinations of P. micra, P. endodontalis, T. forsythia and P. gingivalis may contribute to abscesses or sinus tracts of endodontic origin with bacterial synergism in a Chinese population. © 2015 International Endodontic Journal. Published by John Wiley & Sons Ltd.

Cross-species microarray hybridization to identify developmentally regulated genes in the filamentous fungus Sordaria macrospora.

PubMed

Nowrousian, Minou; Ringelberg, Carol; Dunlap, Jay C; Loros, Jennifer J; Kück, Ulrich

2005-04-01

The filamentous fungus Sordaria macrospora forms complex three-dimensional fruiting bodies that protect the developing ascospores and ensure their proper discharge. Several regulatory genes essential for fruiting body development were previously isolated by complementation of the sterile mutants pro1, pro11 and pro22. To establish the genetic relationships between these genes and to identify downstream targets, we have conducted cross-species microarray hybridizations using cDNA arrays derived from the closely related fungus Neurospora crassa and RNA probes prepared from wild-type S. macrospora and the three developmental mutants. Of the 1,420 genes which gave a signal with the probes from all the strains used, 172 (12%) were regulated differently in at least one of the three mutants compared to the wild type, and 17 (1.2%) were regulated differently in all three mutant strains. Microarray data were verified by Northern analysis or quantitative real time PCR. Among the genes that are up- or down-regulated in the mutant strains are genes encoding the pheromone precursors, enzymes involved in melanin biosynthesis and a lectin-like protein. Analysis of gene expression in double mutants revealed a complex network of interaction between the pro gene products.

Alteration of Gene Expression, DNA Methylation, and Histone Methylation in Free Radical Scavenging Networks in Adult Mouse Hippocampus following Fetal Alcohol Exposure.

PubMed

Chater-Diehl, Eric J; Laufer, Benjamin I; Castellani, Christina A; Alberry, Bonnie L; Singh, Shiva M

2016-01-01

The molecular basis of Fetal Alcohol Spectrum Disorders (FASD) is poorly understood; however, epigenetic and gene expression changes have been implicated. We have developed a mouse model of FASD characterized by learning and memory impairment and persistent gene expression changes. Epigenetic marks may maintain expression changes over a mouse's lifetime, an area few have explored. Here, mice were injected with saline or ethanol on postnatal days four and seven. At 70 days of age gene expression microarray, methylated DNA immunoprecipitation microarray, H3K4me3 and H3K27me3 chromatin immunoprecipitation microarray were performed. Following extensive pathway analysis of the affected genes, we identified the top affected gene expression pathway as "Free radical scavenging". We confirmed six of these changes by droplet digital PCR including the caspase Casp3 and Wnt transcription factor Tcf7l2. The top pathway for all methylation-affected genes was "Peroxisome biogenesis"; we confirmed differential DNA methylation in the Acca1 thiolase promoter. Altered methylation and gene expression in oxidative stress pathways in the adult hippocampus suggests a novel interface between epigenetic and oxidative stress mechanisms in FASD.

Development and experimental validation of a 20K Atlantic cod (Gadus morhua) oligonucleotide microarray based on a collection of over 150,000 ESTs.

PubMed

Booman, Marije; Borza, Tudor; Feng, Charles Y; Hori, Tiago S; Higgins, Brent; Culf, Adrian; Léger, Daniel; Chute, Ian C; Belkaid, Anissa; Rise, Marlies; Gamperl, A Kurt; Hubert, Sophie; Kimball, Jennifer; Ouellette, Rodney J; Johnson, Stewart C; Bowman, Sharen; Rise, Matthew L

2011-08-01

The collapse of Atlantic cod (Gadus morhua) wild populations strongly impacted the Atlantic cod fishery and led to the development of cod aquaculture. In order to improve aquaculture and broodstock quality, we need to gain knowledge of genes and pathways involved in Atlantic cod responses to pathogens and other stressors. The Atlantic Cod Genomics and Broodstock Development Project has generated over 150,000 expressed sequence tags from 42 cDNA libraries representing various tissues, developmental stages, and stimuli. We used this resource to develop an Atlantic cod oligonucleotide microarray containing 20,000 unique probes. Selection of sequences from the full range of cDNA libraries enables application of the microarray for a broad spectrum of Atlantic cod functional genomics studies. We included sequences that were highly abundant in suppression subtractive hybridization (SSH) libraries, which were enriched for transcripts responsive to pathogens or other stressors. These sequences represent genes that potentially play an important role in stress and/or immune responses, making the microarray particularly useful for studies of Atlantic cod gene expression responses to immune stimuli and other stressors. To demonstrate its value, we used the microarray to analyze the Atlantic cod spleen response to stimulation with formalin-killed, atypical Aeromonas salmonicida, resulting in a gene expression profile that indicates a strong innate immune response. These results were further validated by quantitative PCR analysis and comparison to results from previous analysis of an SSH library. This study shows that the Atlantic cod 20K oligonucleotide microarray is a valuable new tool for Atlantic cod functional genomics research.

Methanotrophic bacteria in oilsands tailings ponds of northern Alberta

PubMed Central

Saidi-Mehrabad, Alireza; He, Zhiguo; Tamas, Ivica; Sharp, Christine E; Brady, Allyson L; Rochman, Fauziah F; Bodrossy, Levente; Abell, Guy CJ; Penner, Tara; Dong, Xiaoli; Sensen, Christoph W; Dunfield, Peter F

2013-01-01

We investigated methanotrophic bacteria in slightly alkaline surface water (pH 7.4–8.7) of oilsands tailings ponds in Fort McMurray, Canada. These large lakes (up to 10 km2) contain water, silt, clay and residual hydrocarbons that are not recovered in oilsands mining. They are primarily anoxic and produce methane but have an aerobic surface layer. Aerobic methane oxidation was measured in the surface water at rates up to 152 nmol CH4 ml−1 water d−1. Microbial diversity was investigated via pyrotag sequencing of amplified 16S rRNA genes, as well as by analysis of methanotroph-specific pmoA genes using both pyrosequencing and microarray analysis. The predominantly detected methanotroph in surface waters at all sampling times was an uncultured species related to the gammaproteobacterial genus Methylocaldum, although a few other methanotrophs were also detected, including Methylomonas spp. Active species were identified via 13CH4 stable isotope probing (SIP) of DNA, combined with pyrotag sequencing and shotgun metagenomic sequencing of heavy 13C-DNA. The SIP-PCR results demonstrated that the Methylocaldum and Methylomonas spp. actively consumed methane in fresh tailings pond water. Metagenomic analysis of DNA from the heavy SIP fraction verified the PCR-based results and identified additional pmoA genes not detected via PCR. The metagenome indicated that the overall methylotrophic community possessed known pathways for formaldehyde oxidation, carbon fixation and detoxification of nitrogenous compounds but appeared to possess only particulate methane monooxygenase not soluble methane monooxygenase. PMID:23254511